Multi-scale Least-Weight Design of a Wing-Box Through a Global/Local Modelling Approach

Enrico Panettieri, Marco Montemurro (), Daniele Fanteria and Francesco Coccia
Additional contact information
Enrico Panettieri: Université de Bordeaux
Marco Montemurro: Université de Bordeaux
Daniele Fanteria: Università di Pisa, Dipartimento di Ingegneria Civile e Industriale
Francesco Coccia: Università di Pisa, Dipartimento di Ingegneria Civile e Industriale

Journal of Optimization Theory and Applications, 2020, vol. 187, issue 3, No 8, 776-799

Abstract: Abstract In this work, a multi-scale optimization strategy for lightweight structures, based on a global-local modelling approach is presented. The approach is applied to a realistic wing structure of a civil aircraft. The preliminary design of the wing can be formulated as a constrained optimization problem, involving several requirements at the different scales of the structure. The proposed strategy is characterized by two main features. Firstly, the problem is formulated in the most general sense, by including all design variables involved at each problem scale. Secondly, two scales are considered: (i) the structure macroscopic scale, where low-fidelity numerical models are used; (ii) the structure mesoscopic scale (or component-level), where enhanced models are involved. In particular, the structural responses are evaluated at both global and local scales, avoiding the use of approximated analytical methods. To this end, fully parametric global and local finite element models are interfaced with an in-house genetic algorithm. Refined models are created only for the most critical regions of the structure, and linked to the global one by means of a dedicated sub-modelling approach.

Keywords: Optimization; Genetic algorithms; Wing; Stiffened panels; Global/local modelling approach; 90C26; 90C30; 90C31; 90C90; 74S05; 74K99 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-020-01693-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:187:y:2020:i:3:d:10.1007_s10957-020-01693-y

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-020-01693-y

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().