Computational Grid Optimization in Engineering

网格生成、再分配和自适应细化已经成为当前计算工程的重要方面。随着先进超级计算机的快速发展，大规模的二维和三维问题现在可以用适当的网格分辨率来解决。为了可靠有效地使用相关的有限元或有限差分方法，我们需要改进网格生成方案和算法来进行网格的重新分配和细化。这个研究项目是针对这个问题的网格优化使用重新分配和细化策略。从最优化理论中的非线性规划问题的角度来研究这一问题。研究的重点将是近似方法和算法的发展，以及加速网格优化过程的技术，包括子域上的并行处理。关键技术问题是：网格的再分配与优化、局部自适应网格细化和移动网格的重划分方案。机构支持充足，研究人员是在计算工程领域有重大贡献的资深研究人员。

Grid generation, redistribution and adaptive refinement have emerged as important current aspects of computational engineering. With the rapid evolution of advanced supercomputers, large-scale 2-D and 3-D problems can now be addressed with appropriate grid resolution. To use the associated finite element or finite difference methods reliably and efficiently, we need improved grid-generation schemes and algorithms for grid redistribution and refinement. This research project is directed towards this problem of grid optimization using both redistribution and refinement strategies. The problem is approached from the viewpoint of nonlinear programming problems in optimization theory. The focus of the research will be the development of approximate methods and algorithms as well as techniques for acceleration of the grid optimization procedures including parallel processing on subdomains. The key technical issues are: grid redistribution and optimization, local adaptive grid refinement and remeshing schemes for moving grids. The institutional support is adequate and the investigation is a senior researcher with significant contributions in computational engineering.