Ultimate and proximate analysis of different coal and biomass [22].
\r\n\t
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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"314",title:"Regenerative Medicine and Tissue Engineering",subtitle:"Cells and Biomaterials",isOpenForSubmission:!1,hash:"bb67e80e480c86bb8315458012d65686",slug:"regenerative-medicine-and-tissue-engineering-cells-and-biomaterials",bookSignature:"Daniel Eberli",coverURL:"https://cdn.intechopen.com/books/images_new/314.jpg",editedByType:"Edited by",editors:[{id:"6495",title:"Dr.",name:"Daniel",surname:"Eberli",slug:"daniel-eberli",fullName:"Daniel Eberli"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"79193",title:"Progress on the Co-Pyrolysis of Coal and Biomass",doi:"10.5772/intechopen.101031",slug:"progress-on-the-co-pyrolysis-of-coal-and-biomass",body:'Energy supply is the fundamental basis for rapid economic growth and sustainable social development. Due to abundant reserves of coal worldwide, it has been become one of the most important fossil fuels of the past two centuries, and may continue to be used, somewhat, for up to an additional 200years in the future [1]. However, the use of coal can cause serious environmental problems. For example, sulfur dioxide and nitrogen oxides produced while burning coal can pollute the air and water, and are extremely harmful to humans, animals, and other organisms. In addition, coal burning is one of the main sources of greenhouse gas (GHG) emissions, accounting for at least 20–30% of total CO2 emissions [2].
Biomass energy, resulting from natural photosynthesis, represents a renewable form of energy, and is the fourth largest energy source after coal, oil, and nature gas [3]. It can supply about 14% of the world’s energy consumption, and about 38% of the energy consumption in developing countries [4, 5]. Because of its green, low-carbon, clean and renewable characteristics, it has become one of the most important sustainable energy sources [6, 7]. In order to actively respond to climate change, China has announced that it intends to reach its national CO2 emission peak before 2030, and thereafter achieve carbon neutrality before 2060 [8]. Under this background, biomass energy, as a zero-carbon energy source, will play an important role, and the biomass energy industry will usher in a period of major development opportunities. At present, China produces about 6.3 billion tons of various organic wastes (including: agricultural and forestry residues, domestic waste, domestic sludge, livestock and poultry manure, fruit and vegetable residues, and industrial organic waste liquids) every year; this organic waste is equivalent to about 800 million tons of standard coal. Of this total amount of organic waste, it is estimated that the amount of biomass resources that can be utilized as an energy source in China each year, is approximately equal to 460 million standard tons of coal [9]. Among these, the amount of agricultural waste is about 400 million tons, which is equivalent to about 200 million tons of standard coal. The amount of forestry waste is about 350 million tons, which is also equivalent to about 200 million tons of standard coal. The remaining organic wastes are equivalent to about 60 million tons of standard coal. The development of biomass energy can result in the utilization of eco-friendly, sustainable energy, and also reduce pollution due to the inappropriate discarding of organic wastes; it can also realize the utilization of an otherwise ignored energy resource. More importantly, the utilization of biomass energy cannot only assist in achieving carbon neutrality, but can also result in “negative” carbon emissions when biomass energy is utilized via carbon capture and storage (BECCS). However, biomass has its drawbacks, such as seasonal harvest rather than year-round availability, wide distribution, low energy density, and high transportation costs [10]. These shortcomings, especially the limited supply of biomass raw materials, currently restrict its large-scale industrial application in China. Unfortunately, China’s current utilization of organic waste energy is less than 5%. But if China can expand its use of available biomass, it can begin to reduce its use of coal.
The co-utilization of coal and biomass can not only reduce the pressure of coal supply and environmental problems, but also save the cost of building direct biomass utilization equipment. In terms of fuel characteristics, coal and biomass also have a great possibility to complement one another. In order to utilize them on a large, efficient scale, the co-utilization of coal and biomass may offer a potential benefit, as a promising technical method. As the initial stage of thermal chemical conversion, the co-pyrolysis process of coal and biomass is very important, since it determines the formation characteristics, structures, and properties of volatiles (gas products), tar (liquid products) and char (solid products). The main components of biomass pyrolysis are volatiles and tar; in comparison, the main component of coal pyrolysis is char, which can reach 40–60%. When biomass is combined with coal, the yield of char is affected by the ratio during the co-pyrolysis of biomass and coal. The reaction of the solid phase product (co-pyrolysis char) is the slowest step in the whole thermochemical conversion process, and its reaction rate determines the rate of the whole thermochemical reaction. On the one hand, during co-pyrolysis, the volatiles produced from the biomass and coal, can interact with the co-pyrolysis char, which leads to changes in the properties of the resulting char and volatiles. On the other hand, the changes in the properties of the char and volatiles, can also affect the interactions between volatiles and co-pyrolysis char. The two are interrelated and influence each other. Therefore, during co-pyrolysis, it is very important to study the interactions between the resulting volatiles and char.
Compared to coal, biomass contains more CaO, K2O, P2O5, MgO, Na2O and Mn, and less SiO2, Al2O3, Fe2O3, SO3 and TiO2. Among these, K+, Na+, Ca2+ and Mg2+ belong to alkali and alkaline earth metals (AAEMs) [11]. The content of the alkali and alkaline earth metal oxides in biomass ash exceeds 27%, while the content in coal ash is only 6–10%. The content of silicon and aluminum oxides in biomass ash is 22–57%, while the content in coal ash exceeds 80% [12, 13]. AAEMs play an important role in the process of coupling utilization of coal and biomass, and are good catalysts for combustion and gasification reactions, which can significantly affect the reactivity of the resulting co-pyrolysis char [14]. The presence of AAEMs can affect the dynamic pyrolysis process, and has a direct catalytic effect on the cracking of volatiles and their precursors. However, due to the diversity and superimposition of the reactions, the nature of the interactions between coal and biomass during co-pyrolysis has not been fully understood, especially the catalytic influence of AAEMs, including the influence mechanism of AAEMs on the volatiles generation, the influence of AAEMs on the interaction between volatiles and char, and the influence of AAEMs on the co-pyrolysis char reaction. Therefore, the chemical mechanism of AAEMs during co-pyrolysis is one of the key issues that needs to be investigated further, regarding the basic research of coal and biomass co-utilization.
In this chapter, a comprehensive overview of the co-pyrolysis of coal and biomass is presented. The focus of interest is mainly on the chemical mechanisms, during co-pyrolysis. The properties of coal and biomass, the synergistic mechanism, the release and migration of AAEMs, the interactions between volatiles and char, the volatiles production characteristics, the physicochemical structures and reactivity of co-pyrolysis char, are analyzed in this chapter. Moreover, the influence of AAEMs on the properties of the co-pyrolysis products, is also presented.
Coal is an extremely complex and heterogeneous mixture composed of organic macromolecules and inorganic minerals [11]. It was formed by ancient plants, buried in the ground and experienced complex chemical changes at high temperatures and pressures. The transformation process involved the loss of hydrogen and oxygen and the condensation of carbon. “Coal” can be divided into peat, lignite, bituminous, and anthracite coals, according to the stage of formation and degree of coalification. Although peat is fuel, it is not actually coal, but a “pre-coal”. The main components of the organic macromolecular networks of coal are carbon, hydrogen, oxygen, nitrogen, and sulfur. Calculated by weight, carbon is the main component, accounting for 60% - 95% of the total weight. The carbon content of most coals is below 90%, and the hydrogen content is generally around 5%, while the hydrogen content of coals containing 95% carbon drops to about 2% [15]. The nitrogen content of coals is generally between 1% - 2%. Sulfur is also a very important component of most coals, accounting for 1–4%. The oxygen content is inversely proportional to the carbon content, that is, the higher the carbon content in coal, the lower the oxygen content. The oxygen content in coal is important because coal with more oxygen is more likely to catch fire. Carbon in coal mainly exists in two forms, namely fixed carbon or volatile matter. The ratio of fixed carbon to volatile matter determines the rank of coal [16]. Inorganic minerals account for a small proportion in the overall composition of coal. However, AAEMs in the minerals have obvious catalytic effects on the thermochemical conversion reaction of coal [14, 17].
A wide range of biomass fuels are available in the environment, ranging from wood to materials derived from herbaceous plants and straw. Usually, biomass fuels are classified according to their source and properties. Biomass can be divided into primary residues, secondary residues, tertiary residues, and energy crops according to their sources [18]. Primary residues include biomass such as wood, straw, grain, and corn, which are usually obtained as by-products from forest products and food crops [19]. Secondary residues are derived from biomass materials used in industrial products and food production, such as sawmills, paper mills, food and beverage industries, apricot and other fruit seeds. Tertiary residues include waste materials and dismantled timber, from other previously used biomass materials [20]. Energy crops may include willow, poplar, switchgrass, and miscanthus grass. In addition, biomass can be divided into four types based on properties: woody biomass, herbaceous biomass, organic waste, and aquatic biomass (such as kelp) [21]. Among all these types of biomass, the four types of biomass with the largest reserves are straw, firewood, forestry residues, and agricultural residues; their proportions are shown in Figure 1.
The proportions of four types biomass with the largest reserves.
Biomass is mainly composed of cellulose, hemicellulose, and lignin. Generally, lignocellulosic biomass contains about 35–55% cellulose, 20–35% hemicellulose, and 10–30% lignin [15]. Cellulose is a linear polymer formed by the connection of glucose molecules through ether bonds, which is the most abundant carbohydrate in nature and the main component of plant plasm cells. It decomposes in the temperature range of 240–350°C. Hemicellulose is a mixture of different polysaccharides with a low degree of polymerization and no crystal structure, so it is easily hydrolyzed. The thermal degradation of hemicellulose occurs at temperatures between 130°C and 260°C, mainly above 180°C. Lignin is composed of hydroxyphenyl propane, guaiacyl propane and syringyl propane. These monomers are formed by disordered combination of C-C bonds and C-O bonds through dehydrogenation polymerization. Lignin decomposes over a wide temperature range of 280–500°C.
There are significant differences between biomass and coal in proximate analysis, ultimate analysis, calorific value, ash composition, physical structure, chemical structure, and reactivity. The key differences in the properties of biomass in comparison with coal (see Tables 1 and 2) are [6, 11, 24, 25, 26]: (1) more moisture and volatiles, less fixed carbon and ash content; (2) more O, H and Cl, less C, N and S; (3) lower calorific value; (4) higher alkali content (especially the herbaceous biomass); (5) lower bulk density, larger specific surface area, more abundant pore structure; (6) more oxygen-containing functional groups (hydroxyl, carboxyl, ether and ketone) with highly reactive groups (–COOH, –OCH3 and –OH), complexes, light hydrocarbons, carbohydrates, hydroxyl oxides, carbonates, chloride and phosphate, and lower aromatics, functionality, silicate and sulfide; (7) higher reactivity.
Fuel | Ultimate analysis (db.% w/w) | Proximate analysis (% w/w) | LHV (MJ/kg) | |||||||
---|---|---|---|---|---|---|---|---|---|---|
C | H | O | N | S | Ash | VM | FC | M | ||
Rice husk | 35.20 | 4.79 | 59.00 | 1.01 | — | 9.40 | 66.12 | 13.80 | 10.65 | 13.12 |
Bamboo dust | 43.45 | 5.49 | 50.74 | 0.33 | — | 2.68 | 70.83 | 15.62 | 10.87 | 14.85 |
Wood Sawdust | 42.30 | 5.17 | 51.73 | 0.80 | — | 1.40 | 69.29 | 17.84 | 11.37 | 12.86 |
Cedar wood | 51.10 | 5.90 | 42.50 | 0.12 | 0.02 | 0.30 | 80–82 | 18–20 | — | 19.26 |
Olive–oil residue | 50.70 | 5.89 | 36.97 | 1.36 | 0.30 | 4.60 | 76.00 | 19.40 | 9.50 | 21.20 |
Rice straw | 38.61 | 4.28 | 37.16 | 1.08 | 0.65 | 12.64 | 65.26 | 16.55 | 5.58 | 14.40 |
Pine sawdust | 50.54 | 7.08 | 41.11 | 0.15 | 0.57 | 0.55 | 82.29 | 17.16 | — | 20.54 |
Spruce wood pellet | 49.30 | 5.90 | 44.40 | 0.10 | — | 0.30 | 74.20 | 17.10 | 8.40 | 18.50 |
Marc of grape | 49.66 | 5.56 | 34.42 | 2.23 | 0.14 | 7.83 | 65,77 | 26.40 | — | 19.51 |
Coffee husk | 46.80 | 4.90 | 47.10 | 0.60 | 0.60 | 1.00 | 74.30 | 14.30 | 10.40 | 16.54 |
Coffee ground | 52.97 | 6.51 | 36.62 | 2.80 | 0.05 | 1.00 | 71.80 | 16.70 | 10.50 | 22.00 |
Larch wood | 44.18 | 6.38 | 49.32 | 0.12 | — | 0.12 | 76.86 | 14.86 | 8.16 | 19.45 |
Grapevine Pruning waste | 46.97 | 5.80 | 44.49 | 0.67 | 0.01 | 2.06 | 78.16 | 19.78 | — | 17.91 |
Jute stick | 49.79 | 6.02 | 41.37 | 0.19 | 0.05 | 0.62 | 76–78 | 21–23 | — | 19.66 |
Sugar–cane bagasse | 48.58 | 5.97 | 38.94 | 0.20 | 0.05 | 1.26 | 67–70 | 29–31 | — | 19.05 |
Corn cob | 40.22 | 4.11 | 42.56 | 0.39 | 0.04 | 2.97 | 71.21 | 16.11 | 9.71 | 16.65 |
Peach stone | 51.97 | 5.76 | 40.70 | 0.79 | 0.01 | 0.65 | 81.30 | 18.10 | 8.53 | 21.60 |
Wheat straw | 46.10 | 5.60 | 41.70 | 0.50 | 0.08 | 6.01 | 75.80 | 18.10 | — | 17.20 |
Cotton stem | 42.80 | 5.30 | 38.50 | 1.00 | 0.20 | 4.30 | 72.30 | 15.50 | 7.90 | 15.20 |
Straw | 36.55 | 4.91 | 40.70 | 0.55 | 0.14 | 8.61 | 64.98 | 17.91 | 8.50 | 14.60 |
Camphor wood | 43.43 | 4.84 | 38.53 | 0.32 | 0.10 | 0.49 | 72.47 | 14.75 | 12.29 | 17.48 |
Beech wood | 48.27 | 6.36 | 45.20 | 0.14 | — | 0.80 | 81.00 | 18.00 | — | 19.20 |
Switchgrass | 47.00 | 5.30 | 41.40 | 0.50 | 0.10 | 4.60 | 58.40 | 17.10 | 20.00 | 18.70 |
Petroleum coke | 92.30 | 3.40 | 0.70 | 0.95 | 1.17 | 1.40 | 6.00 | 92.10 | 0.50 | 36.20 |
Lignite coal | 44.66 | 3,66 | 13.90 | 1.0 | 0.21 | 18.42 | 35.17 | 28.27 | 18.4 | 18.05 |
Bituminous coal | 74.73 | 4.43 | 13.68 | 1.02 | 0.19 | 4.08 | 36.95 | 56.90 | 2.07 | 28.05 |
Lean coal | 66.05 | 3.25 | 2.53 | 1.17 | 0.19 | 25.30 | 20.65 | 53.15 | 0.92 | 24.14 |
Quinsam mine coal | 80.30 | 5.50 | 12.60 | 0.9 | 0.70 | 12.90 | 38.80 | 49.10 | 4.20 | 26.99 |
Sub-bituminous coal | 73.10 | 4.30 | 21.10 | 1.0 | 0.40 | 30.50 | 31.30 | 38.30 | 17.5 | 20.10 |
Indonesian coal | 72.13 | 6.67 | 19.58 | 1.40 | 0.22 | 8.39 | 36.84 | 42.36 | 12.42 | 20.79 |
Anthracite coal | 86.56 | 4.90 | 6.20 | 1.70 | 0.61 | 13.71 | 31.71 | 54.58 | 0.34 | 26.00 |
Shenmu coal | 70.35 | 4.56 | 10.53 | 1.04 | 0.55 | 9.19 | 28.51 | 58.52 | 3.78 | 27.08 |
Assam coal | 61.37 | 5.27 | 28.18 | 0.94 | 4.24 | 10.0 | 40.50 | 47.50 | 2.00 | 22.55 |
Fuel | Ash composition (wt. %) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
SiO2 | Al2O3 | CaO | Fe2O3 | K2O | MgO | Na2O | P2O5 | SO3 | TiO2 | |
Switchgrass (Manitoba, Canada) | 52.50 | 2.10 | 6.40 | 0.30 | 20.30 | 6.50 | 1.60 | 5.00 | 0.02 | 2.60 |
Rice straw (Hubei Province, China) | 51.99 | 0.91 | 7.68 | 0.84 | 17.61 | 2.33 | 0.96 | 2.49 | 0.04 | 6.50 |
Sawdust (Hubei Province, China) | 16.47 | 6.50 | 24.89 | 4.57 | 7.76 | 5.56 | 12.84 | 2.42 | 0.58 | 7.64 |
Pine biomass (Statoil, Norway) | 12.80 | 1.00 | 33.00 | 1.70 | 23.20 | 5.40 | 1.70 | 5.30 | — | — |
Corn stalks (Heilongjiang Province, China) | 29.03 | 0.83 | 14.34 | 1.26 | 29.41 | 18.38 | 0.60 | 3.00 | 1.60 | 0.02 |
Sub-bituminous coal (Genesee, Alberta, Canada) | 57.60 | 23.60 | 5.60 | 2.80 | 0.80 | 1.30 | 2.60 | 0.10 | 0.50 | 2.30 |
Lignite coal (Inner Mongolia, China) | 65.79 | 14.73 | 4.33 | 2.67 | 1.71 | 1.44 | 1.04 | 0.97 | 0.50 | 6.67 |
Bituminous coal (NSW, Australia) | 47.90 | 26.50 | 7.90 | 7.50 | 0.20 | 0.60 | 0.10 | 1.30 | 1.90 | 6.10 |
Lean coal (Inner Mongolia, China) | 53.99 | 28.44 | 4.07 | 3.22 | 1.56 | 0.88 | 2.97 | 0.97 | 1.82 | 4.00 |
Sub-bituminous coal (Shaanxi province, China) | 53.85 | 11.55 | 13.94 | 10.96 | 0.79 | 1.38 | 0.13 | 0.47 | 2.65 | 0.74 |
The differences in the characteristics of coal and biomass determines their different pyrolysis characteristics. During the pyrolysis process, volatiles and char can interact with each other, and AAEMs can also be released and migrated. Coal and biomass are mixed during pyrolysis, so the volatiles, char and released AAEMs from the pyrolysis of both are also mixed. As a result, there may be synergies between coal and biomass during co-pyrolysis. The synergies may be caused by several factors. First, the H/C ratio of biomass is higher than that of coal, so H2, OH and H radicals generated by biomass pyrolysis can migrate to the surface of coal during co-pyrolysis. Additional hydrogen donors may prevent the recombination and cross-linking reaction of free radicals, thus promoting coal decomposition to produce more volatiles [27]. Second, the content of AAEMs in biomass is higher than that in coal, especially the alkali metals [28]. AAEMs in biomass can migrate to the coal matrix during co-pyrolysis, and AAEMs can catalyze the pyrolysis and gas phase reaction of the coal [29]. Third, the heat transfer between coal and biomass may also cause synergistic effects during co-pyrolysis [30]. Figure 2 shows the factors leading to synergies during co-pyrolysis of coal and biomass.
Factors leading to synergies during co-pyrolysis of coal and biomass [
Typical pyrolysis temperatures for coal are between 350 °C and 650°C, while that of biomass are between 200°C and 400°C. During batch co-pyrolysis, the combination of the free radicals, especially stable and volatile radicals, lead to a reduction in both radical concentration and mass loss. In addition, the main temperature range of free radical interaction was 380°C ~ 600°C [32]. When the heating rate is slow enough, the pyrolysis of coal and biomass may occur independently from each other, and can be clearly distinguished. The synergistic effects could be limited, so it is easier to observe the additive effect. However, Wu et al. [33] observed that the thermogravimetric curve is not equal to the accumulation of the thermogravimetric curve of the parent fuels, which indicated that there may be synergistic effects during co-pyrolysis. Even in the slow pyrolysis process, the migration of AAEMs can also occur. If the biomass is in close contact with the coal, the migration process is more obvious, and the catalytic effects of AAEMs on volatiles are more prominent. During slow co-pyrolysis of coal and biomass, when the biomass is in the main pyrolysis stage, coal is in the initial pyrolysis stage, and the volatiles generated by the biomass pyrolysis can interact with coal char. When coal is in the main pyrolysis stage, and biomass is in its secondary degassing stage, the volatiles produced by coal pyrolysis can also interact with biomass char [34]. Therefore, during the slow pyrolysis process, even if the main pyrolysis stages of coal and biomass are independent of each other, there are still synergistic or inhibitory effects.
During co-pyrolysis, when the heating rate is fast enough, the pyrolysis processes of coal and biomass can occur simultaneously, and the release of volatiles also overlap. The interaction between volatiles and co-pyrolysis char generated from coal and biomass can occur more easily through the following processes. The volatiles produced by biomass pyrolysis are rich in OH free radicals, H free radicals, and a small amount of other free radicals, which can move to the surface of the coal char, and enter into the char matrix [35]. A large number of fragment structures produced by depolymerization and decomposition of the coal matrix are combined with the above-mentioned small free radicals derived from biomass volatiles, which can inhibit the secondary cracking reaction [34]. In addition, AAEMs contained in biomass volatiles can be moved to the coal char, and AAEMs can significantly promote secondary cracking of volatiles generated from coal pyrolysis [36]. The volatiles produced by coal pyrolysis pass through the surface of the biomass char during the release process, and are catalyzed by AAEMs attached to the surface of biomass char to generate small molecular gases and macromolecular structures. The small molecular gases directly escape, due to their small steric hindrance, but the macromolecular structures remain in the biomass char matrix, and merge with it to form solid products [34]. From literature references since 2010, on the rapid co-pyrolysis of coal and biomass, it can be found that 83% of the studies reported that there are synergistic effects [11]. Yang et al. [37] researched the synergistic effect of cotton stalk (CS) and high-ash coal (HAC) on gas production during co-pyrolysis/gasification, and summarized the main reasons for the synergistic effect.
Higher pyrolysis temperature and narrow space were conducive to the diffusion of biomass-derived AAEMs during co-conversion. At high temperatures, the intermediate products from pyrolysis/gasification may participate in the reforming reaction, and produce non-condensable gases (H2, CO, CO2 and CH4). As shown in Figure 3, changing the flow mode can prolong the contact time between volatiles and residual char (heterogeneous volatilization-char reaction), thereby increasing the yield of H2 and CO, and reducing the yield of CO2.
During the co-pyrolysis of coal and biomass, the biomass would be rapidly decomposed, and the biomass tar would be adsorbed onto the active sites of the residual char. As the proportion of cotton stalk in the mixture increases, the CO yield increased. This may be because AAEMs in the char promoted the decomposition of residual tar on the char (tar → H2, CO; R(1) and R(2), see Table 3) [38]. In addition, the CO2 generated inside the carbon matrix reacted with the char to expand the pores, while the light volatiles reacted with the char on the surface of the char, and consumed the carbon matrix (R(4)) [39]. Moreover, methane reforming (R(7)) and methane decomposition (R(8)) were performed simultaneously at high temperatures.
The catalysis of AAEMs in cotton stalk can be enhanced by the addition of H2O vapor to promote the reaction of active OH, H and − CH− free radicals with high-ash coal, thereby accelerating the C=C cleavage [28, 40]. During co-gasification, with the increase of cotton stalk ratio, the contents of H2 and CO2 increased, while the contents of CO and CH4 decreased. This was due to the promoted heterogeneous carbon-vapor reactions (R(3) and R(4)) [41], water-gas shift reaction (R(5)), and homogeneous hydrocarbon reforming reactions (R(6) and R(7)) by inherent AAEMs [42].
Synergistic mechanisms and reactions in the co-pyrolysis/gasification of CS and HCS [
Reactions | Number | |
---|---|---|
First step | CS/HCS → Gas (H2, CO, CO2, CH4, and others) + Tar (CnHm) + char | R(1) |
Second step | Tar (CnHm) → Gas (H2, CO, CO2, CH4, and others) | R(2) |
Char + H2O → H2 + CO; Char +2H2O → 2H2 + CO2 | R(3) | |
Char + CO2 → 2CO | R(4) | |
CO + H2O → H2 + CO2 | R(5) | |
CH4 + H2O → 3H2 + CO; CH4 + 2H2O → 4H2 + CO2 | R(6) | |
CH4 + CO2 → 2CO + 2H2 | R(7) | |
CH4 → C + 2H2 | R(8) |
Important reactions in the co-pyrolysis/gasification of CS and HCS [37].
AAEMs are easy to volatilize when participating in thermal conversion reactions of fuels [43]. In particular, alkali metals have been recognized for a long time to play a key role in the formation of deposits on the heat exchange surfaces of boilers in power stations [44, 45, 46]. In addition, the residual AAEMs in char could be effective catalysts for char reactions [43]. Therefore, understanding the release and migration behavior of AAEMs during gasification may assist in the development of AAEMs control technology, to effectively improve char reactivity.
AAEMs in coal and biomass can be divided into three forms: water-soluble state, ion-exchangeable state, and insoluble state. Water-soluble AAEMs and ion-exchangeable AAEMs are collectively called active AAEMs, while insoluble AAEMs are called inert AAEMs [31]. During the process of thermochemical conversion of fuel, active AAEMs can play a prominent catalytic role [14].
During the gasification process, the release of active AAEMs is not only due to evaporation to the gas phase, in the form of inorganic salts such as KCl and NaCl, but also due to release through substitution reactions. During high temperature pyrolysis, a large number of free radicals are generated, which can replace AAEMs bonded to the organic carboxyl group or other functional groups in the form of chemical bonds. It causes the chemical bonds between the char matrix and AAEMs to break, and AAEMs to be released. It is usually approximated by the following reaction [35]:
where CM stands for the char matrix, X stands for AAEMs, and R stands for free radical. The valence of the element is another factor affecting the release of AAEMs. Generally, the alkali metals (Na and K) bonded with the functional groups by single bonds are more likely to be released than the alkaline earth metals (Ca and Mg) bonded by double bonds [28, 47]. In addition, the higher the pyrolysis temperature and heating rate, the more AAEMs are released from the coal and biomass [48, 49, 50].
However, the migration of AAEMs during co-gasification of coal and biomass is very different from that of coal or biomass gasification alone, and coal could be a key factor for AAEMs migration. Wei et al. [51] pointed out that the co-pyrolysis process mainly promoted the transfer of active K in the co-pyrolysis char, which weakened with the increase of biomass content in the mixture, but the transfer of active Ca was affected by the type of fuel. Ellis et al. [52] pointed out that the catalytically active calcium in biomass minerals and aluminosilicate minerals in coal can react to produce catalytically inert chabazite crystals during co-pyrolysis. Meng et al. [53] found that the content of AAEM in co-pyrolysis char increased with the increase of biomass ratio in the mixture, which was consistent with the conclusions obtained by Weiland et al. [54, 55]. Zhang et al. [10] indicated that K in biomass could be transferred to the surface of coal char during co-pyrolysis and co-gasification. Chen et al. [56] reported that the presence of coal during co-pyrolysis was not conductive to the volatilization of K and Mg in biomass, but the mixing of coal and corn stalks was conducive to the volatilization of Ca. Guanghui Hu [57] found that during co-pyrolysis of coal and biomass, the amount of K/Na in the biomass released into the gas phase was reduced, and the higher the pyrolysis temperature, the higher the content of K/Na in the char. Tao Ding [58] also found that the volatile amount of K/Na during the co-gasification process of coal and biomass was far less than that during the separate gasification process. Changchun Hu [59] believed that when the co-pyrolysis temperature of coal and biomass exceeded 460°C, the migration of K and Na would occur. In addition, during the subsequent gasification process, the K and Na migrated from the biomass to the coal char could combine with the minerals in coal and be fixed in the ash. It can be concluded that the coupled utilization of coal and biomass can alleviate the high temperature corrosion caused by the release of alkali metals when biomass is used alone. Lin et al. [60] concluded that co-pyrolysis under moderate temperature strongly favored inhibiting potassium from releasing, probably by interfering with free radical reactions. Song et al. [61] researched the migration path of K in biomass during thermal co-processing of coal and biomass (see Figure 4), and found that the mixed raw materials released 84.1 wt% (coal char 65.0 wt%, biochar 19,1 wt%) of biomass-K into the co-pyrolysis char, while only 15.9 wt% of biomass-K was released into the gas phase. The biomass-K migrated from the biomass to the coal char, and biochar was in the water-soluble (6.6 and 11.2 wt %, respectively), acetic acid-soluble (0.9 and 1.4 wt%, respectively), H2SO4-soluble (8.5 and 1.5 wt%, respectively), and H2SO4-insoluble (49.0 and 5.0 wt%, respectively) forms. After gasification, biomass-K accounted for 28.7% wt% in gas phase and 55.4 wt% in ash. Masnadi et al. [62] proposed four possible ways to lose active K during co-gasification: (1) volatilization; (2) forming inert alkali silicate; (3) forming new inert minerals (such as KAlSiO4, KAlSi3O8) through irreversible reaction with minerals or ash in coal; (4) diffusion or implantation from the reaction surface into the carbon matrix.
Material flow of the biomass-K migration during thermal co-processing of coal and biomass. (pyrolysis: N2 atmosphere, 1173 K; gasification: 1173 K, flow rate of H2O/O2 = 70/30 mL/min, gasification time = 20 min) [
During the co-utilization of coal and biomass, in addition to the migration of K from the biomass, the remaining AAEMs in coal and biomass also migrate, but their chemical forms and their migration pathways are not clear. In addition, the migration of AAEMs in coal and biomass to the surface of char and their distribution in solid phase and gas phase are not well understood. These problems could affect the efficiency of the co-utilization of coal and biomass. Therefore, it is necessary to conduct additional research on the chemical form, migration path, redistribution mechanism and evolution of AAEMs during co-gasification of coal and biomass.
The volatile-char interactions are common phenomena in the thermochemical conversion of low order fuels, and their interaction mechanisms are complex. The essence of volatile-char interactions is the reaction between char and H radicals produced by the cracking and reforming of volatiles. The interactions include not only the catalytic reforming effect of volatiles by char, but also the influence of volatiles on the structure and properties of char [63]. The volatile-char interactions can significantly affect many aspects of the gasification process, such as the volatilization of AAEMs, the evolution of char structure, the dispersion of inherent catalysts and thus the reactivity of char [64]. Therefore, the volatile-char interactions should be fully considered in the utilization of low-order fuels, the beneficial aspects of the volatile-char interactions should be strengthened while the adverse aspects should be weakened or eliminated (see Figure 5).
The effect of volatile-char interactions on low rank gasification [
The volatile-char interactions during co-pyrolysis of coal and biomass are more complicated than that of each. Krerkkaiwan et al. [65, 66] found that coal char had catalytic effects on the decomposition of biomass volatiles and heavy aromatic hydrocarbons, and the interactions between biomass volatiles and coal char seriously reduced the gasification reactivity of coal char. Xia Wang [67] reported that lignin volatiles were more difficult than cellulose volatiles to undergo cracking and reforming reactions on the surface of coal char. When the gasification temperature was less than 800°C, biomass volatiles could form carbon deposits on the surface of coal char, which reduced the gasification reactivity of the coal char. Yan et al. [68] indicated that the interactions between biomass volatiles and coal char could reduce the yield of tar, increase the yield of gas volatiles, and change the chemical structure of the coal char. Hu et al. [69] found that the volatile-char interactions can promote the further cracking of tar into non-condensable gas, and can promote the aromatization of char, leading to the reduction of its gasification reaction. It can be found that the volatile-char interactions during co-pyrolysis of coal and biomass have important effects on the characteristics of both volatiles and co-pyrolysis char.
During thermochemical conversion of low-order fuel, the volatile-char interactions and AAEMs are interrelated and mutually influenced. On the one hand, the volatile-char interactions can promote the volatilization and migration of AAEMs. On the other hand, active AAEMs can affect the dynamic pyrolysis process of fuel, and have direct catalytic effects on the cracking of pyrolysis volatiles and their precursors, thus affecting the volatile-char interactions during thermochemical conversion. During co-thermochemical conversion of coal and biomass, the relationship between volatile-char interactions and AAEMs is more complex, and it is also a consideration for equipment design and operation. However, there are few reports on this aspect. Therefore, it is recommended that further research be conducted to understand the chemical mechanism of active AAEMs on volatile-char interactions and the influence of these interactions on the volatilization and migration of AAEMs for the efficient utilization of coal and biomass.
The pyrolysis products of coal and biomass include gas, tar, and char, which can be affected by synergistic effects. During co-pyrolysis of coal and biomass, the synergy can be affected by many factors such as: fuel type, blending ratio, heating rate, reactor design, and pyrolysis temperature. Table 4 showed the effects of temperature and blending ratio on yields of char, tar and gas compared with calculated values. It can be found that the synergy shown by the pyrolysis product yield is not uniform, and can be affected by fuel type, pyrolysis temperature and blending ratio. In addition, the maceral group from low-rank coal can also affect the co-pyrolysis products. Wu et al. [74] researched the main maceral group from low-rank coal and cellulose in lignocellulosic biomass, and found that during co-pyrolysis, the influence of vitrinite on the generation of volatiles was related to the mixing ratio, while inertinite inhibited the generation of volatiles.
Pyrolysis condition | Co-pyrolysis products | # | |||||
---|---|---|---|---|---|---|---|
Samples | Reactor | RC (w/w) | T (°C) | Gas | Tar | Char | |
YE/YC (%) | YE/YC (%) | YE/YC (%) | |||||
lignite, safflower seed | fixed-bed reactor | 3% | 550 | 24.1/24.7 | 36.7/33.4 | 22.0/23.3 | [70] |
5% | 23.5/24.4 | 39.6/32.9 | 21.6/24.0 | ||||
7% | 23.7/24.1 | 37.4/32.4 | 22.6/24.8 | ||||
10% | 23.6/23.6 | 35.6/31.7 | 24.4/26.0 | ||||
20% | 21.9/22.0 | 31.4/29.2 | 28.3/29.9 | ||||
30% | 19.8/20.3 | 25.4/26.6 | 34.5/33.8 | ||||
50% | 17.3/17.1 | 20.8/21.6 | 41.2/41.6 | ||||
65% | 14.4/19.5 | 16.8/25.4 | 46.9/35.7 | ||||
90% | 10.7/10.6 | 11.0/11.5 | 56.6/57.1 | ||||
sub-bituminous, sawdust | fixed-bed reactor | 40% | 400 | 21.2/15.2 | 41.0/45.5 | 37.8/39.2 | |
500 | 21.4/16.3 | 43.3/47.4 | 35.2/36.3 | [71] | |||
600 | 28.5/23.3 | 40.7/43.1 | 30.8/33.6 | ||||
700 | 32.8/28.0 | 36.7/39.8 | 30.6/32.2 | ||||
800 | 35.7/33.6 | 33.2/34.6 | 31.0/31.8 | ||||
20% | 600 | 27.4/26.3 | 50.1/50.1 | 22.1/23.6 | |||
40% | 28.5/23.3 | 40.7/43.1 | 30.8/33.6 | ||||
60% | 26.3/20.2 | 33.2/36.2 | 40.5/43.6 | ||||
80% | 19.3/14.2 | 28.0/29.3 | 52.7/53.5 | ||||
low-rank coal, cedar | fixed-bed reactor | 25% | 450 | 18.0/18.2 | 33.6/35.4 | 34.8/34.2 | [72] |
500 | 22.0/22.2 | 33.2/35.0 | 32.2/31.2 | ||||
550 | 26.3/26.8 | 31.3/32.0 | 31.0/29.6 | ||||
600 | 30.3/33.0 | 29.7/31.1 | 28.5/24.9 | ||||
650 | 33.2/35.6 | 29.0/29.9 | 26.9/23.5 | ||||
50% | 450 | 16.5/15.2 | 28.0/30.1 | 46.4/45.2 | |||
500 | 20.5/18.7 | 26.9/30.1 | 43.5/41.7 | ||||
550 | 25.1/23.0 | 25.8/27.2 | 40.1/39.6 | ||||
600 | 28.7/28.2 | 25.6/26.9 | 38.0/35.6 | ||||
650 | 31.5/30.6 | 25.2/26.0 | 36.8/34.1 | ||||
75% | 450 | 14.0/12.1 | 20.3/24.9 | 57.3/56.2 | |||
500 | 17.2/15.2 | 21.0/25.1 | 53.3/52.2 | ||||
550 | 21.0/19.1 | 19.0/22.5 | 50.2/49.5 | ||||
600 | 24.3/23.4 | 19.6/22.7 | 47.9/46.3 | ||||
650 | 26.4/25.5 | 20.1/22.2 | 46.3/44.6 | ||||
Lignite, Pine sawdust | fixed-bed reactor | 20% | 400 | 41.9/31.6 | 27.5/30.1 | 30.6/38.1 | [73] |
600 | 43.1/46.8 | 13.1/19.9 | 26.6/29.4 | ||||
900 | 51.7/49.7 | 25.7/27.4 | 22.6/22.9 | ||||
50% | 400 | 35.0/27.2 | 15.5/20.3 | 49.6/52.5 | |||
600 | 43.5/37.5 | 15.4/18.9 | 41.2/43.5 | ||||
900 | 52.8/44.0 | 13.1/19.9 | 34.1/36.1 | ||||
80% | 400 | 31.0/22.8 | 8.5/10.4 | 60.5/66.9 | |||
600 | 34.5/28.2 | 11.1/14.0 | 54.4/57.7 | ||||
900 | 41.8/38.3 | 8.5/12.4 | 49.7/49.3 |
Effects of temperature and blending ratio on yields of char, tar and gas compared with calculated values.
RC: mixing ratio of coal/mix (w/w); T: temperature; YE, YC: the experimental value and calculated value of yield, respectively.
Volatiles content is one of the important indicators of fuel characteristics, and it has important influences on furnace volume and shape, burner type and air distribution mode. At present, the research on volatiles during co-pyrolysis of coal and biomass mainly focuses on the influence of co-pyrolysis process on the composition and content of volatiles. Wu et al. [75, 76] found that when coal was co-pyrolyzed with wheat straw/biomass model compounds, co-pyrolysis promoted the generation of H2 and CO, and inhibited the production of CO2. However, the co-pyrolysis of coal and green algae inhibited the generation of H2 and CO. Zhang et al. [77] reported that during co-pyrolysis of coal and biomass, the contents of volatile components (H2, CO, CH4 and CO2) were inconsistent with the calculated values, suggesting that there were synergistic effects during co-pyrolysis. Sonobe et al. [30] indicated that the co-pyrolysis of coal and biomass had little effect on the production of CO and CO2, but significantly promoted the production of CH4. Soncini et al. [78] pointed out that the increase of biomass during the co-pyrolysis inhibited the production of CH4, C2H4, CO and H2. Yang et al. [37] researched the gas yield and the gas concentration of the co-pyrolysis of cotton stalk and high-ash coal at different mixing ratios under 950°C, and found that the co-pyrolysis was beneficial to the generation of gas, and can promote the formation of H2, CO and CH4 (except 20% cotton stalk), but inhibit the generation of CO2. Wu et al. [79] reported that during co-pyrolysis of coal and biomass, the addition of low-rank coal inhibited the formation of CH4 and H2, and the negative synergistic effect was most significant at a 50% mass ratio. Ma et al. [80] found that under the condition of cow manure: coal = 1: 3, CO emissions were significantly increased, CO2 and CH4 were also increased, and co-pyrolysis were beneficial to syngas production. In addition, for sulfur-containing gases, with the increase of cow manure ratio, the emissions of H2S, COS and C4H4S increase, while the emission of SO2 decrease. Zhu et al. [72] pointed out that the synergistic effect of gas yield and composition during co-pyrolysis of coal and biomass was affected by pyrolysis temperature and mix ratio. However, to our best knowledge, there are no reports about the influence of AAEMs on the volatiles production characteristics of the co-pyrolysis of coal and biomass.
The composition of tar is extremely complex, and can be used after separation and purification. The tar fractions are further processed to separate a variety of products. The main products extracted are: naphthalene, phenol, phenanthrene, carbazole, and asphalt. The different properties of biomass and coal lead to great differences in the components of their pyrolysis tar. Coal pyrolysis mainly produces heavy tar, while biomass pyrolysis mainly produces light tar. The interaction between coal and biomass during co-pyrolysis could cause changes in the properties of tar. Onay et al. [70] reported that the co-pyrolysis oil obtained with 5% lignite mixed with biomass contains more aliphatic and aromatic fractions, more relatively heavy hydrocarbons, less polar fractions than biomass pyrolysis oil. Jones et al. [81] found that co-pyrolysis of coal and biomass was conducive to the formation of phenols, but not conducive to the formation of aromatics. Tang et al. [82] indicated that co-pyrolysis improved the formation of phenols and naphthalene, while cotton stalk as an additive inhibited phenanthrene formation during co-pyrolysis of cotton stalk and Shenmu coal. Zhu et al. [72] concluded that the increase of cedar sawdust contributed to the positive synergistic effect of light tar, revealing the role of cedar as a hydrogen donor during co-pyrolysis. In addition, reactive H2 from water-gas shift reaction and hydrogen-rich free radicals such as ∙CH3, ∙OCH3 from cedar can inhibit the secondary polymerization to form methyl-contained phenols and naphthalenes instead of 3-ring phenanthrenes and 4-ring pyrenes. Song et al. [73] reported that co-pyrolysis was unfavorable to the formation of benzene, naphthalene, and hydrocarbons in tar, but favorable to the formation of phenols and guaiacol. Zhao et al. [83] found that the co-pyrolysis of cellulose and lignite was conducive to the generation of −OH components, and cellulose could promote the thermal conversion of lignite to a certain extent, resulting in more ketones or esters in the co-pyrolysis tar, which was conducive to improving the quality of liquid products. Zhu et al. [84] reported that the reactive H2 from water-gas shift reaction and hydrogen-rich radicals such as ∙CH3, ∙OCH3 from cedar can inhibit the secondary polymerization to form methylphenol and naphthalene instead of 3-ring phenanthrenes and 4-ring pyrenes during co-pyrolysis of a massive coal and cedar mixture.
The interaction between coal and biomass during co-pyrolysis can affect the characteristics of the resulting char, which influences the subsequent reactions. Figure 6 shows the relationship between characteristics difference of coal and biomass and their co-pyrolysis char properties. Therefore, it is useful to study the characteristics of the resulting char, to understand the conversion mechanism during the co-pyrolysis of coal and biomass. Generally, the characteristics of char are studied from four aspects: physical structure, chemical structure, AAEM migration and reactivity.
The relationship between characteristics difference of coal and biomass and their co-pyrolysis char characteristics.
The change of the surface morphology of the co-pyrolysis char is the most direct manifestation of the interaction between coal and biomass. Wu et al. [76] found that with the increase of co-pyrolysis temperature, the surface of co-pyrolysis char became rougher and the pores became more developed. Wu et al. [85] reported that cellulose can promote the uniformity of co-pyrolysis char, while hemicellulose, lignin and sodium carboxymethyl cellulose were conducive to the three-dimensional development of co-pyrolysis char. Chen et al. [31] pointed out that during co-pyrolysis of coal and biomass, the presence of corn stalks was beneficial to the production of spherical particles from coal char. But the promotion of the corn stalks in removing active AAEMs through acid pickling was greater than that of the original corn stalks. However, Lin et al. [60] concluded that co-pyrolysis hardly influenced the macro-morphology, and structure of the mineral matter. According to current research results, more than 80% of the researches believed that the surface morphology of co-pyrolysis char was changed during co-pyrolysis [11].
During the reaction process of co-pyrolysis char, the pore structure can provide reaction and diffusion channels for some products, and the pore surface is the main location of chemical reaction of adsorption. Therefore, the structure and surface of pores in the char, play an important role in the reaction of chars. Most studies indicate that the growth of pore structure of co-pyrolysis char is affected by the operating temperature, mixing ratio and fuel type. Wei et al. [86] reported that with the increase of the biomass ratio in the mixture, the development of pore structure was first inhibited and then promoted. Wu et al. [87] found that biomass had an inhibitory effect on the development of the surface area and pore volume of co-pyrolysis char, but the average pore size of co-pyrolysis char was affected by the type of raw materials used. Vyas et al. [88] pointed out that the growth of co-pyrolysis char pore structure was affected by operating temperature and mixing ratio. At low co-pyrolysis temperature, the mixing ratio had little effect on the surface area and micropores. However, with the increase of co-pyrolysis temperature, the presence of biomass in the mixture significantly increased the number of micropores in the co-pyrolysis char. Lin et al. [60] found that specific surface area and pore structures of large micropores and mesopores were more impacted than those of ultramicropores, indicating that the influence was mainly from the formation of secondary char.
The chemical structure of organic compounds in co-pyrolysis char is also one of the important factors affecting the reactivity of the char. However, there is little research on the chemical structure of co-pyrolysis char, especially the functional group structure. Only a few researchers have studied the carbon structure of co-pyrolysis char by Raman spectroscopy. It was found that the more biomass in the mixture, the more favorable the formation of smaller (3–5 rings) aromatic ring structures, and the reduction of larger (no less than 6 rings) aromatic ring structures in the co-pyrolysis char [86]. Wu et al. [85] found that the addition of cellulose inhibited the formation of smaller aromatic ring structures in co-pyrolysis char, while the addition of hemicellulose and lignin contributed to the formation of smaller aromatic ring structures. Chen et al. [56] researched the effects of pyrolysis temperature on the structure and functional groups changes of co-pyrolysis char by Raman and Fourier transform Infrared spectroscopy (FTIR), respectively. They found that with the increase of pyrolysis temperature, the structure of co-pyrolysis char changed from a small aromatic ring system to a large aromatic ring system containing six or more condensed benzene rings through the condensation reaction of the rings, and the aromatic −CH functional groups first increased and then decreased. In addition, the C=O and aliphatic −CH functional groups in the co-pyrolysis char disappeared in the pyrolysis temperature from 600 to 700°C. Chen et al. [31] pointed out that active AAEMs can inhibit the decomposition of aliphatic −CH, C=O and − CH3 in coal, and can also inhibit the decomposition of O − H, aliphatic −CH, and C − O in biomass. But as the pyrolysis temperature increased, the inhibitory effect gradually weakened or even dis appeared.
The co-gasification process of coal and biomass includes two primary steps: the co-pyrolysis of the raw fuel and the co-gasification of the remaining co-pyrolysis char. The gasification reaction rate of co-pyrolysis char is much slower than the release of volatiles during co-pyrolysis. Therefore, the reactivity of co-pyrolysis char becomes one of the important parameters, when evaluating the suitability of industrial gasification materials. It is still uncertain whether the co-pyrolysis process effects the reactivity of the co-pyrolysis char. Most studies found that no matter whether the gasification medium was CO2, steam, or air, the co-pyrolysis process could affect the reactivity of the coal/biomass char. Some researchers believe that co-pyrolysis can inhibit the reactivity of the resulting char [52, 86, 89, 90], while others believe that it can promote the reactivity of char [10, 87, 91, 92, 93, 94, 95]. In addition, some researchers have found that the influence of co-pyrolysis on char reactivity was affected by gasification temperature [51, 96], mixing ratio [54, 97, 98], raw materials [54, 99] and other co-pyrolysis parameters [23]. Wei et al. [51] researched the co-gasification reactivity of rice straw and bituminous coal/anthracite mixed char; they found that the synergistic effect of co-gasification reactivity of rice straw and bituminous coal mixed char, gradually changed from inhibition to promotion. The co-gasification reactivity of rice straw-anthracite mixed char, gradually strengthened with the increase of the conversion rate, reached the strongest point in the middle stage of co-gasification process, and then began to slowly weaken. Chen et al. [23] also pointed out that with the progress of the co-gasification process, the synergistic effect of the gasification reactivity of the char gradually changed from inhibition to promotion. In addition, the gasification reactivity of co-pyrolysis char was affected by mixing ratio and co-pyrolysis temperature, which was consistent with the research conclusion of Yuan et al. [97], Gao et al. [94], and Mafu et al. [98]. Overall, according to current research results, more than 80% of the researches believed that there were synergistic effects of co-pyrolysis char during co-gasification [11].
The synergistic effect of co-gasification reactivity of co-pyrolysis char is mainly caused by two aspects: the interaction between coal and biomass during co-pyrolysis and the interaction between coal char and biomass char during co-gasification. However, existing research on the influence of these two aspects on the gasification reactivity of co-pyrolysis char is obviously insufficient. Only Chen et al. [23] compared the effects of these two aspects on the co-gasification reactivity; they found that the interaction between coal and biomass during co-pyrolysis had a more obvious impact on the co-gasification reactivity.
The gasification reactivity of co-pyrolysis char is most likely controlled by mass transfer, pore diffusion and internal chemical reaction. Therefore, for co-pyrolysis char of coal and biomass, its physicochemical structure and catalysis are the most important factors affecting its reactivity. A large number of studies have shown that the co-pyrolysis process can have a synergistic effect on the gasification reactivity of the resulting char, which was mainly due to the catalysis of AAEMs (mainly K and Ca) during the pyrolysis and gasification process [10, 51, 52, 92, 93, 99]. However, the catalytically active Ca and K in the biomass can interact with the aluminosilicate in coal minerals to form catalytically inert Ca2Al2SiO7 and KAlSiO4 crystals, thereby reducing the reactivity of co-pyrolysis char [22, 52, 99]. In addition, the rich silica components in biomass ash can also reduce the reactivity of chars by converting the catalytically active K and Ca substances into non-catalytically active substances [10]. Krerkkaiwan et al. [91] found that the reactivity of co-pyrolysis char was higher than that of coal char or biomass char, alone, which was related to the increased surface area and pore volume of co-pyrolysis char, as well as the catalytic effect of the K released by the biomass. Wei et al. [86] and Wang et al. [89] reported that the chemical structure of co-pyrolysis char and the migration of catalytically active AAEMs were the main factors affecting the reactivity of co-pyrolysis char, while the physical structure was a secondary factor. Wu et al. [87, 90] pointed out that the increase of the distance between microcrystalline structures and the number of interlayer defects between adjacent aromatic layers can promote the formation of active sites, thus increasing the reactivity of the co-pyrolysis char. Zhang et al. [100] found that the active AAEMs in coal can increase the reactivity of char during co-gasification, promote the production of H2 and CO2, and inhibit the production of CO. Chen et al. [23] found that the active AAEMs in biomass can obviously promote the reactivity of co-pyrolysis char, while the active AAEMs in coal had little effect on the reactivity of the co-pyrolysis char.
Current research on the co-pyrolysis products of coal and biomass seems to be limited to the macroscopic characteristics, such as the yield, properties, and compositions. There are few studies and analyses on the essential causes that affect the co-pyrolysis products. Therefore, it is impossible to clearly understand the production mechanism of products during co-pyrolysis of coal and biomass. In addition, the effect of active AAEMs on the volatiles production during co-pyrolysis of coal and biomass is still unclear, thus further research is recommended. A better understanding of the influence of the physicochemical structure and the active AAEMs on the reactivity of co-pyrolysis char, will be helpful to promote the development of industrial applications for biomass-coal co-pyrolysis. Although some researchers have begun to pay attention to this work, there are still plenty of opportunities for further research and development.
Yao et al. [101] researched the industrial-scale co-pyrolysis of biomass, waste agriculture film, and bituminous coal, and analyzed it from multi-perspective (energy flow, economic, and socioenvironmental benefits analysis). The composition of different feedstock used in the pyrolysis experiment is shown in Table 5. The energy flow analysis showed that the co-pyrolysis processing of fruit tree branch (FTB), bituminous coal (BC), and recycled agriculture film pellets (AFP) resulted in a decrease in energy yield due to the energy loss that occurred during the conversion process. Table 6 shows the results of the economic analysis of the industrial-scale co-pyrolysis of FTB, BC, and AFP. From the economic analysis, it can be concluded that the three pyrolysis methods can bring economic benefits. Among them, the economic performance of FTB-BC-AFP co-pyrolysis was the highest, while that of FTB single pyrolysis was the lowest. The annual profit and the internal financial return rate of FTB-BC-AFP co-pyrolysis were three times and 2.1 times higher than that of single pyrolysis, respectively. In addition, the payback period can be shortened by about 3 years. The biochar produced by the three pyrolysis methods conformed to the national standard (GB/T 31862–2015 and GB/T 34170–2017). The pyrolysis gas meted the calorific value requirements of the national standard (GB/T 13612–2006), and can meet the needs of residents for heating and cooking. Moreover, the implementation of the project has created employment opportunities, and each person can increase their income by 30,000 CNY per year. In addition, The FTB-BC-AFP co-pyrolysis used in this project can replace ~1100 tons of standard coal every year, and reduce CO2 emission, SO2 emission, smoke and other pollutants by 1720 tons, 5 ~ 6 tons, and 320 kg per annum, respectively. At the same time, the project recycled 750 tons of plastic waste, which can reduce 50–66.7 km2 of farmland white pollution and avoid the accumulation of plastic waste.
Feedstock type | Biomass | Fossil fuel | Plastic waste |
---|---|---|---|
Feedstock name | Fruit tree branch | Bituminous coal | Recycled agriculture film pellets |
Feedstock code | FTB | BC | AFP |
Experiment code | Relative contents added in each experiment (wt%) | ||
E1 | 100 | 0 | 0 |
E2 | 50 | 50 | 0 |
E3 | 40 | 40 | 20 |
Total mass processed (kg)a | 450 | 800 | 1222 |
The composition of different feedstock used in the pyrolysis experiment [101].
The total mass of material processed in each experiment was to keep the rotation speed constant based on their densities, and the total volume was fixed.
Category | Term | Unit | E1 | E2 | E3 |
---|---|---|---|---|---|
Financial data | Total investment | 10,000 CNY | 213.79 | 223.37 | 223.37 |
Fixed asset investment | 204 | 204 | 204 | ||
Average income during operation period | 87.6 | 152.58 | 166 | ||
Total cost (average during operation period) | 72 | 129.5 | 129.5 | ||
Total profit (average during operation period) | 15.6 | 23.08 | 36.5 | ||
Financial evaluation indices | Financial internal rate of return (Before tax) | % | 10.51% | 14.20% | 21.26% |
Financial net present value (Before tax) | 10,000 CNY | 31.09 | 82.99 | 185.44 | |
Payback period (Before tax) | year | 8.47 | 7.19 | 5.51 | |
Sensitivity analysis | Product critical point | % | 4.73 | 7.05 | 14.66 |
Feedstock critical point | % | 10.14 | 11.07 | 25.66 | |
Initial investment critical point | % | 16.29 | 37.69 | 64.65 | |
BEP analysis | BEP (%, capacity utilization rate) | % | 62.63% | 53.11% | 41.73% |
Input data and results of the project economic analysis [101].
In response to China’s dual-carbon target, the use of coal should be reduced and eliminated, as burning 1 kg of coal produces 2.62 kg of CO2. As a solid fuel with zero carbon emission, the utilization rate of biomass should be increased. China produces more than 1 billion tons of agriculture and forestry waste each year. Due to its low energy density and high transportation cost, on-site treatment of biomass can effectively reduce the cost of recycling. Although co-pyrolysis may lead to energy loss in the conversion process, the addition of coal increases the bulk density of the raw material mixture and improves the processing capacity of the equipment. In addition, co-pyrolysis can improve the combustion characteristics of char and reduce the emission of pollutants. Co-pyrolysis process can not only effectively meet the needs of clean energy in rural areas, but also realize the on-site treatment and utilization of these major solid wastes. Therefore, the co-pyrolysis of biomass and coal is still a valuable method for engineering applications that require the use of coal. Furthermore, the addition of plastics in co-pyrolysis can improve the yield and quality of gas products, and also has certain environmental benefits.
In summary, there are still many deficiencies in the current research on the co-pyrolysis of coal and biomass, and many opportunities to expand the knowledge of the resulting chemistry, e.g., the influence of the interaction between coal and biomass on the respective pyrolysis process and the entire co-pyrolysis process during co-pyrolysis, the influence of co-pyrolysis conditions on the physicochemical structure and AAEMs content of co-pyrolysis char, especially the influence of co-pyrolysis process on subsequent gasification reaction characteristics. Important system parameters to be studied further, include: (a) the ratio, and limits, of biomass to coal; (b) pyrolysis and gasification operating temperatures; (c) the rate of temperature rise in the reaction vessel; (d) the inter-catalytic effects of AAEMs on product yields and compositions; (e) the yields of volatiles (gases), tars (liquids), and chars (solids); (f) the compositions of these products. The goal of all of this current and future biomass-coal co-pyrolysis work should be to reach industrial scale applications for this as soon as possible. With regard to the current global climate change crisis, it is urgent to continue to minimize the use of all fossil fuels, worldwide, especially coal, and to mitigate the emissions of CO2 into Earth’s atmosphere. With that goal in mind, the growing use of biomass, to replace the use of coal, is of paramount importance.
This chapter has reviewed some of the information regarding the co-pyrolysis of coal and biomass, with a focus on the synergistic mechanism and the resulting influence. The different characteristics of coal and biomass lead to great differences in their pyrolysis characteristics, resulting in a synergistic effect during co-pyrolysis. The synergistic effect can be caused by the migration of active H radicals from biomass to coal, the catalysis of active AAEMs, and heat transfer during co-pyrolysis [102]. During the co-pyrolysis of coal and biomass, changes in product yields and composition of volatiles, as well as the changes in the physicochemical structure and reactivity of co-pyrolysis char are briefly reviewed. In addition, the release and migration of AAEMs and their catalytic effects, and volatile-char interactions are mentioned. Moreover, the analysis of the co-pyrolysis industry demonstration is also mentioned.
The authors gratefully acknowledge the China Postdoctoral Science Foundation Funded Project (2021M690824).
Force constitutes one of the most important parameters in the resistance welding process. The remaining parameters include current and current flow time. During cross-wire projection welding (particularly of aluminium alloys) involving the use of a conventional application, i.e. the pneumatic force system (PFS), it is very difficult, nearly impossible, to make a weld containing the full weld nugget. Aluminium, when subjected to welding, gets plasticised very quickly, which is responsible for the formation of the excessively large area of contact between welded elements and, consequently, results in a rapid decrease in current density. These are not favourable conditions for the melting of materials. In addition, the PFS is characterised by high inertia and the impossibility of performing fast changes in force during current flow. For this reason, the value of preset force is usually constant and unfavourably too high. If the aforesaid force is excessively high, the high deformation of welded elements (bars) may occur as a result. The overly low force may lead to the formation of projection joint imperfections (such as expulsion caused by high temperature in contact areas) [1]. In the PFS, force applied during the welding process results from specific force preset by a pneumatic cylinder. The displacement of electrodes results from the action of this force and the changeable mechanical resistance of materials subjected to welding. A significant disadvantage of the above-presented method of control is the fact that neither force nor displacement (during the flow of current) is actually controlled.
An alternative solution requires another method making it possible to carry out faster changes in force during the welding of materials [1, 2, 3]. In publication [1], the authors emphasise the growing popularity of the electromechanical (servomechanical) force system (EFS) and an advantage consisting in an increase in an electrode displacement rate during welding. In publication [2] the authors inform about the possible extension of the window of technological parameters, improving the weldability of materials. In work [3, 4] the authors mention the possible modulation of force and its fast changes, particularly at the final stage of the welding process. The authors stress an increase in electrode service life in spot resistance welding and the application of servomotors in the riveting technology [5]. In publications [3, 6] authors state that the EFS has eliminated the dynamic impact of electrodes against a welded material (during the exertion of initial force), which was characteristic of pneumatic actuators. The EFS has enabled a gentle “touch” of an electrode against a material being welded. In work [3] the authors enumerate other advantages of the EFS including (i) superior (faster) operation of a welding gun (servo) in space, (ii) greater repeatability of force, (iii) reduced noise, (iv) shorter welding time and (v) shorter movement during the closing and opening of the electrodes, extending the service life of related mechanisms.
The tests discussed in the article aimed at replacing the PFS with the EFS. It was also important to appropriately control the servomotor in order to perform the controlled movement/shift of electrodes, particularly during the flow of current. The control process has changed considerably, i.e. the displacement of electrodes is a preset parameter and resultant force depends on the displacement of electrodes and the resistance of the deformation of a contact area being heated. Available reference publications do not contain information about such a method of electrode movement control as that presented in this study.
The authors [7, 8] describe a new control system and the results of its operation, particularly noticeable in projection welding. In [7, 9] the authors refer to a new control system applied when welding sheets with an embossed projection. Another use of the new solution, i.e. cross-wire welding, and the welding of nuts are presented in publications [10, 11, 12] respectively.
In publications [7, 8, 9, 10, 11, 12] the authors present a completely different solution, i.e. the slowing down of the displacement of an electrode during the projection welding of sheets with an embossed projection. This approach is new and characterised by advantages which are definitely worth mentioning. The above-named idea can be used in relation to aluminium alloys as these materials require a very short welding time (50 ms). It is possible to decrease the penetration of bars and to generate more energy in the optimum place, i.e. in the contact area between the bars. The new idea of electrode displacement control significantly alters the previous approach to the course of the resistance welding process (projection cross-wire welding) and considerably influences the development of the entire research area (pressure welding).
The essence of the EFS (in comparison with that of the PFS) involves a significantly higher rate of changes, i.e. changes in the force and/or displacement of electrodes. During the resistance welding process, the aforesaid approach is of significant importance because of the fact that the time of welding current flow in typical applications is very short and amounts to 0.2 s (200 ms). The optimisation (improvement) of the welding technology requires the modulation (change) of electrode force during the above-named time. Regrettably, as regards the conventional electrode force system (PFS), common in industrial applications, such modulation is impossible because of the significant inertia (delay) of this solution. Figure 1 presents exemplary courses of electrode force and displacement in relation to the PFS (dashed line) and EFS (full line). The aforesaid courses refer to two operating modes, i.e. the approach mode and the force mode. The time necessary to obtain previously adjusted electrode force, i.e. electrode force stabilisation time (EFST), by the PFS exceeds 200 ms. The EFST parameter related to the EFS is significantly shorter and restricted within the range of 50–80 ms, depending on the configuration of the EFS (servomotor power, gear etc.). An important characteristic of this solution is the possibility of modulating the course of electrode force during the flow of current, which is nearly impossible as regards the PFS.
Comparison of the EFS and PFS based on exemplary courses of electrode force and displacement in relation to operating modes: (a) approach mode and (b) force mode [
The EFS can be controlled in two different manners, i.e. using an algorithm enabling the control of force and an algorithm enabling the control of the (electrode) displacement rate. The first of the algorithms is already used in industrial practice. The time of delay in the stabilisation of preset electrode force is restricted within the range of 50–80 ms. In such an operating mode, it is possible to modulate force and obtain two or three different values (in CFT amounting to 200 ms). The aforesaid time (50–80 ms) depends on the configuration of the EFS (motor, gear) and on the preset value of force. In turn, the second algorithm (developed by the author) has been used to weld demanding (in the aforesaid respect) materials, i.e. aluminium alloys. Until today, the author has not come across any information concerning the method of control presented in this chapter.
The unique characteristic of the EFS and of the solution is a special algorithm, where the control of the displacement of electrodes results in the exertion of electrode force. In the above-named algorithm of control, delays between preset and actual values are counted in milliseconds, making it possible to develop a very fast algorithm enabling the exertion of variable (electrode) force [9]. The above-presented manner of controlling the force of electrodes through the control of their displacement alters previous views on methods enabling the control of force (movement of electrodes) in the resistance welding process.
The crosswise projection welding of aluminium bars (Al 5182) performed using the PFS was subjected to numerical analysis verified experimentally and aimed to subsequently optimise the welding process performed using the EFS system. The assumed acceptance criteria included (i) obtainment of the full weld nugget having a diameter of not less than 1.5 mm, (ii) lack of deformation and the penetration of the bars less than 20% of the diameters of elements subjected to welding (ΔlPP = 1.6 mm), (iii) lack of overheating in the area of contact between the electrode and the material being welded (Te-m max ≤ 500°C), (iv) lack of expulsion and (v) maximum current flow time tPP max = 63 ms. An additionally expected result was the reduction of (welding) current flow time.
The material of bars subjected to welding and adopted in FEM-based calculations was aluminium alloy grade 5182 with solidus (temperature) being 577°C and liquidus amounting to 638°C [14]. The chemical composition of the aluminium alloy grade Al 5182 used in the bars is presented in Table 1.
The numerical calculations were performed using the SORPAS® 3D software program [15]. The calculations were carried out for ¼ of the model and its mirror reflection in relation to the plane determined by x-z-axes and y-z-axes (Figure 2). The mesh in the area of contact between the elements (bars) subjected to welding was concentrated in order to provide the appropriate accuracy of calculations. The lack of proper mesh density resulted in the lack of contact between the elements subjected to welding and, consequently, incorrect calculations.
Model (3D) of the crosswise welding of aluminium bars (Al 5182).
The numerical model of the crosswise welding of bars is presented in Figure 2. The calculations were performed using the 3D model [15].
The numerical calculations included the analysis of (i) waveforms of dynamic resistance and momentary power, (ii) energy supplied to the weld, (iii) diameter and volume of the molten material of the weld nugget, (iv) displacement of electrodes (penetration of bars), (v) expulsion (if any) and (vi) temperature in the electrode bar contact area (Te-m, point 251—Figure 2a). The primary objective included the determination of the most favourable space distribution of welding power enabling the melting of the material in the central zone of the joint (to obtain the full weld nugget). As in all other cases of projection welding, the aspect of particular importance was the beginning of the welding process, i.e. the beginning of welding current flow.
The assumptions adopted in the numerical model included (i) copper electrodes (A2/2) and (ii) elements subjected to welding, i.e. aluminium (grade Al 5182) bars having a diameter of 4 mm and a length of 12 mm (Figure 2a). The 3D model was composed of approximately 9000 elements. To ensure the required accuracy of calculations, it was necessary to concentrate the mesh in the area of contact between the bars (Figure 2b).
Data related to the electrodes and materials subjected to welding and used in the FEM calculations were obtained from the SORPAS software program database (Table 2) [14]:
Aluminium bars Al 5182—material database designation SORPAS AA5182(O): Al95, Mn0.25, Mg4.5, solidus (577°C), liquidus (638°C) (Table 3)
Electrodes of class A2/2 CuCrZr (Table 4)
Al (max) | Mn (max) | Mg (max) |
---|---|---|
95.2 | 0.35 | 4.5 |
Chemical composition of the materials subjected to welding, i.e. bars made of aluminium alloy grade Al 5182.
Time step increment | Squeeze | Upslope | Weld | Hold | Unit |
---|---|---|---|---|---|
Pneumatic force system | 500 | 10–70 | 200 | 500 | ms |
Electromechanical force system | 200 | 10 | 250–300 | 500 | ms |
Time step | 0.1 | 0.1 | 0.1 | 1 | ms |
Convergence accuracy | |||||
Electrical model | 1.00E−5 | ||||
Thermal model | 1.00E−5 | ||||
Mechanical model | 1.00E−5 | ||||
Welding current | DC | ||||
Air temperature | 20 | °C | |||
Heat transfer rate | 300 | W/m2 K | |||
Length × width | 10.0 × 8.0 | mm | |||
Electrode height | 5 | mm | |||
Contact between welded elements | Sliding |
Parameters of the SORPAS software program used in numerical (FEM) calculations.
25 | 123.0 | 23 | 794 | 25 | 0.056 | 25 | 2660 | 25 | 23.9 | 25 | 70.0 |
100 | 134.0 | 50 | 825 | 100 | 0.068 | 250 | 25.0 | ||||
200 | 147.6 | 200 | 0.079 | ||||||||
400 | 160.9 | 400 | 0.103 | ||||||||
500 | 164.3 | 500 | 0.115 | ||||||||
600 | 163.3 | 600 | 0.131 |
Material parameters of welded materials (bars Al 95 Mn0.25, Mg4.5) [14].
20 | 326.6 | 20 | 372 | 20 | 0.022 | 20 | 8890 | 25 | 16.5 | 25 | 117.0 |
100 | 342.1 | 127 | 402 | 100 | 0.027 | 1080 | 8320 | ||||
300 | 338.0 | 327 | 422 | 200 | 0.038 | ||||||
500 | 340.3 | 527 | 438 | 300 | 0.042 | ||||||
700 | 332.0 | 727 | 456 | 400 | 0.049 | ||||||
900 | 321.8 | 927 | 485 | 500 | 0.057 | ||||||
600 | 0.065 | ||||||||||
700 | 0.073 | ||||||||||
800 | 0.082 | ||||||||||
900 | 0.091 | ||||||||||
1000 | 0.102 | ||||||||||
1100 | 0.220 |
Material parameters of electrodes ISO 5182 A2–2 electrode CuCrZr [14].
Based on the present recommendations and guidelines concerning the crosswise projection welding of bars, the following ranges of parameters were adopted for:
PFS [16, 17, 18]: (i) welding current I = 8.0–12.0 kA, (ii) welding current flow time tPP = 3 ms (upslope) + 60 ms (primary welding time) and (iii) electrode force F = 0.5–1.5 kN
EFS: (i) welding current I = 8.0 kA, (ii) welding current flow time tPP = 3 ms (upslope) + 35 ms and (iii) control of electrode displacement during the flow of welding current [11].
The numerical calculations were performed in relation to a DC inverter welding machine (1 kHz). The remaining welding cycle parameters are presented in Table 2. Table 5 presents the preset parameters of the welding cycle and the parameters characteristic of variants selected for FEM calculations.
No. | Variant | Current | Welding time | Force | PenetrationΔ l | Weld diameter | Weld volume | Energy | Remarks |
---|---|---|---|---|---|---|---|---|---|
kA | ms | kN | mm | mm3 | kJ | ||||
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
Pneumatic system (PFS) | |||||||||
1 | P1 | 8.0 | 63 | 1.5 | 1.47 | 0.1 | 0.0 | 0.17 | Overly small weld nugget diameter |
2 | P2 | 10.0 | 46 | 2.38 | 0.1 | 0.0 | 0.17 | Excessive penetration of bars | |
3 | P3 | 12.0 | 29 | 1.85 | 0.0 | 0.0 | 0.15 | ||
4 | P4 | 8.0 | 63 | 1.0 | 1.00 | 0.2 | 0.0 | 0.20 | Overly small weld nugget diameter |
5 | P5 | 10.0 | 59 | 2.13 | 1.5 | 0.9 | 0.23 | Most favourable welding conditions in spite of significant penetration of bars | |
6 | P6 | 12.0 | 46 | 2.54 | 0.2 | 0.0 | 0.30 | Overly small weld nugget diameter | |
7 | P7 | 8.0 | 63 | 0.5 | 0.57 | 0.3 | 0.1 | 0.25 | Overly small weld nugget diameter |
8 | P8 | 10.0 | 8 | 0.19 | 1.5 | 0.7 | 0.07 | Unfavourably short welding time, high dynamics of the force system required | |
9 | P9 | 12.0 | 5 | 0.15 | 0.8 | 0.1 | 0.05 | Overly small weld nugget diameter | |
Electromechanical (servo) system (EFS) | |||||||||
10 | E1 | 8.0 | 38 | Servo force | 0.6 | 1.95 | 4.5 | 0.16 | OK, full weld nugget, nugget diameter > 1.6 mm, penetration of \tbars <1.6 mm |
11 | E2 | 9.0 | 25 | 1.2 | 2.00 | 5.3 | 0.10 | ||
12 | E3 | 10.0 | 20 | 1.5 | 2.20 | 5.6 | 0.13 |
Preset welding cycle parameters and parameters characteristic of selected variants in the FEM calculations related to the PFS and EFS (FEM).
Red colour, unacceptable param.; green colour, acceptable param.; orange colour, the most favourable welding conditions.
The PFS variants are designated as P1 ÷ P9 (P, pneumatic system), whereas the EFS variants are designated as E1 ÷ E3 (E, electromechanical system). The analysis of the welding process performed in relation to the PFS aimed to investigate and depict the variability of process parameters and determine the most favourable welding conditions (MFWC). The results of the analysis revealed the lack of the monotonicity of the weld nugget growth (Figure 4a) visible in relation to a force of 0.75 kN. For this reason it was necessary to perform additional calculations in this area, i.e. for a value of 0.7 kN and that of 0.8 kN. In total, the analysis of the process was focused on 35 points (I = 8/9/10/11/12 kA, F = 1.5/1.25/1.0/0.8/0.75/0.7/0.5 kN).
The numerical optimisation concerning the process involving the use of the EFS was performed for lower values of current than those analysed in relation to the PFS (8.0 ÷ 10.0 kA). The numerical calculations were continued until the occurrence of one (of six) previously adopted boundary conditions.
The experimental tests were performed using inverter welding stations (DC 1 kHz) shown in Figure 3a (PFS) and Figure 3b (EFS). The welding parameters were recorded using a LogWeld 4 measurement device.
Welding machine stations: (a) SPD: (1a) inverter welding power source Harms & Wende (25 kA, 1 kHz), (2a) welding machine housing ASPA (5.5 kN), (3a, 4a) measurement device LogWeld 4, (5a) pneumatic actuator, (6a) head for measurements of electrode force, (7a) laser sensor for displacement measurements, (8a) welding current measurement sensor and (9a) leads for measurements of welding voltage. (b) SED: (1b) electromechanical welding machine F = 2 kN, (2b) servomotor, (3b) linear gear, (4b, 5b) measurement device LogWeld 4 and (6b) electrode force measurement module.
The results obtained in the numerical calculations were verified experimentally. The experimental tests involved nine variants (P1–P9) from Table 5 (PFS). All of the variants (Figure 6) were subjected to destructive tests (peeling), confirming the formation of the ring weld. However, none of the PFS variants satisfied the previously assumed criteria. Nonetheless, in spite of the exceeding of the previously assumed value of bar penetration and the obtainment of the ring weld, variant P5 was adopted as the reference variant for further optimisation-related activities. The reason for such a choice resulted from the fact that the aforesaid variant (P5) enabled the obtainment of the longest weld nugget diameter. Parameters similar to those used with reference to variant P5 were used in additional technological welding tests (Table 6, PE1–PE3). The results related to the preset parameters of the technological cycle and characteristic parameters of selected welding tests involving the use of the PFS and variants PE1–PE3 are presented in Table 6.
No. | Variant no. | Preset parameters | Recorded parameters | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Electrode force | Upslope | Main welding time | Total current (Irms) | Welding energy | Bar penetration (displacement of electrode) | Weld diameter | Number of tests | ||||
Current | Time | Current | Time | ||||||||
kN | kA | ms | kA | ms | kA | kJ | mm | mm | pcs | ||
A | B1 | B2 | C1 | C2 | D | E | F | G | H | ||
1 | PE1 | 1.0 | 10.0 | 3 | 10.0 | 40–60 | 10.0 | 0.23 | 1.50 | 1.5 | 20 |
2 | PE2 | 1.0 | 9.5 | 3 | 9.5 | 50–70 | 9.5 | 0.21 | 1.38 | 1.3 | 20 |
Preset and characteristic parameters of the PFS (experiment) [11].
The welding cycle parameters used in relation to variants PE1–PE3 included electrode force F = 1.0 kN, welding current I = 9.0–10 kA and welding time tPP = 43–63 ms. The metallographic tests involving the above-named variants confirmed the results obtained in the numerical calculations, e.g. the ring-like shape of the weld nugget.
Key: Irms, root-mean-square current; PE, pneumatic experiment.
The optimisation of the crosswise projection welding of bars was performed using the EFS. The primary criterion of the optimisation process involved the obtainment of the full weld nugget having a diameter of not less than 1.5 mm. The optimisation process assumed the use of the EFS and, in addition, the adjustment of the lowest possible value of welding current.
The optimisation process also aimed to adjust appropriate and lower electrode force than that applied initially in the process performed using the PFS and to control the displacement of the electrodes so that it could be possible to obtain the most favourable space distribution of welding power, i.e. ensuring the emission of appropriately more heat (energy) in the central part of the contact area between elements being welded (in order to melt the material of these elements) [10, 11].
The preset welding cycle parameters (grey) and the parameters characteristic of the technological welding tests performed using the EFS are presented in Table 7. The technological welding tests were performed using a current of approximately 8.0 kA, i.e. the lowest value analysed in relation to the welding process performed using the PFS. The aforesaid value of current applied in the PFS, within the entire range of analysed values of electrode force (0.5 kN ÷ 1.5 kN), was insufficient to melt the material of the elements subjected to welding. The welding process was optimised using the EFS and a welding current of 8.0 kA and that of 8.5 kA as well as the appropriate profile of electrode force (variants EE1 and EE2, Table 7).
No. | Variant no. | Preset parameters | Recorded parameters | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Force | Upslope | Main welding time | Total current (I rms) | Electrode displacement and time | Welding energy | Bar penetration (displacement of electrode) | Weld diameter | Number of tests | |||||||||
Initial | Min. | Max. | |||||||||||||||
Cur | Time | Cur. | Time | ||||||||||||||
t1/Δl1 | t2/Δl2 | t3/Δl3 | t4/Δl4 | ||||||||||||||
kN | kA | ms | kA | ms | kA | ms/mm | kJ | mm | mm | pcs | |||||||
A1 | A2 | A3 | B1 | B2 | C1 | C2 | D | E0 | E1 | E2 | E3 | F | G | H | I | ||
1 | EE1 | 1.0 | 0.4 | 1.0 | 8.0 | 3 | 8.0 | 45 | 8.0 | 10 0.08 | 30 0.25 | 10 0.05 | 30 0.25 | 0.16 | 0.70 | 1.87 | 20 |
2 | EE2 | 1.0 | 0.4 | 1.0 | 8.5 | 3 | 8.5 | 40 | 8.5 | 10 0.08 | 25 0.25 | 7 0.05 | 30 0.25 | 0.20 | 0.75 | 1.92 | 20 |
Preset and characteristic parameters of the EFS (experiment) [11].
Key: Irms, root-mean-square current; EE, electromechanical experiment.
The PFS-related numerical calculation results are presented in Figure 4 and Table 8. The results are presented in spatial diagrams developed using the Statistica software program [19]. Figure 4 presents (in the form of a spatial diagram) the formation of the weld nugget diameter (Figure 4a), welding time (Figure 4b), bar penetration depth (electrode displacement) (Figure 4c) and welding energy (Figure 4d). The correlations are presented in relation to various values of welding current and electrode force.
Variability of characteristic parameters in relation to the PFS (Al 5182, ϕ = 4 mm, MES) [
Current [kA] | (a) Weld nugget diameter [mm] | |||||||
---|---|---|---|---|---|---|---|---|
0.5 mm < d < 1.5 mm | d < 0.5 mm | Servo | ||||||
Force [kN] | ||||||||
1.50 | 1.25 | 1.00 | 0.80 | 0.75 | 0.70 | 0.50 | ||
8 | 0.1 | 0.1 | 0.2 | 0.0 | 0.1 | 0.0 | 0.3 | 1.95 |
9 | 0.0 | 0.0 | 0.6 | 0.0 | 0.0 | 0.0 | 1.1 | 2.00 |
10 | 0.1 | 0.1 | 1.5 | 1.1 | 0.1 | 0.0 | 1.5 | 2.20 |
11 | 0.0 | 0.7 | 0.3 | 0.0 | 0.2 | 0.5 | 1.1 | |
12 | 0.0 | 0.0 | 0.2 | 0.1 | 0.1 | 1.2 | 0.8 | |
Force [kN] | ||||||||
1.50 | 1.25 | 1.00 | 0.80 | 0.75 | 0.70 | 0.50 | ||
8 | 63 | 63 | 63 | 63 | 63 | 63 | 63 | 38 |
9 | 63 | 63 | 63 | 63 | 63 | 63 | 9 | 25 |
10 | 46 | 56 | 59 | 63 | 63 | 63 | 8 | 20 |
11 | 38 | 48 | 53 | 60 | 63 | 63 | 6 | |
12 | 29 | 39 | 46 | 49 | 49 | 27 | 5 | |
1.50 | 1.25 | 1.00 | 0.80 | 0.75 | 0.70 | 0.50 | ||
8 | 1.47 | 1.25 | 1.00 | 0.95 | 0.9 | 0.80 | 0.57 | 0.60 |
9 | 1.60 | 1.62 | 1.50 | 1.30 | 1.10 | 1.00 | 0.28 | 1.20 |
10 | 2.38 | 2.07 | 2.13 | 1.75 | 1.70 | 1.40 | 0.19 | 1.50 |
11 | 2.00 | 2.20 | 1.90 | 1.80 | 1.70 | 1.65 | 0.16 | |
12 | 1.85 | 2.15 | 2.54 | 1.90 | 0.80 | 0.70 | 0.15 | |
1.50 | 1.25 | 1.00 | 0.80 | 0.75 | 0.70 | 0.50 | ||
8 | 0.17 | 0.19 | 0.20 | 0.20 | 0.21 | 0.22 | 0.25 | 0.16 |
9 | 0.17 | 0.22 | 0.25 | 0.27 | 0.27 | 0.26 | 0.06 | 0.10 |
10 | 0.17 | 0.23 | 0.29 | 0.33 | 0.29 | 0.32 | 0.07 | 0.13 |
11 | 0.16 | 0.24 | 0.30 | 0.35 | 0.32 | 0.36 | 0.06 | |
12 | 0.15 | 0.24 | 0.30 | 0.34 | 0.33 | 0.22 | 0.05 |
Current [kA] | (e) Achieved criterion | |||||||
---|---|---|---|---|---|---|---|---|
D > 1.6 mm | t, welding time (63 ms) | E, expulsion | Servo | |||||
Force [kN] | ||||||||
1.50 | 1.25 | 1.00 | 0.80 | 0.75 | 0.70 | 0.50 | ||
8 | t | t | t | t | t | t | t | OK |
9 | t | t | t | t | t | t | E | OK |
10 | D | D | D | t | t | t | E | OK |
11 | D | D | D | P | t | t | E | |
12 | D | D | D | D | D | E | E | |
1.50 | 1.25 | 1.00 | 0.80 | 0.75 | 0.70 | 0.50 | ||
8 | L | L | L | L | L | L | L | F |
9 | L | L | L | L | L | L | R | F |
10 | L | L | R | R | L | L | R | F |
11 | L | L | L | L | L | L | R | |
12 | L | L | L | L | L | R | R | |
1.50 | 1.25 | 1.00 | 0.80 | 0.75 | 0.70 | 0.50 | ||
8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1 | 4.50 |
9 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2 | 5.25 |
10 | 0.0 | 0.0 | 0.9 | 0.3 | 0.0 | 0.0 | 0.7 | 5.60 |
11 | 0.0 | 0.2 | 0.0 | 0.0 | 0.0 | 0.2 | 0.5 | |
12 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.3 | 0.1 |
FEM calculation results concerning the crosswise projection welding of bars in relation to the PFS and EFS (AL 5182) [11].
Numerical values related to the graphic representation of the results presented in Figure 4 are presented in Table 8(a-d), containing, in addition, information about the following:
Unsatisfied criterion (Table 8e), i.e.:
tPP max—maximum time of welding current flow (tPP max = 63 ms)
ΔL—displacement of electrodes (penetration of bars, ΔLmax = 1.6 mm, 20% of the diameters of the bars)
W—expulsion
Weld itself (Table 8f), i.e.:
D—weld nugget diameter: below 0.7 mm; (
R—ring-shaped weld nugget: 0.7 mm < D ≤ 1.5 mm; (
F—full weld nugget: D > 1.5 mm; (
Weld nugget volume (Table 8g)
current flow time
displacement (of electrodes - penetration of bars)
welding energy.
The results presented in Table 8 supplement the information concerning the (course of) variability of the characteristic parameters from Figure 4.
Table 8 also contains the numerical calculation results obtained for the EFS (green). In relation to all of the previously assumed parameters, the conditions concerning the optimised method of control were satisfied.
The comparison of the FEM calculation results (in the form of the distribution of temperature) related to the two (i.e. PFS and EFS) electrode force systems, different values of welding current (8.0 and 10.0 kA) and various ranges of temperature (20–638°C and 577–638°C) is presented in Figure 5.
Distribution of temperature in the welding area (FEM) in relation to: (a/b) PFS (I = 8 kA, F = 1.0 kN), (c) PFS (I = 10 kA, F = 1.0 kN) and (d) EFS (I = 8.0 kA, force exerted by the servomotor).
The PFS-related technological welding tests involving the aluminium bars were performed in relation to all of the nine variants P1–P9 from Table 5. The results after the peeling tests are presented in Figure 6.
Specimens after the peeling tests (PFS, variants P1–P9).
Parameters similar to those used with reference to variant P5, i.e. in relation to which the longest weld nugget diameter was obtained, were used in additional technological welding tests performed in relation to a wider welding current range of 9.0–10.0 kA. Results (in the form of metallographic structures) related to the above-presented parameters are presented in Figure 7. The preset welding cycle parameters in relation to variants PE1 and PE3 are presented in Table 6.
Results of the metallographic tests for the PFS (F = 1 kN, I = 9.0/10.0 kA).
In terms of the EFS, the technological welding tests were performed in relation to a current of 8.0 kA and that of 8.5 kA (Table 7, variants EE1 and EE2). The comparative results in the form of the metallographic structures of the joints are presented in Figure 8a1–a2 and b1–b2 (in relation to the PFS and EFS, respectively).
Metallographic test results in relation to [
The PFS-related conclusions based on the analysis of the results presented in Figure 4 and Table 8 are the following:
Maximum obtainable weld nugget diameter amounted to 1.5 mm (Table 8a, parameter field 1).
Ring-shaped weld was formed (Table 8f, parameter field 2) within the entire range of the variability of welding current parameters and that of electrode force, also as regards the longest obtained weld nugget diameter (i.e. restricted within the range of 1.0–1.5 mm).
Criterion concerned with the exceeding of the maximum welding current flow time (tPP max = 63 ms) was observed in relation to the lower value of welding current (Table 8e, parameter fields 3a and 3b, respectively).
The highest volume of the molten material was observed in relation to the highest values of welding current and the lowest values of electrode force (Table 8g, parameter field 4). The above-named parameters were also connected with relatively low welding energy (Table 8d, parameter field 5). However, welding time was relatively short and amounted to a few milliseconds. In the aforesaid case, even the slight exceeding of the welding time resulted in expulsion (Table 8e, parameter field 7).
Excessive penetration of the bars (above the acceptable value) was related to the obtainment of the higher value of welding current and the higher value of electrode force (Table 8c, parameter field 6a (final penetration), and Table 8e, parameter field 6b (penetration value ΔlPP > 1.6 mm)).
Risk of expulsion was accompanied by the lowest value of electrode force and the higher value of welding current (Table 8e, parameter field 7).
The crucial aspect which remained was the failure to satisfy the principal criterion, i.e. the obtainment of the full weld nugget having a diameter of 1.5 mm.
The analysis of the FEM-based calculation results, presented in Figure 5, is as follows:
In relation to the PFS, a welding current of 8.0 kA and a force of 1.0 kN, Figure 5 presents the distribution of temperature within the entire range of temperature subjected to analysis, i.e. from ambient temperature to the melting point (liquidus) (Figure 5a). In such an approach, within the range of temperature, the melting of the material did not take place, and the weld nugget diameter calculated by the SOPRPAS software program amounted to a mere 0.2 mm. Figure 5b presents the distribution of temperature within the range of
In relation to a higher current of 10.0 kA (F = 1.0 kN) and the PFS, energy supplied to the weld was higher. However, the plasticisation of the welding area combined with the exertion of constant and excessively high (electrode) force led to the situation where the material was melted and pushed outside. This, in turn, resulted in the increasingly large area of contact between the elements subjected to welding (bars), leading to the abrupt decrease in current density and, consequently, the immediate cooling of the weld material. Although it was possible to observe the melting of the material, the process was extremely short (2 ms) Figure 5c2. Precisely after two milliseconds, the temperature in the entire welding area decreased below the melting point (Figure 5c3).
In relation to the lowest analysed current value amounting to 8.0 kA (Figure 5d) and the EFS, because of a different manner of electrode force control, it was easily possible to observe the welding of the material (subjected to welding) and the formation of the full weld nugget from the very beginning of the flow of welding current. In terms of the case under analysis, i.e. the welding of aluminium bars (Al 5182), the shutdown of current resulted in the immediate (within 1 ms) lowering of temperature below the melting point (Figure 5d5–d6). The foregoing indicated the intense discharge of heat from the welding area and, consequently, demanded process control-related parameters, i.e. welding current and electrode force. It should be noted that in relation to a current of 8.0 kA and the PFS, the joint formed within the entire area of contact (between the elements being welded) was in the solid state and no visible melting of the material had taken place (Figure 5a).
In relation to the EFS and variants EE1 and EE2 from Table 7, it was possible to obtain the melting of the material within the entire area of the weld. Importantly, the melting of the material took place in the central (most favourable) part of the welded joint. The obtained weld nugget diameter exceeded the previously assumed value amounting to 1.5 mm (Figure 8b1–b2).
The comparative metallographic test results concerning the PFS and EFS are presented in Figure 8. In relation to the PFS (Figure 8a1–a2), it was possible to observe the formation of the ring-shaped weld nearly within the entire range of technological cycle parameters (Figures 6 and 7). In terms of the EFS, the material subjected to welding was melted in the central part of the joint, and the weld nugget “grew” from inside towards outside.
Based on the FEM calculation and experimental test results, the optimisation of the crosswise projection welding of (aluminium) bars could be characterised as presented below. The process of optimisation was performed on the basis of characteristic courses/waveforms of related parameters (electrode force, momentary power, electrode displacement and the weld nugget diameter) in relation to the two (i.e. pneumatic and electromechanical) electrode force systems (Figure 9). To present the issue in a more convenient manner, the comparison was based on the same value of welding current, i.e. 8.0 kA. It should be emphasised that in relation to the PFS, the aforesaid value was insufficient to obtain a proper joint. The melting of the material was nearly invisible (Figure 5b). In turn, as regards the EFS, it was possible to obtain the full weld nugget having the previously assumed diameter exceeding a minimum of 1.5 mm (Figure 5d).
FEM calculation results: (a) electrode force, (b) momentary power, (c) weld nugget diameter, (d) displacement of electrodes (bar penetration depth): —Curves 1 and 3, PFS (variant P1, I = 8.0 kA, F = 1.0 kN); —Curves 2 and 4, EFS (variant E1, I = 8.0 kA, force exerted by the servomotor).
Curves 1 and 3 in Figure 9 refer to the PFS, whereas curves nos. 2 and 4 are related to the EFS. Curves 3 and 4 present the welding current waveform in relation to the PFS and EFS, respectively.
There was a strict correlation between the characteristic process parameters, where the change of one of them immediately led to changes in the remaining parameters. To explain the existing correlations, it was necessary to divide the analysis of the process into stages.
The PFS-related process could be described as follows. After adjusting the preset constant electrode force (Figure 9a, curve 1) as well as the specific value of welding current and the time of current flow (Figure 9a, curve 3), during the first stage subjected to analysis (K1), specific welding energy was generated (Figure 9b, curve 1). The waveform of the welding power (stage K2) had a direct effect (ultimately) on the specific displacement of the electrodes (Figure 9d, curve 1). At the subsequent stage (K3), the effect of the above-named factors led to the obtainment of the weld nugget characterised by a specific shape and the diameter of a mere 0.2 mm (Table 5, variant P4; Figure 9c, curve 1).
As regards the use of the PFS, the value of welding current amounting to 8.0 kA was overly low, only enabling the plasticisation of the material and resulting in an excessive increase in the area of contact between the elements subjected to welding. The foregoing led to a decrease in current density and, consequently, precluded the melting of the material subjected to welding. The material in the contact area was only heated and plasticised, whereas the maximum welding time amounting to 63 ms was exceeded.
The starting point for the optimisation of the crosswise projection welding of bars involved a
At the subsequent stage (K5), the above-presented method of control translated into the more favourable course of electrode force (Figure 9a, curve 2). The obtained values of electrode force were lower than those accompanying the use of the PFS. It should be noted that electrode force directly affected the value of resistance in the contact area (particularly in the
The summary of the above-presented analysis concerning a welding current of 8.0 kA identified as overly low to obtain a proper joint using the PFS should contain a statement saying that the use of the EFS and the application of the appropriate control of electrode force and/or displacement (after satisfying the remaining requirements (quality-related criteria)) made it possible to significantly improve the welding process and obtain the full weld nugget having the diameter of a previously assumed length (> 1.5 mm).
The adjustment of the most favourable parameters in the crosswise projection welding of bars performed using the PFS is extremely difficult, if not impossible, particularly as regards soft materials such as aluminium alloys. Electrode force is unfavourably excessively high in relation to necessarily short welding time (bars Al 5182 – 40–60 ms) and high welding current. Such conditions are mutually exclusive and constitute a significant obstacle when adjusting welding parameters. The primary limitation is the dynamics of the electrode force system, i.e. the impossibility of quickly controlling electrode force in short time, particularly during the flow of current.
A characteristic of the PFS is the fact that the preset parameter is (electrode) force and the resultant parameter is the displacement (of electrodes), not controlled in any way.
The improvement of the welding process (extension of the window of parameters) requires the use of the EFS. In the operating mode involving the displacement of electrodes, it is possible to set a more convenient trajectory of electrode movement, enabling the obtainment of the more favourable distribution of current density and the more favourable space distribution of welding power. This, in turns, translates into the generation of higher energy in the central area of the joint and, as result, the generation of higher temperature in the aforesaid area and, consequently, the obtainment of the full weld nugget having larger dimensions that those obtainable using the PFS.
The use of the EFS makes it possible to control the displacement of the electrodes during the flow of current, reach the final, previously assumed, position of the electrodes and exert lower final pressure (force) by the electrodes.
The FEM calculation results indicate the possibility of successful welding using even lower welding current than that used in the experimental verification (8.0 kA).
This work was supported by the Polish National Centre for Research and Development (NCBR) under project no. TANGO1/267374/NCBR/2015 and co-funded by Łukasiewicz – Instytut Spawalnictwa, Poland.
pneumatic (electrode) force system
electromechanical (electrode) force system
(welding) current flow time
time of current upslope from the initial to the final value of the cycle range
most favourable welding conditions
electrode force stabilisation time
maximum displacement of electrodes (penetration of bars)
maximum temperature in the
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\n\nAvoidance Measures for Academic Editors of Conflicts of Interest:
\n\nFor manuscripts submitted by the Academic Editor (or a scientific advisor), an appropriate person will be appointed to handle and evaluate the manuscript. The appointed handling Editor's identity will not be disclosed to the Author in order to maintain impartiality and anonymity of the review.
\n\nIf a manuscript is submitted by an Author who is a member of an Academic Editor's family or is personally or professionally related to the Academic Editor in any way, either as a friend, colleague, student or mentor, the work will be handled by a different Academic Editor who is not in any way connected to the Author.
\n\nCONFLICT OF INTEREST - REVIEWER
\n\nAll Reviewers are required to declare possible Conflicts of Interest at the beginning of the evaluation process. If a Reviewer feels he or she might have any material, financial or any other conflict of interest with regards to the manuscript being reviewed, he or she is required to declare such concern and, if necessary, request exclusion from any further involvement in the evaluation process. A Reviewer's potential Conflicts of Interest are declared in the review report and presented to the Academic Editor, who then assesses whether or not the declared potential or actual Conflicts of Interest had, or could be perceived to have had, any significant impact on the review itself.
\n\nEXAMPLES OF CONFLICTS OF INTEREST:
\n\nFINANCIAL AND MATERIAL
\n\nNON-FINANCIAL
\n\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
\n\nAcademic Editors and Reviewers are required to declare any non-financial, financial and material Conflicts of Interest that could influence their fair and balanced evaluation of manuscripts. If such conflict exists with regards to a submitted manuscript, Academic Editors and Reviewers should exclude themselves from handling it.
\n\nAll Authors, Academic Editors, and Reviewers are required to declare all possible financial and material Conflicts of Interest in the last five years, although it is advisable to declare less recent Conflicts of Interest as well.
\n\nEXAMPLES:
\n\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
\n\nAuthors should declare if they are board members of an organization that could benefit financially or materially from the publication of their work.
\n\nAcademic Editors should declare if they were coauthors or they have worked on the research project with the Author who has submitted a manuscript.
\n\nAcademic Editors should declare if the Author of a submitted manuscript is affiliated with the same department, faculty, institute, or company as they are.
\n\nPolicy last updated: 2016-06-09
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This system can be enhanced to encompass the imaginary numbers set after the addition of three novel axioms. As a result, any random experiment can be executed in the complex probabilities set C which is the sum of the real probabilities set R and the imaginary probabilities set M. We aim here to incorporate supplementary imaginary dimensions to the random experiment occurring in the “real” laboratory in R and therefore to compute all the probabilities in the sets R, M, and C. Accordingly, the probability in the whole set C = R + M is constantly equivalent to one independently of the distribution of the input random variable in R, and subsequently the output of the stochastic experiment in R can be determined absolutely in C. This is the consequence of the fact that the probability in C is computed after the subtraction of the chaotic factor from the degree of our knowledge of the nondeterministic experiment. 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This scheme can be improved to embody the set of imaginary numbers after adding three new axioms. Accordingly, any stochastic phenomenon can be performed in the set C of complex probabilities which is the summation of the set R of real probabilities and the set M of imaginary probabilities. Our objective now is to encompass complementary imaginary dimensions to the stochastic phenomenon taking place in the “real” laboratory in R and as a consequence to gauge in the sets R, M, and C all the corresponding probabilities. Hence, the probability in the entire set C = R + M is incessantly equal to one independently of all the probabilities of the input stochastic variable distribution in R, and subsequently the output of the random phenomenon in R can be evaluated totally in C. This is due to the fact that the probability in C is calculated after the elimination and subtraction of the chaotic factor from the degree of our knowledge of the nondeterministic phenomenon. 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Although this is a trivial problem in theory, in the practice of OMA, this is a troublesome problem. Errors, such as truncation errors, measurement noise, modeling errors, estimation errors make the separation difficult if not impossible. This leads to the appearance of nonphysical modes, and their separation from physical modes is difficult. An engineering solution to this problem is based on the so-called stability diagram which shows alignments for physical modes. This still does not solve the problem since it is rare to find modes stable in the same order. Moreover, nonphysical modes may also stabilize. Recently, the stochastic modal appropriation (SMA) algorithm was introduced as a valid competitor for existing OMA algorithms. This algorithm is based on isolating the modes mode by mode with the advantage that the modal parameters are identified simultaneously in a single step for a given mode. This is conceptually similar to ground vibration testing (GVT). SMA is based on the data correlation sequence which enjoys a special physical structure making the identification of nonphysical modes impossible under the isolating conditions. After elaborating the theory behind SMA, we illustrate these advantages on a simulated system as well as on an experimental case.",book:{id:"11066",slug:"the-monte-carlo-methods-recent-advances-new-perspectives-and-applications",title:"The Monte Carlo Methods",fullTitle:"The Monte Carlo Methods - Recent Advances, New Perspectives and Applications"},signatures:"Maher Abdelghani",authors:[{id:"417124",title:"Associate Prof.",name:"Maher",middleName:null,surname:"Abdelghani",slug:"maher-abdelghani",fullName:"Maher Abdelghani"}]},{id:"80243",title:"Applications of Simulation Codes Based on Monte Carlo Method for Radiotherapy",slug:"applications-of-simulation-codes-based-on-monte-carlo-method-for-radiotherapy",totalDownloads:77,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Monte Carlo simulations have been applied to determine and study different parameters that are challenged in experimental measurements, due to its capability in simulating the radiation transport with a probability distribution to interact with electrosferic electrons and some cases with the nucleus from an arbitrary material, which such particle track or history can carry out physical quantities providing data from a studied or investigating quantities. 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Samim Al Azad and Slimane Ed-dafali",hash:"86a6d33cf601587e591064ce92effc02",volumeInSeries:1,fullTitle:"Leadership in a Changing World - A Multidimensional Perspective",editors:[{id:"418514",title:"Dr.",name:"Muhammad",middleName:null,surname:"Mohiuddin",slug:"muhammad-mohiuddin",fullName:"Muhammad Mohiuddin",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038UqSfQAK/Profile_Picture_2022-05-13T10:39:03.jpg",institutionString:"Université Laval",institution:{name:"Université Laval",institutionURL:null,country:{name:"Canada"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Business and Management",value:86,count:1}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:1}],authors:{paginationCount:249,paginationItems:[{id:"274452",title:"Dr.",name:"Yousif",middleName:"Mohamed",surname:"Abdallah",slug:"yousif-abdallah",fullName:"Yousif Abdallah",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274452/images/8324_n.jpg",biography:"I certainly enjoyed my experience in Radiotherapy and Nuclear Medicine, particularly it has been in different institutions and hospitals with different Medical Cultures and allocated resources. Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:null},{id:"318905",title:"Prof.",name:"Elvis",middleName:"Kwason",surname:"Tiburu",slug:"elvis-tiburu",fullName:"Elvis Tiburu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Ghana",country:{name:"Ghana"}}},{id:"336193",title:"Dr.",name:"Abdullah",middleName:null,surname:"Alamoudi",slug:"abdullah-alamoudi",fullName:"Abdullah Alamoudi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"318657",title:"MSc.",name:"Isabell",middleName:null,surname:"Steuding",slug:"isabell-steuding",fullName:"Isabell Steuding",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"318656",title:"BSc.",name:"Peter",middleName:null,surname:"Kußmann",slug:"peter-kussmann",fullName:"Peter Kußmann",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"338222",title:"Mrs.",name:"María José",middleName:null,surname:"Lucía Mudas",slug:"maria-jose-lucia-mudas",fullName:"María José Lucía Mudas",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}},{id:"147824",title:"Mr.",name:"Pablo",middleName:null,surname:"Revuelta Sanz",slug:"pablo-revuelta-sanz",fullName:"Pablo Revuelta Sanz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}}]}},subseries:{item:{id:"40",type:"subseries",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"\r\n\tScientists have long researched to understand the environment and man’s place in it. The search for this knowledge grows in importance as rapid increases in population and economic development intensify humans’ stresses on ecosystems. Fortunately, rapid increases in multiple scientific areas are advancing our understanding of environmental sciences. Breakthroughs in computing, molecular biology, ecology, and sustainability science are enhancing our ability to utilize environmental sciences to address real-world problems.
\r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.
\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
",annualVolume:11966,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",editor:{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",fullName:"Ismail M.M. Rahman",profilePictureURL:"https://mts.intechopen.com/storage/users/110740/images/2319_n.jpg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null,editorialBoard:[{id:"252368",title:"Dr.",name:"Meng-Chuan",middleName:null,surname:"Ong",fullName:"Meng-Chuan Ong",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRVotQAG/Profile_Picture_2022-05-20T12:04:28.jpg",institutionString:null,institution:{name:"Universiti Malaysia Terengganu",institutionURL:null,country:{name:"Malaysia"}}},{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",fullName:"Mohamed Nageeb Rashed",profilePictureURL:"https://mts.intechopen.com/storage/users/63465/images/system/63465.gif",institutionString:null,institution:{name:"Aswan University",institutionURL:null,country:{name:"Egypt"}}},{id:"187907",title:"Dr.",name:"Olga",middleName:null,surname:"Anne",fullName:"Olga Anne",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBE5QAO/Profile_Picture_2022-04-07T09:42:13.png",institutionString:null,institution:{name:"Klaipeda State University of Applied Sciences",institutionURL:null,country:{name:"Lithuania"}}}]},{id:"39",title:"Environmental Resilience and Management",keywords:"Anthropic effects, Overexploitation, Biodiversity loss, Degradation, Inadequate Management, SDGs adequate practices",scope:"\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
",annualVolume:11967,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",editor:{id:"137040",title:"Prof.",name:"Jose",middleName:null,surname:"Navarro-Pedreño",fullName:"Jose Navarro-Pedreño",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRAXrQAO/Profile_Picture_2022-03-09T15:50:19.jpg",institutionString:"Miguel Hernández University of Elche, Spain",institution:null},editorTwo:null,editorThree:null,editorialBoard:[{id:"177015",title:"Prof.",name:"Elke Jurandy",middleName:null,surname:"Bran Nogueira Cardoso",fullName:"Elke Jurandy Bran Nogueira Cardoso",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGxzQAG/Profile_Picture_2022-03-25T08:32:33.jpg",institutionString:"Universidade de São Paulo, Brazil",institution:null},{id:"211260",title:"Dr.",name:"Sandra",middleName:null,surname:"Ricart",fullName:"Sandra Ricart",profilePictureURL:"https://mts.intechopen.com/storage/users/211260/images/system/211260.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}}]},{id:"40",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"