Abstract
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.