Prediction of CBR Using Dynamic Cone Penetrometer

Al-Refeai, Talal O.; Alsuhaibani, Abdulrahman

doi:10.1016/s1018-3639(18)30676-7

Cited by 23 publications

(26 citation statements)

References 3 publications

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“…In Eqs. (12) to (28), r is the coe cient of correlation, dry is in Mg/m 3 , and I D and w are in %. It can be seen from Eqs.…”

Section: Resultsmentioning

confidence: 99%

“…It can be seen from Eqs. (12) to (28) that the r values in Eqs. (13), (14), (17), (18), (19), (22), (23), and (28) are higher than 0.8, which indicate that there is a strong correlation between the CBR and the soil properties.…”

Section: Resultsmentioning

confidence: 99%

“…It can be also noticed from Eqs. (12) to (28) that Eq. (28) reveals the highest correlation coe cient of r = 0:925, indicating the strong correlation between the CBR and the soil properties (I D , w, G s , C u , and C c ) and particle shape (R F and S R ).…”

Section: Resultsmentioning

confidence: 99%

“…A CBR value is in uenced by the type of soil and di erent soil properties [6]. Many investigators (e.g., [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]) have performed studies to demonstrate the in uence of soil types and characteristics on the CBR values. The CBR value has also been connected empirically with resilient modulus and a variety of other engineering soil properties [20].…”

Section: Introductionmentioning

confidence: 99%

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Investigations on factors influencing the CBR value of some Aegean sands

Erzin¹,

Turkoz²,

Tuskan³

et al. 2016

Scientia Iranica

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The California Bearing Ratio (CBR) value of the soils is very important for geotechnical engineering and earth structures. A CBR value is a ected by the soil type and di erent soil properties. With this in view, in this paper, an attempt has been made for investigating the factors that a ect the CBR values of some Aegean sands collected from nine di erent locations in Manisa (Turkey). The sand samples were tested for mineralogy, particle shape and size, and speci c gravity. The CBR tests were then performed on these samples at di erent dry densities to examine the in uence of dry density, relative density, water content, and particle shape and size on the CBR value. Multiple Regression Analysis (MRA) was performed to predict the CBR value of the sands by using the experimental results. Moreover, several performance indices, such as coe cient of correlation and variance account for mean absolute error and root mean square error, were calculated to check the prediction capacity of the proposed MR equation. The obtained indices make it clear that the equation derived from the samples used in this study applies well, with an acceptable accuracy, to the CBR estimation at the preliminary stage of site investigations.

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“…In Eqs. (12) to (28), r is the coe cient of correlation, dry is in Mg/m 3 , and I D and w are in %. It can be seen from Eqs.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Investigations on factors influencing the CBR value of some Aegean sands

Erzin¹,

Turkoz²,

Tuskan³

et al. 2016

Scientia Iranica

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“…DCP correlations proposed in literature.Correlation ReferenceCalifornia bearing ratioAl-Refeai & Al-Suhaibani (1997);Ese et al (1994);Gabr et al (2000);Harison (1989);Kleyn (1975);Livneh (1989); Paige-Green & Pinard (2012);Smith & Pratt (1983); Van Vuuren (1969) Unconfined compressive strength De Villiers (1980); McElvaney & Bundadidjatnika (1991) Standard penetration test Ampadu et al (2018); Ibrahim & Nyaoro (2011); Sowers & Hedges (1966) Stiffness parameters Alshibli et al (2005); Lee et al (2014); Mohammadi et al (2008); Sawangsuriya & Edil (2005) Shear strength parameters Ayers (1990); Hamid (2013); Mohammadi et al (2008); Rahim et al (2004) Density parameters Azad (2008); Chennarapu et al (2018); Hamid (2013); Hossain (2009); Katakiya & Parekh (2017); Salgado & Yoon (2003)Table 3 -Details of calibration testing. Study Details of calibration chamber Reference void ratio procedureR1Air dried sand was placed in a 0.5 m diameter by 1 m high calibration chamber by air pluviation and vibration.…”

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confidence: 99%

Dynamic Cone Penetrometer (DCP) Relative Density Correlations for Sands

MacRobert¹,

Bernstein²,

Nchabeleng³

2019

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The dynamic cone penetrometer (DCP) is a widely used in-situ device to determine the engineering properties of soils. This paper reports a meta-analysis of laboratory calibration studies to establish a relationship between the rate of penetration and relative density for sands. Fourteen (14) different sands from different geographic and geological settings are compared. A direct relationship between the rate of penetration and relative density is proposed with a standard error in relative density predictions of 11%. A relationship incorporating the sand's median particle size is also proposed with a standard error in relative density predictions of 9%. Whilst there is good agreement between most of these studies, local conditions should be considered before adopting a proposed correlation in engineering design.

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A Scientometrics Review of Soil Properties Prediction Using Soft Computing Approaches

Khatti,

Grover

2023

Arch Computat Methods Eng

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Prediction of CBR Using Dynamic Cone Penetrometer

Cited by 23 publications

References 3 publications

Investigations on factors influencing the CBR value of some Aegean sands

Investigations on factors influencing the CBR value of some Aegean sands

Dynamic Cone Penetrometer (DCP) Relative Density Correlations for Sands

A Scientometrics Review of Soil Properties Prediction Using Soft Computing Approaches

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