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Discrete element method
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{{short description| Numerical methods for computing the motion and effect of a large number of small particles}} {{distinguish|finite element method}} {{More citations needed|date=November 2019}} A '''discrete element method''' ('''DEM'''), also called a '''distinct element method''', is any of a family of [[numerical analysis|numerical]] methods for computing the motion and effect of a large number of small particles. Though DEM is very closely related to [[molecular dynamics]], the method is generally distinguished by its inclusion of rotational [[Degrees of freedom (statistics)|degrees-of-freedom]] as well as stateful contact, particle deformation and often complicated geometries (including polyhedra). With advances in computing power and numerical algorithms for nearest neighbor sorting, it has become possible to numerically simulate millions of particles on a single processor. Today DEM is becoming widely accepted as an effective method of addressing engineering problems in granular and discontinuous materials, especially in granular flows, powder mechanics, ice and rock mechanics. DEM has been extended into the [[Extended Discrete Element Method]] taking [[heat transfer]],<ref name="Peng">{{cite journal |last1=Peng |first1=Z. |last2=Doroodchi |first2=E. |last3=Moghtaderi |first3=B. |date=2020 |title=Heat transfer modelling in Discrete Element Method (DEM)-based simulations of thermal processes: Theory and model development |journal=Progress in Energy and Combustion Science |volume=79,100847 |page=100847 |doi=10.1016/j.pecs.2020.100847|s2cid=218967044 }}</ref> [[chemical reaction]]<ref name="Papadikis">{{cite journal |last1=Papadikis |first1=K. |last2=Gu |first2=S. |last3=Bridgwater |first3=A.V. |date=2009 |title=CFD modelling of the fast pyrolysis of biomass in fluidised bed reactors: Modelling the impact of biomass shrinkage |journal=Chemical Engineering Journal |volume=149 |issue=1–3 |pages=417–427|doi=10.1016/j.cej.2009.01.036 |url=https://eprints.soton.ac.uk/149223/1/Paper.pdf }}</ref> and coupling to [[Computational fluid dynamics|CFD]]<ref name="Kafui">{{cite journal |last1=Kafui |first1=K.D. |last2=Thornton |first2=C. |last3=Adams |first3=M.J. |date=2002 |title=Discrete particle-continuum fluid modelling of gas–solid fuidised beds |journal=Chemical Engineering Science |volume=57 |issue=13 |pages=2395–2410|doi=10.1016/S0009-2509(02)00140-9 |bibcode=2002ChEnS..57.2395K }}</ref> and [[Finite element method|FEM]]<ref name="Trivino">{{cite journal |last1=Trivino |first1=L.F. |last2=Mohanty |first2=B. |date=2015 |title=Assessment of crack initiation and propagation in rock from explosion-induced stress waves and gas expansion by cross-hole seismometry and FEM–DEM method |journal=International Journal of Rock Mechanics & Mining Sciences |volume=77 |pages=287–299|doi=10.1016/j.ijrmms.2015.03.036 |bibcode=2015IJRMM..77..287T }}</ref> into account. Discrete element methods are relatively computationally intensive, which limits either the length of a simulation or the number of particles. Several DEM codes, as do molecular dynamics codes, take advantage of parallel processing capabilities (shared or distributed systems) to scale up the number of particles or length of the simulation. An alternative to treating all particles separately is to average the physics across many particles and thereby treat the material as a [[Continuum mechanics|continuum]]. In the case of [[solid]]-like granular behavior as in [[soil mechanics]], the continuum approach usually treats the material as [[Elasticity (physics)|elastic]] or [[Plasticity (physics)|elasto-plastic]] and models it with the [[finite element method]] or a [[Meshfree methods|mesh free method]]. In the case of liquid-like or gas-like granular flow, the continuum approach may treat the material as a [[fluid]] and use [[computational fluid dynamics]]. Drawbacks to [[Homogenization (chemistry)|homogenization]] of the granular scale physics, however, are well-documented and should be considered carefully before attempting to use a continuum approach.
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