Experimental conditions used to run flotation trials. The cross sectional area of the flotation column had a constant value, S = 283 cm2.
\r\n\tOne basic topic is that of expression manipulation: combining, expanding etc, and the applications of this scholar topic needs focusing on.
\r\n\r\n\tThe general topic of "polynomials" is very large, and here the focus is both on scholar/student basics of it, and on applications of some special polynomials in science and research.
\r\n\r\n\tAn important topic of the book is "algebraic curve". Here the approaches are multiple: basic/scholar on one hand, and applications on the other hand. It must be noticed the use of algebraic curves properties in the field of differential equations, for example for finding the singularities.
\r\n\r\n\tGrobner basis is a very modern and applied topic of algebra. Here we must outline the great importance of Grobner basis and polynomial ideals manipulation, in the differential equations field, an example being in fast finding normal forms of differential systems.
\r\n\r\n\tRelated to this last topic of the book, but applying to all specified topics, it must be noticed the importance of numeric algorithms. The importance of software algorithms in all fields of science is continuously increasing. Therefore, computational approach of the specified algebraic topics is very useful, with applications in other mathematical and scientific fields.
",isbn:"978-1-83968-393-0",printIsbn:"978-1-83968-392-3",pdfIsbn:"978-1-83968-394-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"2a81efb05ce334905cc672188033b15d",bookSignature:"Dr. Adela Ionescu",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9907.jpg",keywords:"expand, factoring, combining, simplifying, random polynomials, special polynomials, orthogonal polynomials, polynomial factorization, two variables polynomials, homogenization, parameterization, singularity, monomial order, polynomial ideal, leading monomial, normal form",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 26th 2019",dateEndSecondStepPublish:"December 17th 2019",dateEndThirdStepPublish:"February 15th 2020",dateEndFourthStepPublish:"May 5th 2020",dateEndFifthStepPublish:"July 4th 2020",remainingDaysToSecondStep:"10 days",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,editors:[{id:"146822",title:"Dr.",name:"Adela",middleName:null,surname:"Ionescu",slug:"adela-ionescu",fullName:"Adela Ionescu",profilePictureURL:"https://mts.intechopen.com/storage/users/146822/images/system/146822.jpg",biography:"Dr. Adela Ionescu is a lecturer at the University of Craiova, Romania. She received her PhD degree from the Polytechnic University of Bucharest, Romania. Her research focuses on development and implementation of new methods in the qualitative and computational analysis of differential equations and their applications. This includes constructing adequate models for approaching the study of different industrial phenomena from a dynamical system standpoint and also from a computational fluid dynamics standpoint. By its optimizing techniques, the aim of the modeling is to facilitate the high understanding of the experimental phenomena and to implement new methods, techniques, and processes. Currently, Dr. Ionescu is working in developing new analytical techniques for linearizing nonlinear dynamical systems, with subsequent applications in experimental cases. The bifurcation theory and its applications in related fields is also a domain of interest for her. She has published six monographs and few scientific papers in high-impact journals. She is also a member of few scientific international associations and has attended more than 45 international conferences.",institutionString:"University of Craiova",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Craiova",institutionURL:null,country:{name:"Romania"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"15",title:"Mathematics",slug:"mathematics"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"287827",firstName:"Gordan",lastName:"Tot",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/287827/images/8493_n.png",email:"gordan@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"6217",title:"Computational Fluid Dynamics",subtitle:"Basic Instruments and Applications in Science",isOpenForSubmission:!1,hash:"0fb7b242fd063d519b361e5c2c99187b",slug:"computational-fluid-dynamics-basic-instruments-and-applications-in-science",bookSignature:"Adela Ionescu",coverURL:"https://cdn.intechopen.com/books/images_new/6217.jpg",editedByType:"Edited by",editors:[{id:"146822",title:"Dr.",name:"Adela",surname:"Ionescu",slug:"adela-ionescu",fullName:"Adela Ionescu"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],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:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.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:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3794",title:"Swarm Intelligence",subtitle:"Focus on Ant and Particle Swarm Optimization",isOpenForSubmission:!1,hash:"5332a71035a274ecbf1c308df633a8ed",slug:"swarm_intelligence_focus_on_ant_and_particle_swarm_optimization",bookSignature:"Felix T.S. Chan and Manoj Kumar Tiwari",coverURL:"https://cdn.intechopen.com/books/images_new/3794.jpg",editedByType:"Edited by",editors:[{id:"252210",title:"Dr.",name:"Felix",surname:"Chan",slug:"felix-chan",fullName:"Felix Chan"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3621",title:"Silver Nanoparticles",subtitle:null,isOpenForSubmission:!1,hash:null,slug:"silver-nanoparticles",bookSignature:"David Pozo Perez",coverURL:"https://cdn.intechopen.com/books/images_new/3621.jpg",editedByType:"Edited by",editors:[{id:"6667",title:"Dr.",name:"David",surname:"Pozo",slug:"david-pozo",fullName:"David Pozo"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"9662",title:"Semi-Empirical Modelling and Management of Flotation Deinking Banks by Process Simulation",doi:"10.5772/8445",slug:"semi-empirical-modelling-and-management-of-flotation-deinking-banks-by-process-simulation",body:'\n\t\tEnergy use rationalization and the substitution of fossil with renewable hydrocarbon sources can be considered as some of the most challenging objectives for the sustainable development of industrial activities. In this context, the environmental impact of recovered papers deinking is questioned (Byström & Lönnstedt, 2000) and the use of recovered cellulose fibres for the production of bio-fuel and carbohydrate-based chemicals (Hunter, 2007; Sjoede et al., 2007) is becoming a possible alternative to papermaking. Though there is still room for making radical changes in deinking technology and/or in intensifying the number of unit operations (Julien Saint Amand, 1999; Kemper, 1999), the current state of the paper industry dictates that most effort be devoted to reduce cost by optimizing the design of flotation units (Chaiarrekij et al., 2000; Hernandez et al., 2003), multistage banks (Dreyer et al., 2008; Cho et al., 2009; Beneventi et al., 2009) and the use of deinking additives (Johansson & Strom, 1998; Theander & Pugh, 2004). Thereafter, the improvement of the flotation deinking operation towards lower energy consumption and higher separation selectivity appears to be necessary for a sustainable use of recovered fibres in papermaking.
\n\t\t\tNevertheless, over complex physical laws governing physico-chemical interactions and mass transport phenomena in aerated pulp slurries (Bloom & Heindel, 2003; Bloom, 2006), the variable composition and sorting difficulties of raw materials (Carré & Magnin, 2003; Tatzer et al., 2005) hinder the use of a mechanistic approach for the simulation of the flotation deinking process. At this time, the use of model mass transfer equations and the experimental determination of the corresponding transport coefficients is the most widely used method for the accurate simulation of flotation deinking mills (Labidi et al., 2007; Miranda et al., 2009; Cho et al., 2009).
\n\t\t\tSolving the mass balance equations in flotation deinking and generally in papermaking systems with several recycling loops and constraints is not straightforward: this requires explicit treatment of the convergence by a robust algorithm and thus computer-aided process simulation appears as one of the most attractive tools for this purpose (Ruiz et al., 2003; Blanco et al., 2006; Beneventi et al., 2009). Process simulation software are widely used in papermaking (Dahlquist, 2008) for process improvement and to define new control strategies. However, paper deinking mills have been involved in this process rationalization effort only recently and the full potential of process simulation for the optimization and management of flotation deinking lines remains underexploited.
\n\t\t\tThis chapter describes the four stages that have been necessary for the development of a flotation deinking simulation module based on a semi-empirical approach, i.e.:
\n\t\t\tthe identification of transport mechanisms and their corresponding mass transfer equations;
the validation of model equations on a laboratory-scale flotation cell;
the correlation of mass transfer coefficients with the addition of chemical additives in the pulp slurry;
the implementation of model equations on a commercial process simulation platform, the simulation of industrial flotation deinking banks and the comparison of simulation results with mill data.
After the validation of the simulation methodology, deinking lines with different configurations are simulated in order to evaluate the impact of line design on process efficiency and specific energy consumption. As a step in this direction, single-stage with mixed tank/column cells, two-stage and three-stage configurations are evaluated and the total number of flotation units in each stage and their interconnection are used as main variables. Explicit correlations between ink removal efficiency, selectivity, energy consumption and line design are developed for each configuration showing that the performance of conventional flotation deinking banks can be improved by optimizing process design and by implementing mixed tank/column technologies in the same deinking line.
\n\t\tParticle transport in flotation deinking cells can be modelled using semi-empirical equations accounting for four main transport phenomena, namely, hydrophobic particle flotation, entrainment and particle/water drainage in the froth (Beneventi et al., 2006).
\n\t\t\tIn flotation deinking system, the gas and the solid phases are finely dispersed in water as bubbles and particles with size ranging between ~0.2 – 2 mm and ~10 – 100 µm, respectively. The collision between bubbles and hydrophobic particles can induce the formation of stable bubble/particle aggregates which are conveyed towards the surface of the liquid by convective forces (Fig. 1a). Similarly, lipophilic molecules adsorbed at the air/water interface are removed from the pulp slurry by air bubbles (Fig. 1b). The rate of removal of hydrophobic materials by adsorption/adhesion at the surface of air bubbles, \n\t\t\t\t\t
where c\n\t\t\t\t\t\n\t\t\t\t\t\tn\n\t\t\t\t\t is the concentration of a specific type of particle (namely, ink, ash, organic fine elements and cellulose fibres) and k\n\t\t\t\t\t\n\t\t\t\t\t\tn\n\t\t\t\t\t its corresponding flotation rate constant,
\n\t\t\t\t\n\t\t\t\t\tQ\n\t\t\t\t\t\n\t\t\t\t\t\tg\n\t\t\t\t\t is the gas flow, α an empirical parameter, S is the cross sectional area of the flotation cell and K\n\t\t\t\t\t\n\t\t\t\t\t\tn\n\t\t\t\t\t is an experimentally determined parameter including particle/bubble collision dynamics and physicochemical factors affecting particle adhesion to the bubble surface.
\n\t\t\tDuring the rising motion of an air bubble in water, a low pressure area forms in the wake of the bubble inducing the formation of eddies with size and stability depending on bubble size and rising velocity. Both hydrophobic and hydrophilic small particles can remain trapped in eddy streamlines (Fig. 1c) and they can be subsequently entrained by the rising motion of air bubbles.
\n\t\t\t\tParticles and solutes entrainment is correlated to their concentration in the pulp slurry and to the water upward flow in the froth (Zheng et al., 2005).
\n\t\t\t\tScheme of transport mechanisms acting during the flotation deinking process. (a) Particle attachment and flotation, (b) liphopilic molecules adsorption, (c) influence of size on the path of cellulose particle in the wake of an air bubble (Beneventi et al. 2007), (d) water and particle drainage in the froth.
The rate of removal due to entrainment, \n\t\t\t\t\t
where ϕ = c\n\t\t\t\t\t\n\t\t\t\t\t\t0f\n\t\t\t\t\t\n\t\t\t\t\t/c\n\t\t\t\t\t\n\t\t\t\t\t\tn\n\t\t\t\t\t is the entrainment coefficient, c\n\t\t\t\t\t\n\t\t\t\t\t\t0f\n\t\t\t\t\t is particle concentration at the pulp/froth interface, \n\t\t\t\t\t
The total rate of removal due to both flotation and entrainment is given by the sum of the two contributions, i.e.\n\t\t\t\t\t
At the surface of the aerated pulp slurry, a froth phase is formed with water films dividing neighbouring bubbles and solid particles either dispersed in the liquid phase or attached to the surface of froth bubbles (Fig. 1d). Despite the complex dynamics of froth systems (Neethilng & Cilliers, 2002), water and particle drainage induced by gravitational forces can be considered as the two main phenomena governing mass transfers in the froth.
\n\t\t\t\tThe water drainage through the froth, described using the water hold-up in the froth (ε), and the froth retention time (FRT) in the flotation cell were taken as main parameters:
\n\t\t\t\twhere Q\n\t\t\t\t\t\n\t\t\t\t\t\tg\n\t\t\t\t\t and Q\n\t\t\t\t\t\n\t\t\t\t\t\tf\n\t\t\t\t\t are the gas and the froth reject flows, h is the froth thickness and J\n\t\t\t\t\t\n\t\t\t\t\t\tg\n\t\t\t\t\t, J\n\t\t\t\t\t\n\t\t\t\t\t\tf\n\t\t\t\t\t are the gas and water superficial velocities in the froth. In flotation froths, the decrease of water hold-up versus time, is well described by an exponential decay (Gorain et al., 1998; Zheng et al., 2006)
\n\t\t\t\twhere ε\n\t\t\t\t\t\n\t\t\t\t\t\t0\n\t\t\t\t\t is the water volume fraction at the froth/pulp interface and L\n\t\t\t\t\t\n\t\t\t\t\t\td\n\t\t\t\t\t is the water drainage rate constant.
\n\t\t\t\tBy analogy with particle entrainment in the aerated pulp slurry, the rate of the entrainment of particles/solutes dispersed in the froth by the water drainage stream, \n\t\t\t\t\t
where δ = c\n\t\t\t\t\t\n\t\t\t\t\t\td\n\t\t\t\t\t\n\t\t\t\t\t/c\n\t\t\t\t\t\n\t\t\t\t\t\tnf\n\t\t\t\t\t is the particle drainage coefficient, c\n\t\t\t\t\t\n\t\t\t\t\t\tnf\n\t\t\t\t\t and c\n\t\t\t\t\t\n\t\t\t\t\t\td\n\t\t\t\t\t are particle concentrations in the froth and in the water drainage stream, respectively and Q\n\t\t\t\t\t\n\t\t\t\t\t\td\n\t\t\t\t\t is the water drainage flow.
\n\t\t\t\tIn order to close-up Eqs. (1-7), perfect mixing is assumed in the lower part and two counter-current piston flows in the upper part (upward flow for the froth and downward flow for water drainage).
\n\t\t\tMechanisms described by Eqs. (1-7) are extensively used in minerals flotation for the simulation of industrial processes. Nevertheless, due to the intrinsic difference between the composition and the rheological behaviour of minerals and recovered papers slurries, the use of Eqs. (1-7) for the simulation of industrial flotation deinking processes is not straightforward and model validation on a pilot flotation cell appears a necessary step.
\n\t\t\tTo run pilot tests, a 19 cm diameter and 130 cm height flotation column was assembled (Fig. 2). The flotation column has two main regions: a collection region, where the pulp slurry is in contact with gas bubbles, and a ~15 cm height aeration region, where the pulp is re-circulated in tangential Venturi aerators where the gas flow is regulated by using a mass flow meter. The froth generated at the top of the flotation column is removed by using an adjustable reverse funnel connected to a vacuum pump. The pulp level in the cell and the froth retention time before removal can be modified by adjusting the position of the overflow system and of the reverse funnel, respectively.
\n\t\t\t\tThe retention time distribution obtained in the absence and in the presence of cellulose fibres (Fig. 3) shows that, whatever the liquid volume in the cell and the feed flow, the flotation cell can be described as a continuous stirred tank reactor (CSTR).
\n\t\t\t\tFlotation experiments were performed using a conventional fatty acid chemical system in order to test independently the contribution of air flow, pulp feed flow, pulp hydraulic retention time in the cell and froth retention time on the ink removal efficiency and the flotation yield. Experimental conditions are summarized in Table 1.
\n\t\t\t\tSchematic representation of the flotation column used in this study. α) Pulp storage chest. β) Volumetric pump. χ) Adjustable froth removal device. δ) Volumetric pump to supply gas injectors. ε) Venturi-type air injectors. ϕ) Flotation cell outlet with adjustable overflow system. γ) Froth collection vessel. η) Vacuum pump. ι) Mass flow meter.
Mixing conditions in the flotation column. Reactor response to a step type increase in the tracer concentration. (a) Effect of the feed flow and cell volume in presence of water (b) Effect of cellulose fibres. Dotted lines represent the CSTR response.
Cell Volume V (L) | \n\t\t\t\t\t\t\tPulp flow Q in (L/min) | \n\t\t\t\t\t\t\tAir flow Q g (L/min) | \n\t\t\t\t\t\t\tFroth removal thickness h (cm) | \n\t\t\t\t\t\t\tHRT V/Q in (min) | \n\t\t\t\t\t\t\tAir ratio Q g /Q in (%) | \n\t\t\t\t\t\t
14.5 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t3 - 1.5 - 4 - 8 | \n\t\t\t\t\t\t\t7.2 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t
14.5 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t6 | \n\t\t\t\t\t\t\t3 - 1.5 - 4 - 8 | \n\t\t\t\t\t\t\t7.2 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t
14.5 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t8 | \n\t\t\t\t\t\t\t3 - 1.5 - 4 - 8 | \n\t\t\t\t\t\t\t7.2 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t
14.5 | \n\t\t\t\t\t\t\t3.5 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t3 - 1.5 - 4 - 8 | \n\t\t\t\t\t\t\t4.1 | \n\t\t\t\t\t\t\t114 | \n\t\t\t\t\t\t
14.5 | \n\t\t\t\t\t\t\t4.5 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t3 - 1.5 - 4 - 8 | \n\t\t\t\t\t\t\t3.2 | \n\t\t\t\t\t\t\t89 | \n\t\t\t\t\t\t
14.5 | \n\t\t\t\t\t\t\t2.5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t3 - 1.5 - 5 - 8 | \n\t\t\t\t\t\t\t5.8 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t
19.5 | \n\t\t\t\t\t\t\t2.5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t3 - 1.5 - 5 - 8 | \n\t\t\t\t\t\t\t7.8 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t
24 | \n\t\t\t\t\t\t\t2.5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t3 - 1.5 - 5 - 8 | \n\t\t\t\t\t\t\t9.6 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t
Experimental conditions used to run flotation trials. The cross sectional area of the flotation column had a constant value, S = 283 cm2.
Froth flows measured during flotation experiments were fitted by using Eqs. (5, 6) and the water volume fraction in the top froth layer before removal was plotted as a function of the froth retention time in the cell. Fig. 4 shows that the water fraction in the froth had an exponential decay with increasing retention time and that Eq. (6) fitted with good accuracy experimental data. The absence of froth recovery when the retention time was higher than 30 s indicates that, when the water fraction was lower than ~0.02, gas bubbles collapsed in the reverse funnel and froth recovery was no longer possible. The decrease of froth processability in the vacuum system was attributed to the destabilization of froth liquid film and to the typical increase in froth viscosity (Shi & Zheng, 2003) when increasing FRT.
\n\t\t\t\t\tWater volume fraction in the froth removed by the vacuum device (all tested conditions) plotted as a function of the froth retention time in the cell.
The frothing behaviour of the pulp slurry was therefore described by Eq. 6, with ε\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tο\n\t\t\t\t\t\t = 0.15 and L\n\t\t\t\t\t\t\n\t\t\t\t\t\t\td\n\t\t\t\t\t\t = 4.44 min-1.
\n\t\t\t\tThe variation of the ink concentration during the flotation transitory and steady states and with froth removal at different heights, were obtained by mass balance from Eqs. (2-7) and the models of reactors. In order to limit the number of free variables in the equation system, the entrainment coefficient of ink particles was assumed similar to that of silica particles with same size (Machaar & Dobby, 1992), namely ~0.2. As expected from Eq. (2), the increase in the gas flow gave a corresponding increase in the ink flotation rate constant which fairly deviated from a linear correlation, i.e. k\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tink\n\t\t\t\t\t\t\n\t\t\t\t\t\t= 0.15 Q\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tg\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t0.73\n\t\t\t\t\t\t (k in min-1, Q\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tg\n\t\t\t\t\t\t in L/min). The ink drainage coefficient given by model equations was δ\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tink\n\t\t\t\t\t\t = 0.30, thus reflecting the limited drainage of ink particles through the froth and the low variation of ink concentration in the pulp when the froth removal height was increased (Fig. 5a). Flotation rate constants and ink drainage coefficient obtained by fitting experimental data were used to predict the contribution of cell volume and froth removal height on the residual ink concentration in the pulp. Calculated ink removal efficiencies matched with experimental values (Fig. 5b).
\n\t\t\t\tThis approach was repeated for fibres, fines and ashes. Since cellulose fibres are hydrophilic particles with large-un-floatable size (~1.5x0.1 mm), only entrainment and drainage were assumed to govern their transport during flotation.
\n\t\t\t\t\tFitting of experimental data gave an entrainment coefficient extremely high for this class of large particles: ϕ\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tfibres\n\t\t\t\t\t\t = 0.30, and a drainage coefficient of δ\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tfibres\n\t\t\t\t\t\t = 0.80. The relevant contribution of entrainment was associated with the natural tendency of cellulose fibres to generate large flocks with small gas bubbles trapped in.
\n\t\t\t\tFines and ashes displayed an intermediate behaviour between ink and fibres. Fitting of experimental data gave low flotation rate constants proportional to the gas flow, k\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tfines\n\t\t\t\t\t\t\n\t\t\t\t\t\t= 0.018 Q\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tg\n\t\t\t\t\t\t for fines and k\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tash\n\t\t\t\t\t\t\n\t\t\t\t\t\t= 0.021 Q\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tg\n\t\t\t\t\t\t for ash (k in min-1, Q\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tg\n\t\t\t\t\t\t in L/min).
\n\t\t\t\t\tVariation of ink concentration plotted as a function of the flotation time and of the froth removal height. (a) Influence of gas flow on residual ink concentration, pulp flow Q\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tin\n\t\t\t\t\t\t\t\t = 2 L/min, cell volume V = 14.5 L. Dotted lines represent experimental data fitting with model equations. (b) Influence of cell volume on residual ink concentration, pulp flow Q\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tin\n\t\t\t\t\t\t\t\t = 2.5 L/min, gas flow Q\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tg\n\t\t\t\t\t\t\t\t = 5 L/min. Dotted lines represent trends obtained from model calculations.
Like ink particles, entrainment coefficients for fines and ash were assumed similar to that of silica particles with similar size, namely ϕ\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tfines\n\t\t\t\t\t\t = 0.25 and ϕ\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tash\n\t\t\t\t\t\t = 0.45 and, as expected for poorly floatable particles, drainage coefficients had high values, namely δ\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tfines\n\t\t\t\t\t\t = 0.85 and δ\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tash\n\t\t\t\t\t\t = 0.8.
\n\t\t\t\t\tPresent results show that model equations derived from the minerals flotation field allowed modelling the flotation deinking of recovered papers when using a conventional-fatty acid chemical system. The contribution of pulp flow, cell volume, viz. HRT, and froth removal height on ink removal and yield was predicted with good accuracy. However, chemical variables (such as the presence of surfactants), which can strongly affect the flotation deinking process, were not accounted in the model. As a step in this direction, the contribution of a model non-ionic surfactant on particle and water transport was investigated.
\n\t\t\t\tRecovered papers may release in process waters a wide variety of dissolved and colloidal substances (Brun et al., 2003; Pirttinen & Stenius, 1998) which limit the use of conventional analytical techniques for the dosage of non-ionic surfactants. In order to avoid using over complex purification and analysis procedures, the surfactant concentration in the pulp slurry can be estimated using an indirect method based on the measurement of surface tension by maximum bubble pressure (Pugh, 2001; Comley et al., 2002). Thereafter, in the presence of a reference surfactant (in this study, an alkyl phenol ethoxylate, NP 20EO, added at the inlet of the flotation cell) it becomes possible to quantify the effect of surfactant concentration on particle, water and surfactant molecules transport during the flotation process and to establish direct cross correlations between surfactant concentration and transport coefficients.
\n\t\t\tThe removal of surfactant molecules from the pulp slurry during flotation is strongly affected by surfactant concentration and by the froth removal thickness (Fig. 6a). Indeed, the increase in NP 20EO concentration boosted surfactant removal and decreased the impact of the froth removal thickness on the residual surfactant in the floated pulp. Surfactant removal rates and drainage coefficients (Fig. 6b) obtained by fitting experimental data with Eqs. (1-7), show that the removal rate constant increased with the equivalent concentration, while the drainage coefficient decreased. This trend was interpreted as reflecting the contribution of the initial surfactant concentration on bubble size and on froth stability: a decrease in bubble coalescence/burst in the aerated pulp and in the froth leads to an increase in the surfactant removal rate and a decrease in the drainage rate, respectively.
\n\t\t\t\tSurfactant removal from the pulp slurry during flotation. (a) Decrease in the surfactant equivalent concentration in the pulp slurry during flotation plotted as a function of the froth removal thickness and of NP 20EO concentration (dotted lines represent data fitting with Eqs. (1-7). (b) Surfactant removal rate constant and drainage coefficient obtained from the interpolation of experimental data with model equations.
\n\t\t\t\t\tFig. 7 shows that the rise in the surfactant flotation rate constant (Fig. 6b) can be ascribed to an increase in the gas hold-up with the surfactant concentration. This trend is due to the bubble stabilization induced by the adsorption of surfactant molecules on the bubble surface and the ensuing stabilization of liquid films formed between colliding bubbles (Danov et al., 1999; Valkovska et al., 2000). The water hold-up in the froth calculated from water recovery data and Eqs. (5, 6) shows an exponential decay (Fig. 8a) and the water hold-up at the pulp/froth interface, ε0, increases with the surfactant concentration, whereas the water drainage coefficient, L\n\t\t\t\t\t\n\t\t\t\t\t\td\n\t\t\t\t\t, decreases (Fig. 8b). This trend reflects the NP 20EO contribution in i) decreasing bubble size in the aerated pulp, ii) stabilizing liquid films between froth bubbles and iii) preventing bubble burst in the froth.
\n\t\t\t\tEffect of the model non-ionic surfactant (NP 20EO) on gas hold-up. Air flow 2 L/min.
Frothing behaviour of the pulp slurry in the flotation cell. (a) Water hold-up in the froth plotted as a function of the froth retention time and of the added non-ionic surfactant concentration. Dotted lines represent data fitting with Eq. 7. (b) Water hold-up at the froth/pulp slurry interface and water drainage rate constant.
In the absence of surfactant, ink particles are efficiently removed during flotation (Fig. 9a). However, ink removal is strongly affected by the low frothing behaviour of the pulp slurry
\n\t\t\t\tEffect of surfactant concentration on ink removal. (a) Variation of ink concentration in the pulp after flotation. (b) Ink flotation rate constant and drainage coefficient.
(Fig. 8) and the increase in the froth removal thickness is responsible for a strong increase in the residual ink concentration in the floated pulp. The addition of surfactant (NP 20EO) in the pulp slurry reduces the ink flotation rate constant (Fig. 9b) and ink removal sensitivity to the FRT. For the highest surfactant concentration, 16 µM, the ink concentration is not affected by the froth removal thickness thus reflecting the stabilization of froth bubbles. The decrease of the ink flotation rate constant for increasing NP 20EO concentration is due to non-ionic surfactant adsorption at both the bubble/ and ink/water interface which induces a decrease in both bubble surface tension and ink/water interfacial energy (Epple et al, 1994). In the froth phase, the non-ionic surfactant improves bubble stability and water hold-up reducing ink particles detachment due to bubble burst and their drainage from the froth into the aerated pulp slurry (Fig. 9b).
\n\t\t\tThe transfer of hydrophilic cellulose fibres in the froth decreases when increasing the surfactant concentration (Fig. 10a). As obtained for surfactant and ink, the froth stabilization due to NP 20EO addition progressively suppresses the contribution of the froth removal thickness on fibre concentration and at the highest surfactant dosage the froth has a constant fibre concentration. The decrease in the fibre entrainment coefficient shown in Fig. 10b is associated with the suppression of fibre flocculation by calcium soap and with a decrease of bubble entrapment in fibre flocs and of the convective motion of fibre/bubble flocs towards the froth.
\n\t\t\t\tThe constant fibre drainage coefficient (Fig. 10b) indicates that fibre drainage is mainly governed by the intensity of the water drainage flow.Fillers and fine elements have a behaviour similar to that of ink particles, i.e. the increase in surfactant dosage depressed fillers/fines flotation and drainage.
\n\t\t\tWithin the current industrial context (environmental and safety constraints, globalization of the economy, need to shorten the “time to market” of products), computer science is more
\n\t\t\t\tFibre removal in the froth. (a) Influence of froth removal height and surfactant concentration on the fibre concentration in the froth during flotation. (b) Fibre entrainment and drainage coefficients plotted as a function of surfactant concentration.
and more often used to design, analyse and optimize industrial processes. This specific area, called “Computer Aided Process Engineering” (CAPE), knows a big success in industries such as oil and gas, chemical and pharmaceutical. Process simulation software are used by chemical engineers in order to provide them with material and energy balances of the process, physical properties of the streams and elements required for equipment design, such as heat duty of exchangers or columns hydraulics. Moreover, process simulation software can also be used for cost estimates (capital expenditure, CAPEX and operational expense, OPEX), to evaluate environmental or security impact, to optimize flowsheets or operating conditions, for debottlenecking of an existing plant, for operator training… At a conceptual level, two kinds of process simulation software exist, the “module oriented” and the “equation oriented” approaches. Software based on this last approach are mainly dedicated to process dynamic simulation (Aspen Dynamics, gPROMS) and they can be compared to solvers for systems of algebraic and differential equations, directly written by users. The “module oriented” approach is adopted by most of the commercial process simulation software (Aspen Plus, Chemcad, Pro/II, ProSimPlus) and correspond to the natural conception of a process, which is constituted by unit operations dedicated to a specific task (heat transfer, reaction, separation). A general view of the structure of these software is provided on Fig. 11.
\n\t\t\t\tThese software provide unit operation library, including most common units such as chemical reactors, heat exchangers, distillation or absorption columns, pumps, turbines, compressors and, sometimes, some more specific equipments such as brazed plate fin heat exchangers, belt filters.
\n\t\t\t\tUser supplies operating and sizing parameters of each unit operations (also called modules) and linked them with streams, which represent material, energy or information flux circulating between the equipments of the real process. Other important parts of a process simulation software are the databases and the physical properties server, on which rely unit operations models to give consistent results, and solvers, which are numerical tools required to access convergence of the full flow sheet.
\n\t\t\t\tStructure of a process simulation software.
Pure component databases include fixed-value properties (molar weight, critical point characteristics, normal boiling point…) and correlation coefficients for temperature-dependent properties (liquid and vapour heat capacity, vapour pressure, liquid and vapour viscosity…). The main reference for thermophysical properties of pure components is DIPPR (Design Institute for Physical Property Data, http://dippr.byu.edu/) which includes, in its 2008 version, 49 thermophysical properties (34 constant properties and 15 temperature-dependent properties) for 1973 compounds. This number of compounds is to compare with the number of chemical substances referenced by the Chemical Abstracts (http://www.cas.org/), which was greater than 33 millions in 2008. The difference between these two figures shows the importance to have models to predict pure physical properties. These models can be based on chemical structure or intrinsic properties of the molecule (molar weight, normal boiling point, critical temperature…), but they are then mainly reliable for a given chemical family. The use of molecular simulation becomes more and more frequent to compute missing data.
\n\t\t\t\tModelling of a physical system rests on the knowledge of pure component and binary properties. Thus, binary interaction parameters between compounds are generally required by thermodynamic models to obtain the mixture behaviour. These parameters are obtained by fitting experimental data to thermodynamics model, the main sources of these data being the DECHEMA (http://www.dechema.de/en/start_en.html) and the NIST (http://www.nist.gov/index.html). Two kinds of methods exist in order to compute fluid phase equilibria. The first way to solve the problem consists in applying a different model to each phase: fugacities in liquid phase are calculated from a reference state which is characterized by the pure component in the same conditions of physical state, temperature and pressure, ideal laws being corrected by using a Gibbs free energy model or an activity coefficients model (NRTL, UNIQUAC, UNIFAC…). Fugacities in vapor phase are calculated by using an Equation of State (ideal gases, SRK, PR…). These methods are used in order to represent the heterogeneity of the system and are classically called heterogeneous methods. Their use covers the low pressure field and it should be noted that they do not satisfy the continuity in the critical zone between vapour phase and liquid phase. The second way to solve the fluid phase equilibria calculation consists in homogeneous methods, which apply the same model, usually an Equation of State, to the two phases, allowing thus to ensure continuity at the critical point. Equations of State with their classical mixing rules (SRK, PR, LKP…) are included in this second category. However, the field of application of these model is limited to non polar or few polar systems. By integrating Gibbs free energy models in the mixing rules for Cubic Equations of State, some authors succeeded in merging both approaches. These models are often called combined approach. It has to be noted that some specific models have been developed for some particular fields of application, like electrolyte solutions, strong acids…
\n\t\t\t\tUser interface helps users to transcribe its problem in the process simulation software language. Providers now propose graphical tools which allows user to build his flowsheet by “drag-and-drop”. Numerous tools are also available to ensure fast access to information and convenient learning: information layers, colour management, right click, double click...
\n\t\t\t\tNew communication standard, called CAPE-OPEN (http://www.colan.org/), is developed to permit the interoperability and integration of software components in process simulation software. Thanks to this standard, a commercial process simulation software can now use a unit operation or a thermodynamic model developed by an expert. With this approach, a process simulation software becomes a blend of software components focused on the real needs expressed by the user.
\n\t\t\t\tWithin this context, correlations shown in Figs. 6-10 and Eqs. (1-7) were coded in FORTRAN in order to obtain a module for the flotation deinking unit operation. The effect of non-ionic surfactant concentration and distribution on ink removal selectivity was then simulated for the conventional multistage flotation system shown in Fig. 12.
\n\t\t\t\tScheme of the conventional multistage deinking line simulated in this study (a) and of relevant pulp stream, flotation process and particle transport variables used to simulate each flotation unit (b).
In the simulated system (Fig. 12), a pulp stream of 32000 L/min is processed in a first stage composed by six flotation cells in series. The outlet pulp of the sixth cell is considered as the outlet of the entire system, whereas, froths generated in the first stage are mixed and further processed in a second stage made of a series of two flotation cells. The froth of the second stage is the reject of the entire system. In order to insure a froth flow sufficient to feed the second stage and to avoid ink drainage, the froth is removed from the first stage with no retention and 75% of the pulp stream processed in the second stage is circulated at the inlet of the second stage. The remaining 25% is cascaded back at the inlet of the first stage. The froth retention time in the second stage ranges between 10 s and 4 min to stabilize the water reject to 5% (i.e. 1600 L/min). Main characteristics of the flotation line used to run simulations are given in Table 2.
\n\t\t\t\tOverall mass balance calculations involving multi stage systems were resolved using a process simulation software (ProSimPlus). Transport coefficients in each flotation cell composing the multistage system were calculated from the surfactant concentration at the inlet of each unit.
\n\t\t\t\tVolume (L) | \n\t\t\t\t\t\t\tFeed flow (L/min) | \n\t\t\t\t\t\t\tAeration rate per cell (%) | \n\t\t\t\t\t\t\tCross section (m 2 ) | \n\t\t\t\t\t\t\tFeed consistency (g/L) | \n\t\t\t\t\t\t\tLine capacity (T/day) | \n\t\t\t\t\t\t
20000 | \n\t\t\t\t\t\t\t40000 | \n\t\t\t\t\t\t\t50 | \n\t\t\t\t\t\t\t12 | \n\t\t\t\t\t\t\t10 | \n\t\t\t\t\t\t\t580 | \n\t\t\t\t\t\t
Characteristics of each flotation cell in the simulated de-inking line.
As shown in Fig. 13a, for a constant surfactant concentration in the pulp feed flow, the surfactant load progressively decreases when the pulp is processed all along the first and the second stage. However, within the range of simulated conditions, the surfactant concentration in the second stage is ~1.5 times higher than in the first stage indicating the low capacity of the first line to concentrate surfactants in the froth phase. Surfactant removal efficiencies illustrated in Fig. 13b show that flotation units in the first stage have similar yield which asymptotically increases from ~6% to ~15%. This trend can be associated to the influence of surfactant concentration on the flotation rate and on pulp frothing. With a low
\n\t\t\t\tEffect of surfactant concentration in the pulp feed flow on surfactant distribution and removal. Surfactant concentration (a) and removal (b) in each flotation unit composing the multistage system.
surfactant concentration in the feed flow, surfactant removal in flotation cells of the second stage is lower than in the first stage. Similar yields are obtained with extremely high surfactant concentrations, i.e. >15 µmol/L. The different froth retention time in the first and in the second stage is at the origin of this trend. Indeed, in the first stage the froth is removed with no retention and surfactant molecules are subjected only to flotation and entrainment. Whereas, in the second stage the froth retention time ranges between 10 s and 4 min in order to promote water drainage and to stabilise the froth flow at 1600 L/min.
\n\t\t\tFor all simulated concentrations, mixing the feed pulp with the pulp flow cascaded back from the second stage gives an increase in the ink concentration at the inlet of the first stage (Fig. 14a). In general, the ink concentration progressively decreases all along the first and the second stage, however, the ink distribution in the deinking line is strongly affected by the surfactant concentration. Fig. 14a shows that, at high surfactant load, the ink concentration along the deinking line progressively converges to the ink concentration in the feed flow. In this condition, the collision and the attachment of ink particles to air bubbles is disfavoured, flotation is depressed and ink removal is due to the hydraulic partitioning of the pulp flow into the reject and the floated pulp streams.
\n\t\t\t\tInk removal versus surfactant concentration plots illustrated in Fig. 14b show that in all flotation cells of the first stage ink removal monotonically decreases, while in the second stage a peak in ink removal appears at 3 µmol/L. For all simulated conditions, ink removal in the second stage is lower than in the first stage. This behaviour is associated to different froth retention time and surfactant concentration in the two stages (Fig. 13a).
\n\t\t\t\tThe peak in ink removal in the second stage reflected the progressive depression of ink upward transfer from the pulp to the froth by flotation and of ink drop back from the froth to the pulp by drainage. At low surfactant concentration, < 3 µmol/L, ink removal is governed by particle transport in the froth. The froth is unstable and bubble burst and water drainage induce ink to drop back into the pulp with an ensuing decrease in ink removal. At
\n\t\t\t\tInk distribution and removal in the flotation line at increasing surfactant concentration in the pulp feed flow. (a) Ink concentration, (b) ink removal.
high surfactant concentration, > 3 µmol/L, froth bubbles are progressively stabilized and ink drainage is reduced. The presence of a maximum in the ink removal vs. surfactant concentration curve corresponds to the best compromise between froth stabilization and ink floatability depression.
\n\t\t\tSimulation results show that both the variation of surfactant load in the pulp feed flow and its distribution in the two flotation stages affect the yield of the deinking line. Except for a peak in ink removal in the second stage at 3 µmol/L, Fig. 15a shows that the ink removal efficiency of the entire deinking line progressively decreases when increasing surfactant concentration.
\n\t\t\t\tTotal ink and surfactant removal (a) and fibres, fines, ash loss (b) plotted as a function of surfactant concentration in the pulp feed flow.
Similar trends are obtained for fibre, fines and ash (Fig. 15b) and only surfactant removal increases when increasing the surfactant load in the pulp feed flow. Fig. 15 shows that with a surfactant load in the pulp flow comparable with the amount released by a standard pulp stock composition of 50% old newspaper and 50% old magazines, i.e. ~4 µmol/L, ink is efficiently removed (~70%), fibre, fines and ash loss have realistic values for a deinking line, i.e. 5, 19 and 65% respectively, and surfactant removal does not exceed 17%. The high sensitivity of the process yield to the surfactant load in the pulp stream and the low surfactant removal efficiency lead to assume that a conventional deinking line weakly attenuates fluctuations in the amount of surface active agents released by recovered papers with a direct effect on the stability of the process yield and on surfactant accumulation in process waters.
\n\t\t\t\n\t\t\t\t\tFig. 16a shows that the residual ink content obtained by simulation with a surfactant load of 4 µmol/L is in good agreement with data collected during mill trial. In the first stage, residual ink obtained from simulation displays higher values than experimental data. This mismatch can be ascribed to the different ink load in the pulp feed flow.
\n\t\t\t\tThe residual ink content in the floated pulp (ERIC) is lower than that of the model pulp used in laboratory experiments and to run simulations (i.e. 830 ppm). When using the industrial pulp composition to run simulations this discrepancy is strongly attenuated.
\n\t\t\t\tThe variation of the surfactant concentration in the deinking mill is in good agreement with simulation results. Fig. 16b shows that surfactant concentration in the first stage is nearly constant and the decrease predicted by process simulation can not be observed since it is within the experimental error. As predicted by the simulation, the surfactant concentration in the second stage is 1.4-1.5 times higher than in the first stage and it progressively decreases all along the line. Ink and surfactant removal determined for the industrial deinking line in the first and second stages matches with quite good accuracy with the yield predicted by process simulation (Fig. 17) thus indicating that particle and water transport mechanisms used for the simulation of the industrial line describe with reasonable accuracy the deinking process.
\n\t\t\t\tComparison of residual ink concentration (a) and surfactant relative concentration (b) obtained from process simulation with mill data.
Comparison of ink (a) and surfactant removal (b) obtained at the industrial scale with simulation results.
In order to clarify the contribution of multistage deinking lines design on ink removal and process yield, six bank configurations of increasing complexity are modelled. As summarized in Table 3, flotation banks are assembled using flotation cells with two different aspect ratios, 0.7 for the tank cell, 2 for the column cell, and with a constant pulp capacity of 20 m3. With both cell geometries, pulp aeration is assumed to take place in Venturi aerators with an aeration rate Q\n\t\t\t\t\t\n\t\t\t\t\t\tg\n\t\t\t\t\t/Q\n\t\t\t\t\t\n\t\t\t\t\t\tpulp\n\t\t\t\t\t = 0.5 and a pressure drop of 1.2 bar (Kemper, 1999). To run simulations under realistic conditions, the superficial gas velocity in a single column cell is set at 2.4 cm/s, which corresponds to an air flow rate of 10 m3/min or half that in the tank cell. Similarly, the pulp flow processed in flotation columns is limited to a maximal value of 10 m3/min. Fig. 18a-d illustrates the four single-stage lines simulated in this study. The first case (Fig. 18a), consists in a simple series of flotation tanks, with common launder collecting flotation froths from each cell to produce the line reject. The number of tanks is varied from 6 to 9. In order to limit fibre loss, rejects of flotation cells at the end of the line are cascaded back at the line inlet (Fig. 18b) while the froth rejected from the first few cells is rejected. Using this configuration, the simulation is carried out with the number of tanks in the line and cascaded reject flows being used as main variables. In the third configuration (Fig. 18c), the pulp retention time at the head of the line is doubled by placing two tanks in parallel followed by a series of 7 tanks whose rejects are returned at the line inlet. The last single-stage configuration (Fig. 18d) consists in a stack of 4 to 6 flotation columns in parallel, followed by a series of 3 to 5 tanks whose rejects are sent back to the line inlet. The aim of this configuration is to increase ink concentration and pulp retention time at the head of the line and to assess the potential of column flotation for ink removal efficiency.
\n\t\t\t\tAs depicted in Fig. 18, two- and three-stage deinking lines were also simulated. As previously mentioned, the two-stage line shown in Fig. 18e is the most widely used one in flotation deinking. In this classical configuration, reject of the first stage, are generated in 5 to 9 primary cells in series. To recover valuable fibres in these combined reject stream, rejects of the primary line are processed in a second stage with 1 to 4 tanks. The number of flotation tanks in the first and in the second stage is here used as main variable to optimize the line design. The three-stage line shown in Fig. 18f is made of a first stage with 7 to 8 flotation tanks, a second stage with 2 tanks and a third stage with 1 tank. The pulp processed in the third stage is partitioned between the inlets of the third and of the second stage.
\n\t\t\t\tRelevant characteristics of flotation units used to assembly the flotation lines simulated in this study. + Estimated assuming a bubble slip velocity relative to the pulp downstream flow of ~7 cm/s.
Flotation lines simulated in this study. (a) Simple line made of a series of n flotation cells. (b) Line with n flotation cells with the reject of the last n-m cells cascaded back at the line inlet. (c) Line composed by n flotation cells with the first two cells in parallel and the remaining cells in series. The reject of the last n-2 cells is cascaded back at the inlet of the line. (d) Line composed by a stack of m flotation columns in parallel and a series of n cells. The reject of flotation cells is cascaded back at the inlet of the line. (e) Conventional two-stage line with n cells in the primary stage and m cells in the secondary stage. (f) Three-stage line with n = 8, m = 2.
The pulp processed in the second stage is partitioned between the inlets of the second stage itself and of the first stage. In order to limit the number of variables, all simulations are run with zero froth retention time. Under this condition, ink removal and fibre/fillers loss are maximized because particle and water drainage phenomena from the froth to the pulp are suppressed but this is obtained at the expense of ink removal selectivity. Simulation results are therefore representative of deinking lines operated at their maximal ink removal capacity.
\n\t\t\tFlotation lines assembled here for simulation purposes are characterized by a fixed (tank cells) and an adjustable (column cells) feed flow. Since the introduction of recirculation loops modifies the processing capacity and the pulp retention time in the whole line, predicting particle removal efficiencies is not sufficient to establish a performance scale between different configurations. Consequently, the specific energy consumption, which is given by the equation
\n\t\t\t\twhere Q\n\t\t\t\t\t\n\t\t\t\t\t\tg\n\t\t\t\t\t is the gas flow injected in each flotation cell (n) in the multistage system, P\n\t\t\t\t\t\n\t\t\t\t\t\tinj\n\t\t\t\t\t the pressure feed of each static aerator (1.2 bar), ρ the aeration rate Q\n\t\t\t\t\t\n\t\t\t\t\t\tg\n\t\t\t\t\t\n\t\t\t\t\t/Q\n\t\t\t\t\t\n\t\t\t\t\t\tpulp\n\t\t\t\t\t (0.5 in the simulated conditions), Q\n\t\t\t\t\t\n\t\t\t\t\t\tout\n\t\t\t\t\t and c\n\t\t\t\t\t\n\t\t\t\t\t\tout\n\t\t\t\t\t are the pulp volumetric flow and consistency at the outlet of the deinking line, the ink removal efficiency and the ink removal selectivity (Z factor) (Zhu et al., 2005), have to be taken into account to establish a correlation between process efficiency and line design.
\n\t\t\t\t\n\t\t\t\t\tFig. 19a illustrates that when the cascade ratio is raised in single-stage lines, the deinking selectivity increases by 4-5 times, whereas the specific energy consumption slightly decreases. Reduced energy is caused by a net increase in pulp production capacity. However, these gains are generally associated with a decrease in ink removal. Hence, the reference target of 80 % ink removal with selectivity factor Z = 8 could only be obtained with a line made of 9 tanks with a cascade ratio of 0.6 and a specific energy consumption of 60 kWh/t. Because target ink removal and selectivity can be achieved only by increasing energy consumption, this configuration does not represent a real gain in terms of process performance. The addition of a high ink removal efficiency stage comprising a stack of flotation columns in parallel at the line head, Fig. 19b, reduces specific energy consumption by 25-50 %. Nevertheless, the efficient removal of floatable mineral fillers and the absence of hydrophilic particle drainage in the froth limits the selectivity factor to ~7.5. According to experimental studies (Robertson et al. 1998; Zhu & Tan, 2005), the increase of the froth retention time and the implementation of a froth washing stage would improve the selectivity factor with a minimum loss in ink removal. Under these conditions, a flotation columns stack equipped with optimized froth retention/washing systems would markedly decrease specific energy consumption. Similarly to the results obtained for single-stage lines, Fig. 20a shows that improved ink removal selectivity in two-stage lines is coupled with a decrease ink removal.
\n\t\t\t\tInk removal efficiency and selectivity obtained for tested configurations plotted as a function of the specific energy consumption. (a) Flotation line composed by 6 to 9 flotation cells and with the reject of the last n-m cells cascaded back at the line inlet (Fig. 18a-b). (b) Flotation line composed by a stack of flotation cells or columns in parallel followed by a series of flotation cells (Fig. 18c-d).
Ink removal efficiency and selectivity obtained for tested configurations plotted as a function of the specific energy consumption. (a) Deinking line composed by a 1ry and a 2ry stage with different number of flotation cells in the two stages (Fig. 18e). The legend in the pictures indicates the number of cells in the 1ry stage. b) Line of 3 stages (Fig. 18f).
The selectivity factor appears to be directly correlated to the number of flotation tanks in the secondary line as it progressively decreases from ~17.5 to 5 when increasing the number of tanks in the second stage. Selectivity drops when the reject flow increases which, for two- and single-stage lines, is induced by the increase of the number of tanks in the second stage and the decrease of the cascade ratio, respectively.
\n\t\t\t\tIn turn, ink removal efficiency is found here to be governed by the number of cells in the first stage. Fig. 20a shows that, with a constant number of tanks in the second stage, ink removal increases by 10 % for each additional cell in the first stage, while selectivity slightly increases. Seven tanks in the first stage and two tanks in the second stage are needed to reach the target of 80 % ink removal and a selectivity factor of 9. With this configuration, the specific energy consumption of the two-stage line (52 kWh/t) is lower than the energy required by a single stage line with the same deinking efficiency/selectivity (60 kWh/t). Overall, the best energetic efficiency is given by the single line with a stack of six flotation columns at the line head (Fig. 19b).
\n\t\t\t\tIf we consider the two-stage line with ink removal and selectivity targets as reference system, the addition of a third stage with a single tank boosts up selectivity, slightly decreases ink removal from 81 to 78% and does not affect specific energy consumption (Fig. 20b). The selectivity index of the three-stage line can be further increased from 21.5 to 41 by setting at 16 s froth residence time in the third stage cell. However, the selectivity gain is coupled to a decrease in ink removal from 78 to 72 % and the need for an additional tank in the first stage to attain the ink removal target of 80 %. With this last configuration of 8 tanks in the first stage, 2 tanks in the second stage and 1 tank in the third stage, 80 % ink removal is attained along the highest selectivity factor of all tested configurations. However, the gain in separation efficiency results in a sizeable increase in the specific energy consumption. As for the other tested configurations, the effective benefit provided by this configuration should be thoroughly evaluated in the light of recovered papers, rejects disposal and energy costs.
\n\t\t\tThis chapter summarizes the four steps that have been necessary to develop and validate a process simulation module that can be used for the management of multistage flotation deinking lines, namely, i) the identification of mass transfer equations, ii) their validation on a laboratory-scale flotation cell, iii) the correlation of mass transfer coefficients with the addition of chemical additives and iv) the simulation of industrial flotation deinking banks.
\n\t\t\tDue to the variability of raw materials and the complexity of physical laws governing flotation phenomena in fibre slurries, general mass transport equations were derived from minerals flotation and validated on a laboratory flotation column when processing a recovered papers pulp slurry in the presence of increasing concentration of a model non-ionic surfactant.
\n\t\t\tCross correlations between particle transport coefficients and surfactant concentration obtained from laboratory tests were used to simulate an industrial two-stage flotation deinking line and a good agreement between simulation and mill data was obtained thus validating the use of the present approach for process simulation.
\n\t\t\tThereafter, the contribution of flotation deinking banks design on ink removal efficiency, selectivity and specific energy consumption was simulated in order to establish direct correlations between the line design and its performance. The simulation of a progressive increase of the line complexity from a one to a three-stage configuration and the use of tank/column cells showed that:
\n\t\t\tIn single-stage banks, ink removal selectivity and specific energy consumption can be improved by increasing the cascade ratio (i.e. the ratio between the number of cascaded cells and the total number of cells in the line) with a minimum decrease in the ink removal efficiency. Above a cascade ratio of 0.6, the ink removal efficiency drops.
The addition of a stack of flotation columns in the head of a single stage line gives an increase in ink removal selectivity and a decrease in specific energy consumption.
In two-stage banks, the ink removal efficiency is mainly affected by the number of flotation tanks in the first stage, whereas, the number of cells in the second stage affects the fibre removal, which linearly increases with the number of cells.
The addition of a third stage allows increasing ink removal selectivity with a negligible effect on the ink removal efficiency and on the specific energy consumption.
Overall, the best deinking performance is obtained with a stack of flotation columns at the line head and the three-stage bankg.
This paper is the outline of a research project conducted over the last four years. Authors wish to thank Mr. J. Allix, Dr. B. Carré, Dr. G. Dorris, Dr. F. Julien Saint Amand, Mr. X. Rousset and Dr. E. Zeno for their valuable contribution.
\n\t\tBone is living tissue that is the hardest among other connective tissues in the body, consists of 50% water. The solid part remainder consisting of various minerals, especially 76% of calcium salt and 33% of cellular material. Bone has vascular tissue and cellular activity products, especially during growth which is very dependent on the blood supply as basic source and hormones that greatly regulate this growth process. Bone-forming cells, osteoblasts, osteoclast play an important role in determining bone growth, thickness of the cortical layer and structural arrangement of the lamellae.
Bone continues to change its internal structure to reach the functional needs and these changes occur through the activity of osteoclasts and osteoblasts. The bone seen from its development can be divided into two processes: first is the intramembranous ossification in which bones form directly in the form of primitive mesenchymal connective tissue, such as the mandible, maxilla and skull bones. Second is the endochondral ossification in which bone tissue replaces a preexisting hyaline cartilage, for example during skull base formation. The same formative cells form two types of bone formation and the final structure is not much different.
Bone growth depends on genetic and environmental factors, including hormonal effects, diet and mechanical factors. The growth rate is not always the same in all parts, for example, faster in the proximal end than the distal humerus because the internal pattern of the spongiosum depends on the direction of bone pressure. The direction of bone formation in the epiphysis plane is determined by the direction and distribution of the pressure line. Increased thickness or width of the bone is caused by deposition of new bone in the form of circumferential lamellae under the periosteum. If bone growth continues, the lamella will be embedded behind the new bone surface and be replaced by the haversian canal system.
Bone is a tissue in which the extracellular matrix has been hardened to accommodate a supporting function. The fundamental components of bone, like all connective tissues, are cells and matrix. Although bone cells compose a small amount of the bone volume, they are crucial to the function of bones. Four types of cells are found within bone tissue: osteoblasts, osteocytes, osteogenic cells, and osteoclasts. They each unique functions and are derived from two different cell lines (Figure 1 and Table 1) [1, 2, 3, 4, 5, 6, 7].
Osteoblast synthesizes the bone matrix and are responsible for its mineralization. They are derived from osteoprogenitor cells, a mesenchymal stem cell line.
Osteocytes are inactive osteoblasts that have become trapped within the bone they have formed.
Osteoclasts break down bone matrix through phagocytosis. Predictably, they ruffled border, and the space between the osteoblast and the bone is known as Howship’s lacuna.
Development of bone precursor cells. Bone precursor cells are divided into developmental stages, which are 1. mesenchymal stem cell, 2. pre-osteoblast, 3. osteoblast, and 4. mature osteocytes, and 5. osteoclast.
The balance between osteoblast and osteoclast activity governs bone turnover and ensures that bone is neither overproduced nor overdegraded. These cells build up and break down bone matrix, which is composed of:
Osteoid, which is the unmineralized matrix composed of type I collagen and gylcosaminoglycans (GAGs).
Calcium hydroxyapatite, a calcium salt crystal that give bone its strength and rigidity.
Bone is divided into two types that are different structurally and functionally. Most bones of the body consist of both types of bone tissue (Figure 2) [1, 2, 8, 9]:
Compact bone, or cortical bone, mainly serves a mechanical function. This is the area of bone to which ligaments and tendons attach. It is thick and dense.
Trabecular bone, also known as cancellous bone or spongy bone, mainly serves a metabolic function. This type of bone is located between layers of compact bone and is thin porous. Location within the trabeculae is the bone marrow.
Structure of a long bone.
Long bones are composed of both cortical and cancellous bone tissue. They consist of several areas (Figure 3) [3, 4]:
The epiphysis is located at the end of the long bone and is the parts of the bone that participate in joint surfaces.
The diaphysis is the shaft of the bone and has walls of cortical bone and an underlying network of trabecular bone.
The epiphyseal growth plate lies at the interface between the shaft and the epiphysis and is the region in which cartilage proliferates to cause the elongation of the bone.
The metaphysis is the area in which the shaft of the bone joins the epiphyseal growth plate.
Bone macrostructure. (a) Growing long bone showing epiphyses, epiphyseal plates, metaphysis and diaphysis. (b) Mature long bone showing epiphyseal lines.
Different areas of the bone are covered by different tissue [4]:
The epiphysis is lined by a layer of articular cartilage, a specialized form of hyaline cartilage, which serves as protection against friction in the joints.
The outside of the diaphysis is lined by periosteum, a fibrous external layer onto which muscles, ligaments, and tendons attach.
The inside of the diaphysis, at the border between the cortical and cancellous bone and lining the trabeculae, is lined by endosteum.
Compact bone is organized as parallel columns, known as Haversian systems, which run lengthwise down the axis of long bones. These columns are composed of lamellae, concentric rings of bone, surrounding a central channel, or Haversian canal, that contains the nerves, blood vessels, and lymphatic system of the bone. The parallel Haversian canals are connected to one another by the perpendicular Volkmann’s canals.
The lamellae of the Haversian systems are created by osteoblasts. As these cells secrete matrix, they become trapped in spaces called lacunae and become known as osteocytes. Osteocytes communicate with the Haversian canal through cytoplasmic extensions that run through canaliculi, small interconnecting canals (Figure 4) [1, 2, 8, 9]:
Bone microstructure. Compact and spongy bone structures.
The layers of a long bone, beginning at the external surface, are therefore:
Periosteal surface of compact bone
Outer circumferential lamellae
Compact bone (Haversian systems)
Inner circumferential lamellae
Endosteal surface of compact bone
Trabecular bone
Bone development begins with the replacement of collagenous mesenchymal tissue by bone. This results in the formation of woven bone, a primitive form of bone with randomly organized collagen fibers that is further remodeled into mature lamellar bone, which possesses regular parallel rings of collagen. Lamellar bone is then constantly remodeled by osteoclasts and osteoblasts. Based on the development of bone formation can be divided into two parts, called endochondral and intramembranous bone formation/ossification [1, 2, 3, 8].
During intramembranous bone formation, the connective tissue membrane of undifferentiated mesenchymal cells changes into bone and matrix bone cells [10]. In the craniofacial cartilage bones, intramembranous ossification originates from nerve crest cells. The earliest evidence of intramembranous bone formation of the skull occurs in the mandible during the sixth prenatal week. In the eighth week, reinforcement center appears in the calvarial and facial areas in areas where there is a mild stress strength [11].
Intramembranous bone formation is found in the growth of the skull and is also found in the sphenoid and mandible even though it consists of endochondral elements, where the endochondral and intramembranous growth process occurs in the same bone. The basis for either bone formation or bone resorption is the same, regardless of the type of membrane involved.
Sometimes according to where the formation of bone tissue is classified as “periosteal” or “endosteal”. Periosteal bone always originates from intramembranous, but endosteal bone can originate from intramembranous as well as endochondral ossification, depending on the location and the way it is formed [3, 12].
The statement below is the stage of intramembrane bone formation (Figure 5) [3, 4, 11, 12]:
An ossification center appears in the fibrous connective tissue membrane. Mesenchymal cells in the embryonic skeleton gather together and begin to differentiate into specialized cells. Some of these cells differentiate into capillaries, while others will become osteogenic cells and osteoblasts, then forming an ossification center.
Bone matrix (osteoid) is secreted within the fibrous membrane. Osteoblasts produce osteoid tissue, by means of differentiating osteoblasts from the ectomesenchyme condensation center and producing bone fibrous matrix (osteoid). Then osteoid is mineralized within a few days and trapped osteoblast become osteocytes.
Woven bone and periosteum form. The encapsulation of cells and blood vessels occur. When osteoid deposition by osteoblasts continues, the encased cells develop into osteocytes. Accumulating osteoid is laid down between embryonic blood vessels, which form a random network (instead of lamellae) of trabecular. Vascularized mesenchyme condenses on external face of the woven bone and becomes the periosteum.
Production of osteoid tissue by membrane cells: osteocytes lose their ability to contribute directly to an increase in bone size, but osteoblasts on the periosteum surface produce more osteoid tissue that thickens the tissue layer on the existing bone surface (for example, appositional bone growth). Formation of a woven bone collar that is later replaced by mature lamellar bone. Spongy bone (diploe), consisting of distinct trabeculae, persists internally and its vascular tissue becomes red marrow.
Osteoid calcification: The occurrence of bone matrix mineralization makes bones relatively impermeable to nutrients and metabolic waste. Trapped blood vessels function to supply nutrients to osteocytes as well as bone tissue and eliminate waste products.
The formation of an essential membrane of bone which includes a membrane outside the bone called the bone endosteum. Bone endosteum is very important for bone survival. Disruption of the membrane or its vascular tissue can cause bone cell death and bone loss. Bones are very sensitive to pressure. The calcified bones are hard and relatively inflexible.
The stage of intramembranous ossification. The following stages are (a) Mesenchymal cells group into clusters, and ossification centers form. (b) Secreted osteoid traps osteoblasts, which then become osteocytes. (c) Trabecular matrix and periosteum form. (d) Compact bone develops superficial to the trabecular bone, and crowded blood vessels condense into red marrow.
The matrix or intercellular substance of the bone becomes calcified and becomes a bone in the end. Bone tissue that is found in the periosteum, endosteum, suture, and periodontal membrane (ligaments) is an example of intramembranous bone formation [3, 13].
Intramembranous bone formation occurs in two types of bone: bundle bone and lamellar bone. The bone bundle develops directly in connective tissue that has not been calcified. Osteoblasts, which are differentiated from the mesenchyme, secrete an intercellular substance containing collagen fibrils. This osteoid matrix calcifies by precipitating apatite crystals. Primary ossification centers only show minimal bone calcification density. The apatite crystal deposits are mostly irregular and structured like nets that are contained in the medullary and cortical regions. Mineralization occurs very quickly (several tens of thousands of millimeters per day) and can occur simultaneously in large areas. These apatite deposits increase with time. Bone tissue is only considered mature when the crystalized area is arranged in the same direction as collagen fibrils.
Bone tissue is divided into two, called the outer cortical and medullary regions, these two areas are destroyed by the resorption process; which goes along with further bone formation. The surrounding connective tissue will differentiate into the periosteum. The lining in the periosteum is rich in cells, has osteogenic function and contributes to the formation of thick bones as in the endosteum.
In adults, the bundle bone is usually only formed during rapid bone remodeling. This is reinforced by the presence of lamellar bone. Unlike bundle bone formation, lamellar bone development occurs only in mineralized matrix (e.g., cartilage that has calcified or bundle bone spicules). The nets in the bone bundle are filled to strengthen the lamellar bone, until compact bone is formed. Osteoblasts appear in the mineralized matrix, which then form a circle with intercellular matter surrounding the central vessels in several layers (Haversian system). Lamella bone is formed from 0.7 to 1.5 microns per day. The network is formed from complex fiber arrangements, responsible for its mechanical properties. The arrangement of apatites in the concentric layer of fibrils finally meets functional requirements. Lamellar bone depends on ongoing deposition and resorption which can be influenced by environmental factors, one of this which is orthodontic treatment.
Intramembranous bone formation from desmocranium (suture and periosteum) is mediated by mesenchymal skeletogenetic structures and is achieved through bone deposition and resorption [8]. This development is almost entirely controlled through local epigenetic factors and local environmental factors (i.e. by muscle strength, external local pressure, brain, eyes, tongue, nerves, and indirectly by endochondral ossification). Genetic factors only have a nonspecific morphogenetic effect on intramembranous bone formation and only determine external limits and increase the number of growth periods. Anomaly disorder (especially genetically produced) can affect endochondral bone formation, so local epigenetic factors and local environmental factors, including steps of orthodontic therapy, can directly affect intramembranous bone formation [3, 11].
During endochondral ossification, the tissue that will become bone is firstly formed from cartilage, separated from the joint and epiphysis, surrounded by perichondrium which then forms the periosteum [11]. Based on the location of mineralization, it can be divided into: Perichondral Ossification and Endochondral Ossification. Both types of ossification play an essential role in the formation of long bones where only endochondral ossification takes place in short bones. Perichondral ossification begins in the perichondrium. Mesenchymal cells from the tissue differentiate into osteoblasts, which surround bony diaphyseal before endochondral ossification, indirectly affect its direction [3, 8, 12]. Cartilage is transformed into bone is craniofacial bone that forms at the eigth prenatal week. Only bone on the cranial base and part of the skull bone derived from endochondral bone formation. Regarding to differentiate endochondral bone formation from chondrogenesis and intramembranous bone formation, five sequences of bone formation steps were determined [3].
The statements below are the stages of endochondral bone formation (Figure 6) [4, 12]:
Mesenchymal cells group to form a shape template of the future bone.
Mesenchymal cells differentiate into chondrocytes (cartilage cells).
Hypertrophy of chondrocytes and calcified matrix with calcified central cartilage primordium matrix formed. Chondrocytes show hypertrophic changes and calcification from the cartilage matrix continues.
Entry of blood vessels and connective tissue cells. The nutrient artery supplies the perichondrium, breaks through the nutrient foramen at the mid-region and stimulates the osteoprogenitor cells in the perichondrium to produce osteoblasts, which changes the perichondrium to the periosteum and starts the formation of ossification centers.
The periosteum continues its development and the division of cells (chondrocytes) continues as well, thereby increasing matrix production (this helps produce more length of bone).
The perichondrial membrane surrounds the surface and develops new chondroblasts.
Chondroblasts produce growth in width (appositional growth).
Cells at the center of the cartilage lyse (break apart) triggers calcification.
The stage of endochondral ossification. The following stages are: (a) Mesenchymal cells differentiate into chondrocytes. (b) The cartilage model of the future bony skeleton and the perichondrium form. (c) Capillaries penetrate cartilage. Perichondrium transforms into periosteum. Periosteal collar develops. Primary ossification center develops. (d) Cartilage and chondrocytes continue to grow at ends of the bone. (e) Secondary ossification centers develop. (f) Cartilage remains at epiphyseal (growth) plate and at joint surface as articular cartilage.
During endochondral bone formation, mesenchymal tissue firstly differentiates into cartilage tissue. Endochondral bone formation is morphogenetic adaptation (normal organ development) which produces continuous bone in certain areas that are prominently stressed. Therefore, this endochondral bone formation can be found in the bones associated with joint movements and some parts of the skull base. In hypertrophic cartilage cells, the matrix calcifies and the cells undergo degeneration. In cranial synchondrosis, there is proliferation in the formation of bones on both sides of the bone plate, this is distinguished by the formation of long bone epiphyses which only occurs on one side only [2, 14].
As the cartilage grows, capillaries penetrate it. This penetration initiates the transformation of the perichondrium into the bone-producing periosteum. Here, the osteoblasts form a periosteal collar of compact bone around the cartilage of the diaphysis. By the second or third month of fetal life, bone cell development and ossification ramps up and creates the primary ossification center, a region deep in the periosteal collar where ossification begins [4, 10].
While these deep changes occur, chondrocytes and cartilage continue to grow at the ends of the bone (the future epiphyses), which increase the bone length and at the same time bone also replaces cartilage in the diaphysis. By the time the fetal skeleton is fully formed, cartilage only remains at the joint surface as articular cartilage and between the diaphysis and epiphysis as the epiphyseal plate, the latter of which is responsible for the longitudinal growth of bones. After birth, this same sequence of events (matrix mineralization, death of chondrocytes, invasion of blood vessels from the periosteum, and seeding with osteogenic cells that become osteoblasts) occur in the epiphyseal regions, and each of these centers of activity is referred to as a secondary ossification center [4, 8, 10].
There are four important things about cartilage in endochondral bone formation:
Cartilage has a rigid and firm structure, but not usually calcified nature, giving three basic functions of growth (a) its flexibility can support an appropriate network structure (nose), (b) pressure tolerance in a particular place where compression occurs, (c) the location of growth in conjunction with enlarging bone (synchondrosis of the skull base and condyle cartilage).
Cartilage grows in two adjacent places (by the activity of the chondrogenic membrane) and grows in the tissues (chondrocyte cell division and the addition of its intercellular matrix).
Bone tissue is not the same as cartilage in terms of its tension adaptation and cannot grow directly in areas of high compression because its growth depends on the vascularization of bone formation covering the membrane.
Cartilage growth arises where linear growth is required toward the pressure direction, which allows the bone to lengthen to the area of strength and has not yet grown elsewhere by membrane ossification in conjunction with all periosteal and endosteal surfaces.
Membrane disorders or vascular supply problem of these essential membranes can directly result in bone cell death and ultimately bone damage. Calcified bones are generally hard and relatively inflexible and sensitive to pressure [12].
Cranial synchondrosis (e.g., spheno ethmoidal and spheno occipital growth) and endochondral ossification are further determined by chondrogenesis. Chondrogenesis is mainly influenced by genetic factors, similar to facial mesenchymal growth during initial embryogenesis to the differentiation phase of cartilage and cranial bone tissue.
This process is only slightly affected by local epigenetic and environmental factors. This can explain the fact that the cranial base is more resistant to deformation than desmocranium. Local epigenetic and environmental factors cannot trigger or inhibit the amount of cartilage formation. Both of these have little effect on the shape and direction of endochondral ossification. This has been analyzed especially during mandibular condyle growth.
Local epigenetics and environmental factors only affect the shape and direction of cartilage formation during endochondral ossification Considering the fact that condyle cartilage is a secondary cartilage, it is assumed that local factors provide a greater influence on the growth of mandibular condyle.
Chondrogenesis is the process by which cartilage is formed from condensed mesenchyme tissue, which differentiates into chondrocytes and begins secreting the molecules that form the extracellular matrix [5, 14].
The statement below is five steps of chondrogenesis [8, 14]:
Chondroblasts produce a matrix: the extracellular matrix produced by cartilage cells, which is firm but flexible and capable of providing a rigid support.
Cells become embed in a matrix: when the chondroblast changes to be completely embed in its own matrix material, cartilage cells turn into chondrocytes. The new chondroblasts are distinguished from the membrane surface (perichondrium), this will result in the addition of cartilage size (cartilage can increase in size through apposition growth).
Chondrocytes enlarge, divide and produce a matrix. Cell growth continues and produces a matrix, which causes an increase in the size of cartilage mass from within. Growth that causes size increase from the inside is called interstitial growth.
The matrix remains uncalcified: cartilage matrix is rich of chondroitin sulfate which is associated with non-collagen proteins. Nutrition and metabolic waste are discharged directly through the soft matrix to and from the cell. Therefore, blood vessels aren’t needed in cartilage.
The membrane covers the surface but is not essential: cartilage has a closed membrane vascularization called perichondrium, but cartilage can exist without any of these. This property makes cartilage able to grow and adapt where it needs pressure (in the joints), so that cartilage can receive pressure.
Endochondral ossification begins with characteristic changes in cartilage bone cells (hypertrophic cartilage) and the environment of the intercellular matrix (calcium laying), the formation which is called as primary spongiosa. Blood vessels and mesenchymal tissues then penetrate into this area from the perichondrium. The binding tissue cells then differentiate into osteoblasts and cells. Chondroblasts erode cartilage in a cave-like pattern (cavity). The remnants of mineralized cartilage the central part of laying the lamellar bone layer.
The osteoid layer is deposited on the calcified spicules remaining from the cartilage and then mineralized to form spongiosa bone, with fine reticular structures that resemble nets that possess cartilage fragments between the spicular bones. Spongy bones can turn into compact bones by filling empty cavities. Both endochondral and perichondral bone growth both take place toward epiphyses and joints. In the bone lengthening process during endochondral ossification depends on the growth of epiphyseal cartilage. When the epiphyseal line has been closed, the bone will not increase in length. Unlike bone, cartilage bone growth is based on apposition and interstitial growth. In areas where cartilage bone is covered by bone, various variations of zone characteristics, based on the developmental stages of each individual, can differentiate which then continuously merge with each other during the conversion process. Environmental influences (co: mechanism of orthopedic functional tools) have a strong effect on condylar cartilage because the bone is located more superficially [5].
Cartilage bone height development occurs during the third month of intra uterine life. Cartilage plate extends from the nasal bone capsule posteriorly to the foramen magnum at the base of the skull. It should be noted that cartilages which close to avascular tissue have internal cells obtained from the diffusion process from the outermost layer. This means that the cartilage must be flatter. In the early stages of development, the size of a very small embryo can form a chondroskeleton easily in which the further growth preparation occurs without internal blood supply [1].
During the fourth month in the uterus, the development of vascular elements to various points of the chondrocranium (and other parts of the early cartilage skeleton) becomes an ossification center, where the cartilage changes into an ossification center, and bone forms around the cartilage. Cartilage continues to grow rapidly but it is replaced by bone, resulting in the rapid increase of bone amount. Finally, the old chondrocranium amount will decrease in the area of cartilage and large portions of bone, assumed to be typical in ethmoid, sphenoid, and basioccipital bones. The cartilage growth in relation to skeletal bone is similar as the growth of the limbs [1, 3].
Longitudinal bone growth is accompanied by remodeling which includes appositional growth to thicken the bone. This process consists of bone formation and reabsorption. Bone growth stops around the age of 21 for males and the age of 18 for females when the epiphyses and diaphysis have fused (epiphyseal plate closure).
Normal bone growth is dependent on proper dietary intake of protein, minerals and vitamins. A deficiency of vitamin D prevents calcium absorption from the GI tract resulting in rickets (children) or osteomalacia (adults). Osteoid is produced but calcium salts are not deposited, so bones soften and weaken.
At the length of the long bones, the reinforcement plane appears in the middle and at the end of the bone, finally produces the central axis that is called the diaphysis and the bony cap at the end of the bone is called the epiphysis. Between epiphyses and diaphysis is a calcified area that is not calcified called the epiphyseal plate. Epiphyseal plate of the long bone cartilage is a major center for growth, and in fact, this cartilage is responsible for almost all the long growths of the bones. This is a layer of hyaline cartilage where ossification occurs in immature bones. On the epiphyseal side of the epiphyseal plate, the cartilage is formed. On the diaphyseal side, cartilage is ossified, and the diaphysis then grows in length. The epiphyseal plate is composed of five zones of cells and activity [3, 4].
Near the outer end of each epiphyseal plate is the active zone dividing the cartilage cells. Some of them, pushed toward diaphysis with proliferative activity, develop hypertrophy, secrete an extracellular matrix, and finally the matrix begins to fill with minerals and then is quickly replaced by bone. As long as cartilage cells multiply growth will continue. Finally, toward the end of the normal growth period, the rate of maturation exceeds the proliferation level, the latter of the cartilage is replaced by bone, and the epiphyseal plate disappears. At that time, bone growth is complete, except for surface changes in thickness, which can be produced by the periosteum [4]. Bones continue to grow in length until early adulthood. The lengthening is stopped in the end of adolescence which chondrocytes stop mitosis and plate thins out and replaced by bone, then diaphysis and epiphyses fuse to be one bone (Figure 7). The rate of growth is controlled by hormones. When the chondrocytes in the epiphyseal plate cease their proliferation and bone replaces the cartilage, longitudinal growth stops. All that remains of the epiphyseal plate is the epiphyseal line. Epiphyseal plate closure will occur in 18-year old females or 21-year old males.
Oppositional bone growth and remodeling. The epiphyseal plate is responsible for longitudinal bone growth.
The cartilage found in the epiphyseal gap has a defined hierarchical structure, directly beneath the secondary ossification center of the epiphysis. By close examination of the epiphyseal plate, it appears to be divided into five zones (starting from the epiphysis side) (Figure 8) [4]:
The resting zone: it contains hyaline cartilage with few chondrocytes, which means no morphological changes in the cells.
The proliferative zone: chondrocytes with a higher number of cells divide rapidly and form columns of stacked cells parallel to the long axis of the bone.
The hypertrophic cartilage zone: it contains large chondrocytes with cells increasing in volume and modifying the matrix, effectively elongating bone whose cytoplasm has accumulated glycogen. The resorbed matrix is reduced to thin septa between the chondrocytes.
The calcified cartilage zone: chondrocytes undergo apoptosis, the thin septa of cartilage matrix become calcified.
The ossification zone: endochondral bone tissue appears. Blood capillaries and osteoprogenitor cells (from the periosteum) invade the cavities left by the chondrocytes. The osteoprogenitor cells form osteoblasts, which deposit bone matrix over the three-dimensional calcified cartilage matrix.
Epiphyseal plate growth. Five zones of epiphyseal growth plate includes: 1. resting zone, 2. proliferation zone, 3. hypertrophic cartilage zone, 4. calcified cartilage zone, and 5. ossification zone.
When bones are increasing in length, they are also increasing in diameter; diameter growth can continue even after longitudinal growth stops. This is called appositional growth. The bone is absorbed on the endosteal surface and added to the periosteal surface. Osteoblasts and osteoclasts play an essential role in appositional bone growth where osteoblasts secrete a bone matrix to the external bone surface from diaphysis, while osteoclasts on the diaphysis endosteal surface remove bone from the internal surface of diaphysis. The more bone around the medullary cavity is destroyed, the more yellow marrow moves into empty space and fills space. Osteoclasts resorb the old bone lining the medullary cavity, while osteoblasts through intramembrane ossification produce new bone tissue beneath the periosteum. Periosteum on the bone surface also plays an important role in increasing thickness and in reshaping the external contour. The erosion of old bone along the medullary cavity and new bone deposition under the periosteum not only increases the diameter of the diaphysis but also increases the diameter of the medullary cavity. This process is called modeling (Figure 9) [3, 4, 15].
Appositional bone growth. Bone deposit by osteoblast as bone resorption by osteoclast.
Recent research reported that bone microstructure is also the principle of bone function, which regulates its mechanical function. Bone tissue function influenced by many factors, such as hormones, growth factors, and mechanical loading. The microstructure of bone tissue is distribution and alignment of biological apatite (BAp) crystallites. This is determined by the direction of bone cell behavior, for example cell migration and cell regulation. Ozasa et al. found that artificial control the direction of mesenchymal stem cell (MSCs) migration and osteoblast alignment can reconstruct bone microstructure, which guide an appropriate bone formation during bone remodeling and regeneration [16].
Bone development begins with the replacement of collagenous mesenchymal tissue by bone. Generally, bone is formed by endochondral or intramembranous ossification. Intramembranous ossification is essential in the bone such as skull, facial bones, and pelvis which MSCs directly differentiate to osteoblasts. While, endochondral ossification plays an important role in most bones in the human skeleton, including long, short, and irregular bones, which MSCs firstly experience to condensate and then differentiate into chondrocytes to form the cartilage growth plate and the growth plate is then gradually replaced by new bone tissue [3, 8, 12].
MSC migration and differentiation are two important physiological processes in bone formation. MSCs migration raise as an essential step of bone formation because MSCs initially need to migrate to the bone surface and then contribute in bone formation process, although MSCs differentiation into osteogenic cells is also crucial. MSC migration during bone formation has attracted more attention. Some studies show that MSC migration to the bone surface is crucial for bone formation [17]. Bone marrow and periosteum are the main sources of MSCs that participate in bone formation [18].
In the intramembranous ossification, MSCs undergo proliferation and differentiation along the osteoblastic lineage to form bone directly without first forming cartilage. MSC and preosteoblast migration is involved in this process and are mediated by plentiful factors in vivo and in vitro. MSCs initially differentiate into preosteoblasts which proliferate near the bone surface and secrete ALP. Then they become mature osteoblasts and then form osteocytes which embedded in an extracellular matrix (ECM). Other factors also regulate the intramembranous ossification of MSCs such as Runx2, special AT-rich sequence binding protein 2 (SATB 2), and Osterix as well as pathways, like the wnt/β-catenin pathway and bone morphogenetic protein (BMP) pathway [17, 19].
In the endochondral ossification, MSCs are first condensed to initiate cartilage model formation. The process is mediated by BMPs through phosphorylating and activating receptor SMADs to transduce signals. During condensation, the central part of MSCs differentiates into chondrocytes and secretes cartilage matrix. While, other cells in the periphery, form the perichondrium that continues expressing type I collagen and other important factors, such as proteoglycans and ALP. Chondrocytes undergo rapid proliferation. Chondrocytes in the center become maturation, accompanied with an invasion of hypertrophic cartilage by the vasculature, followed by differentiation of osteoblasts within the perichondrium and marrow cavity. The inner perichondrium cells differentiate into osteoblasts, which secrete bone matrix to form the bone collar after vascularization in the hypertrophic cartilage. Many factors that regulate endochondral ossification are growth factors (GFs), transforming growth factor-β (TGF-β), Sry-related high-mobility group box 9 (Sox9) and Cell-to-cell interaction [17, 19].
Osteogenesis/ossification is the process in which new layers of bone tissue are placed by osteoblasts.
During bone formation, woven bone (haphazard arrangement of collagen fibers) is remodeled into lamellar bones (parallel bundles of collagen in a layer known as lamellae)
Periosteum is a connective tissue layer on the outer surface of the bone; the endosteum is a thin layer (generally only one layer of cell) that coats all the internal surfaces of the bone
Major cell of bone include: osteoblasts (from osteoprogenitor cells, forming osteoid that allow matrix mineralization to occur), osteocytes (from osteoblasts; closed to lacunae and retaining the matrix) and osteoclasts (from hemopoietic lineages; locally erodes matrix during bone formation and remodeling.
The process of bone formation occurs through two basic mechanisms:
Intramembranous bone formation occurs when bone forms inside the mesenchymal membrane. Bone tissue is directly laid on primitive connective tissue referred to mesenchyma without intermediate cartilage involvement. It forms bone of the skull and jaw; especially only occurs during development as well as the fracture repair.
Endochondral bone formation occurs when hyaline cartilage is used as a precursor to bone formation, then bone replaces hyaline cartilage, forms and grows all other bones, occurs during development and throughout life.
During interstitial epiphyseal growth (elongation of the bone), the growth plate with zonal organization of endochondral ossification, allows bone to lengthen without epiphyseal growth plates enlarging zones include:
Zone of resting.
Zone of proliferation.
Zone of hypertrophy.
Zone of calcification.
Zone of ossification and resorption.
During appositional growth, osteoclasts resorb old bone that lines the medullary cavity, while osteoblasts, via intramembranous ossification, produce new bone tissue beneath the periosteum.
Mesenchymal stem cell migration and differentiation are two important physiological processes in bone formation.
The author is grateful to Zahrona Kusuma Dewi for assistance with preparation of the manuscript.
The authors declare that there is no conflict of interests regarding the publication of this paper.
alkaline phosphatase biological apatite bone morphogenetic protein extracellular matrix growth factors mesenchymal stem cells runt-related transcription factor 2 special AT-rich sequence binding protein 2 sry-related high-mobility group box 9 transforming growth factor-β
IntechOpen celebrates Open Access academic research of women scientists: Call Opens on February 11, 2018 and closes on March 8th, 2018.
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\n\nThe submissions are now closed. All applicants will be notified on the results in due time. Thank you for participating!
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