Simulation of the multi-purpose gamma irradiator dose distribution based on the GEANT4 and GPU system

Abstract

Gamma irradiation systems are used extensively in the industry in order to sterilize medical devices, disinfect hygienic products and increase the shelf life of agricultural products. The method of gamma irradiation is superior to the older methods of heat or chemical treatment because it is by far a simpler operation. In this method, only one parameter, the exposure time is controlled, whereas in the other mentioned methods five or six different parameters need to be controlled. The design of irradiation systems generally includes the size and the location of products, and the arrangement of source rack pencils. In order to optimize the design of the gamma irradiation systems, it is needed to study the product’s dose distribution in a wide range of densities. The Monte Carlo algorithm is an effective way for simulating the irradiation systems which is being used by a variety of codes. Since this method requires a high computation time, it is necessary to speed up the simulation and design the systems by various methods such as using graphics processing units which having a highly parallel design makes them more suitable for algorithms that process a large number of data than central processing units. In this work, a GEANT4-based computational code is developed to adapt on the GPU using the CUDA programming. Since the developed GEANT4-based code utilizes a graphical processor of NVIDIA (in particular a series GTX660 Ti NVIDIA’s GPU), it leads to speed up the process of simulation. Using this computational technique, a IR-136 gamma irradiator is simulated and the results of the simulation are benchmarked against previously published work. In the present work, a new setup of the industrial irradiator system is considered. The results of the simulations using CPU and GPU are compared with the available experimental dosimetry data. The dose calculation in the new setup is significantly faster using GPU in comparison to the GEANT4 code performed by CPU. The system specification used in both the routine GEANT4 code performed by CPU and the GEANT4-based algorithm performed by GPU are the same. The results show that computational speed when using GEANT4-based code with GPU is superior to using GEANT4 code with CPU, and the deviation between the two sets of data is less than 3%. The speed-up factor is averagely about 3300.