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Optimization Module for Abaqus/CAE based on Genetic Algorithm

SIMULIA's picture

Genetic algorithms have become one of successful tools in design and topology optimization. The optimization module based on genetic algorithms was developed and employed in Abaqus/CAE by GUI and kernel scripting. The new module extends advanced functionality of Abaqus/CAE allowing to perform optimization directly in Abaqus Unified FEA product suite from SIMULIA. The genetic algorithms implemented in optimization approach are based on available GPL libraries. Significant improvement in evolving into optimal solution can be achieved when genetic algorithms are combined with neural networks which one can train by running Abaqus jobs, and substantially improve the efficiency of computations. In the paper the shape optimization problem of a tooth implant will be presented and discussed in detail. The particular Abaqus features useful in this application will be highlighted, as well. The presented approach seems to be extremely efficient in parallel computations.

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