Uncertainty Quantification and Predictive Computational Science A Foundation for Physical Scientists and Engineers /

This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-conse...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: McClarren, Ryan G. (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Cham : Springer International Publishing, 2018.
Ausgabe:1st ed. 2018.
Schlagworte:
Physics.
Computer mathematics.
Statistics .
Applied mathematics.
Engineering mathematics.
Mathematical physics.
Computer simulation.
ISBN:9783319995250
Online-Zugang: Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Inhaltsangabe:
  • Part I Fundamentals
  • Introduction
  • Probability and Statistics Preliminaries
  • Input Parameter Distributions
  • Part II Local Sensitivity Analysis
  • Derivative Approximations
  • Regression Approximations
  • Adjoint-based Local Sensitivity Analysis
  • Part III Parametric Uncertainty Quantification
  • From Sensitivity Analysis to UQ
  • Sampling-Based UQ
  • Reliability Methods
  • Polynomial Chaos Methods
  • Part IV Predictive Science
  • Emulators and Surrogate Models
  • Reduced Order Models
  • Predictive Models
  • Epistemic Uncertainties
  • Appendices
  • A. A cookbook of distributions.

Ähnliche Einträge