Neutral particle transport problems are fundamental in the modeling of energy transfer by radiation (photons) and by neutrons with many important applications. In this work, the novel ANN-MoC method for solving unidimensional neutral particle transport problems is presented. Following the Method of Discrete Ordinates (DOM) and decoupling with a Source Iteration (SI) scheme, the proposed method applies Artificial Neural Networks (ANNs) together with the Method of Characteristics (MoC) to solve the transport problem. Once the SI scheme converges, the method gives an ANN that estimates the average flux of particles at any points in the computational domain. Details of the proposed method are given and results for two test cases are discussed. The achieve results show the potential of this novel approach for solving neutral particle transport problems.

翻译：中性粒子输运问题是辐射（光子）和中子能量传输建模的基础，具有诸多重要应用。本文提出了一种新颖的ANN-MoC方法，用于求解一维中性粒子输运问题。该方法遵循离散纵标法（DOM）并采用源迭代（SI）方案进行解耦合，结合人工神经网络（ANNs）与特征线法（MoC）求解输运问题。当SI方案收敛后，该方法可生成一个人工神经网络，用于估算计算域内任意点的平均粒子通量。文中详细阐述了所提方法的原理，并讨论了两个测试案例的结果。取得的成果表明，这种新方法在求解中性粒子输运问题方面具有潜力。