HIGHER-ORDER GENERALIZED PERTURBATION-THEORY FOR BOILING WATER-REACTOR IN-CORE FUEL-MANAGEMENT OPTIMIZATION

Boiling water reactor (BWR) loading pattern assessment requires solvin g the two-group, nodal form of the neutron diffusion equation and drif t-flux form of the fluid equations simultaneously because these equati on sets are strongly coupled via nonlinear feedback. To reduce the com putational burden associated with the calculation of the core attribut es (that is, core eigenvalue and thermal margins) of a perturbed BWR l oading pattern, the analytical and numerical aspects of a higher order generalized perturbation theory (GPT) method, which correctly address es the strong nonlinear feedbacks of two-phase flow have been establis hed. Inclusion of Jacobian information in the definition of the genera lized flux adjoints provides for a rapidly convergent iterative method for solution of the power distribution and eigenvalue of a loading pa ttern perturbed from a reference state. Results show that the computat ional speedup of GPT compared with conventional forward solution metho ds demanding consistent accuracy is highly dependent on the number of spatial nodes utilized by the core simulator, varying from superior to inferior performance as the number of nodes increases.