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The beginning of the Monte Carlo method (1987) [pdf]

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Re: The beginning of the Monte Carlo method (1987) [pdf]

#31
post #29

Nuclear engineer here (specialty in core design/simulation). It's fun to see the Monte Carlo method be used in so many other fields now. Even in nuclear, deterministic methods are still orders of magnitude faster for most 'normal' reactor analyses on reactor configurations that are common enough to have all the important deterministic effects known. But with computers so fast, it's quite common for people, especially…

>But with computers so fast, it's quite common for people, especially in conceptual design space, to use Monte Carlo methods since it's a lot easier to believe the answer once you get it. Is it really easier to "believe" an answer on a purely stochastical level? I'm kinda surprised, I would be way more confident (if I were to choose) with answers from deterministic descriptions/equations despite being more abstract a…

Yes, definitely. With deterministic methods you have to make all sorts of approximations to discretize the spatial details of the fuel assemblies, the energy space of the neutrons, the angular directions of the neutrons, and so on. The approximations are complex and sensitive. With monte carlo methods you can treat all those things without approximations. Under the hood, both deterministic and monte carlo nucleonics methods are depending on the same measured/interpolated nuclear interaction probability tables (aka nuclear cross sections).

Re: The beginning of the Monte Carlo method (1987) [pdf]

#32

Nuclear engineer here (specialty in core design/simulation). It's fun to see the Monte Carlo method be used in so many other fields now. Even in nuclear, deterministic methods are still orders of magnitude faster for most 'normal' reactor analyses on reactor configurations that are common enough to have all the important deterministic effects known. But with computers so fast, it's quite common for people, especially…

That sounds super interesting, how does one get into simulating reactor cores? I'm very familiar with MC methods from computer graphics.

I would definitely start with some of the openmc tutorials.

https://docs.openmc.org/en/stable/usersguide/beginners.html

If you're asking at a higher level, you end up in nuclear engineering school after having a nebulous interest in energy issues.

Re: The beginning of the Monte Carlo method (1987) [pdf]

#33
post #29

Nuclear engineer here (specialty in core design/simulation). It's fun to see the Monte Carlo method be used in so many other fields now. Even in nuclear, deterministic methods are still orders of magnitude faster for most 'normal' reactor analyses on reactor configurations that are common enough to have all the important deterministic effects known. But with computers so fast, it's quite common for people, especially…

>But with computers so fast, it's quite common for people, especially in conceptual design space, to use Monte Carlo methods since it's a lot easier to believe the answer once you get it. Is it really easier to "believe" an answer on a purely stochastical level? I'm kinda surprised, I would be way more confident (if I were to choose) with answers from deterministic descriptions/equations despite being more abstract a…

MC tends to be more physically accurate (in the limit of a large number of particle histories) because it can simulate radiation transport in continuous space, energy, and angular distribution. Deterministic methods can be faster, but the discretization process is somewhat of a dark art because the underlying distributions can be highly nonlinear and rapidly varying. A combination of methods with varying levels of fidelity are typically used in real nuclear engineering applications, and are always referenced back to a common suite of experimental benchmarks for validation.

Re: The beginning of the Monte Carlo method (1987) [pdf]

#34

It's not a very good history. It says "In the late 1940s, Stanislaw Ulam invented the modern version of the Markov Chain Monte Carlo method", but as far as I know, this is incorrect. He invented a Monte Carlo method, but not a Markov chain Monte Carlo method. Markov chain Monte Carlo is generally attributed to Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller. See https://en.wikipedia.org/wiki/Metropolis-Hasting…

[deleted]

Re: The beginning of the Monte Carlo method (1987) [pdf]

#36
post #26

It's not a very good history. It says "In the late 1940s, Stanislaw Ulam invented the modern version of the Markov Chain Monte Carlo method", but as far as I know, this is incorrect. He invented a Monte Carlo method, but not a Markov chain Monte Carlo method. Markov chain Monte Carlo is generally attributed to Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller. See https://en.wikipedia.org/wiki/Metropolis-Hasting…

Here is an article "The beginning of the Monte Carlo method" by N. Metropolis: https://lib-www.lanl.gov/cgi-bin/getfile?00326866.pdf

Nice. We've changed to that from https://en.wikipedia.org/wiki/Monte_Carlo_method#History above. Thanks!

Re: The beginning of the Monte Carlo method (1987) [pdf]

#37

It's not a very good history. It says "In the late 1940s, Stanislaw Ulam invented the modern version of the Markov Chain Monte Carlo method", but as far as I know, this is incorrect. He invented a Monte Carlo method, but not a Markov chain Monte Carlo method. Markov chain Monte Carlo is generally attributed to Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller. See https://en.wikipedia.org/wiki/Metropolis-Hasting…

This comment was posted when the URL at the top was https://en.wikipedia.org/wiki/Monte_Carlo_method#History.

We've since changed it to the URL suggested by sampo at https://news.ycombinator.com/item?id=32889436.

Re: The beginning of the Monte Carlo method (1987) [pdf]

#38
Pretty cool author bio from the end of the article:

N. Metropolis received his B.S. (1937) and his Ph.D. (1941) in physics at the University of Chicago. He arrived in Los Alamos, April 1943, as a member of the original staff of fifty scientists. After the war he returned to the faculty of the University of Chicago as Assistant Professor. He came back to Los Alamos in 1948 to form the group that designed and built MANIAC I and II. (He chose the name MANIAC in the hope of stopping the rash of such acronyms for machine names, but may have, instead, only further stimulated such use.) From 1957 to 1965 he was Professor of Physics at the University of Chicago and was the founding Director of its Institute for Computer Research. In 1965 he returned to Los Alamos where he was made a Laboratory Senior Fellow in 1980. Although he retired recently, he remains active as a Laboratory Senior Fellow Emeritus.

Re: The beginning of the Monte Carlo method (1987) [pdf]

#39
The one thing I love with Monte-Carlo is the way you can use it very simply to give yourself some peace of mind that your probability formula for a finite distribution, derived with sweat and blood using very complicated combinatorics (the kind found in here: https://www.csie.ntu.edu.tw/~r97002/temp/Concrete%20Mathemat...) actually works.
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