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Uncertainty Quantification in Scientific Computing

Overview of attention for book
Uncertainty Quantification in Scientific Computing
Springer, Berlin, Heidelberg

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Uncertainties Using Genomic Information for Evidence-Based Decisions
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    Chapter 2 Considerations of Uncertainty in Regulatory Decision Making
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    Chapter 3 An Industrial Viewpoint on Uncertainty Quantification in Simulation: Stakes, Methods, Tools, Examples
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    Chapter 4 Living with Uncertainty
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    Chapter 5 Uncertainty and Sensitivity Analysis: From Regulatory Requirements to Conceptual Structure and Computational Implementation
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    Chapter 6 Bayes Linear Analysis for Complex Physical Systems Modeled by Computer Simulators
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    Chapter 7 Verified Computation with Probabilities
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    Chapter 8 Defects, Scientific Computation and the Scientific Method
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    Chapter 9 Parametric and Uncertainty Computations with Tensor Product Representations
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    Chapter 10 Uncertainty Quantification in Scientific Computing
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    Chapter 11 Measuring Uncertainty in Scientific Computation Using Numerica 21’s Test Harness
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    Chapter 12 Numerical Aspects in the Evaluation of Measurement Uncertainty
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    Chapter 13 Model-Based Interpolation, Prediction, and Approximation
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    Chapter 14 Uncertainty Quantification for Turbulent Mixing Flows: Rayleigh-Taylor Instability
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    Chapter 15 From Quantification to Visualization: A Taxonomy of Uncertainty Visualization Approaches
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    Chapter 16 Efficient Computation of Observation Impact in 4D-Var Data Assimilation
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    Chapter 17 Interval Based Finite Elements for Uncertainty Quantification in Engineering Mechanics
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    Chapter 18 Reducing the Uncertainty When Approximating the Solution of ODEs
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    Chapter 19 Uncertainties in Predictions of Material Performance Using Experimental Data That Is Only Distantly Related to the System of Interest
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    Chapter 20 A Note on Uncertainty in Real-Time Analytics
Attention for Chapter 5: Uncertainty and Sensitivity Analysis: From Regulatory Requirements to Conceptual Structure and Computational Implementation
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Chapter title
Uncertainty and Sensitivity Analysis: From Regulatory Requirements to Conceptual Structure and Computational Implementation
Chapter number 5
Book title
Uncertainty Quantification in Scientific Computing
Published by
Springer, Berlin, Heidelberg, January 2012
DOI 10.1007/978-3-642-32677-6_5
Book ISBNs
978-3-64-232676-9, 978-3-64-232677-6
Authors

Jon C. Helton, Cédric J. Sallaberry

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 56%
Professor 2 22%
Researcher 1 11%
Student > Master 1 11%
Readers by discipline Count As %
Mathematics 4 44%
Engineering 3 33%
Decision Sciences 1 11%
Design 1 11%