An artificial neural multi-layer network has been developed for predicting the mass transfer coefficients in the liquid and gas phases for the gas absorption (CO2) from the air using an absorbent - water. For the development of neural network the unobservable parameters of the packed absorber were calculated. The obtained results can be used to model an extensive class of chemical engineering processes with the possibility of formalizing the calculation procedures.

A priority task for the development of the energy industry is the replacement of the spent estimated lifetime of the generating equipment by new capacities taking into account progressive technologies. Nowadays, combined cycle technology shows itself to good advantage and provides excellent efficiency for any competing gas turbine systems that are likely to be available for large-scale electricity and heat production. In this article the possibility of modernization of the SDPS by building the combined cycle plant is considered.

In connection with the high competition and strict requirements of the open electricity market, optimization of heat energy supply schemes to consumers is an important task for generating companies. The variant of optimization of the SDPS by construction of rapid cooling unit (RCU) 140/12 and reconstruction of strapping RCU 12/6 is considered in this article.

The absorption of heat by rocks is accompanied by an increase in the kinetic energy of molecules and atoms and is recorded by a change in rock temperature. The thermal properties of rocks characterize the ability to transfer and absorb heat and change their size when the temperature rises. The main thermal properties of rocks are thermal conductivity, heat capacity, linear thermal expansion, and thermal volumetric expansion. In this paper, the influence of temperature effects on the thermal properties of reservoirs – the coefficient of temperature conductivity, specific heat capacity, and thermal conductivity is studied using the samples of oil-saturated reservoirs from the good number 19Bp of the Upper Uplift of Sotnikovsky deposit. The dependence of the thermal properties of the core material on temperature was revealed using a number of laboratory experiments. The results of these studies contribute to improving the reliability of data on the relationship of thermal properties with other physical properties of oil-saturated reservoirs and can be used to improve the efficiency of the development of fields of super-viscous oil.

The method of calculation of the molecular weight distribution (MWD) of rubber SDRN synthesized in the cascade of reactors with a continuous mixer in the presence of chain transfer to the polymer (by direct numerical solution system of equations arising from the kinetic scheme of polymerization with special selection of boundary conditions, maximum length of macromolecules and calculation step value). Numerical solution of mathematical model that is systems of differential equations for concentrations of monomer, co-catalyst and macromolecules of polymer together with thermal balance is obtained. The influence of regime parameters on MWD and molecular mass characteristics of the final product obtained using molecular weight distribution are analyzed.

In order to create a complex of control and prediction of optimal reaction conditions with a minimum value of chemical oxygen demand, a neural network model of supercritical water oxidation of industrial effluent water utilization process of hydroperoxide epoxidation of propylene at PJSC “Nizhnekamskneftekhim” was created. A full application Windows Forms, which implemented functions of loading a training sample from a file, setting the necessary training accuracy, entering a vector for obtaining results of neural network operation and graph plotting, was created.