A Novel and High-Precision Method for Calculating the γ-Ray Build-Up Factor for Multilayer Shields

In the field of radiation protection, the point-kernel code method is a practical tool widely used in the calculation of 3-D radiation field, and the accuracy of the point-kernel integration method strongly depends on the accuracy of the build-up factor. It is well known that calculation of the build-up factor for single-layer shields is composed of single material, but it is very complicated to calculate the build-up factor for multilayer shields (MLBUF). Recently, a novel and high-precision method based on the deep neural network (DNN) for calculating MLBUF has been proposed. In this paper, the novel method is described completely by slab models. Through the study of photon transport in multilayer shields, the parameters that mainly affect the calculation of build-up factor are analyzed. These parameters are trained by DNN as the input vectors, and the build-up factor for multilayer shields is predicted based on the trained DNN. The results predicted by DNN confirm that the method can calculate the build-up factor for multilayer shields quickly and accurately. The method has been preliminarily applicated into a 3-D radiation field calculation software, and it has proved that the method for calculating MLBUF has a broad application prospects in 3-D radiation field calculation.