Experimental investigations and modeling of vacuum oven process using several semi-empirical models and a fuzzy model of
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ORIGINAL
Experimental investigations and modeling of vacuum oven process using several semi-empirical models and a fuzzy model of cocoa beans S. M. Atiqure Rahman 1
&
Ahmed M. Nassef 2,3 & Hegazy Rezk 2,4 & Mamdouh El Haj Assad 1 & Md Enamul Hoque 5
Received: 16 December 2019 / Accepted: 10 August 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract An experimental study combined with a mathematical modeling of vacuum drying of cocoa beans was carried out to enhance the drying kinetics without compromising the quality of dried products. Experiments were conducted to compare the effects of variation of temperature and pressure on the drying process. The temperature was varied between 40 and 60 °C, while the pressure between 735 and 245 mmHg. The experimental study investigated and analyzed the effects of various process parameters on drying kinetics and quality (in terms of color and pH value). Results demonstrated that the cocoa beans dried at 50 °C temperature and 735 mmHg pressure had the highest drying kinetics, lowest acidity, and best color among all the temperature and pressure values. Compared to convective drying conducted at 60 °C temperature and atmospheric pressure (760 mmHg), vacuum oven drying consistently showed better drying performance with a higher quality of dried products. Modeling for vacuum drying kinetics of cocoa beans was performed with semi-theoretical drying kinetic and fuzzy models to verify the experimental results. The graphical representations of the results demonstrated a good fit between the fuzzy model and the experimental data compared with semi-theoretical drying kinetic models. Finally, a suitable model was proposed for optimum drying conditions compared with the fuzzy and drying kinetic models that could play an important role in designing future advanced dryers. Keywords Vacuum drying . Cocoa beans . Drying kinetics . Quality parameters . Fuzzy modeling
Nomenclature Deff Effective moisture diffusivity, m2/s g Constant in the two term and Verma et al. models, s−1 * S. M. Atiqure Rahman [email protected] 1
Department of Sustainable and Renewable Energy Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates
2
College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj, Kingdom of Saudi Arabia
3
Computers and Automatic Control Engineering Department, Faculty of Engineering, Tanta University, Tanta, Egypt
4
Electrical Engineering Department, Faculty of Engineering, Minia University, Minya, Egypt
5
Department of Biomedical Engineering, Military Institute of Science and Technology (MIST), Mirpur Cantonment, Dhaka 1206, Bangladesh
g k k K L, a, b L*, a*, b* mt mds Me M0 Mt MR pH P R2
Constant in the C.L. Hii model, s−1 Constant in the Newton, Henderson and Pabis, logarithmic, two term, and Verma et al. models, s−1 Constant in the page and C.L. Hii models, s−n Thermal diffusivity, m2/s Reference color (lightness, redness and yellowness, respectively), Target color (lightness, redness and
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