Baza Publikacji Pracowników Politechniki Lubelskiej

Status:
Autorzy:	Abbaspour-Gilandeh Yousef, Zadhossein Safoura, Kaveh Mohammad, Szymanek Mariusz, Hassannejad Sahar, Wojciechowska Krystyna
Dyscypliny:
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Rok wydania:	2025
Wersja dokumentu:	Drukowana \| Elektroniczna
Język:	angielski
Numer czasopisma:	3
Wolumen/Tom:	18
Numer artykułu:	696
Strony:	1 - 23
Impact Factor:	3,0
Web of Science® Times Cited:	0
Scopus® Cytowania:	0
Bazy:	Web of Science \| Scopus
Efekt badań statutowych	NIE
Finansowanie:	Opłata 1/6 kwoty ze względu na 6 współautorów. Kwota 400EUR+23%Vat= 492 EUR z wewnętrznego grantu własnego
Materiał konferencyjny:	NIE
Publikacja OA:	TAK
Licencja:
Sposób udostępnienia:	Witryna wydawcy
Wersja tekstu:	Ostateczna wersja opublikowana
Czas opublikowania:	W momencie opublikowania
Data opublikowania w OA:	3 lutego 2025
Abstrakty:	angielski
	Energy consumption in the drying industry has made drying an energy-intensive operation. In this study, the drying time, quality properties (color, shrinkage, water activity and rehydration ratio), specific energy consumption (S.E.C), thermal, energy and exergy efficiency of corn drying using a hybrid dryer convective-infrared-rotary (CV-IR-D) were analyzed. In addition, the energy parameters and exergy efficiency of corn were predicted using the artificial neural network (ANN) technique. The experiments were conducted at three rotary rotation speeds of 4, 8 and 12 rpm, drying temperatures of 45, 55 and 65 °C, and infrared power of 0.25, 0.5 and 0.75 kW. By increasing drying temperature, infrared power and rotary rotation speed, the drying time, S.E.C and water activity decreased while the Deff, energy, thermal and exergy efficiency increased. In addition, the highest values of rehydration ratio and redness (a) and the lowest values of shrinkage, brightness (L), yellowness (b*) and color changes (ΔE) were obtained at an infrared power of 0.5 kW, air temperature of 55 °C and rotation speed of 8 rpm. The range of changes in S.E.C, energy, thermal and exergy efficiency during the corn drying process was 5.05–28.15 MJ/kg, 3.26–29.29%, 5.5–32.33% and 21.22–55.35%. The prediction results using ANNs showed that the R for the drying time, S.E.C, thermal, energy and exergy data were 0.9938, 0.9906, 0.9965, 0.9874 and 0.9893, respectively, indicating a successful prediction.

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Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network

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