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Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines · Study

BookUncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines

Francesco Montomoli2015

Book2015

Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines

Francesco Montomoli · Mauro Carnevale · Antonio D’Ammaro · Michela Massini · Simone Salvadori

75 citations·0/0 files stored·SpringerBriefs in applied sciences and technology

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Probabilistic and Robust Engineering Design Computational Fluid Dynamics and Aerodynamics Aerospace Engineering and Applications

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2018Robust Turbine Blade Optimization in the Face of Real Geometric Variations 2024Aleatory uncertainty quantification based on multi-fidelity deep neural networks 2019A Robust Blade Design Method based on Non-Intrusive Polynomial Chaos Considering Profile Error 2023High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks 2022Efficient Uncertainty Quantification and Sensitivity Analysis on the Aerothermal Performance of Turbine Blade Squealer Tip 2020Uncertainty Quantification Approach on Numerical Simulation for Supersonic Jets Performance 2023A New Approach for Deviation Modeling in Compressors: Sensitivity-Correlated Principal Component Analysis 2023Development of a deviation package method for low-cost robust optimization in compressor blade design

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Year2015

Typebook

Published2015-01-01

VenueSpringerBriefs in applied sciences and technology

ISSN-L2191-530X

Languageen

Citations75

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1007/978-3-319-14681-2

openalex_workW4294360247

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