The conceptual design and evaluation of research reactors utilizing a Monte Carlo and diffusion based computational modeling tool

M.Sc.Due to the demand for medical isotopes, new Materials Testing Reactors (MTR's) are being considered and built globally. Different countries all have varying design requirements resulting in a plethora of different designs. South-Africa is also considering a new MTR reactor for dedicated medical radio-isotope production. A neutronic analysis of these various designs is used to ascertain/evaluate the viability of each. Most safety and utilization parameters can be calculated from the neutron flux. The code systems that are used to perform these analysis are either stochastic or deterministic in nature. In performing such an analysis the tracking of the depletion of isotopes is essential, to ensure that the modeled macroscopic cross-sections are as close as possible to that of the actual reactor. Stochastic methods are currently too slow when performing depletion analysis, but are very accurate and flexible. Deterministic based methods, on the other hand are much faster, but are generally not as accurate or flexible due to the approximations made in solving the Boltzmann Transport Equation. The aim of this work is therefore to synergistically use a deterministic (diffusion) code to obtain an equilibrium material distribution for a given design and a stochastic (Monte Carlo) code to evaluate the neutronics of the resulting core model - therefore applying a hybrid approach to conceptual core design. A comparison between the hybrid approach and the diffusion code demonstrates the limitations and strengths of the diffusion-based calculational path for various core designs. In order to facilitate the described process, and implement it in a consistent manner, a computational tool termed COREGEN has been developed. This tool facilitates the creation of neutronics models of conceptual reactor cores for both the Monte Carlo and diffusion codes in order to implement the described hybrid approach. The system uses the Monte-Carlo based MCNP code system developed at Los Alamos National Laboratory as stochastic solver, and the nodal diffusion based OSCAR-4 code system developed at Necsa as the deterministic solver. Given basic input for a core design, COREGEN will generate a detailed OSCAR-4 and MCNP input model. An equilibrium core obtained by running OSCAR-4, is then used in the MCNP model. COREGEN will analyze the most important core parameters with both codes and provide comparisons. In this work, various MTR reactor designs are evaluated to meet the primary requirement of isotope production. A heavy water reflected core with 20 isotope production rigs was found to be the most promising candidate. Based on the comparison of the various parameters between Monte Carlo and diffusion for the various cores, we found that the diffusion based OSCAR-4 system compares well to Monte Carlo in the neutronic analysis of cores with in-core irradiation positions (average error 4.5% in assembly power). However, for the heavy water reflected cores with ex-core rigs, the diffusion method differs significantly from the MonteCarlo solution in the rig positions (average error 17.0% in assembly power) and parameters obtained from OSCAR must be used with caution in these ex-core regions. The solution of the deterministic approach in in-core regions corresponded to the stochastic approach within 7% (in assembly averaged power) for all core designs