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Quantification of Uncertainty: Improving Efficiency and Technology

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Cover of 'Quantification of Uncertainty: Improving Efficiency and Technology'

Table of Contents

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    Book Overview
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    Chapter 1 Effect of Load Path on Parameter Identification for Plasticity Models Using Bayesian Methods
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    Chapter 2 A Compressive Spectral Collocation Method for the Diffusion Equation Under the Restricted Isometry Property
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    Chapter 3 Surrogate-Based Ensemble Grouping Strategies for Embedded Sampling-Based Uncertainty Quantification
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    Chapter 4 Conservative Model Order Reduction for Fluid Flow
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    Chapter 5 Piecewise Polynomial Approximation of Probability Density Functions with Application to Uncertainty Quantification for Stochastic PDEs
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    Chapter 5 Piecewise polynomial approximation of probability density functions with application to uncertainty quantification for stochastic PDEs
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    Chapter 6 Analysis of Probabilistic and Parametric Reduced Order Models
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    Chapter 7 Reduced Order Isogeometric Analysis Approach for PDEs in Parametrized Domains
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    Chapter 8 Uncertainty Quantification Applied to Hemodynamic Simulations of Thoracic Aorta Aneurysms: Sensitivity to Inlet Conditions
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    Chapter 9 Cavitation Model Parameter Calibration for Simulations of Three-Phase Injector Flows
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    Chapter 10 Non-intrusive Polynomial Chaos Method Applied to Full-Order and Reduced Problems in Computational Fluid Dynamics: A Comparison and Perspectives
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    Chapter 11 A Practical Example for the Non-linear Bayesian Filtering of Model Parameters
Attention for Chapter 4: Conservative Model Order Reduction for Fluid Flow
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Citations

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Chapter title
Conservative Model Order Reduction for Fluid Flow
Chapter number 4
Book title
Quantification of Uncertainty: Improving Efficiency and Technology
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-48721-8_4
Book ISBNs
978-3-03-048720-1, 978-3-03-048721-8
Authors

Babak Maboudi Afkham, Nicolò Ripamonti, Qian Wang, Jan S. Hesthaven

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 44%
Other 1 6%
Student > Master 1 6%
Researcher 1 6%
Student > Postgraduate 1 6%
Other 0 0%
Unknown 6 33%
Readers by discipline Count As %
Engineering 7 39%
Mathematics 1 6%
Medicine and Dentistry 1 6%
Energy 1 6%
Unknown 8 44%