Mathematical Modelling, Energy and Exergy Analysis of Tomato Slices in a Mixed Mode Natural Convection Solar Dryer

Arepally, Divyasree; Ravula, Sudharshan Reddy; Malik, Gulshan Kumar; Kamidi, Venkat Reddy

doi:10.9734/csji/2017/34878

Cited by 12 publications

(4 citation statements)

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“…Recently, several studies have been carried out to energy and exergy analysis in the process of drying products such as potato slices in solar dryer (Kesavan, Arjunan, & Vijayan, 2019), turmeric slices in microwave dryer (Surendhar, Sivasubramanian, Vidhyeswari, & Deepanraj, 2019), Kodo millet grains and fenugreek seeds using wall heated fluidized bed dryer (Yogendrasasidhar & Setty, 2018), dogrose flowers with a hybrid infrared-hot air dryer (Motevali, Jafari, & Hashemi, 2018), and tomato slices in a solar dryer (Arepally, Ravula, Malik, & Kamidi, 2017).…”

Section: Introductionmentioning

confidence: 99%

Prediction kinetic, energy and exergy of quince under hot air dryer using ANNs and ANFIS

Abbaspour‐Gilandeh

Jahanbakhshi

Kaveh

2019

Food Science & Nutrition

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This study aimed to predict the drying kinetics, energy utilization (E u ), energy utilization ratio (EUR), exergy loss, and exergy efficiency of quince slice in a hot air (HA) dryer using artificial neural networks and ANFIS. The experiments were performed at air temperatures of 50, 60, and 70°C and air velocities of 0.6, 1.2, and 1.8 m/s. The thermal parameters were determined using thermodynamic relations. Increasing air temperature and air velocity increased the effective moisture diffusivity (D eff ), E u , EUR, exergy efficiency, and exergy loss. The value of the D eff was varied from 4.19 × 10 -10 to 1.18 × 10 -9 m 2 /s. The highest value E u , EUR, and exergy loss and exergy efficiency were calculated 0.0694 kJ/s, 0.882, 0.044 kJ/s, and 0.879, respectively. Midilli et al. model, ANNs, and ANFIS model, with a determination coefficient (R 2 ) of .9992, .9993, and .9997, provided the best performance for predicting the moisture ratio of quince fruit. Also, the ANFIS model, in comparison with the artificial neural networks model, was better able to predict E u , EUR, exergy efficiency, and exergy loss, with R 2 of .9989, .9988, .9986, and .9978, respectively. K E Y W O R D S adaptive neuro-fuzzy inference system, artificial neural networks, drying, quince, thermodynamic parameters | 595 ABBASPOUR-GILANDEH Et AL.focusing on energy and exergy analysis is very important (Lingayat, Chandramohan, & Raju, 2018;Yogendrasasidhar & Setty, 2018).Şevik, Aktaş, Dolgun, Arslan, and Tuncer (2019) analyzed the exergy and energy in the process of drying mint and apple slices in a solar and solar-infrared. The results indicated that the loss of exergy and exergy efficiency increases by increasing the air temperature. Exergy efficiency for mint in solar dryer and solar-infrared was 69.35% and 59. 07%, respectively. Akpinar, Midilli, and Bicer (2006) analyzed the energy and exergy in pumpkin. They reported that the pumpkin dried within the time range of 5.66-12 hr with a loss of exergy from 0 to 1.165 kJ/s. The maximum exergy of the system input was 2.198 kJ/s. Also, with increased exergy loss, the energy used in the solar dryer increased. Karthikeyan and Murugavelh (2018) studied the energy and exergy required to dry turmeric in a mixed-mode forced convection solar tunnel dryer and concluded that the loss of exergy and energy utilization ratio and its efficiency was increased with increasing temperature.

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Section: Introductionmentioning

confidence: 99%

Prediction kinetic, energy and exergy of quince under hot air dryer using ANNs and ANFIS

Abbaspour‐Gilandeh

Jahanbakhshi

Kaveh

2019

Food Science & Nutrition

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“…The increase in exergy in the early stages of drying may not be rapid because the drying was done under constant radiation intensity of the solar simulator. However, Arepally, Ravula, Malik, and Kamidi (2017) found a sharp increase in exergy efficiency during the first half of the day and a sharp decline during the second half of the day in the drying of tomato slices in a mixed mode natural convection solar dryer. The variation of the exergy efficiency followed the changes in the solar radiation intensity.…”

Section: Figure 5 Energy and Exergy Efficiencies Of The Solar Collectormentioning

confidence: 92%

Energy and Exergy Analysis of an Indirect-Mode Natural Convection Solar Dryer for Maize

Simate¹

2021

EER

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The energy and exergy analysis of an indirect-mode natural convection solar dryer for maize grain is presented. Two different sizes of maize grain bed depths of 0.04 m and 0.02 m translating into grain loads of 10 kg and 5 kg respectively, are used in the study to determine their effects on the collector energy and exergy efficiencies and the drying chamber exergy efficiency. Experiments were carried out using an indirect-mode laboratory solar dryer under a solar simulator with a radiation setting of 634.78 W/m2. The analysis gave average collector energy efficiencies of 33.3 % and 46.2 % for the 10 kg and 5 kg loads, respectively, which are higher than the collector exergy efficiencies of 2.4 % and 2.6 % for the 10 kg and 5 kg loads, respectively. The drying chamber exergy efficiencies are 45.2 % and 28.4 % for the 10 kg and 5 kg loads, respectively. In view of this, the 5 kg load is considered to be more efficient at extracting energy from the collector due to higher air flow resulting from its relatively thin grain bed depth of 0.02 m, but less efficient in utilising the extracted energy to evaporate moisture from the grain which has resulted in a lower drying chamber exergy efficiency. Further, the exergy loss in the drying chamber for the 5 kg load is higher than that in the 10 kg load as 72.3 % of the exergy entering the drying chamber is lost through emissions as well as destroyed through internal irreversibility compared to 57.0 % for the 10 kg load. 

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“…Perolehan data pada penelitian ini berdasarkan penelitian dan pengembalian data secara empiris dengan mengacu pada kaidah metode yang baku dengan acuan perolehan data dari beberapa variable yang digunakan sebagai nilai pembanding dalam statistik [8]. Variable juga dapat disebut sebagai atribut dari bidang keilmuan maupun kegiatan tertentu oleh karenanya disebut variable karena ada variasinya.…”

Section: Metode Pengolahan Dataunclassified

Optimasi Daya Pompa Pendingin Air Radiator Pada Genset 1500 Kva Type 4 Turbo Rocharged Intercooled Dengan Beban 1100 Kw

Kuswara¹,

Iskendar

2021

teknobiz

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Pendinginan pada motor sangat dibutuhkan, karena tanpa pendinginan mesin dan komponen – komponennya akan mengalami over heating, sehingga menimbulkan panas dan mengakibatkan kerusakan berupa keausan yang akhirnya umur mesin dan komponen – komponennya tidak tahan lama. Permasalahan yang menjadi fokus, fungsi tekanan pompa air pendingin radiator pada genset 1500 KVA type 4 cycle Turbo rocharged Intercooled dengan beban 1100 KW, agar disaat menerima beban 90% tidak terjadi trip bertujuan juga dari pembahasan sistem pendingin ini adalah untuk mengetahui, memahami cara mengindentifikasi sistem tekanan pompa pendingin. Gangguan yang sering terjadi pada sistem tekanan pompa pendingin air radiator adalah kebocoran, gangguan dan kotoran yang mengendap sehingga aliran air tidak maksimal. Analisa gangguan diperlukan untuk mengetahui yang terjadi saat genset menerima beban 1100 KW dan temperatur diatas 90°C mesin genset memiliki toleransi temperatur kerja, dalam batas suhu itu mesin dapat bekerja secara optimal sehinnga juga ke bahan bakar yamng ideal. Agar jangan sampai terjadi Overhead dalam hitungan detik.

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Mathematical Modelling, Energy and Exergy Analysis of Tomato Slices in a Mixed Mode Natural Convection Solar Dryer

Cited by 12 publications

References 0 publications

Prediction kinetic, energy and exergy of quince under hot air dryer using ANNs and ANFIS

Prediction kinetic, energy and exergy of quince under hot air dryer using ANNs and ANFIS

Energy and Exergy Analysis of an Indirect-Mode Natural Convection Solar Dryer for Maize

Optimasi Daya Pompa Pendingin Air Radiator Pada Genset 1500 Kva Type 4 Turbo Rocharged Intercooled Dengan Beban 1100 Kw

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