Hale multidisciplinary ecodesign optimization with material selection

TL;DR

This paper presents a multidisciplinary optimization framework for drone design that integrates material selection from a discrete catalog using continuous variables, aiming to minimize CO2 footprint and weight.

Contribution

It introduces a novel method to include discrete material choices in MDO using continuous optimization techniques, applied to drone CO2 footprint reduction.

Findings

Optimal material reduces CO2 footprint and weight

Green surrogate materials must be nearly as light as traditional ones

Material choice significantly impacts drone environmental impact

Abstract

Multidisciplinary Design Optimization (MDO) makes it possible to reach a better solution than by optimizing each discipline independently. In particular, the optimal structure of a drone won't be the same depending on the material used. The CO2 footprint of a solar-powered High Altitude Long Endurance (HALE) drone is optimized here, the structural materials being one of the design variables. The optimization is preformed using a modified version of OpenAeroStruct, a framework based on OpenMDAO. The originality of this work is to include material choice from a discrete catalogue in the MDO approach. This is achieved through a continuous variable, enabling the use of continuous optimization algorithms. Our results show that, in our case, the optimal material in terms of CO2 footprint is also the optimal material in terms of weight. In order for a green surrogate material to enable a lower drone CO2 footprint, it must be almost as good in terms of weight.