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An efficient Bayesian uncertainty quantification approach with application to k-ω-γ transition modeling
9 references·2 citing·30 second hop
An efficient Bayesian uncertainty quantification approach with application to k-ω-γ transition modeling (2017)An efficient Bayesian uncertainty quantif…Simplex stochastic collocation with ENO-type stencil selection for robust uncertainty quantification (2013)Simplex stochastic collocatio…Uncertainty Quantification for Laminar-Turbulent Transition Prediction in RANS Turbomachinery Applications (2011)Uncertainty Quantification fo…Bayesian uncertainty quantification applied to RANS turbulence models (2011)Bayesian uncertainty quantifi…Bayesian uncertainty analysis with applications to turbulence modeling (2011)Bayesian uncertainty analysis…Spectral Methods for Uncertainty Quantification (2010)Spectral Methods for Uncertai…An adaptive high-dimensional stochastic model representation technique for the solution of stochastic partial differential equations (2010)An adaptive high-dimensional …An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations (2009)An adaptive hierarchical spar…A Stochastic Collocation Approach to Bayesian Inference in Inverse Problems (2009)A Stochastic Collocation Appr…High-Order Collocation Methods for Differential Equations with Random Inputs (2005)High-Order Collocation Method…Adaptive Model Refinement Approach for Bayesian Uncertainty Quantification in Turbulence Model (2022)Adaptive Model Refinement App…Evaluation of ensemble methods for quantifying uncertainties in steady-state CFD applications with small ensemble sizes (2020)Evaluation of ensemble method…Stochastic Differential Equations: An Introduction with Applications. (1987)Stochastic Finite Elements: A Spectral Approach (1991)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Adaptive ANOVA decomposition of stochastic incompressible and compressible flows (2011)Uncertainty Quantification in Multiscale Simulation of Materials: A Prospective (2013)Surrogate-assisted global sensitivity analysis: an overview (2020)Scientific reasoning: the Bayesian approach (1990)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2007)Stochastic finite element methods for partial differential equations with random input data (2014)On the Statistical Calibration of Physical Models (2015)Large Sample Properties of Simulations Using Latin Hypercube Sampling (1987)A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (2008)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)A Non-Intrusive Polynomial Chaos Method For Uncertainty Propagation in CFD Simulations (2006)Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics (2008)Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients (2011)An Introduction to Computational Stochastic PDEs (2014)Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey (2020)A hybrid anchored-ANOVA – POD/Kriging method for uncertainty quantification in unsteady high-fidelity CFD simulations (2016)Embedded Model Error Representation for Bayesian Model Calibration (2020)Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments (2021)Simulation-based optimal Bayesian experimental design for nonlinear systems (2012)GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN (2014)Dynamic Adaptive Sampling Based on Kriging Surrogate Models for Efficient Uncertainty Quantification (2013)The Stochastic Collocation Monte Carlo Sampler: Highly Efficient Sampling from 'Expensive' Distributions (2014)Simplex-stochastic collocation method with improved scalability (2015)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2010)A non-adapted sparse approximation of PDEs with stochastic inputs (2011)A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC (2017)On the flow field and performance of a centrifugal pump under operational and geometrical uncertainties (2018)
this work references cited by second hop

References

  • 2005High-Order Collocation Methods for Differential Equations with Random Inputs1,522 cited
  • 2010Spectral Methods for Uncertainty Quantification953 cited
  • 2009An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations447 cited
  • 2009A Stochastic Collocation Approach to Bayesian Inference in Inverse Problems285 cited
  • 2011Bayesian uncertainty analysis with applications to turbulence modeling267 cited
  • 2010An adaptive high-dimensional stochastic model representation technique for the solution of stochastic partial differential equations205 cited
  • 2011Bayesian uncertainty quantification applied to RANS turbulence models132 cited
  • 2013Simplex stochastic collocation with ENO-type stencil selection for robust uncertainty quantification40 cited
  • 2011Uncertainty Quantification for Laminar-Turbulent Transition Prediction in RANS Turbomachinery Applications38 cited

Cited by

  • 2020Evaluation of ensemble methods for quantifying uncertainties in steady-state CFD applications with small ensemble sizes35 cited
  • 2022Adaptive Model Refinement Approach for Bayesian Uncertainty Quantification in Turbulence Model25 cited

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