This report investigates the utility of leading optimisation algorithms for the probabilistic optimisation of composite stiffened panels. Suitable algorithms were selected and applied to a mono-stringer subject to uncertainties in deterministic, robust-design and hybrid robust-reliable design formulations. Gradient, direct, evolutionary, genetic algorithm and combined algorithms were then rigorously compared for both speed and convergence properties. For simpler problems such as deterministic design, direct methods were found to dominate in both speed and accuracy. However, as problem complexity increased, exploratory methods were increasingly found to be superior for locating global optima. The recommendation for future research is therefore, to utilise hybrid uncertainty-based optimisation with a multi-island genetic algorithm to efficiently find lighter, stronger and more consistently performing designs for aircraft structures.
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26 November 2020
FRACTURE AND DAMAGE MECHANICS: Theory, Simulation and Experiment
15–17 September 2020
Mallorca, Spain
Research Article|
November 26 2020
Assessment of algorithms for the probabilistic optimisation of composite panels
Marij Qureshi;
Marij Qureshi
a)
Department of Aeronautics, Imperial College London
, United Kingdom
a)Corresponding author: [email protected]
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Kwangkyu Yoo;
Kwangkyu Yoo
b)
Department of Aeronautics, Imperial College London
, United Kingdom
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M. H. Ferri Aliabadi
M. H. Ferri Aliabadi
c)
Department of Aeronautics, Imperial College London
, United Kingdom
Search for other works by this author on:
Marij Qureshi
a)
Kwangkyu Yoo
b)
M. H. Ferri Aliabadi
c)
Department of Aeronautics, Imperial College London
, United Kingdom
a)Corresponding author: [email protected]
b)
Electronic mail: [email protected]
c)
Electronic mail: [email protected]
AIP Conf. Proc. 2309, 020045 (2020)
Citation
Marij Qureshi, Kwangkyu Yoo, M. H. Ferri Aliabadi; Assessment of algorithms for the probabilistic optimisation of composite panels. AIP Conf. Proc. 26 November 2020; 2309 (1): 020045. https://doi.org/10.1063/5.0034767
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