We propose a projection-based model order reduction procedure for a general class of parametric quasi-static problems in nonlinear mechanics with internal variables. The methodology is integrated in the industrial finite element code code aster. Model order reduction aims to lower the computational cost of engineering studies that involve the simulation to a costly high-fidelity differential model for many different parameters, which correspond, for example to material properties or initial and boundary conditions. We develop an adaptive algorithm based on a POD-Greedy strategy, and we develop an hyper-reduction strategy based on an element-wise empirical quadrature in order to speed up the assembly costs of the reduced-order model by building an appropriate reduced mesh. We introduce a cost-efficient error indicator which relies on the reconstruction of the stress field by a Gappy-POD strategy. We present numerical results for a three-dimensional elastoplastic system in order to illustrate and validate the methodology.
翻译:我们为非线性机械学中具有内部变量的一般参数准静态问题提出了一个基于预测的减少命令示范程序,该方法已纳入工业有限要素代码 aster; 减少命令的模型旨在将涉及模拟的工程研究的计算成本降低到对许多不同参数的昂贵的高不洁差异模型,该模型与物质性质或初始和边界条件等相对应; 我们根据POD-Greedy战略开发一种适应性算法,我们根据一个要素明智的经验二次计算,制定一种大幅度削减战略,以便通过建造一个适当的减缩网格加快减序模型的组装成本; 我们采用一个成本效益错误指标,依靠加皮-POD战略重建压力场; 我们提出三维弹性系统的数字结果,以说明和验证该方法。