Energy Minimization and Preconditioning in the Simulation of Athermal Granular Materials in Two Dimensions

TL;DR

This paper explores energy minimization techniques and preconditioning methods to improve the simulation of dense, athermal granular materials, focusing on quasi-static conditions and phenomena like jamming and shear deformation.

Contribution

It introduces novel preconditioning techniques and evaluates their effectiveness in simulating granular media near critical states, such as jamming transition.

Findings

Preconditioning improves convergence of minimization algorithms.

Methods accurately capture jamming transition and scaling laws.

Enhanced simulation efficiency for dense granular systems.

Abstract

Granular materials are heterogenous grains in contact, which are ubiquitous in many scientific and engineering applications such as chemical engineering, fluid mechanics, geomechanics, pharmaceutics, and so on. Granular materials pose a great challenge to predictability, due to the presence of critical phenomena and large fluctuation of local forces. In this paper, we consider the quasi-static simulation of the dense granular media, and investigate the performances of typical minimization algorithms such as conjugate gradient methods and quasi-Newton methods. Furthermore, we develop preconditioning techniques to enhance the performance. Those methods are validated with numerical experiments for typical physically interested scenarios such as the jamming transition, the scaling law behavior close to the jamming state, and shear deformation of over jammed states.