461 citations · 593 across the 5 of their papers we have counts for
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A Machine Learning Framework for Real-time Inverse Modeling and Multi-objective Process Optimization of Composites for Active Manufacturing Control
Keith D. Humfeld, Dawei Gu, Geoffrey A. Butler +2
For manufacturing of aerospace composites, several parts may be processed simultaneously using convective heating in an autoclave. Due to uncertainties including tool placement, co…
Theory-Guided Machine Learning for Process Simulation of Advanced Composites
Navid Zobeiry, Anoush Poursartip
Science-based simulation tools such as Finite Element (FE) models are routinely used in scientific and engineering applications. While their success is strongly dependent on our un…
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications
Navid Zobeiry, Keith D. Humfeld
A physics-informed neural network is developed to solve conductive heat transfer partial differential equation (PDE), along with convective heat transfer PDEs as boundary condition…
An Iterative Scientific Machine Learning Approach for Discovery of Theories Underlying Physical Phenomena
Navid Zobeiry, Keith D. Humfeld
Form a pure mathematical point of view, common functional forms representing different physical phenomena can be defined. For example, rates of chemical reactions, diffusion and he…