ANN: Prediction of Heat Transfer and Flow Characteristics of a Tube with Modified Twisted Tapes
Abstract
In this paper, we present an Artificial Neural Networks (ANNs) model which is prone to accurately estimate the friction factor and nusselt number of a tube with modified twisted tapes. Numerical analysis were realized using the tapes with six different rates of pitch length of twisted tape to inner diameter of tube (y/D=3, 4, 5) in a range of Reynolds number 8000 to 24000 under uniform heat flux conditions. The ANN model was improved and validated using a databank containing numerical datasets. The back propagation algorithm is recognized to be the most extensive learning method for ANN. This algorithm is used for training and testing of the network. The results of the ANNs were demonstrated superior performance to adapt the numerical datas. Value of the coefficient of multiple determination were obtained. The R2 values were found 0,9994 for nusselt number and 0,9995 for friction factor.
Keywords
References
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Details
Primary Language
Turkish
Subjects
Mechanical Engineering
Journal Section
Research Article
Authors
Aslı Durmuşoğlu
*
0000-0002-2797-1304
Türkiye
Sibel Güneş
0000-0002-8962-3735
Türkiye
Emrah Özaşır
This is me
0000-0003-3780-7644
Türkiye
Publication Date
June 30, 2020
Submission Date
November 21, 2019
Acceptance Date
March 26, 2020
Published in Issue
Year 2020 Volume: 4 Number: 1