Estimation of liquid viscosities of oils using associative neural networks
IR@NISCAIR: CSIR-NISCAIR, New Delhi - ONLINE PERIODICALS REPOSITORY (NOPR)
View Archive Info| Field | Value | |
| Title |
Estimation of liquid viscosities of oils using associative neural networks
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| Creator |
Neelamegam, P
Krishnaraj, S |
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| Subject |
Andrade equation
Associative neural network Oil Regression Viscosity |
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| Description |
463-468
Dynamic viscosities of a number of vegetable oils (castor oil, palm oil, sunflower oil and coconut oil) and lubricant oils (2T and 4T) have been determined at temperature range 30<sup>o</sup> - 90<sup>o</sup>C using Ubbelohde viscometer. An associative neural network is used to compute the viscosities of oils for unknown temperatures after training the neural network with type of oil, temperature as input and viscosity as output. Predicted results agree well with the experimental results. Simplified and modified form of Andrade equations that describe the temperature dependence of dynamic viscosities are fitted to the experimental data and correlations for the best fit are presented. The results obtained from associative neural network and best correlation equation show that both predict the viscosities very well with correlation coefficient <i style="mso-bidi-font-style:normal">R<sup>2 </sup></i>= 0.99. |
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| Date |
2011-12-24T10:49:55Z
2011-12-24T10:49:55Z 2011-11 |
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| Type |
Article
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| Identifier |
0975-0991 (Online); 0971-457X (Print)
http://hdl.handle.net/123456789/13279 |
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| Language |
en_US
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| Rights |
<img src='http://nopr.niscair.res.in/image/cc-license-sml.png'> <a href='http://creativecommons.org/licenses/by-nc-nd/2.5/in' target='_blank'>CC Attribution-Noncommercial-No Derivative Works 2.5 India</a>
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| Publisher |
NISCAIR-CSIR, India
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| Source |
IJCT Vol.18(6) [November 2011]
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