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The simulation of granular soil using advanced soil models relies on the precise determination of model parameters from laboratory or field experiments, or both. Although it is well known that sample reconstitution influences the stress–strain response of granular soil, the effect of different reconstitution methods on the calibration of advanced soil models has not been previously comprehensively addressed. In the present study, a hypoplastic model was calibrated from geotechnical laboratory tests on Cuxhaven sand samples. Triaxial tests were performed on samples having been reconstituted by three different methods: moist tamping, vacuum pluviation, and horizontal vibration. The influence of different reconstitution methods on the simulation performance of the hypoplastic model was quantified through three scenarios of increasing complexity: (1) stress–strain behavior in representative element volume (REV), that is, triaxial tests; (2) in situ plate load test (PLT); and (3) laboratory cone penetration test (CPT). The latter two are typical examples of boundary value problems with different strains and stiffnesses. The adopted reconstitution methods significantly affected the REV simulation at high relative density of both peak friction angles and peak dilation angles. The reconstitution methods have a limited effect on boundary value problem simulations, being moderate for PLTs and small for CPTs. The influence of stiffness (intergranular strain) parameters on simulation results increased from REVs (no influence detected), over boundary value problems with low strain and stiffness (PLTs) to boundary value problems with high strain and stiffness (CPTs). [ABSTRACT FROM AUTHOR]

Design of piles in chalk is considered as an important issue for a number of geotechnical applications in Northern Europe. Few methods exist for predicting the ultimate axial pile capacity in chalk, but little guidance can be found regarding the design of driven piles in this complex material as experience is rather limited. This paper aims to study the short and long-term predictive performance of different pile design methods used in France and the UK where chalk is found widespread in the north-west coast and the south-east coast, respectively. Conventional methods used in France and the UK are compared by considering seven full-scale static load tests performed in Paris Basin and extracted from the LCPC pile database. The ratio of the measured vs calculated pile shaft resistance and base resistance value is analysed and the scatter of each method is studied. The comparison shows large differences between results. Extension of the database is of great importance to improve the predictive reliability. The last part discusses the evolution of the long-term capacity of driven piles in chalk due to ageing effects. Results show an increasing trend after driving, following a hyperbolic evolution curve. [ABSTRACT FROM AUTHOR]

The assessment of pile drivability is the premise of successful pile installation, and completely weathered (CW) rock may bring the risk of pile refusal. This paper presents a case of pile driving refusal that occurred in a CW gneiss layer. The physical and mechanical properties of the CW gneiss are analyzed based on the results of a laboratory test, a cone penetration test (CPT), and a standard penetration test (SPT). By comparing the properties of CW gneiss with those from intact gneiss, the CW gneiss layer in this study was found to be soil-like. Additionally, it is a sand-like layer according to CPT-based soil classification systems. The soil resistance to driving (SRD) in pile driving was calculated with different methods for sand and compared with the SRD inferred from the pile-driving records. The results show that the modified Fugro's method assuming a fully plugged condition may provide good pile drivability assessment in this study. It was found that it is necessary to determine the properties of the CW rock layer reasonably before conducting pile driving analysis, and a framework is proposed for analyzing the pile drivability in a CW rock layer based on this case study. [ABSTRACT FROM AUTHOR]

Cone Penetration Testing (CPT) is a quick survey in situ method through which soil parameters are not determined directly, but have to be estimated using derived relations between required soil parameter and soil resistance at the testing probe. Boundary conditions affect the reliability of the estimated soil parameters, therefore controlled laboratory conditions were applied to the intended CPT procedure analysis. Density, pycnometry, oedometer and direct shear tests of kinetic sand were performed to prove its usability as a reference testing material for further CPT laboratory analysis. The results of testing the kinetic sand are presented in this paper. Executed tests proved the kinetic sand as a reliable material in terms of the homogeneity and consistency of its physical and mechanical parameters. The material is utilizable as a substitution of cohesive sandy soils in physical modeling without the negative impact of the consistency-dependent behavior of fine-grained soils. However, some differences in parameters with respect to the natural soils should be taken into account. Neural network theory and numerical approach will be applied to the intended CPT laboratory analysis under controlled boundary conditions using kinetic sand to evaluate its potential for the determination of soil parameters. [ABSTRACT FROM AUTHOR]

Tidal forcing influences groundwater flow and salt distribution in shallow coastal aquifers, with the interaction between sea level variations and geology proving fundamental for assessing the risk of seawater intrusion (SI). Constraining the relative importance of each is often confounded by the influences of groundwater abstraction and geological heterogeneity, with understanding of the latter often restricted by sampling point availability and poor spatial resolution. This paper describes the application of geophysical and geotechnical methods to better characterize groundwater salinity patterns in a tidally dominated ~ 20 m thick sequence of beach sand, unaffected by groundwater abstraction. Electrical resistivity tomography (ERT) revealed the deposit to consist of an upper wedge of low resistivity (< 3 Ωm), reaching over 8 m thick in the vicinity of the low water mark, overlying a higher resistivity unit. Cone penetrometer testing (CPT), and associated high-resolution hydraulic profiling tool system (HPT), coupled with water quality sampling, revealed the wedge to reflect an intertidal recirculation cell (IRC), which restricts freshwater discharge from a relatively homogeneous sand unit to a zone of seepage within the IRC. The application of CPT and HPT techniques underscored the value of geotechnical methods in distinguishing between geological and water quality contributions to geophysical responses. Survey results have permitted a clear characterization of the groundwater flow regime in a coastal aquifer with an IRC, highlighting the benefit of combining geophysical and geotechnical methods to better characterize shallow SI mechanisms and groundwater flow in coastal hydrogeological environments. [ABSTRACT FROM AUTHOR]

This paper presents different CPT methodologies for the prediction of the pile shaft resistance in tension on the example of three reference screw piles of the Jazowa test site in Poland. The shaft capacity was estimated based on the cone resistance, sleeve friction and CPT excess pore water pressure. Three piles with a diameter of 0.4 m and the length varied from 8 m to 14.6 m were subjected to static load tests in tension. Their results were used to determine the ultimate bearing capacity of the reference piles. The pile shaft resistance was estimated according to the AFNOR standard, Doan and Lehane 2018 centrifuge tests based method (Delft University of Technology approach), the Modified Unicone method, KTRI (Kajima Technical Research Institute) and LCPC (Laboratoire Central des Ponts et Chaussées) method. Then, the ultimate bearing capacity determined in static load tests was compared to the estimated values according to five different methods. The best estimation, fitting almost perfectly to static load test values, was obtained with the AFNOR method, whereas the other predictions significantly underestimated the ultimate bearing capacity. [ABSTRACT FROM AUTHOR]

During the estimation of pile strength ( R t ), a parameter is utilized called pile set-up parameter (A ). The value of this parameter was so controversial because it relates to many factors, such as the material of pile, the resistance of pile, type of pile, dimension of pile, and type of soil. So, developing prediction models based on neural networks could solve this matter. Therefore, this study aimed to develop hybrid random forest (RF) models to predict the pile set-up parameter (A ) from cone penetration test (CPT) for the design aim of the projects. To this goal, the essential hyperparameters of the RF model were tuned by applying the whale optimization algorithm (WOA) and Harris hawks optimization (HHO). The selected variables as input were average corrected cone tip resistance, average skin friction, and average overburden pressure. Results show that both models have acceptable performance in predicting the set-up parameter A , with coefficient of determination ( R 2 ) larger than 0.8699, representing the admissible correlation between observed and predicted values. It is understandable that, in both the learning and validating phase, HHO-RF has better proficiency than the WOA-RF model, with R 2 and root mean square error (RMSE) equal to 0.9436 and 0.0307 for the training phase, and 0.8866 and 0.0371 for testing data, respectively. Moreover, by considering all performance accuracy criteria, the results demonstrate the ability of the HHO algorithm in determining the optimal value of RF hyperparameters than WOA. [ABSTRACT FROM AUTHOR]

As one of the arbitrary Lagrangian–Eulerian methods, the material point method (MPM) owns intrinsic advantages in simulation of large deformation problems by combining the merits of the Lagrangian and Eulerian approaches. Significant computational intensity is involved in the calculations of the MPM due to its very fine mesh needed to achieve a sufficiently high accuracy. A new multiple‐GPU parallel strategy is developed based on a single‐root complex architecture of the computer purely within a CUDA environment. Peer‐to‐Peer (P2P) communication between the GPUs is performed to exchange the information of the crossing particles and ghost element nodes, which is faster than the heavy send/receive operations between different computers through the infiniBand network. Domain decomposition is performed to split the whole computational task over the GPUs with a number of subdomains. The computations within each subdomain are allocated on a corresponding GPU using an enhanced "Particle‐List" scheme to tackle the data race during the interpolation from associated particles to common nodes. The acceleration effect of the parallelization is evaluated with two benchmarks cases, mini‐slump test after a dam break and cone penetration test in clay, where the maximum speedups with 1 and 8 GPUs are 88 and 604, respectively. [ABSTRACT FROM AUTHOR]

The discrete element method (DEM), a discontinuum-based method to simulate the interaction between neighbouring particles of granular materials, suffers from intensive computational workload caused by massive particle numbers, irregular particle shapes, and complicated interaction modes from the meso-scale representation of the macro information. To promote the efficiency of the DEM and enlarge the modelling scales with a higher realism of the particle shapes, parallel computing on the graphics processing unit (GPU) is developed in this paper. The potential data race between the computing cores in the parallelisation is tackled by establishing the contact pair list with a hybrid technique. All the computations in the DEM are made on the GPU cores. Three benchmark cases, a triaxial test of a sand specimen, cone penetration test and granular flow due to a dam break, are used to evaluate the performance of the GPU parallel strategy. Acceleration of the GPU parallel simulations over the conventional CPU sequential counterparts is quantified in terms of speedup. The average speedups with the GPU parallelisation are 84, 73, and 60 for the benchmark cases. [ABSTRACT FROM AUTHOR]

In this study, two hybrid metaheuristic models are developed to discover the applicability of using an optimized radial basis function neural network to predict the undrained shear strength (USS) from cone penetration test (CPT) records. To this aim, genetic algorithm (GA) and grey wolf optimization (GWO) were integrated with radial basis function (RBFNN), named GA-RBFNN and GWO-RBFNN, to determine the optimal determinative parameters of RBFNN. Models trained with five input variables named cone tip resistance, sleeve friction, liquid limit, plastic limit, and overburden weight. To assess the precision of developed models, four statistical performance indices (R2, RMSE, MAE, and PI) were considered. The results demonstrate powerful potential in the learning section as well as approximating in the testing phase. It means that the correlation between observed and predicted USS from hybrid models is acceptable to represent the high accuracy in the training and approximating process. Concerning developed RBFNN models, it can be observed that GWO-RBFNN has better performance than GA-RBFNN based on evaluating the performance evaluator indices. Based on the outline of this paper aimed at finding RBFNN optimal parameters with optimization algorithms, GWO is more capable and rapid than GA for determining these parameters. Therefore, GWO-RBFNN outperforms the GA-RBFNN model with a total ranking of 16, consequently being recognized as the proposed model.

Conventional soil classification methods are expensive and demand extensive field and laboratory work. This research evaluates the efficiency of various machine learning (ML) algorithms in classifying soils based on Robertson’s soil behavioral types. This study employs 4 ML algorithms, including artificial neural network (ANN), random forest (RF), support vector machine (SVM), and decision trees (DT), to classify soils from 232 cone penetration test (CPT) datasets. The datasets were randomly split into training and testing datasets to train and test the ML models. Metrics such as overall accuracy, sensitivity, precision, F1_score, and confusion matrices provided quantitative evaluations of each model. Our analysis showed that all the ML models accurately classified most soils. The SVM model achieved the highest accuracy of 99.84%, while the ANN model achieved an overall accuracy of 98.82%. The RF and DT models achieved overall accuracy scores of 99.23% and 95.67%, respectively. Additionally, most of the evaluation metrics indicated high scores, demonstrating that the ML models performed well. The SVM and RF models exhibited outstanding performance on both majority and minority soil classes, while the ANN model achieved lower sensitivity and F1_score for minority soil class. Based on these results, we conclude that the SVM and RF algorithms can be integrated into software programs for rapid and accurate soil classification.

In engineering practice, properly characterizing the spatial distribution of soil liquefaction potential and induced surface settlement is essential for seismic hazard assessment and mitigation. However, geotechnical site investigations (e.g., cone penetration test (CPT)) usually provide limited and sparse data with high accuracy. Geophysical surveys provide abundant two-dimensional (2D) data, yet their accuracy is lower than that of geotechnical investigations. Moreover, correlating geotechnical and geophysical data can effectively reduce site investigation costs. This study proposes a data-driven adaptive fusion sampling strategy that automatically develops an assessment model of the spatial distribution of soil liquefaction potential from spatially sparse geotechnical data, performs monitoring of liquefaction-induced settlement, and integrates spatiotemporally unconstrained geophysical data to update the model systematically and quantitatively. The proposed strategy is illustrated using real data, and the results indicate that the proposed strategy overcomes the difficulty of generating high-resolution spatial distributions of liquefaction potential from sparse geotechnical data, enables more accurate judgment of settlement variations in local areas, and is an effective tool for site liquefaction hazard analysis.

At present, there is no commonly used method for predicting soil resistance to the driving (SRD) of monopiles, because all available methods are developed based on an installed offshore pile with a diameter of 2–3 m. In addition, due to the complexity of soil profiles in situ, the accuracy of methods used is often not stable under different soil conditions. Based on two typical stratified soil conditions of offshore wind farms in the East China Sea, which are clay-interlayered sand and sand-interlayered clay where, according to the pile driving records of the monopiles in sites, the SRD is obtained by back analysis using the method of the wave equation. At the same time, SRD is also calculated using Steven and Alm methods and compared with that of the back analysis. The results show that the SRDs from the Steven and Alm methods are basically consistent with that of the back analysis, but the predicted SRD of the clay layer is higher than that of back analysis, while the predicted SRD of the sand layer is lower. Based on the characteristics of SRD in different soil layers, a modified method for calculating unit friction in clay and the unit end resistance in sand is proposed for stratified soil, and the error between SRD of the proposed method and of the back analysis was approximately 20%. It could be helpful to improve the accuracy of the monopile drivability analysis in stratified soil.

A probabilistic cone penetration test (CPT) based liquefaction triggering procedure for cohesionless soils is derived using a maximum likelihood method with an updated case history database. The liquefaction analysis framework includes revised relationships for the magnitude scaling factor (MSF) and for estimating fines contents from CPT data when laboratory test data are not available. The updated case history database and methodology for developing the liquefaction correlation are described. Measurement and estimation uncertainties, the potential effects of false positives and false negatives in the case history database, and the effects of the choice-based sampling bias in the case history database are accounted for. Sensitivity analyses showed that the position of the most likely triggering curve and the magnitude of the total error term are reasonably well constrained by the data. The sensitivity study provides reasonable bounds on the effects of different interpretations, from which probabilistic and deterministic relationships for practice are recommended.

A series of centrifuge shake table tests were carried out to investigate liquefaction resistance of sand deposits with different fines content. The effects of clayey fines on the generation and dissipation of excess pore water pressure, acceleration record, surface settlement, and stress-strain behavior were investigated. It was found that for the same initial relative density, liquefaction resistance increased as fines content increased from 0% to 10% and then decreased with a further increase in fines content from 10% to 20% in the centrifuge tests. For all tests, a reduced acceleration within the soil was observed after a certain number of cycles due to the onset of liquefaction. Dilative tendencies are different for all tests, but the sand with 10% clay test showed the most obvious dilative behavior during the cyclic mobility stage. The total ground surface settlement and the time for a complete dissipation of excess pore water pressure increased with increasing fines content. Shear strains in the sand deposits increased as the clay content increased from 0% to 20%. Moreover, cone penetration tests were performed before and after shaking to study the effect of fines on penetration resistance. At the same depth across all tests, the penetration resistance before shaking decreased with increasing clay content. However, the penetration resistance after shaking increased with increasing clay content from 0% to 10% and then decreased with increasing clay content from 10% to 20%. When compared with the before-shaking profile, the percentage change in penetration resistance after shaking increased with clay content at the same depth. [ABSTRACT FROM AUTHOR]

For the foundation settlement monitoring and analysis of offshore reclamation project, the instruments such as settlement plate and layered settlement instrument were usually installed to carry out settlement monitoring after backfilling to form land area, however, it is difficult to monitor the settlement caused by the reclamation process. For the main reclamation works of Hong Kong International Airport three runway system project, cone penetration testing (CPT) detection technology was used to assess the interface of different soil layers for the first time, which is used to calculate and analyze the foundation settlement in the process of backfilling construction. This paper provides a new approach to settlement calculation and measurement, and provides valuable references for similar projects. [ABSTRACT FROM AUTHOR]

Potentially habitable icy Ocean Worlds, such as Enceladus and Europa, are scientifically compelling worlds in the solar system and high-priority exploration targets. Future robotic exploration of Enceladus and Europa by in-situ missions would require a detailed understanding of the surface material and of the complex lander-surface interactions during locomotion or sampling. To date, numerical modeling approaches that provide insights into the icy terrain's mechanical behavior have been lacking. In this work, we present a Discrete Element Model of porous planetary ice analogs that explicitly describes the microstructure and its evolution upon sintering. The model dimension is tuned following a Pareto-optimality analysis, the model parameters' influence on the sample strength is investigated using a sensitivity analysis, and the model parameters are calibrated to experiments using a probabilistic method. The results indicate that the friction coefficient and the cohesion energy density at the particle-scale govern the macroscopic properties of the porous ice. Our model reveals a good correspondence between the macroscopic and bond strength evolutions, suggesting that the strengthening of porous ice results from the development of a large-scale network due to inter-particle bonding. This work sheds light on the multi-scale nature of the mechanics of planetary ice analogs and points to the importance of understanding surface strength evolution upon sintering to design robust robotic systems. [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid artificial neural network and mathematical (ANN-MATH) model to improve the prediction capability of the load-settlement behaviour of shallow foundations in sandy soils. The hybridisation process is performed by replacing the conventional activation function of the ANN output layer by a new mathematical model. Thereafter, 110 full-scale loading tests of shallow foundations, carried out in sand with the cone penetration test (CPT) results, are used to build and validate the proposed model. In terms of accuracy, the proposed model shows a high correlation between the predicted results and the measured data. In addition, the proposed method was compared to the available methods in the literature. It was found that the proposed model is superior to classical and artificial intelligence-based methods by more than 29% and 35%, respectively, in terms of root mean square error (RMSE). Furthermore, a parametric study was undertaken to assess the robustness of the proposed model and to derive the bearing capacity factor based on the CPT test. The bearing capacity factor was found close to those recommended by the French standard NF P 94–261. [ABSTRACT FROM AUTHOR]

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Analysis of pile bearing capacity is an important task in the investigation of soil-structure interaction. The paper is dedicated to the prediction methods for the pile bearing capacity calculation based on the cone penetration test (CPTu) results, namely UniCone method, Laboratoire Central des Ponts et Chaussées method (LCPC), and the method involved in the Eurocode 7—2. A set of CFA piles was tested to obtain reference bearing capacity. The ability of the prediction methods to determine the bearing capacity of the pile was investigated. In each evaluation criteria using statistical tools, the methods were ranked based on their performance. The results of the study indicate that the UniCone method is most applicable for the given conditions. The EC 7—2 method showed the largest variability of results, and we do not recommend its application without a deeper analysis. The applicability of any presented method cannot be considered final or universal. It is advisable to use more modern and updated methods which have been developed from a larger database of pile tests. The development of these methods should continue by expanding the database of tested piles together with the application of more advanced rock environment testing procedures.

This study was an investigation of the interaction of loamy sand and clay loam soils with a sweep under field conditions by studying the role of particle shape utilised in a discrete element method (DEM) model of soil-sweep interaction. Beside the soil modelling a validated DEM model of roots present in the soil was developed which highlighted the role of roots in the soil reinforcement. Using the results of field and laboratory tests, layered DEM model of soil structure was improved. In the DEM soil model developed, Young's modulus in the contacts of particles was selected based on oedometric test as 5 MPa in clay loam and 10 MPa in loamy sand soil. A combined calibration process was performed in three different assemblies composed of clumps or spheres, where a DEM model of cone penetration tests' and a soil-sweep DEM model were applied together to confirm the adequate utilisation of layers with different cohesive and frictional parameters. Clumps were utilised for modelling clay loam soil, while for loamy sand spheres were utilised. The geometry of the utilised particles corresponds to the particle assembly coordination number of 9.4 in clay loam and 4.6 in loamy sand which effected comparable quality change in the DEM, based on field test. The model of root for soil–sweep–root interaction was validated by a laboratory shear cut test. The simulation with the developed model showed that breakable roots have a notable influence on draught force, while the number of roots utilised was also an important parameter. • Young's modulus of 5 MPa was utilised for clay loam and 10 MPa for loamy sand soil. • Higher bond strengths on the lower layer with lower friction angle is increase CPR. • CPT to be calibrated with clumps for clay loam and spheres for loamy sand soil. • The DEM model of plant roots was improved and root breaking was implemented. • The soil–sweep–root interaction DEM model has been improved. [ABSTRACT FROM AUTHOR]

Earthquakes occurring over the past decade in the Canterbury region of New Zealand have resulted in liquefaction case-history data of unprecedented quantity. This provides the profession with a unique opportunity to advance the prediction of liquefaction occurrence and consequences. Toward that end, this article presents a curated dataset containing ∼15,000 cone-penetration-test-based liquefaction case histories compiled from three earthquakes in Canterbury. The compiled, post-processed data are presented in a dense array structure, allowing researchers to easily access and analyze a wealth of information pertinent to free-field liquefaction response (i.e. triggering and surface manifestation). Research opportunities using these data include, but are not limited to, the training or testing of new and existing liquefaction-prediction models. The many methods used to obtain and process the case-history data are detailed herein, as is the structure of the compiled digital file. Finally, recommendations for analyzing the data are outlined, including nuances and limitations that users should carefully consider. [ABSTRACT FROM AUTHOR]

Microbially induced carbonate precipitation (MICP) is an innovative approach to strengthening and improving loose porous media. To advance MICP implementation in various geotechnical applications, the work presented herein investigates the distribution pattern of cementation and quantifies the improved material properties through experimental study. Sand was cemented by MICP via a double wall delivery system under submerged conditions and induced spherical flow in a large-scale box. The assessment on MICP-treated sand was conducted using shear wave velocity, hydraulic conductivity, mass of precipitated mineral, and cone tip resistance measurements. Experimental and numerical results were synthesized to evaluate the distribution of MICP with respect to reaction and transport rates. The shear wave velocity and the cone tip resistance were correlated to identify the level of cementation induced in the treated sand. Results included the general cementation pattern of MICP and the level of cementation as affected by induced seepage velocity and density. The relationship between the measured level of cementation, the shear wave velocity, and the cone tip resistance is presented and discussed. [ABSTRACT FROM AUTHOR]

• Field experiments are conducted in a vineyard to estimate soil properties. • Three soil conditions are considered: soft soil, firm soil, and wet saturated soil. • Resistance coefficient and sinkage are evaluated by FEM for different wheel sizes. • The results are analyzed through response surfaces. In this study a 2D FEM model was developed to analyze ruts formation, rolling resistance, and power loss for a grape transporting cart aimed to replace the use of heavy tractors while harvesting grape. The model was supported by experiments in a vineyard in South Italy. Cone penetration tests were conducted to estimate frictional and cohesive properties in three soil conditions: firm, soft, and wet saturated. A tractor pulled test rig for a single wheel was developed to measure rolling resistance and sinkage, and complete the selection of the soil parameters. Completed the model, the analysis was conducted for a range of different wheel dimensions, and the outputs analyzed through response surfaces. The results showed the different impacts that width and diameter have on ruts formation and rolling resistance for different soil conditions. Wider wheels determined a main reduction of the sinkage, while the width contribution to the rolling resistance was affected by the total soil volume deformed. Larger diameters led to lower rolling resistance, with a higher impact on more deformable soils. Contact stress was compared with the thresholds recommended in the literature to determine the acceptable designs. This analysis represents a tool to select the running gear dimensions. [ABSTRACT FROM AUTHOR]

The existing correlations between pile and cone penetration test (CPT) results often lack versatility for silty geomaterials, as they were primarily developed for clays or sands. To establish meaningful correlations, it is essential to understand the geology of the environment under examination. The CPT and its derived parameters, including the Soil Behavior Type (SBT) index, have proven to provide reliable soil information, particularly in the field of pile foundation engineering. This paper presents the findings and interpretations from several pile load tests conducted alongside field cone penetration tests on a Holocene saline interlayered silty formation, a distinct condition encountered in practice. Various CPT-based pile design methods were employed to evaluate pile capacity based on CPT results. As observed, predictions for pile shaft resistance in this geological formation remained consistent across all methods, while notable variations emerged in estimating pile end bearing. This was inferred to be a result of limited research on pile end bearing capacity in the literature, leading to proposals of broad ranges for pile influence zone and toe coefficient values, as well as various CPT tip resistance averaging techniques across different methods. Consequently, to improve accuracy, modifications based on site-specific test data may be necessary. Drawing from the assessments, effective modifications involved considering the SBT index near the pile tip. Subsequently, the current study introduces a new region-specific adjustment to the widely recognized Enhanced Unicone method based on the SBT index, resulting in a more accurate estimate of pile end bearing in such interlayered silty contexts, with less scatter compared to other available approaches. [ABSTRACT FROM AUTHOR]

Accurate determination of the load-penetration behaviour of spudcan footings is vital in predicting the performance of offshore structures. Often, insufficient site investigation data is a limiting factor in assessing spudcan penetration, with the selection of suitable parameters typically derived from triaxial tests or Cone Penetrometer Test (CPT) data. A method is presented for simulating spudcan insertion in loose to medium-dense sand, based on minimal data, whereby the CPT tip resistance is used in combination with known correlations of soil properties, allowing for back analysis of CPT profiles through Large Deformation Finite Element (LDFE) simulation. The use of LDFE allows for failure mechanisms to be determined a priori, as a result of the simulation process, while a range of constitutive models can be implemented as necessary. Friction angle, dilation angle and relative density correlations are combined with a calibration of the elastic modulus, used to develop numerical models based on a set of soil sub-layers, each 1 m in depth. The resulting soil characterisations were used to calculate the load-penetration behaviour of several spudcan geometries (which deviate from conventional spudcan shapes) using the LDFE, to assess their performance. Results generated using the proposed technique show strong agreement with a presented field observations. • The article introduces a method for simulating the insertion of spudcan footings in sand, with limited site investigations. • The method uses CPT cone tip resistance, combined with soil property correlations for Coupled Eulerian Lagrangian simulation. • The results provide an accurate means of predicting the load-penetration behaviour and bearing capacity of spudcan footings. • The method reduces risks such as punch-through failure for unconventional spudcans by using limited geotechnical data. [ABSTRACT FROM AUTHOR]

The coefficient of lateral earth pressure at rest (K 0) is a key state soil variable for the design of foundations and underground structures, characterizes in-situ stress state and soil condition. In this study, a method for the in-situ estimation of K 0 using the cone penetration test (CPT) is proposed considering vertical and inclined cone resistances (q c). For this purpose, a series of laboratory CPTs in a soil chamber were conducted to obtain and characterize vertical and inclined q c values at various inclination angles (θ) and relative densities (D R). It was observed that the values of q c increased as θ increased, which was more pronounced at higher D R. Coupled Eulerian-Lagrangian (CEL) finite element analyses were performed to quantify the values of inclined q c at various cone penetration and soil conditions. Based on results from laboratory CPTs and CEL analyses, a CPT-based K 0 correlation model was established, which was given as a function of vertical and inclined q c values. The model parameter for the proposed method was evaluated and quantified. The validity of the proposed method was confirmed from the comparison with case examples. [ABSTRACT FROM AUTHOR]

The mean annual air temperature in Svalbard has increased between 3 ℃ and 5 ℃ during the last 40 to 50 years. The continuous warming trend observed in Svalbard during the last 30 years has raised concerns about the stability and durability of existing infrastructure on permafrost and uncertainties related to the design of new structures and infrastructure in the region. It is therefore of special interest and importance to establish a reference field site for geotechnical testing in permafrost in Svalbard. Two benchmark sites are established near Longyearbyen, Svalbard (78°13'N, 15°28'E) for geotechnical testing and evaluation of field investigation methods in saline, permafrost soils. These sites, named “Adventdalen” and “UNIS East” based on their locations, form part of the research infrastructure of the Norwegian GeoTest Sites project. Since 2016, efforts have focused on geotechnical and geothermal characterization and instrumentation of the upper 30 m of the soil stratigraphy. Field investigations included drilling and core retrieval, installation of thermistor strings, CPTU, and ERT. Laboratory investigations focused on index testing and the evaluation of soil thermal properties. This paper characterizes soil conditions at these sites and may serve as a reference for others working with saline, permafrost soils.

The relevance of the research is caused by the ever-increasing use of the method of cone penetration tests of soils, changing the requirements for design of foundations in modern construction and revealed significant discrepancy of physical and mechanical characteristics of the soils determined using cone penetration tests according to the tables of SP 11-105 and the data of laboratory tests. The main aim of the research is the comparative analysis between laboratory studies and cone penetration tests in the study area. Objects: soil basement of the foundations of a residential complex in Kazan, Rodina Street. Methods: analysis of domestic and foreign experience, cone penetration tests of soils, laboratory studies of physical and mechanical properties of soils, statistical processing of test results. Results. Using the example of the construction site for a complex of residential 9–25-storey houses in Kazan the authors have shown the impossibility of applying the SP 11-105 tables to determine the mechanical characteristics of a number of soils. This conclusion was made on the basis of processing the results of 125 points of cone penetration tests, passed to a depth of 20 m, drilling of 59 boreholes to a depth of 40 m, as well as laboratory tests of soil samples with determination of strength and strain properties. Comparative analysis of field and laboratory researches for various engineering-geological elements on the study area shown that the values of the strength and strain characteristics of soils obtained using the method of cone penetration test, are significantly overestimated, and the carrying capacity of the piles is underestimated. It is proposed to solve this problem by creating regional building standards in the field of cone penetration tests of soils for Kazan and the Republic of Tatarstan. This will improve the accuracy of engineering and geological surveys and increase the economic profitability of construction.

A national database of detailed 2D data and 1D ground investigation data is being developed for the Dutch sector of the North Sea. The 2D data mostly comprise interpreted results of high-resolution seismic reflection surveys. The ground investigation data typically comprise cone penetration test (CPT) results, S-wave velocity derived from seismic downhole tests, soil sample descriptions, soil sample classifications and results of geotechnical laboratory tests. The availability of public-domain geodata is rapidly increasing, primarily because of a licensing approach in which the Dutch government provides geotechnical and geological data to tenderers for design and operation of wind farms. The increasing availability of geodata provides new interests and opportunities for the apportioning, development and maintenance of offshore and coastal facilities. This paper describes the contents of the geo database. In addition, it discusses opportunities for testing and validation of new methods for site investigation, as well as integration of geophysical data, CPT results and sample data for state-of-the-art mapping and ground modelling purposes.

This paper presents a novel Bayesian machine-learning approach for unsupervised and simultaneous soil stratigraphic interpretation of cone penetration test (CPT) soundings at the site scale. The proposed approach interprets numerous CPT soundings in a joint manner, and it leverages the statistical similarity of the measured sounding data in feature space (i.e., the Robertson chart) and the spatial constraints induced from spatial correlations of the sounding data both vertically along a single CPT sounding and horizontally across multiple soundings in physical space. The mathematical core of the proposed approach consists of the following two parts: (1) a quasi-3D (or 3D axial-symmetric) hidden Markov random field (HMRF) model describing both the statistical and spatial patterns of the CPT soundings; and (2) a model inference process, in which the statistical and spatial patterns are extracted from the dataset using a Bayesian unsupervised learning algorithm. The joint interpretation strategy of the proposed approach facilitates the use of rich statistical information and spatial constraints contained in an ensemble of CPT soundings to enhance the accuracy and consistency of a stratigraphic interpretation at the site scale. The proposed approach has been tested in a real-world case consisting of 44 CPT soundings collected from a geotechnical investigation site. The interpretation results show that the proposed approach can extract the soil spatial and statistical patterns from multiple CPT soundings and significantly increase the accuracy and consistency of the soil stratigraphic interpretation results. [ABSTRACT FROM AUTHOR]

Cone penetration test (CPT) is widely used to explore the in situ soil mechanical properties and the stratigraphy. The numerical simulation of CPT can help understand its mechanical process and link the testing data to soil properties. However, this task is challenging due to multiple (i.e., geometric, material and contact) nonlinearity of the problem. This study extends a large deformation numerical framework, smoothed particle finite element method (SPFEM), to address this problem. A finite element formulation for multibody frictional contact problems is incorporated to deal with the interaction between the steel cone and soil. An explicit stress point integration scheme with substepping is adopted to solve the elastoplastic constitutive equation of soil. The details of the novel numerical procedure are demonstrated. Using the developed approach, parametric studies are conducted for both undrained Tresca soil and fully drained modified Cam-Clay. The correctness and robustness of the proposed approach are validated. For the undrained Tresca soil, a linear relationship between the cone factor N kt and the natural logarithm of rigidity index ln (I r) is confirmed, and then, a new equation for the interpretation of soil undrained shear strength is proposed. For fully drained modified Cam-Clay, the effects of some model parameters and earth pressure coefficient at-rest K 0 on the drained cone factor are elucidated. Direct numerical simulation of CPT with SPFEM can provide an effective approach to determine some key parameters of the soil constitutive model and therefore improve the accuracy of numerical simulation for engineering applications. [ABSTRACT FROM AUTHOR]

Various liquefaction vulnerability indices (LVIs) have been proposed to quantify the severity of liquefaction, and used to create the liquefaction hazard map. In producing the liquefaction hazard map, the spatial variability of LVI is important because the number of available in-situ data is typically limited, and the values at the unmeasured locations are predicted using kriging operations that consider the spatial correlation of observed values. In addition, the liquefaction hazard map may vary significantly depending on how LVI was spatially interpolated. This study aims to evaluate the spatial variability of soil properties based on cone penetration test (CPT) data, and to investigate the changes in geostatistical properties of LVIs depending on shaking intensity. A simplified CPT-based procedure was used to calculate the factor of safety against liquefaction, and the geostatistical properties of LVI according to shaking intensity were evaluated using the parameters of semivariogram. In addition, the LVIs at unmeasured locations were predicted using two geostatistical modeling approaches, and their results were compared to investigate the accuracy of geostatistical approaches in predicting LVIs according to the peak ground acceleration (PGA). [ABSTRACT FROM AUTHOR]

The assessment of pile drivability is the premise of successful pile installation, and completely weathered (CW) rock may bring the risk of pile refusal. This paper presents a case of pile driving refusal that occurred in a CW gneiss layer. The physical and mechanical properties of the CW gneiss are analyzed based on the results of a laboratory test, a cone penetration test (CPT), and a standard penetration test (SPT). By comparing the properties of CW gneiss with those from intact gneiss, the CW gneiss layer in this study was found to be soil-like. Additionally, it is a sand-like layer according to CPT-based soil classification systems. The soil resistance to driving (SRD) in pile driving was calculated with different methods for sand and compared with the SRD inferred from the pile-driving records. The results show that the modified Fugro’s method assuming a fully plugged condition may provide good pile drivability assessment in this study. It was found that it is necessary to determine the properties of the CW rock layer reasonably before conducting pile driving analysis, and a framework is proposed for analyzing the pile drivability in a CW rock layer based on this case study.

It is commonly assumed that dry and saturated sands exhibit similar cone resistance–relative density relationships. Some studies pointed out that partial saturation and calcareous sands with considerable fines content are potential factors affecting these relationships. However, there is experimental evidence in Shaqour Bull Eng Geol Environ 66:59-70, (2006) that clean uncemented quartz sand may exhibit lower cone resistance in saturated conditions. The present study aims on contributing towards better understanding the effect of water saturation on cone resistance in sand. For this purpose, Ticino sand samples were prepared dry and saturated in a calibration chamber and cone penetration tests were performed over a wide range of relative densities and at two consolidation stresses. Overall, it was observed that dry and saturated samples exhibited similar cone resistances. Only slightly higher cone resistances were observed for dry samples at the lower consolidation stress. Two anomalous samples, which were tested dry at medium relative density, were found to exhibit way higher cone resistances than expected from published cone resistance–relative density relationships. The Young's modulus was observed to be proportional to cone resistance and independent of whether a sample was tested dry or saturated, being therefore considered as more robust soil property for cone resistance relationships. [ABSTRACT FROM AUTHOR]

Establishing a soil liquefaction prediction model with high accuracy is a critical way to evaluate the quality of in situ and prevent the loss caused by seismic. In this paper, considering the advantage of cone penetration test (CPT) over standard penetration test (SPT) and the suitability for dealing with the nonlinear problems of the extreme learning machine (ELM), the ELM was tried to train the prediction model. Firstly, seven prediction parameters were analyzed and determined; then 226 CPT samples were divided into the training set and test set; then the parameter of ELM model was assured by comparing the training accuracy and speed of model when setting the number of the neuron of the hidden layer from 5 to 16 and the activation function as sig , sin , hardlim . Finally, the performance of the established ELM model was tested through the test set. The results showed the accuracy of using function sin was 81.43% and 87.50% for the training set and test set, respectively; at the same time, the operation was 1.5055 s which was not much different from other two functions. The prediction model based on CPT perform better than that of SPT and can obtain a highly accurate prediction of 100% for the liquefied case and overall accuracy of 87.5%. ELM was proved to be feasible to be used and developed into the in situ evaluation. [ABSTRACT FROM AUTHOR]

The paper presents the results of a series of Cone Penetration Test CPTu performed near the city of Wroclaw (Poland). The tests were carried out in 13 testing points located in close distance to each other. To verify the results of the penetration tests, fine-grained soil samples from selected depths were taken for laboratory tests. The study focuses on the evaluation of soil type, unit weight, and undrained shear strength cu, and compression index Cc. The grain size distribution of the soil and its mechanical parameters on the basis of a uniaxial compression and an oedometer tests were estimated. A comparison of laboratory and CPTu for selected values is presented. Determination of soil type was carried out on the basis of ISBT and IC values and good agreement with the granulometric composition was found. For undrained shear strength, commonly used correlations based on Nk, Nkt and Nke were adopted. However, the values obtained from the CPT are significantly lower than the results from laboratory tests. Therefore, values of cone factors suitable for investigated soil type and reference test were proposed. In the case of the compression index, the coefficient values ßc and am obtained agreed with those available in the literature. The findings presented in the paper indicate that laboratory tests remain necessary to identify soil properties from CPTu. The presented results are also a contribution to the knowledge of local soil conditions in the Lower Silesia area (Poland). [ABSTRACT FROM AUTHOR]