The neural network collocation method for solving partial differential equations

被引：0
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作者：
Brink, Adam R. [1 ]
Najera-Flores, David A. [2 ]
Martinez, Cari [3 ]
机构：
[1] Department of Structural Mechanics, Sandia National Laboratories, P.O. Box 5800, MS 0346, Albuquerque,NM,57185-0346, United States
[2] Department of Component Sciences and Mechanics, ATA Engineering, Inc, 13290 Evening Creek Drive S, San Diego,CA,92128, United States
[3] Department of Applied Machine Learning, Sandia National Laboratories, P.O. Box 5800, MS 0346, Albuquerque,NM,57185-0346, United States
来源：
Neural Computing and Applications | 2021年 / 33卷 / 11期
关键词：
This work was sponsored by Sandia National Laboratories’ Lab Directed Research and Development (LDRD) 2019 campaign. AcknowledgementsSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia; LLC; a wholly owned subsidiary of Honeywell International Inc; for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the US Department of Energy or the US Government.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia; for the US Department of Energy?s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the US Department of Energy or the US Government;
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页码：5591 / 5608
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