openmc
MCandPython
| openmc | MCandPython | |
|---|---|---|
| 4 | 2 | |
| 699 | 8 | |
| 2.3% | - | |
| 9.4 | 0.0 | |
| 6 days ago | almost 7 years ago | |
| Python | Jupyter Notebook | |
| GNU General Public License v3.0 or later | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
openmc
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The Law of Large Numbers, or Why It Is a Bad Idea to Go to the Casino
It was actually invented for this.
Open source radiation transport Monte Carlo code here if you'd like to play around:
https://github.com/openmc-dev/openmc
- Ask HN: Has anyone worked at the US National Labs before?
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The art of solving problems with Monte Carlo simulations
Even given their nuclear weapons origin, we lowly civil nuclear power engineers still use Monte Carlo methods all day every day. We all make our employers buy big supercomputers or get us access to the national lab leadership class HPC to just pound the hell out of our reactor design problems with random particle transport chains. Sure there are (dramatically) faster deterministic methods that are generally good enough, but Monte Carlo allows you to use exact geometry and not bother too much with the pesky art of computing average nuclear interaction probabilities.
Heck, my buddy at MIT made an open-source Monte Carlo code called OpenMC that's now run by Argonne National Lab [1]. Now everyone can do truly legit reactor design with Monte Carlo!
[1] https://github.com/openmc-dev/openmc
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What is the difference between std::bad_alloc and std::out_of_range
openmc source code
MCandPython
- Monte Carlo techniques and numerical estimations
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The art of solving problems with Monte Carlo simulations
I don't know if I can plug-in here some of the materials I prepared some years ago. It might help to bridge/connect the use of Monte Carlo techniques and its relations with integration:
https://github.com/ChristopheRappold/MCandPython/blob/master...
Also just to mention something else that is very interesting related with MC : "quasi-Monte Carlo techniques" (small example in https://github.com/ChristopheRappold/MCandPython/blob/master... ). For people interested in MC, just take a look to those keywords.
What are some alternatives?
monteCarlo - Finding Areas Using the Monte Carlo Method
Svelte - Cybernetically enhanced web apps
simsopt - Simons Stellarator Optimizer Code
PokerMonteCarloAPI
TexasSolver - 🚀 A very efficient Texas Holdem GTO solver :spades::hearts::clubs::diamonds:
awesome-nuclear - A curated list of open source projects used in nuclear science and engineering