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Physics-Informed Feature-to-Feature Learning for Design-Space Dimensionality Reduction in Shape Optimisation

https://doi.org/10.2514/6.2021-1235
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-85829-1openalex-snapshot
Boundary-Layer Theory
inferredcites →https://doi.org/10.1007/s11081-019-09477-8openalex-snapshot
A multi-criteria based selection method using non-dominated sorting for genetic algorithm based design
inferredcites →https://doi.org/10.1016/j.cad.2018.03.003openalex-snapshot
Sampling CAD models via an extended teaching–learning-based optimization technique
inferredcites →https://doi.org/10.1016/j.cad.2019.02.003openalex-snapshot
A Generative Design and Drag Coefficient Prediction System for Sedan Car Side Silhouettes based on Computational Fluid Dynamics
inferredcites →https://doi.org/10.1016/j.cma.2014.10.042openalex-snapshot
Design-space dimensionality reduction in shape optimization by Karhunen–Loève expansion
inferredcites →https://doi.org/10.1016/j.jmp.2018.03.001openalex-snapshot
A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions
inferredcites →https://doi.org/10.1016/j.oceaneng.2017.03.013openalex-snapshot
A novel design framework for generation and parametric modification of yacht hull surfaces
inferredcites →https://doi.org/10.1016/j.oceaneng.2019.106462openalex-snapshot
GenYacht: An interactive generative design system for computer-aided yacht hull design
inferredcites →https://doi.org/10.1016/j.oceaneng.2019.106852openalex-snapshot
Design-space assessment and dimensionality reduction: An off-line method for shape reparameterization in simulation-based optimization
inferredcites →https://doi.org/10.1016/j.proeng.2012.09.551openalex-snapshot
Modal Assurance Criterion
inferredcites →https://doi.org/10.1016/j.ress.2017.01.013openalex-snapshot
Global sensitivity metrics from active subspaces
inferredcites →https://doi.org/10.1115/1.4028273openalex-snapshot
A Shape Parameterization Method Using Principal Component Analysis in Applications to Parametric Shape Optimization
inferredcites →https://doi.org/10.1115/1.4033427openalex-snapshot
Improving Design Preference Prediction Accuracy Using Feature Learning
inferredcites →https://doi.org/10.1115/1.4036134openalex-snapshot
Design Manifolds Capture the Intrinsic Complexity and Dimension of Design Spaces
inferredcites →https://doi.org/10.1115/1.4043678openalex-snapshot
Evolving a Psycho-Physical Distance Metric for Generative Design Exploration of Diverse Shapes
inferredcites →https://doi.org/10.1115/1.4044076openalex-snapshot
Synthesizing Designs With Interpart Dependencies Using Hierarchical Generative Adversarial Networks
inferredcites →https://doi.org/10.1137/1.9781611973860openalex-snapshot
Active Subspaces
inferredcites →https://doi.org/10.1145/3072959.2983618openalex-snapshot
Retrieval on Parametric Shape Collections
inferredcites →https://doi.org/10.1145/3197517.3201325openalex-snapshot
Learning three-dimensional flow for interactive aerodynamic design
inferredcites →https://doi.org/10.2514/6.2014-1171openalex-snapshot
Active Subspaces for Shape Optimization
inferredcites →https://doi.org/10.2514/6.2016-4294openalex-snapshot
On Active Subspaces in Car Aerodynamics
inferredcites →https://doi.org/10.2514/6.2018-1648openalex-snapshot
Deep Autoencoder for Off-Line Design-Space Dimensionality Reduction in Shape Optimization
inferredcites →https://doi.org/10.2514/6.2018-3416openalex-snapshot
Shape Optimization under Stochastic Conditions by Design-space Augmented Dimensionality Reduction
inferredcites →https://doi.org/10.2514/6.2019-2218openalex-snapshot
Stochastic Shape Optimization via Design-Space Augmented Dimensionality Reduction and RANS Computations
inferredcites →https://doi.org/10.48550/arxiv.1408.0545openalex-snapshot
Computing active subspaces with Monte Carlo
inferredcites →https://doi.org/10.5267/j.ijiecopenalex-snapshot
international journal of industrial engineering computations
inferredcites →https://doi.org/10.5267/j.ijiec.2015.8.004openalex-snapshot
Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems
inferredcites →https://doi.org/10.5957/josr.09180056openalex-snapshot
Assessing the Interplay of Shape and Physical Parameters by Unsupervised Nonlinear Dimensionality Reduction Methods

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3987061openalex-extracted
Geometric Moment-Dependent Sensitivity Analysis for Shape Optimisation Without Simulation Data: Application to Ship Design
inferred← citeshttps://doi.org/10.1002/nme.7159openalex-snapshot
A multifidelity approach coupling parameter space reduction and nonintrusive POD with application to structural optimization of passenger ship hulls
inferred← citeshttps://doi.org/10.1016/j.aei.2021.101314openalex-snapshot
From regional sensitivity to intra-sensitivity for parametric analysis of free-form shapes: Application to ship design
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2021.109406openalex-snapshot
A reduced order data-driven method for resistance prediction and shape optimization of hull vane
inferred← citeshttps://doi.org/10.1016/j.renene.2021.04.005openalex-snapshot
Machine learning-based surrogate model for accelerating simulation-driven optimisation of hydropower Kaplan turbine
inferred← citeshttps://doi.org/10.1038/s44172-024-00289-yopenalex-snapshot
A rapid-convergent particle swarm optimization approach for multiscale design of high-permeance seawater reverse osmosis systems
inferred← citeshttps://doi.org/10.1109/icai52203.2021.9445243openalex-snapshot
A Data-Driven Interactive System for Aerodynamic and User-centred Generative Vehicle Design
inferred← citeshttps://doi.org/10.3390/jmse9090955openalex-snapshot
Application of Improved Particle Swarm Optimisation Algorithm in Hull form Optimisation
inferred← citeshttps://doi.org/10.3390/machines14060708openalex-snapshot
On the Role of Feature Extraction in Transformer PD Severity Classification: A Controlled Comparison of PCA and Autoencoder Models
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