| Issue |
E3S Web Conf.
Volume 471, 2024
XIV International Conference on Transport Infrastructure: Territory Development and Sustainability (TITDS-XIV-2023)
|
|
|---|---|---|
| Article Number | 03003 | |
| Number of page(s) | 6 | |
| Section | Technosphere and Environmental Safety | |
| DOI | https://doi.org/10.1051/e3sconf/202447103003 | |
| Published online | 04 January 2024 | |
Approximation method for the potential composition of petroleum fractions
1 Sholom-Aleichem Priamursky State University, 70a, Shirokaya str., Birobidzhan, 679015, Russia
2 Tashkent University of Information Technologies named by Muhammad Al-Khwarizmi, 108, Amir Temur ave., Tashkent, 100084, Uzbekistan
3 Khabarovsk State University of Economics and Law, 134 Tikhookeanskaya str., Khabarovsk, 680042, Russia
4 Chuvash State University, Cheboksary, 15, Moskovsky ave., 428015, Russia
* Corresponding author: r-i-bazhenov@yandex.ru
The paper gives a brief review of mathematical models of potential composition of oil fractions. The stages of obtaining approximating dependence of the fractional composition of oil are defined. A multicomponent mixture is represented as a discrete series of narrow hydrocarbon fractions. Each of them is characterized by its average boiling point. The results of approximation obtained for oil of different fields are given. The criterion for choosing dependence is the sum of squared deviations of factored values from experimental (reference) values. The following approximating dependencies of the curve of true boiling points for oil of different deposits are obtained. They are cubic parabola, power function, arctangence, exponentiation function, cubic parabola-arctangence. It is shown that the best results are obtained for combined ‘cubic parabolaarctangent’ model. In case of data deviation on oil fractional composition coming from chemical analytical laboratory coefficients are corrected in TBP approximation. Oil fractional composition awareness is important when choosing the direction of oil refining, in process and simulation modeling, when determining the top performance of processing units.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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