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<p>Several rolling resistance models are documented in the literature and implemented in discrete element method (DEM) software. Specifically, constant directional torque (CDT) and elasto-slipping (ES) models are frequently used in similar simulation conditions but often lead to inconsistent outcomes. A limitation of CDT models is that they are known to be sensitive to numerical oscillations. In the present work, we attempt to define the range of validity of CDT models through the identification of a dimensionless oscillation number (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40571_2025_1034_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="15" /> </InlineMediaObject> <EquationSource Format="TEX">\(\varPsi \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>Ψ</mi> </math></EquationSource> </InlineEquation>) via an order of magnitude analysis. This oscillation number is demonstrated to effectively predict the division between two series of DEM simulations conducted using CDT and ES models.</p>

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Dimensionless criterion to select the rolling resistance models in DEM simulations

  • 期刊论文

  • 发表日期：

    2025年7月29日

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  • Maxime Stephan,
  • Guilhem Roux,
  • Alexis Burr,
  • Carine Ablitzer,
  • Jean-Paul Garandet

摘要

Several rolling resistance models are documented in the literature and implemented in discrete element method (DEM) software. Specifically, constant directional torque (CDT) and elasto-slipping (ES) models are frequently used in similar simulation conditions but often lead to inconsistent outcomes. A limitation of CDT models is that they are known to be sensitive to numerical oscillations. In the present work, we attempt to define the range of validity of CDT models through the identification of a dimensionless oscillation number ( \(\varPsi \) Ψ ) via an order of magnitude analysis. This oscillation number is demonstrated to effectively predict the division between two series of DEM simulations conducted using CDT and ES models.