In the modeling and simulation of neutron transport in a system, the probabilities of specific interactions such as neutron capture, fission, and scattering determine how neutrons interact with materials. These interaction probabilities (or cross sections) are strongly dependent on the material temperature in the system and, because temperatures are often changing in a reactor environment, many cross section datasets are needed for a realistic simulation. In recent years, methods have been developed in the fast and epithermal energy ranges to reduce data storage and obtain the cross section at the desired temperature ‘on-the-fly’ during radiation transport simulations using Monte Carlo codes. At thermal energies, however, the scattering of neutrons in a system is complicated by the comparable velocities of the neutron and target, resulting in competing upscattering and downscattering events. The neutron wavelength is also similar in size to the target’s interatomic spacing making the scattering process a quantum mechanical problem. Because of the complicated nature of scattering at low energies, the thermal data files in ACE format used in continuous-energy Monte Carlo codes are quite large — on the order of 20 – 100 megabytes for a single temperature and nuclide. This can be prohibitive for realistic reactor physics simulations. In addition, accuracy is lost because of the need to interpolate between coarse-temperature thermal scattering tables.
To reduce this storage burden and to more accurately represent thermal neutron scattering at all temperatures, a fitting approach in temperature is investigated that allows for the efficient evaluation of the thermal neutron scattering physics at an arbitrary temperature within a predefined range. In addition to the reduction in storage, the need to pre-generate thermal scattering data tables at fine temperatures has been eliminated. This is advantageous for multi-physics simulations which may involve temperatures not known in advance. The physics for thermal neutron scattering in graphite and hydrogen bound in water are evaluated with this approach. In both cases, the functional fits are able to accurately reproduce the scattering probabilities at any temperature with only a few megabytes of total storage.