Spatial homogeneity of drying in a batch type food dryer with diagonal air flow design

Amjad, Waseem; Munir, Anjum; Esper, A.; Hensel, Oliver

doi:10.1016/j.jfoodeng.2014.08.003

Cited by 27 publications

(11 citation statements)

References 12 publications

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“…The simulated results of airflow and experimental value were found a good agreement in terms of coefficient of correlation, i.e. 87.09% for airflow distribution [12].…”

Section: Cfd Simulationsupporting

confidence: 56%

Applications of software in solar drying systems: A review

Chauhan

Kumar

Tekasakul

2015

Renewable and Sustainable Energy Reviews

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“…The simulated results of airflow and experimental value were found a good agreement in terms of coefficient of correlation, i.e. 87.09% for airflow distribution [12].…”

Section: Cfd Simulationsupporting

confidence: 56%

Applications of software in solar drying systems: A review

Chauhan

Kumar

Tekasakul

2015

Renewable and Sustainable Energy Reviews

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“…Normally, in CFD dryer simulations, the results are shown as velocity vectors in different planes of the [5,7,[9][10][11]. For this study, they are represented in terms of the effective viscosity as a measure of the turbulence and thermal conductivity of the fluid.…”

Section: Resultsmentioning

confidence: 99%

“…Many investigations of batch drying have focused on the effects of temperature and the air velocity at the dryer inlet as the main parameters that influence the drying quality, leaving aside the flow uniformity, which may be linked to design variables [7]. However, obtaining products with a uniform moisture content in a tray dryer is not common.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous investigations have begun to use simulation techniques such as computational fluid dynamics (CFD) to evaluate the lack of homogeneity inside the dryers, considerably reducing the experimentation times in the proposed models without increasing the design costs [5,7,[9][10][11]. The CFD technique allows one to simulate and validate the internal behaviour of parameters that are difficult to access for measurement such as the air velocity and turbulence profiles in the drying chamber.…”

Section: Introductionmentioning

confidence: 99%

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Influence of the Thermal Conductivity of Air on the Moisture Homogeneity of a Tray Dryer

Jessica¹,

Felipe²,

José³

et al. 2019

IJHT

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The objective of this study was to identify the incidence of the local thermal conductivity of a fluid in a tray dryer by means of CFD simulation. In the experimental part, identical pieces of mandarin epicarp (Citrus reticulata) were dried at 40 º C at two air inlet velocities (3.5 m/s and 5.5 m/s). For the simulations, equations of energy, continuity and momentum were used, which were solved with ANSYS software (Student v.19.2). The simulations showed spatial variations in the eddy viscosity and thermal conductivity of the air generated in the dryer, where higher experimental moisture values correspond to lower values of the eddy viscosity (<0.0001 P×s) and thermal conductivity (<0.45 W/ m 2 ×K). Therefore, this study proposes that in the design of tray dryers, the drying kinetics should be reported in values of the effective thermal conductivity, which must be homogeneous to ensure homogeneity in the product

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“…These rays are then absorbed by atmospheric gases, such as carbon dioxide, methane, nitrous oxide, and water vapor. Infrared rays that are held by atmospheric gases increase the temperature of the earth's surface, an event known as the greenhouse effect [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Heat Transfer Coefficient in Solar Greenhouse Type Drying Systems

Çerçi

Daş

2019

Sustainability

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As a sustainable energy source, solar energy is used in many applications. A greenhouse type dryer, which is a food drying system, directly benefits from solar energy. Convective heat transfer coefficient (hc) is an important parameter in food drying systems, in terms of system design and performance. Many parameters and equations are used to determine hc. However, as it is difficult to manually process and analyze large amounts of data and different formulations, machine learning algorithms are preferred. In this study, natural and forced convective solar greenhouse type dryers were designed. In a solar greenhouse type dryer, grape is dried in natural (GDNC) and forced convection (GDFC). For convective heat transfer coefficient (hc), predictive models were created using a multilayer perceptron (MLP)—which has many uses in drying applications, as mentioned in the literature—and decision tree (DT), which has not been used before in food drying applications. The machine learning algorithms and results of the estimated models are compared in this study. Error analyses were performed to determine the accuracy rates of the obtained models. As a result, the hc value of the dried grape product in a natural convective solar greenhouse type dryer was 11.3% higher than that of the forced type. The DT algorithm was found to be a more successful model than the MLP algorithm in estimating hc values in HDFC according to Root Mean Square Error. (RMSE = 0.0903). On the contrary, the MLP algorithm was more successful than the DT algorithm in estimating hc values in GDNC (RMSE = 0.0815).

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Spatial homogeneity of drying in a batch type food dryer with diagonal air flow design

Cited by 27 publications

References 12 publications

Applications of software in solar drying systems: A review

Applications of software in solar drying systems: A review

Influence of the Thermal Conductivity of Air on the Moisture Homogeneity of a Tray Dryer

Modeling of Heat Transfer Coefficient in Solar Greenhouse Type Drying Systems

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