Search Results for author:
Found 4 papers, 0 papers with code
A Machine Learning Framework for Real-time Inverse Modeling and Multi-objective Process Optimization of Composites for Active Manufacturing Control
In this study, a novel machine learning (ML) framework is presented capable of optimizing air temperature cycle in real-time based on TC data from multiple parts, for active control of manufacturing.
Theory-Guided Machine Learning for Process Simulation of Advanced Composites
A recent successful implementation of a TGML model to assess producibility of aerospace composite parts is presented.
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications
In addition, theory of heat transfer is used for feature engineering.
An Iterative Scientific Machine Learning Approach for Discovery of Theories Underlying Physical Phenomena
By comparing the rates of convergence or mean error in training, expressions describing the underlying physical problems can be discovered, leading to extracting explicit analytic equations.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
