International Journal for Uncertainty Quantification
Published 6 issues per year
ISSN Print: 2152-5080
ISSN Online: 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
Volume 2, 2012 Issue 2
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2
ROBUST STOCHASTIC DESIGN OF BASE-ISOLATED STRUCTURAL SYSTEMS
pp. 95-110
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2.20
STOCHASTIC DRILL-STRING DYNAMICS WITH UNCERTAINTY ON THE IMPOSED SPEED AND ON THE BIT-ROCK PARAMETERS
pp. 111-124
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2.30
FORWARD AND BACKWARD UNCERTAINTY PROPAGATION FOR DISCONTINUOUS SYSTEM RESPONSE USING THE PADÉ-LEGENDRE METHOD
pp. 125-143
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2.40
A STOCHASTIC COLLOCATION APPROACH FOR UNCERTAINTY QUANTIFICATION IN HYDRAULIC FRACTURE NUMERICAL SIMULATION
pp. 145-160
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2.50
RELATIONSHIP BETWEEN BAYESIAN AND FREQUENTIST SIGNIFICANCE INDICES
pp. 161-172
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2.60
A BAYES NETWORK APPROACH TO UNCERTAINTY QUANTIFICATION IN HIERARCHICALLY DEVELOPED COMPUTATIONAL MODELS
pp. 173-193
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2.70
Latest Issue
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
Forthcoming Articles
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