Experimental Investigation and Neural network based parametric prediction in a multistage reciprocating humidifier

Salins, Sampath Suranjan and Reddy, Kota S V and Kumar, Shiva (2021) Experimental Investigation and Neural network based parametric prediction in a multistage reciprocating humidifier. Applied Energy, 293. ISSN 0306-2619

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Cooling of the buildings is very much mandatory in summer and to meet this, considerable energy will be spent for cooling purpose across the world. Present work focuses on the multistage evaporative cooling pads where four different packing are used to analyze the different humidification output parameters. Cam shaft which is powered by the motor gives reciprocating motion to the cooling pads which is made to dip inside the stagnant water. Input operating parameters such as air velocity, cam shaft speed and the number of cooling pads are varied and the output parameters like pressure drop, cooling effect, coefficient of performance, relative humidity drop and energy consumption rate are determined. Results indicated that, there is an increase in COP, pressure drop and the energy consumption rate with the rise in the air velocity. Artificial neural network has been used for predicting the performance parameters of the experimental results. 3-15-4 structured MLP based network is considered and is trained by using trainscg, trainlm and using trainbr networks. Results indicated a good pre�diction capability of ANN techniques with MRE of test data lying below 12%. Trainbr outperformed the other two networks as the correlation coefficient was much higher and MRE was lower for both training as well as test data.

Item Type: Article
Uncontrolled Keywords: Multistage Reciprocating cooling pads Cooling effect Energy consumption Artificial Neural network Mean relative error
Subjects: Engineering > MIT Manipal > Mechanical and Manufacturing
Depositing User: MIT Library
Date Deposited: 27 Sep 2021 04:28
Last Modified: 27 Sep 2021 04:28
URI: http://eprints.manipal.edu/id/eprint/157416

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