SUMMARY
The discussion centers on resources for learning MCNP (Monte Carlo N-Particle Transport Code), particularly for beginners. Key recommendations include the new version of the MCNP Primer by J. Kenneth Shultis and Amir A. Bahadori, and the MCNP Guide by Dr. Andy Boston, which provides practical insights into simulating real events. The MCNP version 6.3 manual is also highlighted as a valuable resource, despite its length. Additionally, the CardSharp Python library is introduced as a tool for generating MCNP input decks, beneficial for newcomers to the software.
PREREQUISITES
- Familiarity with MCNP (Monte Carlo N-Particle Transport Code)
- Basic understanding of nuclear reactor physics
- Knowledge of Python programming for using CardSharp
- Access to the MCNP version 6.3 manual
NEXT STEPS
- Study the MCNP Primer by J. Kenneth Shultis and Amir A. Bahadori
- Read the MCNP Guide by Dr. Andy Boston for practical simulation techniques
- Explore the CardSharp Python library for generating MCNP input decks
- Review the MCNP version 6.3 manual for comprehensive understanding
USEFUL FOR
This discussion is beneficial for researchers, students, and professionals in nuclear engineering, particularly those new to MCNP and seeking effective learning resources and tools.