Computational Nuclear Engineering and Radiological Science Using Python

Paperback Engels 2017 9780128122532
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9780128122532
Taal:Engels
Bindwijze:Paperback

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Inhoudsopgave

<p>Part I Introduction to Python<br>1. Getting Started in Python<br>2. Digging Deeper into Python<br>3. Functions, Scoping, and Other Fun Stuff<br>4. NumPy and Matplotlib<br>5. Dictionaries and Functions as Arguments<br>6. Testing and Debugging</p> <p>Part II Numerical Methods<br>7. Gaussian Elimination<br>8. LU Factorization and Banded Matrices<br>9. Iterative Methods for Linear Systems<br>10. Interpolation<br>11. Curve Fitting<br>12. Closed Root Finding Methods<br>13. Newton’s Methods and Related Root-Finding Techniques<br>14. Finite Difference Derivative Approximations<br>15. Numerical Integration with Newton-Cotes Formulas<br>16. Gauss Quadrature and Multi-dimensional Integrals<br>17. Initial Value Problems<br>18. One-Group Diffusion Equation<br>19. One-Group k-Eigenvalue Problems<br>20. Two-Group k-Eigenvalue Problems</p> <p>Part III Monte Carlo Methods<br>21. Introduction to Monte Carlo Methods<br>22. Non-analog and Other Monte Carlo Variance Reduction Techniques<br>23. Monte Carlo Eigenvalue Calculations</p> <p>Part IV Appendices<br>Appendix A. Installing and Running Python<br>Appendix B. Jupyter Notebooks<br></p>

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        Computational Nuclear Engineering and Radiological Science Using Python