Nuclear Technology / Volume 168 / Number 1 / October 2009 / Pages 95-100
Dose/Dose Rate / Special Issue on the 11th International Conference on Radiation Shielding and the 15th Topical Meeting of the Radiation Protection and Shielding Division (Part 1) / Radiation Protection / dx.doi.org/10.13182/NT09-A9106
Monte Carlo methods are typically used for simulating radiation fields around gamma-ray spectrometers and pulse-height tallies within those spectrometers. Deterministic codes that discretize the linear Boltzmann transport equation can offer significant advantages in computational efficiency for calculating radiation fields, but stochastic codes remain the most dependable tools for calculating the response within spectrometers. For a deterministic field solution to become useful to radiation detection analysts, it must be coupled to a method for calculating spectrometer response functions. This coupling is done in the RADSAT toolbox.
Previous work has been successful using a Monte Carlo boundary sphere around a handheld detector. It is desirable to extend this coupling to larger detector systems such as the portal monitors now being used to screen vehicles crossing borders. Challenges to providing an accurate Monte Carlo boundary condition from the deterministic field solution include the greater possibility of large radiation gradients along the detector and the detector itself perturbing the field solution, unlike smaller detector systems. The method of coupling the deterministic results to a stochastic code for large detector systems can be described as spatially defined rectangular patches that minimize gradients.
The coupled method was compared to purely stochastic simulation data of identical problems, showing the methods produce consistent detector responses while the purely stochastic run times are substantially longer in some cases, such as highly shielded geometries. For certain cases, this method has the ability to faithfully emulate large sensors in a more reasonable amount of time than other methods.