Study of heuristics in ant system for nuclear reload optimisation
Creators
- 1. Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE). Programa de Engenharia Nuclear
Description
A Pressurized Water Reactor core must be reloaded every time the fuel burnup reaches a level when it is not possible to sustain nominal power operation. The nuclear core fuel reload optimization consists in finding a burned-up and fresh-fuel-assembly loading pattern that maximizes the number of effective full power days, minimizing the relationship cost/benefit. This problem is NP-hard, meaning that complexity grows exponentially with the number of fuel assemblies in the core. Besides that, the problem is non-linear and its search space is highly discontinual and multimodal. In this work a parallel computational system based on Ant Colony System (ACS) called Artificial-Ant-Colony Networks is used to solve the nuclear reactor core fuel reload optimization problem, with compatibles heuristics. ACS is a system based on artificial agents that uses the reinforcement learning technique and was originally developed to solve the Traveling Salesman Problem, which is conceptually similar to the nuclear fuel reload problem. (author)
Additional details
Publishing Information
- ISBN
- 978-85-99141-02-1
- Imprint Title
- Proceedings of the INAC 2007 International nuclear atlantic conference. Nuclear energy and energetic challenges for 21st. century. 15. Brazilian national meeting on reactor physics and thermal hydraulics; 8. Brazilian national meeting on nuclear applications
- Imprint Pagination
- [vp.]
- Journal Page Range
- [6 p.]
Conference
- Title
- INAC 2007 International nuclear atlantic conference. Nuclear energy and energetic challenges for 21st. century. 15. Brazilian national meeting on reactor physics and thermal hydraulics; 8. Brazilian national meeting on nuclear applications
- Dates
- 30 Sep - 5 Oct 2007
- Place
- Santos (Brazil)
INIS
- Country of Publication
- Brazil
- Country of Input or Organization
- Brazil
- INIS RN
- 39107798
- Subject category
- S21: SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS;
- Resource subtype / Literary indicator
- Conference, Non-conventional Literature
- Descriptors DEI
- ALGORITHMS; ANGRA-1 REACTOR; ANTS; COMPARATIVE EVALUATIONS; FUEL MANAGEMENT; MATHEMATICAL SOLUTIONS; OPTIMIZATION; REACTOR CORES; REACTOR FUELING; REACTOR OPERATION
- Descriptors DEC
- ANIMALS; ARTHROPODS; ENRICHED URANIUM REACTORS; EVALUATION; HYMENOPTERA; INSECTS; INVERTEBRATES; MANAGEMENT; MATHEMATICAL LOGIC; NUCLEAR MATERIALS MANAGEMENT; OPERATION; POWER REACTORS; PWR TYPE REACTORS; REACTOR COMPONENTS; REACTORS; THERMAL REACTORS; WATER COOLED REACTORS; WATER MODERATED REACTORS
Optional Information
- Notes
- 9 refs., 1 fig., 1 tab. Code: R17_1012.pdf