IDO Syunji Saitama Univ.・Associate Professor, 工学部, 助教授 (40135752)
BEN Goichi Nihon Univ.・Professor, 生産工学部, 教授 (90060079)
SAKAI Yuzuru Yokohama National Univ.・Associate Professor, 工学部, 助教授 (90114975)
KANTO Yasuhiro Toyohashi Univ.of Tech.・Associate Professor, エネルギー工学系, 助教授 (60177764)
FURUKAWA Tomonari The Univ.of Tokyo・Assistant, 大学院・工学系研究科, 助手 (10272395)
OKUDA Hiroshi The Univ.of Tokyo・Professor, 大学院・工学系研究科, 助教授 (90224154)
YOSHIMURA Shinobu The Univ.of Tokyo・Associate Professor, 大学院・工学系研究科, 助教授 (90201053)
ATLURI Satya N. Georgia Inst.of Tech.・Associate Professor, コンピューテーショナル モデリングセンター, 教授
|Budget Amount *help
¥4,100,000 (Direct Cost : ¥4,100,000)
Fiscal Year 1995 : ¥4,100,000 (Direct Cost : ¥4,100,000)
For overcoming the limitation of the computational power by the vector-pipeline, shared memory-type supercomuputer, trend in the supercomputer development is towards the massively parallel platform with the distributed memory. This study aims at the high-performance computing, which can make the best use of the massively parallel processors. Research subjects consist of two approaches ; one is to apply the conventional and/or currently available software to the massively parallel environments and to attain the high scalability, and the other is to develop the innovative algorithms, which are suitable for the massively parallel platform.
First, in the CFD (Computational Fluid Dynamics) area, a CFD code, which is constructed on an EBE (Element-by-Element) basis, is ported to KSR1 or T3D.The inherent parallelism of the EBE code was observed. Also, an unstructured multi-color method is proposed, and implemented in the neural network solver with the feedback mechanism. The neuro-solver is us
ed to solve the Poisson's equation for pressure.
Secondly, a meshless method is proposed, which needs only nodal data for computations, and hence avoids burdensome mesh generation process. Comparing with the conventional FEM,which utilizes the Delaunay triangulation, its accuracy and efficiency are investigated. The applicability of the meshless method to the massively parallel platform is also examined. The meshless method is furthermore enhanced to realize the adaptive analysis and the fluid analysis, both of which can take good advantage of the meshless nature. As another type of meshless method, a parallel cooperationtype type FEM is proposed. Incorporating the idea of the artificial life, i.e.agent, cooperationtype type automatic mesh generation is realized.
Finally, the evolutional algorithm in the continuum space search is proposed, and is applied to an inverse problem, i.e.the parameter identification for constitutive equations. Parallel nature of the evolutional algorithm is also investigated. Less