Free shipping on orders over $99
Uncertainty Quantification and Predictive Computational Science

Uncertainty Quantification and Predictive Computational Science

A Foundation for Physical Scientists and Engineers

by Ryan G. McClarren
Hardback
Publication Date: 19/01/2019

Share This Book:

  $175.45
or 4 easy payments of $43.86 with
afterpay
This item qualifies your order for FREE DELIVERY
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-consequence decision-making throughout the engineering and physical sciences.



Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment.



The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems.




Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.
ISBN:
9783319995243
9783319995243
Category:
Mathematical physics
Format:
Hardback
Publication Date:
19-01-2019
Publisher:
Springer International Publishing AG
Country of origin:
Switzerland
Pages:
345
Dimensions (mm):
235x155mm
Weight:
0.71kg

This title is in stock with our Australian supplier and should arrive at our Sydney warehouse within 2 - 3 weeks of you placing an order.

Once received into our warehouse we will despatch it to you with a Shipping Notification which includes online tracking.

Please check the estimated delivery times below for your region, for after your order is despatched from our warehouse:

ACT Metro: 2 working days
NSW Metro: 2 working days
NSW Rural: 2-3 working days
NSW Remote: 2-5 working days
NT Metro: 3-6 working days
NT Remote: 4-10 working days
QLD Metro: 2-4 working days
QLD Rural: 2-5 working days
QLD Remote: 2-7 working days
SA Metro: 2-5 working days
SA Rural: 3-6 working days
SA Remote: 3-7 working days
TAS Metro: 3-6 working days
TAS Rural: 3-6 working days
VIC Metro: 2-3 working days
VIC Rural: 2-4 working days
VIC Remote: 2-5 working days
WA Metro: 3-6 working days
WA Rural: 4-8 working days
WA Remote: 4-12 working days

Reviews

Be the first to review Uncertainty Quantification and Predictive Computational Science.