Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

A novel parallel method for layup optimization of composite structures with ply drop-offs

Liu, Xiaoyang, Featherston, Carol A. ORCID: https://orcid.org/0000-0001-7548-2882 and Kennedy, David ORCID: https://orcid.org/0000-0002-8837-7296 2023. A novel parallel method for layup optimization of composite structures with ply drop-offs. Composite Structures 312 , 116853. 10.1016/j.compstruct.2023.116853

[thumbnail of 1-s2.0-S0263822323001976-main.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview

Abstract

This paper presents a novel parallel optimization method for obtaining blended layups of composite laminates which closely match target lamination parameters. Firstly, a guide-based adaptive genetic algorithm (GAGA) which stochastically searches the layups is developed. Then the parallel optimization method DLBB-GAGA is developed by combining GAGA and a dummy layerwise branch and bound method (DLBB) which performs logic-based search in a parallel computation, during which optimization information is shared between the two methods. The combination of these two different methods gives the parallel DLBB-GAGA method the advantages of both, enhancing the searching ability for the blended layup optimization. The superiority of the parallel DLBB-GAGA method is demonstrated through comparisons between the three methods, and it is concluded that the method is particularly effective for practical design where more layup design constraints are considered.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0263-8223
Date of First Compliant Deposit: 21 February 2023
Date of Acceptance: 17 February 2023
Last Modified: 06 Jan 2024 03:48
URI: https://orca.cardiff.ac.uk/id/eprint/157180

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics