Parameter estimation in vapor-liquid equilibrium modeling of compounds related to biodiesel production using opposite
1Process Systems Engineering Laboratory, University School of Chemical Technology, Guru Gobind Singh Indraprastha University, Sector 16-C, Dwarka, Delhi, 110078, India.
Environmental Science and Pollution Research International
|October 29, 2024
Summary
This study enhances biodiesel production by improving vapor-liquid equilibrium (VLE) modeling using advanced algorithms. The OPDE algorithm and least-squares approach offer faster convergence and accurate parameter estimation for VLE data.
Area of Science:
- Chemical Engineering
- Thermodynamics
- Sustainable Energy
Background:
- Biodiesel is a key alternative to fossil fuels, requiring efficient separation processes.
- Accurate thermodynamic models are crucial for predicting phase equilibria in biodiesel production.
Purpose of the Study:
- To evaluate differential evolution (DE) and an enhanced OPDE algorithm for modeling vapor-liquid equilibrium (VLE) in biodiesel systems.
- To compare classical least-squares (LS) and error-in-variable (EIV) approaches for parameter estimation.
- To present novel findings from VLE datasets.
Main Methods:
- Application of classical differential evolution (DE) and the OPDE algorithm.
- Parameter estimation for Wilson, NRTL, and UNIFAC thermodynamic models.
- Comparison of LS and EIV data-fitting approaches.
Main Results:
- The OPDE algorithm demonstrated superior performance over the DE algorithm.
- The LS approach showed faster convergence and parameter values consistent with literature.
- The EIV approach, while yielding higher objective function values, exhibited low deviation and significant enhancement in RMSTD (91%-99%).
Conclusions:
- The OPDE algorithm and LS approach provide efficient and accurate methods for VLE modeling in biodiesel production.
- Optimized thermodynamic models are essential for enhancing the efficiency of biodiesel separation processes.
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