Model‐based analysis of chemical‐looping combustion experiments. Part II: Optimal design of CH4‐NiO reduction experiments

There is significant controversy in the reduction kinetics of chemical‐looping combustion (CLC) between NiO and CH₄. We propose an application of a model‐based framework to improve the quality of CLC experiments with respect to model discrimination and parameter estimation. First, optimal experiments are designed and executed to reject inadequate models and to determine a true model structure for the reaction kinetics of the CH₄‐NiO system. Then, kinetics with statistical significance is estimated from experiments aimed at reducing parameter uncertainty. To maximize the observability of the NiO reduction reactions, fixed bed experiments should exhibit a peak separation of the concentration profiles, an initial high methane slip, and low overall CO₂ selectivity. Several case studies are presented to check the adequacy of the recommended model and evaluate its predictive ability and extrapolation capabilities. The model resulting from this work is validated and suitable for application in process design and optimization. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2432–2446, 2016     

Uncertainty quantification of property models: Methodology and its application to CO2‐loaded aqueous MEA solutions

Uncertainties in property models can significantly affect the results obtained from process simulations. If these uncertainties are not quantified, optimal plant designs based on such models can be misleading. With this incentive, a systematic, generalized uncertainty quantification (UQ) methodology for property models is developed. Starting with prior beliefs about parametric uncertainties, a Bayesian method is used to derive informed posteriors using the experimental data. To reduce the computational expense, surrogate response surface models are developed. For downselecting the parameter space, a sensitivity matrix‐based approach is developed. The methodology is then deployed to the property models for an MEA‐CO₂‐H₂O system. The UQ analysis is found to provide interesting information about uncertainties in the parameter space. The sensitivity matrix approach is also found to be a valuable tool for reducing computational expense. Finally, the effect of the estimated parametric uncertainty on CO₂ absorption and monoethanolamine (MEA) regeneration is analyzed. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1822–1839, 2015     

Bayesian estimation of parametric uncertainties,quantification and reduction using optimal design of experiments for CO2 adsorption on amine sorbents

Uncertainty quantification plays a significant role in establishing reliability of mathematical models, while applying to process optimization or technology feasibility studies. Uncertainties, in general, could occur either in mathematical model or in model parameters. In this work, process of CO₂ adsorption on amine sorbents, which are loaded in hollow fibers is studied to quantify the impact of uncertainties in the adsorption isotherm parameters on the model prediction. The process design variable that is most closely related to the process economics is the CO₂ sorption capacity, whose uncertainty is investigated. We apply Bayesian analysis and determine a utility function surface corresponding to the value of information gained by the respective experimental design point. It is demonstrated that performing an experiment at a condition with a higher utility has a higher reduction of design variable prediction uncertainty compared to choosing a design point at a lower utility.     

Development of formation and growth models of CO2 hydrate film

This study aims to develop models to estimate the CO₂ hydrate film formation and growth for different temperature and flow velocity conditions. First, the CO₂ hydrate film thickness at the initial stage of its formation is experimentally measured under different temperature and flow velocity conditions using laser interferometry. Based on the results, the CO₂ hydrate film thickness was found to decrease with increasing temperature and flow velocity. Next, the CO₂ hydrate film formation model and growth model are developed, and the models are verified using the present experimental data. Finally, the long term growth of CO₂ hydrate film thickness is estimated by the proposed growth model of CO₂ hydrate film thickness. © 2016 American Institute of Chemical Engineers AIChE J, 62: 4078–4089, 2016     

Distributional uncertainty analysis and robust optimization in spatially heterogeneous multiscale process systems

Multiscale models have been developed to simulate the behavior of spatially‐heterogeneous porous catalytic flow reactors, i.e., multiscale reactors whose concentrations are spatially‐dependent. While such a model provides an adequate representation of the catalytic reactor, model‐plant mismatch can significantly affect the reactor's performance in control and optimization applications. In this work, power series expansion (PSE) is applied to efficiently propagate parametric uncertainty throughout the spatial domain of a heterogeneous multiscale catalytic reactor model. The PSE‐based uncertainty analysis is used to evaluate and compare the effects of uncertainty in kinetic parameters on the chemical species concentrations throughout the length of the reactor. These analyses reveal that uncertainty in the kinetic parameters and in the catalyst pore radius have a substantial effect on the reactor performance. The application of the uncertainty quantification methodology is illustrated through a robust optimization formulation that aims to maximize productivity in the presence of uncertainty in the parameters. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2374–2390, 2016     

Macro‐economic multi‐objective input–output model for minimizing CO2 emissions: Application to the U.S. economy

Designing effective environmental policies for mitigating global warming is a very challenging task that requires detailed knowledge of the international channels through which goods are traded. This work presents a decision‐support tool that minimizes the environmental impact at a global macroeconomic scale by performing changes in the economic sectors of an economy. Our tool combines multi‐objective optimization, environmentally extended input–output tables and life cycle assessment within a unified framework. Our results on the U.S. economy to minimize CO₂ emissions identify sectors that should be regulated first to reach a given environmental target while maximizing the demand satisfaction. The impact of shale gas on our results is also studied. Our findings show that the application of process systems engineering tools at a macroeconomic level can provide valuable insight for public policy makers into problems of general interest. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3639–3656, 2016     

Numerical investigation on CO2 absorbed in aqueous N‐methyldiethanolamine + piperazine

A multiphase and multicomponent mass transfer model of CO₂ absorbed in aqueous N‐methyldiethanolamine and piperazine (PZ) was built in the study. In the model, a simple method of mass transfer between phases was proposed. Besides, the hydrodynamics, thermodynamics, and complex reversible chemical reaction were considered simultaneously. The model was validated by comparing with the previous experimental data which showed that simulated results can represent the experimental data with reasonable accuracy. Based on the model, the effects of gas velocity, liquid load and CO₂ loading on the absorption rate, and enhancement factor were analyzed. Model results showed that the enhancement factor increased with a rising gas velocity while decreased with a rising liquid load or CO₂ loading. The change of enhancement factor with CO₂ loading was similar to that of equilibrium concentration of PZ which indicated that PZ was significant to the absorption process. Furthermore, the distributions of specie concentrations were discussed in detail. © 2016 American Institute of Chemical Engineers AIChE J, 63: 2386–2393, 2017     

CO2 sorption performance by aminosilane functionalized spheres prepared via co‐condensation and post‐synthesis methods

Amine functionalized silica microspheres were synthesised via a modified Stöber reaction for carbon dioxide (CO₂) adsorption. A number of adsorbents were synthesized by co‐condensation and post synthesis immobilization of amines on porous silica spheres. CO₂ adsorption studies were carried out on a fixed bed gas adsorption rig with online mass spectrometry. Amine co‐condensed silica spheres were found to adsorb up to 66 mg CO₂ g^?1 solid in a 0.15 atm CO₂ stream at 35°C. Simple post‐synthesis addition of aminopropyltriethoxysilane to amine co‐condensed silica was found to significantly increase the uptake of CO₂ to 211 mg CO₂ g^?1 under similar conditions, with CO₂ desorption commencing at temperatures as low as 60°C. The optimum temperature for adsorption was found to be 35°C. This work presents a CO₂ adsorbent prepared via a simple synthesis method, with a high CO₂ adsorption capacity and favorable CO₂ adsorption/desorption performance under simulated flue gas conditions. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2825–2832, 2016     

Hybrid neural network for prediction of CO<Subscript>2</Subscript> solubility in monoethanolamine and diethanolamine solutions

The solubility of CO₂ in single monoethanolamine (MEA) and diethanolamine (DEA) solutions was predicted by a model developed based on the Kent-Eisenberg model in combination with a neural network. The combination forms a hybrid neural network (HNN) model. Activation functions used in this work were purelin, logsig and tansig. After training, testing and validation utilizing different numbers of hidden nodes, it was found that a neural network with a 3-15-1 configuration provided the best model to predict the deviation value of the loading input. The accuracy of data predicted by the HNN model was determined over a wide range of temperatures (0 to 120 °C), equilibrium CO₂ partial pressures (0.01 to 6,895 kPa) and solution concentrations (0.5 to 5.0M). The HNN model could be used to accurately predict CO₂ solubility in alkanolamine solutions since the predicted CO₂ loading values from the model were in good agreement with experimental data.     

Parameter estimation in multiple contact CO2 miscibility simulation with uncertain experimental core flooding data

CO₂ flooding, which is an efficient method of enhanced oil recovery, is a very complicated process involving phase behavior. To understand the performance of CO₂ flooding and provide accurate data for designing reservoir development, a comprehensive investigation of the phase behavior of CO₂ miscible flooding and an accurate compositional reservoir simulation needs to be conducted. In PVT modeling, an effective and more physically reasonable equation of state model was achieved and the feasibility of CO₂ miscible flooding was determined by multiple contact minimum miscibility pressure (MCMMP) calculation. Furthermore, compositional reservoir simulation studies for predicting CO₂ miscible performance were designed and constructed with core flooding data. By matching with laboratory core flooding data, we can estimate parameters with uncertainty. The objective of this study was to find a work flow for parameter estimation in CO₂ miscible flooding process that can be used to design and optimize field CO₂ miscible floods.     

Dew‐point measurements for water in compressed carbon dioxide

When transporting CO₂ for sequestration, it is important to know the water dew point in order to avoid condensation that can lead to corrosion. A flow apparatus to measure the water content at saturation in a compressed gas has been constructed. A saturator humidifies the flowing gas by equilibrating it with liquid water. Then, a gravimetric hygrometer measures the water mole fraction of the humid gas. Dew‐point data for H₂O in CO₂ on six isotherms between 10 and 80 °C at pressures from 0.5 to 5 MPa are reported. The uncertainties in water content at the dew point (expanded uncertainty with coverage factor k = 2) are on average 0.3%, significantly smaller than in any previous work. The data have been analyzed to extract the interaction second virial coefficient; the values are consistent with the theoretical estimates of Wheatley and Harvey but have a much smaller uncertainty. Published 2015 American Institute of Chemical Engineers AIChE J, 2015 © 2015 American Institute of Chemical Engineers AIChE J, 61: 2913–2925, 2015     

Absorption of carbon dioxide into aqueous blends of 2-amino-2-methyl-1-propanol and monoethanolamine

This work presents an investigation of CO₂ absorption into aqueous blends of 2-amino-2-methyl-1-propanol (AMP) and monoethanolamine (MEA). The acid gas mass transfer has been modeled using equilibrium-mass transfer-kinetics-based combined model to describe CO₂ absorption into the amine blends according to Higbie's penetration theory. The effect of contact time and relative amine concentration on the rate of absorption and enhancement factor were studied by absorption experiment in a wetted wall column at atmospheric pressure. The model was used to estimate the rate coefficient of the reaction between CO₂ and monoethanolamine at 313 K from experimentally measured absorption rates. A rigorous parametric sensitivity test has been done to identify the key systems’ parameters and quantify their effects on the mass transfer using the mathematical model developed in this work. The model predictions have been found to be in good agreement with the experimental rates of absorption of CO₂ into (AMP+MEA+H₂O).     

UNIFAC model for ionic liquid‐CO2 systems

The new group binary interaction parameters of UNIFAC model (a_nm and a_mn) between CO₂ and 22 ionic liquid (IL) groups were obtained by means of correlating the solubility data of CO₂ in pure ILs at different temperatures (>273.2 K). We measured the CO₂ solubility at low temperatures down to 243.2 K in pure ILs, i.e., [OMIM]⁺[BF₄]^? and [OMIM]⁺[Tf₂N]^?, and their equimolar amount of mixture, in order to fill the blank of solubility data at low temperatures and also to justify the applicability of UNIFAC model over a wider temperature range. It was verified that UNIFAC model can be used for predicting the CO₂ solubility in pure ILs and in the binary mixture of ILs both at high (>273.2 K) and low temperatures (<273.2 K) effectively, as well as identifying the new structure–property relation. This is the first work to extend the UNIFAC model to IL‐CO₂ systems. © 2013 American Institute of Chemical Engineers AIChE J 60: 716–729, 2014     

CFD investigation of a centrifugal compressor derived from pump technology for supercritical carbon dioxide as a working fluid

Due to the pressing needs to develop and improve compressors to be used in supercritical carbon dioxide Brayton (S-CO₂) cycle, a 3D numerical study has been carried out for the full S-CO₂ compressor geometry including diffuser and volute. The predictions were compared with measurements obtained from the recently constructed S-CO₂ compressor test facility called SCO₂PE (Supercritical CO₂ Pressurizing Experiment), based on existing liquid water technology. The objective of the experimental and numerical work is to obtain fundamental data for the design optimization of compressor and to measure the overall performance near the critical point and in the supercritical state.To simulate nonlinear behavior near the critical point of CO₂, the fluid properties were implemented, via property table, in the computational analysis code. Before embarking in the CFD approach evaluation, a number of parametric runs were conducted to examine the order of errors induced by the property table resolution and to achieve grid convergence.The steady-state numerical predictions using the k–ω SST model were found to return satisfactory results for liquid water and in the case of S-CO₂ operating condition, quite far from the critical point. However, as the compressor operating condition approaches more toward the critical point; deviation from the reference data start to become more apparent. In the more challenging case, the disagreement with experimental data might be partially due to the modeling limitations but is also attributed to the subcritical region observed in the contour plot of the static pressure.     

Hydrophobic protic ionic liquids tethered with tertiary amine group for highly efficient and selective absorption of H2S from CO2

Developing absorbents with both high absorption capacity of H₂S and large selectivity of H₂S/CO₂ is very important for natural gas sweetening process. To this end, a class of novel hydrophobic protic ionic liquids (ILs) containing free tertiary amine group as functional site for the absorption of H₂S were designed in this work. They were facilely synthesized through a simple neutralization‐metathesis methodology by utilizing diamine compounds and bis(trifluoromethylsulfonyl)imide as the building blocks for cation and anion, respectively. Impressively, the solubility of H₂S can reach 0.546 mol mol^?1 (1 bar) and 0.225 mol mol^?1 (0.1 bar), and the selectivity of H₂S/CO₂ can reach 37.2 (H₂S solubility at 1 bar vs. CO₂ solubility at 1 bar) and 15.4 (H₂S solubility at 0.1 bar vs. CO₂ solubility at 1 bar) in the hydrophobic protic ILs at 298.2 K. Comparing the hydrophobic protic ILs with other absorbents justifies their superior performance in the selective absorption of H₂S from CO₂. © 2016 American Institute of Chemical Engineers AIChE J, 62: 4480–4490, 2016     

CO2 removal by single and mixed amines in a hollow‐fiber membrane module—investigation of contactor performance

This work investigates CO₂ removal by single and blended amines in a hollow‐fiber membrane contactor (HFMC) under gas‐filled and partially liquid‐filled membrane pores conditions via a two‐scale, nonisothermal, steady‐state model accounting for CO₂ diffusion in gas‐filled pores, CO₂ and amines diffusion/reaction within liquid‐filled pores and CO₂ and amines diffusion/reaction in liquid boundary layer. Model predictions were compared with CO₂ absorption data under various experimental conditions. The model was used to analyze the effects of liquid and gas velocity, CO₂ partial pressure, single (primary, secondary, tertiary, and sterically hindered alkanolamines) and mixed amines solution type, membrane wetting, and cocurrent/countercurrent flow orientation on the HFMC performance. An insignificant difference between the absorption in cocurrent and countercurrent flow was observed in this study. The membrane wetting decreases significantly the performance of hollow‐fiber membrane module. The nonisothermal simulations reveal that the hollow‐fiber membrane module operation can be considered as nearly isothermal. © 2014 American Institute of Chemical Engineers AIChE J, 61: 955–971, 2015     

A controllability analysis of a pilot‐scale CO2 capture plant using ionic liquids

Nowadays there is a world concern on the impact and effect of large CO₂ atmospheric concentrations on human health. Fossil‐fuel combustion processes in power plants are among the major contributors to this issue. Hence, it becomes important to develop new clean and sustainable processes aimed to reduce the amount of CO₂ released to atmosphere by combustion processes in power plants. One of the best feasible manners to achieve this purposes lies in the use of a closed‐loop control system able to keep the amount of green‐house gases under specification even in the presence of unexpected scenarios. Of course, CO₂ capture has been extensively researched in the past. However, in this regard the industrial practice has consisted in using Amines leading to sustainability and safety issues. Hence, it makes sense to seek for new and potentially environmental friendly process design to address CO₂ reduction from power plants but applying a new type of sustainable stripping solvents. In this work we address the sustainable CO₂ reduction issue from a process control point of view applying a previous design proposed by our research team based on the deployment of Ionic Liquids (IL) as potential green solvents and developing an efficient and decentralized multiloop control system. We demonstrate that the closed‐loop system is able to maintain the CO₂ concentration levels under specification by testing in presence of several demanding scenarios. Overall, from an economic, sustainable and control point of view it looks feasible to replace the traditional amines‐based CO₂ capture process by other alternatives based on the application of IL as potential green solvents. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3298–3309, 2016     

Dealing with Uncertainty in Diffusion Tensor MR Data

This paper explains how radio frequency (RF) background noise produces uncertainty in measured diffusion tensor MRI (DT-MRI) data, how this noise can be modeled, and how its effects can be mitigated. DT-MRI data are derived from a series of magnitude diffusion-weighted images (DWI) in which RF noise is rectified. A new Gaussian distribution is proposed that describes the variability of the estimated diffusion tensor, D, in an ideal experiment in which RF noise is the only artifact present. We show how to improve the design of DT-MRI experiments by requiring that the statistical distribution of D be independent of the laboratory coordinate system. Non-parametric empirical methods of analyzing uncertainty in DT-MRI experiments are also described. Monte Carlo simulations are useful in designing and interpreting DT-MRI experiments. Bootstrap methods help us measure the true variability of D (and quantities derived from it), and assess the quality of DT-MRI data. Matrix Perturbation techniques predict how the uncertainty in D propagates to its eigenvalues and eigenvectors. A method for obtaining a continuous diffusion tensor field from the measured discrete noisy DT-MRI data also reduces the uncertainty of D and quantities derived from it. Finally, we describe schemes that use wavelets to remove noise from DWI and DT-MRI data while preserving boundaries between different tissue regions. Collectively, these parametric and nonparametric methods provide a unified statistical framework to improve the design of DT-MRI experiments and their subsequent analysis.     

Molecular Simulation Study for CO2 Clathrate Hydrate

The present work has concentrated on the structure of CO₂ hydrate in the NPT ensemble using SPC (simple point charge) intermolecular potential model of water by the Monte Carlo (MC) molecular simulation. A mixture of water and CO₂ placed arbitrarily in a cubic cell has been used as a model system to simulate the CO₂ clathrate hydrate at temperatures ranging from 150–280 K and pressure up to 10 MPa. The result shows that the obtained MC simulation agrees well with the results obtained by molecular dynamic (MD) simulation. The present work is also directed to the study of structure with TIP4P potential model of water.     

Modification of polystyrene properties by CO2: Experimental study and correlation

The sorption of CO₂ in polymers entails their swelling and plasticization whose study is crucial for the design of processes and further applications. The operating conditions during foaming, purification, or impregnation of polymers in CO₂ are mainly determined by the mentioned binary system. In this work, the modification of polystyrene's physical properties (glass transition temperature and viscosity) has been experimentally studied. Since plasticization phenomena are very valuable for the processing of polymers, the amount of CO₂ absorbed into the polymer is related with the changes in the described properties. Furthermore, interfacial tension is also correlated with the sorption of CO₂ from literature data. The proposed correlation fits pretty well the properties shifts in the studied working conditions. Finally, the influence of pressure and temperature on the diffusivity of the CO₂ in the polystyrene is calculated through the measurement of viscosity along time. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41696.