Comparative Analysis of Granular Material Flow: Discrete Element Method and Smoothed Particle Hydrodynamics Approaches

TL;DR

This paper compares the Discrete Element Method and Smoothed Particle Hydrodynamics for modeling granular flows, highlighting their respective advantages, limitations, and suitability for different flow scenarios based on experimental validation.

Contribution

It provides a detailed comparison of DEM and SPH approaches, including parameter calibration, computational efficiency, and ability to replicate complex granular behaviors.

Findings

DEM requires extensive parameter calibration.

SPH is computationally more efficient and easier to parameterize.

DEM better captures complex flow behaviors in granular materials.

Abstract

We compare two widely used Lagrangian approaches for modeling granular materials: the Discrete Element Method (DEM) and Smoothed Particle Hydrodynamics (SPH). DEM models individual particle interactions, while SPH treats granular materials as a continuum using constitutive rheological models. In particular, we employ the Drucker Prager viscoplastic model for SPH. By examining key parameters unique to each method, such as the coefficient of restitution in DEM and the dilatancy angle in SPH, we assess their influence on two dimensional soil collapse predictions against experimental results. While DEM requires computationally expensive parameter calibration, SPH benefits from a continuum scale rheological model, allowing most parameters to be directly determined from laboratory measurements and requiring significantly fewer particles. However, despite its computational efficiency, viscoplastic SPH struggles to capture complex granular flow behaviors observed in DEM, particularly in rotating drum simulations. In contrast, DEM offers greater versatility, accommodating a broader range of flow patterns while maintaining a relatively simple model formulation. These findings provide valuable insights into the strengths and limitations of each method, aiding the selection of appropriate modeling techniques for granular flow simulations.