NEW STRATEGY ON THE EVALUATION OF DANCOFF FACTOR IN A PEBBLE BED REACTOR USING MONTE CARLO METHOD

Abstract

The Dancoff factor is used in deterministic codes for the calculation of resonance absorption. In using the Monte Carlo simulation, some techniques, such as repeated structure, are commonly used for geometry modeling of pebbles and kernels. However, these methods, with some assumptions, can cause an error in the calculation of the Dancoff factor. In this study, a Monte Carlo simulation method for the evaluation of the Dancoff factor was developed to solve these problems. Random sampling and rejection techniques are used for geometry modeling of pebbles and kernels. Also, the random selection method of the pebble type is used for modeling of the fuel and moderator pebbles that are randomly mixed in the core. By using this method, the Dancoff factor was calculated, and the results were compared with the results calculated by the INTRAPEB code and the MCNP5 code. The results of the average intrapebble Dancoff factor agree well within 1% difference compared with the result of the other study that was calculated by the INTRAPEB code. The result of the average interpebble Dancoff factor was underestimated by similar to 8%, compared with the result by using the MCNP5 code. Analysis shows that the difference is caused by modeling assumptions in using the MCNP5 code. In addition, the Dancoff factor of the HTR-PRTEUS reactor and its spatial dependency were evaluated. The results show that the method can be used in the calculation of the Dancoff factor with the consideration of the spatial dependency with good accuracy. It is expected that the method can simply calculate the average Dancoff factor calculation without the direct modeling of the complex pebble bed reactor geometries. Also, the Monte Carlo simulations with various fuel-to-moderator ratios can be evaluated. Therefore, it will be a powerful method to evaluate the Dancoff factor with consideration of a real geometrical distribution for the pebble bed reactors.