computational nuclear engineering and radiological science using python

Computational Nuclear Engineering And Radiological Science Using Python
Author: Ryan McClarren
Publisher: Academic Press
Release Date: 2017-10-27
Pages: 460
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Computational Nuclear Engineering and Radiological Science Using Python provides the necessary knowledge users need to embed more modern computing techniques into current practices, while also helping practitioners replace Fortran-based implementations with higher level languages. The book is especially unique in the market with its implementation of Python into nuclear engineering methods, seeking to do so by first teaching the basics of Python, then going through different techniques to solve systems of equations, and finally applying that knowledge to solve problems specific to nuclear engineering. Along with examples of code and end-of-chapter problems, the book is an asset to novice programmers in nuclear engineering and radiological sciences, teaching them how to analyze complex systems using modern computational techniques. For decades, the paradigm in engineering education, in particular, nuclear engineering, has been to teach Fortran along with numerical methods for solving engineering problems. This has been slowly changing as new codes have been written utilizing modern languages, such as Python, thus resulting in a greater need for the development of more modern computational skills and techniques in nuclear engineering. Offers numerical methods as a tool to solve specific problems in nuclear engineering Provides examples on how to simulate different problems and produce graphs using Python Supplies accompanying codes and data on a companion website, along with solutions to end-of-chapter problems

Exam Prep For  Computational Nuclear Engineering And
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Uncertainty Quantification And Predictive Computational Science
Author: Ryan G. McClarren
Publisher: Springer
Release Date: 2018-11-23
Pages: 345
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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.

Government Reports Announcements   Index
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Release Date: 1996
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Available Language: English, Spanish, And French
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Issues In Biological And Life Sciences Research  2011 Edition
Author:
Publisher: ScholarlyEditions
Release Date: 2012-01-09
Pages: 5106
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Issues in Biological and Life Sciences Research: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Biological and Life Sciences Research. The editors have built Issues in Biological and Life Sciences Research: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Biological and Life Sciences Research in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Biological and Life Sciences Research: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.