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A reinforcement learning approach to airfoil shape optimization
The literature is rich with illustrations where machine learning methods, when coupled with current airfoil shape optimization methods, have surpassed other gradient-based …
Nature.com[2202.07141] Machine Learning in Aerodynamic Shape …
View PDF Abstract: Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and …
Arxiv.orgMulti-fidelity deep learning for aerodynamic shape …
Aerodynamic shape design is essential for improving aircraft performance and efficiency. First, this study introduces a data-driven optimization framework utili
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These machine learning models are embedded in a surrogate-based aerodynamic optimization framework and perform aerodynamic shape optimization for airfoils and wings. …
Arc.aiaa.orgMachine learning-enabled parameterization scheme for …
This study proposes a machine learning-based scheme that can automatically learn a low-dimensional latent representation of complex aerodynamic shapes for bluff-body …
Koreascience.or.krManifold Learning for Aerodynamic Shape Design Optimization
For the fast aerodynamic shape optimization design framework based on a reduced-order model (ROM), the dimensionality of the design space becomes too high, …
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Link.springer.comA CNN-PINN-DRL driven method for shape …
Shape optimization of airfoils is crucial for enhancing the aerodynamic performance of large blades. Nowadays, the integration of computational fluid dynamics and intelligent optimization algorithm has …
Tandfonline.comAerodynamic shape optimization using graph variational …
The use of machine learning in aerodynamic shape optimization problems has significantly increased in recent years. While existing deep learning techniques enable efficient …
Link.springer.comPhysics-informed shape optimization using coordinate projection
Figure 2 illustrates the entire optimization framework that will be implemented to address the case studies aforementioned; it consists of a shape neural network \(NN_\phi \) …
Nature.comAerodynamic shape optimization using a novel optimizer based …
This paper proposes a novel optimizer for the challenging aerodynamic shape optimization problem using two machine learning techniques, namely reinforcement learning …
Sciencedirect.com(PDF) Machine Learning in Aerodynamic Shape Optimization
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued …
Researchgate.netAirfoil Shape Optimization using Deep Reinforcement Learning
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Arc.aiaa.orgA comprehensive deep learning geometric shape optimization …
In this context, deep learning has emerged as a promising tool for shape optimization. Deep learning methods have demonstrated remarkable capabilities in various …
Pubs.aip.org[2201.06210] Deep convolutional neural network for shape …
This article presents a reduced-order modeling methodology via deep convolutional neural networks (CNNs) for shape optimization applications. The CNN provides …
Arxiv.orgMachine learning for adjoint vector in aerodynamic shape
Shape optimization, such as Yan et al.[29, 30] built a DNN with the design variables of the rocket as the input and the corresponding changes as the output. However, there are strict limitations …
Arxiv.orgAn adaptive machine learning-based optimization method in the ...
Over the years, aerodynamic shape optimization (ASO) has become an important research area in reducing greenhouse gas emissions and aircraft fuel consumption. ... In this …
Sciencedirect.comA contact aware regularization technique for shape optimization
A novel regularization method for shape optimization of contacting structures is proposed. The shape optimization avoids parameterizations via splines or the level set method …
Link.springer.comEfficient aerodynamic shape optimization using transfer learning …
Computational efficiency and precision pose a classic contradiction in aerodynamic shape optimization. To address this challenge, this study introduces an effec ... Efficient …
Pubs.aip.orgImage-Based Laser-Beam Diagnostics Using Statistical Analysis …
This study is a comprehensive experimental and computational investigation into high-resolution laser beam diagnostics, combining classical statistical techniques, numerical …
Mdpi.comAllying topology and shape optimization through machine …
The most relevant techniques are topology and shape optimization. Topology optimization provides the optimal material distribution layout into a given, static, design …
Sciencedirect.com[2109.13337] DEBOSH: Deep Bayesian Shape Optimization
Computer Science > Machine Learning. arXiv:2109.13337 (cs) [Submitted on 28 Sep 2021 ... Hence, we propose a novel uncertainty-based method tailored to shape …
Arxiv.orgData-driven and unsupervised machine learning for …
Data-driven and unsupervised machine learning for comprehensive quality evaluation and intelligent optimization of multi-stage design in horizontal wells within shale reservoir. ...
Sciencedirect.comShape functional optimization with restrictions boosted with machine ...
Shape optimization is a widely used technique in the design phase of a product. Current ongoing improvement policies require a product to fulfill a series of conditions from the …
Sciencedirect.comModel Compression: Make Your Machine Learning Models Lighter …
Model pruning. Pruning is probably the most intuitive compression technique. The idea is very simple: remove some of the weights of the network, either randomly or remove the “less …
Towardsdatascience.comDevelopment and validation of machine learning models for …
To ensure optimal performance for each machine learning model, we used Bayesian optimization to tune the key model parameters and conducted 10 iterations to …
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