Архив

Том 2, 2012 / Выпуск 1

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 страниц
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 страниц
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 страниц
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 страниц
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 страниц
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 страниц
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.60

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