Title :
Neutron flux flattening in PWRs using neural networks in fuel management
Author :
Sadighi, Mostafa ; Setayeshi, Saeed ; Salehi, Ali Akbar
Author_Institution :
Nucl. Power Plant Div., Atomic Energy Organ. of Iran, Tehran, Iran
fDate :
6/1/2002 12:00:00 AM
Abstract :
The Hopfield network is studied from the standpoint of taking it as a computational model in optimizing the fuel management of pressurized water reactors (PWRs). In this paper, the flattening of the neutron flux is considered as the objective function. By this consideration, the power peaking inside the reactor core is also minimized. Regarding the local minimum problem of Hopfield network, the simulated annealing method is applied to improve the Hopfield solution. The method is applied to Bushehr Nuclear Power Plant (PWR design) and the result is compared with the core configuration purposed by the designer
Keywords :
Hopfield neural nets; fission reactor kinetics; fission reactor operation; neutron flux; nuclear engineering computing; simulated annealing; Bushehr Nuclear Power Plant; Hopfield network; PWRs; core configuration; fuel management; local minimum problem; neutron flux flattening; objective function; power peaking; pressurized water reactors; simulated annealing method; Assembly; Biological neural networks; Computer network management; Fuels; Hopfield neural networks; Inductors; Intelligent networks; Neural networks; Neutrons; Power generation;
Journal_Title :
Nuclear Science, IEEE Transactions on
DOI :
10.1109/TNS.2002.1039702
