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Abstract
Coal pyrolysis is highly dependent on the pore diffusion. However, classic diffusion laws, such as Fick’s law and Knudsen’s law, cannot accurately predict multicomponent gas diffusion during coal pyrolysis. To study multicomponent gas diffusion during coal pyrolysis, fractal pore models generated by a random walk algorithm were used to simulate coal particles, and the governing equations of multicomponent gas diffusion were established to model gas diffusion in fractal pore models. Many simulations were used to develop a diffusivity correlation for the fractal pores. The developed diffusivity correlation for fractal pores can be applied to multicomponent gas diffusion during coal pyrolysis. The diffusivity increases with increasing porosity, decreasing fractal dimension, and increasing equivalent pore diameter.
| = | gas molar concentration (mol/m3) | |
| = | molecular effective collision diameter | |
| = | equivalent pore diameter | |
| = | gas diffusion coefficient in a large space (m2/s) | |
| = | pore fractal dimension | |
| = | molecular flux (number of molecules/s) | |
| = | side length of each cubic element | |
| = | molecular weight | |
| = | molecular concentration (number of molecules/m3) | |
| = | total number of molecules without intermolecular collisions after traveling distance x | |
| = | molecular effective collision radius | |
| = | equivalent pore radius | |
| = | universal gas constant ( | |
| = | specific pore surface area (1/m or m2·m−3) | |
| = | temperature (K) | |
| = | mean molecular velocity (m/s) | |
| = | molecular mean collision frequency | |
| = | molecular collision cross-section area (m2) | |
| = | mean free path (m) | |
| = | pore structural modulus | |
| = | porosity |