FuelGen: a genetic algorithm-based system for fuel loading pattern design in nuclear power reactors

✍ Scribed by Jun Zhao; Brian Knight; Ephraim Nissan; Alan Soper

• Book ID: 104361316
• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 369 KB
• Volume: 14
• Category: Article
• ISSN: 0957-4174
• DOI: 10.1016/s0957-4174(98)00005-0

✦ Synopsis

How to 'refuel' a nuclear power reactor, when it is shut down every year or so between two successive operation cycles, is the 'in-core fuel management' problem. To solve it, it is necessary to design and simulate a safe and efficient fuel loading pattern. 'Reload design' plays a crucial role in nuclear power plant operation, in terms of both economy and safety. This article presents FuelGen, a system embodying a specialized genetic algorithm for designing refuellings. The tests on well-researched cases have shown that the algorithm is capable of finding a better loading pattern-enabling the reactor to run both longer and more efficiently per cycle-than solutions reported in the domain literature and found by other methods, such as expert systems and simulated annealing. Over a decade, the parent-project Fuelcon first inaugurated the rule-driven refuelling paradigm, then turned to probing hybrid architectures. Its sequel, FuelGen, radically supersedes Fuelcon's search mechanism, while retaining the architectural and ergonomic outlook that Fuelcon had evolved.