Advanced CANDU Reactors Fuel Analysis Through Optimal Fuel Management at Approach to Refuelling Equilibrium

Abstract

The analysis of alternate CANDU fuels along with natural uranium-based fuel was carried out from the view point of optimal in-core fuel management at approach to refuelling equilibrium. The alternate fuels considered in the present work include thorium- containing oxide mixtures (MOX), plutonium-based MOX, and Pressurised Water Reactor (PWR) spent fuel recycled in CANDU reactors (Direct Use of spent PWR fuel in CANDU (DUPIC)); these are compared with the usual natural UO₂ fuel. The focus of the study is on the "Approach to Refuelling Equilibrium" period which immediately follows the initial commissioning of the reactor. The in-core fuel management problem for this period is treated as an optimization problem in which the objective function is the refuelling frequency to be minimized by adjusting the following decision variables: the channel to be refuelled next, the time of the refuelling and the number of fresh fuel bundles to be inserted in the channel. Several constraints are also included in the optimisation problem which is solved using Perturbation Theory.

Both the present 37-rod CANDU fuel bundle and the proposed CANFLEX bundle designs are part of this study. The results include the time to reach refuelling equilibrium from initial start-up of the reactor, the average discharge burnup, the average refuelling frequency and the average channel and bundle powers relative to natural UO₂. The model was initially tested and the average discharge burnup for natural UO₂ came within 2% of the industry accepted 199 MWh/kgHE. For this type of fuel, the optimization exercise predicted the savings of 43 bundles per full power year. In addition to producing average discharge burnups and other parameters for the advanced fuels investigated, the optimisation model also evidenced some problem areas like high power densities for fuels such as the DUPIC. Perturbation Theory has proven itself to be an accurate and valuable optimization tool in predicting the time between successive channel refuelling operations.