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Том 10, 2020 / Выпуск 6

Special Issue: Multilevel-Multifidelity Approaches for Uncertainty Quantification Part 2
Guest Editors: Gianluca Geraci, Gianluca Iaccarino, and Michael Eldred

DOI: 10.1615/Int.J.UncertaintyQuantification.v10.i6

Table of Contents:

FOREWORD: SPECIAL ISSUE ON MULTILEVEL-MULTIFIDELITY APPROACHES FOR UNCERTAINTY QUANTIFICATION Michael S. Eldred, Gianluca Geraci, Gianluca Iaccarino

Michael S. Eldred
Optimization and Uncertainty Quantification, Sandia National Laboratories, Albuquerque,NM, 87185, USA

Gianluca Geraci
Optimization and Uncertainty Quantification, Sandia National Laboratories, Albuquerque,New Mexico, 87185, USA

Gianluca Iaccarino
Department of Mechanical Engineering Institute for Computational Mathematical Engineering Stanford University Bldg 500, RM 500-I, Stanford CA 94305 - USA

v-ix страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.v10.i6.10

MULTIFIDELITY MODELING OF IRRADIATED PARTICLE-LADEN TURBULENCE SUBJECT TO UNCERTAINTY Lluis Jofre, M. Papadakis, P. T. Roy, A. Aiken, G. Iaccarino

Lluis Jofre
Center for Turbulence Research, Stanford University, Stanford, California, 94305, USA; Department of Fluid Mechanics, Technical University of Catalonia, BarcelonaTech, Barcelona, 08019, Spain

M. Papadakis
Stanford Computer Science, Stanford University, Stanford, California, 94305, USA

P. T. Roy
Bongfish, Am Eisernen Tor 3, 8010 Graz, Austria

A. Aiken
Stanford Computer Science, Stanford University, Stanford, California, 94305, USA

G. Iaccarino
Center for Turbulence Research, Stanford University, Stanford, California, 94305, USA

499-514 страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.2020032236

BAYESIAN INFERENCE OF STOCHASTIC REACTION NETWORKS USING MULTIFIDELITY SEQUENTIAL TEMPERED MARKOV CHAIN MONTE CARLO Thomas A. Catanach, Huy D. Vo, Brian Munsky

Thomas A. Catanach
Sandia National Laboratories, Livermore, California, 94550, USA

Huy D. Vo
Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado, 80521, USA

Brian Munsky
Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado, 80521, USA

515-542 страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.2020033241

ON TRANSFER LEARNING OF NEURAL NETWORKS USING BI-FIDELITY DATA FOR UNCERTAINTY PROPAGATION Subhayan De, Jolene Britton, Matthew Reynolds, Ryan Skinner, Kenneth Jansen, Alireza Doostan

Subhayan De
University of Colorado, Boulder, Colorado 80309, USA

Jolene Britton
University of California, Riverside, California 92521, USA

Matthew Reynolds
National Renewable Energy Laboratory, Golden, Colorado 80401, USA

Ryan Skinner
University of Colorado, Boulder, Colorado 80309, USA

Kenneth Jansen
University of Colorado, Boulder, Colorado 80309, USA

Alireza Doostan
Aerospace Mechanics Research Center, College of Engineering and Applied Science, University of Colorado, Boulder, CO 80309-0429, USA

543-573 страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.2020033267

MULTILEVEL MONTE CARLO SAMPLING ON HETEROGENEOUS COMPUTER ARCHITECTURES Christiane Adcock, Yinyu Ye, Lluis Jofre, Gianluca Iaccarino

Christiane Adcock
Stanford University, Stanford, California, 94305

Yinyu Ye
Stanford University, Stanford, California, 94305

Gianluca Iaccarino
Department of Mechanical Engineering Institute for Computational Mathematical Engineering Stanford University Bldg 500, RM 500-I, Stanford CA 94305 - USA

575-594 страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.2020033179

MFNets: MULTI-FIDELITY DATA-DRIVEN NETWORKS FOR BAYESIAN LEARNING AND PREDICTION Alex A. Gorodetsky, John D. Jakeman, Gianluca Geraci, Michael S. Eldred

Alex A. Gorodetsky
Optimization and Uncertainty Quantification, Sandia National Laboratories, Albuquerque, New Mexico, 87123, USA

John D. Jakeman
Optimization and Uncertainty Quantification, Center for Computing Research, Sandia National Laboratories, Albuquerque, NM 87123, USA

Gianluca Geraci
Optimization and Uncertainty Quantification, Sandia National Laboratories, Albuquerque,New Mexico, 87185, USA

Michael S. Eldred
Optimization and Uncertainty Quantification, Sandia National Laboratories, Albuquerque,NM, 87185, USA

595-622 страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.2020032978

INDEX, VOLUME 10, 2020 623-627 страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.v10.i6.70

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