Prediction of Reflection Characteristics for Gas Molecules on Solid Surfaces

Abstract

The investigation of characteristics of reflected gas molecules on solid surfaces is important to analyze the flow fields for high Knudsen number flows such as rarefied gas flows and micro/nano scale flows. However, the scattering behavior of gas molecules depends on many factors based on atomic species, pressure, temperature, and surface states. It is difficult to completely consider these factors for the investigation of the gas-surface interaction. The purpose of the present study is to construct an effective model for predicting the reflection characteristics for gas molecules on solid surfaces with water adsorbed surfaces. The molecular velocity distribution functions of reflected gas molecules were obtained by prediction of fitting parameters of the velocity distribution functions using the Neural Network Console (NNC) tool based on the scattering data of the molecular dynamics simulations. The velocity distribution functions of the reflected gas molecules for the constructed model properly predict those of molecular dynamics simulations.