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Elementary-level intrusive coupling of machine learning for efficient mechanical analysis of variable stiffness composite laminates: a spatially-adaptive fidelity-sensitive computational framework

Elementary-level intrusive coupling of machine learning for efficient mechanical analysis of variable stiffness composite laminates: a spatially-adaptive fidelity-sensitive computational framework
Elementary-level intrusive coupling of machine learning for efficient mechanical analysis of variable stiffness composite laminates: a spatially-adaptive fidelity-sensitive computational framework
0177-0667
Garg, A.
270ec1e5-3112-4a22-a6c2-1dd3dd67ab72
Naskar, S.
5f787953-b062-4774-a28b-473bd19254b1
Mukhopadhyay, T.
2ae18ab0-7477-40ac-ae22-76face7be475
Garg, A.
270ec1e5-3112-4a22-a6c2-1dd3dd67ab72
Naskar, S.
5f787953-b062-4774-a28b-473bd19254b1
Mukhopadhyay, T.
2ae18ab0-7477-40ac-ae22-76face7be475

Garg, A., Naskar, S. and Mukhopadhyay, T. (2024) Elementary-level intrusive coupling of machine learning for efficient mechanical analysis of variable stiffness composite laminates: a spatially-adaptive fidelity-sensitive computational framework. Engineering With Computers. (In Press)

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Accepted/In Press date: 27 October 2024

Identifiers

Local EPrints ID: 495894
URI: http://eprints.soton.ac.uk/id/eprint/495894
ISSN: 0177-0667
PURE UUID: 4b89f338-78a7-48dc-949a-030a188139d9
ORCID for S. Naskar: ORCID iD orcid.org/0000-0003-3294-8333

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Date deposited: 27 Nov 2024 17:32
Last modified: 28 Nov 2024 03:00

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Contributors

Author: A. Garg
Author: S. Naskar ORCID iD
Author: T. Mukhopadhyay

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