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Random field characterization of CPTU soil behavior type index of Jiangsu quaternary soil deposits

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Abstract

The soil behavior type index (I c) obtained from piezocone penetration tests (CPTU) has been widely applied in a series of geotechnical issues including the identification of soil stratum, estimation of soil properties and liquefaction analysis. To provide spatial statistics of I c for the probabilistic analysis of these geotechnical applications, this paper investigated the inherent vertical variability of the I c data using Gaussian random field theory. To achieve the analysis, 134 CPTU soundings were performed at the sites of four typical geologic formations. These formations included marine, Yangtze River Delta, long river floodplain and abandoned Yellow River floodplain deposits in the Jiangsu Province, China. Statistically homogeneous soil units (HSUs) were firstly identified based on a screening procedure. Then the probability density distribution of the I c data in each HSU was studied using a formal normality test and the quantile plot method. Afterwards, the method of moment was used to estimate the three random field model parameters of I c, including the mean value (μ Y ), coefficient of variation (COV), and vertical scale of fluctuation (δ v). It was shown that the normality hypothesis may be suitable for both raw I c and the fluctuation components of I c data in a qualified sense, whereas, in a strict sense, the feasibility of this assumption is complicated with about 50 % data passing the formal normality test. The COV of I c data of the Jiangsu soils varies from 1.9 to 14 %. The δ v of I c profile ranges from 0.1 to 1.17 m. The impacts of the geologic formation and soil behavior type on the probability density distribution and random field characteristics of I c data were observed as the normality, COV and scale of fluctuation values of I c tend to be similar, provided that the soils are of the same geologic formation. Finally, suggestions for future selections of the normality hypothesis, coefficient of variation and vertical scale of fluctuation of I c data are proposed.

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Abbreviations

RFT:

Random field theory

COV:

Coefficient of variation

CPTU:

Piezocone penetration test

I c :

Soil behavior type index

OLS:

Ordinary least squares

z :

Depth

PDF:

Probability density function

Q tn :

Normalized cone tip resistance

F r :

Normalized sleeve friction resistance

q c :

Measured cone tip resistance

q t :

Cone tip resistance corrected for the pore water pressure

a :

Cone area ratio

u 2 :

Measured pore water pressure

f s :

Measured sleeve friction resistance

σ v0 :

Vertical total overburden stress

\( \sigma^{'}_{{{\text{v}}0}} \) :

Vertical effective overburden stress

n :

Stress exponent

p a :

Atmospheric pressure

MBS:

Modified Bartlett’s statistics

B stat :

Bartlett’s statistics

B max :

Maximum Bartlett’s statistics

B crit :

Critical Bartlett’s statistics

δ v :

Vertical scale of fluctuation

Δz :

Sampling interval

HSU:

Homogeneous soil unit

r B :

Bartlett’s limit

R(τ):

Autocorrelation model function

ACF:

Autocorrelation function

Q–Q plot:

Quantile–Quantile plot

R 2 :

Coefficient of determination

KS test:

Kolmogorov–Smirnov test

P value:

The probability of the evidence that the null hypothesis is true

α :

Significance level

H0 :

Null hypothesis

X :

Standardized I c or residuals of I c data of each HSU

Y :

Raw I c or residuals of I c data of each HSU

μ Y :

Mean value of the Y variable

σ Y :

Standard deviation of the Y variable

g(z):

Raw I c data

w(z):

Fluctuation component of I c

t(z):

Trend of I c

δ :

Scale of fluctuation

BLM:

Intersecting Bartlett’s limits method

\( \hat{R}(\tau ) \) :

Sample autocorrelation function

m :

Number of data points

s 2 :

Sample variance

τ :

Lag distance

ACM:

Autocorrelation model

SNX:

Single exponential autocorrelation model

CSX:

Cosine exponential autocorrelation model

SMK:

Second-order Markov autocorrelation model

SQX:

Squared exponential autocorrelation model

t M :

Mean value of raw I c data

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Acknowledgments

A majority of the work presented in this paper was funded by the Foundation for the New Century Excellent Talents of China (grant no. NCET-13-0118), the Foundation of Jiangsu Province Outstanding Youth (grant no. BK20140027) and the Foundation for the Author of National Excellent Doctoral Dissertation of PR China (grant no. 201353). These financial supports are gratefully acknowledged.

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Authors and Affiliations

  1. Institute of Geotechnical Engineering, Southeast University, Nanjing, 210096, Jiangsu, China

    Guojun Cai, Haifeng Zou & Songyu Liu

  2. Department of Civil Engineering, The University of Texas at Arlington, Arlington, TX, 76019, USA

    Anand J. Puppala

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  1. Guojun Cai
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  2. Haifeng Zou
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  3. Songyu Liu
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Correspondence to Haifeng Zou.

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Cai, G., Zou, H., Liu, S. et al. Random field characterization of CPTU soil behavior type index of Jiangsu quaternary soil deposits. Bull Eng Geol Environ 76, 353–369 (2017). https://doi.org/10.1007/s10064-016-0854-x

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