Predicting Parameters of Heat Transfer in a Shell and Tube Heat Exchanger Using Aluminum Oxide Nanofluid with Artificial Neural Network (ANN) and Self-Organizing Map (SOM)

Predicting Parameters of Heat Transfer in a Shell and Tube Heat Exchanger Using Aluminum Oxide Nanofluid with Artificial Neural Network (ANN) and Self-Organizing Map (SOM)

This study is a model of artificial perceptron neural network including three inputs to predict the Nusselt number and energy consumption in the processing of tomato paste in a shell-and-tube heat exchanger with aluminum oxide nanofluid. The Reynolds number in the range of 150–350, temperature in th...

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Bibliographic Details
Main Authors: Amir Zolghadri, Heydar Maddah, Mohammad Hossein Ahmadi, Mohsen Sharifpur
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sustainability
Subjects:
artificial neural network
Nusselt number
mean square error
SOM
Online Access:https://www.mdpi.com/2071-1050/13/16/8824

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