Common-substructure Approach Of Structural Topology Optimization Under Multiple Loading Cases

Structural topology optimization is widely accounted as a particular challenging research area instructural optimization discipline after sizing optimization and configuration optimization. Recently,Aerospace products are raising special demands for weight and markets are moving towards a morecompetitive direction, which contribute to the proliferation of the structural topology optimization inthese areas, as well as provide basic application of weight loss of aerospace typical structures. Aboveall, it is of important significance and value to do research on Continuum topology optimization.SIMP and RAMP are two kinds density penalty function interpolation model，which are widelyused in variable density method. But the unclear problem of the final topology structure caused byunreasonable selection of penalty function still exist, this paper presents a new model oftwo-parameter function interpolation and applies an improved filter technique, to achieve the updateof structural topology. Several numerical results of typical beam structure declare the feasibility andeffectiveness of this method. After that, some typical numerical instability phenomenon that existduring topology optimization process are elaborated, besides, the causes of these phenomenon andsome existing strategy to solve these problems are found out; then the appropriate range of the twoparameters (interpolation point and penalty factor) in the two-parameter interpolation function modelduring the update of the final topology results will be given.Finally, this paper puts forth a common-substructure approach to solve topology optimization ofsingle continuum structure under multiple loading cases and with multiple constraints. It employs theSIMP density interpolation model, is based on the idea of load carry path in the structure, and thenestablishes an algorithm to search the topology optimization solution of structure under multipleloading cases and with multiple constraints. Two typical examples were carried out and the resultsshow that the presented approach is high efficient and good effective.