Development and validation of a genetic L-System programming framework for topology optimization of multifunctional structures

•Bio-inspired topology optimization method based on an L-System formal grammar.•Coupled with genetic algorithm to generated families of complex branched topologies.•Framework evaluated using both conventional and multifunctional benchmark problems.•Designs validated against physical prototypes to ensure framework creates realistic structures. When considering the complex problem of developing new multifunctional structures, it is essential to narrow the vast design space and reduce the infinite number of possible solutions to a finite subset of feasible designs. Nature provides examples of ramified, or branched, topologies that form non-intuitive solutions to various structural design problems. This work focuses on the development of a bio-inspired topology optimization framework that couples genetic algorithms with a parallel rewriting system known as a Lindenmayer System (or L-System), which acts as an analogy to the evolutionary process and formalizes the encoding of a 2-D structure. Example design problems and the solutions determined using this novel framework are presented and compared to ideal solutions, where it is shown that a family of branched solutions allowed to evolve over generations can eventually arrive at effective multifunctional structures. Select designs from each example problem are also thickened into 3-D bodies, which are assessed experimentally via fully functional prototypes, demonstrating that the L-System framework is capable of generating realistic solutions for multifunctional structure development.