Reliability Topology Optimization of Collaborative Design for Complex Products Under Uncertainties Based on the TLBO Algorithm

Abstract

The topology optimization design of complex products can significantly improve material and power savings, and reduce inertial forces and mechanical vibrations effectively. In this study, a large-tonnage hydraulic press was chosen as a typically complex product to present the optimization method. We propose a new reliability topology optimization method based on the reliability-and-optimization decoupled model and teaching–learning-based optimization (TLBO) algorithm. The supports formed by the plate structure are considered as topology optimization objects, characterized by light weight and stability. The reliability optimization under certain uncertainties and structural topology optimization are processed collaboratively. First, the uncertain parameters in the optimization problem are modified into deterministic parameters using the finite difference method. Then, the complex nesting of the uncertainty reliability analysis and topology optimization are decoupled. Finally, the decoupled model is solved using the TLBO algorithm, which is characterized by few parameters and a fast solution. The TLBO algorithm is improved with an adaptive teaching factor for faster convergence rates in the initial stage and performing finer searches in the later stages. A numerical example of the hydraulic press base plate structure is presented to underline the effectiveness of the proposed method.

Keywords

• Plates structure
• Reliability
• Collaborative topology optimization
• Teaching–learning-based optimization algorithm
• Uncertainty
• Collaborative design for product life cycle