Meso-Scale Fuel Performance Modeling using the MARMOT Code

Abstract

The in-pile behavior of light-water-reactor (LWR) fuels is governed by the physics from various time and spatial scales. Accordingly, multi-scale modeling and simulation are needed to accurately predict the fuel performance at the engineering scale. To improve the traditional fuel performance modeling, the Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program targets at developing multi-scale, multiphysics modeling tools for in-pile fuel behavior prediction under various operating or accident scenarios. In traditional fuel performance modeling, the history of fuel is represented by a single parameter, fuel burn-up. Burn-up measures the energy that has been extracted from fuels. However, it is not an adequate measure of fuel history as it ignores the flux effect, which is critical for the irradiation-induced microstructural evolution in fuels. Moreover, the traditional fuel performance models are usually fitted to experimental data. Their capabilities of being extrapolated to new operating conditions and being extended to new types of fuels are strongly limited by the empirical or semi-empirical nature. To improve the burn-up based models, a microstructure based fuel approach, the MOOSE-BISON-MARMOT (MBM) tool-kit, is being developed under the fuel product line (FPL) of the NEAMS program for predictive fuel performance modeling. In the MBM approach, the evolution of fuel microstructure and changes in fuel properties are described by the MARMOT code. The transient fuel properties obtained from MARMOT are then fed into the BISON code for engineering scale fuel performance modeling. Both BISON and MARMOT are developed within the MOOSE framework, which was developed at Idaho National Laboratory. In this summary, the development and the capabilities of the MARMOT code will be introduced. In the past few years, several materials models have been developed including: (1) a grain growth model that describes the grain size evolution as a function of time, temperature and fuel porosity, considering the effects of impurity and porosity dragging and anisotropic grain boundary energy, (2) a fission gas release model that describes the fission gas diffusion in grain interior, fission gas bubble formation in grain interior and at grain boundaries, and fission gas release to the fuel-cladding gap, (3) a fracture model that describes the fracture initiation and propagation in grain interior and along grain boundaries, and (4) a thermal conductivity model that describes the change in thermal conductivity due to grain growth, gas bubble formation, fracture and radiation damage. Several other models are also being developed in MARMOT for hydride formation in Zr-based cladding, radiation damage and grain size subdivision. In most cases, these materials models are coupled with each other. For instance, to accurate predict the transient thermal conductivity, information on grain size, fission gas density, porosity and fracture is required. Further development is on going to improve all these models. These models are developed primarily for UO{sub 2} fuels used in LWRs. They can be extended to other fuels with possibly new development. All models in MARMOT will be rigorously verified and validated before being applied for fuel performance modeling. A version of MARMOT was recently released in September 2015 with an assessment report. (authors)