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Uncertainty quantification and film cooling
7 references·5 citing·32 second hop
Uncertainty quantification and film cooling (2012)Uncertainty quantification and film cooli…Comparison of Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Quantification (2009)Comparison of Non-Intrusive P…Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods (2007)Probabilistic collocation met…A Non-Intrusive Polynomial Chaos Method For Uncertainty Propagation in CFD Simulations (2006)A Non-Intrusive Polynomial Ch…Uncertainty analysis for fluid mechanics with applications (2002)Uncertainty analysis for flui…The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)The Wiener--Askey Polynomial …Direct incorporation of uncertainty in chemical and environmental engineering systems (1995)Direct incorporation of uncer…Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Investigation on high-dimensional uncertainty quantification and reliability analysis of aero-engine (2023)Investigation on high-dimensi…Multi-fidelity uncertainty quantification of film cooling flow under random operational and geometrical conditions (2020)Multi-fidelity uncertainty qu…Efficient uncertainty quantification of turbine blade leading edge film cooling using bi-fidelity combination of compressed sensing and Kriging (2020)Efficient uncertainty quantif…Efficient uncertainty quantification of stochastic heat transfer problems by combination of proper orthogonal decomposition and sparse polynomial chaos expansion (2018)Efficient uncertainty quantif…Effects of operational and geometrical uncertainties on heat transfer and pressure drop of ribbed passages (2017)Effects of operational and ge…Polynomial Chaos in Stochastic Finite Elements (1990)Stochastic Finite Elements with Multiple Random Non-Gaussian Properties (1999)Uncertainty analysis for the steady-state flows in a dual throat nozzle (2004)Robust Aerodynamic Design Optimization Using Polynomial Chaos (2009)Uncertainty Quantification of Hypersonic Reentry Flows with Sparse Sampling and Stochastic Expansions (2014)The Massachusetts Institute of Technology (1999)Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos (2002)A concept for data-driven uncertainty quantification and its application to carbon dioxide storage in geological formations (2011)Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations (2014)Coherence motivated sampling and convergence analysis of least squares polynomial Chaos regression (2015)Structural reliability under combined random load sequences (1978)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)Mixed aleatory-epistemic uncertainty quantification with stochastic expansions and optimization-based interval estimation (2011)Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual (2014)First order reliability method for time-variant problems using series expansions (2014)Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Efficient Sampling for Non-Intrusive Polynomial Chaos Applications with Multiple Uncertain Input Variables (2007)Simulation-based optimal Bayesian experimental design for nonlinear systems (2012)Stochastic finite element methods for partial differential equations with random input data (2014)The Predictive Sample Reuse Method with Applications (1975)Global sensitivity analysis using polynomial chaos expansions (2007)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Efficient uncertainty quantification of stochastic problems in CFD by combination of compressed sensing and POD-Kriging (2022)Design and Analysis of Experiments (2017)Uncertainty quantification and global sensitivity analysis of double-diffusive natural convection in a porous enclosure (2020)Propagating input uncertainties into parameter uncertainties and model prediction uncertainties—A review (2023)The Impact of Uncertainty Shocks (2009)POLYNOMIAL-CHAOS-BASED KRIGING (2015)AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)A least-squares approximation of partial differential equations with high-dimensional random inputs (2009)Uncertainty quantification in chemical systems (2009)DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. (2011)
this work references cited by second hop

References

  • 1991Stochastic Finite Elements: A Spectral Approach5,753 cited
  • 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
  • 2009Comparison of Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Quantification348 cited
  • 2006A Non-Intrusive Polynomial Chaos Method For Uncertainty Propagation in CFD Simulations335 cited
  • 2007Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods253 cited
  • 1995Direct incorporation of uncertainty in chemical and environmental engineering systems147 cited
  • 2002Uncertainty analysis for fluid mechanics with applications143 cited

Cited by

  • 2018Efficient uncertainty quantification of stochastic heat transfer problems by combination of proper orthogonal decomposition and sparse polynomial chaos expansion27 cited
  • 2017Effects of operational and geometrical uncertainties on heat transfer and pressure drop of ribbed passages27 cited
  • 2023Investigation on high-dimensional uncertainty quantification and reliability analysis of aero-engine24 cited
  • 2020Efficient uncertainty quantification of turbine blade leading edge film cooling using bi-fidelity combination of compressed sensing and Kriging22 cited
  • 2020Multi-fidelity uncertainty quantification of film cooling flow under random operational and geometrical conditions14 cited

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