An Error-Controlled Adaptive Time-Stepping Method for Particle Advancement in Coupled CFD-DEM Simulations

Hariswaran Sitaraman, Deepthi Vaidhynathan, Ray Grout, Thomas Hauser, Christine M. Hrenya, Jordan Musser

Research output: Contribution to journalArticlepeer-review

5 Scopus Citations


Coupled Computational-Fluid-Dynamics (CFD) and Discrete-Element-Method (DEM) models provide an accurate description of multiphase physical systems where a solid granular particle phase exists in an underlying gaseous continuous medium. The time integration of the granular phase in these simulations is typically handled using an explicit scheme with a constant time-step among all particles that is invariant in time to resolve inter-particle collisions. A locally third-order accurate adaptive time integration technique for particles that employs an embedded locally second-order scheme for error determination is presented in this work. The particle time-step size is dynamically adapted based on solution error, thus leading to significant savings in computational time. The efficacy of our scheme is quantified using four test cases of varying complexity (binary collision, homogeneous cooling system, fluidized bed and hopper discharge). The adaptive time-stepping method exhibits improved performance (~ 2–3 times in most of the cases studied) compared to three commonly used non-adaptive time-step methods (first-order Euler-explicit, second-order Adams-Bashforth and third-order Runge-Kutta schemes), while maintaining the same level of accuracy and parallel scalability.

Original languageAmerican English
Pages (from-to)203-216
Number of pages14
JournalPowder Technology
StatePublished - Feb 2021

Bibliographical note

Publisher Copyright:
© 2020

NREL Publication Number

  • NREL/JA-2C00-75953


  • adaptive time-stepping
  • computational-fluid-dynamics
  • discrete-element-methods
  • Lagrangian methods


Dive into the research topics of 'An Error-Controlled Adaptive Time-Stepping Method for Particle Advancement in Coupled CFD-DEM Simulations'. Together they form a unique fingerprint.

Cite this