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Efficient uncertainty quantification of stochastic CFD problems using sparse polynomial chaos and compressed sensing
16 references·12 citing·28 second hop
Efficient uncertainty quantification of stochastic CFD problems using sparse polynomial chaos and compressed sensing (2017)Efficient uncertainty quantification of s…Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies (2014)Compressive sampling of polyn…A non-adapted sparse approximation of PDEs with stochastic inputs (2011)A non-adapted sparse approxim…Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)Efficient computation of glob…Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Adaptive sparse polynomial ch…An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis (2009)An adaptive algorithm to buil…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…A Non-Intrusive Polynomial Chaos Method For Uncertainty Propagation in CFD Simulations (2006)A Non-Intrusive Polynomial Ch…Stochastic Approaches to Uncertainty Quantification in CFD Simulations (2005)Stochastic Approaches to Unce…An adaptive multi-element generalized polynomial chaos method for stochastic differential equations (2005)An adaptive multi-element gen…Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes (2004)Numerical Challenges in the U…Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection (2003)Uncertainty quantification in…The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)The Wiener--Askey Polynomial …An importance quantification technique in uncertainty analysis for computer models (2002)An importance quantification …Ingredients for a general purpose stochastic finite elements implementation (1999)Ingredients for a general pur…Numerical solution of spectral stochastic finite element systems (1996)Numerical solution of spectra…An active sparse polynomial chaos expansion approach based on sequential relevance vector machine (2023)An active sparse polynomial c…Efficient aerodynamic analysis and optimization under uncertainty using multi-fidelity polynomial chaos-Kriging surrogate model (2022)Efficient aerodynamic analysi…Uncertainty and multi-criteria global sensitivity analysis of structural systems using acceleration algorithm and sparse polynomial chaos expansion (2021)Uncertainty and multi-criteri…Multi-Fidelity, Gradient-enhanced, and Locally Optimized Sparse Polynomial Chaos and Kriging Surrogate Models Applied to Benchmark Problems (2020)Multi-Fidelity, Gradient-enha…Multi-fidelity uncertainty quantification of film cooling flow under random operational and geometrical conditions (2020)Multi-fidelity uncertainty qu…Efficient uncertainty quantification of turbine blade leading edge film cooling using bi-fidelity combination of compressed sensing and Kriging (2020)Efficient uncertainty quantif…Active learning polynomial chaos expansion for reliability analysis by maximizing expected indicator function prediction error (2020)Active learning polynomial ch…Multifidelity Sparse Polynomial Chaos Surrogate Models Applied to Flutter Databases (2019)Multifidelity Sparse Polynomi…An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework (2019)An efficient and robust adapt…On the flow field and performance of a centrifugal pump under operational and geometrical uncertainties (2018)On the flow field and perform…Global sensitivity analysis with a hierarchical sparse metamodeling method (2018)Global sensitivity analysis w…Efficient uncertainty quantification of stochastic heat transfer problems by combination of proper orthogonal decomposition and sparse polynomial chaos expansion (2018)Efficient uncertainty quantif…Stochastic Finite Elements: A Spectral Approach (1991)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)UQLab: A Framework for Uncertainty Quantification in Matlab (2014)POLYNOMIAL-CHAOS-BASED KRIGING (2015)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)Stochastic spectral methods for efficient Bayesian solution of inverse problems (2006)The Malliavin Calculus and Related Topics (2006)On the convergence of generalized polynomial chaos expansions (2011)Simulation-based optimal Bayesian experimental design for nonlinear systems (2012)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)A new surrogate modeling technique combining Kriging and polynomial chaos expansions – Application to uncertainty analysis in computational dosimetry (2015)Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark (2021)Structural Reliability Methods (1996)Reliability-based design optimization using kriging surrogates and subset simulation (2011)A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)LIF: A new Kriging based learning function and its application to structural reliability analysis (2016)Factorial Sampling Plans for Preliminary Computational Experiments (1991)An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis (2018)Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)A Stochastic Projection Method for Fluid Flow (2001)Efficient Sampling for Non-Intrusive Polynomial Chaos Applications with Multiple Uncertain Input Variables (2007)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2010)Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Multi-Element Generalized Polynomial Chaos for Arbitrary Probability Measures (2006)An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations (2009)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2010Adaptive sparse polynomial chaos expansion based on least angle regression1,507 cited
  • 2009An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis834 cited
  • 2005An adaptive multi-element generalized polynomial chaos method for stochastic differential equations578 cited
  • 2004Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes451 cited
  • 2011A non-adapted sparse approximation of PDEs with stochastic inputs436 cited
  • 1999Ingredients for a general purpose stochastic finite elements implementation401 cited
  • 2010Efficient computation of global sensitivity indices using sparse polynomial chaos expansions383 cited
  • 2006A Non-Intrusive Polynomial Chaos Method For Uncertainty Propagation in CFD Simulations335 cited
  • 2003Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection333 cited
  • 1996Numerical solution of spectral stochastic finite element systems294 cited
  • 2005Stochastic Approaches to Uncertainty Quantification in CFD Simulations

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281 cited
  • 2002An importance quantification technique in uncertainty analysis for computer models251 cited
  • 2014Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies212 cited
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    • 2021Uncertainty and multi-criteria global sensitivity analysis of structural systems using acceleration algorithm and sparse polynomial chaos expansion25 cited
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    • 2022Efficient aerodynamic analysis and optimization under uncertainty using multi-fidelity polynomial chaos-Kriging surrogate model20 cited
    • 2020Active learning polynomial chaos expansion for reliability analysis by maximizing expected indicator function prediction error20 cited
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    • 2018Global sensitivity analysis with a hierarchical sparse metamodeling method14 cited
    • 2020Multi-Fidelity, Gradient-enhanced, and Locally Optimized Sparse Polynomial Chaos and Kriging Surrogate Models Applied to Benchmark Problems13 cited
    • 2023An active sparse polynomial chaos expansion approach based on sequential relevance vector machine12 cited