Frictional Pressure Drop for Gas− Non-Newtonian Liquid Flow through 90° and 135° Circular Bend: Prediction Using Empirical Correlation and ANN

2012 ◽  
Vol 39 (5) ◽  
pp. 416-437 ◽  
Author(s):  
Nirjhar Bar ◽  
Sudip Kumar Das
Author(s):  
Suman Debnath ◽  
Anirban Banik ◽  
Tarun Kanti Bandyopadhyay ◽  
Mrinmoy Majumder ◽  
Apu Kumar Saha

2014 ◽  
Vol 917 ◽  
pp. 244-256 ◽  
Author(s):  
Nirjhar Bar ◽  
Sudip Kumar Das

This paper is an attempt to compare the the performance of the three different Multilayer Perceptron training algorithms namely Backpropagation, Scaled Conjugate Gradient and Levenberg-Marquardt for the prediction of the gas hold up and frictional pressure drop across the vertical pipe for gas non-Newtonian liquid flow from our earlier experimental data. The Multilayer Perceptron consists of a single hidden layer. Four different transfer functions were used in the hidden layer. All three algorithms were useful to predict the gas holdup and frictional pressure drop across the vertical pipe. Statistical analysis using Chi-square test (χ2) confirms that the Backpropagation training algorithm gives the best predictability for both cases.


2010 ◽  
Author(s):  
T. K. Bandyopadhyay ◽  
A. B. Biswas ◽  
S. K. Das ◽  
Swapan Paruya ◽  
Samarjit Kar ◽  
...  

2010 ◽  
Author(s):  
Nirjhar Bar ◽  
Asit Baran Biswas ◽  
Manindra Nath Biswas ◽  
Sudip Kumar Das ◽  
Swapan Paruya ◽  
...  

2012 ◽  
Vol 38 ◽  
pp. 171-183 ◽  
Author(s):  
Jiann-Cherng Chu ◽  
Jyh-Tong Teng ◽  
Ting-ting Xu ◽  
Suyi Huang ◽  
Shiping Jin ◽  
...  

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