Abstract
A model based on simulated annealing approach is used with e-UNIQUAC model as well as two other algorithms to study the absorption of carbon dioxide by monoethanolamine solutions. In this work, we propose to compare the performance (through the knowledge of RMSD values) of two stochastic methods, namely the GA (genetic algorithm) and SA (simulated annealing) methods and a deterministic method that is the simplex method. These methods were applied to the absorption of carbon dioxide by an alkanolamine solution using a chemical equilibrium model and a thermodynamic equilibrium model. The latter is based on the use of the modified-UNIQUAC (UNIQUAC-electrolyte) model instead of e-NRTL model for the liquid phase and a fugacity model for the vapor phase. The chemical equilibrium in this work represents the absorption of CO2 by monoethanolamine solution at different temperatures. Solving the coupled system of material and charge balances gives us the carbon dioxide pressure while taking into account the non-ideality of the system. The three-optimization methods show good agreement with the experimental data with a better performance of the simulated annealing method..
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: The authors state no conflict of interest.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Research funding: None declared.
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Data availability: Not applicable.
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© 2024 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Comparative study of deterministic and stochastic optimization algorithms applied to the absorption of CO2 by alkanolamine solution
- Modeling the kinetics, energy consumption and shrinkage of avocado pear pulp during drying in a microwave assisted dryer
- Study of municipal solid waste treatment using plasma gasification by application of Aspen Plus
- Numerical analysis of segregation of microcrystalline cellulose powders from a flat bottom silo with various orifice positions
- Prediction of syngas production in the gasification process of biomass employing adaptive neuro-fuzzy inference system along with meta-heuristic algorithms
- Industrial high saline water desalination by activated carbon in a packed column- an experimental and CFD study
- Dual-loop PID control strategy for ramp tracking and ramp disturbance handling for unstable CSTRs
- A control perspective on hybrid membrane/distillation propane/propylene separation process
- Prediction of surface heating effect on non-equilibrium homogeneous condensation in supersonic nozzle using CFD method
- Modeling the emitted carbon dioxide and monoxide gases in the gasification process using optimized hybrid machine learning models
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Comparative study of deterministic and stochastic optimization algorithms applied to the absorption of CO2 by alkanolamine solution
- Modeling the kinetics, energy consumption and shrinkage of avocado pear pulp during drying in a microwave assisted dryer
- Study of municipal solid waste treatment using plasma gasification by application of Aspen Plus
- Numerical analysis of segregation of microcrystalline cellulose powders from a flat bottom silo with various orifice positions
- Prediction of syngas production in the gasification process of biomass employing adaptive neuro-fuzzy inference system along with meta-heuristic algorithms
- Industrial high saline water desalination by activated carbon in a packed column- an experimental and CFD study
- Dual-loop PID control strategy for ramp tracking and ramp disturbance handling for unstable CSTRs
- A control perspective on hybrid membrane/distillation propane/propylene separation process
- Prediction of surface heating effect on non-equilibrium homogeneous condensation in supersonic nozzle using CFD method
- Modeling the emitted carbon dioxide and monoxide gases in the gasification process using optimized hybrid machine learning models