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Model discrepancy calibration across experimental settings
16 references·2 citing·37 second hop
Model discrepancy calibration across experimental settings (2020)Model discrepancy calibration across expe…Representing Model Inadequacy: A Stochastic Operator Approach (2018)Representing Model Inadequacy…On the Statistical Calibration of Physical Models (2015)On the Statistical Calibratio…Integration of model verification, validation, and calibration for uncertainty quantification in engineering systems (2015)Integration of model verifica…Selection of model discrepancy priors in Bayesian calibration (2014)Selection of model discrepanc…A Bayesian statistical method for quantifying model form uncertainty and two model combination methods (2014)A Bayesian statistical method…Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability (2012)Quantification of Model Uncer…Toward a Better Understanding of Model Validation Metrics (2011)Toward a Better Understanding…DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual. (2010)DAKOTA : a multilevel paralle…A systematic approach to model validation based on Bayesian updates and prediction related rejection criteria (2008)A systematic approach to mode…A Framework for Validation of Computer Models (2007)A Framework for Validation of…Validation and error estimation of computational models (2006)Validation and error estimati…The Design and Analysis of Computer Experiments (2004)The Design and Analysis of Co…Probabilistic Formulations for Transferring Inferences from Mathematical Models to Physical Systems (2004)Probabilistic Formulations fo…Combining Field Data and Computer Simulations for Calibration and Prediction (2004)Combining Field Data and Comp…Error and uncertainty in modeling and simulation (2002)Error and uncertainty in mode…Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…BAYESIAN CALIBRATION WITH ADAPTIVE MODEL DISCREPANCY (2023)BAYESIAN CALIBRATION WITH ADA…A collaborative model calibration framework under uncertainty considering parameter distribution (2022)A collaborative model calibra…Stochastic Finite Elements: A Spectral Approach (1991)A Stochastic Projection Method for Fluid Flow (2002)Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics (2008)Embedded Model Error Representation for Bayesian Model Calibration (2020)An extended polynomial chaos expansion for PDF characterization and variation with aleatory and epistemic uncertainties (2021)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Comparison of Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Quantification (2009)Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design (2009)Chaospy: An open source tool for designing methods of uncertainty quantification (2015)Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences (1994)Calibration, validation, and sensitivity analysis: What's what (2006)Measures of agreement between computation and experiment: Validation metrics (2006)Verification and Validation in Computational Science and Engineering (1998)Computational methods for model reliability assessment (2007)Simulation and the Monte Carlo Method (2007)Quantitative model validation techniques: New insights (2012)Simulation and the Monte Carlo Method (2016)Geostatistics: Modeling Spatial Uncertainty (2000)Uncertainty quantification in prediction of material properties during additive manufacturing (2016)Review of statistical model calibration and validation—from the perspective of uncertainty structures (2019)Unified Framework and Survey for Model Verification, Validation and Uncertainty Quantification (2020)STATISTICS FOR SPATIAL DATA (1992)Reliability Analysis With Monte Carlo Simulation and Dependent Kriging Predictions (2016)A Tutorial on Bayesian Inference to Identify Material Parameters in Solid Mechanics (2019)Modeling, analysis, and optimization under uncertainties: a review (2021)Minimax and maximin distance designs (1990)Choosing the Sample Size of a Computer Experiment: A Practical Guide (2009)Probability, reliability and statistical methods in engineering design (1999)Probability, Reliability and Statistical Methods in Engineering Design (2001)Verification, validation, and predictive capability in computational engineering and physics (2004)Simulation Modeling and Analysis. 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References

  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 2010DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual.775 cited
  • 2007A Framework for Validation of Computer Models656 cited
  • 2002Error and uncertainty in modeling and simulation629 cited
  • 2004Combining Field Data and Computer Simulations for Calibration and Prediction622 cited
  • 2012Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability332 cited
  • 2011Toward a Better Understanding of Model Validation Metrics175 cited
  • 2006Validation and error estimation of computational models162 cited
  • 2015On the Statistical Calibration of Physical Models138 cited
  • 2015Integration of model verification, validation, and calibration for uncertainty quantification in engineering systems123 cited
  • 2004The Design and Analysis of Computer Experiments122 cited
  • 2004Probabilistic Formulations for Transferring Inferences from Mathematical Models to Physical Systems105 cited
  • 2014Selection of model discrepancy priors in Bayesian calibration99 cited
  • 2008A systematic approach to model validation based on Bayesian updates and prediction related rejection criteria

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76 cited
  • 2014A Bayesian statistical method for quantifying model form uncertainty and two model combination methods53 cited
  • 2018Representing Model Inadequacy: A Stochastic Operator Approach42 cited
  • Cited by

    • 2022A collaborative model calibration framework under uncertainty considering parameter distribution13 cited
    • 2023BAYESIAN CALIBRATION WITH ADAPTIVE MODEL DISCREPANCY11 cited