Multi-Objective Optimization of Thin-Walled Composite Axisymmetric Structures Using Neural Surrogate Models and Genetic Algorithms

Multi-Objective Optimization of Thin-Walled Composite Axisymmetric Structures Using Neural Surrogate Models and Genetic Algorithms

Composite shells find diverse applications across industries due to their high strength-to-weight ratio and tailored properties. Optimizing parameters such as matrix-reinforcement ratio and orientation of the reinforcement is crucial for achieving the desired performance metrics. Stochastic optimiza...

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Bibliographic Details
Main Authors: Bartosz Miller, Leonard Ziemiański
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Materials
Subjects:
shell
composite
optimization
surrogate model
genetic algorithms
artificial neural networks
Online Access:https://www.mdpi.com/1996-1944/16/20/6794

Internet

https://www.mdpi.com/1996-1944/16/20/6794

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