Finite elements, genetic algorithms and &bgr;-splines: a combined technique for shape optimization
Finite Elements in Analysis and Design
Finite Elements in Analysis and Design
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
CEA'07 Proceedings of the 2007 annual Conference on International Conference on Computer Engineering and Applications
Finite Elements in Analysis and Design
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The research presented here utilises the 'Generalised Frost-Dugdale law' with a genetic algorithm in a numerical three-dimensional fatigue based optimisation study of a 7050-T7451 aluminium structure. Genetic algorithm has been utilised in many stress based optimisation applications, however to date, it has not been used in a three dimensional structural fatigue based optimisation study involving short crack lengths. The generalised Frost-Dugdale law was developed to allow for the accurate prediction of fatigue crack growth from short crack lengths. Consequently, design against fatigue failure can include the analysis of near-threshold crack propagation. The structural optimisation procedure proposed integrates 3D geometrical modelling, structural analysis and optimization into one complete and automated computer-aided design process. This paper indicates that the proposed combined procedure provides a more accurate and robust optimised solution. It was discovered that the results resembled the solutions from other optimisation algorithms. As a result, this procedure illustrates a procedure for the design of light weight structures using a fatigue based optimisation in conjunction with a genetic algorithm. Furthermore, the possibility of the application of the generalised Frost-Dugdale model in design optimisation has been demonstrated.