Home » Introduction to Uncertainty Quantification

Introduction to Uncertainty Quantification Book [PDF] Download

Download the fantastic book titled Introduction to Uncertainty Quantification written by T.J. Sullivan, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Introduction to Uncertainty Quantification", which was released on 14 December 2015. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Mathematics genre.

Summary of Introduction to Uncertainty Quantification by T.J. Sullivan PDF

This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study. Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field. T. J. Sullivan was Warwick Zeeman Lecturer at the Mathematics Institute of the University of Warwick, United Kingdom, from 2012 to 2015. Since 2015, he is Junior Professor of Applied Mathematics at the Free University of Berlin, Germany, with specialism in Uncertainty and Risk Quantification.

Introduction to Uncertainty Quantification

Detail About Introduction to Uncertainty Quantification PDF

  • Author : T.J. Sullivan
  • Publisher : Springer
  • Genre : Mathematics
  • Total Pages : 342 pages
  • ISBN : 3319233955
  • PDF File Size : 43,8 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

Clicking on the GET BOOK button will initiate the downloading process of Introduction to Uncertainty Quantification by T.J. Sullivan. This book is available in ePub and PDF format with a single click unlimited downloads.

GET BOOK

Introduction to Uncertainty Quantification

Introduction to Uncertainty Quantification
  • Publisher : Springer
  • File Size : 51,5 Mb
  • Release Date : 14 December 2015
GET BOOK

This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which

Handbook of Uncertainty Quantification

Handbook of Uncertainty Quantification
  • Publisher : Springer
  • File Size : 38,9 Mb
  • Release Date : 08 May 2016
GET BOOK

The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of ideas

Uncertainty in Engineering

Uncertainty in Engineering
  • Publisher : Springer Nature
  • File Size : 43,5 Mb
  • Release Date : 06 June 2024
GET BOOK

This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then

Uncertainty Quantification

Uncertainty Quantification
  • Publisher : Springer
  • File Size : 30,9 Mb
  • Release Date : 24 April 2017
GET BOOK

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it

Uncertainty Quantification

Uncertainty Quantification
  • Publisher : SIAM
  • File Size : 46,6 Mb
  • Release Date : 02 December 2013
GET BOOK

The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate

Uncertainty Quantification and Predictive Computational Science

Uncertainty Quantification and Predictive Computational Science
  • Publisher : Springer
  • File Size : 22,7 Mb
  • Release Date : 23 November 2018
GET BOOK

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

Spectral Methods for Uncertainty Quantification

Spectral Methods for Uncertainty Quantification
  • Publisher : Springer Science & Business Media
  • File Size : 24,9 Mb
  • Release Date : 11 March 2010
GET BOOK

This book deals with the application of spectral methods to problems of uncertainty propagation and quanti?cation in model-based computations. It speci?cally focuses on computational and algorithmic features of

An Introduction to Uncertainty in Measurement

An Introduction to Uncertainty in Measurement
  • Publisher : Cambridge University Press
  • File Size : 23,5 Mb
  • Release Date : 01 June 2006
GET BOOK

Measurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify

Nanoelectronic Coupled Problems Solutions

Nanoelectronic Coupled Problems Solutions
  • Publisher : Springer Nature
  • File Size : 45,9 Mb
  • Release Date : 06 November 2019
GET BOOK

Designs in nanoelectronics often lead to challenging simulation problems and include strong feedback couplings. Industry demands provisions for variability in order to guarantee quality and yield. It also requires the