Dimensionless Moisture Content Research Articles

Methods of calculating the kinetics of drying of natural leather

A method for calculating drying kinetics based on A. V. Lyikov’s kinetics equation and drying rate curves for the drying process of natural leather is presented. Methods of approximating velocity curves to determine the drying time are considered. An equation for calculating the drying time of natural leather with a variable drying factor is presented. Based on the processing of experimental data on drying of natural leathers, equations for calculating heat flux densities, intensity of moisture evaporation and material temperature in the period of falling drying rate are presented. Based on the approximation of drying speed curves for natural leathers, the equations for calculating the drying time by the methods of A. V. Lyikov, V. V. Krasnikov, and N. S. Mikheeva are considered. The dependence of the relative drying rate on the dimensionless moisture content is presented. The reliability of the experimental equations was checked and the calculated values of the drying time and material temperature were compared with the experiment. The proposed approximate methods of calculating the skin drying speed curve make it possible to evaluate the nature of the drying process of a particular material by individual zones of the second period and when changing the drying mode. They also make possible determination of the most important parameters of drying kinetics and reduction of the number of experiments.

Application of Response Surface Methodology based D-optimal Design for Modeling and Optimisation of Osmotic dehydration of Zucchini

The current study aims to optimize the osmotic dehydration parameter of a food product by adjusting the quantities of several osmotic agents. In this study, a cube-shaped Zucchini is utilized as an example food product. Maltose, fructose, lactose, and fructo-oligosaccharide (FOS) were used as osmotic agents at varying concentrations (30%, 40%, and 50%) at a temperature of 26 °C. The Dimensionless moisture content (DMC), Water loss (WL), and Solid gain (SG) were chosen as performance parameters. Using the dataset collected from the experiments, the D-optimal approach-based design was used for the design of the experiment (DoE). The response surface methodology (RSM) and analysis of variance (ANOVA) were used for each osmotic agent to build prediction models in the form of simple mathematical expressions. The resulting prognostic model was evaluated using several regression and error indices. The model's regression coefficients were admirable, with R ranging from 0.988 to 0.9938 and R2 ranging from 0.9761 to 0.9878. As assessed by mean squared error, the predicted error varied from 0.001 to 0.0415. The D-optimal and RSM-based prognostic model is demonstrated as a robust prognostic model due to improved regression indices and fewer model errors. The desirability technique was employed for parametric optimization to achieve the best outcomes. Lactose yielded the best water loss of 5.88 g/g idm, a good solid gain of 0.872 g/g idm, and dimensionless moisture content of 0.704 g/g idm.

Investigation of Heat and Mass Transfer in the Processes of Heat Treatment and Drying of Thermal Insulation Materials

The results of the study of heat and mass transfer in the processes of heat treatment and drying processes of thermal insulating materials when the values of the Biot heat exchange criterion are less than one and the main factor is the interaction of the evaporation surface of the material with the environment (external problem) are presented. It was assumed that at low temperature gradients over the cross section of a wet body, thermal transfer of matter can be neglected, and phase transformations are absent (Posnov's criterion is equal to zero). By processing the experimental data on convective heat treatment of materials carried out by the least squares method, experimental equations for calculating the kinetics of drying have been obtained. Equations are given for determining the duration of drying, material temperature, heat flux density. On the basis of the theory of regular thermal regime, equations for the rate of heating of a solid and the rate of decrease in moisture content have been obtained. The verification of the reliability of the obtained equations and comparison of the calculated values of the parameters with the experimental ones are presented. An experimental dependence of the relative drying rate on the dimensionless moisture content has been established. The dependence of the generalized drying time on the relative moisture content is given. Also, based on the analysis of the experimental data on the thermal conductivity coefficients for wet thermal insulation materials, the dependences of the thermal conductivity coefficients on moisture content and temperature have been established. As a result of solving the criterion heat transfer equation, the values of the heat transfer coefficients for the period of the decreasing drying rate are obtained. The values of the Biot criterion in the processes of drying porous ceramics and asbestos are determined, too. It has been determined that the ratio of the moisture content loss rate to the drying rate in the first period does not depend on the drying mode and is a function of the initial moisture content.

Predicting Drying Performance of Osmotically Treated Heat Sensitive Products Using Artificial Intelligence

The main goal of this research is to develop and apply a robust Artificial Neural Networks (ANNs) model for predicting the characteristics of the osmotically drying treated potato and apple samples as a model heat-sensitive product in vacuum contact dryer. Concentrated salt and sugar solutions were used as the osmotic solutions at 27C. Series of experiments were performed at various temperatures of 35C, 40C, and 55C for conduction heat input under vacuum ( −760 mm Hg) condition. Some experiments were also performed in a pure vacuum without heat addition. Dimensionless moisture content (DMC), effective moisture diffusivity, and mass flux were considered as the performance parameters in this study. Results revealed that the osmotic dehydration using a concentrated sugar solution shows a higher reduction in the initial moisture loss of 19.87% compared to 5.3% in the salt solution. Furthermore, a significant enhancement of drying performance of about 27% in DMC was observed for both samples at vacuum and 40C compared to pure vacuum drying conditions. Using the experimental data, a robust artificial neural network (ANN) was proposed to describe the osmotic dehydration’s behavior on the drying process. The ANN model outputs are the dimensionless moisture contents (DMC), the diffusivity, and the mass flux. Whereas the ANN inputs were the drying time, the percent of sugar solution, and the percent of salt solution. For the ANN apple’s model, the minimum root mean square error (RMSE) values were 0.0261, 0.0349 and 0.0406, for DMC, diffusivity, and mass flux, respectively. Whereas the best correlation coefficients of the above three parameters’ determination values were 0.9909, 0.9867 and 0.9744, respectively. For the ANN potato’s model, the minimum RMSE values were 0.0124, 0.0140 and 0.0333, for DMC, diffusivity, and mass flux, respectively. And the best correlation coefficients of the parameters’ values were found 0.9969, 0.9968 and 0.9736, respectively. Accordingly, the ANN model’s prediction has a perfect agreement with the experimental dataset, which confirmed the ANN model’s accuracy.

Investigation of Mass Transfer with Different Models in a Solar Energy Food-Drying System

In drying systems, the examination of the drying rate values of the food product in advance gives important information about the raw material to be dried. In this study, thin-layer drying behavior of apple slices in a convective solar dryer was investigated. The experiments were carried out at a drying air temperature of 46–63 °C and a drying air speed of 0.7–1.8 m/s. In order to determine the drying kinetics, the mass change of apple slices was recorded under all drying air conditions. The effects of drying air temperature and speed, drying speed of apple slices, dimensionless moisture content, were investigated. In a solar drying system, thermal efficiency, solar radiation and air velocity values were measured. The drying kinetics of 15-mm thick apple slices were examined for three days in the solar drying system. Using the decision tree algorithm, which is a machine learning algorithm, a predictive model was created for moisture rate in drying experiments and four linear equations were obtained. According to obtained equations, the collector in the drying system depends on the inlet–outlet temperature values, the drying room inlet–outlet temperature values, the drying room humidity values and air velocity values. Moisture rate data were applied to twelve different models and their performance was determined by root mean square error (RMSE) analysis. The mathematical model with the least error rate was (RMSE: 0.09) Midilli model. A comparison was made between these drying models in the literature and the model generated by the decision tree algorithm. According to the results of RMSE error analysis, it was shown that the model created with the decision tree algorithm predicted the moisture rate values with less error values RMSE: 0.03) than the Midilli model.

Modeling the effect of shrinkage on fluidized bed drying of orthodox broken type tea

Fermented tea particles (dhool) are a polydisperse system subject to shrinkage during fluidized bed drying, which is an important process in the production of orthodox broken type tea. The effect of shrinkage on the physical properties and the minimum fluidization velocity were studied. Five different moisture contents of dhool particles were chosen in the range of 3-106 mass% (dry basis) and the changes in particle diameters and particle densities were measured. For each of the moisture contents, the minimum fluidization velocity was found for three different bed loadings using ambient air at 25?C in a fluidized bed with an area of 351?345 mm2. Since the conventional industrial type fluidized bed dryers operate at 124?C, the new correlations among the Archimedes number, Reynolds number at minimum fluidization and dimensionless moisture content were developed using air properties at 124?C. The results were validated for orthodox broken type tea, drying at 124?C, in a fluidized bed dryer with bed loadings in the range of 44.5 to 50.5 kg/m2. The predicted fluidization velocity was found to be in good agreement with the experimental data and the difference was below 10% for most cases.

Performance and economic analyses on solar-assisted heat pump fluidised bed dryer integrated with biomass furnace for rice drying

This study is concerned with the performance and economic analyses on solar-assisted heat pump fluidised bed dryer integrated with biomass furnace for rice drying. The dryer decreased the moisture content of rice from 32.85% (dry basis) to 16.29% (dry basis) in 22.95 min, with a mass flow rate of 0.1037 kg/s at an average temperature of 80.9 °C and average relative humidity of 8.14%. The specific moisture extraction rate varied from 0.13 kg/kWh to 0.40 kg/kWh, with an average value of 0.24 kg/kWh. The specific energy, specific thermal energy and specific electrical energy consumptions varied in the range of 2.50–2.62, 0.98–3.03 and 0.90–2.78 kWh/kg, with average values of 4.76, 1.86 and 1.71 kWh/kg, respectively. The thermal dryer, pickup and exergy efficiencies varied in the range of 8.4%–25.6%, 23.7%–73.4% and 13.6%–61.8%, with average values of 15.4%, 43.8% and 41.3%, respectively. Improvement potential varied from 223.3 W to 1391.2 W, with an average value of 630.6 W. The payback period of the dryer was approximately 1.6 years. Furthermore, the experimental dimensionless moisture content data fitted well with the Page’s model.

Prediction of moisture transfer parameters for convective drying of shrimp at different pretreatments

Abstract By the analytical model proposed by Dincer and Dost, the mass transfer parameters (moisture transfer coefficient and moisture diffusivity) of shrimp samples were determined. Three sets of drying experiments were performed with three samples of shrimp: without boiling (WB), boiled in salt solution (SB) and boiled in salt solution and subjected to liquid smoking process (SBS). The experiments were performed under controlled conditions of drying air at temperature of 60°C and velocity of 1.5 m/s. Experimental dimensionless moisture content data were used to calculate the drying coefficients and lag factors, which were then incorporated into the analytical model for slab and cylinder shapes. The results showed an adequate fit between the experimental data and the values predicted from the correlation. The boiling is the most recommended pretreatment, because provided a shorter drying time, with high values of moisture transfer coefficient and moisture diffusivity.

The potential of computer vision, optical backscattering parameters and artificial neural network modelling in monitoring the shrinkage of sweet potato (Ipomoea batatas L.) during drying.

Drying is a method used to preserve agricultural crops. During the drying of products with high moisture content, structural changes in shape, volume, area, density and porosity occur. These changes could affect the final quality of dried product and also the effective design of drying equipment. Therefore, this study investigated a novel approach in monitoring and predicting the shrinkage of sweet potato during drying. Drying experiments were conducted at temperatures of 50-70 °C and samples thicknesses of 2-6 mm. The volume and surface area obtained from camera vision, and the perimeter and illuminated area from backscattered optical images were analysed and used to evaluate the shrinkage of sweet potato during drying. The relationship between dimensionless moisture content and shrinkage of sweet potato in terms of volume, surface area, perimeter and illuminated area was found to be linearly correlated. The results also demonstrated that the shrinkage of sweet potato based on computer vision and backscattered optical parameters is affected by the product thickness, drying temperature and drying time. A multilayer perceptron (MLP) artificial neural network with input layer containing three cells, two hidden layers (18 neurons), and five cells for output layer, was used to develop a model that can monitor, control and predict the shrinkage parameters and moisture content of sweet potato slices under different drying conditions. The developed ANN model satisfactorily predicted the shrinkage and dimensionless moisture content of sweet potato with correlation coefficient greater than 0.95. Combined computer vision, laser light backscattering imaging and artificial neural network can be used as a non-destructive, rapid and easily adaptable technique for in-line monitoring, predicting and controlling the shrinkage and moisture changes of food and agricultural crops during drying. © 2017 Society of Chemical Industry.

Quantitative model prediction of the combined effect of moisture content and temperature on purple mudstone decay in south-western China

Rock decay is mainly the result of the combined effects of moisture content and temperature, but little is known about the quantitative relationship between these variables and the rate of rock decay. In this study we develop quantitative calculation models of rock decay rate under laboratory conditions and validate the efficiency of these models by comparing the predicted rock decay mass and that measured for rock exposed in the field. Rainfall and temperature data in the field were standardised to a dimensionless moisture content and temperature variables, respectively, and then the predicted rock decay mass was calculated by the models. The measured rock decay mass was determined by manual sieving. Based on our previously determined relationship between a single factor (moisture content or temperature) and the rate of rock decay in the laboratory, power function models are developed. Results show that the rock decay mass calculated by the model was comparable with field data, with averaged relative errors of 1.53%, 9.00% and 11.82% for the Tuodian group (J3t), Matoushan group (K2m) and Lufeng group (J1l), respectively, which are mainly due to inaccurate transformation of field rainfall into the rock moisture content and artificial disturbance when the samples were sieved in the field. Our results show that the developed models based on laboratory-derived rates can accurately predict the decay rates of mudstones exposed in the field.

Real-time color change monitoring of apple slices using image processing during intermittent microwave convective drying.

An intermittent microwave convective drying method combined with a real-time computer vision technique was employed to detect the effect of drying parameters on color properties of apple slices. The experiments were performed at air temperature of 40 to 80℃, air velocities of 1-2 m/s, microwave powers of 200-600 W, and pulse ratios (PRs) of 2-6. Drying rate and drying time varied from 0.014 to 0.000001 min-1 and 27 to 244 min, respectively. The normalized lightness values had ascending and descending parabolic trends with decrease in product moisture content. With descending dimensionless moisture content, redness, yellowness, color change, hue angle, and chroma were enlarged. The normalized redness values changed from -4 to 3. Models relating drying parameters with drying time, drying rate, and lightness were obtained and found to be significant (P < 0.01). Results indicated that microwave power and PRs had more influence on lightness and color change than other parameters.

Determination of bulk density of Mirabelle plum during hot air drying as influenced by ultrasound-osmotic pretreatment

Prunes are generally produced by drying fresh plums with a stream of hot air. Changes in various quality indicators, such as bulk density of foodstuffs, have substantial impact on the performance of drying processes. Optimization of bulk density is, therefore, a requirement for development and perpetuity of drying technologies. The aim of this study was to investigate the effect of ultrasound-assisted osmotic dehydration pretreatment on bulk density of Mirabelle plum at various operating conditions (sonication time, concentration of osmotic solution and immersion time in the osmotic solution). Results showed that application of ultrasound-assisted osmotic dehydration, compared to control sample, led to a significant (p < 0.05) increase in bulk density from 1.33 to 9.90 %. Experimental data of bulk density variations versus dimensionless moisture content were well fitted to an empirical power model with high R2.

Performance Analysis of Solar Assisted Fluidized Bed Dryer Integrated Biomass Furnace with and without Heat Pump for Drying of Paddy

The performances of a solar assisted fluidized bed dryer integrated biomass furnace (SA-FBDIBF) and a solar assisted heat pump fluidized bed dryer integrated biomass furnace (SAHP-FBDIBF) for drying of paddy have been evaluated, and also drying kinetics of paddy were determined. The SA-FBDIBF and the SAHP-FBDIBF were used to dry paddy from 11 kg with moisture content of 32.85% db to moisture content of 16.29% db (14% wb) under an air mass flow rate of 0.1037 kg/s within 29.73 minutes and 22.95 minutes, with average temperatures and relative humidities of 80.3°C and 80.9°C and 12.28% and 8.14%, respectively. The average drying rate, specific energy consumption, and specific moisture extraction rate were 0.043 kg/minute and 0.050 kg/minute, 5.454 kWh/kg and 4.763 kWh/kg, and 0.204 kg/kWh and 0.241 kg/kWh for SA-FBDIBF and SAHP-FBDIBF, respectively. In SA-FBDIBF and SAHP-FBDIBF, the dryer thermal efficiencies were average values of 12.28% and 15.44%; in addition, the pickup efficiencies were 33.55% and 43.84% on average, whereas the average solar and biomass fractions were 10.9% and 10.6% and 36.6% and 30.4% for SA-FBDIBF and SAHP-FBDIBF, respectively. The drying of paddy occurred in the falling rate period. The experimental dimensionless moisture content data were fitted to three mathematical models. Page’s model was found best to describe the drying behaviour of paddy.

Comparison between continuous and intermittent drying of whole bananas using empirical and diffusion models to describe the processes

Four experiments were carried out with continuous and intermittent drying of whole bananas, using hot air. Three intermittent processes were performed with the same intermittency ratio (1/2), with intermittency times of 0.5, 1.0 and 2.0h. Dimensionless moisture content as a function of the effective operation time was described by empirical and diffusion models. Peleg model enabled to observe that eight hours of continuous drying were equivalent to four hours of discontinuous process with 1h of intermittency. In addition, this model enabled to determine an expression for drying rate and to observe that discontinuous process increase the value of this rate. Diffusion model with boundary of the third kind described well the drying processes and made it possible to realize that the mass transfer Biot number was reduced from 11.5 (continuous) to 0.6 (1h of intermittency), indicating that in the discontinuous case the product is submitted to smaller stresses.

Estimation of whole lemon mass transfer parameters during hot air drying using different modelling methods

To design new dryers or improve existing drying equipments, accurate values of mass transfer parameters is of great importance. In this study, an experimental and theoretical investigation of drying whole lemons was carried out. The whole lemons were dried in a convective hot air dryer at different air temperatures (50, 60 and 75 °C) and a constant air velocity (1 m s−1). In theoretical consideration, three moisture transfer models including Dincer and Dost model, Bi–G correlation approach and conventional solution of Fick’s second law of diffusion were used to determine moisture transfer parameters and predict dimensionless moisture content curves. The predicted results were then compared with the experimental data and the higher degree of prediction accuracy was achieved by the Dincer and Dost model.

Description of Seedless Grape Drying and Determination of Drying Rate

This article compares some empirical models, with one or two parameters, used to describe seedless grape drying at low temperature. Chosen models have, as a common characteristic, an analytical expression for the derivative of dimensionless moisture content with respect to time. Comparison of the results for the simulations of drying kinetics indicates that, despite Page and Silva et alli models well represent the process, the best model is Peleg. For this model, the statistical indicators of the simulation can be considered excellent (the determination coefficient is R2 = 0.99944 and the chi-square is χ2 = 1.2335 x 10-3).

The Impact of Hot Air Drying on the Physical-Chemical Characteristics, Bioactive Compounds and Antioxidant Activity of Acerola (M alphigia emarginata ) Residue

This article evaluates the effect of hot air drying on the physicochemical characteristics, color, concentration of bioactive compounds and antioxidant activity of agroindustrial residue of acerola, which was hot air dried under different conditions of temperature (60, 70 and 80C) and air velocity (4, 5 and 6 m/s), taking up the residue in natura as the control group. The experimental dimensionless moisture content as a function of drying time of acerola residue is also presented and discussed. The retention values of total phenolic (26–31%), carotenoids (50–61%), anthocyanins (23–36%), proanthocyanidins (21%), ascorbic acid (40–70%) and the antioxidant activity measured by 2,2-diphenyl-1-picrylhydrazyl method (20%) were calculated and discussed. Considering the concentration of bioactive compounds detected in the final product, as well as the microbiological stability achieved by the substantial moisture reduction, it can be concluded that the dried acerola residue is an important source of bioactive compounds with appropriate characteristics to be utilized as a health-relevant food ingredient. Practical Applications Brazil is one of the largest agricultural producers in the world. In recent years, the processing industry has developed and as a consequence, the generation of residues has also increased. The search for answers to this technological challenge was the motivation of this research, which evaluated the drying process as means for obtaining a natural functional powder from acerola residue. The data shown would provide the scientific rationale for a better exploitation of this tropical fruit residue.

Determination of convective heat transfer coefficient and specific energy consumption of potato using an ingenious self tracking solar dryer

In the present work, an attempt has been made to experimentally determine the heat transfer properties of potato in terms of convective heat transfer coefficient, specific energy consumption and specific heating rate. Drying experiments with potato cylinders have been performed in an in-house fabricated laboratory scale natural convection indirect solar dryer with self tracking mechanism. The convective heat transfer coefficient of cylindrical potato samples was evaluated by considering the combined effects of heat capacities of food product as well as radiative heat transfer from drying chamber to the food product. This study revealed that the convective heat transfer coefficient for potato cylinders was varying from 11.73 to 16.23 W/m2 °C with an experimental error of 7.86 %. The specific energy consumption was decreasing exponentially with drying time, and the average value was estimated to be 3,491 kJ/kg. It was also observed that the specific heating rate for potato cylinders decrease with dimensionless moisture content.

Application of computer vision technique for on-line monitoring of shrimp color changes during drying

The effects of drying temperature and drying medium velocity on color change kinetics of shrimp viz. lightness (L∗), redness (a∗), yellowness (b∗), total color difference (ΔE), chroma (CH), hue angle (H°), and browning index (BI) were on-lineally investigated. Drying experiments were carried out on dryer equipped with computer vision systems using hot air drying (HAD) temperatures of 50–90°C and superheated steam drying (SSD) temperatures of 110–120°C at drying medium velocities of 1–2m/s. Zero-, first-order, and fractional conversion models were utilized to describe the color changes of shrimps and the fractional conversion model successfully tracked the experimental data. The results showed that the color parameters were significantly influenced by the studied parameters. Lightness of the samples decreased, while other color parameters increased as drying proceeded. Generally, increasing drying medium temperature decreased L∗ and H°, whereas increased other color parameters. The color characteristic of the SSD finished products were acceptable than the HAD processed samples. Finally, dimensionless moisture content of shrimps during drying was accurately correlated to the color parameters and drying time using a quadratic regression model. Moisture ratio had strong relationship with the lightness change compared with the redness and yellowness variations.

Performance evaluation of an enhanced fruit solar dryer using concentrating panels

Concentrating solar panels (CSP) improve the process of solar drying Roma tomatoes. This paper presents a performance comparison between two mixed-mode solar dryers. The dryers were identically constructed, however one of the dryers utilized mobile and easily adjustable flat concentrating solar panels to maximize incident solar energy on the dryer. Temperatures inside the dryer that utilized the concentrating solar panels were approx. 10°C higher than those in the normal dryer during the majority of a sunny day testing period. This increase in temperature led to shorter Roma tomato drying times in the dryer with CSP. The concentrating solar panels showed a considerable increase in drying rate on sunny days, with a 27% decrease in total drying time as compared to the normal dryer to reach the target dimensionless moisture content of 0.2. A less significant increase in drying capacity was achieved when the dryer was tested in simulated cloudy conditions. The faster drying rate achieved in the dryer utilizing solar concentrators, under both sunny and simulated cloudy conditions, demonstrates the ability to dry produce to an acceptable moisture content in a reasonable time, with the objective of reducing postharvest loss and preventing spoilage.