Archive Files

Volume 9, 2019 / Edição 3

SPECIAL ISSUE: CELEBRATING THE ESTABLISHMENT OF A NEW UQ SOCIETY IN CHINA PART 2
GUEST EDITOR: TAO ZHOU

DOI: 10.1615/Int.J.UncertaintyQuantification.v9.i3

Table of Contents:

PREFACE: A SPECIAL ISSUE CELEBRATING A NEW UQ ACTIVITY GROUP IN CHINA Tao Zhou

Tao Zhou
LSEC, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

v páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.v9.i3.10

AN ADAPTIVE MULTIFIDELITY PC-BASED ENSEMBLE KALMAN INVERSION FOR INVERSE PROBLEMS Liang Yan, Tao Zhou

Liang Yan
Department of Mathematics, Southeast University, Nanjing, 210096, China

Tao Zhou
LSEC, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

205-220 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2019029059

A GENERAL FRAMEWORK FOR ENHANCING SPARSITY OF GENERALIZED POLYNOMIAL CHAOS EXPANSIONS Xiu Yang, Xiaoliang Wan, Lin Lin, Huan Lei

Xiu Yang
Lehigh University

Xiaoliang Wan
Department of Mathematics and Center of Computation and Technology, Louisiana State University, Baton Rouge, LA, 70803

Lin Lin
Department of Mathematics, University of California, Berkeley and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720

Huan Lei
Advanced Computing, Mathematics and Data Division, Pacific Northwest National Laboratory, Richland, WA, 99352

221-243 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2019027864

VARIABLE-SEPARATION BASED ITERATIVE ENSEMBLE SMOOTHER FOR BAYESIAN INVERSE PROBLEMS IN ANOMALOUS DIFFUSION REACTION MODELS Yuming Ba, Lijian Jiang , Na Ou

Yuming Ba
College of Mathematics and Econometrics, Hunan University 1, Changsha 410082, China

Lijian Jiang
School of Mathematical Sciences, Tongji University, Shanghai 200092, China

Na Ou
College of Mathematics and Econometrics, Hunan University 1, Changsha 410082, China

245-273 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2019028759

AN EFFICIENT NUMERICAL METHOD FOR UNCERTAINTY QUANTIFICATION IN CARDIOLOGY MODELS Xindan Gao, Wenjun Ying, Zhiwen Zhang

Xindan Gao
School of Mathematical Sciences, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang, Shanghai, P.R. China, 200240

Wenjun Ying
Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong, SAR, China

Zhiwen Zhang
Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong, SAR, China

275-294 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2019027857

USING PARALLEL MARKOV CHAIN MONTE CARLO TO QUANTIFY UNCERTAINTIES IN GEOTHERMAL RESERVOIR CALIBRATION Tiangang Cui, C. Fox, G. K. Nicholls, M. J. O'Sullivan

Tiangang Cui
School of Mathematical Sciences, Monash University, VIC 3800, Australia

C. Fox
Department of Physics, University of Otago, Dunedin 9016, New Zealand

G. K. Nicholls
Department of Statistics, University of Oxford, Oxford, OX1 3LG, United Kingdom

M. J. O'Sullivan
Department of Engineering Sciences, The University of Auckland, Auckland 1010, New Zealand

295-310 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2019029282

A WEIGHT-BOUNDED IMPORTANCE SAMPLING METHOD FOR VARIANCE REDUCTION Tenchao Yu, Linjun Lu, Jinglai Li

Tenchao Yu
School of Mathematical Sciences and Institute of Natural Sciences, Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai 200240, China

Linjun Lu
School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Jinglai Li
School of Mathematics, University of Birmingham, Birmingham B15 2TT, United Kingdom

311-319 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.2019029511

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