Bearing Capacity Of Piles Research Articles

Geotechnical engineering surveys and soil testing in the construction of buildings and structures

The article suggests a way to increase the efficiency of geotechnical engineering surveys through the rational use of fast approximate methods of soil testing (“express methods”). Such tests are recommended to be carried out in large volume and considered as a means of assessing the geotechnical structure of the site as a whole. In this paper, these issues are considered by the example of determining the bearing capacity of piles according to static sounding data and static tests of full-scale piles. A mathematical model for assessing the information content of the test complex based on the concepts of information theory is proposed. Calculations based on this model show that the informativeness of a large number of approximate tests may (due to the heterogeneity of the soil) exceed the informativeness of a small number of accurate tests.

Influence of the Internal Friction Resistance on the Vertical Compressive Bearing Capacity of Large-Diameter Steel Pipe Piles

Current calculation methods for the vertical bearing capacity of steel pipe piles are predominantly designed for smaller diameters and do not account for the soil inside the pile. This necessitates an evaluation of their applicability to piles with diameters exceeding 2.0 m. This study aims to refine the existing formula for calculating vertical bearing capacity, as outlined in the Port Engineering Foundation Code of China, by investigating the vertical bearing capacity of large-diameter steel pipe piles through numerical simulations. By analyzing the relationship between the internal friction resistance of the soil core within the pipe and the bearing capacity for diameters ranging from 2 m to 10 m, this paper proposes a revised formula specifically tailored for steel pipe piles with diameters greater than 2 m, incorporating the effect of the soil core. The validity of the proposed formula is then confirmed through comparison with field data from four large-diameter steel pipe piles. The results demonstrate that the modified method proposed in this study performs better than the original formula when compared with the measured data.

Analysis of the Vertical Dynamic Response of SDCM Piles in Coastal Areas

The stiffened deep cement mixing (SDCM) pile, as a new type of rigid–flexible composite pile, significantly enhances the vertical bearing capacity of traditional precast piles, thus holding broad application prospects in the substructure construction of nearshore bridges and marine energy structures. This paper investigates the vertical dynamic response of SDCM piles through theoretical derivation and parameter analysis. Firstly, based on elastic dynamics theory and the three-phase porous media model, vertical vibration control equations for both SDCM piles and fractional-order viscoelastic unsaturated soils are established. Secondly, theoretical derivations yield exact analytical solutions for the surrounding dynamic impedance, top dynamic stiffness, and dynamic damping of the SDCM pile. Finally, through numerical examples and parameter studies, the impact mechanisms of physical parameters in the SDCM pile–unsaturated soil dynamic coupling system on the top dynamic stiffness and dynamic damping of the SDCM pile are analyzed. The research results presented in this paper indicate that reducing the radius of the rigid core pile while increasing the thickness of the exterior pile has a positive effect on enhancing its vibration resistance. Additionally, increasing the length of SDCM piles contributes to improved vibration performance. However, an increase in the elastic modulus of the cement–soil exterior pile is detrimental to the vibration resistance of the rigid composite pile. On the other hand, an increase in the elastic modulus of the concrete core pile only enhances its ability to resist vibration under low-frequency load excitation. Furthermore, enlarging the soil saturation, decreasing the intrinsic permeability, and enlarging the soil relaxation shear modulus have a significant positive impact on improving the vibration resistance of SDCM piles. In contrast, changes in porosity have a negligible effect on the ability to resist vertical vibrations of SDCM piles.

Study on Bearing Mechanism of Steel Screw Pile

In order to study the bearing mechanism of a steel screw pile (SSP), a 3D-FEM of “SSP-stratum” was established based on the large-scale general finite element analysis platform ABAQUS. Secondly, the real friction coefficient between pile and soil was determined by comparing it with the field bearing test data of screw piles. Finally, the bearing mechanism and failure criterion of the SSP was revealed. The research showed that the pile-soil friction coefficient was about 0.6 under the condition of this stratum, and the screw pile was in the elastic working stage under the conditions of compression and tension load, which had a large bearing reserve. The magnitude of Young’s modulus was inversely correlated with the settlement value and the extreme value of principal stress. The increase in the Young’s modulus of the stratum was helpful in improving the bearing capacity of the screw pile. The compressive capacity of circular steel tube + screw pile (CST + SP) was about 2 times higher than CST, and the compressive capacity of circular steel tube + large blade + screw pile (CST + LB + SP) was about 2.4 times higher than CST. The tensile capacity of CST + SP was about 3.4 times higher than CST, and the tensile capacity of CST + LB + SP was about 4.9 times higher than CST. The arrangement of large blades better bore the load of the screw part and optimized the stress distribution of the structure. Based on the mechanical analysis in the vertical direction, the bearing mechanism of the SSP under compression and tension conditions was elaborated. The bearing failure criterion of the SSP was summarized from the aspects of mechanics and displacement. The bearing design of the SSP should meet the control of mechanics and deformation at the same time. The research work could provide a useful reference for the design and construction of SSPs.

Bearing Characteristics of Deep Cement Mixing Integrated Drilling, Mixing and Jetting Piles Based on Numerical Simulation

The Deep Cement Mixing Integrated Drilling, Mixing and Jetting (DMJ) technique has been developed through the installation of high-pressure spray holes at the mixing blades, with the objective of enhancing the bearing capacity of deep-mixed piles in the Yellow River floodplain. In order to enhance the bearing capacity of the foundation, variable-modulus piles and capped piles were incorporated within the DMJ piles. Engineering applications have demonstrated that DMJ piles can effectively address the issue of foundation reinforcement in the Yellow River floodplain region, minimize the wastage of cement, and reduce the environmental pollution associated with waste slurry. Nevertheless, a comprehensive study of the relevant factors is still lacking in the available literature. This study addresses this gap by conducting a numerical simulation of these two types of DMJ piles based on the preliminary field test data, with the objective of analyzing both the single-pile-bearing characteristics and the composite foundation-bearing characteristics. Furthermore, the study seeks to optimize the DMJ pile’s structure based on the simulation results. The findings demonstrate that the premature failure of a single pile during the bearing process can be averted if the modulus of the pile core reaches a minimum of 0.3 GPa or if the pile cap thickness exceeds 1 m. The utilization of large-diameter drilling, stirring and spraying piles can markedly enhance the bearing capacity of the composite foundation and mitigate the differential settlement of pile and soil. The spacing of the pile has been identified as a significant factor influencing the differential settlement of pile and soil. Consequently, this study also examines the impact of pile spacing on the differential settlement of piles and soil.

A novel hybrid model for predicting the bearing capacity of piles

Due to the uncertainty of soil condition and pile design characteristics, it is always a challenge for geotechnical engineers to accurately determine the bearing capacity of piles. The main objective of this study is to propose a hybrid model coupling least squares support vector machine (LSSVM) with an improved particle swarm optimization (IPSO) algorithm for the prediction of bearing capacity of piles. The improved PSO algorithm was used to optimize the LSSVM hyperparameters. The performance of the IPSO-LSSVM model was compared with seven artificial intelligence models, namely adaptive neuro-fuzzy inference system (ANFIS), M5 model tree (M5MT), multivariate adaptive regression splines (MARS), gene expression programming (GEP), random forest (RF), regression tree (RT) and a stacked ensemble model. Six statistical indices (e.g., coefficient of determination (R2), mean absolute error (MAE), root mean squared error (RMSE), relative root mean squared error (RRMSE), BIAS and discrepancy ratio (DR)) were used to evaluate the performance of the models. The R2, MAE, RMSE, RRMSE and BIAS values of the IPSO-LSSVM model were 1, 4.27 kN, 6.164 kN, 0.005 and 0, respectively, for the training datasets and 0.9977, 22 kN, 36.03 kN, 0.0275 and –11, respectively, for the testing datasets. Compared with the ANFIS, MARS, GEP, M5MT, RF, RT and the stacked ensemble models, the proposed IPSO-LSSVM model shows high accuracy and robustness on the test datasets. In addition, the sensitivity, uncertainty, reliability and resilience of the IPSO-LSSVM model were also analyzed in this study. First published online 22 October 2024

An Analysis of the Flexural Stiffness and Horizontal Bearing Capacity of CFRP Composite Pipe Piles in Marine Environments

Carbon-fiber-reinforced polymer (CFRP) is a composite material consisting of a resin matrix reinforced with carbon fibers. This study focuses on CFRP composite pipe piles as the subject of investigation, exploring the impact of substituting steel bars with CFRP bars on the bending performance of pipe piles through rigorous three-point bending tests. The attenuation of flexural stiffness in CFRP pipe piles under a chloride salt environment was anticipated. The lateral bearing capacity of CFRP pipe piles was calculated by introducing a stiffness degradation coefficient for the piles and utilizing the finite difference method. The findings of the analysis suggest that as the CFRP reinforcement replacement rate increases, the initial bending stiffness of the composite pipe pile experiences a corresponding decrease. After serving for 28.15 years, the steel reinforcement within the pipe pile commences rusting, resulting in a nonlinear decline in the bending stiffness of the composite pipe pile. As the service time of pipe piles increases, a higher replacement rate of CFRP reinforcement results in a slower attenuation of pile stiffness. Consequently, both the horizontal displacement at the top of the pile and the bending moment along the body of the composite pipe pile gradually increase over time. During the same service period, the higher the rate of CFRP reinforcement, the less noticeable the attenuation in the horizontal bearing capacity of the pile shaft.

Influence of edge scour on lateral responses of monopiles with precast microbial reinforcement

Microbiologically Induced Calcite Precipitation (MICP) technology offers a promising method for stiffness reinforcement of offshore wind turbines (OWTs). However, edge scour around microbial reinforcement raises concerns about potential stiffness degradation. This study examines the effects of edge scour on the lateral responses of rigid piles reinforced with precast microbial reinforcement using a low-pH one-phase grouting method. Results from static tests, validated by numerical simulations, demonstrated that MICP technology bonded loose sand grains with the pile, forming a bio-reinforced pile with a larger diameter in the shallow soil layer, which significantly enhanced the original pile's bearing capacity and stiffness. However, edge scour reduced the embedment depth of the bio-reinforced pile, leading to a decrease in its bearing capacity and stiffness. Geometrically, protection width was found to have a relatively greater influence on stiffness and capacity compared to protection thickness. Additionally, symmetric cyclic loading tests were conducted to evaluate the effects of edge scour on backbone curves, secant stiffness, and damping ratio. Although MICP-based reinforcement notably enhanced both the secant stiffness and damping ratio of the piles, its effectiveness was completely lost once the scour depth reached the reinforcement thickness of the bio-reinforced soil block.

Improving the estimation of the pile bearing capacity via hybridization technique based on adaptive network based fuzzy inference

Improving the estimation of the pile bearing capacity via hybridization technique based on adaptive network based fuzzy inference

Investigation on the Bearing Performance of a Single Pile in Shallow Reinforced Soft Soil Foundation under Horizontal Load

The overall reinforcement of soft soil foundation has the disadvantages of large engineering quantity and high cost. When the pile foundation bears horizontal loads in the soil, the mechanical properties of the soil near the surface have a greater impact on it compared to the deep soil. Therefore, studying the influence of shallow soil reinforcement on the horizontal bearing capacity of pile foundations has important engineering significance. Studying the influence of shallow soft soil reinforcement around piles on the horizontal bearing performance of piles is of great significance for improving the economic efficiency of pile foundation reinforcement technology in soft soil areas. In this paper, seven pile-soil finite element models are established based on ABAQUS 2022 software to study the influence of shallow reinforcement on the horizontal bearing capacity of single pile. The models were established on the basis of a field test and its validity was verified. The influence of different reinforcement degrees on the horizontal bearing capacity of piles is analyzed by taking the reinforcement width and reinforcement depth as variables. The results indicate that shallow ground improvement significantly enhances the horizontal bearing capacity of the pile. The horizontal bearing capacity of the pile is increased by 83.0%, 104.3%, and 224.4%, respectively, corresponding to a reinforcement width of 2 times, 3 times, and 4 times the diameter of the pile, respectively. With the increase of the reinforcement width, the bending moment and deformation of the pile under the same horizontal load decrease significantly, while it has no significant effect on the location of the maximum bending moment of the pile. The bearing capacity of the pile foundation gradually increases with the increase of the reinforcement depth. Compared with the unreinforced situation, the horizontal bearing capacity of the pile body is increased by 224.4%, 361.3%, and 456.8%, respectively, corresponding to a reinforcement depth of 0.1 times, 0.2 times, and 0.3 times the pile length. As the reinforcement depth increases, the corresponding increase in bearing capacity does not increase linearly, but gradually decreases. This indicates that blindly carrying out deep soil reinforcement without comprehensive evaluation is not advisable.

Application of a support vector regression model employing meta-heuristic algorithms for estimating pile bearing capacity

ABSTRACT The design of pile foundations hinges significantly on the pile-bearing capacity (PBC), a crucial factor affected by numerous soil features and parameters. Piles serve as a key component in relocating structural loads to the ground, underscoring the need for accurately determining PBC in geotechnical design. While prior research has delved into utilizing artificial neural networks (ANN) for predicting PBC, they encounter shortcomings such as grappling with finding global minima and slow convergence rates. This study introduces Support Vector Regression (SVR) as a machine-learning approach, augmented by two meta-heuristic optimization techniques: the Giant Trevally Optimizer (GTO) and Smell Agent Optimization (SAO), to achieve optimal results. These techniques empower engineers and data scientists to develop more precise and reliable predictive models in geotechnical engineering, ultimately enhancing the safety and efficiency of foundation design and construction. Drawing upon an extensive dataset compiled from previous studies, a predictive model was constructed to estimate PBC using soft computing techniques. The outcomes overwhelmingly favored the SVGT model, a fusion of the SVR model with GTO, demonstrating excellent anticipative capacities with an outstanding R2 value of 0.998 and an impressively low RMSE value of 91.21.

Bearing performance and failure mechanisms of HSCM piles in marine soft soil under lateral loads

Helix Stiffened Cement Mixing (HSCM) pile represents a novel type of grouted composite pile known for its excellent compressive and tensile performance. Based on field tests, this study introduces a laboratory-based test design methodology and piling technique for HSCM piles. A comprehensive analysis of their horizontal bearing capacity, pile-soil failure mode, optimal piling technique, and reinforcement mechanism is performed. SEM-EDS technology is utilized at a microscopic scale to examine the reinforcement mechanism of HSCM piles. Through ABAQUS finite element simulation, a full-scale model simulating the HSCM pile-soil interaction is developed. The analysis includes pile cross-sectional stress, displacement, and pile-soil failure mode. The p−y curve of the HSCM pile is then plotted, elucidating the reinforcement mechanism of cemented soil. The results indicate that compared to ordinary helical piles, the horizontal bearing capacity of HSCM piles increases by 125.9%. SEM-EDS images reveal that cement and kaolin form a mutual bond, enhancing the strength of the soil around the pile. Additionally, unlike other composite piles, the direction of soil flow around HSCM piles encircles the first helix of the pile core. This research offers a design basis for understanding the horizontal bearing performance and failure mechanisms of HSCM piles in marine soft soil.

A frictional arch model for pile-cap-beam-supported embankment

The pile-cap-beam-supported (PCBS) system can strength the soil arching effect of embankment, increase the lateral stiffness, bending resistance and vertical bearing capacity of the rigid pile, however there is no frictional soil arch model of PCBS embankment. In this paper, first a frictional arch model for PCBS embankment modified from Russell’s frictional arching model was proposed. The proposed model in this paper considers the algorithm of lateral pressure coefficient k and a changing critical height of soil arch. In this new method, the influence of pile spacing, filling properties, height and pile spacing on critical height soil arch was comprehensively considered. Second, a series of numerical cases were performed to verify the effectiveness of the proposed model and study the arching effect of PCBS embankment. By comparing the vertical stress and settlement between the theoretical and simulation results, the rationality of the proposed method to estimate the stress and critical height of arch was validated. The effectiveness of the proposed method was further validated by comparing loading efficacy to a reported case. Last, the stress and deformation of PCBS and pile-cap-supported (PCS) embankment were analyzed and the superiority of PCBS system in improving the performance of embankment was observed finally.

Micro–Macro Assessment of the Pile Bearing Capacity Interaction with Single and Double Voids in Different Soil Densities Using the Discrete-Element Method

Micro–Macro Assessment of the Pile Bearing Capacity Interaction with Single and Double Voids in Different Soil Densities Using the Discrete-Element Method

Experimental and Numerical Simulation Investigations on the Bearing Capacity of Stepped Variable-Section DX Piles under Vertical Loading

Experimental and Numerical Simulation Investigations on the Bearing Capacity of Stepped Variable-Section DX Piles under Vertical Loading

Performance Analysis of Pile Group Installation in Saturated Clay

In offshore pile engineering, the installation of jacked piles generates compaction effects within soil, thus further affecting previously installed adjacent piles. This study proposes a three-dimensional numerical model for pile group installation, soil consolidation, and loading analysis. Subsequently, the effect of pile spacing and pile length-to-diameter ratio on the deformation, internal forces, and vertical bearing capacity of adjacent piles are investigated. The results indicate that with an increase in pile center distance, the peak lateral displacement of the adjacent piles decreases, whereas the peak vertical displacement increases. As the pile length-to-diameter ratio increases, the peak vertical and lateral displacements of the adjacent piles are enhanced. In addition, the peak axial force of the adjacent piles initially decreases and then increases with the penetration depth of the subsequent pile, whereas the peak bending moment initially increases and then decreases. The vertical bearing capacity of the subsequent pile is significantly superior to that of the adjacent piles. Therefore, the effects of pile installation on adjacent piles should be included in pile engineering. The impact of the subsequent pile installation on the bearing capacity of adjacent piles can be significantly reduced by increasing the pile center distance and pile length-to-diameter ratio. The findings provide useful guidance for pile group engineering.

Research on pile bearing capacity prediction improved by grey wolf optimization in the SSA-LSSVM model

Abstract Pile foundations in soft soil often encounter challenges regarding abnormal bearing capacity, significantly impacting the safety of engineering projects. The bearing capacity of pile foundations is influenced by various factors, often characterized by complexity and unpredictability. Therefore, this study proposes a comprehensive model, termed GWOASSA-LSSVM, based on Grey Wolf Optimization (GWO)-enhanced Sparrow Search Algorithm (SSA) and Least Squares Support Vector Model (LSSVM). By introducing a grey wolf hierarchy to enhance the global search capability of the sparrow search algorithm and automating the optimization of parameters (γ, δ) in the LSSVM model using GWO, the GWOASSA-LSSVM predictive model is established. Evaluation metrics including correlation, and correlation between pile bearing capacity and the predictive target are considered, with pile bearing capacity as the predictive target. The GWOASSA-LSSVM model is compared with SSA-LSSVM, LSSVM, and Back Propagation Neural Network (BPNN). Results indicate that the GWOASSA-LSSVM model outperforms SSA-LSSVM, LSSVM, and BPNN across metrics such as Coefficient of Determination (R2), Variance Accounted For (VAF), Performance Index (PI), Index of Agreement (IOA), Index of Scatter (IOS), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and a20-index, demonstrating its capability for accurate prediction of pile bearing capacity.

Analisis Daya Dukung Lateral Bored Pile Ø 80 Cm dengan Menggunakan Uji Beban Lateral dan Menggunakan Metode Elemen Hingga pada Proyek Menara BRI - Medan

Bored pile foundations are deep foundations that are often used in the construction of large construction sites located in dense areas with the consideration of reducing noise and the influence of vibrations that would occur if pile foundations were used. This analysis aims to calculate the lateral bearing capacity of the bored pile foundation based on the results of analytical calculations using the Broms method, the Davisson method, the Chin method, the Mazurkiewich method, and analyzing the displacement of the bored pile foundation based on loading tests in the field. and the results of soil modeling with Allpile and finite element methods with the Mohr-Coulomb soil model, and the Hardening Soil model. Based on the analysis that has been carried out, the ultimate bearing capacity of the bored pile based on SPT data using the Broms method is 18.92 tons, while the results of the interpretation of the loading test using the Davisson method are 18 tons, the Chin method is 18.98 tons, and the Mazurkiewich method is 19 tons. For the large deflection of a single bored pile with a load of 200% with the Allpile program the large deflection that occurs is 4.25 mm and analysis based on FEM PLAXIS 3D using soil modeling with Mohr - Coulomb large deflection of 3.0 mm and soil modeling with Hardening Soil 2.99 mm.

Assessing the effects of horizontal loads on the ultimate vertical bearing capacity of energy piles: A comparative numerical and analytical study

Previous studies have not extensively explored the collective impact of lateral, axial, and thermal loading on the ultimate vertical bearing capacity of energy piles, qu. This study investigates qu values for energy piles in dry sandy and clayey soils under varying lateral loads and temperature conditions using numerical and analytical solutions, considering temperature-dependent variables. The numerical results were validated against experimental data. The analytical solution aligns well with numerical analyses, though it yields slightly higher qu values in sandy soil. Both numerical and analytical solutions show that cooling and heating can respectively increase and decrease qu under corresponding conditions. Numerical simulations indicate that in clay, lateral load enhances qu, with increases ranging from 8 % to 20 % across different thermomechanical conditions. In sand, the effect of lateral load depends on thermal conditions, increasing by 2 %–5 % during cooling and decreasing by 3 %–5 % during heating. The analytical solution showed that increasing lateral load would increase qu in sand by 0.5 %–2 % and in clay by 1 %–5 %, with a more significant increase in clay. Analytical and numerical parametric studies also revealed the higher influence of soil cohesion and pile diameter on qu values under different thermomechanical conditions.

Discussion on adaptive neuro-fuzzy inference system-based models for predicting ultimate bearing capacity of rock-socketed piles

Discussion on adaptive neuro-fuzzy inference system-based models for predicting ultimate bearing capacity of rock-socketed piles