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research-article

L-System-Generated Mechanism Topology Optimization Using Graph-Based Interpretation

[+] Author and Article Information
Brent R Bielefeldt

Department of Aerospace Engineering, Texas A&M University, College Station, Texas 77843
brbielefeldt@tamu.edu

Ergun Akleman

Department of Vizualization, Texas A&M University, College Station, TX 77843
ergun.akleman@gmail.com

Gregory W. Reich

Aerospace Systems Directorate, US Air Force Research Laboratory, WPAFB, OH 45433
gregory.reich.1@us.af.mil

Philip Beran

Aerospace Systems Directorate, US Air Force Research Laboratory, WPAFB, OH 45433
philip.beran@us.af.mil

Darren Hartl

Department of Aerospace Engineering, Texas A&M University, College Station, Texas 77843
darren.hartl@tamu.edu

1Corresponding author.

ASME doi:10.1115/1.4042512 History: Received October 12, 2018; Revised January 10, 2019

Abstract

Traditional topology optimization techniques, such as density-based and level set methods, have proven success- ful in identifying potential design configurations for struc- tures and mechanisms but suffer from rapidly increasing de- sign space dimensionality and the possibility of converging 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 de- velopment of the structure when coupled with an interpreter to translate genomic information into structural topologies. This work discusses the development of a graph-based inter- pretation scheme referred to as Spatial Interpretation for the Development of Reconfigurable Structures (SPIDRS). This framework allows for the effective exploration of mechanism design spaces using a limited number of design variables. The theory and implementation of this method are detailed, and multiple case studies are presented to demonstrate the ability of SPIDRS to generate adaptive structures capable of achieving multiple design goals.

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