Simulation Model Validation for Structure Material Characterization

A method, apparatus, system, and computer program product for managing a physics simulation model. A machine learning model is trained to output predicted test results for sets of simulation values for a set of simulation parameters using a training data set based on test results for physical struct...

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Bibliographic Details
Main Authors Byar, Alan Douglas, Zobeiry, Navid, Joseph, Ashith, Dong, John J, Kabir, Mohammed H, Stere, Alexandru I, Doty, Christina
Format Patent
LanguageEnglish
Published 10.08.2023
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:A method, apparatus, system, and computer program product for managing a physics simulation model. A machine learning model is trained to output predicted test results for sets of simulation values for a set of simulation parameters using a training data set based on test results for physical structures to form a surrogate model. Current simulation values for simulation parameters are selected using the surrogate model and a cost function. Simulation test results are generated using the physics simulation model that implements the current simulation values selected for the simulation parameters. The simulation test results are compared with physical test results from testing the set of physical structures using physical test inputs applied to the physical structures to form a comparison. The surrogate model is trained using the current simulation values selected for the simulation parameters using the surrogate model in response to the comparison being outside of a tolerance.
Bibliography:Application Number: US202217648526