Abstract

A novel method of assessing the reliability of 37-element CANDU [Canada deuterium uranium (reactor)] fuel bundle was explored. The method implements a "best-estimate plus uncertainty" approach where a probabilistic treatment of manufacturing and operating inputs are used to predict fuel performance. The fuel performance was predicted using the Canadian industry standard codes for fuel performance, ELESTRESS and ELOCA, which respectively model fuel behaviors during normal and transient conditions. The outputs of the codes were compared against failure criteria from industry norms to determine the probability of failure. A Monte Carlo Simulation method was applied to analyze this problem. Probability distributions of manufacturing input variables were estimated from real data, which were then randomly sampled. The inputs for fuel burnup and power were simulated using core-following data generated using a 3D diffusion code, the Reactor Fuelling Simulation Program, which were also then randomly sampled. The results of the simulations predict significant improvements in margins to limits for all performance parameters. An average improvement of 500°C in centerline temperature, 10°C in sheath temperature, 12MPa in element internal pressure, and 0.8% in pellet end sheath hoop strain was predicted for the highest powered region of the core, during normal operations, in comparison to the limit-of-envelope benchmark. An 80% reactor overhead break transient simulation was also simulated, and an average improvement of 500°C in centerline temperature, 150°C in sheath temperature, 6.5 MPa in internal pressure, and 2% in sheath hoop strain was predicted

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