Optimization of Core Loading Patterns

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Discussion Overview

The discussion centers around the optimization of core loading patterns in nuclear reactors, exploring various methods and their effectiveness. Participants examine both automated optimization techniques and the importance of expert knowledge in achieving optimal designs, with a focus on burnup calculations and neutronics models.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant suggests that optimization methods like Genetic Algorithms and Neural Networks may not be effective for core loading pattern optimization, emphasizing the role of expert knowledge.
  • Another participant notes that vendors have their own optimization codes based on designer experience, and that no unit has developed a fully optimized equilibrium cycle.
  • A participant highlights the significance of accurate burnup calculations in core pattern optimization and the need for in-core fuel management experts to evaluate different criteria.
  • Discussion includes references to specific optimization codes, such as ROSA, and mentions the potential for improvement in reactor optimization based on academic research.
  • Automated optimization methods like simulated annealing and genetic algorithms are discussed, with a participant noting that while they can provide new ideas, they often do not outperform experienced designers.
  • Concerns are raised about the computational speed of optimization methods, with a focus on the balance between model accuracy and computational expense.
  • Participants express curiosity about the neutronics models and computational methods used in the ROSA code, with references to specific methodologies like LWRSIM.

Areas of Agreement / Disagreement

Participants express a range of views on the effectiveness of various optimization methods, with no consensus on the superiority of any particular approach. There is acknowledgment of the importance of expert input, but also recognition of the potential benefits of automated methods.

Contextual Notes

Participants mention limitations related to the accuracy of certain methods and the computational demands of different optimization techniques, indicating that the discussion is influenced by specific operational contexts and assumptions about model performance.

Who May Find This Useful

This discussion may be of interest to professionals and researchers in nuclear engineering, particularly those focused on reactor design, optimization techniques, and computational modeling in nuclear systems.

libertad
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Hi There,
What's the best core loading pattern optimization method?
I believe this is very depended to experts knowledge, I mean the methods such as Genetic Algorithm or Neural Network or Ant Colony are not so useful for such these optimization.
Please correct me if I'm wrong on this.

Thanks
 
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Each vendor has a loading pattern optimization code, and it does come from a designers experience. No unit ever develops an optimized equilibrium cycle, but some come close. The actual design depends on the operations of a given cycle, whether it runs long or short, and has an excess or deficiency in reactivity.

A Dutch company, NRG, is an independent company (not a fuel supplier). They have a LP-optimization code, ROSA. Here are some papers:

http://www.nrg.eu/docs/ppt/rosa/rosatop.pdf

http://www.nrg.eu/docs/ppt/rosa/rosanfm3.pdf

http://www.nrg.eu/docs/ppt/rosa/rosatopfuel05.pdf

Here is a brochure for the Westinghouse system
http://www.westinghousenuclear.com/Products_&_Services/docs/NEXUSANC9Brochure.pdf
 
Last edited by a moderator:
Thanka Astronuc,
I know about Rosa code. I believe the most important part in core pattern optimization is an accurate burnup calculation.
With the accurate burnup calculation now this is the in-core fuel management expert who shoud compare the different criteria for some patterns to choose the best one.
the criteria for BOC and then criteria for during the cycle I mean from BOC to EOC.
What's your idea?
 
At Ohio State University, a PhD student did her thesis by optimizing the research reactor more that it had been, so there's always room for improvement.
 
daveb said:
At Ohio State University, a PhD student did her thesis by optimizing the research reactor more that it had been, so there's always room for improvement.

How can I reach to her study?
 
This is a slightly old post, but I'll comment anyway.

As for automated optimization methods, there is a plethora of recent work on all sorts of bizarre methods (ant colony, swarm, etc.). The most important methods in practice have been simulated annealing, and, to a lesser extent, genetic algorithms. The main drawback to simulated annealing is the relatively long computation times, though this has been alleviated by parallel versions of the algorithm (look up Studsvik's COPERNICUS code). Genetic algorithms are much more easily parallelized, but some details of implementation become tedious for LP problems (e.g. given two patterns, what makes a good "mating" scheme so that materials are conserved as well as portions of the pattern that are "good").

Either of these methods can be helped by heuristics based on experience or plain old good sense. From what I've been told by folks who have done a lot of this stuff, the automated schemes rarely produce better patterns than an experienced designer. What the automated schemes can do, however, is provide new ideas that may lead the designer toward even better patterns.

As for the most important component of it all, really speed is the critical issue. Optimizers can use any neutronics model; the better a model is, the more expensive it tends to be. Codes like ROSA or XIMAGE have quite good models that are also relatively inexpensive computationally. I think a standard practice has been to use as crude a neutronics model as possible, after which the best patterns are evaluated with a license-grade model.

If you're at all interested in the implementation of this stuff, I have a little side project called "poropy" (look it up at github) for really simple LP problems. It doesn't have burnup or thermal hydraulic feedback yet (though hopefully this summer in my spare time).
 
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Recently I saw a run of ROSA code and I was really surprised with the speed of core calculation of ROSA code.
anyone know about the neutronic models and computation methods they applied in ROSA?
 
libertad said:
Recently I saw a run of ROSA code and I was really surprised with the speed of core calculation of ROSA code.
anyone know about the neutronic models and computation methods they applied in ROSA?

"The neutronics model in ROSA is an accelerated version of LWRSIM."
ftp://ftp.nrg.eu/pub/www/nrg/ppt/rosa/rosamb.pdf

"The neutronics model is based upon a kernel method."
www.nrg.eu/docs/ppt/rosa/rosajt.pdf

One will have to find some papers on LWRSIM.
 
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Thanks Astronuc,
LWRWIMis really fast. I think this method is proper to only compare different LP as it became applied in ROSA. this method has not been applied in well known reactor core simulator codes because I think it is not too accurate.
 

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