The field of human space travel is in the midst of a dramatic revolution. Upcoming missions
are looking to push the boundaries of space travel, with plans to travel for longer distances …

In this paper, the artificial neural networks (ANN) based deep learning (DL) techniques were
developed to solve the neutron diffusion problems for the continuous neutron flux …

阐述了基于物理信息指引的神经网络模型(PINN), 构造深度神经网络作为试函数,
将其代入中子学扩散方程形成残差, 并作为机器学习的加权损失函数, 进而通过深度机器学习 …

Gamma spectroscopy is a technique for identifying radioactive sources and evaluating their
activity. Reliable estimation of activity levels remains challenging due to various physical …

Gamma sensitive plastic scintillators are of critical importance in the fields of nuclear
nonproliferation, medical imaging, and high energy physics. However, there is often a trade …

As more complex predictive models are used for gamma-ray spectral analysis, methods are
needed to probe and understand their predictions and behavior. Recent work has begun to …

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization
of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis …

A study is conducted to improve the performance of Convolutional Neural Networks (CNNs)-
based radioisotope identification (RIID). This study introduces a novel method to transform …

This study proposes a novel feature extraction approach for radionuclide identification to
increase the precision of identification of the gamma-ray energy spectrum set. For easier …

Measured spectra in a high count rate environment are difficult to analyze because of the
spectral distortions caused by the pulse pile-up effect. This study proposes a deep learning …