Prediction Of Mass Transfer Coefficients Research Articles

Effect of operating variables on isopropanol absorbed by triethylene glycol solution and discussions on the mass transfer coefficient predicted by artificial neural network

The mass transfer performance of isopropanol (IPA) absorption by triethylene glycol (TEG) aqueous solution in a spray-bed absorber was investigated, and the mass transfer coefficients predicted by an artificial neural network (ANN) and response surface methodology were compared in this study. The operating variables affecting the mass transfer performance of a spray-bed absorber include the gas and TEG fluxes, concentration of IPA, concentration of TEG aqueous solution, and operating temperature. The experimental results demonstrated that the mass transfer coefficient of a spray-bed absorber increased with increases in gas and liquid fluxes and decreased with increases in concentration of IPA. The Back-Propagation algorithm in the ANN model was selected to predict the mass transfer coefficients of the spray–bed absorption system. Hidden layers with 2, 4 and 6 neurons respectively were set to analyze the effect of the number of neurons on the target value, and then different transfer functions were used to compare the accuracy in predicting mass transfer coefficient. Finally, the influences of the number of hidden layers and different learning rules on the prediction of mass transfer coefficients were examined. The simulated results showed that the average error of the ANN using the TanhAxon transfer function, the Conjugate Gradient learning rule, two hidden layers, and 6 neurons in each hidden layer was within 1%. The results not only verified the successful establishment of the experimental device but also proved the accurate prediction of mass transfer coefficients by the ANN model.

Ozone nanobubble technology as a novel AOPs for pollutants degradation under high salinity conditions

Conventional water treatment systems frequently exhibit diminished efficiency at high salinity - a significant issue especially for real industrial effluents - mostly due to the creation of intricate structures between pollutants and salts. One of the primary obstacles associated with high salinity conditions is the generation of by-products that pose additional hurdles for treatment. In this work, we have investigated the novel advanced oxidation process a so-called ozone nanobubble technology for degradation of the pollutants at high salinity conditions. The mass transfer is often the rate-limiting step in gas-liquid process and the poor rate of mass transfer diminishes the overall efficacy. One of the primary disadvantages associated with ozone is its restricted solubility and instability when dissolved in an aqueous solution. These characteristics impose limitations on its potential applications and need the use of specialized systems to facilitate gas-liquid interaction. In this work, we have also suggested enhancing the ozonation process through the utilization of ozone nanobubbles. The findings of our experiment and subsequent analysis indicate that the presence of nanobubbles enhances the process of ozonation through three key mechanisms: (i) an increased mass transfer coefficient, (ii) a higher rate of reactive oxygen species (ROS) generation attributed to the charged interface, and (iii) the nanobubble interface serving as an active surface for chemical reactions. The predicted mass transfer coefficients were found to range from 3 to 3.5 min−1, a value that is notably greater than that seen for microbubbles. The study showcased the degradation of methylene blue dye through the utilization of ozone nanobubbles, which exhibited a much higher rate of dye degradation compared to ozone microbubbles. The confirmation of the radical degradation mechanism was achieved by the utilization of electron spin resonance (ESR) measurements. The developed process has high potential for application in industrial scale textile wastewater treatment.

Characterization Data for the Establishment of Scale-Up and Process Transfer Strategies between Stainless Steel and Single-Use Bioreactors

The reliable transfer of bioprocesses from single-use bioreactors (SUBs) of different scales to conventional stainless steel stirred-tank bioreactors is of steadily growing interest. In this publication, a scale-up study for SUBs with volumes of 200 L and 2000 L and the transfer to an industrial-scale conventional stainless steel stirred-tank bioreactor with a volume of 15,000 L is presented. The scale-up and transfer are based on a comparison of mixing times and the modeling of volumetric mass transfer coefficients kLa, measured in all three reactors in aqueous PBS/Kolliphor solution. The mass transfer coefficients are compared with the widely used correlation of van’t Riet at constant stirrer tip speeds. It can be shown that a van’t Riet correlation enables a robust and reliable prediction of mass transfer coefficients on each scale for a wide range of stirrer tip speeds and aeration rates. The process transfer from single-use bioreactors to conventional stainless steel stirred-tank bioreactors is proven to be uncritical concerning mass transfer performance. This provides higher flexibility with respect to bioreactor equipment considered for specific processes.

Simulating Tablet Dissolution Using Computational Fluid Dynamics and Experimental Modeling

The study of mass transfer is essential in the food digestion process, especially when gastric acid interacts with food and nutrients dissolve in the gastric system. In this study, a computational fluid dynamics (CFD) model was built based on an in vitro study, which investigated the mass transfer in a tablet dissolution process in a beaker and stirrer system. The predicted mass transfer coefficients from the simulation aligned well with the experimental values. The effect of the type and rotation speed of the stirrers was also investigated. Mass transfer from the tablet was found to be closely related to the tablet Reynolds number of the fluid (ranging from 0 to 938) and the shear stress (0 to 0.167 Pa) acting on the tablet. The relationship between the power number (0.0061 to 0.196) and the Reynolds number for the impeller (719 to 5715) was also derived for different stirrers.

Generic AI models for mass transfer coefficient prediction in amine-based CO2 absorber, Part I: BPNN model

Accurate and reliable prediction of mass transfer coefficient is critical to evaluate the mass transfer performance of amine-based carbon capture process. This work aims to establish a generic mass transfer model applicable to CO2 absorption into amine solutions in absorber columns. A series of back-propagation neural network (BPNN) models were established based on the experimental data of 23 amine-based systems. The BPNN models trained for a specific CO2 absorption process matched well with the experimental data with all the AAREs of below 4%. Meanwhile, models with better applicability were proposed and established by introducing extra parameters related to amine properties or column characteristics to better describe and predict the mass transfer behavior in different amine-based systems. Particularly, the generic mass transfer coefficient model was developed with the consideration of all influencing factors including operating conditions, amine properties, and packing characteristics, to achieve the accurate prediction of mass transfer coefficient of CO2 absorption into amine solutions in packed columns. The developed generic model could serve as a fast and efficient tool for preliminary selection and evaluation of potential amines by presenting the mass transfer performance in CO2 absorber.

Generic AI models for mass transfer coefficient prediction in amine‐based CO2 absorber, Part II: RBFNN and RF model

AbstractIn this work, the radial basis function neural network (RBFNN) and random forest (RF) algorithms were employed to develop generic AI models predicting mass transfer coefficient in amine‐based CO2 absorber. The models with operating parameters as input gave quite different prediction performance in different CO2 absorption systems. To secure better applicability, extra parameters related to amine type and packing characteristics were introduced to reasonably describe mass transfer behaviors, respectively. Moreover, the generic models were proposed by considering all influencing factors of mass transfer in CO2 absorber column. Furthermore, the performance of BPNN, RBFNN, and RF models was completely compared and fully discussed in terms of AARE. All three generic models could predict mass transfer coefficient of CO2 absorber very well. It was found that the BPNN models provide the best predication with AAREs of below 5%. The developed generic model could serve as a fast and efficient tool for preliminary selection and evaluation of potential amines for CO2 absorption. The framework of generic ML model development was also clearly presented, which could provide theoretical basis and practical guidance for the implementation and application of ML models in the carbon capture field.

Unified Approach for Prediction of the Volumetric Mass Transfer Coefficients in a Homogeneous and Heterogeneous Bubble Column Based on the Non-Corrected Penetration Theory: Case Studies

A critical review on the improvement of penetration theory is presented in this work. The volumetric liquid-phase mass transfer coefficients kLa in seven different liquids (1-butanol, 2-propanol, anilin, decalin, nitrobenzene, tetralin, and ethylene glycol) aerated with air in a small bubble column (BC) (inner diameter: 0.095 m) were measured at ambient conditions and further analyzed. It was found that the kLa values can be predicted satisfactorily on the basis of the classical Higbie’s penetration model. The gas–liquid contact time was defined as the ratio of the Sauter-mean bubble diameter to bubble rise velocity. Moreover, the experimental kLa values were well predicted, not only in the homogeneous regime, but also in the transition and heterogeneous regimes. This is a new finding, since to date, it was considered that the penetration theory needs a correction factor for a successful application to any liquid, even in the homogeneous regime. The predictions of the mass transfer coefficients kLa in the above-mentioned seven liquids imply that the mean bubble diameters are always ellipsoidal or spherical, which is the key condition for the applicability (without a correction) of penetration theory. In the presented (in this work) model-based kLa predictions, the Sauter-mean bubble diameters were estimated by means of the reliable correlation of Wilkinson et al., which always predicts a gradually decreasing bubble size at higher gas velocities.

Experimental Investigation of Mass Transfer Intensification for CO2 Capture by Environment-Friendly Water Based Nanofluid Solvents in a Rotating Packed Bed

In this research, two intensification approaches for CO2 capture via a rotating packed bed (RPB) and nanofluids were examined simultaneously to maximize the experimental mass transfer coefficient. The two intensification approaches were done by using water as a green, environmentally friendly absorption solvent and as the base fluid for preparing nanofluids and also by using centrifugal acceleration in an RPB. Physicosorption of CO2 in an RPB was carried out by applying Al2O3, TiO2, and SiO2 nanofluids to intensify the mass transfer in water, and the operation parameters such as the angular speed of the rotor, concentration and type of nanoparticles, gas and liquid flow rates, and CO2 concentration in mass transfer intensification were evaluated and several nanofluids were selected to survey investigate how they affect the mass transfer at low pressure. The results show that the Al2O3 nanofluid was more effective than other nanofluids and that the 40 nm nanofluid of this type was more efficient than the 20 nm size. Therefore, a correlation is proposed in this paper for liquid volumetric mass transfer coefficient prediction that includes the microconvection of nanoparticles and surface tension.

Scaling up extractive deacidification of waste cooking oil

Biodiesel produced from waste feedstocks can play a significant role in fighting climate change, improperly disposed waste and growing energy demand. Waste feedstocks such as used cooking oil have a great potential for energy production. However, they often have to be purified from free fatty acids prior to biodiesel production. Extractive deacidification with deep eutectic solvents is a promising alternative to conventional purification methods.To evaluate the process of extractive deacidification of waste cooking oil, a full set of physical, hydrodynamic and kinetic data were experimentally determined on a laboratory scale. Hydrodynamic and kinetic experiments were performed in three geometrically similar jacketed agitated vessels. Vessels were equipped with axial flow impeller (four pitched blade impeller). Physical properties (density, viscosity and surface tension) were experimentally determined. Preliminary hydrodynamic experiments involved several model systems without mass transfer. As a result, correlation between power number and Reynolds number as well as scale-up criterion was developed. Obtained dependencies were correlated with the physical properties. Mixing intensity for achieving complete dispersion was determined. Second stage of investigation involved two sets of experiments, hydrodynamic and kinetic, with interphase mass transfer (the extraction of free fatty acids from waste cooking oil with deep eutectic solvent, potassium carbonate:ethylene glycol, 1:10). Obtained results enabled understanding interphase mass transfer and prediction of mass transfer coefficient from the derived dimensionless correlations. The values of volumetric mass transfer coefficients were smaller for the dispersed phase, indicating that the prevailing mass transfer resistance was within the droplets. The working hypothesis was that the same process result should be achieved at the same dispersion rate, and that hypothesis was confirmed – at all scales extraction efficiency was 97.9 ± 0.1%.

Insight into bubble-to-emulsion mass transfer of an isolated clouded bubble in an incipiently fluidized bed

When the gas flowing out of the bubble in a gas–solid fluidized bed is recirculated to the bottom and then re-enters the bubble, a clouded bubble is formed. Or else, the gas directly flows into the emulsion phase, forming the cloudless bubble. Owing to different flow patterns between clouded bubble and cloudless bubble, there are different mechanisms for the bubble-to-emulsion mass transfer process. In this work, mass transfer behaviors of an isolated clouded bubble are studied by a coupled computational fluid dynamics-discrete element method (CFD-DEM). The mass exchange contributions by convection and diffusion are evaluated. The results reveal that the diffusion-induced mass transfer is more significant for the clouded bubble than that for the cloudless bubble. The predicted mass transfer coefficient considering the local gas concentration in the emulsion phase shows a good agreement with the correlation prediction by Kunii and Levenspiel (1991). Moreover, the impact of the non-isothermal condition is also explored. When the hot tracer gas is injected into the cold bed, a reverse convective mass transfer is presented at the start stage after the gas injection owing to a strong driving force of gas suction in the bubble wake. Whereas for the tracer gas injection at the room temperature into the bed with pre-heated particles, the mass transfer by diffusion is enhanced and the reverse mass transfer process disappears.

Kinetic study of SO2 with sodium lactate based deep eutectic solvents and modelling of desulfurization intensification in rotating packed bed reactor

As ionic liquids alternative, the deep eutectic solvents (DESs) are expected to realize green and efficient SO2 recovery. In this work, the reaction kinetics of SO2 and sodium lactate (NaLa)/water DES was first studied. The reaction kinetic parameters, including order of reaction, rate constant, pre-exponential factor, and activation energy were determined. In view of the reaction characteristics, desulfurization intensification by high gravity technology was proposed. A mathematic model based on the reaction kinetics was developed to describe the SO2-DES mass transfer and reaction process in a rotating packed bed reactor. To validate this model, the desulfurization efficiency and mass transfer coefficient were measured under different operating conditions. It was demonstrated that SO2 removal efficiency was above 99% under optimized conditions, realizing efficient SO2 recovery. The validity of the proposed model was confirmed by the fact that most predicted mass transfer coefficients agreed well with the experimental results with deviations within ± 15%.

Carbothermic Reduction of Zinc Containing Industrial Wastes: A Kinetic Model

Effective recycling of zinc-containing industrial wastes, most importantly electric arc furnace dust, is of tremendous importance for the circular economy of the steel and zinc industry. Herein, we propose a comprehensive kinetic model of the combined carbothermic and metallothermic reduction of zinc oxide in a metal bath process. Pyro-metallurgical, large-scale lab experiments of a carbon-saturated iron melt as reduction agent for a molten zinc oxide slag were performed to determine reaction constants and accurately predict mass transfer coefficients of the proposed kinetic model. An experimentally determined kinetic model demonstrates that various reactions run simultaneously during the reduction of zinc oxide and iron oxide. For the investigated slag composition, the temperature-dependent contribution of the metallothermic zinc oxide reduction was between 25 and 50 pct of the overall reaction mechanism. The mass transfer coefficient of the zinc oxide reduction quadrupled from 1400 °C to 1500 °C. The zinc recovery rate was > 99.9 pct in all experiments.

Applicability of linear driving force (LDF) mass transfer model for heavy metal biosorption in packed bed column

Adsorption technique for industrial effluent treatment as well as recovery of valuable components have been widely accepted for application. Since then, many researches on adsorption field have been established to investigate the economical yet having high separation efficiency of adsorbent for specific purpose. Biosorbent, for instance have shifted the focused of researches due to their abundant existence that can be easily converted into adsorbent, and some showed promising separation properties. However, the study on the biosorbent adsorption usually limited until the isotherm determination in batch experimental study. The dynamic behaviour of the system requires the experimental set-up in packed bed column, which is primarily controlled by the mass transfer mechanism. Mathematical expression describing the system is very useful as preliminary estimation of the system dynamic behaviour, provided by several input parameters such as isotherm parameters and mass transfer coefficients. Linear driving force (LDF) model approximation has proved its reliability to describe the dynamic behaviour of a system over a wide range of adsorption process. By taking three (3) experiments adsorption system on packed bed, the respective systems were simulated employing LDF approximation to obtain the dynamic behaviour of the system. The breakthrough curves were simulated by using the simplified mathematical model of LDF approximation. It is shown that the predicted LDF approximation give acceptable agreement to the experimental data with error of less than 15%, provided with mass transfer coefficient predicted from correlation. Overall, this work proved that it is possible to accurately determine the behaviour of the system using LDF approximation accompanied with the predicted mass transfer coefficient (MTC) from correlation and accurately determined adsorption isotherm for continuous system. Therefore, the mass transfer approximation is further used for evaluation of industrial-scaled packed bed column.

Recovery of Minor Palm Oil Compounds Using Packed Bed Adsorption Column

Carotene and tocopherol are valuable products that exist as minor compounds in palm oil and mostly extracted out during many stages of palm oil processing. Hence, most of it ended up in wastewater or palm oil mill effluent (POME). Fortunately, adsorption is potentially one of the most efficient method as compared to the others. In fact, it is widely studied in laboratory scale, in order to obtain equilibrium data for the steady state system. However, industrial practices are mostly operated in unsteady state in a continuous manner. Consequently, this study is executed to design a recovery process of one of the minor compounds in palm oil mill effluent (POME), which is carotene, using silica gel. It aims to predict the dynamic adsorption of recovery of minor compounds from palm oil mill effluent based on available equilibrium data, investigate the effects of dynamic and physical properties of the system towards the process by analyzing the breakthrough curve and study the feasibility of the scale up process by performing a sensitivity analysis on the system. Then, a base simulation was prepared by using available equilibrium data. Operating and design parameters such as, bed height, inlet flowrate and concentration were manipulated. Consistent with previous packed column studies, increase flow and concentration will reduce the time required for the column to achieve saturation, while increase bed height effects were vice versa. Finally, the last objective to achieve was to study the practicality of the packed bed column and perform a sensitivity on assumptions and predictions such as predicted mass transfer coefficient and isotherm model. It is proven that the selection of isotherm model and prediction in coefficient did not pose a large impact to the breakthrough curve and the average time required for the column of 1.5 m tall and 0.8 in diameter, to reach breakthrough time is 1.7 days. Hence, it can be concluded that adsorption technology using silica gel as its adsorbent can be applied is recovering minor compounds in palm oil mills.

Electro Winning from Dilute Solutions at Enhanced Rates using Three-Phase Flow Reactor

Enhancement of mass transfer coefficient is highly desirable for economic design of process equipment. The present study is essentially carried out to know the effect of flow variables such as gas and liquid velocities and geometric parameters of the internal on mass transfer coefficients in a three phase fluidized bed. The mass transfer coefficient data were obtained using a string of cones internal in a three-phase fluidized bed electrochemical reactor. The flow system investigated was nitrogen, a fluid electrolyte and spherical glass beads as gas, liquid and solid phases respectively. Limiting current technique was employed to obtain mass transfer data. The internal comprises of a string of cones arranged concentrically on a central rod which is placed coaxially in a three phase fluidized bed. The presence of internal in three phase fluidized beds augmented the mass transfer coefficient significantly. In the present investigation it was found that the effect of gas velocity, liquid velocity, rod diameter and cone diameter was only marginal. However, the influence of pitch, half apex angle of cone and particle diameter was found to be significant. Correlations were developed based on least squares regression analysis for the prediction of mass transfer coefficient in terms of pertinent variables.

Mass transfer enhancement in a two-phase flow electrochemical reactor

Experimental investigations were carried out to determine the possible levels of augmentation in mass transfer coefficient in gas–liquid flow system using a string of inverted cones. It is noticed that the mass transfer coefficient nearly doubled due to insertion of this promoter. Studies revealed that gas velocity, liquid velocity, pitch and rod diameter have no effect on mass transfer coefficient. The mass transfer coefficient increased with base diameter of cone. An empirical correlation is also obtained to predict mass transfer coefficient.

Modeling the Transient Effects of Pore-Scale Convection and Redox Reactions in the Pseudo-Steady Limit

We introduce theory to study the convection of active species with redox reactions at solid/solution interfaces within porous media, motivated by applications in energy storage devices where cyclic charge and discharge with recirculating flow requires the consideration of transient mass transfer. We show that under pseudo-steady conditions the coupled mass transfer problem involving redox of active species can be simplified to a linear, time-independent auxiliary problem. The proposed model is then solved numerically for porous media containing periodically spaced cylinders in crossflow. The results show three transport mechanisms depending on Péclet number Pe. Interactions between solid surfaces induced either by diffusion or advection produce spatial variation of surface flux. With Pe increasing from unity, advection initially causes diffusive flux to redistribute, causing a rise in Sherwood number Sh (non-dimensional mass transfer coefficient). The locations of flux maxima coincide with those of vorticity and strain rate for Pe above a certain “saturation” value. The variations of Sh with porosity and Pe are interpreted using a regime map that is defined based on the spatial variance of solute concentration. The auxiliary problem introduced provides a framework to predict mass transfer coefficients for arbitrary microstructures to guide the design of high-performance electrodes.

Artificial neural network modeling on the prediction of mass transfer coefficient for ozone absorption in RPB

It has been proved that Higee technology can intensify the processes involving the multiphase mass transfer, and be applied to the ozone-based advanced oxidation processes. Modeling and prediction of mass transfer coefficient are rare in this field. A modeling approach based on artificial neural network (ANN) was developed in this work to predict mass transfer coefficient of ozone absorption process in rotating packed bed (RPB). Serial experiments were conducted to obtain data for the establishment of ANN model, which was then employed to predict the overall mass transfer coefficient (KLa) using dimensionless quantities such as Reynolds number of gas and liquid, Froude number and Weber number, calculated in terms of the geometry of RPB and operating conditions. To optimize the model structure and performance, random grid search for hyperparameters was adopted in this work. The final model exhibits a prediction ability with R2 of 0.9896 and 0.9877, RMSE of 0.01801 and 0.03085, and MAE of 0.01265 and 0.02219 on the training set and the test set, respectively.

Influence of climatic conditions on evaporation in soil samples

Evaporation rates can be successfully modelled for soil–atmosphere interaction problems by means of a convective vapour flux at the soil surface equal to the product of a driving force (difference between the vapour density at the soil surface and that of the surroundings) and a mass transfer coefficient characterising the resistance of a boundary layer where the transfers take place. While the vapour density at the soil surface can be deduced from solving the coupled heat and moisture transfer equations for the soil below the surface, the determination of the mass transfer coefficients under varying weather conditions is rarely investigated. Laboratory-scale drying tests are performed on a compacted silt specimen, focusing on the influence of atmospheric conditions (relative humidity and wind speed) on the evaporation kinetics and the mass transfer coefficient. Two experimental techniques are used and compared: a drying chamber with relative humidity controlled through saline solutions and a convective microdryer. New insights are given into the prediction of mass transfer coefficients from mass transfer theories. Finally, the results highlight the necessity of testing specimens that are large enough to define relevant mass transfer coefficients for geotechnical applications.

A novel mass transfer coefficient correlation for improved rare earth metals extraction via supported nanoliquids membrane

Rare earth metals Gadolinium (Gd) and Neodymium (Nd) extraction from aqueous media were investigated by supported nanoliquid membrane. The supported nanoliquid membrane was prepared by dispersion of nanoparticles in organic membrane phase. Different sizes and concentrations of the nanoparticles were tested in order to find their influence on the extraction. Using hydrophobic nanoparticle SiO2, permeability coefficient improvement of 28.3% and 49.5% for Gd and Nd extraction were observed, respectively. It was found that the SiO2 nanoparticle gained the highest intensification in metal ion extraction via supportel nanoliquid membrane. Moreover, a novel correlation for mass transfer coefficient prediction was developed with AARE of 17.03%, based on theoretical equations related to the supported liquid membrane transport mechanism which was function of nanoparticle size and concentration.