Extended discrete element method: Difference between revisions

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{{Short description|Granular material interaction simulation technique}}

[[File:Internal temperature distribution in a particle.png|thumb|An internal temperature distribution for a spherical particle versus radius and time under a time-varying [[heat flux]].]]

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| authorlink2=D. J. Tildesley

| title=Computer Simulation of Liquids

| publisher=ClaredonClarendon Press Oxford

| year=1990}}</ref>) by additional properties such as the [[thermodynamic]] state, [[Stress (mechanicalmechanics)|stress]]/[[Deformation (mechanics)|strain]] or [[electro-magnetic]] field for each particle. Contrary to a [[continuum mechanics]] concept, the XDEM aims at resolving the particulate phase with its various processes attached to the particles. While the discrete element method predicts position and orientation in space and time for each particle, the extended discrete element method additionally estimates properties such as internal [[temperature]] and/or [[species]] distribution or mechanical impact with structures.

==History==

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| year=1959

| volume=31

| pagesissue=4592

| pages=459–466

| doi=10.1063/1.1730376

| bibcode=1959JChPh..31..459A}}</ref> and early 1960s by Rahman<ref>{{cite journal

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| year=1964

| volume=136

| issue=2A

| doi=10.1103/physrev.136.a405

| pages=A405–A411

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| doi=10.1016/0009-2509(95)00271-5

| pages=99–118

| citeseerx=10.1.1.470.6532

| s2cid=17460834

}}</ref> Xu 1997<ref>{{cite journal

| first1=B. H.

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| year=1997

| volume=52

| issue=16

| pages=2785–2809

| doi=10.1016/s0009-2509(97)00081-x

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| year=1998

| volume=53

| issue=14

| pages=2646–2647

| doi=10.1016/s0009-2509(98)00086-4

}}</ref> Due to a discrete description of the solid phase, [[constitutive equation|constitutive]] relations are omitted, and therefore, leads to a better understanding of the fundamentals. This was also concluded by Zhu 2007 et al.<ref>{{cite journal

| first1=H. P.

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| year=2007

| volume=62

| issue=13

| pages=3378–3396

| doi=10.1016/j.ces.2006.12.089

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| year=2008

| volume=63

| issue=23

| pages=5728–5770

| doi=10.1016/j.ces.2008.08.006

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| year=2003

| volume=78

| issue=2–3

| pages=111–121

| doi=10.1002/jctb.788

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| year=2004

| volume=43

| issue=26

| pages=8378–8390

| doi=10.1021/ie049387v

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| year=2007

| volume=62

| issue=1–2

| pages=28–44

| doi=10.1016/j.ces.2006.08.014

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| year=2009

| volume=87

| issue=2

| pages=318–328

| doi=10.1002/cjce.20143

| citeseerx=10.1.1.335.4108

}}</ref>

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| year=1999

| volume=116

| issue=1–2

| pages=297–301

| doi=10.1016/s0010-2180(98)00048-0

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| year=2002

| volume=131

| issue=1–2

| pages=132–146

| doi=10.1016/s0010-2180(02)00393-0

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| year=2009

| volume=193

| issue=3

| pages=266–273

| doi=10.1016/j.powtec.2009.03.011

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| year=2010

| volume=50

| issue=2

| pages=207–214

| doi=10.2355/isijinternational.50.207

| doi-access=free

}}</ref> Numerical simulation of fluid injection into a gaseous environment nowadays is adopted by a large number of CFD-codes codes such as Star-CD of [[CDSimcenter STAR-adapcoCCM+]], [[Ansys]] and [[AVL (Engineering Firm)|AVL]]-Fire. Droplets of a spray are treated by a zero-dimensional approach to account for heat and mass transfer to the fluid phase.

==Methodology==

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| year=1996

| volume=105

| issue=4

| pages=591–599

| doi=10.1016/0010-2180(96)00221-0

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| doi=10.1016/0009-2509(95)00271-5

| pages=99–118

| citeseerx=10.1.1.470.6532

| s2cid=17460834

}}</ref> however, Chu and Yu<ref>{{cite journal

| first1=K. W.

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| year=2008

| volume=179

| issue=3

| pages=104–114

| doi=10.1016/j.powtec.2007.06.017

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| year=2011

| volume=90

| issue=4

| pages=1584–1590

| doi=10.1016/j.fuel.2010.10.017

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| year=2009

| volume=22

| issue=11

| pages=893–909

| doi=10.1016/j.mineng.2009.04.008

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| year=1976

| volume=15

| issue=2

| pages=141–147

| doi=10.1016/0032-5910(76)80042-3

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| year=2004

| volume=43

| issue=26

| pages=8378–8390

| doi=10.1021/ie049387v

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| year=2008

| volume=6

| issue=6

| pages=549–556

| doi=10.1016/j.partic.2008.07.011

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| year=2002

| volume=57

| issue=13

| pages=2395–2410

| doi=10.1016/s0009-2509(02)00140-9

}}</ref> describe discrete particle-continuum fluid modelling of gas-solid fluidised beds. Further applications of XDEM include thermal conversion of biomass on a backward and forward acting grate. Heat transfer in athermal/reacting [[packedparticulate bed]] reactorsystems was also solved and investigated, foras hotcomprehensively airreviewed streamingby upwardPeng throughet theal.<ref packedname="Peng">{{cite bedjournal to|last1=Peng heat|first1=Z. the|last2=Doroodchi particles,|first2=E. which|last3=Moghtaderi dependent|first3=B. on|date=2020 |title=Heat transfer modelling in Discrete Element Method (DEM)-based simulations of thermal processes: positionTheory and sizemodel experiencedevelopment different|journal=Progress heatin transferEnergy ratesand Combustion Science |volume=79,100847 |page=100847 |doi=10.1016/j.pecs.2020.100847|s2cid=218967044 }}</ref> The [[deformation (engineering)|deformation]] of a conveyor belt due to impacting [[granular material]] that is discharged over a chute represents an application in the field of [[Stress (mechanicalmechanics)|stress]]/[[Deformation (mechanics)|strain]] analysis.

{|