On Multiple-Material Optimal Compliant Topologies: Discrete Variable Parameterization Using Genetic Algorithm Available to Purchase

Ideally, topology design problems are posed in binary form wherein density-like parameters, that model material properties, assume values corresponding to either no material or material state at a point in the continuum. However, to facilitate the use of calculus-based algorithms, which rely on gradient information for their search, the densities are often relaxed and posed as continuous interpolating functions between the two states. An alternative is to employ an algorithm that uses only the function information as its search criteria while strictly maintaining the original binary form. Genetic algorithm, which simulates nature’s mechanism of natural selection and survival of the fittest, is employed in this paper for topology optimization of compliant mechanisms. The algorithm is capable of converging to a global optimum, and therefore, is additionally beneficial as the design spaces for compliant mechanisms are often multi-modal. During the search, a barrier assignment approach is employed for densities to assume values corresponding only to the material or no material states. A cardinal advantage is the generalization to multiple-material modeling that enables suitable juxtaposition of flexible and stiff material in optimal compliant topology design and is supplemented well by modern manufacturing techniques. Numerous synthesis examples are solved, both with two and multiple material models, to illustrate the efficacy of the proposed method for the design of compliant continua. The approach is generic and can be employed to any topology design problem at hand and with any finite element approximation to the continuum.