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Design and Analysis of Computer Experiments
3 references·16 citing·44 second hop
Design and Analysis of Computer Experiments (2014)Design and Analysis of Computer Experimen…Design and Modeling for Computer Experiments (2005)Design and Modeling for Compu…The Design and Analysis of Computer Experiments (2003)The Design and Analysis of Co…Designs for Computer Experiments (1989)Designs for Computer Experime…An adaptive Kriging method based on K-means clustering and sampling in n-ball for structural reliability analysis (2023)An adaptive Kriging method ba…Quantile-based robust optimization of a supersonic nozzle for organic rankine cycle turbines (2020)Quantile-based robust optimiz…On the usefulness of gradient information in surrogate modeling: Application to uncertainty propagation in composite material models (2020)On the usefulness of gradient…Extension of AK-MCS for the efficient computation of very small failure probabilities (2020)Extension of AK-MCS for the e…Reliability Analysis Using Adaptive Kriging Surrogates with Multimodel Inference (2019)Reliability Analysis Using Ad…Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification (2019)Demonstration of the relation…Novel algorithm using Active Metamodel Learning and Importance Sampling: Application to multiple failure regions of low probability (2018)Novel algorithm using Active …Kriging models for aero-elastic simulations and reliability analysis of offshore wind turbine support structures (2018)Kriging models for aero-elast…Emulation of environmental models using polynomial chaos expansion (2018)Emulation of environmental mo…A Decision Support System Architecture Based on Simulation Optimization for Cyber-Physical Systems (2018)A Decision Support System Arc…Zone-based reliability analysis on fatigue life of GH720Li turbine disk concerning uncertainty quantification (2017)Zone-based reliability analys…Statistical metamodeling of dynamic network loading (2017)Statistical metamodeling of d…Statistical metamodeling of dynamic network loading (2017)Statistical metamodeling of d…Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data (2017)Kriging-based inverse uncerta…Bayesian sensitivity analysis of a 1D vascular model with Gaussian process emulators (2017)Bayesian sensitivity analysis…Adaptive Uncertainty Propagation for Coupled Multidisciplinary Systems (2017)Adaptive Uncertainty Propagat…Simulation Modeling and Analysis. (1983)Design and Analysis of Computer Experiments (1989)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions (2008)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Making best use of model evaluations to compute sensitivity indices (2002)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Global sensitivity analysis for assessing the parameters importance and setting a stopping criterion in a biomedical inverse problem (2021)Efficient sensitivity analysis for biomechanical models with correlated inputs (2023)Importance Sampling for Stochastic Simulations (1989)Sensitivity of complex, internally coupled systems (1990)Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles (2011)Bayesian Optimization for Efficient Design of Uncertain Coupled Multidisciplinary Systems (2020)Bayesian Optimization Objective-Based Experimental Design (2020)Bayesian Surrogate Learning for Uncertainty Analysis of Coupled Multidisciplinary Systems (2021)Simulation and the Monte Carlo Method (2007)Simulation and the Monte Carlo Method (2016)An integrated reliability approach with improved importance sampling for low-cycle fatigue damage prediction of turbine disks (2020)Machine learning-based probabilistic fatigue assessment of turbine bladed disks under multisource uncertainties (2023)Distributed-collaborative surrogate modeling approach for creep-fatigue reliability assessment of turbine blades considering multi-source uncertainty (2024)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Uncertainty quantification of two-phase flow and boiling heat transfer simulations through a data-driven modular Bayesian approach (2019)Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments (2021)Global Sensitivity Analysis. The Primer (2007)Bayesian calibration of computer models based on Takagi–Sugeno fuzzy models (2021)Bayesian inverse uncertainty quantification of a MOOSE-based melt pool model for additive manufacturing using experimental data (2021)Functional PCA and deep neural networks-based Bayesian inverse uncertainty quantification with transient experimental data (2024)A fast and efficient response surface approach for structural reliability problems (1990)Application of kriging method to structural reliability problems (2004)Uncertainty modeling in reliability analysis of floating wind turbine support structures (2020)Sensitivity analysis of design parameters for reliability assessment of offshore wind turbine jacket support structures (2022)Reliability analysis of floating wind turbine dynamic cables under realistic environmental loads (2023)Estimation of small failure probabilities in high dimensions by subset simulation (2001)AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)Structural Reliability Analysis and Prediction (2017)A novel hybrid adaptive scheme for Kriging-based reliability estimation – A comparative study (2022)Ensemble of metamodels-assisted probability density evolution method for structural reliability analysis (2022)On active learning for Gaussian process-based global sensitivity analysis (2024)Stochastic Kriging for Simulation Metamodeling (2009)A Review on Global Sensitivity Analysis Methods (2015)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (2011)Sensitivity analysis: A review of recent advances (2015)
this work references cited by second hop

References

  • 2003The Design and Analysis of Computer Experiments2,204 cited
  • 2005Design and Modeling for Computer Experiments1,135 cited
  • 1989Designs for Computer Experiments970 cited

Cited by

  • 2017Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data75 cited
  • 2017Zone-based reliability analysis on fatigue life of GH720Li turbine disk concerning uncertainty quantification68 cited
  • 2017Adaptive Uncertainty Propagation for Coupled Multidisciplinary Systems47 cited
  • 2018Kriging models for aero-elastic simulations and reliability analysis of offshore wind turbine support structures47 cited
  • 2019Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification44 cited
  • 2017Bayesian sensitivity analysis of a 1D vascular model with Gaussian process emulators39 cited
  • 2019Reliability Analysis Using Adaptive Kriging Surrogates with Multimodel Inference38 cited
  • 2020Extension of AK-MCS for the efficient computation of very small failure probabilities35 cited
  • 2018A Decision Support System Architecture Based on Simulation Optimization for Cyber-Physical Systems34 cited
  • 2018Novel algorithm using Active Metamodel Learning and Importance Sampling: Application to multiple failure regions of low probability32 cited

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  • 2023An adaptive Kriging method based on K-means clustering and sampling in n-ball for structural reliability analysis29 cited
  • 2020On the usefulness of gradient information in surrogate modeling: Application to uncertainty propagation in composite material models24 cited
  • 2017Statistical metamodeling of dynamic network loading22 cited
  • 2020Quantile-based robust optimization of a supersonic nozzle for organic rankine cycle turbines20 cited
  • 2017Statistical metamodeling of dynamic network loading17 cited
  • 2018Emulation of environmental models using polynomial chaos expansion15 cited