Estimation of four-day soaked CBR using index properties

Jayamali, KVSD; Nawagamuwa, UP; Indraratna, B

Estimation of four-day soaked CBR using index properties

Jayamali, KVSD Nawagamuwa, UP Indraratna, B

Permalink

Publication Type:: Journal Article
Citation:: Australian Geomechanics Journal, 2018, 53, (4), pp. 149-158
Issue Date:: 2018-12-01

Closed Access

	Filename	Description	Size
	19504943_8780241380005671.pdf	Published version	3.8 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Jayamali, KVSD
dc.contributor.author	Nawagamuwa, UP
dc.contributor.author	Indraratna, B https://orcid.org/0000-0002-9057-1514
dc.date.accessioned	2022-09-09T03:52:05Z
dc.date.available	2022-09-09T03:52:05Z
dc.date.issued	2018-12-01
dc.identifier.citation	Australian Geomechanics Journal, 2018, 53, (4), pp. 149-158
dc.identifier.issn	0818-9110
dc.identifier.uri	http://hdl.handle.net/10453/161572
dc.description.abstract	California Bearing Ratio (CBR) is an important parameter used to evaluate the strength of subgrade and sub-base soils for design of flexible pavements and hence it plays a significant role in road and highway constructions. Obtaining CBR is heavily time consuming and it is difficult to acquire a representative CBR value. Therefore, many correlations have been developed by various researchers worldwide to predict the CBR. Due to differences in soil formations in the tropical environment, these existing global correlations found to be not satisfactory with local soils in Sri Lanka. Hence, this study was carried out to develop empirical correlations between CBR and index properties those best suit for local soils, using the data obtained from Atterberg limits and sieve analysis tests together with compaction tests. The new correlations were established using the method of regression analysis in the form of empirical equations representing the role of index properties. Robust regression by the method of least absolute residuals using MATLAB was considered in the analysis to reduce the impact of outliers along with traditional multiple regression using Microsoft Excel. As a final verification, several laboratory tests were conducted to compare the results with proposed regression equations.
dc.language	en
dc.relation.ispartof	Australian Geomechanics Journal
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0905 Civil Engineering, 0914 Resources Engineering and Extractive Metallurgy
dc.title	Estimation of four-day soaked CBR using index properties
dc.type	Journal Article
utslib.citation.volume	53
utslib.for	0905 Civil Engineering
utslib.for	0914 Resources Engineering and Extractive Metallurgy
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2022-09-09T03:52:03Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	53
utslib.citation.issue	4

Abstract:

California Bearing Ratio (CBR) is an important parameter used to evaluate the strength of subgrade and sub-base soils for design of flexible pavements and hence it plays a significant role in road and highway constructions. Obtaining CBR is heavily time consuming and it is difficult to acquire a representative CBR value. Therefore, many correlations have been developed by various researchers worldwide to predict the CBR. Due to differences in soil formations in the tropical environment, these existing global correlations found to be not satisfactory with local soils in Sri Lanka. Hence, this study was carried out to develop empirical correlations between CBR and index properties those best suit for local soils, using the data obtained from Atterberg limits and sieve analysis tests together with compaction tests. The new correlations were established using the method of regression analysis in the form of empirical equations representing the role of index properties. Robust regression by the method of least absolute residuals using MATLAB was considered in the analysis to reduce the impact of outliers along with traditional multiple regression using Microsoft Excel. As a final verification, several laboratory tests were conducted to compare the results with proposed regression equations.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/161572