Humbul Suleman

Review and selection criteria of classical thermodynamic models for acid gas absorption in aqueous alkanolamines

Abstract The knowledge of vapour-liquid equilibrium (VLE) and thermodynamic properties plays a pivotal role in the process development of absorption systems for acid gas capture in precombustion and postcombustion streams. A large number of thermodynamic modelling approaches for acid gas absorption in aqueous alkanolamine solutions are published in the literature. However, the reviews of these modelling techniques are limited and scattered. Moreover, poor guidelines exist for the selection of an appropriate modelling approach for the VLE prediction of the aforementioned system. Therefore, the current study presents a concise classification and review of classical thermodynamic models for acid gas absorption in aqueous alkanolamine solutions since their inception. The article systematically details the chronological development and highlights the major capabilities and limitations of classical thermodynamic approaches, namely, semiempirical models, activity coefficient models, and equation of state (and equation of state/excess Gibbs energy) models. A graphical comparison of VLE prediction by each classical approach is presented to form a general guideline in the selection of a suitable approach for process development studies. The review precisely discusses the issues, challenges, and future prospects of each classical thermodynamic approach in the context of application, complexity, and development.

Reconciliation of outliers in CO2-alkanolamine-H2O datasets by robust neural network winsorization

It is normal to find at least a few measured values in CO2-alkanolamine-H2O datasets that deviate greatly from the majority of published data, as the data come from different sources. These values, termed as data outliers, are the major source of conflict in modeling, simulation and process development studies. Therefore, removal of data outliers is mandatory. However, available statistical techniques are known to lose information at the boundaries of the system and exhibit substantial deviation from holistic data trend. Hence, an adaptive approach combining artificial neural networks and robust winsorization is presented for identification and reconciliation of data outliers in CO2-alkanolamine-H2O system. The proposed approach flexibly transforms to the nonlinear data distribution and predicts corrected values for data outliers (winsorized values), thus maintaining the information at extremes of the system. The results have been graphically analyzed and show good conformance in treated data, with retention of winsorized values. The proposed method improves the shortcomings of previous statistical approaches and can be potentially extended to other nonlinear experimental datasets in chemical process systems.

A hybrid equation of state and Kent-Eisenberg model for accurate prediction of carbon dioxide separation by aqueous alkanolamines

ABSTRACT A hybrid predictive model has been developed for accurate prediction of thermodynamics of carbon dioxide separation by aqueous alkanolamines. The model incorporates equation of state/excess Gibbs energy model into Kent–Eisenberg approach to predict carbon dioxide–alkanolamine–water equilibria. The approach imparts theoretical corrections to Kent–Eisenberg approach and significantly extends their range of application for monoethanolamine, diethanolamine, methyldiethanolamine, and 2-amino-2-methyl-1-propanol solutions. The proposed model suitably predicts thermodynamics of carbon dioxide separation, well beyond the regressed range of parameters. The results are in excellent agreement with experimental data for a wide range of process parameters and found superior to existing thermodynamic approaches.

A Fugacity Corrected Thermodynamic Framework for Aqueous Alkanolamine Solutions

A generalized thermodynamic framework for correlating the vapor–liquid equilibria of aqueous primary, secondary and tertiary alkanolamine solutions is presented. The model uses Universal Functional Activity Coefficient (UNIFAC) and translated modified Peng–Robinson equation of state to correlate the activity and fugacity effects of the solution, respectively. New UNIFAC binary interaction parameters are reported for aqueous monoethanolamine, diethanolamine and N-methyldiethanolamine solutions for a wide range of temperature, pressure and concentration. The results are in excellent agreement with experimental data.

Comparative Study of Linear Co-Volume Based Mixing Rules for Equation of State/ Excess Gibbs Energy (EOS/GE) Models for CO2 – MEA and CO2 – MDEA Systems

With the advent of Equation of State/ Excess Gibbs Energy (EOS/GE) models, the linear co-volume based mixing rules have gained vast importance for predicting multi-component VLE for polar mixtures. Owing to their inherent ease of calculation and good prediction abilities, these mixing rules have been applied in extension, to a variety of systems especially for CO2-H2O-alkanolamine systems. However, no comparative study is available to select appropriate mixing rule for prediction of thermodynamic properties. In this study, pressure prediction of various linear co-volume mixing rules has been compared for CO2 – MEA and CO2 – MDEA systems, while effects of activity coefficients and process parameters have been kept constant. The infinite pressure mixing rules have heavily under – predicted and approximate zero reference pressure mixing rules have over – predicted, but latter are valid for low and medium pressure ranges. The linear combination of Vidal and Michelsen (LCVM) mixing rule have good predictions at high pressures.

VLE Determination of Carbon Dioxide Loaded Aqueous Alkanolamine Mixtures Using Modified Kent Eisenberg Model

Abstract A computationally simple thermodynamic framework has been presented to correlate the vapour-liquid equilibria of carbon dioxide absorption in five representative types of alkanolamine mixtures. The proposed model is an extension of modified Kent Eisenberg model for the carbon dioxide loaded aqueous alkanolamine mixtures. The model parameters are regressed on a large experimental data pool of carbon dioxide solubility in aqueous alkanolamine mixtures. The model is applicable to a wide range of temperature (298–393 K), pressure (0.1–6000 kPa) and alkanolamine concentration (0.3–5 M). The correlated results are compared to the experimental values and found to be in good agreement with the average deviations ranging between 6% and 20%. The model results are comparable to other thermodynamic models.

Economic Optimization of CO2 Capture Process Using MEA-MDEA Mixtures

Amine based solvents are extensively being used for post combustion carbon capture through absorption. Each solvent has its associated benefits and drawbacks. In order to overcome their drawbacks, a number of mixed amine streams have been used. However, this amalgamation step is usually overshadowed by process optimization issues and cost limitations. In this study, Monoethanolamine (MEA) – Methyldiethanolamine (MDEA) is used as the mixed amine-based solvent for removal of carbon dioxide. A simulation model of CO2 removal is developed using Aspen HYSIS to optimize the process. Subsequently, an economic analysis is constructed to evaluate the operating expenditure (OPEX) and capital expenditure (CAPEX) based on the simulation model, followed by sensitivity analysis. It is found that 25 wt% MDEA and 15 wt% MEA is the optimal operating condition that achieve the minimal total cost. Sensitivity analysis reveals that utilities cost affects the total cost significantly, followed by CAPEX. However, the effect of raw material costs on total cost is negligible.