FUELGEN: effective evolutionary design of refuellings for pressurized water reactors

The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.

Safety issues with the South African Pebble Bed Modular Reactor: when were the issues apparent? A briefing paper

This is a briefing report on when the safety issues identified in a July 2008 report by Jülich should have become apparent In July 2008, the German Jülich nuclear research centre published a report entitled ‘A safety re-evaluation of the AVR pebble bed reactor operation and its consequences for future HTR concepts.’ It concluded: ‘pebble bed HTRs require additional safety related R&D effort and updating of safety analyses before construction.’