Title of article :
Reverse adaptivity - a new evolutionary tool for structural optimization
Author/Authors :
D. Reynolds، نويسنده , , J. McConnachie، نويسنده , , J. Trevelyan and P. Bettess، نويسنده , , W. C. Christie، نويسنده , , J. W. Bull، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 1999
Pages :
24
From page :
529
To page :
552
Abstract :
This paper presents a new method, Reverse Adaptivity, for automatically generating solutions to initial design and redesign problems. The method is based on a combination of existing adaptive "nite element methods and evolutionary structural optimization methods. The usual di$culties inherent in structural optimization problems, and the shortcomings of the evolutionary methods in tackling these di$culties, are reviewed as a prelude to discussing Reverse Adaptivity. Once the initial "nite element problem is de"ned, the method proceeds with reverse adaptive analysis, which re"nes low stress regions of the "nite element mesh by element subdivision. Following this, any low stress subdivided elements are removed and the process is repeated. With successive decrements of adapted element size, the process satis"es many of the shortcomings of existing evolutionary optimization methods, yet is simple to understand and can be readily implemented. The results produced by the method are superior to those produced by existing methods, yet can be obtained with highly practicable computational resources. As a demonstration, solutions to a number of wellknown classical problems are presented, and highlight the methodʹs ability to distinguish new classes of solutions for some problems. Full implementation and parameter details are also presented
Keywords :
Shape optimization , Evolution , "nite element analysis , hard kill , topological optimization , reverse adaptivity , self-designing structures
Journal title :
International Journal for Numerical Methods in Engineering
Serial Year :
1999
Journal title :
International Journal for Numerical Methods in Engineering
Record number :
423780
Link To Document :
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