Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing

Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing

In the field of parametric partial differential equations, shape optimization represents a challenging problem due to the required computational resources. In this contribution, a data-driven framework involving multiple reduction techniques is proposed to reduce such computational burden. Proper or...

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Bibliographic Details
Main Authors: Nicola Demo, Marco Tezzele, Andrea Mola, Gianluigi Rozza
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Journal of Marine Science and Engineering
Subjects:
shape optimization
reduced order modeling
high-dimensional optimization
parameter space reduction
computational fluid dynamics
Online Access:https://www.mdpi.com/2077-1312/9/2/185

Internet

https://www.mdpi.com/2077-1312/9/2/185

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