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Monotonic Gaussian Process for Physics-Constrained Machine Learning With Materials Science Applications
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Physics-constrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods ...
An Analytical Model of Four Point Contact Rolling Element Ball Bearings
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The purpose of this work is to establish an analytical model and standard way to predict the performance characteristics of a fourpoint contact, or gothic arch type, rolling element ball bearing. Classical rolling element ...
An Efficient First-Principles Saddle Point Searching Method Based on Distributed Kriging Metamodels
Publisher: The American Society of Mechanical Engineers (ASME)
Monotonic Gaussian Process for PhysicsConstrained Machine Learning With Materials Science Applications
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Physicsconstrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods ...
sMF-BO-2CoGP: A Sequential Multi-Fidelity Constrained Bayesian Optimization Framework for Design Applications
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Bayesian optimization (BO) is an efiective surrogate-based method that has been widely used to optimize simulation-based applications. While the traditional Bayesian optimization approach only applies to single-fidelity ...
Erratum: “sMF-BO-2CoGP: A Sequential Multi-Fidelity Constrained Bayesian Optimization Framework for Design Applications” [ASME J. Comput. Inf. Sci. Eng., 20(3), p. 0031007; DOI: 10.1115/1.4046691]
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This article was intended to be published as part of the October 2020 Special Issue on Highlights of 2020 CIE Conference.
srMO-BO-3GP: A Sequential Regularized Multi-Objective Bayesian Optimization for Constrained Design Applications Using an Uncertain Pareto Classifier
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capability of the classical BO, many extensions, ...
Determination of Energy Release Rate Through Sequential Crack Extension
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A method to determine the critical energy release rate of a peel tested sample using an energy-based approach within a finite element framework is developed. The method uses a single finite element model, in which the ...