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Uncertainty Quantification of NOx and CO Emissions in a Swirl-Stabilized Burner
9 references·0 citing·40 second hop
Uncertainty Quantification of NOx and CO Emissions in a Swirl-Stabilized Burner (2019)Uncertainty Quantification of NOx and CO …OpenTURNS: An Industrial Software for Uncertainty Quantification in Simulation (2015)OpenTURNS: An Industrial Soft…Chaospy: An open source tool for designing methods of uncertainty quantification (2015)Chaospy: An open source tool …Uncertainty quantification of an Aviation Environmental Toolsuite (2014)Uncertainty quantification of…Combustion kinetic model uncertainty quantification, propagation and minimization (2014)Combustion kinetic model unce…Point-Collocation Nonintrusive Polynomial Chaos Method for Stochastic Computational Fluid Dynamics (2010)Point-Collocation Nonintrusiv…Uncertainty quantification in chemical systems (2009)Uncertainty quantification in…Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design (2009)Recent Advances in Non-Intrus…Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…Being Sensitive to Uncertainty (2007)Being Sensitive to UncertaintyStructural reliability under combined random load sequences (1978)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Comparison of Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Quantification (2009)Mixed aleatory-epistemic uncertainty quantification with stochastic expansions and optimization-based interval estimation (2011)First order reliability method for time-variant problems using series expansions (2014)Stochastic Finite Elements: A Spectral Approach (1991)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)Intrusive Galerkin methods with upwinding for uncertain nonlinear hyperbolic systems (2010)Uncertainty Quantification in MD Simulations. Part II: Bayesian Inference of Force-Field Parameters (2012)Fundamental limitations of polynomial chaos for uncertainty quantification in systems with intermittent instabilities (2013)Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Uncertainty Quantification of Hypersonic Reentry Flows with Sparse Sampling and Stochastic Expansions (2014)Uncertainty Quantification of Turbulence Model Closure Coefficients for Transonic Wall-Bounded Flows (2016)A Critical Review of Surrogate Assisted Robust Design Optimization (2017)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)UQLab: A Framework for Uncertainty Quantification in Matlab (2014)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Importance measures in global sensitivity analysis of nonlinear models (1996)Global Sensitivity Analysis. The Primer (2007)Uncertainty Quantification of NOx Emission Due to Operating Conditions and Chemical Kinetic Parameters in a Premixed Burner (2018)A Nonparametric-based Approach for the Characterization and Propagation of Epistemic Uncertainty due to Small Datasets (2019)Probabilistic surrogate models for uncertainty analysis: Dimension reduction‐based polynomial chaos expansion (2019)Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2004)Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2005)Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience (2018)Validation of the Sleep Regularity Index in Older Adults and Associations with Cardiometabolic Risk (2018)Gaze bias differences capture individual choice behaviour (2019)Design and Analysis of Computer Experiments (1989)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Accelerate global sensitivity analysis using artificial neural network algorithm: Case studies for combustion kinetic model (2016)Facilitating Bayesian analysis of combustion kinetic models with artificial neural network (2019)An Introduction to Copulas (1999)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Certain trends in uncertainty and sensitivity analysis: An overview of software tools and techniques (2019)UQpy: A general purpose Python package and development environment for uncertainty quantification (2020)Estimation of small failure probabilities in high dimensions by subset simulation (2001)Adaptive coupling of reduced basis modeling and Kriging based active learning methods for reliability analyses (2019)Sensitivity Analysis of a Mathematical Model Simulating the Post-Hepatectomy Hemodynamics Response (2022)PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling (2023)
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References

  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2007Being Sensitive to Uncertainty953 cited
  • 2009Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design371 cited
  • 2014Combustion kinetic model uncertainty quantification, propagation and minimization342 cited
  • 2015Chaospy: An open source tool for designing methods of uncertainty quantification336 cited
  • 2010Point-Collocation Nonintrusive Polynomial Chaos Method for Stochastic Computational Fluid Dynamics244 cited
  • 2009Uncertainty quantification in chemical systems139 cited
  • 2015OpenTURNS: An Industrial Software for Uncertainty Quantification in Simulation125 cited
  • 2014Uncertainty quantification of an Aviation Environmental Toolsuite26 cited

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