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Heat Transfer Research
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Heat Transfer Research

DOI: 10.1615/HeatTransRes.2015007463
pages 923-935

PREDICTION OF THE RATE OF MOISTURE EVAPORATION FROM JAGGERY IN GREENHOUSE DRYING USING THE FUZZY LOGIC

Om Prakash
Department of Mechanical Engineering, Birla Institute of Technology, Mesra Ranchi-835215, India
Anil Kumar
Energy Technology Research Center, Department of Mechanical Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand; Department of Energy (Energy Center), Maulana Azad National Institute of Technology, Bhopal-462003, India
Ajay Kumar Kaviti
Department of Mechanical Engineering, Sagar Institute of Science and Technology, Gandhinagar, Bhopal, M.P., India
P. Vishwanath Kumar
Institute of Fronter Materials, Deakin University, Waurn Campus, 3216 Australia

RÉSUMÉ

In this study an attempt has been made to predict the rate of moisture evaporation by natural and forced convection from jaggery in a controlled environment. For this purpose, we have adopted simulating software called Fuzzy logic in MATLAB software (Version 7.0.1). Initially the input values from the literature, namely the jaggery temperature (Tj), surface temperature (Te), and the relative humidity (RH), were taken corresponding to different jaggery dimensions (0.03 × 0.03 × 0.01 m3, 0.03 × 0.03 × 0.02 m3, and 0.03 × 0.03 × 0.03 m3) with a total quantity of jaggery of a (0.75 kg and 2.0 kg) that are fed in the software tool box and the output values of moisture evaporation (me) were predicted. These values were compared with the experimental values and it was seen that there is close accuracy between the values. The results from this investigation indicate that the Fuzzy tool predicts the moisture evaporation rate with an absolute error varying from no error in the case of a jaggery piece of dimensions 0.03 × 0.03 × 0.01 m3 to a maximum error of 0.27 for a jaggery piece of 2 kg and of dimensions 0.03 × 0.03 × 0.02 m3 in the forced convection mode. The values of root mean square error and coefficient of determination are calculated and they are found to be 0.112 and 0.986, respectively. Thus it is concluded that the Fuzzy logic can be used to accurately predict the results with a minimum error and the present model can be extended to different places corresponding to different weather conditions, namely ambient temperature, solar radiation, and relative humidity.


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