International Journal for Uncertainty Quantification
Выходит 6 номеров в год
ISSN Печать: 2152-5080
ISSN Онлайн: 2152-5099
IF:
1.7
5-Year IF:
1.9
Immediacy Index:
0.5
Eigenfactor:
0.0007
JCI:
0.5
SJR:
0.584
SNIP:
0.676
CiteScore™::
3
H-Index:
25
Indexed in
Том 3, 2013 Выпуск 6
DOI: 10.1615/Int.J.UncertaintyQuantification.v3.i6
SPECIAL ISSUE DEDICATED TO THE 1ST INTERNATIONAL SYMPOSIUM ON UNCERTAINTY QUANTIFICATION AND STOCHASTIC MODELING (UNCERTAINTIES 2012)
pp. vii-viii
DOI: 10.1615/Int.J.UncertaintyQuantification.2013007487
UNCERTAINTY QUANTIFICATION IN LOW-FREQUENCY DYNAMICS OF COMPLEX BEAM-LIKE STRUCTURES HAVING A HIGH-MODAL DENSITY
pp. 475-485
DOI: 10.1615/Int.J.UncertaintyQuantification.2012005286
OPTIMAL DESIGN UNDER UNCERTAINTY OF REINFORCED CONCRETE STRUCTURES USING SYSTEM RELIABILITY APPROACH
pp. 487-498
DOI: 10.1615/Int.J.UncertaintyQuantification.2013005786
A MULTI-STAGE BAYESIAN PREDICTION FRAMEWORK FOR SUBSURFACE FLOWS
pp. 499-522
DOI: 10.1615/Int.J.UncertaintyQuantification.2013005281
EFFECT OF PARAMETRIC UNCERTAINTIES ON THE EFFECTIVENESS OF DISCRETE PIEZOELECTRIC SPATIAL MODAL FILTERS
pp. 523-540
DOI: 10.1615/Int.J.UncertaintyQuantification.2012005287
DESIGN-POINT EXCITATION FOR CRACK PROPAGATION UNDER NARROW-BAND RANDOM LOADING
pp. 541-554
DOI: 10.1615/Int.J.UncertaintyQuantification.2013005074
Последний выпуск
MODEL ERROR ESTIMATION USING PEARSON SYSTEM WITH APPLICATION TO NONLINEAR WAVES IN COMPRESSIBLE FLOWS
DECISION THEORETIC BOOTSTRAPPING
UNCERTAINTY QUANTIFICATION AND GLOBAL SENSITIVITY ANALYSIS OF SEISMIC FRAGILITY CURVES USING KRIGING
STOCHASTIC GALERKIN METHOD AND PORT-HAMILTONIAN FORM FOR LINEAR FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS
Статьи, принятые к публикации
EXTREME LEARNING MACHINES FOR VARIANCE-BASED GLOBAL SENSITIVITY ANALYSIS
Application of global sensitivity analysis for identification of probabilistic design spaces
SENSITIVITY ANALYSES OF A MULTI-PHYSICS LONG-TERM CLOGGING MODEL FOR STEAM GENERATORS
Stochastic Galerkin method and port-Hamiltonian form for linear first-order ordinary differential equations
Analysis of the Challenges in Developing Sample-Based Multi-fidelity Estimators for Non-deterministic Models