Computational Skills of a Nuclear Engineer

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Discussion Overview

The discussion centers around the importance of computational skills in nuclear engineering, particularly focusing on the role of programming languages such as Python, Fortran, and C in scientific computing applications within the field. Participants explore the relevance of computational physics and share insights on learning and practicing these skills.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants suggest that computational skills are not strictly necessary in nuclear engineering but can provide a valuable niche for those who enjoy them.
  • Python is noted for its ease of use and rapid development time, particularly for data analysis, with libraries like scipy and numpy enhancing its capabilities.
  • Others argue that Fortran and C are more suitable for serious scientific computing, especially due to the prevalence of legacy code in the industry.
  • One participant expresses a preference for Python, stating that it is easier to learn and use compared to Fortran and C, despite acknowledging Python's slower performance.
  • There is mention of the MOOSE system and other modern methods being developed in C++, indicating a shift in some areas of nuclear engineering programming.
  • Concerns are raised about the future of Fortran, with some participants believing it is becoming obsolete.
  • Participants emphasize the importance of the specific applications within nuclear engineering when considering the necessity of computational skills.

Areas of Agreement / Disagreement

Participants express a mix of opinions regarding the importance of computational skills and the choice of programming languages, with no clear consensus on the superiority of one language over another for nuclear engineering applications. Some believe Python is sufficient for certain tasks, while others maintain that Fortran and C are essential for more complex scientific computing.

Contextual Notes

There are varying assumptions about the applications of nuclear engineering and the specific contexts in which different programming languages are utilized. The discussion reflects a range of experiences and perspectives on the relevance of computational skills in the field.

Who May Find This Useful

This discussion may be useful for students and professionals in nuclear engineering, programming enthusiasts, and those interested in the computational aspects of scientific research.

Vnt666Skr
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This Fall I will be joining my university for MS Nuclear Engineering. My undergraduate major is Mechanical Engineering. I have a few questions.

1. How important is computational physics in Nuclear Engineering?
2. How to go about learning and practicing it in the context of nuclear engineering applications?

I have some experience in basic programming using Python 2.7 and would like to take it to the next level.

3. How does python fare in comparison to C,FORTRAN etc in scientific computing?Thank you
 
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I can answer 3 to a certain extant. For quick calculations, maybe, but for any real scientific computing, you should probably be using Fortran or C. That being said, python is quite nice for data analysis, particularly with scipy and numpy. I used python in that manner for about 10 years, producing publication quality plots quite easily.
 
Thank you very much kinkmode ! Waiting for more responses.
 
computational skills are not necessary in nuclear engineering, but they will certainly place you in a valuable niche if it's something you enjoy. Python is an excellent language that can be integrated with much of the software used in the industry, especially for data analysis as mentioned above. With that said, much of the industry software is written in Fortran. This is mostly because much of the industry software is very old and resistant to change. In my personal opinion, Fortran does not have much of a future, but perhaps I'll be proven wrong.
 
I do not have much experience in nuclear engineering, however, I am a novice programmer and I would like to state that python is a great language for computations and it has fast developing time and many libraries. I wouldn't bother with fortran, because it is dying out.

I can't think of any scenario where you would want to use C over Python for calculations, with the exception of boolean algebra or if you have to directly access some memory addresses or do some OS internals. And even then, Python can even do boolean algebra
 
Vnt666Skr said:
This Fall I will be joining my university for MS Nuclear Engineering. My undergraduate major is Mechanical Engineering. I have a few questions.

1. How important is computational physics in Nuclear Engineering?
2. How to go about learning and practicing it in the context of nuclear engineering applications?

I have some experience in basic programming using Python 2.7 and would like to take it to the next level.

3. How does python fare in comparison to C,FORTRAN etc in scientific computing?Thank you

1. It depends on what type of applications of nuclear engineering you end up working on. There is a lot of subfields in nuclear engineering and the starter question is what interests you the most?

2. Introduction to Nuclear Engineering by Lamash is a great starter texts for learning the basics of nuclear engineering. https://www.amazon.com/dp/0201824981/?tag=pfamazon01-20. That will give you some insight into where computational physics is utilized. (See Neutron Transport Equation and diffusion equation)

3. I've never seen python used outside of simple data analysis. In my experience, Fortran is almost exclusively used for any major programming efforts in nuclear engineering. It's not great, but that's what a lot of people still use in the industry. I have seen a lot of noise about using C or C++ in nuclear detection applications though.

Good luck!
 
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Thanks for your insight Smed,x86 and Thermalne.
I enjoyed programming in Python. FORTRAN and C although more popular, are not as easy to use and learn as Python. Yes, Python tends to be slower than the other two. But now that I am learning and liking it, I don't think it's wise to leave it midway and pursue something else. Better to be good at one thing than dabble in two, isn't it?
 
Most scientific programming is done in Fortran or C/C++, with some support (e.g., script files) doen in python.

A lot of legacy code (core simulators, CFD/TH, reactor/plant analysis, . . . ) is written in Fortran. Modern methods (INL's MOOSE system and herd) are more likely to be written in C++, especially for large scale analytical software requiring massive parallelization.
 

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