Effect of IR intensity and air temperature on exergy and energy at hybrid infrared-hot air dryer

Jafari, Hassan; Hashemi, Jafar

doi:10.2298/ciceq170123015m

Cited by 23 publications

(15 citation statements)

References 27 publications

(42 reference statements)

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“…Since at the final stage of the process, the initial moisture content of the material was below the critical moisture content, the effect of external variables was of reduced importance as the drying rate was governed by the rate of internal moisture movement. The same results were true for the drying of mushroom slices, [48] dog-rose, [51] Kodo millet grains and Fenugreek seeds, [43] and potato cubes. [28] 3.8.…”

Section: Relationship Between Energy and Exergysupporting

confidence: 68%

Drying of organic blackberry in combined hot air-infrared dryer with ultrasound pretreatment

et al. 2020

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In this study, prediction and analysis of energy and exergy in a combined hot air-infrared dryer with ultrasound pretreatment for organic blackberry was carried out. The effect on product color and greenhouse gas (GHG) emission was assessed. To predict energy and exergy parameters such as energy utilization ratio, energy utilization, exergy loss, and exergy efficiency, both the artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) methods were employed. Drying experiments were undertaken at three temperature levels of 50, 60, and 70 C in air speed of 1 m/s and ultrasound pretreatment time 15, 30, and 45 min, as compared to controlled samples (without pretreatment). Results demonstrated that by raising the inlet air temperature and ultrasound pretreatment time, color change rate decreased, while energy utilization and exergy efficiency increased. Energy and exergy prediction results by means of ANN and ANFIS methods showed that ANFIS method achieved a higher R2 and lower RMS as compared to ANN. The highest level of GHG emission (NO x , CO 2 ) was obtained at 50 C temperature for samples without pretreatment.

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Section: Relationship Between Energy and Exergysupporting

confidence: 68%

Drying of organic blackberry in combined hot air-infrared dryer with ultrasound pretreatment

et al. 2020

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“…The total specific energy consumption for convection dryer at different air temperatures and velocity levels was obtained using Equation 9 (Motevali, Jafari, & Hashemi, 2018; Onwude, Hashim, Abdan, Janius, & Chen, ):

{SEC}_{con} = \frac{(A \times v \times C_{pa} \times ρ_{normala} \times Δ T \times t)}{m_{v_{con}}}

where, ρ a was calculated using other researchers (Motevali et al, ):

ρ_{a} = \frac{101.325}{0.287 T}

where, SEC con is specific energy consumption for convection (kW hr/kg), A is cross‐sectional area of the sample tray (m 2 ), v is air velocity (m/s), ρ a is density of air (kg/m 3 ), C pa is the specific heat capacity of air (i.e., 1.00504 kJ/kg K) (Onwude et al, ), Δ T is the temperature difference between drying air and ambient air, t is the drying time (hr),

m_{v_{con}}

is total moisture removed by drying (kg).…”

Section: Methodsmentioning

confidence: 99%

Section: Determination Of Specific Energy Consumptionmentioning

confidence: 99%

The effect of ultrasound pre‐treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network

Kaveh

Jahanbakhshi

Abbaspour‐Gilandeh

et al. 2018

J Food Process Engineering

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In this study, different drying conditions were investigated on quality and thermodynamic properties of almond kernel. Experiments were performed using a convection dryer with ultrasound pretreatment in 40, 50, 60, and 70 °C air temperature, 1 m/s air velocity, and duration of ultrasonic pre‐treatment of 0 min (for control sample), 10, 20, and 40 min. The drying kinetic of the almond kernel was estimated by 15 mathematical models. Furthermore, Artificial Neural Networks (ANNs) and Adaptive Neuro‐Fuzzy Inference Systems (ANFIS) were applied to fit the experimental data on the thin layer drying. The lowest and highest values of the effective moisture diffusivity (Deff) was 1.81 × 10−9 and 9.70 × 10−9 m2/s, respectively. Activation energy (Ea) of the samples was obtained between 26.35 and 36.44 kJ/mol. The highest and lowest values of specific energy consumption (SEC) were calculated 561.72 and 169.88 kW hr/kg, respectively. Maximum (13.14%) and the minimum (7.1%) values of shrinkage were achieved at air temperatures of 70 and 40 °C, respectively. The color changing of dried samples was obtained between 9.14 and 17.96. Furthermore, results revealed that the ANFIS model had the high ability to predict the moisture ratio (R2 = 0.9998 and MSE = 0.0003) during drying. As a result, ANFIS model has the highest ability to evaluate all output as compared with other models and ANNs method. Practical applications Algorithms are modern methods that have been successfully applied to solve the various problems and modeling in engineering and science. Drying is one of the oldest procedures to preserve the food quality. Reduction of moisture content to a certain value can be caused to decay and minimize the microbiological activity and deteriorating chemical reactions in agricultural products, respectively. Determination of almond drying process under convective with ultrasound pre‐treatment dryer in terms of desirable thermal properties (effective moisture diffusivity and energy consumption) provides the high‐quality products. Furthermore, this research can be able to provide a technical basis for almond drying and the related equipment designing.

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“…The mechanical energy consumed by the blower was obtained using Equation (15) (Motevali, Jafari, & Hashemi, ):

E U_{italicmec} = Δ P . M_{italicair} . t

…”

Section: Methodsmentioning

confidence: 99%

The effect of microwave and convective dryer with ultrasound pre‐treatment on drying and quality properties of walnut kernel

Abbaspour‐Gilandeh

Kaveh

Jahanbakhshi

2019

J Food Process Preserv

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In this study, the drying kinetics of walnuts was investigated including specific energy consumption (SEC), shrinkage, and walnut kernels' color in two dryers, namely ultrasonic‐convection (US‐CON) and ultrasonic‐microwave (US‐MIC). To carry out this study, walnut samples were dried at three MIC powers (270, 450, and 630 W), three input air temperatures (40, 55, and 70°C) and four duration of ultrasonic pre‐treatment (0 min (control sample), 10, 20, and 40 min). Fifteen mathematical models were used to describe the walnuts' moisture ratio. The results showed that the Midilli et al. model was the best model for describing the process of drying walnuts in US‐CON and US‐MIC dryers. Effective moisture diffusivity (Deff) values were calculated to be between 2.77 × 10–9 and 5.56 × 10–9 m2/s for the US‐CON dryer and 3.12 × 10–9 to 8.99 × 10–9 m2/s for the US‐MIC dryer. The lowest rates of color change were observed in the US‐MIC dryer at the lowest microwave power and the lowest duration of ultrasonic pre‐treatment. The lowest SEC for the US‐CON dryer was 19.52 kWh/kg, and it was 15.90 kWh/kg for the US‐MIC dryer. The highest rate of shrinkage was 14.21%, which was seen in the US‐CON dryer at the air temperature of 70°C and the duration of ultrasonic pre‐treatment of 40 min. According to the results, the best quality of walnut with the lowest changes of color and shrinkage in the microwave dryer was calculated at microwave power 270 W and control sample. Practical applications Drying foods and agricultural products using microwave dryers is a relatively cheap method and has attracted the attention of many researchers today. Also, numerous studies have been conducted on drying agricultural products through microwave and convection dryers with ultrasound pre‐treatment. The result of this study could be applied for gathering comprehensive information regarding the drying process (kinetic, Deff, Ea, and SEC) as well as the qualitative properties (color and shrinkage) of walnut kernels dried using the microwave and convective hot air dryers accompanied by ultrasound pre‐treatment.

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Effect of IR intensity and air temperature on exergy and energy at hybrid infrared-hot air dryer

Abstract: Article Highlights • Increasing IR radiation intensity caused improvement in energy and exergy efficiencies • Highest energy and exergy efficiency values were 13.50 and 62.26%, respectively • The lowest energy and exergy efficiencies were 3.95% and 20.37%, respectively

Cited by 23 publications

References 27 publications

Drying of organic blackberry in combined hot air-infrared dryer with ultrasound pretreatment

Drying of organic blackberry in combined hot air-infrared dryer with ultrasound pretreatment

The effect of ultrasound pre‐treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network

The effect of microwave and convective dryer with ultrasound pre‐treatment on drying and quality properties of walnut kernel

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