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Numerical Modelling of Metal Forming by SPH with Multi-GPU Acceleration
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 02, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Large material distortion, plastic deformation and forging make the numerical modelling of metal forming a difficult task. Grid-based methods such as the Finite Element Method (FEM) are incapable of simulating this process as these schemes suffer from mesh distortion and mesh entanglement. The mesh-based numerical frameworks with discontinuous enrichment can model finite deformation problems with limited success. Moreover, the presence of flaws, multiple crack surfaces and their interaction make the simulation even more numerically and computationally intensive. In this regard, Lagrangian particle-based meshfree methods are more relevant. There exist several mesh-free methods and among these Smoothed Particle Hydrodynamics (SPH) is a truly meshfree method. In SPH the computational domain is discretised by a set of particles. A given particle interacts only with its neighbouring particles through a kernel function with a constant radius. The interaction between particles stops when the particles move out of each other’s influence domain. Due to the absence of mesh/grids, SPH is naturally equipped to handle large deformation problems. Based on SPH, a solver with multi GPU acceleration for modelling metal forming process is developed. SPH provides a detailed insight into the material deformation, accumulation of plastic strain, and material flow patterns. The effect of different parameters and their influence can also be investigated. The material hardening effects are considered. The presence of voids in the material, the asymmetry in the forging process, the material flaws and their interaction and evolution over time can be modelled accurately. In the present work, we discuss the current needs for a computational framework for metal forming, the limitations of existing simulation software and the potential advantages and disadvantages of SPH.
CitationIslam, M., Peng, C., and Eslamian, A., "Numerical Modelling of Metal Forming by SPH with Multi-GPU Acceleration," SAE Technical Paper 2019-01-1085, 2019, https://doi.org/10.4271/2019-01-1085.
Data Sets - Support Documents
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