Nuclear Mathematics: Simplifying Complex Equations in Reactor Physics

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SUMMARY

The discussion centers on the complexities of nuclear mathematics in reactor physics, specifically addressing the challenges posed by transport theory and diffusion theory. Participants recommend "Advanced Engineering Mathematics, 9th Edition" by Erwin Kreyszig as a comprehensive resource for understanding the necessary mathematical concepts, including ordinary differential equations, linear algebra, and partial differential equations. The book covers essential topics such as Laplace transforms, Fourier analysis, and numerical analysis, which are critical for mastering the mathematical foundations of nuclear reactor physics. A link to purchase the book is provided for convenience.

PREREQUISITES
  • Understanding of partial differential equations
  • Familiarity with ordinary differential equations (ODEs)
  • Knowledge of linear algebra and vector calculus
  • Basic concepts of Fourier analysis
NEXT STEPS
  • Study "Advanced Engineering Mathematics, 9th Edition" by Erwin Kreyszig
  • Learn about numerical methods for ODEs and PDEs
  • Explore advanced topics in linear algebra, including eigenvalue problems
  • Research applications of Fourier series and transforms in engineering
USEFUL FOR

Nuclear engineers, physics students, and anyone involved in reactor physics who seeks to simplify complex mathematical equations and improve their understanding of the underlying mathematical principles.

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Is there any book that details the nuclear mathematics equations?
i am facing a problems in reading "Nuclear reactor physics", it contains complex mathematics.

B/R
 
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Nuclear reactor physics involves primarily transport theory and it's simplification, diffusion theory, both of which require knowledge of partial differential equations and systems of equations.

Perhaps Advanced Engineering Mathematics, 9th Edition by Erwin Kreyszig would help.

PART A: ORDINARY DIFFERENTIAL EQUATIONS (ODE'S).
Chapter 1. First-Order ODE's.

Chapter 2. Second Order Linear ODE's.

Chapter 3. Higher Order Linear ODE's.

Chapter 4. Systems of ODE's Phase Plane, Qualitative Methods.

Chapter 5. Series Solutions of ODE's Special Functions.

Chapter 6. Laplace Transforms.

PART B: LINEAR ALGEBRA, VECTOR CALCULUS.

Chapter 7. Linear Algebra: Matrices, Vectors, Determinants: Linear Systems.

Chapter 8. Linear Algebra: Matrix Eigenvalue Problems.

Chapter 9. Vector Differential Calculus: Grad, Div, Curl.

Chapter 10. Vector Integral Calculus: Integral Theorems.

PART C: FOURIER ANALYSIS, PARTIAL DIFFERENTIAL EQUATIONS.

Chapter 11. Fourier Series, Integrals, and Transforms.

Chapter 12. Partial Differential Equations (PDE's).

Chapter 13. Complex Numbers and Functions.

Chapter 14. Complex Integration.

Chapter 15. Power Series, Taylor Series.

Chapter 16. Laurent Series: Residue Integration.

Chapter 17. Conformal Mapping.

Chapter 18. Complex Analysis and Potential Theory.

PART E: NUMERICAL ANALYSIS SOFTWARE.

Chapter 19. Numerics in General.

Chapter 20. Numerical Linear Algebra.

Chapter 21. Numerics for ODE's and PDE's.

PART F: OPTIMIZATION, GRAPHS.

Chapter 22. Unconstrained Optimization: Linear Programming.

Chapter 23. Graphs, Combinatorial Optimization.

PART G: PROBABILITY; STATISTICS.

Chapter 24. Data Analysis: Probability Theory.

Chapter 25. Mathematical Statistics.
 
Do u have the link for this book?

Thaks...
but do u have the link for this book?
 

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