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Volume 5, 2024 / Issue 4

Table of Contents:

MESH REFINEMENT AS PROBABILISTIC LEARNING Philippe Hawi, Roger Ghanem

Philippe Hawi
University of Southern California

Roger Ghanem
Sony Astani Department of Aerospace and Mechanical Engineering, University of Southern California, 210 KAP Hall, Los Angeles, CA 90089, USA

1-21 pages
DOI: 10.1615/JMachLearnModelComput.2024054830

ROBUST TOPOLOGY OPTIMIZATION USING MULTI-FIDELITY VARIATIONAL AUTOENCODERS Rini Jasmine Gladstone, Mohammad Amin Nabian, Vahid Keshavarzzadeh, Hadi Meidani

Rini Jasmine Gladstone
Department of Civil Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, 61801, USA

Mohammad Amin Nabian
NVIDIA, Santa Clara, CA, 95051, USA

Vahid Keshavarzzadeh
General Motors, 13201 McCallen Pass, Austin, TX, 78753, USA

Hadi Meidani
Department of Civil and Environmental Engineering, 1211 Newmark Civil Engineering Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61822, USA

23-52 pages
DOI: 10.1615/JMachLearnModelComput.2024054646

HYBRID CHANCE-CONSTRAINED OPTIMAL POWER FLOW UNDER LOAD AND RENEWABLE GENERATION UNCERTAINTY USING ENHANCED MULTI-FIDELITY GRAPH NEURAL NETWORKS Kamiar Khayambashi, Md Abul Hasnat, Negin Alemazkoor

Kamiar Khayambashi
Department of Civil and Environmental Engineering, University of Virginia

Md Abul Hasnat
Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA 22904, USA

Negin Alemazkoor
Assistant Professor, Department of Civil and Environmental Engineering/Systems and Information Engineering, University of Virginia, Charlottesville, VA 22904, USA

53-76 pages
DOI: 10.1615/JMachLearnModelComput.2024054885

MULTI-FIDELITY MACHINE LEARNING FOR UNCERTAINTY QUANTIFICATION AND OPTIMIZATION Ruda Zhang, Negin Alemazkoor

Ruda Zhang
University of Houston

Negin Alemazkoor
Assistant Professor, Department of Civil and Environmental Engineering/Systems and Information Engineering, University of Virginia, Charlottesville, VA 22904, USA

77-94 pages
DOI: 10.1615/JMachLearnModelComput.2024055786

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