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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=
| year=1990}}</ref>) by additional properties such as the [[thermodynamic]] state, [[Stress (
==History==
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| year=1959
| volume=31
|
| 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
}}</ref> may be regarded as a first step toward the extended discrete element method, although the forces due to collisions between particles were replaced by energy potentials e.g. [[Lennard-Jones]] potentials of [[molecules]] and [[atoms]] as long range forces to determine interaction.▼
| doi=10.1103/physrev.136.a405
| pages=A405–A411
▲|bibcode = 1964PhRv..136..405R }}</ref> may be regarded as a first step toward the extended discrete element method, although the forces due to collisions between particles were replaced by energy potentials e.g. [[Lennard-Jones]] potentials of [[molecules]] and [[atoms]] as long range forces to determine interaction.
Similarly, the fluid dynamic interaction of particles suspended in a flow were investigated. The [[drag (physics)|drag]] forces exerted on the particles by the relative velocity by them and the flow were treated as additional forces acting on the particles. Therefore, these [[multiphase flow]] phenomena including a solid e.g.~particulate and a gaseous or fluid phase resolve the particulate phase by discrete methods, while gas or liquid flow is described by continuous methods, and therefore, is labelled the combined continuum and discrete model (CCDM) as applied by Kawaguchi et al.,<ref>{{cite journal
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| year=1993
| volume=77
| doi=10.1016/0032-5910(93)85010-7
| pages=79–87
}}</ref> Hoomans,<ref>{{cite journal
| first1=B. P. B.
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| year=1996
| volume=51
| 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-
==Methodology==
[[File:Staggered methodology for software coupling.png|thumb|Staggered methodology for discrete/continuous applications.]]
Although research and development of numerical methods in each domains of discrete and continuous solvers is still progressing,
*'''Monolithic
*'''Partitioned or staggered
The former
The latter, partitioned, approach couples a number of solvers representing individual domains of physics offers advantages over a monolithic concept. It encompasses a larger degree of flexibility because it can use many solvers. Furthermore, it allows a more modular software development. However, partitioned simulations require stable and accurate coupling algorithms.
Within the staggered concept of XDEM, continuous fields are described by the solution the respective continuous (conservation) equations. Properties of individual particles such as temperature are also resolved by solving respective conservation equations that
▲Within the staggered concept of XDEM, continuous fields are described by the solution the respective continuous (conservation) equations. Properties of individual particles such as temperature are also resolved by solving respective conservation equations that yields both a spatial and temporal internal distribution of relevant variables. Mayor conservation principles with their equations and variables to be solved for and that are employed to an individual particle within XDEM are listed in the
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| volume=97
| pages=1–16
| doi=10.1016/0010-2180(94)90112-0
}}</ref> while the importance of a transient behaviour is stressed by Lee et al.<ref>{{cite journal
| first1=J. C.
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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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| year=1996
| volume=51
| 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
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