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Sensitivity study of dynamic systems using polynomial chaos
16 references·13 citing·29 second hop
Sensitivity study of dynamic systems using polynomial chaos (2012)Sensitivity study of dynamic systems usin…Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)Efficient computation of glob…Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design (2009)Recent Advances in Non-Intrus…Polynomial chaos expansion for sensitivity analysis (2008)Polynomial chaos expansion fo…Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…Stochastic finite element: a non intrusive approach by regression (2006)Stochastic finite element: a …A new uncertainty importance measure (2006)A new uncertainty importance …Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2005)Sensitivity Analysis in Pract…Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2004)Sensitivity Analysis in Pract…Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Modeling uncertainty in flow …Sensitivity Analysis in Practice (2002)Sensitivity Analysis in Pract…Sensitivity Analysis for Importance Assessment (2002)Sensitivity Analysis for Impo…Identification and Review of Sensitivity Analysis Methods (2002)Identification and Review of …A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)A Quantitative Model-Independ…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Nonlinear sensitivity analysis of multiparameter model systems (1978)Nonlinear sensitivity analysi…Variance-based sensitivity analysis of dynamic systems with both input and model uncertainty (2021)Variance-based sensitivity an…Knowledge-inspired operational reliability for optimal LNG production at the offshore site (2019)Knowledge-inspired operationa…Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks (2018)Reduced Dimensional Chebyshev…Incomplete statistical information limits the utility of high-order polynomial chaos expansions (2017)Incomplete statistical inform…Cross-covariance based global dynamic sensitivity analysis (2017)Cross-covariance based global…Accurate Reduced Dimensional Polynomial Chaos for Efficient Uncertainty Quantification of Microwave/RF Networks (2017)Accurate Reduced Dimensional …Uncertainty quantification and global sensitivity analysis of complex chemical processes with a large number of input parameters using compressive polynomial chaos (2016)Uncertainty quantification an…Uncertainty quantification and global sensitivity analysis of complex chemical process using a generalized polynomial chaos approach (2016)Uncertainty quantification an…An efficient method for evaluating the effect of input parameters on the integrity of safety systems (2015)An efficient method for evalu…Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study (2014)Space-partition method for th…Dynamic system uncertainty propagation using polynomial chaos (2014)Dynamic system uncertainty pr…Global Sensitivity Analysis in a Multi-State Physics Model of Component Degradation Based on a Hybrid State-Space Enrichment and Polynomial Chaos Expansion Approach (2013)Global Sensitivity Analysis i…Global sensitivity analysis for dynamic systems with stochastic input processes (2013)Global sensitivity analysis f…Factorial Sampling Plans for Preliminary Computational Experiments (1991)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)A simple and efficient method for global sensitivity analysis based on cumulative distribution functions (2015)Variable importance analysis: A comprehensive review (2015)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)Statistics for Experimenters (1979)Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences (1994)“Opening Up” and “Closing Down” (2007)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)Design and Analysis of Computer Experiments (1989)Handbook on Constructing Composite Indicators (2005)An effective screening design for sensitivity analysis of large models (2007)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)UQLab: A Framework for Uncertainty Quantification in Matlab (2014)Rank Correlation Methods. (1957)Statistical principles in experimental design. (1962)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Sensitivity analysis practices: Strategies for model-based inference (2006)AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)Handbook on Constructing Composite Indicators: Methodology and User Guide (2008)An adaptive multi-element generalized polynomial chaos method for stochastic differential equations (2005)Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics (2008)Fast Numerical Methods for Stochastic Computations: A Review (2009)Tools for Composite Indicators Building (2005)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)
this work references cited by second hop

References

  • 1991Stochastic Finite Elements: A Spectral Approach5,753 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 1999A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output2,274 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 2005Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,843 cited
  • 2004Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,797 cited
  • 2003Modeling uncertainty in flow simulations via generalized polynomial chaos1,428 cited
  • 2002Sensitivity Analysis for Importance Assessment1,303 cited
  • 2002Identification and Review of Sensitivity Analysis Methods1,035 cited
  • 2006A new uncertainty importance measure1,030 cited
  • 2008Polynomial chaos expansion for sensitivity analysis747 cited
  • 1978Nonlinear sensitivity analysis of multiparameter model systems696 cited
  • 2002Sensitivity Analysis in Practice526 cited
  • 2006Stochastic finite element: a non intrusive approach by regression427 cited
  • 2010Efficient computation of global sensitivity indices using sparse polynomial chaos expansions

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383 cited
  • 2009Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design371 cited
  • Cited by

    • 2016Uncertainty quantification and global sensitivity analysis of complex chemical process using a generalized polynomial chaos approach39 cited
    • 2017Accurate Reduced Dimensional Polynomial Chaos for Efficient Uncertainty Quantification of Microwave/RF Networks39 cited
    • 2014Dynamic system uncertainty propagation using polynomial chaos36 cited
    • 2014Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study32 cited
    • 2017Incomplete statistical information limits the utility of high-order polynomial chaos expansions30 cited
    • 2013Global sensitivity analysis for dynamic systems with stochastic input processes27 cited
    • 2018Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks23 cited
    • 2017Cross-covariance based global dynamic sensitivity analysis22 cited
    • 2021Variance-based sensitivity analysis of dynamic systems with both input and model uncertainty17 cited
    • 2019Knowledge-inspired operational reliability for optimal LNG production at the offshore site17 cited
    • 2013Global Sensitivity Analysis in a Multi-State Physics Model of Component Degradation Based on a Hybrid State-Space Enrichment and Polynomial Chaos Expansion Approach16 cited
    • 2016Uncertainty quantification and global sensitivity analysis of complex chemical processes with a large number of input parameters using compressive polynomial chaos15 cited
    • 2015An efficient method for evaluating the effect of input parameters on the integrity of safety systems11 cited