Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/10457
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRajesh, Kumar, B.
dc.contributor.authorVardhan, H.
dc.contributor.authorGovindaraj, M.
dc.contributor.authorSaraswathi, P.S.
dc.date.accessioned2020-03-31T08:19:14Z-
dc.date.available2020-03-31T08:19:14Z-
dc.date.issued2013
dc.identifier.citationGeomechanics and Geoengineering, 2013, Vol.8, 1, pp.53-61en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/10457-
dc.description.abstractIn many rock engineering applications such as foundations, slopes and tunnels, the intact rock properties are not actually determined by laboratory tests, due to the requirements of high quality core samples and sophisticated test equipments. Thus, predicting the rock properties by using empirical equations has been an attractive research topic relating to rock engineering practice for many years. Soft computing techniques are now being used as alternative statistical tools. In this study, artificial neural network models were developed to predict the rock properties of the intact rock, by using sound level produced during rock drilling. A database of 832 datasets, including drill bit diameter, drill bit speed, penetration rate of the drill bit and equivalent sound level (Leq) produced during drilling for input parameters, and uniaxial compressive strength (UCS), Schmidt rebound number (SRN), dry density (?), P-wave velocity (Vp), tensile strength (TS), modulus of elasticity (E) and percentage porosity (n) of intact rock for output, was established. The constructed models were checked using various prediction performance indices. Goodness of the fit measures revealed that recommended ANN model fitted the data as accurately as experimental results, indicating the usefulness of artificial neural networks in predicting rock properties. 2013 Copyright Taylor and Francis Group, LLC.en_US
dc.titleArtificial neural network model for prediction of rock properties from sound level produced during drillingen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.