Lattice Discrete Particle Model (LDPM): Comparison of Various Time Integration Solvers and Implementations

TL;DR

This paper compares various CPU and GPU implementations of the LDPM for simulating heterogeneous materials, evaluating their accuracy, efficiency, and stability across multiple benchmark tests.

Contribution

It provides a comprehensive comparison of different time integration solvers and implementations for LDPM, including open source code and detailed benchmark data.

Findings

GPU implementations are faster than CPU counterparts.

Explicit solvers perform well for dynamic problems.

Steady-state solvers are effective for static responses.

Abstract

This article presents a comparison of various implementations of the Lattice Discrete Particle Model (LDPM) for the numerical simulation of concrete and other heterogeneous quasibrittle materials. The comparison involves the use of transient implicit and explicit solvers and steady-state (static) solvers and implementations for Central Processing Unit (CPU) as well as Graphics Processing Unit (GPU). The various implementations are compared on the basis of a set of benchmarks tests describing behaviors of increasing computational complexity. They include elastic vibrations, confined strain-hardening compressive response, tensile fracture, and unconfined strain-softening compressive response. Metrics of interest extracted from the simulations include macroscopic stress versus strain responses, computational times, number of iterations, and energy balance error. Pairwise comparison of final crack patterns is provided through the correlation coefficient and normalized root mean square error of the crack opening vectors. Moreover, for the most numerically challenging case of unconfined compression with sliding boundary conditions, the stability of the strain-softening response is tested by perturbing the solutions as well as changing the convergence criteria and time step size. Attached to this paper is the complete input data of the benchmark tests; this will allow researchers to run the examples and compare them with their own implementations. In addition, most of the reported implementations are publicly available in open source packages.