Fuel burnup analysis requires a high computational cost for full core calculations, due to the amount of the information processed for the total reaction rates in many burnup regions. Indeed, they reach the order of millions or more by a subdivision into radial and axial regions in a pin-by-pin description. In addition, if multi-physics approaches are adopted to consider the effects of temperature and density fields on fuel consumption, the computational load grows further. In this way, the need to find a compromise between computational cost and solution accuracy is a crucial issue in burnup analysis. To overcome this problem, the present work aims to develop a methodological approach to implement a Reduced Order Model (ROM), based on Proper Orthogonal Decomposition (POD), in fuel burnup analysis. We verify the approach on 4 years of burnup of the TMI-1 unit cell benchmark, by reconstructing fuel materials and burnup matrices over time with different levels of approximation. The results show that the modeling approach is able to reproduce reactivity and nuclide densities over time, where the accuracy increases with the number of basis functions employed.
We present a new model, developed with the Serpent Monte Carlo code, for neutronics simulation of the TRIGA Mark II reactor of Pavia (Italy). The complete 3D geometry of the reactor core is implemented with high accuracy and detail, exploiting all the available information about geometry and materials. The Serpent model of the reactor is validated in the fresh fuel configuration, through a benchmark analysis of the first criticality experiments and control rods calibrations. The accuracy of simulations in reproducing the reactivity difference between the low power (10 W) and full power (250 kW) reactor condition is also tested. Finally, a direct comparison between Serpent and MCNP simulations of the same reactor configurations is presented.
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