Regression Modelling of California Bearing Ratio (CBR) Predicted from Index Properties for Lateritic Soils
Keywords:
california bearing ratio, index properties, multivariate regression model,
Abstract
Obtaining California Bearing Ratios (CBR) of soils for road construction projects could be a time-consuming and costly exercise. In order to reduce the time and cost of obtaining CBR values of soils, this paper presents a mathematical relationship between index properties of lateritic soils, which can easily be obtained from simple laboratory investigations, and their CBR (soaked and unsoaked) values.
Downloads
- Article PDF
- TEI XML Kaleidoscope (download in zip)* (Beta by AI)
- Lens* NISO JATS XML (Beta by AI)
- HTML Kaleidoscope* (Beta by AI)
- DBK XML Kaleidoscope (download in zip)* (Beta by AI)
- LaTeX pdf Kaleidoscope* (Beta by AI)
- EPUB Kaleidoscope* (Beta by AI)
- MD Kaleidoscope* (Beta by AI)
- FO Kaleidoscope* (Beta by AI)
- BIB Kaleidoscope* (Beta by AI)
- LaTeX Kaleidoscope* (Beta by AI)
How to Cite
Kayode-Ojo, N., Ehizokhale, M. E., Ehiorobo, & J. O. (2019). Regression Modelling of California Bearing Ratio (CBR) Predicted from Index Properties for Lateritic Soils. Global Journals of Research in Engineering, 19(E4), 39–55. Retrieved from https://engineeringresearch.org/index.php/GJRE/article/view/1977
Published
2019-10-15
Issue
Section
Articles
License
Copyright (c) 2019 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.