Mathematical modeling of intermittent and convective drying of rice and coffee using the reaction engineering approach (REA)

Multiphysical field and multiobjective mathematical modeling of grain-oilseed storage: Current status and future trends

Storage is an important process involved in the postharvest treatment of grain-oilseed and is necessary for maintaining high quality and ensuring the long-term supply of these commodities in the food industry. Proper storage practices help prevent spoilage, maintain nutritional value, and preserve marketable quality. It is of great interest for storage to investigate flow, heat and mass transfer processes, and quality change for optimizing the operation parameters and ensuring the quality of grain-oilseed. This review discusses the mathematical models developed and applied to describe the physical field, biological field, and quality change during the storage of grain-oilseed. The advantages, drawbacks, and industrial relevance of the existing mathematical models were also critically evaluated, and an organic system was constructed by correlating them. Finally, the future research trends of the mathematical models toward the development of multifield coupling models based on biological fields to control quality were presented to provide a reference for further directions on the application of numerical simulations in this area. Meanwhile, artificial intelligence (AI) can greatly enhance our understanding of the coupling relationships within grain-oilseed storage. AI's strengths in both qualitative and quantitative analysis, as well as its effectiveness, make it an invaluable tool for this purpose.

Computational Modeling of Drying of Pharmaceutical Wet Granules in a Fluidized Bed Dryer Using Coupled CFD-DEM Approach

Drying of wet granules in a fluidized bed dryer is an important part of the pharmaceutical tablet manufacturing process. Complicated gas-solid flow patterns appear in the fluidized bed dryer, and interphase momentum, heat, and mass transfer happen during the drying process. A coupled computational fluid dynamics (CFD)-discrete element method (DEM)-based approach was used to model the drying process of pharmaceutical wet granules in a fluidized bed dryer. The evaporation of water from the surfaces of the particles and the cohesion force between the particles due to the formation of liquid bridges between the particles were also considered in this model. The model was validated by comparing the model predictions with the experimental data available from the literatures. The validated model was used to investigate the drying kinetics of the wet granules in the fluidized bed dryer. The results from numerical simulations showed that the dynamics and rate of increase of temperature of wet particles were considerably different from those of dry particles. Finally, the model was used to investigate the effects of inlet air velocity and inlet air temperature on the drying process. The model predicted increase in drying rate with the increase of inlet air velocity and inlet air temperature. This model can help not only to understand the multiphase multicomponent flow in fluidized bed dryer but also to optimize the drying process in the fluidized bed dryer.

Mathematical analysis of solar conduction dryer using reaction engineering approach

Solar conduction dryer (SCD) utilizes all three modes of heat transfer, viz., conduction, convection, and radiation. The effect of individual mode of heat transfer in SCD on agricultural product drying was studied using drying kinetics and basic heat transfer calculations. It was observed that the order of influence of mode of heat transfer mechanism as conduction followed by radiation and then convection. The correlation for relative activation energy (∆Ev/∆Ev,∞) as a function of moisture content (X−X∞), effective diffusivity (Deff), and mass transfer coefficient (hm) were determined for each mode of heat transfer. It was observed that the reaction engineering approach (REA) is appropriate tool to understand the physics of drying mechanism in SCD.

Drying Characteristics of Soybean (Glycine Max) Using Continuous Drying and Intermittent Drying

The effects of drying temperature by continuous and intermittent drying on the drying characteristics of soybean were determined in this study. Among the thin-layer drying models, the Midilli–Kucuk model showed the best fit (R2> 0.99) to describe the drying of soybean. At 300 min of the effective drying time, the moisture content of continuous drying at 35, 40, and 45 ºC were 9.38 (±0.00), 8.69 (±0.17), and 7.70 % (±0.48), respectively; while the moisture content of intermittent drying at 35, 40, and 45 ºC were 8.28 (±0.21), 7.31 (±0.41), and 6.97 % (±0.07), respectively. The image analysis method for detection of the crack in soybean demonstrated that at the target moisture content (7.7 %), cracked grain ratios with intermittent drying at 35, 40, and 45 ºC were reduced by 52.08, 27.59, and 18.24 %, respectively. With the effective drying time, the activation energy for intermittent drying (9.33 kJ/mol) was significantly lower than that value for continuous drying (21.23 kJ/mol).

The effect of intermittent drying on the cracking ratio of soybeans (Glycine max) at different relative humidity using reaction engineering approach modeling

Intermittent drying (ID) was applied to reduce soybean cracking because of the low moisture gradient and little thermal stress on soybeans during their tempering period. The drying temperature and relative humidity (RH) for the drying and tempering periods were 35°C and 20% and 25°C and 43%, respectively. The intermittency (α) of the drying was defined as the ratio of the drying period to the duration of the drying and tempering periods, and it varied at α = 1, 0.5, 0.4, and 0.25 to evaluate the drying characteristics and the soybeans' quality. Intermittency processes redistributed the moisture in the soybean so that the low thermal stress was applied to the soybeans. The percentage of cracked grains increased with increasing the duration of drying period and decreasing tempering period. The moisture content and temperature changes during drying of soybeans were well fitted by reaction engineering approach (REA) modeling. Additionally, the physics that describe the soybeans' drying behavior during ID were explained by the model parameters obtained from the REA modeling, such as the surface relative humidity and the surface water vapor concentration. ID showed the highest drying efficiency at α = 0.25 regarding the total drying time (13,800 s, i.e., the shortest drying time) and the lowest cracking ratio (<2.18%).

Modeling and Improving the Performance of Cabinet Solar Dryer Using Computational Fluid Dynamics

In this study, a new approach for numerically modeling of an entire cabinet solar dryer is proposed. Collector, drying chamber and chimney are the three principle sections considered in the present modeling. The collector section containing a cover and an absorber plate is modeled applying energy and fluid flow equations to obtain temperature distribution inside the collector. Due to the non-linear behavior of the governing equations as well as variety of effective variables, an iterative method is employed for solution. Regarding the geometry complexity of the drying chamber along with the air compressibility (that in turn causes coupling of momentum and energy equations) drying chamber is simulated by CFD method. Chimney’s effect and effective parameters in suction are comprehensively considered in the present model. The numerical results are in line with experimental results which show that the model can be applied with certainty to employ the dryer for drying highly demanded and time-consuming products in a scientific, sanitary, and timely manner. The model is then optimized by adding some baffles to achieve higher efficiencies and accelerate the drying process.