L-System-Generated Topology Optimization of Compliant Mechanisms Using Graph-Based Interpretation

Abstract

Traditional topology optimization techniques, such as density-based and level set methods, have proven successful in identifying potential design configurations but suffer from rapidly increasing design space dimensionality and convergence to local minima. A heuristic alternative to these approaches couples a genetic algorithm with a Lindenmayer System (L-System), which encodes design variables and governs the development of the structure when coupled with some sort of interpreter. This work discusses the development of a graph-based interpretation scheme referred to as Spatial Interpretation for the Development of Reconfigurable Structures (SPIDRS). This framework allows for the effective exploration of the design space using a limited number of design variables. The theory and implementation of this method are detailed, and a compliant mechanism case study is presented to demonstrate the ability of SPIDRS to generate structures capable of achieving multiple design goals.