A fast simulation method for radiation maps using interpolation in a virtual environment

Abstract

In nuclear decommissioning, virtual simulation technology is a useful tool to achieve an effective work process by using virtual environments to represent the physical and logical scheme of a real decommissioning project. This technology is cost-saving and time-saving, with the capacity to develop various decommissioning scenarios and reduce the risk of retrofitting. The method utilises a radiation map in a virtual simulation as the basis for the assessment of exposure to a virtual human. In this paper, we propose a fast simulation method using a known radiation source. The method has a unique advantage over point kernel and Monte Carlo methods because it generates the radiation map using interpolation in a virtual environment. The simulation of the radiation map including the calculation and the visualisation were realised using UNITY and MATLAB. The feasibility of the proposed method was tested on a hypothetical case and the results obtained are discussed in this paper.

Validation of the neural network for 3D photon radiation field reconstruction under various source distributions

“…Subsequently, the nonlinear method represented by the neural network is likely to become an effective tool for radiation field reconstruction. Li et al (2018) proposed using a simple radial basis function (RBF) neural network model that, when combined with the inverse distance weighting method used to calculate difference values, can be used to obtain whole space radiation parameters, as verified by a simple calculation. Zhou et al (2021) proposed an adaptive back propagation (BP) neural network with learning rate attenuation, and its accuracy and feasibility were verified.…”