A feature-driven robust topology optimization strategy considering movable non-design domain and complex uncertainty

Abstract

With the diversification of engineering structure performance requirements and the continuous development of refinement of processing and manufacturing, structural design is faced with more and more factors to be considered. By quantifying the important features of non-design domain location and parameter uncertainty, a feature-driven robust topology optimization strategy considering movable non-design domain and complex uncertainty is proposed. Firstly, the influence of non-design domain on structural topology is quantified by a shape description function. The slight boundary discontinuity caused by non-design domain is further solved. In addition, the mathematical properties of structural response about uncertainty are analyzed, and vertex method and subinterval dimension-wise method are adopted to quantify the influence of uncertainties. Finally, the sensitivity of the robust optimization model is derived based on the shape derivative principle, which provides the basis for the implementation of gradient based optimization algorithm. Three examples illustrate the effectiveness, necessity and influence of important parameters of the topology optimization method considering movable non-design domain and complex uncertainty from different aspects.