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Prediction of abrasiveness index of some Indian rocks using soft computing methods

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Title Prediction of abrasiveness index of some Indian rocks using soft computing methods
 
Creator TRIPATHY, A
SINGH, TN
KUNDU, J
 
Subject ARTIFICIAL NEURAL-NETWORKS
CERCHAR ABRASIVITY INDEX
PHYSICOMECHANICAL PROPERTIES
STRENGTH
CAI
TOOLS
WEAR
Cerchar abrasivity index
Penetration rate
Artificial neural networking
Multi linear regression analysis
Soft computing
 
Description The present paper mainly describes the prediction methodology to determine the Cerchar Abrasiveness Index and Penetration Rate related to rock excavation using simple geomechanical parameters as predictors. As abrasiveness of rocks is influenced by many geomechanical parameters, an attempt is made to use these parameters for its prediction using Multivariate Regression Analysis and Artificial Neural Networking. Abrasiveness Index as well as Penetration Rate are very vital in deciding the economics of the excavations as they directly govern the wear and tear of drill bit. It was observed that ANN shows a better prediction capability than MVRA using UCS, Point load index, P wave velocity and Young's modulus as predictors. (C) 2015 Elsevier Ltd. All rights reserved.
 
Publisher ELSEVIER SCI LTD
 
Date 2016-01-15T04:38:17Z
2016-01-15T04:38:17Z
2015
 
Type Article
 
Identifier MEASUREMENT, 68,302-309
0263-2241
1873-412X
http://dx.doi.org/10.1016/j.measurement.2015.03.009
http://dspace.library.iitb.ac.in/jspui/handle/100/17777
 
Language en