Modeling the Drying Kinetics of Pigeon Pea [Cajanus cajan (L.) Millspaugh]

We set out to model the oven-drying kinetics of a legume known as pigeon pea, harvested in the Bouenza department in the south-west of the Republic of Congo. The drying kinetics of pigeon peas was carried out in an oven under experimental conditions using temperatures of: 50°C, 60°C and 70°C. Seven mathematical models were used to describe pigeon pea drying. During drying, water loss was faster and shorter at 70°C [10.446 g/25 g wet weight (wwb) for 320 min (5.3 h)] compared to 50°C [10.996 g/25 g wet weight (wwb) for 520 min (8.6 h)] and 60°C [10.616 g/25 g wet weight (wwb) for 420 min (7.0 h)] where it was slower and longer. With regard to modeling, and based on the principle of choosing the right model focusing on the high value of R2 and low values of χ2 and RMSE, two models were selected, the Midili model for temperatures of 50°C and 60°C and the Henderson and Pabis model modified for temperature of 70°C showed better results. The R2, χ2 and RMSE values calculated for pigeon pea are 0.99985, 3.93404E-5 and 0.00627;0.9997, 9.245E-5 and 0.00962;0.99996, 1.56332E-5 and 0.00395 respectively at 50°C, 60°C and 70°C.

Microwave drying characteristics and kinetics of ilmenite

The microwave drying of ilmenite was investigated.The effects of power levels and sample mass on drying characteristics of moisture content,drying rate,moisture ratio were studied,with microwave power ranging from 119 W to 700 W and sample mass from 5 g to 25 g.The drying processes were completed within 2-8 min at different conditions.The moisture content and drying rates are found to be dramatically affected by microwave power density.For all drying processes the prior microwave absorption of moisture produces an accelerating peak on the drying rate curves in the initial stage.For the sample mass of 25 g and power of 385 W,the drying kinetics were studied.The experimental results fit better to the Henderson-Pabis index model rather than the Page＇s semi-empirical model;the drying rate constant k is increased with the increase of microwave power and decrease of sample mass.

Modeling of temperature-humidity for wood drying based on time-delay neural network

The temperature-humidity models of wood drying were developed based on Time-delay neural network and the identification structures of Time-delay neural network were given. The controlling model and the schedule model, which revealed the relation between controlling signal and temperature-humidity and the relation between wood moisture content and temperature-humidity of wood drying, were separately presented. The models were simulated by using the measured data of the experimental drying kiln. The numerical simulation results showed that the modeling method was feasible, and the models were effective.

Effect of Seed Coat on Drying Kinetics of Kidney Bean Seed

Kidney bean seed was dried in a laboratory scale fixed bed. The effect of seed coat on drying dynamic characteristics and the changes of seed coat structure were investigated. A mathematical model was established to simulate the drying process and determine the moisture diffusivity. Numerical results agree well with the experimental data. The average moisture diffusivity of the seed with separated coat is 1.67 times larger than that of the seed with coat, and the moisture diffusivity of seed cotyledon is 3.2 times larger than that of the seed coat. It is proved that the seed coat is the most main resistance of mass transfer and is also one of the key points of the optimization of heat and mass transfer for seed drying.

Liquid penetration of freeze-drying and air-drying wood of plantation Chinese fir

A comparative study was conducted on liquid penetration of the freeze-drying and air-drying sapwood and heartwood lumber of plantation Chinese fir （Cunninghamia lanceolata）. The maximum amount of dyeing solution uptake by the capillary rise method was used to evaluate the liquid penetration properties of the treated wood. The pit aspiration ratio was determined by semithin section method. Changes in wood microstructure were investigated using scanning electron microscopy. The results showed that compared with air drying, the freeze drying had a significant effect on liquid penetration of sapwood and heartwood of Chinese fir. The liquid penetration of sapwood is significantly higher than that of the heartwood for both drying treatments. Low pit aspiration ratio and cracks of pits membrane of some bordered pits are the main reasons for increasing liquid penetration after freeze drying treatment.

Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms

The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.

Optimization of processing parameters for microwave drying of selenium-rich slag using incremental improved back-propagation neural network and response surface methodology

In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of independent variables （the microwave power, the acting time and the rotational frequency） for microwave drying of selenium-rich slag. The optimum operating conditions obtained from the quadratic form of the RSM are： the microwave power of 14.97 kW, the acting time of 89.58 min, the rotational frequency of 10.94 Hz, and the temperature of 136.407 ℃. The relative dehydration rate of 97.1895% is obtained. Under the optimum operating conditions, the incremental improved BP neural network prediction model can predict the drying process results and different effects on the results of the independent variables. The verification experiments demonstrate the prediction accuracy of the network, and the mean squared error is 0.16. The optimized results indicate that RSM can optimize the experimental conditions within much more broad range by considering the combination of factors and the neural network model can predict the results effectively and provide the theoretical guidance for the follow-up production process.

Drying Kinetics and Energy Consumption in Vacuum Drying Process with Microwave and Radiant Heating

The general objective of this work is to analyze energy input in a vacuum process with the incorporation of microwave heating. Thus, necessary criteria for designing an efficient freeze-drying operation are considered through the analysis of strategies based on the combination of different intensities of radiant and microwave heating.The other aim of this research topic is to study the kinetics of drying in relation to mass transfer parameters.Five freeze-drying strategies using both heating systems were used. Consequently, energy input could be related to diffusivity coefficients, temperature and pressure profiles during dehydration of the product and analyzed in comparison to a conventional freeze-drying process.

Kinetic model research on drying characteristics of artificial magnetite green pellet

In this study,the effects of drying temperature,hot airflow speed and diameter of green pellet on drying rate of artificial magnetite pellet were deeply investigated to clarify the drying characteristics of artificial magnetite green pellet.The results show that the drying process of artificial magnetite green pellet has three stages,accelerated drying stage,constant drying stage and decelerated drying stage.And drying temperature and hot airflow speed both have significant reciprocal effects on moisture ratio and drying rate of green pellet during the drying process.However,the diameter of green pellet has little effect on drying process of green pellet.Then the drying fitting models of Correction Henderson and Pabis,Lewis,Correction Page(III),Wang and Singh are used to describe the drying kinetics of artificial magnetite green pellet.The fitting results indicate that the drying process of artificial magnetite pellet can be described by Correction Page(III)model accurately.Finally,the contrast experiments demonstrate that the fitting model can well describe the actual drying process.

Sauna Technique, Drying Kinetic Modeling and Effectiveness on Solar Drying Compared with Direct Drying in Drying Process of <i>Kappaphycus striatum</i>in Selakan Island Malaysia

A sauna drying technique—the solar drier was designed and imposed, constructed and tested for drying of seaweed. The seaweed moisture content was decreased around 50% in 2-day sauna. Kinetic curves of drying of seaweed were known to be used in this system. The non-linear regression procedure was used to fit three different drying models. The models were compared with experimental data of red seaweed being dried on the daily average of air temperature about 40℃. The fit quality of the models was evaluated using the coefficient of determination (R2), Mean Bias Error (MBE) and Root Mean Square Error (RMSE). The highest values of R2 (0.99027), the lowest MBE (0.00044) and RMSE (0.03039) indicated that the Page model was the best mathematical model to describe the drying behavior of sauna dried seaweed. The percentage of the saved time using this technique was calculated at 57.9% on the average solar radiation of about 500 W/m2 and air flow rate of 0.056 kg/s.

Drying kinetics of soy protein isolate-corn starch film during preparation and its moisture adsorption characteristics during storage

To better understand the mass transfer process of moisture in the soy protein isolate-corn starch(SPI-CS)films during preparation and storage process,the drying kinetics model of SPI-CS films with different formation conditions during the drying process and the moisture adsorption characteristics of the SPI-CS films under different humidity conditions were investigated.Within the range of experimental conditions,the moisture migration rule in the SPI-CS films during the drying preparation was combined with the Page model which was expressed as MR=exp(-kt^(n)).It was found that the adsorption equilibrium needed shorter time(about 3 h)when the SPI-CS films existed in the environment with lower humidity(RH<54%).Additionally,the secondorder adsorption kinetic equation was successful to describe the moisture adsorption characteristic of the SPICS films during storage under different humidity conditions.

Performance Analysis and Drying Kinetics of Maize in an AflaSTOP Dryer

The performance of an AflaSTOP dryer which utilises biomass energy for drying maize was investigated. The drying behaviour of maize grains in the dryer was also investigated using ten (10) thin-layer mathematical models. The models were compared based on coefficient of determination (R2) and Root Mean Square Error (RMSE) values between experimental and predicted moisture ratios. At an average drying air temperature of 50°C and drying air velocity of 2.5 m/s, maize at average moisture content (MC) of 17.5% (wb) was dried to an average MC of 11.5% (wb) in three (3) hours. The drying and thermal efficiency were calculated as 81.1% and 29.6% respectively. Overall, drying took place in the falling rate period. The Logistics model was best to describe the thin-layer drying kinetics of maize in the dryer with R2 value of 0.9902 and RMSE value of 0.04908.

Kinetic Models for Drying Techniques—Food Materials

Drying operations can help in reducing the moisture content of food materials for avoidance of microbial growth and deterioration, for shelf life elongation, to minimize packaging and improving storage for easy transportation. Thin-layer drying of materials is necessary to understand the fundamental transport mechanism and a prerequisite to successfully simulate or scale up the whole process for optimization or control of the operating conditions. Researchers have shown that to rely solely on experimental drying practices without mathematical considerations for the drying kinetics, can significantly affect the efficiency of dryers, increase the cost of production, and reduce the quality of the dried product. An effective model is necessary for the process design, optimization, energy integration and control;hence, the use of mathematical models in finding the drying kinetics of agricultural products is very important. The statistical criteria in use for the evaluation of the best model(s) has it that coefficient of determination (R2) has to be close to unity while the rest statistical measures will have values tending to zero. In this work, the essence of drying using thin-layer, general approaches to modeling for food drying mechanisms thin layer drying models and optimization of the drying processes have been discussed.

Modeling the Drying Kinetics of Earth Bricks Stabilized with Cassava Flour Gel and Amylopectin

Earth bricks could contribute to alleviate the housing shortage in the world, thanks to their low cost, easy production, and low environmental impact. However, to manufacture bricks with required properties, many raw soils must be ameliorated. In Central and Eastern Africa, the waste water of the cassava processing is used to improve earth brick mechanical properties. This technique is interesting, because it is sustainable, low-cost and easy to implement. But, studies on this stabilization method are scarce, in particular on the drying kinetics of these bricks. Now, it is important to know the drying duration, because the earth brick’s strength is strongly correlated to its moisture content. Thus, this study aims to quantify and to model the effect of adding cassava flour gel and amylopectin on the drying kinetics of earth bricks. Depending on the soil nature, the drying duration decreases from 7% to 25% for a stabilizer content of 20%. For the five models used, the coefficient of determination is superior to 0.997 and the chi square is inferior to 3 × 10&#8722;4. In average, the best model is Khazaei, followed in order by Avrami-Page, diffusion, Yong and Peleg. The effective coefficient of diffusion of water is about 4 × 10&#8722;5 m&#8901;s&#8722;2. The parameter T of the Khazaei’s model is strongly correlated to the drying duration and the stabilizer content, and their relationships have been deduced.

Effect of different drying methods on the amino acids,α-dicarbonyls and volatile compounds of rape bee pollen

The significant demand for high quality food has motivated us to adopt appropriate processing methods to improve the food nutritional quality and flavors.In this study,the effects of five drying methods,namely,pulsed vacuum drying(PVD),freeze drying(FD),infrared drying(IRD),hot-air drying(HAD)and sun drying(SD)on free amino acids(FAAs),α-dicarbonyl compounds(α-DCs)and volatile compounds(VOCs)in rape bee pollen(RBP)were determined.The results showed that FD significantly released the essential amino acids(EAAs)compared with fresh samples while SD caused the highest loss.Glucosone was the dominantα-DCs in RBP and the highest loss was observed after PVD.Aldehydes were the dominant volatiles of RBP and SD samples contained more new volatile substances(especially aldehydes)than the other four drying methods.Comprehensively,FD and PVD would be potential methods to effectively reduce the quality deterioration of RBP in the drying process.

Asymmetric Drying and Wetting Trends in Eastern and Western China

As an important factor that directly affects agricultural production, the social economy, and policy implementation,observed changes in dry/wet conditions have become a matter of widespread concern. However, previous research has mainly focused on the long-term linear changes of dry/wet conditions, while the detection and evolution of the non-linear trends related to dry/wet changes have received less attention. The non-linear trends of the annual aridity index, obtained by the Ensemble Empirical Mode Decomposition(EEMD) method, reveal that changes in dry/wet conditions in China are asymmetric and can be characterized by contrasting features in both time and space in China. Spatially, most areas in western China have experienced transitions from drying to wetting, while opposite changes have occurred in most areas of eastern China. Temporally, the transitions occurred earlier in western China compared to eastern China. Research into the asymmetric spatial characteristics of dry/wet conditions compensates for the inadequacies of previous studies, which focused solely on temporal evolution;at the same time, it remedies the inadequacies of traditional research on linear trends over centennial timescales. Analyzing the non-linear trend also provides for a more comprehensive understanding of the drying/wetting changes in China.

Artificial neural network techniques to predict the moisture ratio content during hot air drying and vacuum drying of Radix isatidis extract

Background:To predict the moisture ratio of Radix isatidis extract during drying.Methods:Artificial neural networks were designed using the MATLAB neural network toolbox to produce a moisture ratio prediction model of Radix isatidis extract during hot air drying and vacuum drying,where regression values and mean squared error were used as evaluation indexes to optimize the number of hidden layer nodes and determine the topological structure of artificial neural networks model.In addition,the drying curves for the different drying parameters were analyzed.Results:The optimal topological structure of the moisture ratio prediction model for hot air drying and vacuum drying of Radix isatidis extract were“4-9-1”and“5-9-1”respectively,and the regression values between the predicted value and the experimental value is close to 1.This indicates that it has a high prediction accuracy.The moisture ratio gradually decreases with an increase in the drying time,reducing the loading,initial moisture content,increasing the temperature,and pressure can shorten the drying time and improve the drying efficiency.Conclusion:Artificial neural networks technology has the advantages of rapid and accurate prediction,and can provide a theoretical basis and technical support for online prediction during the drying process of the extract.

Research on the Degradation Kinetics Model in the Drying Process of Chinese Herb

Curative compositions such as catolpol in Rehmannia Glutinosa, flavone in Ophiopogon Japonicus and ginsenoside Re in Panax Ginseng in Chinese herbs were measured as the experimental indices by the method of high performance liquid chromatography under different drying conditions. The reaction order and parameters of the degradation kinetics model were determined and the model was verified by experiments. It was indicated that by comparing with the thin drying method, the prospective model could predict the degradation of curative compositions with drying time, temperature and moisture content of herbal materials with enough precision and could be used to simulate the degradation in the drying process of Chinese herb.

Study of Kinetic Characteristics for Drying Rice Husk

Rice husk (biomass fuel) samples have been dried in drying oven and a series of drying curve for illustrating moisture migration of rice husk have been obtained. It is first research for rice husk drying,and it can provide reference of fuel processing for different boilers which require rice husk with various water contents. In this paper,we apply Page equation to reflect the drying process and obtain drying characteristic curve,then analyze the drying law. Kinetic analysis of the results of moisture migration test has been done,after which, effective moisture diffusion coefficient,activation energy and drying kinetic equation of rice husk samples are obtained in test temperature range (80 - 130 ℃) . And these results show specific influence law of temperature for effective moisture diffusion coefficient.

Drying Kinetics of Paper Mill Sludge

Drying experiments of two paper mill sludge were carried using hot air with a temperature range of 50?C - 80?C and an air velocity of 0.96 m/son a laboratory convective dryer. The drying characteristics were discussed and the drying kinetic equation was solved. The dependence of the reaction rate constant on the drying temperature was given by Arrhenius equation, and the activation energies for moisture diffusion in paper mill sludge sample A and B were found to be 21.53 kJ/mol and 15.38 kJ/mol, respectively.