| Title: | Prediction of California Bearing Ratio (CBR) and Compaction Characteristics of granular soil |
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| Authors: | ID Rehman, Attique ul (Author)
ID Farooq, Khalid (Author)
ID Mujtaba, Hassan (Author)
ID Fakulteta za gradbeništvo, prometno inženirstvo in arhitekturo Univerze v Mariboru (Copyright holder) |
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| Files: |  Acta_Geotechnica_Slovenica_2017_Rehman,_Farooq,_Mujtaba_Prediction_of_California_Bearing_Ratio_(CBR)_and_Compaction_Characteristics_of_g_unlocked.pdf (830,76 KB)
MD5: 37B5F10E06D7BBF3102EEEB739352ED8
PID: 20.500.12556/dkum/6d54674c-553e-45d3-b484-30e17345c007
 http://fgserver3.fg.um.si/journal-ags/2017-1/article-6.asp
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FGPA - Faculty of Civil Engineering, Transportation Engineering and Architecture
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| Abstract: | This research is an effort to correlate the index properties of granular soils with the California Bearing Ratio (CBR) and the compaction characteristics. Soil classification, modified proctor and CBR tests conforming to the relevant ASTM methods were performed on natural as well as composite sand samples. The laboratory test results indicated that samples used in this research lie in SW, SP and SP-SM categories based on Unified Soil Classification System and in groups A-1-b and A-3 based on the AASHTO classification system. Multiple linear regression analysis was performed on experimental data and correlations were developed to predict the CBR, maximum dry density (MDD) and optimum moisture content (OMC) in terms of the index properties of the samples. Among the various parameters, the coefficient of uniformity (Cu), the grain size corresponding to 30% passing (D30) and the mean grain size (D50) were found to be the most effective predictors. The proposed prediction models were duly validated using an independent dataset of CBR tests on sandy soils. The comparative results showed that the variation between the experimental and predicted results for CBR falls within ±4% confidence interval and that of the maximum dry density and the optimum moisture content are within ±2%. Based on the correlations developed for CBR, MDD and OMC, predictive curves are proposed for a quick estimation based on Cu , D30 and D50. The proposed models and the predictive curves for the estimation of the CBR value and the compaction characteristics would be very useful in geotechnical & pavement engineering without performing the laboratory compaction and CBR tests. |
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| Keywords: | CBR, regression, model, prediction, compaction characteristics |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Year of publishing: | 2017 |
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| Number of pages: | str. 63-72 |
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| Numbering: | Letn. 14, št. 1 |
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| PID: | 20.500.12556/DKUM-70887  |
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| ISSN: | 1854-0171 |
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| ISSN on article: | 1854-0171 |
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| COBISS.SI-ID: | 302986752 |
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| NUK URN: | URN:SI:UM:DK:PKRK054J |
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| Copyright: | Fakulteta za gradbeništvo, prometno inženirstvo in arhitekturo Univerze v Mariboru |
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| Publication date in DKUM: | 18.06.2018 |
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| Views: | 1439 |
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| Downloads: | 227 |
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| Metadata: |    |
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| Categories: | Misc.
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