Текущий год

Том 5, 2024 / Выпуск 3

DOI: 10.1615/JMachLearnModelComput.v5.i3

Table of Contents:

MACHINE LEARNING−BASED IDENTIFICATION OF THE INTERFACE REGIONS FOR COUPLING LOCAL AND NONLOCAL MODELS Noujoud Nader, Patrick Diehl, Marta D'Elia, Christian Glusa, Serge Prudhomme

Noujoud Nader
Louisiana State University

Patrick Diehl
Center of Computation and Technology, Louisiana State University, 340 E. Parker Blvd, Baton Rouge, LA 70803, USA; Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA 70803, USA; Applied Computer Science, Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 87545, USA

Marta D'Elia
Pasteur Lab., 19 Morris Ave, Brooklyn, NY 11205, USA

Christian Glusa
Center for Computing Research, Sandia National Laboratories, Albuquerque, NM 87123, USA

Serge Prudhomme
Polytechnique Montréal

1-29 страниц
DOI: 10.1615/JMachLearnModelComput.2024053706

MACHINE-LEARNED INFERENCE OF FRACTURE FLOWRATE FROM TEMPERATURE LOGS Xiaoyu Yang, Roland N. Horne, Daniel M. Tartakovsky

Xiaoyu Yang
Department of Energy Science and Engineering, Stanford University, Stanford, CA 94305, USA

Roland N. Horne
The Ohio State University, Columbus, Ohio Stanford University, Stanford, California

Daniel M. Tartakovsky
Department of Energy Resources, Engineering, Stanford University, 367 Panama St., Stanford, CA 94305, USA

31-45 страниц
DOI: 10.1615/JMachLearnModelComput.2024055928

IMPROVING ADAM THROUGH AN IMPLICIT-EXPLICIT (IMEX) TIME-STEPPING APPROACH Abhinab Bhattacharjee, Andrey A. Popov, Arash Sarshar, Adrian Sandu

Abhinab Bhattacharjee
Virginia Tech

Andrey A. Popov
Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, 78712, USA; Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas, 78712, USA

Arash Sarshar
Department of Computer Engineering and Computer Science, California State University, Long Beach, CA 90840, USA

Adrian Sandu
Computational Science Laboratory, Department of Computer Science, Virginia Polytechnic Institute and State University, 2201 Knowledgeworks II, 2202 Kraft Drive, Blacksburg, Virginia 24060, USA

47-68 страниц
DOI: 10.1615/JMachLearnModelComput.2024053508

PHYSICS-INFORMED ENCODER-DECODER GATED RECURRENT NEURAL NETWORK FOR SOLVING TIME-DEPENDENT PDES Jie Long, A. Q. M. Khaliq, Y. Xu

Jie Long
Middle Tennessee State University

A. Q. M. Khaliq
Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, Tennessee 37132, USA

Y. Xu
Department of Mathematical Sciences, Michigan Technological University, Houghton, Michigan 49931, USA

69-85 страниц
DOI: 10.1615/JMachLearnModelComput.2024054403

MODELING UNKNOWN STOCHASTIC DYNAMICAL SYSTEM VIA AUTOENCODER Zhongshu Xu, Yuan Chen, Qifan Chen, Dongbin Xiu

Zhongshu Xu
Department of Mathematics, The Ohio State University, Columbus, OH 43210, USA

Yuan Chen
Ohio State University

Qifan Chen
Department of Mathematics, The Ohio State University, Columbus, OH 43210, USA

Dongbin Xiu
Department of Mathematics, The Ohio State University, Columbus, 43210 Ohio, USA

87-112 страниц
DOI: 10.1615/JMachLearnModelComput.2024055773

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