Development of a Reduced Order Model for Fuel Burnup Analysis

Christian Castagna,Manuele Aufiero,Stefano Lorenzi,Antonio Cammi,Guglielmo Lomonaco

doi:10.3390/en13040890

Christian Castagna, Manuele Aufiero + Show 3 more

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https://doi.org/10.3390/en13040890

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Abstract

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.

Highlights

In nuclear reactor analysis, the time evolution of the fuel composition and the reactivity during the in-core reactor irradiation is relevant for the fuel management and for determining the amount of long-lived radionuclides in spent nuclear fuel [1,2]
We show the results from A reconstruction
From the Singular Value Decomposition (SVD) applied to Sn (Equation (9)), we obtain the Proper Orthogonal Decomposition (POD) basis functions {ξ 1, ξ 2, ..., ξ N }

Summary

Introduction

The time evolution of the fuel composition and the reactivity during the in-core reactor irradiation is relevant for the fuel management and for determining the amount of long-lived radionuclides in spent nuclear fuel [1,2]. The neutronics characterization of a nuclear system depends on the isotopic composition of the fuel material It follows that, in nuclear reactors, burnup calculations are needed to evaluate the concentrations of the various nuclides over time. Neutronics can be simulated by deterministic codes that solve approximations of the transport equation and implement a multi-stage computational procedure from meso-scales (pin cell, fuel assembly) to macro-scales (reactor core) [8]. These codes are widely used for industrial applications, since they provide results in a fast and reasonable computational times

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