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.

Development of an Efficient Tool for Evaluating Dose at Through-Holes

In the design of nuclear power plants, it is demanded to quickly and calculate gamma ray scattering line (streaming) from the penetrating portion provided in the shielding such as electrical cables and ducts. However, when conducting gamma-ray streaming calculations from multiple penetrations, MCNP, a detailed calculation code, requires a long calculation time. This is due to the nature of MCNP, where many particles must reach the evaluation point when calculating in order for the results to be within an acceptable accuracy. To shorten the computation time, an analysis code utilizing a simple calculation method is necessary. Thus, we have developed a new method and a simple calculation tool (SVD-Dorc) for streaming computation. This method combines dose rate at an evaluation point with point kernel integration method and a simple streaming calculation formula for straight cylindrical ducts. Properties of SVD-Dorc are as follows: • Point kernel integration method • Simple streaming calculation formula for straight cylindrical ducts • Manual and automatic meshing of rectangular and cylindrical sources • Differentiation between direct line and non-direct sources • 3D drawing of input data • File output The validity of SVD-Dorc was confirmed by comparison with MCNP calculations and measured values from benchmark tests [2].

Kernel integration by Graphical LASSO

Integration of unstructured and very diverse data is often required for a deeper understanding of complex biological systems. In order to uncover communalities between heterogeneous data, the data is often harmonized by constructing a kernel and numerical integration is performed. In this study we propose a method for data integration in the framework of an undirected graphical model, where the nodes represent individual data sources of varying nature in terms of complexity and underlying distribution, and where the edges represent the partial correlation between two blocks of data. We propose a modified GLASSO for estimation of the graph, with a combination of cross-validation and extended Bayes Information Criterion for sparsity tuning. Furthermore, hierarchical clustering on the weighted consensus kernels from a fixed network is used to partitioning the samples into different classes. Simulations show increasing ability to uncover true edges with increasing sample size and signal to noise. Likewise, identification of non existing edges towards disconnected nodes is feasible. The framework is demonstrated for integration of longitudinal symptom burden data from the 2nd and 3rd year of life with 21 diseases precursors as well as the development of asthma and eczema at the age of 6 years from 403 children from the COPSAC2010 mother-child cohort, suggesting that maternal predisposition as well as being born preterm indirectly lead to higher risk of asthma via increased respiratory symptom burden.