Particle Swarm Optimization Applied to the Nuclear Fuel Bundle Spacer Grid Spring Design

Particle Swarm Optimization: A Powerful Technique for Solving Engineering Problems

“…In [24], the authors perform the optimization of dimples and spring geometries existing in the nuclear fuel bundle (FB) spacer grid (SG). An FB is a structured group of fuel rods (FRs), and it is also known as fuel assembly, and on the other hand, an FR is a long, slender, zirconium metal tube containing pellets of fissionable material, which provide fuel for nuclear reactors [25].…”

“…In PSO simulations from Ref. [24], for each position vector X t i , there is an FEA model with the geometry variable values of its related vector. In such FEA model, there are boundary conditions of an elastic static analysis.…”

“…The goals of the optimization performed in [24] are three: first, to minimize the stress intensity (SI) within the structure; second, to create an SG geometry featuring a gripping stiffness value as close as possible to some K reference ; and finally, to find a geometry that allows some axial thermal expiation by the FR. These three features are the main mechanical design requirements for an SG [26].…”

“…Meanwhile, the parameter c k is a coefficient that must be set in order to fit the order of magnitude between the fitness function's terms, so none of them gets greater importance. In [24], c k parameter had been calibrated by performing several PSO simulations, and then, this value was set to be 60. One should notice that the fitness function does not require a unit consistency, as its value is only a mathematical abstraction.…”

“…In [31], the authors performed an FEA and a real experiment to measure the SI and the gripping stiffness of the Chashma Nuclear Power Plant Unit 1's (CHASNUPP-1's) SG spring under the same conditions as considered in [24]. The results from [31] regarding a real SG that is in operation at CHASNUPP-1, which might not have been optimized, are 27.2 N/mm for the gripping stiffness and 816 MPa for the SI; meanwhile, the optimized result found in [24] has the same gripping stiffness although with an SI over 75% lower than CHASNUPP-1's SG. Thus, when comparing the results of the most likely optimal found using the PSO algorithm with those from a real SG [31], one can conclude that PSO had played its role well to design the component under study.…”