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

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 b...

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Published inFuture generation computer systems Vol. 21; no. 6; pp. 920 - 929
Main Authors Hakki Eres, M., Pound, Graeme E., Jiao, Zhouan, Wason, Jasmin L., Xu, Fenglian, Keane, Andy J., Cox, Simon J.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.06.2005
Subjects
Computational fluid dynamics
Engineering design optimisation
Grid computing
Matlab software
Problem solving environment
Grid computing
Engineering design optimisation
Computational fluid dynamics
Problem solving environment
Matlab software
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Abstract 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.
AbstractList 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.
Author Hakki Eres, M.
Keane, Andy J.
Jiao, Zhouan
Pound, Graeme E.
Wason, Jasmin L.
Xu, Fenglian
Cox, Simon J.
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Keywords Grid computing
Engineering design optimisation
Computational fluid dynamics
Problem solving environment
Matlab software
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Engineering design optimisation
Grid computing
Matlab software
Problem solving environment
Title Implementation and utilisation of a Grid-enabled problem solving environment in Matlab
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