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Определение параметров ведения процесса регенерации отработанного моторного масла с помощью мембран на основе экспериментально-статистической модели

Определение параметров ведения процесса регенерации отработанного моторного масла с помощью мембран на основе экспериментально-статистической модели

Abstract

Application of mathematical methods of optimization of the process of filtration as part of recovery of used engine oils is considered in the article. The method of the full factorial experiment which contemplates generation of the mathematical model of the filtering process is applied with account for numerous factors and missing data. The mathematical model provides the information about the influence of various factors to identify the quantitative values of response functions in the pre-set mode of the process to serve as the basis for optimization.Permeability of polymeric membranes, liquid flow velocity and temperature have been chosen as filtration optimization criteria. As a result of the mathematical processing of the experimental data, factors have been calculated and verified in terms of their importance, and the process description has been provided in the form of a regression equation. Dependences obtained by the authors are recommended for use in the calculation of the process of permeability. For example, they may be used to substantiate the periodicity of maintenance of filtration units.

Рассмотрено применение математических методов оптимального планирования эксперимента с целью получить математическую модель мембранного процесса восстановления отработанных моторных масел, применяемых в строительной технике, учитывая его многофакторность и неполные сведения о механизме данного процесса.

Keywords

ПЛАНИРОВАНИЕ ЭКСПЕРИМЕНТА,EXPERIMENT PLANNING,ЭКСПЕРИМЕНТАЛЬНО-СТАТИСТИЧЕСКАЯ МОДЕЛЬ,EXPERIMENTAL AND STATISTICAL MODEL,УРАВНЕНИЕ РЕГРЕССИИ,REGRESSION EQUATION,ПРОНИЦАЕМОСТЬ,PERMEABILITY,ПОЛИМЕРНЫЕ МЕМБРАНЫ,POLYMERIC MEMBRANES,ФИЛЬТРОВАНИЕ,FILTERING

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold