Open AccessA deep learning framework for mesh relaxation in arbitrary Lagrangian-Eulerian simulations
Author(s) -
Ming Jiang,
Brian Gallagher,
Noah Mandell,
Alister Maguire,
Keith Henderson,
George F. Weinert
Publication year - 2019
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1117/12.2529731
Subject(s) - computer science , eulerian path , relaxation (psychology) , coherence (philosophical gambling strategy) , lagrangian relaxation , convolutional neural network , set (abstract data type) , deep learning , lagrangian , artificial intelligence , artificial neural network , computational science , algorithm , mathematical optimization , mathematics , physics , programming language , psychology , social psychology , quantum mechanics
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