Cone Penetration Test Measurements Research Articles

Assessment of Liquefaction Potential of Some Coastal Soils in Lagos, South-Western Nigeria Using Geophysical and Geotechnical Methods

Liquefaction occurs in shallow, loose, saturated deposits of cohesionless soils subjected to strong shearing stresses. This leads to the transfer of stress from the soil skeleton to the pore water precipitating a decrease in effective stress and shear resistance of the soil. The study gives the results of the liquefaction potential assessment in some part of Lagos wetland areas of Lagos. The aim of this study was to assess the liquefaction potential through the evaluation of its severity in response to Earth tremors. In order to achieve this purpose, Multi-channel Analysis of Surface waves (MASW) and Cone penetration testing (CPT) were carried out. For an optimal coverage of the study area, twenty-four channels 4.5Hz geophones connected to the ABEM Mark 6 Seismograph through two cable reels were used to detect the generated seismic wave produced by the weight drop of about 19.1 kg. The CPT soundings for assessing subsurface stratigraphy with respect to liquefiable soils were carried out with a 10-Ton Dutch Cone Penetrometer. The softwares used were SeisImager, for processing the MASW data and CLiq for the CPT measurements. The shear wave velocity models were generated for the MASW measurements. The models show that sand sediments with velocity ranging from 118 - 279 m/s dominated most of the study area. Also, the results show that for the potential liquefiable sands identified, the shear wave velocity ranges between 118.0 – 180 m/s delineated at depths between 10.0 – 20.0 m within study profile an is typical of liquefiable sands. Simplified procedure of assessment of Liquefaction potential from CPT showed a model curve whereby some CPT points were within the liquefiable zones.

Interpretation of Cone Penetration Test Data in Layered Soils Using Cavity Expansion Analysis

Cavity expansion theory plays an important role in many geotechnical engineering problems, including the cone penetration test (CPT). One of the challenges of interpreting CPT data is the delineation of interfaces between soil layers and the identification of distinct thin layers, a process which relies on an in-depth understanding of the relationship between penetrometer readings and soil properties. In this paper, analytical cavity expansion solutions in two concentric regions of soil are applied to the interpretation of CPT data, with a specific focus on the layered effects during penetration. The solutions provide a large-strain analysis of cavity expansion in two concentric regions for dilatant elastic-perfectly plastic material. The analysis of CPT data in two-layered soils highlights the effect of respective soil properties (strength, stiffness) on CPT measurements within the influence zones around the two-soil interface. Results show good comparisons with numerical results and elastic solutions. A simple superposition method of the two-layered analytical approach is applied to the analysis of penetration in multilayered soils. A good comparison with field data and numerical results is obtained. It is illustrated that the proposed parameters effectively capture the influence of respective soil properties in the thin-layer analysis. It is also shown that results based on this analysis have better agreement with numerical results compared with elastic solutions.

Probabilistic identification of soil stratification

Identification of soil stratification is vital to geotechnical structural design and construction where the soil layer, soil type and properties are necessary inputs. Although methods are available for classifying the soil profiling using measured cone penetration test (CPT) data, the identification of soil stratification at unsampled locations is still difficult due to significant variability of natural soil. The identification is further complicated by the considerable uncertainties in the CPT measurements and soil classification methods. This study aims to develop a probabilistic method to predict soil stratification at unsampled locations by explicitly filtering the uncertainties in soil classification systems. An established Kriging interpolation technique is used to estimate the CPT parameters which are further interpreted to identify the soil stratification. Equations are derived to quantify the degree of uncertainties reduced by this method. The approaches are illustrated using a database of 26 CPT tests recently sourced from a dike near Ballina, Australia. Results show that the majority of the uncertainties in the soil parameters are screened by a soil classification index. The remaining uncertainties are further filtered by the soil classification systems. A clear stratification with a high degree of confidence is obtained in both horizontal plane and vertical unsampled locations, which shows excellent agreement with the existing CPT tests. This study provides a methodology to clearly identify the soil strata and reduce the uncertainties in prediction of design properties, paving the way for a more cost-effective geotechnical design.

Evaluation of liquefaction potential based on CPT data using random forest

The prediction of liquefaction potential of soil due to an earthquake is an essential task in civil engineering. In this paper, random forest (RF) method is introduced and investigated for the prediction of seismic liquefaction potential of soil based on the cone penetration test data. RF has been proposed on the basis of classification and regression trees with “ensemble learning” strategy. The RF models were developed and validated on a relatively large dataset comprising 226 field records of liquefaction performance and cone penetration test measurements. The database contains the information about depth of potentially liquefiable soil layer (D), cone tip resistance ( $$q_{\text{c}}$$ ), sleeve friction ratio ( $$R_{\text{f}}$$ ), effective vertical stress ( $$\sigma_{0}^{\prime }$$ ), total vertical stress ( $$\sigma_{0}$$ ), maximum horizontal ground surface acceleration ( $$\alpha_{\hbox{max} }$$ ) and earthquake magnitude ( $$M_{\text{w}}$$ ). Two RF models (Model I and Model II) are developed for predicting the occurrence and non-occurrence of liquefaction on the basis of combination of above input parameters. The results of RF models have been compared with the available artificial neural network (ANN) and support vector machine (SVM) models. It is shown that the proposed RF models provide more accurate results than the ANN and SVM models proposed in the literature. The developed RF provides a viable tool for civil engineers to determine the liquefaction potential of soil.

Comparing CPT and Vs Liquefaction Triggering Methods

Significant developments have taken place over the past 20 years to evaluate the liquefaction potential of soils using in situ tests. The cone penetration test (CPT) is now commonly used to evaluate liquefaction potential in soils. There have also been significant developments to evaluate liquefaction potential based on in situ shear wave velocity (Vs) measurements. Liquefaction methods base on shear wave velocity have the advantage that they are essentially independent of soil characteristics, such as fines content, but often lack the stratigraphic detail obtained using the CPT. Liquefaction methods based on the CPT have the advantage of continuous, repeatable measurements but require corrections based on soil characteristics that can be significant in soils with high fines content. Comparing the most recent Vs-based method with a CPT-based method provides an independent evaluation of the associated corrections applied to the CPT-based method. This paper compares the current Vs-based method with a specific CPT-based method from the literature to evaluate the associated CPT-based corrections. The paper also examines the advantage of using both CPT and Vs measurements (e.g., using the seismic CPT) to evaluate liquefaction potential.

Application of a Support Vector Machine for Liquefaction Assessment

This study presents a support vector machine (SVM)-based approach for predicting earthquake liquefaction. The SVM model database includes five indexes: earthquake magnitude, total overburden pressure, effective overburden pressure, qc values from cone penetration tests (CPT), and peak ground acceleration. The proposed model was trained and tested on a dataset comprising 466 field liquefaction performance records and CPT measurements. A grid search method with k-fold cross-validation was also used to verify the feasibility. Compared with an artificial neural network (ANN)-based method, the SVM-based method has the advantage of increased accuracy and simpler operation. Experimental results show that the proposed SVM approach can increase the classification accuracy rate to a standard of 98.71%.

Evaluation of SPT energy for Donut and Safety hammers using CPT measurements in Egypt

Standard Penetration Test (SPT) blow counts require correction prior to utilization in soil characterization and determination of properties and behavior. Among the most important corrections is the energy correction required to adjust the blow counts to 60% energy efficiency. However, there are no published data supporting commonly used value in Egypt. This paper presents an evaluation of the energy efficiency of the Donut and Safety hammers commonly used in Egypt and the associated energy correction factor. The energy efficiency is estimated by comparing N-values from the SPT to back-calculated N60 values from the Cone Penetration Test (CPT) using well established correlations. Results indicate that the energy efficiency of the Donut hammer based on current practice in Egypt is approximately 50%. Thus, the back-calculated energy correction factor is approximately 0.82. For the Safety hammer, results indicate that the energy efficiency is approximately 60%, and the energy correction factor is approximately 1.0.

CPT-based Seismic Liquefaction Potential Evaluation Using Multi-gene Genetic Programming Approach

This study examines the potential of multi-gene genetic programming (MGGP) based classification approach to evaluate liquefaction potential of soil in terms liquefaction index (LI) using a large database from post liquefaction cone penetration test (CPT) measurements and field manifestations. The database consists of CPT measurements; cone tip resistance (qc), friction ratio (Rf), vertical total stress (σv) and vertical effective stress of soil (σv′), seismic parameters; peak horizontal ground surface acceleration (amax) and earthquake moment magnitude (Mw), and the depth under consideration (z). The MGGP models (Model-I and Model-II) are developed for predicting occurrence and non-occurrence of liquefaction on basis of combination of above input parameters. The performance of the Model-I (95 %) is found to be more efficient compared to available artificial neural network model (91 %) and that of the Model-II (97 %) is found to be at par with the available support vector machine model (97 %) in terms of rate of successful prediction of liquefied and non-liquefied cases for testing data. Using an independent database of 96 cases, the overall classification accuracies are found to be 87 and 86 % for Model-I and Model-II respectively. Sensitivity analyses are made to identify the important parameters contributing to the prediction of LI.

Investigation of the reduction in uncertainty due to soil variability when conditioning a random field using Kriging

Spatial variability of soil properties is inherent in soil deposits, whether as a result of natural geological processes or engineering construction. It is therefore important to account for soil variability in geotechnical design in order to represent more realistically a soil's in situ state. This variability may be modelled as a random field, with a given probability density function and scale of fluctuation. A more convenient way to deal with the uncertainty of a soil property due to spatial variability, by constraining the generated random field at the locations of actual field measurements, is presented in this article. Conditioning the random field at known locations is a powerful tool, not only because it more accurately represents the observed variability on site, but also because it uses the available field information more efficiently. In situ cone penetration test (CPT) data from a particular test site are used to determine the input statistics for generating random fields, which are later constrained (conditioned) at the locations of actual CPT measurements using the Kriging interpolation method. The results from the conditional random fields are then analysed, to quantify how the number of field measurements used influences the reduction of uncertainty. It is shown that the spatial uncertainty relative to the original (unconditional) random field reduces with the number of CPTs used in the conditioning.

Reliability Analysis of CPT Measurements for Calculating Undrained Shear Strength

Abstract The cone penetration test (CPT) has been widely used in Louisiana to classify soils, measure undrained shear strength (Su), and identify bearing stratum for driven piles. This paper compares the values of Su based on CPT measurement with Su of the unconfined compression test. A total of 752 CPT soundings were collected and archived using ArcGIS software in which 503 were matched with adjacent boreholes and 249 did not have adjacent borehole data available. The dataset was analyzed for general as well as specific trends in order to identify appropriate parameters to be included in the investigation. The calibration of the CPT expression for Su was conducted using the first order reliability method (FORM) and accounting for all sources of uncertainty. Optimum CPT coefficient (Nkt) values to calculate Su were computed for various target reliability values. It was determined that the soil classification is the only parameter showing clear trends that affect CPT estimates of the undrained shear strength. Values of Nkt for each soil type based on the Robertson (1990) classification and the Zhang and Tumay (1999) classification were determined for three target reliability levels. It is obvious that the Nkt coefficient for soils with higher clay content is lower than those with less clay content. A single Nkt value that is valid for all soil types is unwarranted as will lead to acceptable results for some soil conditions and unacceptable results for others, which can be unconservative.

Retesting of Liquefaction and Nonliquefaction Case Histories from the 1976 Tangshan Earthquake

A field investigation was performed to retest liquefaction and nonliquefaction sites from the 1976 Tangshan earthquake in China. These sites were carefully investigated in 1978 and 1979 by using standard penetration test (SPT) and cone penetration test (CPT) equipment; however, the CPT measurements are obsolete because of the now nonstandard cone that was used at the time. In 2007, a modern cone was mobilized to retest 18 selected sites that are particularly important because of the intense ground shaking they sustained despite their high fines content and/or because the site did not liquefy. Of the sites reinvestigated and carefully reprocessed, 13 were considered accurate representative case histories. Two of the sites that were originally investigated for liquefaction have been reinvestigated for cyclic failure of fine-grained soil and removed from consideration for liquefaction triggering. The most important outcome of these field investigations was the collection of more accurate data for three nonliquefaction sites that experienced intense ground shaking. Data for these three case histories is now included in an area of the liquefaction triggering database that was poorly populated and will help constrain the upper bound of future liquefaction triggering curves.

Reliability-based pile design in sandy soils by CPT measurements

Field tests, such as static cone penetration tests (CPT), are widely used in granular soil characterisation because they are largely correlated by empirical charts and graphics to the main physical and mechanical soil properties (i.e. DR, φ, lithology etc.), although the uncertainties concerning with such estimations are taken into account. Whereas those formulations are widely accepted by literature and used in practice, they are not discussed in terms of reliability level of the pile bearing capacity. In this paper, Bustamante and Gianeselli's formulation has been adopted as a direct method for estimating pile bearing capacity from qc profile at Scanzano Jonico site. As far as the reliability-based design of limit pile resistance is concerned, the statistical properties of the design variables are based on the variability study carried out on such sand. Results are discussed with respect to the advantages in usage of direct instead of indirect methods for pile design in sand.

Characterization of subsoil heterogeneity, estimation of grain size distribution and hydraulic conductivity at the Krauthausen test site using Cone Penetration Test

A Cone Penetration Test (CPT) survey with a high spatial resolution was performed in order to investigate the stratigraphy as well as the spatial variability of various soil properties of the Krauthausen test site. Analyses of the CPT measurements showed the subsurface to be dominated by a planar layered structure. Variogram analysis of the various CPT parameters disclosed that within each layer the soil properties have an anisotropic spatial correlation structure. A correlation analysis of the measured CPT data and co-located grain size distributions from soil samples was performed. Since the correlation coefficients were greater equal to 0.7, a reliable empirical relationship between the data sets could be developed. Based on this empirical relationship grain size distributions were estimated at CPT locations. The statistical processing of estimated and measured grain size distributions with respect to their spatial correlation structure disclosed good agreement between the data sets. The estimated grain size distributions from CPT data were used to estimate the hydraulic conductivity in the aquifer. The results provide detailed information of the spatial heterogeneity of the hydraulic conductivity at Krauthausen test site. The validation of these results, using a prior investigation of hydraulic conductivity statistics, suggests the CPT a fast and inexpensive tool for the estimation of three dimensional hydraulic conductivity fields with sufficient accuracy.

Support vector machines: Their use in geotechnical engineering as illustrated using seismic liquefaction data

Empirical models based on known or measured sample data are often used to develop solutions to problems in which the underlying first principles are not well defined and it is not possible to define a concise relationship between the variables, or the problem is too complicated to be described mathematically. Increasingly, various modern “learning” algorithms such as neural networks are being considered to develop models that essentially map a dependency between the inputs and outputs from known data patterns. This study looks at a fairly new pattern recognition tool known as support vector machines (SVM) that can be used for solving classification-type problems. There are two main ideas underlying the SVM for discriminant-type problems. The first is an optimum linear separating hyperplane (decision surface) that separates the data patterns. The second main idea is the use of kernel functions (dot product of two vectors) to apply mapping to the original nonlinear data patterns, such that the data becomes linearly separable in a high-dimensional feature space. An overview of the SVM is first presented followed by an illustration of its use to assess seismic liquefaction data. The SVM model was trained and tested on a relatively large data set comprising 226 field records of liquefaction performance and cone penetration test measurements. The overall classification success rate for the entire data set is 98%.

Mapping Liquefaction Potential Considering Spatial Correlations of CPT Measurements

The past studies of liquefaction phenomena during earthquakes have contributed to the development of simplified methods employing field test data to assess the liquefaction potential. Since the field data are limited by exploration cost, it is of interest to obtain valuable and meaningful distribution of liquefaction potential of an area from the limited data. This study proposes a method for assessing liquefaction potential over an extensive area according to the random field concept. The spatial structures of soil properties are estimated from the available cone penetration test (CPT) measurements. The soil properties at unsampled locations are simulated using Monte Carlo simulation. The reliability against liquefaction at every location within the study area is evaluated to map the liquefaction potential. The comparison between simulated distributions of liquefaction potential and observed liquefaction phenomena is discussed. The spatial correlation of soil property provides more information than the traditional approach that solely uses the field test data. The influences of CPT data, penetration locations, and spatial structures of soil properties on the mapping results of liquefaction potential are also discussed.

Truth: non-additive measures for the determination of relative density of sands using CPT measurements

In this Note, a fuzzy-integral based approach is developed for aggregating some of the available correlations that are commonly used for determining relative density D r , from cone penetration test (CPT) data, in which non-additive measures are used as fuzzy measures to relate the actual compressibility measured by the friction ratio of sands to the base correlations. The results of the case studied show that fuzzy measures and the fuzzy integral can be utilized for a new approach in geo-technical engineering. To cite this article: C. Tran, C. R. Mecanique 333 (2005).

Modeling aquifer heterogeneity using cone penetration testing data and stochastic upscaling methods

Cone penetration testing (CPT) has become an increasingly popular characterization method for subsurface investigations under 60 m (200 ft) depth in the Atlantic coastal plain of South Carolina. The shallow Tertiary sediments consist primarily of interbedded and interfingering fluvial, deltaic, and shallow-marine sediments. Cone penetration testing is relatively inexpensive and does not require disposal of drilling fluid or cuttings. At the Savannah River Site, CPT is typically used to obtain depth-discrete groundwater samples and small-diameter permeability samples, and to define hydrostratigraphic horizons. The focus of this study is an environmental waste site where CPT at 139 locations was used to define contaminant plumes and hydrostratigraphy over an 8-km2 (3-mi2) area, instead of conventional borehole techniques (e.g., monitoring wells, cores, electric well logs, slug, and pumping tests). This investigation used the CPT lithologic data to predict hydraulic conductivity variations in hydrostratigraphic zones of the uppermost aquifer unit. The method developed involves correlating tip resistance, sleeve resistance, and pore-pressure measurements to fines (mud, silt, and clay) content and hydraulic conductivity. Predicted fines content at the scale of the CPT measurements (0.03 m; 0.1 ft) are then categorized into high, medium and low conductivity and upscaled to the flow model resolution using a geostatistical approach. The resulting model conductivity field provides a realistic representation of aquifer heterogeneity in coastal-plain sediments and significantly improves groundwater modeling predictions. Subsequent contaminant transport simulations compare well with field data.

Empirical correlations of soil parameters based on Cone Penetration Tests (CPT) for Greek soils

This study presents the results of Cone Penetration Tests (CPT) and estimated correlations with the results of other in-situ tests (standard penetration test, cross-hole, seismocone) and laboratory tests (classification and undrained shear strength tests). These tests cover nearly all types of penetrable soils in Greece and, together with the formulation of empirical correlations, complement and improve on previous studies due to the significant number of CPT measurements.

Simplified Cone Penetration Test-based Method for Evaluating Liquefaction Resistance of Soils

This paper presents a new simplified method for assessing the liquefaction resistance of soils based on the cone penetration test (CPT). A relatively large database consisting of CPT measurements and field liquefaction performance observations of historical earthquakes is analyzed. This database is first used to train an artificial neural network for predicting the occurrence and nonoccurrence of liquefaction based on soil and seismic load parameters. The successfully trained and tested neural network is then used to generate a set of artificial data points that collectively define the liquefaction boundary surface, the limit state function. An empirical equation is further obtained by regression analysis to approximate the unknown limit state function. The empirical equation developed represents a deterministic method for assessing liquefaction resistance using the CPT. Based on this newly developed deterministic method, probabilistic analyses of the cases in the database are conducted using the Bayesian mapping function approach. The results of the probabilistic analyses, expressed as a mapping function, provide a simple means for probability-based evaluation of the liquefaction potential. The newly developed simplified method compares favorably to a widely used existing method.

Field measurements of shear strength of an underconsolidated marine clay

This paper presents the observations of cone penetration testing (CPT), in situ vane shear testing and undrained triaxial testing of underconsolidated marine clay in the Craney Island Dredged Material Management Area (CIDMMA), Norfolk, VA. Comparison of vane shear measurements, taken during 1981–1983, to CPT measurements, taken during 1993, indicates a change in undrained shear strength. Both the vane shear and cone penetration resistances are lowest at the mid-heights of the clay layers and the excess pore water pressures are highest at the mid-height of the clay layers, indicating that the clay layer is underconsolidated.