Implementation and utilisation of a Grid-enabled problem solving environment in Matlab

被引:20
作者
Eres, MH [1 ]
Pound, GE [1 ]
Jian, Z [1 ]
Wason, JL [1 ]
Xu, FL [1 ]
Keane, AJ [1 ]
Cox, SJ [1 ]
机构
[1] Univ Southampton, Sch Engn Sci, Southampton SO17 1BJ, Hants, England
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2005年 / 21卷 / 06期
基金
英国工程与自然科学研究理事会;
关键词
engineering design optimisation; computational fluid dynamics; problem solving environment; Matlab software; Grid computing;
D O I
10.1016/j.future.2003.12.016
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In many areas of design search and optimisation one needs to utilise computational fluid dynamics (CFD) methods in order to obtain a numerical solution of the flow field in and/or around a proposed design. From this solution measures of quality for the design may be calculated, which are then used by the optimisation methods. In large models the processing time for the CFD computations can very well be many orders of magnitude larger than for the optimisation methods themselves; and the overall optimisation process usually demands a combination of computational and database resources; therefore this class of problems is well suited to Grid computing. The Geodise toolkit is a suite of tools for Grid-enabled parametric geometry generation, meshing, CFD analysis, design optimisation and search, databasing, Grid computing, and notification within the Matlab environment. These Grid services are presented to the design engineer as Matlab functions that conform to the usual syntax of Matlab. The use of the Geodise toolkit in Matlab introduces a flexible and Grid-enabled problem solving environment (PSE) for design search and optimisation. This PSE is illustrated here with two exemplar problems. (c) 2003 Elsevier B.V All rights reserved.
引用
收藏
页码:920 / 929
页数:10
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