NISCAIR Online Periodicals Repository

NISCAIR ONLINE PERIODICALS REPOSITORY (NOPR)  >
NISCAIR PUBLICATIONS >
Research Journals >
Indian Journal of Engineering and Materials Sciences (IJEMS) >
IJEMS Vol.17 [2010] >
IJEMS Vol.17(6) [December 2010] >


Title: Neural network model for temperature sensitivity of emulsified asphalt mixtures
Authors: Oruc, Seref
Keywords: Emulsified asphalt mixture
Temperature sensitivity
Neural networks
Resilient modulus
Regression analysis
Issue Date: Dec-2010
Publisher: NISCAIR-CSIR, India
Abstract: This study intends to investigate temperature sensitivity of emulsified asphalt mixtures (cold-mix) and to establish a methodology that would provide an economic and rapid means for future experimental researches. Temperature sensitivity of the mixtures is investigated for 0ºC, 5ºC, 15ºC, 25ºC and 40ºC. The samples are prepared for three residual asphalt contents (4.2%, 5.2% and 6.2%). Portland cement is substituted for mineral filler in different ratios from 1% to 6%. A neural network (NN) model is developed for predicting, with sufficient approximation, relationship between the factors affecting resilient modulus (inputs; temperature, cement and asphalt content) and the resilient modulus (output) of emulsified asphalt mixture. A backpropagation neural network of three layers is employed. First resilient modulus data is obtained by conducting laboratory resilient modulus tests on emulsified asphalt samples, and then the results are used to train the neural network. The effectiveness of different neural network configurations is investigated. Effect of parameters such as temperature, cement addition level and residual asphalt content that influence the resilient modulus is explored. The prediction capability of the NN model is also compared to the traditional regression approach. Results indicate that NN predicts the resilient modulus with high accuracy. It is also demonstrated that NN is an excellent method that can reduce time consumed and can be used as an important tool in evaluating the factors affecting resilient modulus of the mixtures for the design process.
Page(s): 438-448
CC License:  CC Attribution-Noncommercial-No Derivative Works 2.5 India
ISSN: 0975-1017 (Online); 0971-4588 (Print)
Source:IJEMS Vol.17(6) [December 2010]

Files in This Item:

File Description SizeFormat
IJEMS 17(6) 438-448.pdf355.19 kBAdobe PDFView/Open
 Current Page Visits: 579 
Recommend this item

 

National Knowledge Resources Consortium |  NISCAIR Website |  Contact us |  Feedback

Disclaimer: NISCAIR assumes no responsibility for the statements and opinions advanced by contributors. The editorial staff in its work of examining papers received for publication is helped, in an honorary capacity, by many distinguished engineers and scientists.

CC License Except where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India

Copyright © 2012 The Council of Scientific and Industrial Research, New Delhi. All rights reserved.

Powered by DSpace Copyright © 2002-2007 MIT and Hewlett-Packard | Compliant to OAI-PMH V 2.0

Home Page Total Visits: 593465 since 06-Feb-2009  Last updated on 18-Sep-2014Webmaster: nopr@niscair.res.in