Cone Penetration Test Test Research Articles

Discrete element modelling of rotary CPT and its applications

The cone penetration test (CPT) is a major in-situ testing with advantages in efficiency, reliability, and continuous measurement. However, it is often limited in penetration depth in soils such as dense sand and gravel due to high resistance and insufficient pushing force. Studies have shown that rotation can reduce penetration resistance, leading to the development of the rotary CPT. In addition, the torque measurement in rotary CPT could potentially provide extra information for soil behavior. This study simulates regular and rotary CPT tests with varied confining pressure and initial relative density using the discrete element method (DEM). Macroscale results verify that rotation can improve the penetrability of CPT by reducing vertical soil resistance. The reduction mechanism was explained by the microscopic observations and theoretical calculations that rotation can reduce the magnitude of the contact force and tilt its main direction horizontally. To advance the application of rotary CPT, a strong linear correlation between the measurements in rotary and regular CPTs was established, enabling interpretation of the rotary CPT measurements via the vast knowledge accumulated for regular CPT soundings. Furthermore, a theoretical derivation was developed to calculate the soil-probe interface friction coefficient directly by using the measurements of rotary CPT. The influence of the confining pressure, probe friction coefficient, and rotational speed ratio on the calculation accuracy are discussed and explained via particle-scale observations.

Determining The Depth of Hard Soil Layers Using Geoelectric Resistivity and Cone Penetration Test Methods (Case Study: Kelurahan Bontoramba Kecamatan Somba Opu Kabupaten Gowa)

Hard soil layers can impact the loading, stability, and behavior of structures in the geotechnical field. Comprehensive understanding of the depth and properties of hard soil layers can aid in designing suitable structures. Therefore, this study employed the resistivity geoelectric and Cone Penetration Test (CPT) methods to map the features of hard soil layers. Resistivity data were acquired through measurements utilizing the geoelectric method, while data on cone resistance, shear resistance, and friction ratio were gathered through field measurements using the CPT tool. The collected data was analyzed comprehensively to obtain a complete understanding of soil conditions. Based on resistivity values, the results indicated the research site comprises alluvium, very dry clay, and dry sandy soil. Based on the CPT test, it is determined that the layers contain mixtures of fine-grained soils, clay, silt, and sand. Therefore, it can be inferred that the dense sand lithology constitutes the hard soil layer geologically. The employment of both approaches delivers supplementary details on soil features and depth.

Quantifying CPT cone factors in clays derived from weathered mudstone

The empirical interpretation of cone penetration test (CPT) cone factors ( N k ) can be subject to considerable variability for clays derived from weathered mudstones, leading to significant deviations in the estimation of undrained shear strength ( S u ). This paper presents a comparison of triaxial and CPT data from a site investigation in clays derived from weathered mudstones in central England. Corrected cone factors ( N kt,UU ) were derived from a one-to-one comparison of 94 pairs of unconsolidated, undrained triaxial and CPT data from equivalent depths. The performance of the cone factors was evaluated using a training set (75 pairs) and a test set (19 pairs). A parametric study was used to explore the variability of N kt,UU , quantified using the coefficient of variation (COV Nkt,UU ), for varied separation distance thresholds ( D s ) between individual triaxial and CPT data. The absolute deviation between the laboratory shear strength ( S u(Lab) ) and that predicted from CPT profiles (S u(CPT) ) was not sensitive to N kt,UU values in the range 25 < N kt,UU < 31. The parametric study showed that D s could be increased from 50 to 250 m, to include more data pairs for estimates of N kt,UU , without substantially increasing COV Nkt,UU .

A Unified Approach for the Analysis of CPT Partial Drainage Effects within a Critical State Soil Mechanics Framework in Mine Tailings

Results from both laboratory and in-situ cone penetration tests (CPTs) on predominantly sandy silt platinum tailings from an operational mine in South Africa are reported. The CPTs were conducted with four different cone diameters at varied penetration rates. With the results interpreted in terms of the normalized tip resistance and the initial state parameter, in addition to dissipation tests, it was possible to identify the CPTs affected by significant partial drainage effects. A review of the partial drainage concept enabled the formulation of a novel characteristic surface approach, which uses a unified continuous equation to estimate the state parameter from the CPT data from drained to partially drained and undrained regimes and from contractive to dilative states. A review of different methods for the estimation of the coefficient of consolidation, and hence the normalized penetration velocity, enables a comparison of the estimated state parameter with independent values calculated from recovered saturated samples, showing the ability of this technique to infer the state parameter from CPT tests where partial drainage occurs.

Assessment of a new pluviation system designed to prepare uniform samples of sand

In soil and soil-structure interaction laboratory experiments, the technique applied to prepare the sand deposit remarkably influence the performance of the system, including the stress–strain behavior. Air pluviation techniques represent the most suitable choice when a wide range of densities is required. This study presents the details of a simple and effective air pluviation system designed to be suitable for reconstituting small specimens of sand. Many of the previous studies have focused on traveling the pluviator in the horizontal direction only, without paying much attention to the vertical movement during pluviation. The apparatus described in this paper has the ability to overcome this issue by providing automatic lifting tools to the sand container while the thickness of the sand deposit builds up inside the collecting mold. To understand the influence of grain size distribution of sand on the achieved relative density (RD), three different samples of poorly graded sands were used in the experiments. Parametric studies, including the influence of the height of drop (HD) and deposition intensity (DI) on the relative density, were carried out on the three sand samples. It was observed that the range of obtained RDs depends mainly on the grain size distribution of the sand used. Three distinguished zones were observed in the RD-HD relationship, starting with a linear variation, followed by a nonlinear relationship until achieving a constant RD regardless of the increase of HD value. The uniformity of pluviated sand was assessed using a cone penetration test (CPT). Results of the CPT test showed that denser and more uniform samples could be obtained by raising the container up during the pluviation process.

Application of CPT test in the evaluation of the test effect of lime soil compacting pile

In the course of highway construction and use in loess area, subgrade settlement disease is common and has great destructiveness. The cone penetration test (CPT), especially the pore pressure cone penetration test, can provide three continuous readings along the exploration depth cone tip resistance, lateral friction resistance and excess pore water pressure. In this paper, CPT tests are carried out in the losses areas in Shanxi, China. Some data and curves are obtained by using CPT, which are quite different from those obtained by conventional drilling, reflecting the soil layer characteristics of the subgrade section, in order to provide a reference for similar projects. The results showed that CPT has a strong advantage in the analysis of the effect of compacted pile in the treatment of pile length and the improvement and reduction of indicators of different layers along the depth direction. However, the correlation between the static penetration and the compaction coefficient commonly used in the current norms still needs to be further studied to enhance the correlation analysis with detection parameters.

Design of Laterally Loaded Single Piles by Using P-Y Curves and the Cone Penetration Test (CPT) in Sandy Soils

The aim of this paper is to present a simple method of construction of the load-transfer P-Y curves for the design of laterally loaded piles in sand based on the cone penetration test (CPT). The proposed method was developed on the basis of interpretation of 5 field tests on single instrumented piles conducted in sandy sites in France and shows a simple relationship linking the P-Y curve parameters, the cone penetration resistance and the lateral pile/soil stiffness ratio. The validation process was carried out by direct comparison of the predicted load-deflection curves based on the proposed method to those obtained from a worldwide case history of field lateral loading tests on piles and showed a very good quality of the prediction using the proposed method. KEYWORDS: Piles, Lateral load, Sand, Full-scale loading, P-Y curves, CPT test.

A correlation based on pressuremeter, SPT and CPT tests for characterizing of coastal alluvium: A study for phase 14 South Pars, Iran

Pressuremeter Test (PMT), Cone Penetration Test (CPT), and Standard Penetration Test (SPT) are the key in-situ experiments to directly estimate the in-situ modulus of deformation and strength parameters of soils, which are highly used in coastal alluvium. In addition, CPT and SPT are unique tests for estimating engineering properties that are ideal for onshore regions. These tests are adaptable for coastal alluvium with different saturation levels, which facilitates the determination of the field deformation modulus. Regression analysis, on the other hand, is primarily employed to estimate the empirical relationship between measured parameters and to predict geo-engineering properties. This technique is typically used to estimate the in-situ modulus of deformation and strength parameters from CPT, SPT, and PMT results. The proposed formulas in this paper used regression to correlate and characterize coastal alluvium located in phase 14 South Pars (Assalouyeh) and were compared with previously published equations. As a result of the evaluations, the correlations provided for phase 14 South Pars can be expressed as Em = 0.442 qc + 2.221 (R2 = 0.999) and PL = 0.06 Em0.778 (R2 = 0.515).•This empirical method can be useful for ground assessment and estimating the in-situ modulus of deformation.•This relationship can use as a modification for the original formula used based on CPT-PMT-SPT for alluvium.•This empirical correlation provides fast and reliable data for Southwest Iran nearby the Persian Gulf.

Factors influencing correlations between CPT and DPH

AbstractDespite the widespread availability and superior information provided by the cone penetration test (CPT), dynamic probes like the DPH (dynamic probe heavy) remain an important soil investigation method under certain circumstances. In order to make use of the results of the DPH in the context of the vast body of interpretation and design methods developed for CPT tests, the drop count N10 of the DPH is correlated to the tip resistance qc of the CPT. There are numerous correlations between both values available in the standards and in the literature. However, any soil‐related differences, limitations, and factors influencing those correlations are not necessarily obvious. The present paper presents a simple framework for the illustration of influencing factors and the interpretation of correlations between DPH and CPT. The proposed framework is based on the information provided in EN ISO 22476‐1 and published scientific literature. Linear correlation factors based on the proposed framework are derived. These factors are then compared with our own field data and information from the literature.

Correlation between SPT and CPT for Sandy Soils in Port Sudan City using the Linear Regression Model

In geotechnical engineering, in-situ tests, like standard penetration test (SPT) and cone penetration test (CPT), are essential to evaluate the underground conditions. SPT is a frequently used geotechnical approach, while CPT is considered one of the best exploration apparatuses. However, there is a demand for a correlation of SPT-CPT that can be used in the geotechnical design. This research aimed to find the relationships between the standard penetration test’s blow count (N) and cone penetration test’s tip resistance (qc) for different groups of sandy soils in Port Sudan city, Sudan. The data used in this study was attained from numerous projects conducted in the city to identify the underground conditions. The values of the SPT and CPT tests were compared and tried to generate specific statistical data. The correlations were established between qc and N for various soils. Uphill linear relationships wear found between qc and N for different sandy soils. These results were interpreted based on their correlation coefficients. The study proposed formulas to predict qc from N for three soil groups, with a high correlation coefficient. Besides, qc/N ratios were calculated for different soil groups; the current research results agree with those in the published literature with less high values.

SHALLOW FOUNDATION BEARING CAPACITY ANALYSIS BASED ON CONE PENETRATION TEST

In the simple buildings, shallow foundations can be used to support the construction above them. This shallow foundation has various types, including the type of footplate which can be calculated using the Terzaghi equation. In the Terzaghi equation, it requires dimension parameters of the footing and soil material parameters such as cohesion and soil volume weight which requires laboratory testing to obtain it. Meanwhile, Schmertmann provides an equation to obtain the Terzaghi bearing capacity factor in the form of Nq and Nγ by using the Cone Penetration Test (CPT). This bearing capacity factor value can be used to calculate the bearing capacity using the Terzaghi Equation. In addition, Schmertmann also provides an equation to directly calculate the bearing capacity value based on CPT data. Based on this problem, this study analyzes the bearing capacity of various footplate dimensions using the Schmertmann approach. The study took place in the Argoboga, Salatiga which the type of soil based on the CPT test value generally is sandy soil. The results show that the bearing capacity calculated by the Nq correlation method is greater than the Nγ correlation method and the direct correlation method. In addition, the greater the difference between the dimensions and the depth of the foundation, the greater the deviation of the bearing capacity results between each method.

Estimation of standard penetration test value on cohesive soil using artificial neural network without data normalization

Artificial neural networks (ANNs) are often used recently by researchers to solve complex and nonlinear problems. Standard penetration test (SPT) and cone penetration test (CPT) are field tests that are often used to obtain soil parameters. There have been many previous studies that examined the value obtained through the SPT test with the CPT test, but the research carried out still uses equations that are linear. This research will conduct an estimated value of SPT on cohesive soil using CPT data in the form of end resistance and blanket resistance, and laboratory test data such as effective overburden pressure, liquid limit, plastic limit and percentage of sand, silt and clay. This study used 242 data with testing areas in several cities on the island of Sumatra, Indonesia. The developed artificial neural network will be created without data normalization. The final results of this study are in the form of root mean square error (RMSE) values 3.441, mean absolute error (MAE) 2.318 and R2 0.9451 for training data and RMSE 2.785, MAE 2.085, R2 0.9792 for test data. The RMSE, MAE and R2 values in this study indicate that the ANN that has been developed is considered quite good and efficient in estimating the SPT value.

Treatment of Liquefiable Soils by the Ballasted Column Technique: Case of Martil River Bridge in the North of Morocco

The seismic activity in northern Morocco is largely due to an intense tectonic activity Plio-Quaternary and current generated by the approach of the two lithospheric plates Africa-Eurasia. Certainly, the liquefaction of soils is a phenomenon that presents a potential risk and a major challenge for the construction of foundations of engineering structures. The objective of this work is the realization of test plates to decide on adequate treatment in a soil liquefiable. For our case during the construction of a double bridge on a liquefiable soil and in a seismic zone, we were confronted with two technical problems, on the one hand the choice of the method of treatment of the soil in place and on the other hand the verification of this improvement by the results of the CPT tests (Cone Penetration Test) carried out before and after the densification of the soil. Many types of liquefaction remediation methods have been developed. However, for our case, the results indicate the effectiveness of the vibrocompaction method in improving the in-place soil compared to the dry method in eliminating the risk of soil liquefaction. It should be noted that the wet columns were lowered to 22m/TN, and the dry columns were stopped at varying depths between 2 and 14m/TN, and the results of the CPT (Cone Penetration Test) confirm the effectiveness of vibrocompaction and that the bridge foundations are protected against the phenomenon of soil liquefaction.

Comparison of California Bearing Ratio (CBR) Value Based on Cone Penetration Test (CPT) and Dynamic Cone Penetrometer (DCP)

In civil engineering, land is important because as a place for building infrastructure to be built, so that the building infrastructure on it is stable, adequate carrying capacity is needed. The amount of soil bearing capacity can be determined in several ways, including the California Bearing Ratio (CBR) Field Test, Cone Penetration Test (CPT) and Dynamic Cone Penetrometer (DCP). The CBR and DCP tests are often used to determine the level of surface soil density on road structures, while CPT is usually used to determine the hard soil layer on the building structure. However, in certain situations Sondir and DCP data are often used to predict the CBR value, because the test is quite practical and efficient compared to the CBR test. CBR testing requires heavy equipment which in most small-scale projects is not available. In this study, we compared the CBR value based on the data obtained from the Sondir and DCP tests. Data collection was carried out in Surakarta and its surroundings. Based on the test results, the CBR value generated from the DCP test tends to be smaller than that from the CPT test with a ratio of 0.62: 1. This study resulted in the relationship between CBR values from the results of the CPT and DCP tests shown in the following equation: CBR (DCP) % = 0.2552 CBR(CPT) + 2.6306 and CBR (DCP) % = 0.617 CBR(CPT).

The Identification of the Uncertainty in Soil Strength Parameters Based on CPTu Measurements and Random Fields.

The present paper responds to the challenge of modeling uncertainty in soil strength parameters concerning its spatial variability in a situation of limited soil information. Understanding this uncertainty allows for the management of the risk of geotechnical structure failure. In the present work, this uncertainty is identified based on signals from the cone penetration test (CPT) device. Signals are directly transformed using existing interpretation methods (typically used as a source of mean values of parameters for a given range of depths) to obtain depth-varying effective strength parameters of the soil. The process is performed by incorporating data from two case studies from different locations in similar soil materials. First, Keswick clay from Australia, for which the results of both CPT and laboratory tests are available, is examined. Second, to further verify the obtained results, the soil from Poland called Świerzna clay, for which only CPT signals were available, is also tested. As shown, the variability of the transformed signals can be a good source of information for identifying uncertainty in soil strength. It agrees well with literature data and can be used to identify random fields describing soil parameters.

Prediction of standard penetration test value on cohesive soil using artificial neural networks

Soil investigation is the main key in starting construction. Standard Penetration Test (SPT) and Cone Penetration Test (CPT) are field tests often used to estimate soil parameters for foundation design purposes. The SPT value (N-SPT) shows a correlation between the CPT value and other soil parameters. At present, there have been many conventional correlations examining these correlations, but the nonlinear nature of the soil due to very complex soil formations means that this correlation cannot be used in all situations. This research aimed to predict the value of SPT on cohesive soil based on CPT test data and soil physical properties using artificial neural network capabilities using the Backpropagation algorithm, and the activation function was bipolar sigmoid. This study used 284 data from several places in Sumatra Island, Indonesia, with data input were tip resistance, shaft resistance, effective overburden pressure, percentage of liquid limit, plastic limit, sand, silt, and clay. The results showed that the training data of RMSE was 3.441, MAE and R2 were 0.9451 and 2.318, respectively while test data showed RMSE, MAE, R2 were 2.785, 2.085, and 0.9792, respectively. It means that the proposed artificial neural network NN_Nspt(C) was promising to predict the N-SPT value with a minimum error value and a strong regression equation.

Learning decision boundaries for cone penetration test classification

AbstractIn geotechnical field investigations, cone penetration tests (CPT) are increasingly used for ground characterization of fine‐grained soils. Test results are different parameters that are typically visualized in CPT based data interpretation charts. In this paper we propose a novel methodology which is based on supervised machine learning that permits a redefinition of the boundaries within these charts to account for unique soil conditions. We train ensembles of randomly generated artificial neural networks to classify six soil types based on a database of hundreds of CPT tests from Austria and Norway. After training we combine the multiple unique solutions for this classification problem and visualize the new decision boundaries in between the soil types. The generated boundaries between soil types are comprehensible and are a step towards automatically adjusted CPT interpretation charts for specific local conditions.

Koni Penetrasyon Testi (CPT) İle USCS Zemin Sınıfının Belirlenmesi ve Değerlendirilmesi

In all geotechnical studies the classification of soil is important both for correct foundation design and prediction of soil behavior. In practice, determination of the soil class can be carried out by drilling or research pit works in the field. Besides, approaches to determine of soil classes from Cone Penetration Test (CPT) data are used. This study was carried out to correlate the predicted USCS soil groups by CPT tests with actual test results which were carried out on the samples taken from field. For this purpose, 15 exploration drillings and 15 CPT test data which were carried out on an alluvial soil were used. The results obtained by the experimental data on the samples taken from the research drillings were compared with the soil classes by CPT tests and correlated together. The findings revealed that the experimentally determined soil classes are considerably different from the soil classes determined by CPT end resistance values. The CPT method, which is insufficient to determine the plasticity of the soil, caused the SM group to be defined as “Sand – Clay”. Same situation was evaluated for SC group it was observed that CPT data were defined this group as “Clay”. This clearly demonstrates that soil classes that cannot be identified by in-situ sampling can lead to erroneous evaluations.

Numerical simulations of cone penetration in cemented sandstone

In this study, three-dimensional simulations of cone penetration tests (CPT) in cemented sandstone have been investigated using the Discrete Element Method (DEM). We generated the realistic grain size distribution of sandstone in the numerical simulations using the Ustyurt-Buzachi Sedimentary Basin samples. Numbers of numerical CPT tests at different bond strength values were performed with the penetrometer vertically moved down at a constant rate. The results of the real-world particle size distribution show that the cone penetration resistance and side friction increase with increasing depths; and with increase in bond strength the cone resistance and side friction decrease, while the friction ratio increases. The result of numerical CPT tests in cemented sandstone was found to be in good agreement with the Soil Behaviour Type (SBT) classification system from CPT data.

Generation and evaluation of synthetic cone penetration test (CPT) data using various spatial interpolation techniques

The cone penetration test (CPT) has been widely used in many geotechnical engineering applications, including soil identification and classification, and evaluation of different soil properties. However, the uncertainties associated with site variation are typical characteristics of subsurface soil conditions that cannot be ignored. Therefore, the effect of site variability on the correlated soil properties from collected field data, such as CPT data, obtained from discrete locations across the site needs to be evaluated. In this study, six well-established spatial interpolation techniques — ordinary kriging (OK), simple kriging (SK), universal kriging (UK), inverse distance weight (IDW), spline, and natural neighbor (NaN) — were investigated to evaluate the best interpolation method for incorporating site variability. Six CPT test sites were used to evaluate the performance of these spatial interpretation methods. For each site, CPT profiles at specified locations were generated using the different interpolation techniques, and the generated CPT profiles were compared with the measured CPT profiles. The best-fit line of measured versus predicted cone tip resistance (qc) values, mean bias factor (λ), coefficient of variation (COV), and root mean square error (RMSE) were calculated for each CPT profile and used as a criteria for evaluating the different spatial interpolation methods. The results of this study demonstrated the ability of these spatial interpolation methods for generating CPT profiles with good accuracy. The slope of best-fit line of measured versus predicted qcranges from 0.93 to 0.95, the mean of λ ranges from 0.90 to 0.98, and the COV ranges from 0.34 to 0.53. The IDW, OK, and SK showed the best spatial interpolation methods (in order) for four out of the six CPT sites. For site 4, OK, IDW, and SK showed the best spatial interpolation methods (in order); while for site 5, the three best spatial interpolation techniques are SK, IDW, and OK (in order).