Simulation of Heat and Mass Transfer in Adsorption of Gas Mixtures in a Transition Regime View Full Text


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Article Info

DATE

2019-03-04

AUTHORS

F. V. Yusubov, A. S. Bairamova

ABSTRACT

The problems of simulating heat and mass transfer of the process of adsorption in a stationary adsorbent layer are considered. At elevated concentrations of gaseous mixtures, the thermal effect exerts a substantial influence on the progress of the adsorption process and requires it to be taken into account. The adsorption heat, while increasing the internal temperature of the adsorbent and adsorptive layer, exerts a negative effect on the absorption of undesirable gaseous mixture components. Attainment of the rate of equilibrium state in heat and mass transfer processes is very important in determining the efficiency of operation of adsorption apparatuses. In the case of nonisothermal adsorption, it is very important to be able to predict the behavior of the stationary adsorbent layer temperature in time, because it turns out to be most advantageous economically to carry out abstraction of the product from an industrial adsorber prior to the establishment of equilibrium state, i.e., in a transition regime. A mathematical description of heat transfer of industrial adsorbers has been obtained. A mathematical model has been developed allowing one to determine the temperature in a stationary adsorbent layer at each instant of time (using as an example the process of adsorption refining of gaseous mixtures CO2, H2S, NO2 on NaX zeolite). To model heat and mass transfer, the heat conduction equation is used, i.e., a differential equation of parabolic type. Heat and mass transfer was investigated for each moment in a stationary layer, and heat and mass transfer between the gaseous flow and the stationary layer of NaX zeolite has been determined. More... »

PAGES

1-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10891-019-01913-x

DOI

http://dx.doi.org/10.1007/s10891-019-01913-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112519810


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