Issue |
E3S Web Conf.
Volume 486, 2024
IX International Conference on Advanced Agritechnologies, Environmental Engineering and Sustainable Development (AGRITECH-IX 2023)
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Article Number | 03021 | |
Number of page(s) | 8 | |
Section | Information Technologies, Automation Engineering and Digitization of Agriculture | |
DOI | https://doi.org/10.1051/e3sconf/202448603021 | |
Published online | 07 February 2024 |
Method for determining estimates of random variable models for describing phase equilibrium in rectification processes
1 Tashkent State Technical University, Tashkent, Uzbekistan
2 Navoi State University of Mining and Technologies, Navoi, Uzbekistan
3 Bukhara Engineering Technological Institute, Bukhara, Uzbekistan
* Corresponding author: abrorov1975@mail.ru
The phase equilibrium modeling for multi-component systems is essential in process systems engineering. In particular, phase stability analysis, Gibbs free energy minimization and estimation of parameters in thermodynamic models are challenging global optimization problems involved in phase equilibrium calculations and modeling for both reactive and non-reactive systems. To date, many significant works have been performed in the area of global optimization, and several algorithms and computational contributions of global optimization have been used for solving these problems; global optimization methods used include both deterministic and stochastic algorithms. To the best of our knowledge, there is no review in the literature that focuses on the global optimization methods and their applications to phase equilibrium modeling and calculations. In this paper, we briefly describe the deterministic and stochastic optimization algorithms selected for our rectification process, and then consider their use for phase stability analysis, Gibbs free energy minimization, and parameter estimation in phase equilibrium models. In short, we present an overview of global optimization for modeling and computing the phase behavior of systems with and without chemical reactions, including the prediction of azeotropes and critical points.
© The Authors, published by EDP Sciences, 2024
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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