One of the main successes of the kinetic theory of gases is the explicit calculation of the transport coefficients of rarefied gases. However, the greatest problems arise when calculating the thermal conductivity coefficient, especially for polyatomic gases. Also, when using different potentials, it is necessary to systematically calculate the so-called Ω-integrals, which in itself is a rather difficult task. For this reason, direct numerical molecular modeling of the processes of transfer of rarefied gases, in particular, the calculation of their transfer coefficients, is also relevant. A well-known method for such modeling is the molecular dynamics method. Unfortunately, until now this method is not available for modeling the processes of rarefied gas transfer. Under nor-mal conditions, the simulation cell should contain tens or even hundreds of millions of molecules during calculations. At the same time, the numerical implementation of the molecular dynamics method is accompanied by a systematic appearance of errors, which is the reason for the appearance of dynamic chaos. With this simulation, the true phase trajectories of the system under consideration cannot be obtained. Therefore, naturally, the idea of developing a method for modeling transport processes arises, in which phase trajectories are not calculated based on Newton's laws, but are simulated, and then are used to calculate any observables. In our works, we developed a method of stochastic molecular modeling (STM) of rarefied gas transfer processes, where this idea was implemented. The efficiency of the SMM method was demonstrated by calculating the coefficients of self-diffusion, diffusion, and viscosity of both monoatomic gases and polyatomic gases. At the same time, the possibility of modeling the most complex transfer process – the energy transfer process – has not yet been considered. This work aims to simulate the thermal conductivity coefficient by the SMM method. Both monoatomic (Ar, Kr, Ne, Xe) and polyatomic gases (CH4, O2) were considered.
Simulation of thermal conductivity of rare gases by the stochastic method
