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

Abstract

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.