Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

Abstract

This paper presents a design automation process using optimization via a genetic algorithm to design the conceptual structure of a Lunar Pallet Lander. The goal is to determine a design that will have the primary natural frequencies at or above a target value as well as minimize the total mass. Several iterations of the process are presented. First, a concept optimization is performed to determine what class of structure would produce suitable candidate designs. From this a stiffened sheet metal approach was selected leading to optimization of beam placement through generating a two-dimensional mesh and varying the physical location of reinforcing beams. Finally, the design space is reformulated as a binary problem using 1dimensional beam elements to truncate the design space to allow faster convergence and additional mechanical failure criteria to be included in the optimization responses. Results are presented for each design space configuration. The final flight design was derived from these results.

Reusability Analysis for Lunar Landers

“…MDO has already been applied to a range of architectures including aircraft, launch vehicles, and mission profiles [28,29,30]. Within the area of lunar lander design, MDO has been used to calculate the optimal path to the lunar surface from cislunar orbit [31] and to optimize the design of lunar cargo landers [32,33].…”