Computational Nuclear Engineering and Radiological Science Using Python,
Edition 1
By Ryan McClarren

Publication Date: 19 Oct 2017

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.

Key Features

  • 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
About the author
By Ryan McClarren, Associate Professor, Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, USA
Table of Contents

Part I Introduction to Python
1. Getting Started in Python
2. Digging Deeper into Python
3. Functions, Scoping, and Other Fun Stuff
4. NumPy and Matplotlib
5. Dictionaries and Functions as Arguments
6. Testing and Debugging

Part II Numerical Methods
7. Gaussian Elimination
8. LU Factorization and Banded Matrices
9. Iterative Methods for Linear Systems
10. Interpolation
11. Curve Fitting
12. Closed Root Finding Methods
13. Newton’s Methods and Related Root-Finding Techniques
14. Finite Difference Derivative Approximations
15. Numerical Integration with Newton-Cotes Formulas
16. Gauss Quadrature and Multi-dimensional Integrals
17. Initial Value Problems
18. One-Group Diffusion Equation
19. One-Group k-Eigenvalue Problems
20. Two-Group k-Eigenvalue Problems

Part III Monte Carlo Methods
21. Introduction to Monte Carlo Methods
22. Non-analog and Other Monte Carlo Variance Reduction Techniques
23. Monte Carlo Eigenvalue Calculations

Part IV Appendices
Appendix A. Installing and Running Python
Appendix B. Jupyter Notebooks

Book details
ISBN: 9780128122532
Page Count: 460
Retail Price : £93.99
  • Murray and Holbert, Nuclear Energy, 7e, Feb 2014, 576 pages, 9780124166547, Butterworth-Heinemann, $99.95
  • O'Connor, Violent Python, Nov 2012, 288 pages, 9781597499576, Syngress, $49.95
  • Lindfield and Penny, Numerical Methods, 3e, Jul 2012, 552 pages, 9780123869425, Academic Press, $94.95
  • Dunn and Shultis, Exploring Monte Carlo Methods, Apr 2011, 400 pages, 9780444515759, Elsevier Science, $127.00
  • Lewis, Fundamentals of Nuclear Reactor Physics, Jan 2008, 280 pages, 9780123706317, Academic Press, $104.00
Instructor Resources

Nuclear engineers, scientists and engineers working in radiological sciences, graduate students in nuclear sciences