Lattice Discrete Particle Model (LDPM): Comparison of Various Time Integration Solvers and Implementations
This work provides a benchmark for researchers in computational mechanics to optimize LDPM implementations, but it is incremental as it focuses on comparing existing methods rather than introducing new ones.
The paper compares various implementations of the Lattice Discrete Particle Model (LDPM) for simulating concrete and quasibrittle materials, evaluating transient implicit, explicit, and static solvers on CPU and GPU across benchmark tests, with results including computational times, energy balance errors, and crack pattern correlations.
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.