Examining the Suitability of the Reaction Engineering Approach (REA) to Modeling Local Evaporation/Condensation Rates of Materials with Various Thicknesses

The reaction engineering approach (REA) is examined here to investigate its suitability as the local evaporation rate to be used in multiphase drying. For this purpose, REA is first implemented to model the convective drying of materials with various thicknesses. The relative activation energy, as the fingerprint of REA, generated from one size of a material is used to model the convective drying of the same material with different thicknesses. Because the results indicate that REA parameters can model the drying of materials with various thicknesses, REA can be scaled down to describe the local evaporation rate (at the microscale as affected by local composition and temperature). The relative activation energy is used to describe the global drying rate in modeling the local evaporation rate. REA is combined with a system of equations of conservation of heat and mass transfer in order to yield the spatial reaction engineering approach (S-REA) as a nonequilibrium multiphase drying model. By using S-REA, the spatial profiles of moisture content, concentration of water vapor, temperature, and local evaporation rate can be generated, which can assist in comprehending the transport phenomena.     

Modeling Intermittent Drying of Wood under Rapidly Varying Temperature and Humidity Conditions with the Lumped Reaction Engineering Approach (L-REA)

For improving product quality and minimizing energy consumption during drying, intermittent drying is often recommended. The mathematical models that are used to describe intermittent drying are usually transport phenomena based, complex models. In this study, the lumped reaction engineering approach (L-REA) is implemented to model wood drying under rapid periodically changed drying air temperature and humidity with high number of cycles of intermittency. The equilibrium activation energy (ΔE _v,b ), an important parameter for REA approach, is evaluated according to the corresponding drying air temperature and humidity in each drying section. The results of modeling suggest the L-REA works well with the experimental data. The simplicity of the L-REA is obvious and is hoped to be used in an industrial setting more readily. The L-REA can be used for sustainable processing in industries to assist in energy audit and management.     

Application of the reaction engineering approach (REA) to model cyclic drying of thin layers of polyvinyl alcohol (PVA)/glycerol/water mixture

Rapid development of industrial polymer-based product requires considerable research in polymer drying. Cyclic or intermittent drying is used occasionally to save energy and improve product quality. Most published studies employ diffusion-based models. Reaction engineering approach (REA) is a lumped parameter model which is comparably simple and is now applied to cyclic situation for the first time. New definitions of equilibrium activation energy (ΔE_v,b) had to be introduced. With these definitions, very reasonable agreement between the predicted and published experimental data is shown. It has advantage over the diffusion model where in general complex diffusivity functions are used and had to be established using experimental data anyway. REA may be used in plant-wide simulations, where the drying kinetics has to be coupled with many other equations to be solved together. In this case, the computation time would be generally reduced if there is no need to solve the spatial distribution of water content inside the product.     

The Relative Activation Energy of Food Materials: Important Parameters to Describe Drying Kinetics

An effective drying model should be accurate and require a small number of experiments to generate the parameters. The relative activation energy of various food materials, important drying kinetic properties used in the reaction engineering approach, is evaluated and summarized. The reaction engineering approach is then implemented to model the global and local drying rates of food materials. By using the relative activation energy, the reaction engineering approach describes the (R² higher than 0.99) global drying rate of food materials well. The reaction engineering approach can be coupled with a set of equations of conservation of heat and mass transfer to model the local drying rate of food materials. The relative activation energy is indeed proven to be accurate to model the local drying rate. While the predictions are accurate, the reaction engineering approach is very effective in generating the drying parameters since the relative activation energy can be generated from one accurate drying run. Different drying conditions of the same material with similar initial moisture content would result in the similar relative activation energies. The drying kinetics parameters generated here are readily used for design of new equipment, evaluating the performance of existing dryers, and monitoring the product quality.     

Application of the reaction engineering approach (REA) for modeling intermittent drying under time-varying humidity and temperature

A ‘good’ drying model is important for the design of dryer, evaluation of dryer performance and prediction of product quality. Among the available models, the reaction engineering approach (REA) is a lumped model, proven to be simple, robust and accurate to model drying of several materials. In this paper, the REA is implemented to model intermittent drying, which is usually practiced for saving energy consumption and maintaining product quality during drying, under time-varying drying air temperature and humidity, which is a challenging drying case to model. For this purpose, the equilibrium activation energy (ΔE_v,b) is defined according to the drying settings in each time period and combined with the relative activation energy (ΔE_v/ΔE_v,b) generated from the convective drying experimental data obtained under constant drying conditions. The mass and heat balances also implement the corresponding drying settings in each time period during the intermittent drying. The results indicate that the REA can describe both the moisture content and temperature profiles of the intermittent drying under time-varying drying air temperature and humidity well. The accuracy, simplicity and robustness of the REA for the intermittent drying under time-varying drying air temperature and humidity are proven here. This has provided a major and significant extension of the REA on modeling challenging drying cases.     

Recovery of aconitic and lactic acids from simulated aqueous effluents of the sugar‐cane industry through liquid–liquid extraction

The recovery of aconitic and lactic acids from dilute aqueous effluents of the sugar‐cane industry by a solvent extraction technique has been investigated in order to reduce environmental pollution and in view of the possible uses of pure solutes in the field of foods and pharmaceuticals. Reactive extraction of carboxylic acids with tributylphosphate dissolved in dodecane was examined. Experiments were performed at 25 °C for three extractant concentrations of 50%, 60% and 70% (mass %) in dodecane. The decrease of specific gravity and viscosity of solvent resulting from the presence of an inert diluent was favourable to the phase settling and the mass transfer. The percentage of acids recovered in the organic phase for a volumetric solvent ratio varying from 0.5 to 5.0 was determined. Taking into account the difference between the partition coefficients for the carboxylic acids under consideration, the selectivity of solvent with regard to aconitic acid also was quantified. Moreover, owing to its water‐insolubility, its availability and its low cost, tributylphosphate can be considered as a promising extractant for large‐scale applications. © 2000 Society of Chemical Industry     

A continuum‐approach modeling of surface composition and ternary component distribution inside low fat milk emulsions during single droplet drying

Surface composition of dairy powders plays an important role in determining the functionality. However, the surface composition may be different from the bulk composition because of component migration during drying. In this study, a comprehensive mathematical model has been developed to describe the phenomena. To the best of our knowledge, it is the first mathematical model which predicts the dynamics of surface composition during drying. The model consists of a set of equations of conservation of mass of water, lactose, protein, and fat as well as conservation of heat and momentum in which the effects of diffusion induced material migration and surface activity are incorporated. This model is applicable to describe the kinetics of surface composition of dairy droplets during drying. It suggests that both diffusion and protein surface activity govern the component segregation during drying. The study indicates that the model implementing the measured initial surface composition as the initial conditions generates more realistic profiles than the one using the bulk composition. The modeling confirms that the difference between the surface and bulk composition that occurs prior to drying is not primarily governed by diffusion, but the emulsion's atomization behavior seems to play an essential role in the overrepresentation of fat. © 2017 American Institute of Chemical Engineers AIChE J, 63: 2535–2545, 2017     

Modeling of Convective Drying of Sawdust Using a Reaction Engineering Approach

Drying as a simultaneous heat and mass transfer process can be modeled via the reaction engineering approach (REA) where the apparent activation energy of the material is established and related to its moisture content during drying. This relationship is unique as the normalized activation energies can be collapsed into a single equation irrespective of the drying conditions and dryer types. Here, REA was applied to model the drying kinetics of sawdust using convective hot air in a laboratory setup. The normalized (relative) activation energy curve generated from one drying experiment was employed to predict the drying kinetics and temperature profiles. The REA can describe well the convective drying kinetics of sawdust, and major physics of the drying process was captured well with this technique.     

Microwave drying at various conditions modeled using the reaction engineering approach

ABSTRACT

One of the most significant process intensification schemes in drying is microwave drying. Modeling the process of microwave drying is very useful. The lumped reaction engineering approach (REA) is now coupled with appropriate equations for modeling microwave heating. Here, a slight modification of the equilibrium activation energy is needed since the product temperature is higher than the ambient temperature. Unlike the diffusion-based approach, the REA drying parameters were generated from minimum number of drying runs. It has been found that the modifications lead to excellent agreements between the predicted and experimental data. The results of modeling match well with the experimental data. The overall model is accurate to describe the moisture content and temperature profiles. Comparisons with the diffusion-based approach indicate that the REA can achieve comparable or even better agreement toward the experimental data. This exercise has demonstrated that a simple combination of the lumped reaction engineering approach and the microwave energy absorption is versatile in predicting the microwave drying process accurately; thus, this worked example will be illustrative for future needed studies.     

An accurate account of mass loss during cheese ripening described using the reaction engineering approach (REA)‐based model

Cheese ripening is an important step in cheese making for modifying surface and curd properties. Due to physical, chemical and biological changes, mass loss usually occurs during the process. Although these changes are essential for developing the texture and flavour of cheese, mass loss decreases product yields. A reliable mathematical model is used to quantify mass loss during cheese ripening so that the processing conditions can be fine‐tuned to achieve the desirable throughput. In this study, for the first time, the reaction engineering approach (REA)‐based model is applied to model the cheese ripening. The study shows that the REA‐based model is accurate to model cheese ripening of Camembert and French smear cheese. In addition, the REA is able to model the cheese ripening under time‐varying environmental conditions. For this purpose, the equilibrium activation energy is evaluated according to the corresponding humidity and temperature in each period, while the same relative activation energy for ripening under constant environmental conditions is implemented. The REA is a simple yet effective approach to model the simultaneous heat and mass transfer process accompanied by chemical and biological reactions. Considering its effectiveness, the REA can be applied in industrial settings for predicting mass loss during cheese ripening.