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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 5: Piecewise polynomial approximation of probability density functions with application to uncertainty quantification for stochastic PDEs
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Chapter title
Piecewise polynomial approximation of probability density functions with application to uncertainty quantification for stochastic PDEs
Chapter number 5
Book title
Quantification of Uncertainty: Improving Efficiency and Technology
Published in
arXiv, June 2019
DOI 10.48550/arxiv.1906.10869
Book ISBNs
978-3-03-048720-1, 978-3-03-048721-8
Authors

Giacomo Capodaglio, Max Gunzburger

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 June 2019.
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#20,667,544
of 25,385,509 outputs
Outputs from arXiv
#517,221
of 915,125 outputs
Outputs of similar age
#278,688
of 365,944 outputs
Outputs of similar age from arXiv
#12,722
of 21,469 outputs
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