2015
DOI: 10.1007/s40571-015-0056-5
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Discrete element modelling (DEM) input parameters: understanding their impact on model predictions using statistical analysis

Abstract: Selection or calibration of particle property input parameters is one of the key problematic aspects for the implementation of the discrete element method (DEM). In the current study, a parametric multi-level sensitivity method is employed to understand the impact of the DEM input particle properties on the bulk responses for a given simple system: discharge of particles from a flat bottom cylindrical container onto a plate. In this case study, particle properties, such as Young's modulus, friction parameters … Show more

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Cited by 180 publications
(81 citation statements)
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“…Thek ey feature to obtain accurate results through DEM leans on the correct choice of the contact model and the reliability of input parameters.O nt op of that, an appropriate time step must be selected in such aw ay that no disturbance propagates further than ap article'si mmediate neighbor within one time step. [14] Heat conduction in DEM To introduce heat transfer within the electrode,i ti sn ecessary to combine the mechanical features from the contact model with ah eat conduction model. To that purpose,t he temperature of the particles was also considered as an additional degree of freedom and, thus,the heat transfer was calculated as follows,…”
Section: Discrete Elementmethodsmentioning
confidence: 99%
“…Thek ey feature to obtain accurate results through DEM leans on the correct choice of the contact model and the reliability of input parameters.O nt op of that, an appropriate time step must be selected in such aw ay that no disturbance propagates further than ap article'si mmediate neighbor within one time step. [14] Heat conduction in DEM To introduce heat transfer within the electrode,i ti sn ecessary to combine the mechanical features from the contact model with ah eat conduction model. To that purpose,t he temperature of the particles was also considered as an additional degree of freedom and, thus,the heat transfer was calculated as follows,…”
Section: Discrete Elementmethodsmentioning
confidence: 99%
“…DEM simulations hitherto have been demonstrated their extremely desirability to predict what happens in reality, as well as the quantitatively accurate information representation inside the mills, while the accuracy of outcomes for DEM simulations depends highly on the input parameters [13,14,15,16,17,18], including parameters such as contact parameters (restitution coefficient, static friction coefficient, and rolling friction coefficient), mechanical properties (shear modulus, Poisson’s ratio, and density), and particle shape.…”
Section: Introductionmentioning
confidence: 99%
“…The analysis at the grain scale has helped researchers to improve their understanding on the complex behavior of granular materials and analyze multiscale problems (Guo & Zhao, ; O'Sullivan, ; Soga & O'Sullivan, ). The parameters obtained through micromechanical tests at the grain scale (for example, interparticle friction, normal and tangential stiffness) comprise important input in numerical simulations using DEM analyses, for example, in the analysis of the macroscale response of granular materials subjected to monotonic or cyclic loading and the flowability behavior of granular materials (Huang et al, ; Iverson et al, ; Sazzad & Suzuki, ; Yan et al, ). Based on this, significant advancements took place in recent years in microscale experimentation investigating the contact behavior of geological materials and lunar regolith simulants (e.g., Cavarretta et al, ; Cole, ; Cole & Peters, ; Nardelli et al, ; Nardelli & Coop, ; Sandeep & Senetakis, , , ; Senetakis et al, , ; Senetakis & Coop, ).…”
Section: Introductionmentioning
confidence: 99%