Injection Properties.
\r\n\t2) Human sexual disorders in males and females.
\r\n\t3) Psychological aspects of the human sexual response cycle and its disorders.
\r\n\t4) The therapeutic aspects.
\r\n\tThe human sexual response cycle and human sexual behavior are interrelated. How this inter-relationship and its association to normal sexual health need to be delineated. In a world torn between sex and sexually transmitted disease, clear-cut scientific information in the form of a monograph is required to educate.
\r\n\r\n\tHuman sexuality, gender identity, and sexuo-erotic orientation play great roles in human health and disease. Sex education is the need of the hour and a reflection will be timely.
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Understanding of the combustion phenomenon through experimentation is involved and expensive. In such situations, numerical simulations act as an alternative platform. There is a need to develop mathematical models for the reactive flows. Due to variation of density, the heat transfer and fluid motion inside the engine is unsteady and turbulent. Most of the simplified real process versions are based on the idealization of the cylindrical geometry models. Combustion phenomenon is greatly influenced by fuel properties, fuel preparation and fuel distribution inside the cylinder. The advancement in computer technology is helpful in solving the complicated equations relevant to the turbulence-chemistry interactions.
Jafarmadar and Zehni [4] have studied the high-speed diesel engine combustion using AVL-FIRE code CFD. They have analyzed the peak pressure rise and heat release rate. They have made comparison of numerical simulations with experiments varying the fuel injection pressure. The KIVA group of codes will be helpful in performing diesel engine simulations with less computational time. The enhanced code and coarse meshes are utilized to simulate combustion in a heavy-duty Mitsubishi Heavy Industries diesel engine for the service loads, speeds, and injection pressure. The normal simulation time from IVC to EVO is reduced from 60 hours to 1 hour using 12 processors [5]. Various researchers have developed alternative codes and models for minimizing the simulation time of combustion [6, 7, 8].
Mirko Baratta et al. [9] have utilized CFD models and analyzed laminar flame speed for different fuel composition and mixture dilution rates. Michela Costa et al. [10] have performed simulations on premixed syngas and biodiesel as pilot injection. The combustion efficiency decreases, exhaust gas temperature and thermal efficiency increase with increasing the % of syngas. The reduced chemical kinetics model gives an improved solution. Amin Maghbouli et al. [11] have used a 3D-CFD/Chemical kinetics framework model to investigate the diesel engine/gas dual-fuel engine combustion process. Methane and n-heptane are used as natural gas representatives. Source terms in conservation equations of energy and species are calculated by integrating CHEMKIN solver into KIVA code. Pressure, ingniton delay and heat release rate are in good agreement with experiments. Vijayshree and Ganesan [12] have performed CFD simulations for designing IC engine through combustion process analysis.
CFD studies thus provide flow visualization, optimal engine parameters and knowledge in combustion phenomenon, which are difficult to acquire from experiments. Experimental investigations are involved in obtaining the penetration length, velocity distribution, swirl ratio, tumble ratio and heat release rate. Modifications in engine design and parameters are difficult to implement. The task will be definitely a time-consuming process. CFD serves as a versatile and powerful tool for designing IC engine and gives insight into the complex fluid dynamics. Experiments on various blends (5–30%) indicate B-20 blend as viable in terms of performance and emission. Combustion simulations help in minimizing engine bench tests.
Comparative studies are made in this article to examine the combustion behaviour of diesel and B-20 blend of Jatropha. Combustion simulations have been performed utilizing ANSYS Fluent 15.0 version. Combustion simulations are in line with those of DSC (differential scanning calorimetry) analysis with a heating rate of 10°C/min in atmospheric air.
This section deals with the combustion simulations on the four-stroke single-cylinder direct injection compression ignition engine running at a constant speed of 1500 rpm, injection timing of 25° BTDC with diesel and 20% blend of Jatropha biodiesel. Standard finite volume method of computational fluid dynamics (CFD) is capable of simulating the two-phase engine flow. Three-dimensional Navier–Stokes equations are solved with k-ε turbulence model. The details of combustion simulations carried out for half-cycle by considering the two strokes compression and expansion at zero load condition are presented below. Figure 1 shows the front view and 3D view of the geometry model. The model is a four-stroke diesel engine with 4 valves and 4 ports for air sucking inlets and hot gas outlets. The green portion in Figure 1 is the assembly of a cylinder and piston. Specifications are made from the standard engine KIRLOSKAR AV-1 model. The mathematical models in CFD begin with representation of combustion chamber geometry (meshing of engine). The meshing of the geometry model Figure 2 is generated using the pre-processor of ANSYS Fluent 15.0 version.
Geometry model. (a) Front view. (b) 3D view.
Geometry mesh.
The fluid chamber bottom of ICE is modelled with 450,570 elements and 470,654 nodes. The fluid chamber top of ICE is modelled with 9795 elements and 13,544 nodes. Fluid piston of ICE is modelled with 66,443 elements and 73,360 nodes. The model domain consists of 526,808 elements and 557,558 nodes. Mesh parameters of IC sector are: Reference size = 0.947 mm; Minimum mesh size = 0.19 mm; Maximum mesh size = 0.474 mm; and the chamber body mesh size = 1.487 mm with 3 inflation layers.
The complex physical phenomenon of combustion flows in IC engines (see Figure 2) can be understood by solving the following 3-Dimensional Naiver-Stokes (N-S) equations with the Reynold’s Average Navier–Stokes (RANS) model [13, 14, 15] and the k-ε turbulence model [16, 17].
N-S equations:
RANS model:
k-ε turbulence model:
Here ρ is density; μ is dynamic viscosity; u and v are velocity components in x and y directions; p refers to pressure; μt is the eddy or turbulent viscosity;
Finite volume equations are crucial for CFD simulations to handle fluid boundary layers on surfaces [19, 20]. The shear gap is heavily influenced by boundary conditions. Fluid near the wall (i.e., layer close to the wall) is the viscous sub-layer, whereas above this layer is dominated by turbulent shears. The laminar pressure-stress relation is
Here
The temperature at the ICE-cylindrical chamber bottom and top surfaces is 567 K. The ICE-cylindrical-piston wall temperature is also specified as 567 K. The wall temperature of ICE-piston is 645 K. The wall temperature is 602 K on ICE-sector-top-faces. Relaxation of crank angles are: Engine speed = 1500 rev/min.; Crank radius = 55 mm; Piston pin-offset = 0 mm; Connecting rod length = 165 mm; Cylinder bore length = 110 mm; and Cylinder bore diameter = 90 mm. Table 1 provides the injection properties. Tables 2 and 3 provide thermo-physical properties of diesel, Jatropha oil methyl ester (JOME) and its B-20 blend for combustion simulations. The properties are measured from TPS 500S with Kapton and Teflon sensors.
Parameter | Dimension |
---|---|
X-Position | 0 |
Y-Position | −0.00012 |
Z-Position | 2E-05 |
X-Axis | 0 |
Y-Axis | −0.34202 |
Z-Axis | 0.939693 |
Diameter (m) | 2.54E-4 |
Evaporating Species | C7h16 |
Temperature (K) | 366.7 |
Start Crank Angle (deg) | 721 |
End Crank Angle (deg) | 742.5 |
Cone Angles (deg) | 9 |
Cone Radius (deg) | 1.27E-4 |
Total Flow Rate (kg/s) | 1.3333E-05 |
Velocity Magnitude (m/s) | 468 |
Injection Properties.
Fuel | Calorific value (MJ/kg) | Kinematic Viscosity @40°C (cst) | Cetane value | Density (kg/m3) | Flash point (°C) | Pour point (°C) | Cloud point (°C) |
---|---|---|---|---|---|---|---|
DIESEL | 44.22 | 2.87 | 47.8 | 840 | 76 | −3 | 6.5 |
JOME | 39.79 | 4.73 | 52 | 862.2 | 182.5 | 3 | 3 |
B-20JOME | 44.10 | 3.99 | 49 | 840.2 | 93.5 | −3 | 4 |
Biodiesel and diesel properties [2].
Fuel | Thermal Conductivity (W/mk) | Specific Heat (MJ/m3K) | Thermal Diffusivity (mm2/s) |
---|---|---|---|
Diesel | 0.3390 | 0.2563 | 1.323 |
JOME | 0.2537 | 0.5773 | 0.4083 |
B-20 JOME | 0.3090 | 0.3894 | 0.7934 |
Thermo-physical properties of diesel and biodiesel.
Fuel starts to penetrate into the combustion chamber at 728°C for the diesel as well as biodiesel. Due to the high viscosity of the B-20 Jatropha leads to poor atomization. As in [21], the temperature rise during the fuel spray is around 2770°C for diesel and 2670°C for biodiesel (see Figures 3 and 4). As in [22], B-20 Jatropha exhibits high magnitude of velocity for atomization due to viscosity on fuel spray. Hot air presence prior to the fuel injection evaporates the fuel just beyond fixed length (which is called a break-up the length). Engine cylinder spray is around 50–100 atmosphere. At that time, fuel is injected into the chamber. Since the high-velocity jet has to mix with compressed air in a small interval of time thereby B-20 blend exhibits slightly low velocity magnitude (see Figures 5 and 6).
Visualization of spray at 728° for diesel.
Visualization of spray at 728° for B-20 Jatropha.
Velocity contour plot at the time of spray for diesel.
Velocity contour plot at the time of spray for B-20 Jatropha.
Fuel injection starts at 724°C and ends at 740°C. During fuel injection temperature varies from 500 to 2770°C. But at the end of the compression stroke, diesel temperature varies from 500 to 2360°C, whereas biodiesel temperature varies from 500 to 2180°C. Since B-20 blend is having less heat of vaporization when compared to that of diesel, heat transfer lowers the local air temperature as observed in [23]. Similarly, the magnitude of velocity for B-20 blend is slightly lower than that of diesel (see Figures 5 and 6).
Figures 7 and 8 show the variation of temperature after the combustion for diesel and B-20 Jatropha. Temperature varies from 443 to 705°C for the diesel, whereas it varies from 437 to 685°C for biodiesel. Slightly low temperature variation is noticed for the B-20 blend. This could be due to high diffusion burning phase for the biodiesel. Due to increase in volatility of the slow-burning biodiesel, burning time is significantly high for B-20 as in [24].
Temperature distribution after combustion for diesel.
Temperature distribution after combustion for B-20 Jatropha.
It is noted at the end of the expansion stroke that the velocity magnitude for diesel varies up to 9.34 m/s, whereas in case of B-20 blend, it varies up to 9.4 m/s. Some amount of residual gases present in the engine at the end of expansion stroke.
DSC experiments are performed under air atmosphere to diesel, Jatropha oil methyl ester (JOME), and its B-20 blend at 10°C/min in Universal TA instruments with alumina pan. Performing experiments on liquid samples is difficult due to evaporation and non-stability of complex during heating. Hermetically sealed pans are used in experiments with universal cramper. Two types of calibration are performed on instrument: (i) Initially with T-Zero (Temperature) calibration; and (ii) Enthalpy calibration. Initially Experiments are performed without the samples to get baseline further with known material (sapphire or Al2O3) heat of fusion is calculated by heating up to its melting point. Heat of fusion value is compared with theoretical estimates.
Convergence study is made by varying mesh (See Figure 9). Computational domain is chosen for three different meshes (430,542, 557,558 and 662,731). Maximum deviation of 9.4% is observed in results by increasing the number of meshes from 430,542 to 557,558. Further increasing to 662,731, maximum deviation of 1.3% is observed. From this study, number of meshes finalized for computation is 557,558.
Mesh Convergence study.
Deformation on the working fluid increases due to viscous shear stress. Thereby its internal energy increases at the expense of its turbulent kinetic energy. During compression, the airflow is forced into the piston and the swirl rotational velocity increases at the end of the compression stroke. The radius is reduced while the momentum is conserved leading to increase in angular velocity. When the piston moves down, reverse trend happens. The flow slows down due to the friction against the combustion chamber walls [25].
Velocity magnitude in Figure 10 shows little variation from 570° to 725° and large variation where injection starts at 725° and ends at 748°. Biodiesels show slightly low velocity magnitudes resulting in the time delay. The penetration length in Figure 11 can be divided into 3 phases as in. [26]. In the initial phase, there is no penetration length (i.e., zero) for the crank angles from 722° to 725°. In the second phase, the penetration length increases rapidly from starting to ending of injection period for the crank angles from 725° to 737°, which indicates more amount of fuel injected inside the engine cylinder. Similar phenomenon is observed for the biodiesel with less penetration length.
Magnitude of velocity versus crank angle.
Penetration length versus Crank angle.
Turbulence is of the major concern in the engine cylinder. The diffusion in the engine cylinder results from the local fluctuations in the flow field. This leads to the enhanced rates of momentum, heat and mass transfer yielding to the satisfactory engine operation. The engine flows involve complicated shear layer combination, boundary layer, and reticulating regions [27]. As the flow is unsteady it exhibits cycle by cycle fluctuations. In diesel engine swirl is used for rapid mixing between the inducted charge and the injected fuel. It is also used for speeding the combustion process. Figure 12 shows the swirl ratio versus crank angle for diesel and B-20 Jatropha. For diesel and biodiesel compression starts at 570.25 deg. crank angle with a temperature of 404°C and ends at 712° CA with temperature 1008°C, Swirl ratio varies from 1.3 to 0.89 during the CA 570° to 830° for the biodiesel swirl ratio varies from 1.3 to 0.92 with same crank angle. B-20 JOME is having high viscosity when compared to that of diesel, which may lead to the complicated shear layer combination thereby increasing the thickness of the boundary layer.
Swirl ratio versus crank angle.
Tumble ratio strongly affects the mixture formation. The high-pressure fuel injection certainly disturbs the bulk motion of the cylinder in the engine. The effect of fuel injection pressure on bulk motion of air is negligible because of symmetrical positioning of the fuel injector holes about the axis of the injector. The tumble ratio in Figure 13 decreases (from −0.03 to −0.42) initially from 570° to 700° CA and again increases (from −0.42 to 0) during the combustion stroke (i.e., from 720 to 800° CA). In case of B-20 JOME, tumble ratio decreases from −0.03 to 0.44 and increases from 0.44 to 0.03. For biodiesel tumble ratio, there are some fluctuations from 700° to 720°CA. During that situation, piston is nearer to the TDC and fuel injection happens period. This phenomenon may be due to the presence of oxygen content in biodiesels leading to the oxidation process. This behaviour can be noticed from the temperature contour plot for diesel and biodiesel. Tumble ratio does not vary much till certain crank angle degree and for the reduced volume of high combustion chamber. Tumble ratio is found to be high at high engine speeds during the fuel injection phase because of high piston velocity helping tumble motion [28]. Peak pressure rise depends on the combustion rate during the initial phase. In turn it depends on the amount of fuel present in the uncontrolled combustion phase. The volatility of the slow-burning biodiesel increases the combustion duration thereby giving the high rate of pressure rise (see Figure 14).
Tumble ratio versus crank angle.
Static pressure versus crank angle.
Premixed burning phase associated with high heat release rate is significant to the diesel. It gives high thermal efficiency for the diesel. Figure 15 shows apparent heat release rate (AHRR) versus crank angle. From the heat release rate graph, one can analyse the occurrence of short premixed heat release flame for the esters. Diffusion burning phase under the second peak is high for biodiesel when compared to that of diesel. This may be due to viscosity of biodiesels on fuel spray, reduction of air entrainment and fuel-air mixing rates. Biodiesels possess low latent heat of vaporization. Thereby, heat transfer lowers local air temperature [29]. The heat release rate for the biodiesel is found to be low when compared to that of diesel.
Apparent heat release rate (AHRR) versus crank angle.
Figure 16 shows the comparison of DSC combustion curves. Generally, combustion process of organic fuels exhibit exothermic reaction in air due to double bond presence [30]. JOME consists of the carbon number varying from 14 to 20 (i.e., C14 to C20) which decomposes in the range of 30–240°C. JOME exhibits 298°C peak temperature of combustion with 84 J/g enthalpy. Biodiesel in engine results in hard burning with less enthalpy [31, 32]. Combustion curve of B-20 exhibits 268°C peak temperature with 147.5 J/g enthalpy, which is comparable to that of diesel having 138 J/g enthalpy. This indicates that combustion of B-20 JOME is close to that of diesel. Combustion of diesel molecules takes place initially followed by biodiesel [33, 34]. B-20 JOME combustion starts early resulting in better combustion when compared to JOME and diesel with high reaction region. During the initial phase of biodiesel combustion short pre-mixed flame occurs followed by diffusion burning phase requiring blending [34]. B-20 JOME indicates that JOME and diesel molecules mixed perfectly and homogenous mixture occurs at 20%. Therefore, performance of B-20 blend is close to that of diesel.
Comparison of DSC Combustion curves.
Combustion simulations are performed on the four-stroke single-cylinder direct injection compression ignition engine running at a constant speed of 1500 rpm, injection timing of 25° BTDC with diesel and 20% blend of Jatropha biodiesel. Standard FVM (finite volume method) of CFD (computational fluid dynamics) is considered while simulating the two-phase engine flow. 3-Dimensional N-S (Navier–Stokes) equations are solved with k-ε turbulence model.
Results of combustion simulations are presented for half-cycle by considering the two strokes compression and expansion at zero load condition.
Combustion simulations confirm the B-20 blend as an alternative for diesel. DSC profiles of the diesel and B-20 JOME show endothermic peak, which is related to vaporization of methyl esters for B-20 JOME and volatilization of small fraction for the diesel.
Biodiesel exhibits high enthalpy despite combustion of the engine, and causing serious engine problems. B-20 blend exhibits high enthalpy when compared to that of diesel with reduced peak temperature. Biodiesel exhibits high enthalpy despite of satisfactory performance as a fuel, its high viscosity causing poor fuel atomization. The trend of simulations matches with DSC results.
The authors would like to acknowledge the encouragements received from the Visvesvarayya Technological University Belgaum and the Koneru Lakshmaiah Educational Foundation, deemed to be University, Vaddeswaram, India.
The authors declare that there is no conflict of interests.
High strength to low weight ratio is a sought-after feature in the materials used in the structural elements of today’s world. With the technological advances in recent years, composite materials are used in many industries, where durability and lightness are at the forefront, especially from the aerospace to automotive sectors. Polymeric composites have been used in many engineering applications due to their high strength in proportion to their weight, high stability, rigidity, superior corrosion, and fatigue resistance [1, 2, 3]. Woven or knitted fabrics of durable synthetic fibers such as glass, carbon, or aramid are used to reinforce polymer matrix composite. Woven reinforcement exhibits good stability in the warp and weft directions and offers the highest cover or yarn packing density in relation to fabric thickness [4]. Knitting is another technique of fabric formation for reinforcing. The fabric is formed by the inter-looping of yarn. The inter-looping of yarn can be done in two ways, namely, warp and weft knitting [5]. Complex lattice structures can be produced by local deformation of the loop in knitted structures. The loop that oriented through-thickness direction improves the out-of-plane mechanical properties of the structure. In addition, thanks to the perfectible geometry of the loop, high impact resistance and damage tolerance can be achieved. Textile-reinforced composites consist of a textile form as the reinforcement phase and usually a polymer for the matrix phase. 2D or 3D woven fabrics, knitted fabrics, stitched fabrics, braids, nonwovens, and multiaxial fabrics can be used as textile materials. Each of these textile forms has its own fiber architecture and combination of properties such as strength, stiffness, flexibility, and toughness, which are reflected on the composite performance to a certain extent [6]. A number of researchers have studied the damage strength of knitted fabric-reinforced composite structures under loading of tensile, compressive, fracture, and impact [7, 8, 9, 10].
\nLower cost, lower density, comparable specific strength, and better deformation capacity are the advantages of glass fibers as compared to carbon fibers. However, types of glass fibers have worse mechanical properties than carbon fibers, which is a limitation to the applications, especially when these materials are exposed to more severe stresses. One way to overcome this problem is hybridization, i.e., the combination of glass and carbon fibers, using a matrix compatible with both fibers, to obtain a composite material with satisfactory properties and lower cost. Hybridization with different fiber types within laminated composites increases the design space and opens up possible new engineering applications with optimized mechanical and functional properties. In addition, in the classical composites, the hybridization of carbon and glass fibers may cause a positive hybrid effect, which relies on the increase of carbon fibers failure strain, when compared to the pure carbon-based composites [11]. Generally, as far as the strength of the carbon/glass hybrid is concerned, the higher the volume percentage of carbon fibers is, the stronger the hybrid laminate becomes. The reason is that the carbon fibers are very tough and stiff, while the glass fibers are less stiff and less durable. In carbon/glass fiber-reinforced composites, an advantageous hybrid effect is also observed, which consists in increasing the carbon fiber failure strain when compared to the pure carbon fiber. In the literature, there are studies investigating the effects of carbon/glass hybridization on mechanical behavior. Tabrizi et al. [12] have investigated damage evolution in carbon/glass fiber hybrid composites with various stacking sequences under pure bending and tensile loading conditions. Swolfs et al. [13] concluded that the effect for tensile failure strain is well established, with a typical range of 10–50% for traditional hybrid composites such as carbon/glass. Wisnon et al. [14] have investigated hybrid effects on thin ply carbon/glass unidirectional laminates. Test results showed that the magnitude of the hybrid effect depends on the ply thickness. Dong and Davies [15] have studied the mechanical properties of the hybrid composites reinforced with the glass and carbon fibers. Naito and Oguma [16] have investigated tensile properties and fracture behavior of carbon/glass hybrid thermoplastic composite rods consisting of unidirectional PAN-based carbon fiber, braids of E-glass glass fibers, and thermoplastic epoxy matrix.
\nComposite materials used for structural purposes can be damaged during manufacturing, assembly, and usage of them. These damages can cause breaking of the materials under environmental effects and external loadings. One of these damages is crack onset and fracture, which depends on crack formation. Fracture, which is precarious for composite structures, can cause loss of life and property. Thus, the fracture analysis of the composite materials, especially focusing on the growth of defects that occur during the service that leads to destruction, is vital to the safety of the composite structures. The value of fracture toughness of composite materials strongly depends on three loading states at the end of the crack tip as the tensile opening mode (mode I), the in-plane shear mode (mode II), and the out-of-plane shear mode (mode III). However, fracture state does not form in pure mode I or mode II in the fiber-reinforced composite materials due to combined loading or anisotropy of composite structures [17]. For this reason, the study of the mixed-mode interlaminar fracture toughness is very important. Zhao et al. [18] have studied interlaminar fracture toughness of hybrid woven carbon-Dyneema composites with different hybridization schemes. The results showed that hybridization improves both mode I and mode II fracture toughness of carbon-Dyneema interfaces. Bienias et al. [19] have investigated interlaminar fracture toughness of woven glass and carbon-reinforced multidirectional fiber metal laminates under mixed-mode (mode I/II) loading. Jung and Kim [20] have investigated the fracture toughness of carbon-glass/epoxy interply hybrid composite under mode I loading condition. Saidane et al. [21] have investigated mode-I interlaminar fracture toughness of flax; glass and hybrid flax-glass fiber are woven composites by using a double cantilever beam test method. Swolf et al. [22] have studied translaminar fracture toughness of woven carbon/glass hybrid composites under impact loading.
\nHybridizing two or more reinforcement materials within a matrix seeks to enhance the advantages of the reinforcing constituents and lessen the effect of the less desirable characteristics. In this study, the fracture toughness of pure and intraply hybrid knitted fabric-reinforced laminated composite plates have been investigated, experimentally and numerically. For this purposes, hybrid fabrics were knitted in a 1 × 1 rib-knitted structure by using glass and carbon fibers with equal weight carbon/glass fibers (50–50%). In order to investigate the effect of the knitting pattern width on the fracture behavior, the reinforcing hybrid fabrics were knitted at three different widths, such as 50, 25, and 12.5 mm. Arcan test apparatus was used to define mode I (opening mode), mode II (shearing mode), and mode I/II (mixed-mode) fracture toughness of test specimens. Also, fracture toughness for all composite samples was numerically determined in finite element analysis by using the J-integral method.
\nKnitting is primarily classified as weft knitting and warp knitting. This classification is based on the direction of movement of yarn with respect to the direction of fabric formation. If the yarns run in the width or crosswise direction with reference to the direction of fabric formation during knitting, then the process of knitting is called weft knitting. The yarns in the knitted structure are just like weft yarns in woven fabrics. The weft-knitted fabrics made with one set of needles arranged in the grooves on one needle bed are called single jersey fabrics or plain knitted fabrics. In the experimental study, intraply hybrid reinforcement fabrics, which have 1×1 rib knitting structure, were knitted in a V-bed semi-automatic knitting machine. For this aim, 2400tex E-glass fibers and 3K carbon fibers were used as a knitting reinforcement element.
\nA loop is called a face loop or back loop according to the direction of the passing of one loop through another one during inter-looping (Figure 1a). A course is a horizontal row of loops produced by all the adjacent needles during the same knitting cycle. A wale is a vertical column of loops made by the same needle in successive knitting cycles. The direction of course and wale in weft-knitted fabric is shown in Figure 1b.
\n(a) A knitted loop and (b) wale and course directions of loops.
The row numbers of glass and carbon corresponding to the considered width are shown in Table 1. The average width of a single row is around 2.8–3.3 mm in the scope of this study. The average weight of hybrid and non-hybrid reinforcement fabrics was 730 g/m2. The thickness of knitted fabric is approximately 2.7 mm.
\nFiber type | \nPattern width (mm) | \n||
---|---|---|---|
12.5 | \n25 | \n50 | \n|
Glass | \n4 | \n8 | \n15 | \n
Carbon | \n4 | \n9 | \n17 | \n
The row numbers of glass and carbon fibers for desired pattern widths.
The matrix material was procured from Duratek Epoxy and Polyurethane Systems in Turkey. Hybrid laminated composite materials having four laminas were produced by hand lay-up methods. After all, laminas were saturated with epoxy resin; semi-product laminated composites were cured at 100oC under pressure of 8 MPa for 100 min, by using temperature-time-pressure-controlled hydraulic press.
\nAfter this process, the composite plates were cooled to room temperature under the same pressure to avoid warping effects. The fiber volume fractions for hybrid carbon-glass/epoxy laminated composites were determined as 55% approximately. In this study, the hybridization process is carried out using reinforcing fabrics knitted with different types of fibers on the same layer [23, 24, 25]. During stacking of layers, the same type of fibers was brought one on the top of another. The photographic representation of produced knitted hybrid composites is shown in Figure 2.
\nManufactured knitted fabric laminated composites (a) pure carbon/epoxy and (b) pure glass/epoxy fabric, and hybrid carbon-glass/epoxy composites with (c) 12.5, (d) 25, and (e) 50 mm pattern widths.
The fracture toughness of pure and hybrid knitted laminated composites was determined for mode I (0°), mode I–II (30°, 45°, and 60°), and mode II (90°) by using modified Arcan test apparatus. In this context, Arcan test samples were cut with a CNC router machine by using 3 mm cutter blade (Figure 3). After cutting, crack having 4 mm was created on the Arcan test sample by using a jigsaw, which had 0.6 mm diameter. Hybrid composite specimens had two different reinforcement materials like glass and carbon fibers in the same layer. Therefore, crack onset in a different reinforcement material may occur in a different shape under load. Crack in the Arcan test sample having the same knitting pattern width was varied in two different forms to investigate crack onset mechanism in glass and carbon fibers.
\nArcan test specimen (a) pure carbon/epoxy, (b) pure glass/epoxy, and hybrid carbon-glass/epoxy having (c) carbon side crack and (d) glass side crack.
In the first form, the crack was opened to glass fiber side and made to move toward the carbon fiber side. In the other form, the crack was opened to carbon fiber side and made to move toward the glass fiber side (Figure 3c, d). Linear elastic fracture mechanics (LEFM) has been found as a useful tool for the investigation of cracks in composite materials. The purpose of fracture toughness testing is to determine the value of the critical stress intensity factor or plane strain fracture toughness K
where P
The geometric factor formulas \n
For the mixed-mode loading effective fracture toughness,
where
The energy release rate (G) is defined as the amount of energy released per unit of the new fractured area formed due to cracking. The energy release rate is also defined as the crack extension force. A simple procedure using energy concepts is utilized to develop an analytical description of the crack extension force. The energy release rates for orthotropic material with the crack line parallel to the principal orthotropic direction which coincides with the fiber orientation can be calculated by Eq. (6):
\nwhere
where \n
where similar to the effective fracture toughness formula, the values of G
In fracture analysis of composite materials, J-integral method expresses the stress energy release rate or work (energy) per unit fracture surface area. The J-integral defines the plastic stress and strain intensity in a manner similar to the fracture toughness (K) parameter, which represents the stress intensity of the surrounding elastic field, in the crack vicinity. The J-integral depends on stress, strain, crack size, and the geometry of the crack and body. The expression of J in the 2D form can be given by Eq. (9). It assumes that the crack lies in the global Cartesian x(u)–y(v) plane:
\nwhere Γ is a contour around the crack in the Cartesian coordinate system, W is stress field energy density, and \n
The coordinates and typical paths to evaluate the J-integral.
where \n
The numerical analysis was performed in the commercial finite element software ANSYS Workbench by the use of a quasi-static rate-independent J-integral method, which can be used to determine the pure mode and mixed-mode fracture toughness. Eight-node quadrilateral plane elements with two degrees of freedom per node were used to model the cracked test specimens. The element has plasticity, creep, swelling, stress stiffening, large deflection, and large strain capabilities. The mesh was refined around the crack tip so that the smallest element size found in the crack tip elements was approximately 0.2 mm. The numerical model consists of 29,600 nodes approximately. An implicit solver was used for the finite element analysis. Implicit solutions are based on quantities calculated in the previous time step (backward Euler time scheme), which means even for large time steps the solution remains stable (unconditionally stable) [41]. In modeling fracture mechanics for laminated composite where both tensile and shear failure are common, a fracture criterion for predicting mode I, mode II, and mixed-mode I/II fracture onset is needed. Crack tip opening displacement test or CTOD is one of a family of fracture criteria that measures the resistance of a material to growing a crack. In this context, CTOD failure criteria were employed for the crack onset in finite element analysis. There are two elastic-plastic parameters widely accepted by the fractured community; J-integral and CTOD [42, 43]. In case of LEFM, the elastic calculation for the CTOD can be expressed in Eq. (12):
\nwhere
The connection between the fixture and specimen is idealized by a rigid and continuous joint, based on the fact that the fixture and pins used in Arcan tests are relatively rigid compared to the specimen. Thus in the finite element analysis, the specimen-fixture system was treated as one continuous solid with two regions of different thickness and material properties. The fixed boundary condition was used, and distributed loads were assigned for the numerical model. Figure 5 shows the state of the finite element model after the analysis.
\nThe state of the finite element model after the analysis.
The fracture tests were carried out using the Arcan test apparatus for 0°, 30°, 45°, 60°, and 90° loading angles. Figure 6 has presented the load-displacement curve of pure glass/epoxy and pure carbon/epoxy at different loading angles. Load-displacement graphs of hybrid composites are not given because they behave similarly to others. When the loading angle changes from mode I to mode II plane, the maximum damage load (P
Load-displacement curves according to loading angles (a) pure glass/epoxy and (b) pure carbon/epoxy.
Material type | \nLoading angle | \n|||||
---|---|---|---|---|---|---|
0o\n | \n30o\n | \n45o\n | \n60o\n | \n90o\n | \n||
Glass side cracked | \nPure glass/epoxy | \n6883 | \n6902 | \n6453 | \n7576 | \n8553 | \n
Carbon-glass/epoxy (12.5 mm width) | \n8642 | \n7970 | \n8557 | \n9345 | \n9669 | \n|
Carbon-glass/epoxy (25 mm width) | \n8531 | \n7791 | \n8323 | \n8990 | \n8917 | \n|
Carbon-glass/epoxy (50 mm width) | \n7900 | \n7373 | \n7440 | \n8405 | \n8745 | \n|
Carbon side cracked | \nPure carbon/epoxy | \n9358 | \n8406 | \n9567 | \n10366 | \n12510 | \n
Carbon-glass/epoxy (12.5 mm width) | \n8771 | \n8772 | \n9119 | \n9816 | \n9943 | \n|
Carbon-glass/epoxy (25 mm width) | \n8718 | \n8187 | \n9049 | \n9453 | \n9654 | \n|
Carbon-glass/epoxy (50 mm width) | \n8426 | \n8178 | \n8491 | \n9356 | \n9413 | \n
Average critical fracture loads P
The average P
Material type | \nLoading angle | \n|||||
---|---|---|---|---|---|---|
0o\n | \n30o\n | \n45o\n | \n60o\n | \n90o\n | \n||
Pure glass/epoxy | \n\n | \n562.55 | \n441.17 | \n343.75 | \n259.71 | \n– | \n
\n | \n– | \n63.46 | \n83.40 | \n109.18 | \n161.30 | \n|
\n | \n562.55 | \n445.71 | \n353.72 | \n281.73 | \n161.30 | \n|
Carbon-glass/epoxy (12.5 mm) | \n\n | \n629.80 | \n500.37 | \n438.25 | \n336.11 | \n– | \n
\n | \n– | \n70.28 | \n110.97 | \n146.10 | \n158.59 | \n|
\n | \n629.80 | \n505.28 | \n452.08 | \n366.50 | \n158.59 | \n|
Carbon-glass/epoxy (25 mm) | \n\n | \n597.71 | \n468.11 | \n398.30 | \n330.30 | \n– | \n
\n | \n– | \n67.03 | \n103.33 | \n135.53 | \n146.70 | \n|
\n | \n597.71 | \n472.89 | \n411.49 | \n357.02 | \n146.70 | \n|
Carbon-glass/epoxy (50 mm) | \n\n | \n585.46 | \n454.56 | \n383.10 | \n304.46 | \n– | \n
\n | \n– | \n64.14 | \n94.61 | \n130.11 | \n141.90 | \n|
\n | \n585.46 | \n459.06 | \n394.61 | \n331.10 | \n141.90 | \n
Fracture toughness (MPa
Material type | \nLoading angle | \n|||||
---|---|---|---|---|---|---|
0o\n | \n30o\n | \n45o\n | \n60o\n | \n90o\n | \n||
Pure carbon/epoxy | \n\n | \n664.64 | \n532.40 | \n494.83 | \n360.78 | \n– | \n
\n | \n– | \n73.25 | \n119.60 | \n159.56 | \n177.15 | \n|
\n | \n664.64 | \n537.41 | \n509.08 | \n394.49 | \n177.15 | \n|
Carbon-glass/epoxy (12.5 mm) | \n\n | \n635.60 | \n523.76 | \n467.58 | \n352.70 | \n– | \n
\n | \n– | \n71.40 | \n115.39 | \n153.05 | \n165.03 | \n|
\n | \n635.60 | \n528.60 | \n481.61 | \n384.47 | \n165.03 | \n|
Carbon-glass/epoxy (25 mm) | \n\n | \n619.57 | \n505.11 | \n436.68 | \n345.04 | \n– | \n
\n | \n– | \n70.15 | \n109.41 | \n147.50 | \n151.22 | \n|
\n | \n619.57 | \n509.96 | \n450.18 | \n375.24 | \n151.22 | \n|
Carbon-glass/epoxy (50 mm) | \n\n | \n599.85 | \n479.02 | \n415.84 | \n337.96 | \n– | \n
\n | \n– | \n68.60 | \n107.79 | \n144.49 | \n148.98 | \n|
\n | \n599.85 | \n483.90 | \n429.59 | \n367.55 | \n148.98 | \n
Fracture toughness (MPa
The calculated fracture toughness results showed that the loading angle, crack position, and pattern width directly affect the fracture behavior of the composite material. As loading angle increases from mode I to mode II, fracture toughness for each material type decreases. Applied load during mode I loading case forces the crack to open. So, damage occurs in the form of fiber and matrix fracture. In the case of the opening mode, the damage occurs in the form of a matrix crack and subsequent fiber breakage. Also, the breakage occurs in a fast and brittle form, due to high-stress concentrations occurring at the crack end in the opening mode. During mode II loading, the applied load progresses the crack by shearing. As a result of shear deformation, the separation between laminas named delamination occurs. Damage of the brittle matrix material holding the lamina together allows the delamination to spread easily between the laminas. Thus, the material gains more ability to deform. The loads on the sample are transferred to the reinforcing hybrid fabric with increasing deformation, and the fiber structure is subjected to shear force. Due to the anisotropic behavior of the knitting structure, it can be seen from fracture test results that the shear strength of reinforcement fabric was higher than the tensile strength.
\nWhen fracture toughness values of pure glass and carbon fabric-reinforced composites were compared, fracture toughness of carbon/epoxy composites was found to be up to 43% higher than glass/epoxy. If a similar comparison is made for hybrid composites that had the same pattern width, the fracture toughness of the samples with carbon side cracked is 11% higher than for samples with glass side cracked. According to the results obtained from pure and hybrid composites, the crack on the carbon side has a tougher spreading mechanism than on the glass side.
\nAlthough all hybrid fabric-reinforced composites contain equal amounts of glass and carbon fiber, different fracture toughness values were obtained for the same loading angle and crack location. Glass and carbon knitting pattern widths of hybrid fabrics have affected the fracture toughness of the material. At the combination boundary of the glass and carbon fiber knitting, a new intermediate form is occurred by the interlocking of glass fiber and carbon fiber loops. This intermediate form increased the strength of the structure due to exhibited behavior that is as flexible as the glass fiber and as strong as the carbon fiber. Accordingly, the fracture toughness value of the material has increased by decreasing pattern width or in other words increasing the number of intermediate forms. When the fracture toughness values at the same loading angle of the samples having the carbon side crack were compared with regard to the pattern width, the samples having a pattern width of 12.5 mm have more toughness value up to 9 and 12%, respectively, than the samples with 25 and 50 mm pattern width. If the similar comparison was made for the samples having a crack on the glass side, it was seen that the samples with a pattern width of 12.5 mm have more toughness value up to 10 and 15% than those with a pattern width of 25 and 50 mm, respectively.
\nA numerical study was also performed by using ANSYS finite element program for all loading angles. Some mechanical test values, which required to create a finite element model of glass and carbon knitted fabric-reinforced composite structures, were determined experimentally, and the obtained results are given in Table 5. The elasticity modulus in the wale direction (
Material type | \n\n | \n\n | \n\n | \n\n | \n\n | \n\n | \n\n | \n\n | \n\n | \n
---|---|---|---|---|---|---|---|---|---|
Glass/epoxy | \n24105.84 | \n19621.19 | \n4160.16 | \n127.82 | \n117.80 | \n98.61 | \n81.94 | \n40.33 | \n36.21 | \n
Carbon/epoxy | \n40437.71 | \n29891.17 | \n5112.89 | \n200.91 | \n156.36 | \n125.80 | \n99.27 | \n51.94 | \n46.23 | \n
Mechanical properties of nonhybrid knitted fabric-reinforced composite specimens.
From the physical point of view, the energy release rate is the most appropriate physical quantity to characterize the fracture behavior. For purely elastic materials, the energy release rate G is identical to the J-integral because there is no energy stored in the crack cavity. In linear elastic fracture mechanics, the J-integral coincides with total energy release rate,
The J-integral value is calculated by the ANSYS program with the aid of the finite element model. The comparisons of the J-integral and strain energy release rate values, which were obtained from experimental and numerical analyses, were given in Tables 6 and 7 depending on the crack location. When the comparisons in Tables 6 and 7 are examined, it is seen that experimental and numerical results are compatible with each other. However, for the samples having the same pattern width, the energy required to progress the carbon side crack is higher than the glass side crack at the same loading angle.
\nMaterial type | \nLoading angle | \n|||||
---|---|---|---|---|---|---|
0o\n | \n30o\n | \n45o\n | \n60o\n | \n90o\n | \n||
Pure glass/epoxy | \n\n | \n17.81 | \n8.52 | \n3.19 | \n2.16 | \n1.28 | \n
\n | \n14.98 | \n9.38 | \n5.88 | \n3.68 | \n1.06 | \n|
Carbon-glass/epoxy (12.5 mm) | \n\n | \n16.97 | \n11.61 | \n9.63 | \n6.65 | \n0.95 | \n
\n | \n18.78 | \n12.05 | \n9.59 | \n6.22 | \n1.02 | \n|
Carbon-glass/epoxy (25 mm) | \n\n | \n14.93 | \n11.13 | \n7.93 | \n5.53 | \n0.90 | \n
\n | \n16.91 | \n10.56 | \n7.94 | \n5.91 | \n0.88 | \n|
Carbon-glass/epoxy (50 mm) | \n\n | \n14.34 | \n10.02 | \n7.93 | \n4.82 | \n0.67 | \n
\n | \n16.23 | \n9.95 | \n7.31 | \n5.08 | \n0.82 | \n
Comparison of J-integral and strain energy release rate (
Material type | \nLoading angle | \n|||||
---|---|---|---|---|---|---|
0o\n | \n30o\n | \n45o\n | \n60o\n | \n90o\n | \n||
Pure carbon/epoxy | \n\n | \n18.38 | \n11.98 | \n9.81 | \n6.65 | \n1.47 | \n
\n | \n20.91 | \n13.64 | \n12.17 | \n7.20 | \n1.28 | \n|
Carbon-glass/epoxy (12.5 mm) | \n\n | \n17.45 | \n12.96 | \n9.82 | \n7.09 | \n1.09 | \n
\n | \n19.12 | \n13.19 | \n10.89 | \n6.84 | \n1.11 | \n|
Carbon-glass/epoxy (25 mm) | \n\n | \n15.20 | \n11.05 | \n8.84 | \n5.84 | \n0.95 | \n
\n | \n18.17 | \n12.28 | \n9.51 | \n6.52 | \n0.93 | \n|
Carbon-glass/epoxy (50 mm) | \n\n | \n15.62 | \n10.26 | \n7.82 | \n5.52 | \n1.05 | \n
\n | \n17.03 | \n11.05 | \n8.66 | \n6.26 | \n0.90 | \n
Comparison of J-integral and strain energy release rate (G
In linear elastic fracture mechanics, Eq. (11) is valid between the fracture stress intensity factor (K
A comparison of the experimentally obtained fracture toughness values ((K
Material type | \nLoading angle | \n|||||
---|---|---|---|---|---|---|
0o\n | \n30o\n | \n45o\n | \n60o\n | \n90o\n | \n||
Pure glass/epoxy | \n( | \n562.55 | \n445.71 | \n353.72 | \n281.73 | \n161.30 | \n
( | \n516.85 | \n417.70 | \n317.40 | \n261.29 | \n145.66 | \n|
% error | \n8.12 | \n6.28 | \n10.27 | \n7.25 | \n9.70 | \n|
Carbon-glass/epoxy (12.5 mm) | \n( | \n629.80 | \n505.28 | \n452.08 | \n366.50 | \n158.59 | \n
( | \n639.68 | \n551.30 | \n515.75 | \n400.53 | \n172.45 | \n|
% error | \n1.57 | \n9.11 | \n14.08 | \n9.29 | \n8.74 | \n|
Carbon-glass/epoxy (25 mm) | \n( | \n597.71 | \n472.89 | \n411.49 | \n357.02 | \n146.70 | \n
( | \n549.63 | \n536.17 | \n462.49 | \n371.52 | \n159.11 | \n|
% error | \n8.04 | \n13.38 | \n12.39 | \n4.06 | \n8.46 | \n|
Carbon-glass/epoxy (50 mm) | \n( | \n585.46 | \n459.06 | \n394.61 | \n331.10 | \n141.90 | \n
( | \n499.28 | \n517.96 | \n437.08 | \n377.01 | \n127.37 | \n|
% error | \n14.72 | \n12.83 | \n10.76 | \n13.87 | \n10.24 | \n
Experimental and numerical fracture toughness values of glass side cracked specimens.
Material type | \nLoading angle | \n|||||
---|---|---|---|---|---|---|
0o\n | \n30o\n | \n45o\n | \n60o\n | \n90o\n | \n||
Pure glass/epoxy | \n( | \n664.64 | \n537.41 | \n509.08 | \n394.49 | \n177.15 | \n
( | \n623.11 | \n564.88 | \n468.68 | \n408.48 | \n189.78 | \n|
% error | \n6.25 | \n5.11 | \n7.94 | \n3.55 | \n7.13 | \n|
Carbon-glass/epoxy (12.5 mm) | \n( | \n635.60 | \n528.60 | \n481.61 | \n384.47 | \n165.03 | \n
( | \n607.15 | \n597.83 | \n541.68 | \n426.50 | \n180.12 | \n|
% error | \n4.48 | \n13.10 | \n12.47 | \n10.93 | \n9.14 | \n|
Carbon-glass/epoxy (25 mm) | \n( | \n619.57 | \n509.96 | \n450.18 | \n375.24 | \n151.22 | \n
( | \n674.09 | \n574.84 | \n513.97 | \n417.84 | \n163.68 | \n|
% error | \n8.80 | \n12.72 | \n14.17 | \n11.35 | \n8.24 | \n|
Carbon-glass/epoxy (50 mm) | \n( | \n599.85 | \n483.90 | \n429.59 | \n367.55 | \n148.98 | \n
( | \n524.25 | \n553.78 | \n484.21 | \n406.19 | \n160.65 | \n|
% error | \n12.60 | \n14.44 | \n12.72 | \n10.51 | \n7.83 | \n
Experimental and numerical fracture toughness values of carbon side cracked specimens.
According to Tables 8 and 9, it can be said that the results are close to each other when numerical values are compared with experimental values. The maximum error value was 15% for the finite element analysis when the experimental values are taken as reference. This maximum error value indicates that the numerical model created for finite element analysis successfully converges to the fracture test condition.
\nDamage modes and stress distributions of laminated composites were given in Figure 7 after experimental fracture damage and FEM analysis. Due to important stress concentrations around the notches in uniaxial tension, specimen fracture generally occurred in the significant crack tip. As noticed from previous tests, the fracture mechanism consisted of one unique cracked interface identical for all glass/epoxy composite samples tested whatever the loading direction. In such a case, the crack propagated between the two loops of rows, which is in the direction of the wale, and the crack could not pass through the other loops. Although different crack onset mechanisms did not appear depending on the loading angle in the glass/epoxy specimens, FEM analyses have shown that the stress distributions in the crack region vary depending on the loading angle. Fractured carbon/epoxy composite samples presented a nearly horizontal cracked zone that was different from a plane surface for loading angle of 30o and 60o. During the experimental Arcan test, it was observed that the crack progress in the main delamination plane without any side cracking and branching. Fiber bending and breaking behind the crack tip were observed macroscopically in crack onset during the test.
\nDamage and stress distributions after experimental fracture and FEM analysis of laminated composites for (a) glass/epoxy and (b) carbon/epoxy.
The experimental and numerical analysis visual results of hybrid composites with 12.5 mm pattern width, which have the maximum fracture toughness values, are given in Figure 8. The crack propagates by the glass in Figure 8(a) and by carbon in Figure 8(b). Von Mises stress distribution for different loading angles, which obtained from finite element analysis, is shown. The crack started from the crack tip due to high-stress concentration at the crack tip, and it propagates to the other side by breaking fibers and/or fiber pull out. It can be clearly said that the numerical damage forms were obtained in the similar views of the experimental damage forms as illustrated in Figure 8. According to the results of numerical damage, Von Mises stresses show a vertical progression in the case of mode I, while a more horizontal progression occurs in the case of mode II.
\nThe experimental and numerical visual results of hybrid composites with 12.5 mm pattern width having (a) glass side crack and (b) carbon side crack.
This paper has presented the fracture behavior of pure and hybrid knitted fabric-reinforced laminated composites based on experimental and numerical analyses. In this context, the effect of crack location, loading angle, and pattern width on fracture behavior are examined. A modified version of the Arcan test fixture was employed to conduct a mode I, mode II, and mode I/II test. The obtained fracture test results of hybrid specimens are compared with the test results of pure glass/epoxy and pure carbon/epoxy samples. In addition, finite element models of cracked test specimens were created according to the data obtained from the mechanical tests. Fracture behaviors of hybrid composites were numerically analyzed using J-integral method. The concluding remarks in this study can be summarized as follow:
According to the results obtained from the mechanical tests, knitted fabrics have been found to be an alternative to woven fabrics for reinforcing polymer composites. In addition, the test results show that the mechanical strength values change depending on the knitting direction and all mechanical test values are larger in the wale direction.
The maximum and minimum fracture toughness value for carbon-glass/epoxy hybrid laminated composites was obtained in mode I and mode II loading conditions. The highly complex structure of the knitted fabric composites induces various toughening mechanisms. Fracture toughness behaviors of pure and hybrid composites varied in terms of loading angle. When, the loading angle increased from 0 (mode I) to 90 (mode II), the critical damage load increases. On the contrary, the fracture toughness and energy release rate decreases. The results indicated that the Arcan cracked specimen is tougher in tensile loading conditions and weaker in shear loading conditions.
The rib-knitted fabric-reinforced composite shows different fracture toughness and energy release rate values for both crack progression directions despite the fact that damage images showed that the crack growth modes are different: in the wale direction, the crack followed the wavy surface of the fabric, and in the course direction, the majority of yarns is broken. In the wale direction, the major fracture mechanisms were the matrix deformations, leading to micro-cracks, which will branch in a network. In the course direction, the crack does not strictly follow the waviness of the fabrics but tends to grow through them. The main damage occurs by multiple fiber breakage. This phenomenon is supposed to be highly energy consuming because it implies events such as peel off, yarn bridging, and yarn failure.
For all fracture tests of pure fabric-reinforced composite, carbon/epoxy specimens were much more resistant than glass/epoxy in terms of failure loads whatever the loading angle.
As the width of the pattern increased, the fracture strength of the hybrid composites decreased. In this respect, the hybridization processing should be done in the narrowest pattern width for high resistance to fracture.
In terms of crack locations, the progression of the crack in the glass-reinforced zone is more hazardous than the progress in the carbon reinforcing zone. During the assembly of carbon-glass hybrid composites, it is better to ensure that the bolt holes are opened on the carbon side if the bolts are to be used.
When the fracture toughness values that were obtained experimentally and numerically are compared, it is seen that the results are consistent. In addition, in terms of fracture energy, experimentally obtained strain energy release rate (G) and numerical fracture energy (J-integral) values are similar. In this respect, the usability and validity of the J-integral method have been proven to simulate numerical fracture analysis of knitted fabric-reinforced laminated composites.
The Internet has irrevocably changed the dynamics of scholarly communication and publishing. Consequently, we find it necessary to indicate, unambiguously, our definition of what we consider to be a published scientific work.
",metaTitle:"Prior Publication Policy",metaDescription:"Prior Publication Policy",metaKeywords:null,canonicalURL:"/page/prior-publication-policy",contentRaw:'[{"type":"htmlEditorComponent","content":"A significant number of working papers, early drafts, and similar work in progress are openly shared online between members of the scientific community. It has become common to announce one’s own research on a personal website or a blog to gather comments and suggestions from other researchers. Such works and online postings are, indeed, published in the sense that they are made publicly available. However, this does not mean that if submitted for publication by IntechOpen they are not original works. We differentiate between reviewed and non-reviewed works when determining whether a work is original and has been published in a scholarly sense or not.
\\n\\nThe significance of Peer Review cannot be overstated when it comes to defining, in our terms, what constitutes a published scientific work. Peer Review is widely considered to be the cornerstone of modern publishing processes and the key value-adding contribution to a scholarly manuscript that a publisher can make.
\\n\\nOther than the issue of originality, research misconduct is another major issue that all publishers have to address. IntechOpen’s Retraction & Correction Policy and various publication ethics guidelines identify both redundant publication and (self)plagiarism to fall within the definition of research misconduct, thus constituting grounds for rejection or the issue of a Retraction if the work has already been published.
\\n\\nIn order to facilitate the tracking of a manuscript’s publishing history and its development from its earliest draft to the manuscript submitted, we encourage Authors to disclose any instances of a manuscript’s prior publication, whether it be through a conference presentation, a newspaper article, a working paper publicly available in a repository or a blog post.
\\n\\nA note to the Academic Editor containing detailed information about a submitted manuscript’s previous public availability is the preferred means of reporting prior publication. This helps us determine if there are any earlier versions of a manuscript that should be disclosed to our readers or if any of those earlier versions should be cited and listed in a manuscript’s references.
\\n\\nSome basic information about the editorial treatment of different varieties of prior publication is laid out below:
\\n\\n1. CONFERENCE PAPERS & PRESENTATIONS
\\n\\nGiven that conference papers and presentations generally pass through some sort of peer or editorial review, we consider them to be published in the accepted scholarly sense, particularly if they are published as a part of conference proceedings.
\\n\\nAll submitted manuscripts originating from a previously published conference paper must contain at least 50% of new original content to be accepted for review and considered for publication.
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\\n\\n2. NEWSPAPER & MAGAZINE ARTICLES
\\n\\nNewspaper and magazine articles usually do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense. Articles appearing in newspapers and magazines rarely possess the depth and structure characteristic of scholarly articles.
\\n\\nSubmitted manuscripts stemming from a previous newspaper or magazine article will be accepted for review and considered for publication. However, Authors are strongly advised to report any such publication in an accompanying note to the External Editor.
\\n\\nAs with the conference papers and presentations, Authors should obtain any necessary permissions from the newspaper or magazine that published the work, and indicate that they have done so in a note to the External Editor.
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\\n\\nAlthough such papers are regularly made publicly available via personal websites and institutional repositories, their general purpose is to gather comments and feedback from Authors’ colleagues in order to further improve a manuscript intended for future publication.
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\\n\\n4. SOCIAL MEDIA, BLOG & MESSAGE BOARD POSTINGS
\\n\\nWe feel that social media, blogs and message boards are generally used with the same intention as grey literature, to formulate ideas for a manuscript and gather early feedback from like-minded researchers in order to improve a particular piece of work before submitting it for publication. Therefore, we do not consider such internet postings to be publication in the scholarly sense.
\\n\\nNevertheless, Authors are encouraged to disclose the existence of any internet postings in which they outline and describe their research or posted passages of their manuscripts in a note to the Academic Editor. Please note that we will not strictly enforce this request in the same way that we would instructions we consider to be part of our conditions of acceptance for publication. We understand that it may be difficult to keep track of all one’s internet postings in which the researcher´s current work might be mentioned.
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\\n\\nPolicy last updated: 2017-03-20
\\n"}]'},components:[{type:"htmlEditorComponent",content:'A significant number of working papers, early drafts, and similar work in progress are openly shared online between members of the scientific community. It has become common to announce one’s own research on a personal website or a blog to gather comments and suggestions from other researchers. Such works and online postings are, indeed, published in the sense that they are made publicly available. However, this does not mean that if submitted for publication by IntechOpen they are not original works. We differentiate between reviewed and non-reviewed works when determining whether a work is original and has been published in a scholarly sense or not.
\n\nThe significance of Peer Review cannot be overstated when it comes to defining, in our terms, what constitutes a published scientific work. Peer Review is widely considered to be the cornerstone of modern publishing processes and the key value-adding contribution to a scholarly manuscript that a publisher can make.
\n\nOther than the issue of originality, research misconduct is another major issue that all publishers have to address. IntechOpen’s Retraction & Correction Policy and various publication ethics guidelines identify both redundant publication and (self)plagiarism to fall within the definition of research misconduct, thus constituting grounds for rejection or the issue of a Retraction if the work has already been published.
\n\nIn order to facilitate the tracking of a manuscript’s publishing history and its development from its earliest draft to the manuscript submitted, we encourage Authors to disclose any instances of a manuscript’s prior publication, whether it be through a conference presentation, a newspaper article, a working paper publicly available in a repository or a blog post.
\n\nA note to the Academic Editor containing detailed information about a submitted manuscript’s previous public availability is the preferred means of reporting prior publication. This helps us determine if there are any earlier versions of a manuscript that should be disclosed to our readers or if any of those earlier versions should be cited and listed in a manuscript’s references.
\n\nSome basic information about the editorial treatment of different varieties of prior publication is laid out below:
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\n\nGiven that conference papers and presentations generally pass through some sort of peer or editorial review, we consider them to be published in the accepted scholarly sense, particularly if they are published as a part of conference proceedings.
\n\nAll submitted manuscripts originating from a previously published conference paper must contain at least 50% of new original content to be accepted for review and considered for publication.
\n\nAuthors are required to report any links their manuscript might have with their earlier conference papers and presentations in a note to the Academic Editor, as well as in the manuscript itself. Additionally, Authors should obtain any necessary permissions from the publisher of their conference paper if copyright transfer occurred during the publishing process. Failure to do so may prevent Us from publishing an otherwise worthy work.
\n\n2. NEWSPAPER & MAGAZINE ARTICLES
\n\nNewspaper and magazine articles usually do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense. Articles appearing in newspapers and magazines rarely possess the depth and structure characteristic of scholarly articles.
\n\nSubmitted manuscripts stemming from a previous newspaper or magazine article will be accepted for review and considered for publication. However, Authors are strongly advised to report any such publication in an accompanying note to the External Editor.
\n\nAs with the conference papers and presentations, Authors should obtain any necessary permissions from the newspaper or magazine that published the work, and indicate that they have done so in a note to the External Editor.
\n\n3. GREY LITERATURE
\n\nWhite papers, working papers, technical reports and all other forms of papers which fall within the scope of the ‘Luxembourg definition’ of grey literature do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense.
\n\nAlthough such papers are regularly made publicly available via personal websites and institutional repositories, their general purpose is to gather comments and feedback from Authors’ colleagues in order to further improve a manuscript intended for future publication.
\n\nWhen submitting their work, Authors are required to disclose the existence of any publicly available earlier drafts in a note to the Academic Editor. In cases where earlier drafts of the submitted version of the manuscript are publicly available, any overlap between the versions will generally not be considered an instance of self-plagiarism.
\n\n4. SOCIAL MEDIA, BLOG & MESSAGE BOARD POSTINGS
\n\nWe feel that social media, blogs and message boards are generally used with the same intention as grey literature, to formulate ideas for a manuscript and gather early feedback from like-minded researchers in order to improve a particular piece of work before submitting it for publication. Therefore, we do not consider such internet postings to be publication in the scholarly sense.
\n\nNevertheless, Authors are encouraged to disclose the existence of any internet postings in which they outline and describe their research or posted passages of their manuscripts in a note to the Academic Editor. Please note that we will not strictly enforce this request in the same way that we would instructions we consider to be part of our conditions of acceptance for publication. We understand that it may be difficult to keep track of all one’s internet postings in which the researcher´s current work might be mentioned.
\n\nIn cases where there is any overlap between the Author´s submitted manuscript and related internet postings, we will generally not consider it to be an instance of self-plagiarism. This also holds true for any co-Author as well.
\n\nFor more information on this policy please contact permissions@intechopen.com.
\n\nPolicy last updated: 2017-03-20
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He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,annualVolume:11419,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,annualVolume:11420,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,annualVolume:11421,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. 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In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,annualVolume:11422,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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