Microwave-assisted Fluidized Bed Drying Research Articles

Effect of hybrid drying technique on non-traditional Chicory (Cichorium intybus L.) herb: Phytochemical, antioxidant characteristics, and optimization of process conditions

This research investigated the influence of microwave-assisted fluidized bed drying (MAFBD) on the antioxidant and phytochemical characteristics of Chicory. Microwave power, temperature, and air velocity were used as process variables varied between 180–540 W, 50–70 °C, and 15–20 m/s, respectively. The responses determined for deciding the optimal criteria were total phenolics content, ascorbic acid, DPPH radical scavenging activity, total chlorophyll, carotene content, total flavonoid content, tannin content, and saponin content of the dried chicory. Statistical analyses were done by using the response surface methodology, which showed that independent variables affected the responses to a varied extent. The design expert predicted 462.30 W microwave power, 70°C temperature, and 15 m/s air velocity as optimum conditions to obtain highest desirability for the dried chicory. Separate validation experiments were conducted, under optimum conditions, to verify the predictions and adequacy of the second-order polynomial models. Under these optimal conditions, the predicted amount of ascorbic acid content was 38.32 mg/100g DW, total phenolic content 216.42 mg/100g DW, total flavonoid content mg/100g DW, DPPH scavenging activity 36.10 μg/ml, total chlorophyll content 311.79 mg/100g, carotene content 7.30 mg/100g, tannin content 2.72 mg/100g, and saponin content 0.46 mg/100g. The investigated parameters had a significant effect on the quality of the dried chicory. Taking the aforesaid results into consideration, our study recommended MAFBD as a promising technique with minimum changes in antioxidant and phytochemical content of chicory.

Multi-objective optimization of hybrid microwave-fluidized bed drying conditions of rice using response surface methodology

The present study is aimed to examine the drying of paddy to a moisture level of 12% wet basis using a microwave-assisted fluidized bed dryer. The experiments were designed and analysed using response surface methodology through which, the drying conditions were optimized in terms of minimized energy consumption and maximized quality of the final dried rice. A central composite design was applied for the three featured parameters including air temperature (40–80 °C), air velocity (1–5 m/s) and microwave power level (100–900 W). The quality of dried rice was specified in terms of whiteness index, water uptake ratio, elongation ratio and head rice yield. A modified cubic model was observed in all responses with high R2 values (>0.9). The whiteness index of dried paddy increased as the microwave power and fluidization velocity was simultaneously raised. Moreover, higher microwave power and lower temperatures resulted in improved head rice yield of paddy samples. On the other hand, high microwave power accompanied by high temperatures reduced the drying time and correspondingly the specific energy consumption. It could be concluded that a microwave-fluidized bed dryer provides samples with better properties than the single fluidized bed dryer. The optimum conditions of microwave-fluidized bed drying of rice with maximum product quality and minimum time and energy consumption were: air velocity of 4.2 m/s, air temperature of 72 °C and microwave power of 652 W.

Fluidized bed and microwave-assisted fluidized bed drying of seed grade soybean

Soybean seeds were dried under fluidized bed drying (FBD) and microwave-assisted fluidized bed drying (MFBD) conditions in this study. During FBD, the effect of air temperature (30–50 °C) and air velocity (1–7 m/s) on drying parameters and some quality attributes (viz. vigor index, germination, fissure and cracking percentage, and seed coat hardness) of dried seeds were analyzed through response surface method. In MFBD, the effect of air temperature and microwave power levels was studied on the drying kinetics and quality parameters at a constant air velocity of 7 m/s. A face-centered central composite design with three levels of each variable was used to generate models for the responses. The study showed that the drying of seeds under two methods resulted in high germination percentage (>77%) and low cracking percentage (<20%). However, an increase in the germination time as depicted through the vigor index was found in the dried seeds. Also, the seed coat was highly damaged during drying and resulted in fissures (∼100%) and a decrease in hardness of the seed coat.

Drying behavior, diffusion modeling, and energy consumption optimization of Cuminum cyminum L. undergoing microwave-assisted fluidized bed drying

A semi-empirical mathematical model of mass transfer was developed to investigate the microwave-assisted fluidized bed drying of Cuminum cyminum L. and to optimize drying condition based on drying rate and energy consumption. Accordingly, the drying kinetics of this seed undergoing microwave-assisted fluidized bed dryer at various microwave output powers (300, 600, 900 W), air velocities (3.60, 5.45, 7.30 m/s), and air temperatures (45 °C, 55 °C, 65 °C) were studied. Concerning the distinctive shape of seeds, we tried to find a convenient and efficient model to evaluate moisture effective diffusivity ( and activation energy (). The range of and values were estimated to be from 0.382 10−10 to 2.746 10−10 m2/s for Deff and 8.464 W/g 44.653 kJ/mol for Ea.

Optimization of microwave-assisted fluidized-bed drying of carrot slices

ABSTRACTThe drying of carrot slices in a microwave-assisted fluidized-bed drying (MWFBD) system was investigated. The drying conditions such as the initial microwave power density and the inlet air temperature were optimized. The effects of different pretreatment processes such as water blanching, osmotic drying with 20% sugar solution, and 1% citric acid solution on the drying of carrot slices were investigated under the optimized drying conditions. The drying kinetics and the physical properties of the dried carrot slices were analyzed. Different mathematical models of the drying process were explored and fitted to the drying of carrot slices in MWFBD. The pretreatment of the carrot slices reduced the drying time required and improved the qualities such as color and textural strength of the dried carrot slices.

Experimental study on three-stage microwave-assisted fluidized bed drying of Shengli lump lignite

ABSTRACTThe drying characteristics of Shengli lump lignite in a three-stage microwave-assisted fluidized bed dryer (MFBD) are investigated in this study. The fluidized bed was operated with a continuous feed in the modes with one to three stages. The effects of microwave power and microwave time on the drying rate and fragmentation rate are studied. The drying rate of Shengli lump lignite increased with increasing microwave power. The fragmentation rate depended on microwave power, microwave time, and final moisture content. The fragmentation rate of dried lignite was in the range of 3–15%. Furthermore, an increase in fragmentation rate at a high microwave power correlates with an increase of the drying time. Pore size distribution in the lignite was determined by mercury intrusion porosimetry (MIP method). With increasing microwave power, total pore volume significantly decreased and average pore diameter was nearly unchanged.

Prediction of Physicochemical Properties of Raspberry Dried by Microwave-Assisted Fluidized Bed Dryer Using Artificial Neural Network

The main target of this research is to dry raspberries in a microwave-assisted fluidized bed dryer. Artificial neural network (ANN) modeling was used in order to evaluate and predict the physicochemical properties of this fruit. In this research, the effects of five variables—microwave power (0, 300, and 600 W), temperature (55, 70, and 85°C), air flow rate (15, 20, and 25 m/s), starting time of microwave input (from the moment when the moisture content decreased until 334, 400, and 466 g water/g dry matter), and amount of loaded material (50, 100, and 150 g)—on nine outputs—drying time, rehydration capacity, density, porosity, hardness, water activity, phenolic compounds content, anthocyanins content, and the antioxidant activity of dried raspberries—were studied. A feed-forward multilayered perceptron trained by back-propagation algorithms for five independent variables was developed to predict these nine outputs. The optimal configuration of the neural network model had a hidden layer with nine neurons. The predictive ability of the ANN was compared using a separate data set of 52 unseen experiments based on root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R 2) for each output parameter. The optimum model was able to predict the nine output parameters with a coefficient of determination higher than 0.92. The results indicated that the experimental and ANN-predicted data sets were in good agreement, so it is feasible to use an ANN to predict the physicochemical properties of dried black raspberry.

Simulation of energetic- and exergetic performance of microwave-assisted fluidized bed drying of soybeans

The performance of microwave-assisted fluidized bed drying of soybeans was simulated (using a previously validated mathematical model) and analyzed based on the first- and second law of thermodynamics. The energy and exergy analysis were carried out for several drying conditions. The effects of inlet air temperature, microwave power density, bed thickness and inlet air velocity on the efficiencies and inefficiencies of drying process have been simulated and discussed. Generally, application of microwave energy during fluidized bed drying enhanced the exergy efficiency of drying process. However, the results showed that it was more efficient not to apply microwave energy at the first stage of fluidized bed drying process. The application of higher levels of drying air temperature led in higher exergy efficiencies. The values of mean relative deviations for the predictions of efficiencies and inefficiencies of drying process were less than 14%, compared with those calculated using experimental data.

CFD Modeling of Microwave-Assisted Fluidized Bed Drying of Moist Particles Using Two-Fluid Model

The drying behavior of moist spherical particles in a microwave-assisted fluidized bed dryer was simulated. The two-fluid Eulerian model incorporating the kinetic theory of granular flow was applied to simulate the gas–solid flow. The simulations were carried out using the commercial computational fluid dynamics (CFD) package Fluent 6.3.26. The effects of different levels of microwave power densities as well as initial gas temperature on the prediction of solids moisture content, gas temperature, and gas absolute humidity were investigated. The effect of microwaves was incorporated into calculations using a concatenated user-defined function (UDF). The simulation results were compared with experimental data obtained from drying of soybeans in a pilot-scale microwave-assisted fluidized bed dryer and reasonable agreement was found. The mean relative deviation for prediction of solids moisture content, gas temperature, and gas absolute humidity were less than 3, 10, and 5%, respectively. Further work is needed to validate the proposed model for large-scale plants.

Simulation and Validation of Microwave-Assisted Fluidized Bed Drying of Soybeans

A general mathematical model of heat and mass transfer was developed to simulate the microwave-assisted fluidized bed drying of bulk grain. The model was solved using the well-known Runge-Kutta-Gill method. The model is capable of predicting the moisture content of soybean as well as the drying air parameters (i.e., drying air temperature and moisture content) during drying. The values of mean relative deviation (MRD) were less than 8 and 10% for prediction of grain moisture content and outlet air parameters, respectively, which reflects an acceptable accuracy. In comparison with conventional fluidized bed drying of soybean, microwave-assisted fluidized bed drying led to 83.39–98.07% savings in drying time and 82.07–95.22% savings in specific energy consumption when reducing soybean moisture content from 18.32 to 12% (db).

English

Grain drying is a vital unit operation in many processing plants. An undesirable change associated with this operation is shrinkage of dried product which results in decreased quality. Recently many attempts have been made to decrease the shrinkage of food stuff during drying. Microwave-assisted fluidized bed drying has particularly been proposed as a potentially effective method. In the present study, at each drying operating condition, the volume of shelled corn was calculated by measuring the three principal characteristic dimensions. The varia- tion of the ratio of mean diameter of the kernel to its initial mean diameter was investigated for different operating conditions. It has been shown that employing microwave in fluidized bed drying reduces the shrinkage of particles considerably. Also, in this study, Artificial Neural Networks (ANN) analysis was employed to predict the extent of shelled corn shrinkage. In the construction of the network, three independent variables: microwave heat source, drying air temperature and moisture content were chosen as the input parameters and shrinkage of dried sample was set as the output parameter (dependent variable). The ANN model with 5 neurons was selected for studying the influence of transfer functions and training algorithms. It has been observed that back-propagation networks with logsig transfer function and trainlm algo- rithm were the most appropriate ANN configuration for predicting shrinkage. Results from the experiments and modeling showed good agree- ment. In order to test the ANN model the random errors were within an acceptable range of ±5% with a correlation coefficient (R2) of 98%.

Experimental and theoretical investigation of shelled corn drying in a microwave-assisted fluidized bed dryer using Artificial Neural Network

Drying characteristics of shelled corn ( Zea mays L ) with an initial moisture content of 26% dry basis (db) was studied in a fluidized bed dryer assisted by microwave heating. Four air temperatures (30, 40, 50 and 60 °C) and five microwave powers (180, 360, 540, 720 and 900 W) were studied. Several experiments were conducted to obtain data for sample moisture content versus drying time. The results showed that increasing the drying air temperature resulted in up to 5% decrease in drying time while in the microwave-assisted fluidized bed system, the drying time decreased dramatically up to 50% at a given and corresponding drying air temperature at each microwave energy level. As a result, addition of microwave energy to the fluidized bed drying is recommended to enhance the drying rate of shelled corn. Furthermore, in the present study, the application of Artificial Neural Network (ANN) for predicting the drying time (output parameter for ANN modeling) was investigated. Microwave power, drying air temperature and grain moisture content were considered as input parameters for the model. An ANN model with 170 neurons was selected for studying the influence of transfer functions and training algorithms. The results revealed that a network with the Tansig (hyperbolic tangent sigmoid) transfer function and trainrp (Resilient back propagation) back propagation algorithm made the most accurate predictions for the shelled corn drying system. The effects of uncertainties in output experimental data and ANN prediction values on root mean square error (RMSE) were studied by introducing small random errors within a range of ±5%.

Mathematical modeling of microwave-assisted inert medium fluidized bed drying of cylindrical carrot samples

Drying behavior of cylindrical samples of carrot was investigated in a microwave-assisted fluidized bed of inert particles. A pilot-scale microwave-assisted fluidized bed dryer was set up for this purpose. Glass beads particles were used as inert materials. Based on the simultaneous heat and mass transfer, a mathematical model was proposed for predicting the temperature and moisture distribution in the drying sample. Considering the carrot radiuses and the penetration depth of the electromagnetic waves, a uniform electric field strength distribution within the drying material was assumed in the proposed model. The heat loss due to surface evaporative cooling was also considered at the external boundaries. A numerical solution was developed for the proposed model using an implicit finite difference method in one-dimensional system. The model was validated by comparing the predicted data with the experimental data, obtained from different cylindrical carrot samples during drying. The effects of microwave power density and also drying air temperature on the moisture and temperature profiles were investigated.