Nuclear Technology / Volume 168 / Number 2 / November 2009 / Pages 391-398
Shielding / Special Issue on the 11th International Conference on Radiation Shielding and the 15th Topical Meeting of the Radiation Protection and Shielding Division (Part 2) / Radiation Protection / dx.doi.org/10.13182/NT09-A9215
The X-ray container/vehicle inspection system is a large and complex radiation application facility. To evaluate and optimize the shielding design for the system, a Monte Carlo method including two-step simulation, biasing sampling, and a scattering flag technique has been used to perform the shielding analysis - instead of the traditional empirical formula calculation.
When the Monte Carlo method is applied to a complicated large system, some special techniques shall be used to obtain high accuracy and high efficiency in calculation. A special Monte Carlo method based on Geant4, including two-step simulation, biasing sampling, and scattering flag techniques, has been developed in this paper. For the two-step simulation, the first step is to simulate the electron transport inside the tungsten target of a linac and generate X-ray photons; the second step is to simulate the X-ray photon transport in the inspection system. For the biasing sampling, only the photons inside the X-ray beam are simulated and tracked. This allows more photons to reach the inspection system boundary. For the scattering flag, the trace of every photon reaching the inspection system boundary is recorded and stored, thus providing the possibility to tag the main dose contributors to the system boundary and allowing optimization of the shielding design.
The simulation results on the inspection system boundary agree well with the measured results, and the key radiation contributors to the radiation dose on the system boundary are found with the scattering flag technique.
A special Monte Carlo method combined with two-step simulation, biasing sampling and scattering flag techniques, has been developed and successfully used in the shielding design and optimization in an X-ray container/vehicle inspection system.