Editing Discrete element method (section)

==Advantages and limitations==
Advantages
* DEM can be used to simulate a wide variety of granular flow and rock mechanics situations. Several research groups have independently developed simulation software that agrees well with experimental findings in a wide range of engineering applications, including adhesive powders, granular flow, and jointed rock masses.
* DEM allows a more detailed study of the micro-dynamics of powder flows than is often possible using physical experiments. For example, the force networks formed in a granular media can be visualized using DEM. Such measurements are nearly impossible in experiments with small and many particles.
* The general characteristics of force-transmitting contacts in granular assemblies under external loading environments agree with experimental studies using Photo-stress analysis (PSA).<ref>{{cite journal |doi=10.1098/rsta.2007.0004 |title=Link between single-particle properties and macroscopic properties in particulate assemblies: Role of structures within structures |date=2007 |last1=Antony |first1=S.J |journal=Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences |volume=365 |issue=1861 |pages=2879–2891 |pmid=17875541 |bibcode=2007RSPTA.365.2879A }}</ref><ref>{{cite journal |last1=S. J. Antony, D. Chapman, J. Sujatha and T. Barakat |title=Interplay between the inclusions of different sizes and their proximity to the wall boundaries on the nature of their stress distribution within the inclusions inside particulate packing |journal=Powder Technology |date=2015 |volume=286 |pages=286, 98–106|doi=10.1016/j.powtec.2015.08.007 |url=https://eprints.whiterose.ac.uk/89428/1/Manuscript-FinalV.pdf }}</ref>

Disadvantages
* The maximum number of particles, and duration of a virtual simulation is limited by computational power. Typical flows contain billions of particles, but contemporary DEM simulations on large cluster computing resources have only recently been able to approach this scale for sufficiently long time (simulated time, not actual program execution time). 
* DEM is computationally demanding, which is the reason why it has not been so readily and widely adopted as continuum approaches in computational engineering sciences and industry. However, the actual program execution times can be reduced significantly when graphical processing units (GPUs) are utilized to conduct DEM simulations, due to the large number of computing cores on typical GPUs. In addition GPUs tend to be significantly more energy efficient than conventional computing clusters when conducting DEM simulations i.e. a DEM simulation solved on GPUs requires less energy than when it is solved on a conventional computing cluster.<ref>{{Cite journal|last1=He|first1=Yi|last2=Bayly|first2=Andrew E.|last3=Hassanpour|first3=Ali|last4=Muller|first4=Frans|last5=Wu|first5=Ke|last6=Yang|first6=Dongmin|date=2018-10-01|title=A GPU-based coupled SPH-DEM method for particle-fluid flow with free surfaces|journal=Powder Technology|volume=338|pages=548–562|doi=10.1016/j.powtec.2018.07.043|issn=0032-5910|doi-access=free}}</ref>