Expanding and optimizing fuel management and data analysis capabilities of MCODE-FM in support of MIT research reactor (MITR-II) LEU conversion

[摘要] Studies are underway in support of the MIT research reactor (MITR-II) conversion from high enriched Uranium (HEU) to low enriched Uranium (LEU), as required by recent non-proliferation policy. With the same core configuration and similar assembly type, high-density monolithic U-Mo fuel will replace the current HEU fuel with comparable performance. Part of the required analysis for relicensing includes detailed fuel management and burnup studies with the new LEU fuel, to be carried out with a recently developed fuel management tool called MCODE-FM. This code-package is a Python wrapper enabling automatic fuel shuffling between successive runs of MIT;;s MCODE, which couples MCNP with ORIGEN for full-core neutronics and depletion. In this work, the capabilities of MCODE have been expanded, and the effects of depletion mesh parameters have been explored. Several features have been added to the fuel management tool to encompass the the full range of fuel management options needed for detailed analysis, including assembly flipping, rotation, and temporary storage above the core. In addition, an option to easily manage experiments and custom dummy elements has been added, and a parallel version of MCODE for MCODE-FM that better handles finer discretizations of full-core runs has been developed. These changes have been made in the main wrapper utility as well as the graphical user interface (GUI). In addition to the new MCODE-FM capabilities, a suite of automatic data analysis utilities were developed to consistently parse results. These include utilities to extract or calculate isotope data, fission powers, blade heights, peaking factors, and 3D VTK files for visualization at any time step. The suite has been developed as a series of Python scripts, accessible also through the MCODE-FM GUI. Finally, the effects of the spatial discretization parameters for the depletion mesh have been explored, and mesh choice recommendations have been made for different types of studies. In summary, coarser meshes in the radial and lateral dimensions have been found to yield conservative power peaking results, whereas a finer axial mesh is needed axially. Thus for iterative fuel management studies a fast-running depletion mesh of 8 axial regions, 3 radial regions, and 1 lateral region can be used. However, for safety studies and benchmarking that only need to run once or twice, 16 axial regions, 15 or 18 radial regions (HEU or LEU, respectively), and 4 lateral regions should be used.

[发布机构] Massachusetts Institute of Technology