CO2 footprint minimization of solar-powered HALE using MDO and eco-material selection

Multidisciplinary Design Optimization (MDO) enables one to reach a better solution than by optimizing each discipline independently. In particular, the optimal structure of a drone varies depending on the selected material. The C O 2 footprint of a solar-powered High Altitude Long Endurance (HALE) d...

Full description

Saved in:
Bibliographic Details
Published in:Scientific reports Vol. 13; no. 1; p. 11994
Main Authors: Duriez, Edouard, Guadaño Martín, Víctor Manuel, Morlier, Joseph
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 01.12.2023
Nature Publishing Group
Subjects:
639/166/984
639/166/988
Carbon dioxide
Carbon footprint
Design optimization
Humanities and Social Sciences
Mathematics
multidisciplinary
Physics
Science
Science (multidisciplinary)
Topology
ISSN:2045-2322, 2045-2322
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Multidisciplinary Design Optimization (MDO) enables one to reach a better solution than by optimizing each discipline independently. In particular, the optimal structure of a drone varies depending on the selected material. The C O 2 footprint of a solar-powered High Altitude Long Endurance (HALE) drone is optimized here, where the structural materials used is one of the design variables. Optimization is performed using a modified version of OpenAeroStruct, a framework based on OpenMDAO. Our EcoHale framework is validated on a classical HALE testcase in the MDO community (FBhale) constructed using high-fidelity codes compared to our low-fidelity approach. The originality of our work is to include two specific disciplines (energy and environment) to adapt to a new problem of C O 2 minimization. The choice of eco-materials is performed in the global MDO loop from a choice of discrete materials . This is achieved through a variable relaxation, enabling the use of continuous optimization algorithms inspired from multimaterial topology optimization. Our results show that, in our specific case of electric drone, the optimal material in terms of C O 2 footprint is also the optimal material in terms of weight. It opens the door to new researches on digital microarchitectured materials that will decrease the C O 2 footprint of the drone.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-39221-3