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Probability-based unified sensitivity analysis for multi-objective performances of composite laminates: a surrogate-assisted approach

Probability-based unified sensitivity analysis for multi-objective performances of composite laminates: a surrogate-assisted approach
Probability-based unified sensitivity analysis for multi-objective performances of composite laminates: a surrogate-assisted approach

The present paper proposes a surrogate-assisted moment-independent stochastic sensitivity analysis of laminated composite plates for establishing a unified measure in the case of multi-objective performances. With the advancements in artificially engineered structural systems spanning across different length scales, it has become more common to design composite structures for multi-objective performances like the criteria of deflection, buckling and vibration of multiple modes, different impact parameters, and failure. Normally sensitivity analysis is carried out separately and individually for different such performance parameters. This paradigm is no more suitable for advanced multi-functional structures like composite laminates. In this article, we propose an efficient unified sensitivity analysis approach based on weighted relative importance of different performance parameters by introducing the notion of engineering judgment. A moment-independent sensitivity analysis is proposed here based on finite element modeling of composites in conjunction with the Least Angle Regression assisted Polynomial Chaos Expansion (PCE) to achieve computational efficiency without compromising the outcome. Such surrogate-assisted finite element approaches are particularly crucial for computationally intensive multi-objective systems like composites. The layer-wise unified sensitivity quantification of laminated composites considering multi-functional objectives, as presented here, would lead to more optimized designs and better quality control while manufacturing the complex advanced structural systems.

Layer-wise sensitivity of composite laminates, Machine learning in composites, Multi-objective performance of composites, Polynomial chaos expansion, Unified sensitivity analysis
0263-8223
Kushari, S.
be270505-67ef-4a98-9cdb-54026b8f0588
Mukhopadhyay, T.
2ae18ab0-7477-40ac-ae22-76face7be475
Chakraborty, A.
be13dce2-c2fe-46ed-98d0-19a004a27a55
Maity, S. R.
b948351d-4550-4588-82a7-f2ba60940419
Dey, S.
353abbc8-49c8-4e88-ab85-cf0531aa9342
Kushari, S.
be270505-67ef-4a98-9cdb-54026b8f0588
Mukhopadhyay, T.
2ae18ab0-7477-40ac-ae22-76face7be475
Chakraborty, A.
be13dce2-c2fe-46ed-98d0-19a004a27a55
Maity, S. R.
b948351d-4550-4588-82a7-f2ba60940419
Dey, S.
353abbc8-49c8-4e88-ab85-cf0531aa9342

Kushari, S., Mukhopadhyay, T., Chakraborty, A., Maity, S. R. and Dey, S. (2022) Probability-based unified sensitivity analysis for multi-objective performances of composite laminates: a surrogate-assisted approach. Composite Structures, 294, [115559]. (doi:10.1016/j.compstruct.2022.115559).

Record type: Article

Abstract

The present paper proposes a surrogate-assisted moment-independent stochastic sensitivity analysis of laminated composite plates for establishing a unified measure in the case of multi-objective performances. With the advancements in artificially engineered structural systems spanning across different length scales, it has become more common to design composite structures for multi-objective performances like the criteria of deflection, buckling and vibration of multiple modes, different impact parameters, and failure. Normally sensitivity analysis is carried out separately and individually for different such performance parameters. This paradigm is no more suitable for advanced multi-functional structures like composite laminates. In this article, we propose an efficient unified sensitivity analysis approach based on weighted relative importance of different performance parameters by introducing the notion of engineering judgment. A moment-independent sensitivity analysis is proposed here based on finite element modeling of composites in conjunction with the Least Angle Regression assisted Polynomial Chaos Expansion (PCE) to achieve computational efficiency without compromising the outcome. Such surrogate-assisted finite element approaches are particularly crucial for computationally intensive multi-objective systems like composites. The layer-wise unified sensitivity quantification of laminated composites considering multi-functional objectives, as presented here, would lead to more optimized designs and better quality control while manufacturing the complex advanced structural systems.

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More information

Accepted/In Press date: 4 April 2022
Published date: 15 August 2022
Additional Information: Funding Information: The authors would like to acknowledge the Aeronautics Research and Development Board (AR&DB), Government of India (Project Sanction no.: ARDB/01/105885/M/I) for the financial support for the present research work. TM gratefully acknowledges the initiation grant received from IIT Kanpur. Publisher Copyright: © 2022 Elsevier Ltd
Keywords: Layer-wise sensitivity of composite laminates, Machine learning in composites, Multi-objective performance of composites, Polynomial chaos expansion, Unified sensitivity analysis

Identifiers

Local EPrints ID: 483941
URI: http://eprints.soton.ac.uk/id/eprint/483941
ISSN: 0263-8223
PURE UUID: 3ed98041-b1e8-4848-8192-447c4afd4951
ORCID for T. Mukhopadhyay: ORCID iD orcid.org/0000-0002-0778-6515

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Date deposited: 07 Nov 2023 18:32
Last modified: 18 Mar 2024 04:10

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Contributors

Author: S. Kushari
Author: T. Mukhopadhyay ORCID iD
Author: A. Chakraborty
Author: S. R. Maity
Author: S. Dey

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