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ISSN Imprimir: 2152-5080
ISSN On-line: 2152-5099
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DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1
Table of Contents:
PREFACE
Nicholas Zabaras
Nicholas Zabaras
Department of Mechanical and Aerospace Engineering, Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA; University of Warwick, Coventry CV4 7AL, UK
ii páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.10
ON THE ROBUSTNESS OF STRUCTURAL RISK OPTIMIZATION WITH RESPECT TO EPISTEMIC UNCERTAINTIES
Andre T. Beck, W. J. S. Gomes, F. A. V. Bazan
Andre T. Beck
Structural Engineering Department, EESC, University of São Paulo, Av. Trabalhador São-carlense, 400, 13566-590 São Carlos, SP, Brazil
W. J. S. Gomes
Structural Engineering Department, EESC, University of São Paulo, Av. Trabalhador São-carlense, 400, 13566-590 São Carlos, SP, Brazil
F. A. V. Bazan
Structural Engineering Department, EESC, University of São Paulo, Av. Trabalhador São-carlense, 400, 13566-590 São Carlos, SP, Brazil
1-20 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.20
DISTANCES AND DIAMETERS IN CONCENTRATION INEQUALITIES: FROM GEOMETRY TO OPTIMAL ASSIGNMENT OF SAMPLING RESOURCES
Tim Sullivan, Houman Owhadi
Tim Sullivan
Freie Universität Berlin
Houman Owhadi
Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA
21-38 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.30
A NON-PARAMETRIC METHOD FOR INCURRED BUT NOT REPORTED CLAIM RESERVE ESTIMATION
Helio Lopes, Jocelia Barcellos, Jessica Kubrusly, Cristiano Fernandes
Helio Lopes
Departamento de Matematica, Pontiftcia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brazil
Jocelia Barcellos
Departamento de Matematica, Pontiftcia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brazil
Jessica Kubrusly
Instituto de Matematica e Estatistica, Universidade Federal Fluminense, Niteroi, Rio de Janeiro, Brazil
Cristiano Fernandes
Departamento de Engenharia Eletrica, Pontificia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brazil
39-51 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.40
UNCERTAINTY QUANTIFICATION IN COMPUTATIONAL PREDICTIVE MODELS FOR FLUID DYNAMICS USING A WORKFLOW MANAGEMENT ENGINE
Gabriel Guerra, Fernando Alves Rochinha, Renato Elias, Daniel de Oliveira, Eduardo Ogasawara, Jonas Furtado Dias, Marta Mattoso, Alvaro L. G. A. Coutinho
Gabriel Guerra
Mechanical Engineering Department, Federal University of Rio de Janeiro, Brazil
Fernando Alves Rochinha
Mechanical Engineering Program,
COPPE,
University City of the Federal University of Rio de Janeiro,
Rio de Janeiro, Brazil
Renato Elias
High Performance Computing Center, Federal University of Rio de Janeiro, Brazil
Daniel de Oliveira
Systems Engineering and Computer Science Department, Federal University of Rio de Janeiro, Brazil
Eduardo Ogasawara
Systems Engineering and Computer Science Department, Federal University of Rio de Janeiro, Brazil
Jonas Furtado Dias
Systems Engineering and Computer Science Department, Federal University of Rio de Janeiro, Brazil
Marta Mattoso
Systems Engineering and Computer Science Department, Federal University of Rio de Janeiro, Brazil
Alvaro L. G. A. Coutinho
High Performance Computing Center
53-71 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.50
ON THE ROLE OF DATA MINING TECHNIQUES IN UNCERTAINTY QUANTIFICATION
Chandrika Kamath
Chandrika Kamath
Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, 94551, USA
73-94 páginas
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.60
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