A new MOX Report entitled “Portable, Massively Parallel Implementation of a Material Point Method for Compressible Flows” by Baioni, P.J.; Benacchio, T.; Capone, L.; de Falco, C. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/79-2024.pdf Abstract: The recent evolution of software and hardware technologies is leading to a renewed computational interest in Particle-In-Cell (PIC) methods such as the Material Point Method (MPM). Indeed, pro- vided some critical aspects are properly handled, PIC methods can be cast in formulations suitable for the requirements of data locality and fine-grained parallelism of modern hardware accelerators such as Graphics Processing Units (GPUs). Such a rapid and continuous technological development increases also the importance of generic and portable implementations. While the capabilities of MPM on a wide range continuum mechanics problem have been already well as- sessed, the use of the method in compressible fluid dynamics has re- ceived less attention. In this paper we present a portable, highly par- allel, GPU based MPM solver for compressible gas dynamics. The implementation aims to reach a good compromise between porta- bility and efficiency in order to ! provide a first assessment of the potential of this approach in solving strongly compressible gas flow problems, also taking into account solid obstacles. The numerical model considered constitutes a first step towards the development of a monolithic MPM solver for Fluid-Structure Interaction (FSI) problems at all Mach numbers up to the supersonic regime.
You may also like
A new MOX Report entitled “Efficient particle generation for depth-averaged and fully 3D MPM using TIFF image data” by Fois, M.; de […]
A new MOX Report entitled “Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures” by Fresca, […]
A new MOX Report entitled “Discontinuous Galerkin time integration for second-order differential problems: formulations, analysis, and analogies” by Ciaramella, G.; Gander, M.J.; […]
A new MOX Report entitled “Discovering Artificial Viscosity Models for Discontinuous Galerkin Approximation of Conservation Laws using Physics-Informed Machine Learning” by Caldana, […]