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Uncertainty quantification

Known as: UQ (disambiguation) 
Uncertainty quantification (UQ) is the science of quantitative characterization and reduction of uncertainties in both computational and real world… Expand
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Bayesian programmingComputer experimentComputer simulationDATADVANCE
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Broader (1)

Operations research

Papers overview

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Highly Cited
2015
Highly Cited
2015
PIV uncertainty quantification from correlation statistics
The uncertainty of a PIV displacement field is estimated using a generic post-processing method based on statistical analysis of… Expand
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Highly Cited
2014
Highly Cited
2014
Uncertainty Quantification - Theory, Implementation, and Applications
  • Ralph C. Smith
  • Computational science and engineering
  • 2014
    • Corpus ID: 30334130
The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified… Expand
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Highly Cited
2010
Highly Cited
2010
Spectral Methods for Uncertainty Quantification: With Applications to Computational Fluid Dynamics
Introduction: Uncertainty Quantification and Propagation.- Basic Formulations.- Spectral Expansions.- Non-intrusive Methods… Expand
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Highly Cited
2010
Highly Cited
2010
Spectral Methods for Uncertainty Quantification
 
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Highly Cited
2009
Highly Cited
2009
Comparison of Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Quantification
Non-intrusive polynomial chaos expansion (PCE) and stochastic collocation (SC) methods are attractive techniques for uncertainty… Expand
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Highly Cited
2009
Highly Cited
2009
Uncertainty quantification for systems of conservation laws
Uncertainty quantification through stochastic spectral methods has been recently applied to several kinds of non-linear… Expand
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Highly Cited
2008
Highly Cited
2008
Stochastic approaches to uncertainty quantification in CFD simulations
This paper discusses two stochastic approaches to computing the propagation of uncertainty in numerical simulations: polynomial… Expand
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Highly Cited
2006
Highly Cited
2006
DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis.
The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a e xible and extensible interface… Expand
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Highly Cited
2004
Highly Cited
2004
Uncertainty quantification using evidence theory in multidisciplinary design optimization
Abstract Advances in computational performance have led to the development of large-scale simulation tools for design. Systems… Expand
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Highly Cited
2003
Highly Cited
2003
Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection
Abstract A spectral formalism has been developed for the “non-intrusive” analysis of parametric uncertainty in reacting-flow… Expand
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