Cone Penetration Test Research Articles

Geotechnical characterization of municipal solid waste via cone penetration testing - A case study from landfills in Delhi, India.

Geotechnical characterization of municipal solid waste via cone penetration testing - A case study from landfills in Delhi, India.

Large deformation numerical analysis of cone penetration test considering sand state effect

Large deformation numerical analysis of cone penetration test considering sand state effect

UAV-Based Quantitative Assessment of Road Embankment Smoothness and Compaction Using Curvature Analysis and Intelligent Monitoring

Smart construction technology integrates artificial intelligence, Internet of Things, UAVs, and building information modeling to improve productivity and quality in construction. In road embankment earthworks, ground compaction quality is critical for structural stability and maintenance. This study proposes a methodology combining UAV photogrammetry with intelligent compaction quality management systems to evaluate surface flatness and compaction homogeneity in real-time. High-resolution UAV images were used to generate digital elevation models, from which surface roughness was extracted using terrain element analysis and fast Fourier transform. Local terrain changes were interpreted through contour gradient, outline gradient, and tangential gradient curvature analysis. Field tests were conducted at a pilot site using a vibratory roller, followed by four compaction quality assessments: plate load test, dynamic cone penetration test, light falling weight deflectometer, and compaction meter value. UAV-based flatness analysis revealed that, when surface flatness met the standard, a strong correlation was observed, with results from conventional field tests and intelligent compaction data. The proposed method effectively identified poorly compacted zones and spatial inhomogeneity without interrupting construction. These findings demonstrate that UAV-based terrain analysis can serve as a nondestructive real-time monitoring tool and contribute to automated quality control in smart construction environments.

Model study on refined interpretation of internal friction angle of marine soil based on CPTu

The Cone Penetration test (CPT) has become an increasingly widely used and cost-effective method for determining marine soil properties. The internal friction angle, a critical indicator of shear strength, has been predicted from CPT data by numerous studies. However, existing methods for predicting the internal friction angle are prone to significant errors and generalized conditions of use. This study proposes a method for calculating the internal friction angle of various soil types based on CPT data, in conjunction with Soil Behavior Type (SBT) maps, and validates it with experimental data. The reliability and potential applicability of this method are also investigated. The results demonstrate that: (1) Marine sediments in the Ningbo area are predominantly silty clay and muddy clay, with considerable variation in stratigraphic distribution; (2) The internal friction angle of marine soils is generally proportional to grain size and inversely proportional to the SBT index; (3) A new method capable of classifying soils and accurately predicting the angle of internal friction of different soil types is presented; (4) The prediction results show that approximately 91.7% of data points fall within a 30% error margin, and about 72.5% fall within a 15% error margin, significantly outperforming existing models.

A Comparative Analysis of In Situ Testing Methods for Clay Strength Evaluation Using the Coupled Eulerian–Lagrangian Method

The progression of marine resource exploration into deepwater and ultra-deepwater regions has intensified the requirement for precise quantification of the undrained shear strength of clay. Although diverse in situ testing methodologies—including the vane shear test (VST), cone penetration test (CPT), T-bar penetration test (TPT), and ball penetration test (BPT)—are widely utilized for the assessment of clay strength, systematic discrepancies and correlations between their derived measurements remain inadequately resolved. The aim of this work is to provide a systematic comparison of strength interpretations across different in situ testing methods, with emphasis on identifying method-specific biases under varying soil behaviors. To achieve this, a unified numerical simulation framework was developed to simulate these four prevalent testing techniques, employing large-deformation finite element analysis via the Coupled Eulerian–Lagrangian (CEL) approach. The model integrates critical constitutive behaviors of marine clays, specifically strain softening and strain rate dependency, to replicate in situ shear strength evolution. Rigorous sensitivity analyses confirm the model’s robustness. The results indicate that, when the stain rate and softening effects are neglected, the resistance factors from the CPT and VST remain largely insensitive to shear strength variations. However, T-bar and ball penetrometers tend to underestimate strength by up to 15% in high-strength soils due to the incomplete development of a full-flow failure mechanism. As a result, their application in high-strength soils is not recommended. With both the strain rate and softening effects considered, the interpreted strength value Sut from the CPT increases by 13.5% compared to cases excluding these effects, while other methods exhibit marginal decreases of 4–5%. The isolated analysis of strain softening reveals that, under identical softening parameters, the CPT demonstrates the least sensitivity to strain softening among the four methods examined, with the factor reduction ratio Ns/N0 ranging from 0.76 to 1.00, while the other three methods range from 0.65 to 0.88. The results indicate that the CPT is well suited for strength testing in soils exhibiting pronounced softening behavior, as it reduces the influence of strain softening on the measured results. These findings provide critical insights into method-specific biases in undrained shear strength assessments, supporting a more reliable interpretation of in situ test data for deepwater geotechnical applications.

Mechanical Strength of Waste Materials: A Cone Penetration Testing-Based Geotechnical Assessment for the Reclamation of Landfills.

The stability and mechanical properties of municipal solid waste (MSW) deposits in closed landfills are critical for safe land reclamation and infrastructure development. This study employs Cone Penetration Testing (CPT) to evaluate the geotechnical parameters of aged waste at three closed landfill sites in central Poland. Key parameters, including shear strength, internal friction angle, density, and liquidity index, were assessed to determine slope stability and bearing capacity for future redevelopment. Due to the heterogeneous nature of MSW, CPT results were analyzed in conjunction with empirical correlations and nomograms to improve accuracy, so the parameters can be used for future numerical modeling and proposing new computational approaches for landfill body elastic and mechanical behavior predictions. The findings indicate significant variability in landfill waste mechanical properties, influenced by waste composition, decomposition stage, and compaction history. The study highlights CPT's reliable detremination of geotechnical parameters for landfill restoration projects, particularly for infrastructure, creating the potential for green energy and sustainable development. The results contribute to improving engineering practices in landfill restoration and ensuring the long-term stability of post-closure land use. This study also contributes to obtaining reliable results on anthropogenic waste material mechanical parameters at both the material point and at the overall structural scale, benefiting future computational methods and modeling approaches for analyzing structural and geotechnical safety of such complex and demanding structures as landfills.

Application of high-resolution site characterisation tools and sampling methods for assessing microplastic migration beneath MSW dumpsites.

Application of high-resolution site characterisation tools and sampling methods for assessing microplastic migration beneath MSW dumpsites.

Probabilistic soil model for seismic risk assessment based on SDMT results

A geotechnical site investigation has been conducted in the southern breakwater basin of the Port of Barcelona, for which hundreds of in-situ and lab tests have been performed. Among these tests, this study focuses on the evaluation of triple points. That is, at the prospected locations, there are results from seismic dilatometer Marchetti test (SDMT), cone penetration tests (CPTu), and laboratory tests based on soil samples. By using this information, the probabilistic distribution of the dynamic and geometrical properties of the soil profiles can be properly characterized. In this way, eleven closely spaced boreholes have been used to characterise the statistical properties of the input variables. Then, it has been performed a probabilistic generation of one-thousand soil profiles, which are statistically compatible with the data provided by the eleven aforementioned boreholes. Then, it has been analysed how the elastic properties of the generated soil profiles evolve once seismic waves have passed through them. To do so, a large set of ground motion recorded in hard soils have been employed. The main objective has been to obtain mathematical arrangements exhibiting highefficiency to predict parameters that can be used to characterize the nonlinear dynamic response of the soil. This has been achieved by employing bivariate and multivariate analyses in the log-log space. Results show that the soil response can be properly parametrized if considering intensity measures extracted from the ground motions acting at the bedrock level and specific soil parameters. Finally, fragility curves and surfaces have been derived for risk assessment purposes.

Numerical and field study of wick drains performance in soft clay

The Soft soil formations are considered huge challenge for geotechnical engineers worldwide. Soft clay soil usually appears in coastal areas. This paper presents a field case study where the extended soft clay layers were a huge geotechnical challenge. The executed site investigation consists of boreholes and cone penetration tests (CPTu). The upper soft clay extends to depths more than 30m. Many field and laboratory tests were performed. The anticipated stresses due to the proposed structures were high for the existing soft soil deposits. The preloading system with vertical drains was selected as soil improvement system in some wide areas. Field instrumentation measurements were conducted in site during the preloading works. The detailed construction activities performed in the site are presented for two different areas. Both two-dimensional and three-dimensional finite element analyses are performed considering the construction activities for both areas. The results of the finite element analyses are compared with field measurement results. In addition, the final consolidation settlement due to the preloading load is estimated by different methods based on the recorded field measurements. The estimated results of final settlement are compared with the finite element analysis results. The presented results show that the use of preloading and vertical drains in the discussed project was successful and that the finite element analysis predictions were accurate.

Optimizing number, locations, and types of ground investigations for slope stability assessment with value of information analysis

ABSTRACT This study examines the application of Value of Information (VOI) analysis to identify the optimal number, types, and locations of ground investigations for slope safety assessment. VOI analysis integrates a probabilistic slope stability model with uncertain shear strength of clay, a detailed ground investigation model, and a utility function to assess the benefits of reducing uncertainties in soil properties by conducting ground investigations. This study extends earlier VOI approaches for optimising ground investigations by examining not only the optimal number and locations, but also the types of ground investigations. The optimal ground investigations are determined among several common ground investigation methods for estimating undrained shear strength of clay including cone penetration, traxial, uniaxial compression, and vane shear tests. A comprehensive ground investigation model is implemented to realistically evaluate the costs for each of the investigations methods. This was complemented by a detailed assessment of the quality of the investigation methods by accounting for the measurement and transformation errors. The optimal number, locations and types of ground investigations were examined for a range of parameters that can affect outcomes of VOI analyses including the level of prior knowledge on uncertain soil properties, spatial similarity of soil properties, and consequences of slope failures.

BEARING CAPACITY AND FOUNDATION QUALITY OF SUBSOILS IN PARTS OF THE MAIN CAMPUS OF AKWA IBOM STATE UNIVERSITY, IKOT AKPADEN, AKWA IBOM STATE, NIGERIA

The study of the Foundation quality of Subsoils in parts of the main campus of Akwa Ibom State University, Ikot Akpaden, Eastern Niger Delta, Nigeria was carried out with the aim of determining the bearing capacity of the subsoils and designing suitable foundations for the construction of structures. Through field and laboratory investigations carried out, the geophysical study revealed four geo-electric layers namely; the top soil, silty clay, sand, and clayey sand. Six geotechnical boreholes were drilled in the field to a maximum depth of 15m each, with standard penetration tests and cone penetration tests carried out. Soil samples were extracted at 1meters each for different laboratory tests including; moisture content, liquid limit, plastic limit, bulk density, specific gravity, particle size distribution, shear box test, undrained shear strength and Consolidation test. The subsurface stratigraphic profile consists of clayey silty sand (0-7m), sandy silty clay (2-14m) and sand (10-15m) from top to bottom. The clayey silty sand are soft to firm, low to medium compressibility clays with liquid limit, plastic limit and average cohesion values of 23% to 41.5%, 14% to 24% and 14KN/m2 to 64KN/m2 respectively. Ultimate bearing capacity values of the clayey silty sand range from 152.65KN/m2 to 667.94KN/m2. The sandy silty clays are soft, intermediate to high compressibility clays with liquid limit, plastic limit and average cohesion values of 44% to 83%, 25.5% to 51% and 10KN/m2 to 32KN/m2 respectively. Ultimate bearing capacity values of the sandy silty clay range from 269.43KN/m2 to 582.4KN/m2.The sand is poorly graded, medium dense with standard penetration N- values ranging from 13-16. The ultimate bearing capacity ranges from 7878.12KN/m2 to 11423.36KN/m2 respectively. Standard penetration tests and pile bearing capacity analysis indicate that the sands are suitable foundation materials for construction. A Pile foundation terminated within the sand substratum is recommended for large structures.

Adaptive Penetration Unit for Deep-Sea Sediment Cone Penetration Testing Rigs: Dynamic Modeling and Case Study

The reliability and continuity of data are key issues in deep-sea sediment cone penetration testing. Cone penetration testing employs static force to uniformly insert rods into sediment, a process crucial for assessing its mechanics and layering. The clamping manipulator can perform this operation while accommodating sediment sensors of varying types and sizes. However, its requirement to reset post-penetration creates zero-velocity points that diminish test continuity and should be minimized. To address these limitations, this paper proposes a load-adaptive sediment rig that minimizes zero-velocity points, ensures data continuity, and contributes to sedimentology research. This paper analyzes the mechanical properties and layering patterns of sediment, along with the interaction mechanisms between sediment and mechanical structures. Subsequently, a mechanical structure–sediment-integrated model with adaptive control logic is established. Finally, real sediment data are introduced into the physical model for simulation experiments. The simulation results demonstrate that the load-adaptive rig reduces data breakpoints by 50% and increases the maximum single penetration stroke to 1.8 m. Additionally, the load-adaptive rig provides redundancy between penetration force and stroke, automatically reducing penetration force for greater stroke when encountering low-strength sediments and, conversely, sacrificing part of the stroke for greater force. These improvements significantly enhance the continuity of in situ detection data of sediment.

RCPTU evaluation and artificial neural network prediction of diesel contamination in silty clay: a study of resistivity response

Abstract To validate the application of in-situ resistivity cone penetration testing (RCPTU) in assessing organic-contaminated soil sites, correlation analysis was conducted between RCPTU and the Wenner four-electrode method. Soil samples with varying moisture and oil contents were prepared using typical silty clay from Nanjing and 0# diesel for both RCPTU tests and Wenner four-electrode resistivity experiments. The results demonstrate that resistivity decreases with increasing moisture content under constant oil conditions and increases with rising oil content under constant moisture conditions. Diesel-contaminated soil exhibited higher resistivity than uncontaminated soil. The strong linear relationship between RCPTU and indoor four-electrode test results confirms the effectiveness of RCPTU in assessing contaminated sites. Further validation through oil–water adsorption experiments and microscopic analyses revealed that increasing oil content enhances particle encapsulation by diesel, thereby impeding cation transport and altering resistivity. Integrating RCPTU data with artificial neural network models enabled more accurate predictions of diesel concentration in soil, demonstrating the potential of machine learning to enhance prediction precision and efficiency.

Grading Model for Fine Soils Classification Using Cone Penetration Testing

The grading of fine-grained soils is one of fundamental properties, and studying how to obtain this information using in-situ methods is essential. However, existing cone penetration tests (CPT) lack a direct approach for measuring particle size and its content. In order to address that issue, the relationship between cone tip resistance (qc) and sleeve friction resistance (fs) with these curve parameters (CPs) was established using in-situ CPT. Finally, an expression for the grading curves based on the results obtained from the CPT was presented. The main conclusions are as follows: 1) An exponential relationship exists between fine-grained particle content and the variation pattern of fitting parameters used to characterize the grading curve, depending on the soil layer type. 2) The depth-corrected CPs are related to the qc and fs by a power function, revealing a link between the CPT and grading curve; 3) By utilizing global CPT and soil layer data, the boundaries of CPs were precisely defined, and the content of different particle sizes across various soil layers was predicted. The applicability of the fitting results was then analyzed for both homogeneous fine-grained soils and complex soil type.

ON the Numerical Discrete Modeling of a Boundary Value Problem Using an Adaptative Discretization Approach

Abstract An adaptative discretization approach is proposed to build numerical models of boundary value problems with the discrete element method (DEM). It roughly consists of discretizing a domain with small particles within an area of interest (where large displacements, strain localization, grain crushing, … may occur) and coarsening the particle size distribution away from it, while preserving the uniformity of mechanical properties as much as possible, thanks to a proper scaling of the parameters of the contact models. It presents the advantage of limiting the number of particles involved in the model and thus the computational cost. This approach is implemented and evaluated for the modeling of a Cone Penetration Test (CPT) in a calibration chamber.

Soil Bearing Parameters and Settlement Prediction Using CPT Data in Southwestern Nigeria

The study was aimed at deriving important soil parameters relevant to civil engineering construction in schistose quartzite/quartzite dominated soil of RUGIPO, Ondo State, Nigeria, using cone penetration test (CPT). Key engineering parameters’ findings revealed a high degree of overlapping values within the two geological formations. However, both soils are very dense, stiff/hard soil, with a high dominance of coarse particles (sand) over the finer soil matrix (silt). Soil from quartzite has better bearing pressure (avg. 405 kN m-2) than schistose quartzite (324 kN m-2), even above the regional average of 346 kN m-2. The CPT material index with a regional average of 2.40, with schistose quartzite and quartzite showing average values of 2.39 and 2.42, and average soil permeability of 6.19×10-7 m s-1 and 4.498×10-7 m s-1, respectively. The soils have a mean CBR value of 38%, with the CBR of schistose quartzite (35%) less than that of quartzite (42%). The regression models between all the parameters correlated gave positive correlation coefficients, especially CBR and (0.6522), RD and CBR (0.6536), Su and qc (0.9849). The practical implications of the result indicated that both soils are competent for construction (pavement, foundation, and embankment construction) in both geological formations.

Bayesian trans‐dimensional soil behaviour type inference using conditional posterior proposals

ABSTRACTIdentification of subsurface geological profiles is indispensable to geotechnical design and construction. Subsurface stratification through Bayesian inversion of soil behaviour type index data, obtained from cone penetration tests, is achieved through the development of a novel three‐block Markov chain Monte Carlo algorithm. Working in a trans‐dimensional context, where the number of layers, layer depths and soil random field parameters are unknown, the algorithm is able to estimate the range of non‐unique solutions or the uncertainty of these parameters. A blocking strategy has been applied that allows for the development of a formulation that primarily involves computationally inexpensive tasks such as sampling from truncated normal and Inv‐Gamma distributions and evaluation of general normal densities. Part of this strategy involves the design of a novel proposal density for jumping between parameter spaces of different dimensions in the reversible jump Markov chain Monte Carlo applied in the first block. Optimal sampling in trans‐dimensional problems with a single reversible jump Markov chain using random walk Metropolis–Hastings proposals is often difficult and requires ad hoc concatenation of multiple independent chains or sophisticated methods like parallel tempering or delayed rejection. The formulation presented in this study renders the conditional posterior density over the mean of the random field representing the soil parameters to be analytical, thereby allowing the corresponding proposals to be made directly from the conditional posterior. Hence, unlike most other existing algorithms, we avoid random walks altogether by sampling from the conditional posterior distribution directly. The algorithm is validated using synthetic and real soil behaviour type index data from benchmark problems. A standard normality check of the decorrelated residuals is used as a measure to test algorithm performance. Results show that the algorithm is able to identify the soil stratification parameters and random field properties correctly and also identify their uncertainties.

Geoengineering Characteristics of Site Soil Profile Analysis using Cone Penetration Tests Data

Classification and stratification of subsurface soils are critical aspects for a geotechnical site assessment to design and construct geotechnical structures. A probabilistic interpretation method is devised to adequately account for the uncertainty associated with subsurface soil categorization and stratification based on cone penetration test (CPT) data. CPT data is frequently directly employed in the construction of deep and shallow foundations, as well as a range of other purposes. It is advantageous to employ CPT data to create stratigraphic profiles as well, in order to generate more cost-effective designs. The method is demonstrated using CPT data from several locations in the Banda Aceh area. From limited CPT data, the approach accurately identifies subsurface soils in a 2D vertical cross-section. The objectives of this paper are to utilize CPT data to examine the soil profile in Banda Aceh, Indonesia. Additionally, soil parameters must be evaluated to obtain a better knowledge of Banda Aceh's soil conditions. The evaluation indicates that the average depth of the hard layer in the Kuta Alam District ranges from 5 to 8 meters beneath the ground surface. However, at certain locations, the hard soil stratum reaches a depth exceeding 18 meters. The findings are expected to be one source for determining the preliminary soil profile condition in Banda Aceh before doing additional soil investigation for construction design requirements.

Estimating shear strength parameters of a fine-grained alluvial soil using resedimented samples and multivariate regression

The number of studies concerning the shear strength of resedimented alluvial soils is extremely limited compared to the studies conducted on fine-grained marine sediments, since alluvial soils are generally tested in remolded or reconstituted state especially in the studies investigating their liquefaction potential. In this study, estimation models were developed to predict cohesion (c) and internal friction angle (ϕ) parameters of a fine-grained alluvial soil using resedimented samples. A total of 60 undisturbed soil samples were obtained from Bafra district of Samsun province (Türkiye) by core drilling. A cone penetration test with pore water pressure measurement (CPTu) was also carried out alongside each borehole to determine the over-consolidation ratios of the samples. Physical-index property determinations and triaxial tests were conducted on the undisturbed samples. 20 sample sets were created with known physical, index, and strength characteristics. The samples are classified as CH, CL, MH, and ML according to the Unified Soil Classification System, with liquid and plastic limits ranging from 31.6–75% and 19.3 to 33.6% respectively. The c and ϕ values of the samples varied from 4.1 to 46.1 kPa and 26 to 35º respectively. The samples were then resedimented in the laboratory under conditions reflecting their original in-situ properties, and triaxial tests were repeated. The c and ϕ values of the resedimented samples ranged from 5.3 to 24.5 kPa and 28 to 32º respectively. The results indicate that the c values of the resedimented samples are generally lower than those of the undisturbed samples, whereas upper and lower bounds for ϕ values are similar. Multivariate regression analyses (MVR) were utilized to develop estimation models for predicting c and ϕ using strength and physical properties of 20 soil samples as independent variables. Three estimation models with R2 values varying between 0.723 and 0.797 were proposed for c and ϕ which are statistically significant for p ≤ 0.05. Using artificial neural networks (ANN), the estimation models developed by MVR were replicated to validate the models. ANN yielded very similar results to the MVR, where the R2 values for the correlations between c and ϕ values predicted by both methods varied from 0.852 to 0.955. The results indicate that c and ϕ values of undisturbed samples can be estimated with acceptable accuracy by determining basic physical and index properties of the disturbed samples and shear strength parameters of the resedimented samples. This approach, which enables the reuse of disturbed soil samples, can be used when undisturbed soil samples cannot be obtained from the field due to economic, logistical, or other reasons. Further research on the shear strength parameters of resedimented alluvial soils is needed to validate the estimation models developed in this study and enhance their applicability to a wider range of alluvial soils.

Characteristic Shear Strength Parameters Derived from Cone Penetration Test

Characteristic Shear Strength Parameters Derived from Cone Penetration Test