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Multi-Fidelity Uncertainty Analysis in CFD Using Hierarchical Kriging · Study

WorkMulti-Fidelity Uncertainty Analysis in CFD Using Hierarchical Kriging

Pramudita Satria Palar2017

Work2017

Multi-Fidelity Uncertainty Analysis in CFD Using Hierarchical Kriging

Pramudita Satria Palar · Koji Shimoyama

25 citations·0/0 files stored·AIAA Applied Aerodynamics Conference

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Probabilistic and Robust Engineering Design Computational Fluid Dynamics and Aerodynamics Advanced Multi-Objective Optimization Algorithms

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References

2007Global sensitivity analysis using polynomial chaos expansions 2010Adaptive sparse polynomial chaos expansion based on least angle regression 2003Modeling uncertainty in flow simulations via generalized polynomial chaos 2008Polynomial chaos expansion for sensitivity analysis 2006Stochastic finite element: a non intrusive approach by regression 2010Point-Collocation Nonintrusive Polynomial Chaos Method for Stochastic Computational Fluid Dynamics 1983Cross validation of kriging in a unique neighborhood 2014A Bayesian Approach for Global Sensitivity Analysis of (Multifidelity) Computer Codes

Cited by

2020Efficient uncertainty quantification of turbine blade leading edge film cooling using bi-fidelity combination of compressed sensing and Kriging 2020Multi-fidelity uncertainty quantification of film cooling flow under random operational and geometrical conditions 2023Performance assessment of Kriging with partial least squares for high-dimensional uncertainty and sensitivity analysis 2021A maximum cost-performance sampling strategy for multi-fidelity PC-Kriging

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Year2017

Typeother

Published2017-06-02

VenueAIAA Applied Aerodynamics Conference

Languageen

Citations25

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.2514/6.2017-3261

openalex_workW2636043142

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