Comparison of Lattice Discrete Particle Model (LDPM) Implementations: Lessons Learned and Future Work

Comparison of Lattice Discrete Particle Model (LDPM) Implementations: Lessons Learned and Future Work

Stať ve sborníku mimo WoS a Scopus

The Lattice Discrete Particle Model (LDPM) is a discrete mesoscale model of concrete that can accurately describe the macroscopic behavior of concrete during elastic, fracturing, softening, and hardening regimes. The LDPM formulation is obtained by modeling the interaction among coarse meso-scale aggregate pieces between polyhedral cells (each containing one aggregate particle) whose external surfaces are defined by sets of triangular facets. At each facet, a vectorial form of constitutive model is used to simulate physical mechanisms such as tensile fracture, cohesion, friction, etc. LDPM has been calibrated and validated extensively through the analysis of a large variety of experimental tests. Numerical results show that it can reproduce with great accuracy the response of concrete under uniaxial and multiaxial stress states in both compression and tension and under both quasi-static and dynamic loading conditions. In this presentation, we will give an overview of recent implementations of LDPM in various computational platforms. LDPM was implemented in the following software packages: Abaqus/Explicit via user subroutine; Project Chrono, a physics-based modeling and simulation infrastructure based on a platform-independent open-source design; Cast3m a multi-physics software developed by CEA; Open Academic Solver, an open-source software developed at Brno University; JAX-LDPM, an open-source GPU-based software in active development by researchers from the Hong Kong University of Science and Technology; and FE-MultiPhys, developed at Virginia Tech. The different implementations will be compared by simulating typical failure tests for concrete, including, unconfined compression test, three-point bending test, and direct tensile test. Finally, the presentation will provide a vision for future LDPM developments that will likely be implemented in these software packages.

The Lattice Discrete Particle Model (LDPM) is a discrete mesoscale model of concrete that can accurately describe the macroscopic behavior of concrete during elastic, fracturing, softening, and hardening regimes. The LDPM formulation is obtained by modeling the interaction among coarse meso-scale aggregate pieces between polyhedral cells (each containing one aggregate particle) whose external surfaces are defined by sets of triangular facets. At each facet, a vectorial form of constitutive model is used to simulate physical mechanisms such as tensile fracture, cohesion, friction, etc. LDPM has been calibrated and validated extensively through the analysis of a large variety of experimental tests. Numerical results show that it can reproduce with great accuracy the response of concrete under uniaxial and multiaxial stress states in both compression and tension and under both quasi-static and dynamic loading conditions. In this presentation, we will give an overview of recent implementations of LDPM in various computational platforms. LDPM was implemented in the following software packages: Abaqus/Explicit via user subroutine; Project Chrono, a physics-based modeling and simulation infrastructure based on a platform-independent open-source design; Cast3m a multi-physics software developed by CEA; Open Academic Solver, an open-source software developed at Brno University; JAX-LDPM, an open-source GPU-based software in active development by researchers from the Hong Kong University of Science and Technology; and FE-MultiPhys, developed at Virginia Tech. The different implementations will be compared by simulating typical failure tests for concrete, including, unconfined compression test, three-point bending test, and direct tensile test. Finally, the presentation will provide a vision for future LDPM developments that will likely be implemented in these software packages.

Lattice discrete particle, heterogeneity, explicit solver, implicit solver, numerical implementation

Lattice discrete particle, heterogeneity, explicit solver, implicit solver, numerical implementation

LALE, E.; YU, K.; TROEMNER, M.; PATHIRAGE, M.; PIJAUDIER-CABOT, G.; KHOURY, J.; KOUTROMANOS, I.; ELIÁŠ, J.; STŘEDULOVÁ, M.; XUE, T.; ALNAGGAR, M.; DI LUZIO, G.; CUSATIS, G.

25.04.2025

IA-FraMCoS

978-3-903039-01-8

1

9

9

http://framcos.org/FraMCoS-12/Full-Papers/1299.pdf

http://hdl.handle.net/11012/255731