MODELING AND OPTIMIZATION OF TECHNOLOGICAL PROCESSES FOR THE PURIFICATION OF RAW GLYCEROL USING INFORMATION TECHNOLOGY
DOI:
https://doi.org/10.31548/humanhealth.4.2026.37Keywords:
machine learning; regression analysis; thermodynamic balance; rich criteria analysis; energy efficiency; digital twins; encouragement to praise decisionAbstract
The purification of raw glycerol extracted during diesel fuel production is complicated by the abundance of raw materials, the presence of organic and inorganic compounds, and the need to maintain stable viscosity. Product for rational expenditure of resources. Information technologies generate new approaches to complex analysis, forecasting, and optimization of various technological processes.
The method of work is the systematization and equal evaluation of methods of mathematical and computer modeling of processes for the purification of raw glycerol, the evaluation of their capabilities, limitations, and prospects for integrated stagnation. Research methodology supports critical analysis of scientific publications, updating of mathematical models, refinement of statistical analysis methods, experimental design, thermodynamic and simulation modeling, machine learning, and optimization of criteria. I will review the results systematically and provide a comprehensive description of the purification processes. It has been established that regression models enable evaluation of temperature rise, pressure, and reagent waste within the following ranges. Thermodynamic and simulation modeling are used to develop phase, material, and heat balances, and to forecast flow storage and the process's energy characteristics. Machine learning methods are suitable for creating foldable, non-linear deposits but will require representative data, reliable validation, and theft control. Multi-criteria optimization enables improved purity and yield of glycerol, as well as reduced energy and reagent consumption. The completeness of matching physico-chemical models with data analysis for storage of the output syrup has been demonstrated. Particular attention is given to the criteria of model equalization, forecasting accuracy, interpretation of results, computational complexity, and the possibility of transferring models between technological schemes. The importance of using experimental data from development results has been shown, since the insignificance of the output parameters can seriously affect the validity of technological solutions and the reliability of evaluating the effectiveness of purification for various vibrator minds.
The practical significance lies in the formulated methodological basis for selecting software features, implementing technological modes, and creating decision support systems. The considered approaches can combine the presence of glycerol with standardized viscosity indicators for potential valorization in grub technologies, after confirming the type of viscosity.
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