Axial Pile Capacity Research Articles

Effect of installation method on static and dynamic load test response for piles in sand

Static load tests (SLTs) are rarely performed on offshore piles, instead relying on dynamic load tests (DLTs). Evaluation techniques for DLTs were developed originally for solid piles, and caution is needed in applying the techniques directly to open-ended piles, particularly for the large-diameter monopiles used for offshore wind turbines. Centrifuge tests are reported here, investigating the influence of pile installation method and sand relative density for pairs of DLTs and SLTs. The piles were successfully driven to penetration of 3–4·6 diameters, which was much deeper than proved possible to jack the piles. Due to limited hammer energy, loads mobilised during the DLTs were less than 25% of the corresponding SLT values. The soil resistance mobilised at limited displacements was lowest for wished-in-place piles, and also for DLTs conducted on shallowly embedded jacked piles. For driven piles, the DLT and SLT results were relatively consistent, with surprisingly similar values for piles driven into loose and dense sand despite significant differences in cone resistance. Given the potential for low mobilisation of soil resistance in DLTs, care is needed when using DLTs for evaluating the static axial pile capacity of open-ended piles of low length-to-diameter ratio.

Comparison of direct SPT method for calculating axial capacity of piles in Jakarta Area

Estimating axial capacity of piles using Direct Method are still considered as challenges these days. Estimation mainly achieved after construction is done and field method such as static load test or PDA are used for calculating axial capacity of piles in real field cosnditions. This paper discussed estimation from 8 building project cases from Jakarta and Depok that have complete standard penetration test data and field calculations (static load test & PDA). The main objectives are to observe and correlate the results between every Direct Methods and field methods and to obtain which Direct Method is the most efficient to use for estimating axial capacity of piles in Jakarta area. Direct Methods that are used are Meyerhoff, Shariatmadari, Decourt, Aoki, and Robert. Calculation results showed that the most efficient standard penetration test method is that proposed by Decourt with average result of comparison between estimated axial capacity of piles and field calculation is roughly 1.03. The most underpredicted between every standard penetration test method is the one proposed by Aoki de Alencar with roughly 92% underprediction ratios and the largest overpredicted method is proposed by Shariatmadari with roughly ratios of 56%.

A field investigation into the mechanisms of pile ageing in sand

The design of axially loaded piles has been an area of focus for the offshore industry in recent years. A number of studies report substantial increases in the shaft capacity of piles driven in sand, known as pile ageing. The offshore industry has been slow to implement ageing into practice because of uncertainty over the mechanisms controlling ageing and variability on the impact of ageing. This paper presents the results of tests using an instrumented pile with two separate installations considered, one where the pile was load tested 4 days after installation and the second where the load test was performed after an ageing period of 116 days. Data from the installation, ageing period, load testing and pile extraction provide further insights into the mechanisms governing the effect of time on the axial capacity of piles in sand.

A TLBO-optimized artificial neural network for modeling axial capacity of pile foundations

Due to a considerable level of uncertainty describing the pile–soil behavior, many pile capacity prediction methods have focused on correlation with in situ tests. In recent years, artificial neural networks (ANNs) have been applied successfully in many problems in geotechnical engineering, especially, axial pile capacity estimation for driven and drilled shaft piles. Training neural networks is a crucial task that needs effective optimization algorithms. The most popular algorithm is a back-propagation method (BP), which is based on a gradient descent that can trap in local minima. The paper proposes a new artificial neural network (ANN) in which the learning is performed using a recent teaching–learning-based optimization algorithm (TLBO), improving axial capacity predictions. The model is trained and validated on 479 data sets for a wide range of uncemented soils and pile configurations, obtained from the literature. Results show that the considered TLBO-ANN model outperforms other state-of-the-art models in the prediction accuracy and the generalization capability. For instance, we obtained a coefficient of determination $$R^2=0.941$$ and a variance accounted for $${\text{VAF}} = 94.09\%$$ for TLBO-ANN while $$R^2=0.871$$ and $${\text{VAF}} = 87.31\%$$ for the classical BP-ANN. In addition, error investigation with log-normal approaches demonstrates that the probability that predictions fall within a $$\pm \,25\%$$ accuracy level for TLBO-ANN model is 0.93 and that for BP-ANN model is 0.75. The proposed TLBO-ANN model predicts pile capacity with more accuracy, less scatter, and higher reliability.

Estimation of long-term set-up of driven piles in sand

ABSTRACT Observations derived from updated field test databases indicate that total axial pile capacity of driven piles in sand continues to increase with time long after complete dissipation of excess pore pressure generated by pile driving. The increase in pile capacity with time is attributed to time-dependent increase in shaft capacity which is termed in the literature pile ‘set up’. Although, many hypotheses have been proposed in literature, the exact mechanism that governs the observed set-up is not yet fully understood and the estimation of the magnitude and rate of driven piles set-up remains relying on empirical relationships derived from widely scattered data. In this paper, a new hypothesis is introduced which attributes the observed set-up to the recovery of the soil surrounding the pile shaft from the friction fatigue processes induced during pile driving and a new methodology is formulated for the estimation of the magnitude and rate of driven pile set-up in cohessionless soil. Comparison of predicted and measured shaft friction capacities of some well-documented field cases comprising previously untested piles indicates acceptable results and suggests that the proposed approach can be used to estimate long time set-up of driven piles in sand.

Physical Modelling of Axial Compressive Bearing Capacity of Instrumented Piles in Oil-Contaminated Sandy Soil

Oil and its derivatives such as gasoline, gasoil and ‎kerosene are the main sources of energy in the transport and industry sectors, and also the most common ‎soil contaminants. Oil contamination of the soils as a serious geoenvironmental problem not only affects soil quality ‎but also changes its geotechnical properties. Any changes in the geotechnical properties of the soils affect the axial bearing capacity of pile. The main objective of the current study is to determine the effects of various concentrations of different oil ‎products, as well as different soil relative densities, and thickness of the contaminated sand layer on the load–displacement (axial compressive) behaviour of two ‎instrumented, close-ended steel pipe piles with different diameters and slenderness ratios implemented in an oil-contaminated sandy soil through physical modelling. Tests results were compared with the CFEM ‎analytical method of calculating pile axial bearing capacities. Results showed that increasing the percentage of the oil in the soil reduces the values of net total, toe and shaft bearing ‎capacity of the pile. The type of the oil had a remarkable effect on the bearing capacities of the pile. The higher the kinematic ‎viscosity, the lower the amount of bearing capacities. ‎Comparing the measured and predicted values of bearing capacity based on modified CFEM ‎method concluded that, although a good agreement can be seen between the results of shaft capacity, the ‎CFEM method with modified bearing capacity factors could not predict the effects of oil contamination ‎on the toe bearing capacities of piles precisely.

A Method for Predicting Pile Capacity Using Cone Penetration Test Data

The massive construction in poor lands has encouraged engineers to use deep foundations in order to transfer superstructure loads to the subsoil. Since soil excavation, sampling, and laboratory testing as a part of site investigation are relatively difficult, in-situ tests such as cone penetration test (CPT) as a very informative test may be recommended. The CPT has been widely used in engineering as a part of site investigation, and its data has been used to determine the axial capacity of piles. In this paper, the prediction capability of three empirical widely famous old methods used to predict the axial pile capacity based on CPT data is evaluated by using field data obtained from direct field pile loading tests. In this evaluation, the direct pile load test results are used as measured data. Three popular famous statistical evaluation methods namely the best-fitted line, geometric mean, and geometric standard deviation have been used. The evaluation results indicate that generally although predicting methods based on CPT data have been widely used to determine the axial bearing capacity of piles, they need to be upgraded for the economic and relatively accurate design of piles. According to the statistical studies carried out in the current research, among three old empirical methods, although the Nottingham and Schmertmann Method (1975, 1978) (NSM) [7, 8] has the best agreement with test results, it is felt that the method needs to be upgraded. The modification of NSM has been done in the current paper using a comprehensive database.

Piles Subjected to Torsional Cyclic Load: Numerical Analysis

Pile foundations supporting large structures (such as high-rise buildings, oil drilling platforms, bridges etc.) are often subjected to eccentric lateral load (in addition to the vertical loads) due to the action of wind, waves, high speed traffic and ship impacts etc. The eccentric lateral load, which is usually cyclic (repetitive) in nature, induces torsion in the pile foundation. This paper presents a numerical model based on boundary element approach to study the performance of a single pile subjected to the torsional cyclic load. The model is initially validated by comparing it with the experimental data available from the literature. Thereafter, the model has been utilised to conduct a parametric study to understand the influence of the torsional cyclic loading parameters on the axial pile capacity. The results indicated that the model is able to capture the degradation in the axial pile capacity due to the torsional cyclic loading with a reasonable accuracy. Moreover, the parametric study showed that the frequency, amplitude and number of cycles play a significant role in the torsional cyclic response of the pile. The present study is essential for the development of design guidelines for pile foundations subjected to torsional cyclic load.

A simplified calculation method for axial cyclic degradation of offshore wind turbine foundations in clay

Pile foundation is the most popular option for the foundation of offshore wind turbines. The degradation of stiffness and bearing capacity of pile foundation induced by cyclic loading will be harmful for structure safety. In this article, a modified undrained elastic–plastic model considering the cyclic degradation of clay soil is proposed, and a simplified calculation method (SCM) based on shear displacement method is presented to calculate the axial degradated capacity of a single pile foundation for offshore wind turbines resisting cyclic loadings. The conception of plastic zone thickness Rp is introduced to obtain the function between accumulated plastic strain and displacement of soil around pile side. The axial ultimate capacity of single piles under axial cyclic loading calculated by this simplified analysis have a good consistency with the results from the finite element analysis, which verifies the accuracy and reliability of this method. As an instance, the behavior of pile foundation of an offshore wind farm under cyclic load is studied using the proposed numerical method and SCM. This simplified method may provide valuable reference for engineering design.

Reliability prediction of the axial ultimate bearing capacity of piles: A hierarchical Bayesian method

The sea reclamation is one of the efficient ways to alleviate the shortage of land resources due to population growth, and the corresponding axial ultimate bearing capacity of piles has become one of the critical factors for evaluating the performance of the soil layer reclamation work. Many models are used to analyze the testing data. However, these models cannot describe the mean population bearing capacity and unit-to-unit variation simultaneously, and they cannot give the reliability of predicting the axial ultimate bearing capacity of piles. Thus, they are rarely used in practice. In this article, we propose a mixed-effects model, which could overcome the drawback of the models in the literature. A hierarchical Bayesian framework is developed to estimate the model parameters using Gibbs sampling. The proposed model is applied to a real pile dataset collected in silt-rock layer area, and we predict the mean axial bearing capacities under different reliability levels.

On the Cautious Estimation of Characteristic Soil Strength for Axial Pile Capacity

On the Cautious Estimation of Characteristic Soil Strength for Axial Pile Capacity

Pile load test of jacked open-ended prestressed high-strength concrete pipe pile in clay

The performance of open-ended piles can be different from that of closed piles due to the effect of soil plugging. This paper presents the results of a large-scale field pile load test conducted on an open-ended pile in clay under static compressive loads. A prestressed high-strength concrete pipe pile with an outer diameter of 400 mm and a wall thickness of 75 mm was instrumented with strain sensors and installed in a marine deposit for static load testing. The measured load-transfer data during pile installation and the pile load test results are reported and analysed. The data show that the pile was in a partially plugged condition during jacking and behaved in a fully plugged mode in the static load test. The measured ultimate shaft resistance and total resistance of the test pile were 659 and 1180 kN, respectively, which were smaller than the values calculated using a previously proposed method. The back-calculated α and β values (as used in the α and β methods) for axial pile capacity in marine deposits were 0·42 and 0·56, respectively.

Numerical ANFIS-Based Formulation for Prediction of the Ultimate Axial Load Bearing Capacity of Piles Through CPT Data

This study explores the potential of adaptive neuro-fuzzy inference systems (ANFIS) for prediction of the ultimate axial load bearing capacity of piles (Pu) using cone penetration test (CPT) data. In this regard, a reliable previously published database composed of 108 datasets was selected to develop ANFIS models. The collected database contains information regarding pile geometry, material, installation, full-scale static pile load test and CPT results for each sample. Reviewing the literature, several common and uncommon variables have been considered for direct or indirect estimation of Pu based on static pile load test, cone penetration test data or other in situ or laboratory testing methods. In present study, the pile shaft and tip area, the average cone tip resistance along the embedded length of the pile, the average cone tip resistance over influence zone and the average sleeve friction along the embedded length of the pile which are obtained from CPT data are considered as independent input variables where the output variable is Pu for the ANFIS model development. Besides, a notable criticism about ANFIS as a prediction tool is that it does not provide practical prediction equations. To tackle this issue, the obtained optimal ANFIS model is represented as a tractable equation which can be used via spread sheet software or hand calculations to provide precise predictions of Pu with the calculated correlation coefficient of 0.96 between predicted and experimental values for all of the data in this study. Considering several criteria, it is represented that the proposed model is able to estimate the output with a high degree of accuracy as compared to those results obtained by some direct CPT-based methods in the literature. Furthermore, in order to assess the capability of the proposed model from geotechnical engineering viewpoints, sensitivity and parametric analyses are done.

Axial compressive bearing capacity of piles in ‎oil-contaminated sandy soil using FCV

ABSTRACTOil and its derivatives contaminate many soils and not only affect their chemical and biological properties but also their geotechnical properties. As oil contamination may deteriorate the functioning of piles, this paper addresses the effects of oil contamination on soil–pile interactions. Axial compressive bearing capacities of two close-ended, instrumented piles were investigated in different oil-contaminated sand using frustum confining vessel. Three different oils (gasoil, crude oil, and used motor oil) at different contamination levels were considered and using some strain gauges, the toe, shaft, and the net total bearing capacity of piles, as well as load distributions along the pile length, were derived. The results show that the presence of oil between soil particles has considerable adverse effects on bearing capacities of model piles, especially the shaft bearing capacity. The oil viscosity and percentage, as well as the contaminated sand bed thickness around the piles, are the most influential parameters. The higher the oil viscosity and oil content, the lower the values of the piles’ bearing capacities in comparison to the uncontaminated sand. With some modifications on the bearing capacity parameters of CFEM method, a good agreement was observed between measured and calculated bearing capacity values.

Evaluation of axial pile bearing capacity based on pile driving analyzer (PDA) test using Neural Network

A few decades, many methods have been developed to predict and evaluate the bearing capacity of driven piles. The problem of the predicting and assessing the bearing capacity of the pile is very complicated and not yet established, different soil testing and evaluation produce a widely different solution. However, the most important thing is to determine methods used to predict and evaluate the bearing capacity of the pile to the required degree of accuracy and consistency value. Accurate prediction and evaluation of axial bearing capacity depend on some variables, such as the type of soil, diameter, and length of pile, etc. The aims of the study of Artificial Neural Networks (ANNs) are utilized to obtain more accurate and consistent axial bearing capacity of a driven pile. ANNs can be described as mapping an input to the target output data. The method using the ANN model developed to predict and evaluate the axial bearing capacity of the pile based on the pile driving analyzer (PDA) test data for more than 200 selected data. The results of the predictions obtained by the ANN model and the PDA test were then compared. This research as the neural network models give a right prediction and evaluation of the axial bearing capacity of piles using neural networks.

Field behaviour of screw micropiles subjected to axial loading in cohesive soils

Field tests of full-scale screw micropiles with a diameter varying from 76 to 114 mm and a length varying from 1.6 to 3 m were undertaken to investigate the axial pile capacities, load-transfer mechanism, and end installation torques of the piles in cohesive soils. Forty tests were performed on piles subjected to axial compressive and tensile loads. Six tests were instrumented with strain gauges on the pile shaft. Results showed the piles reached the limit state before the displacement exceeded 10% of the shaft diameter. The majority of axial load was transferred to the threaded segment. The adhesion coefficient of the top smooth shaft at the limit state was less than 0.1. The failure mode along the cylindrical threaded shaft was cylindrical shearing along the edge of the threads; the threads increased the axial capacities of the segment. Axial capacities of the threaded tapered segment were 43% on average greater than that of a cylindrical segment with the equivalent volume. Compressive capacities of all test piles were estimated and the results agreed reasonably well with the measured capacities. A theoretical torque model was proposed to estimate the end installation torques based on the cone penetration test results; the theoretical results matched the measured end torques very well.

Axial behaviour of jacket piles for offshore wind turbines

To improve our understanding and to quantify the behaviour of a jacket foundation for offshore wind turbines, several tests have been conducted using a geotechnical centrifuge at 100g. The monotonic tension and compression tests carried out on single small-scale model piles (prototype dimensions: 1·8 m in diameter and an embedment depth of 40 m in dense sand) jacked at 1g and 100g show the influence of the set-up method on the axial ultimate capacity and on the tip and shaft resistances. The pile axial capacity in compression is improved, whereas the normalised displacement of the pile is bigger in tension when piles are jacked at 1g. Vertical cyclic loads on single piles jacked at 1g (pure tension tests or two-way tests) and horizontal cyclic loads on a four-pile jacket structure are applied to examine the behaviour under more realistic loading paths. The piles of the jacket structure are considered and studied as singles piles. Finally, the stability diagrams for the single and the jacket piles are discussed to visualise the significant difference in performance of a single pile against the comparable pile in the jacket.

Impact of pile installation method on the axial capacity in sand

The impact of installation methods on pile axial capacity is studied using centrifuge model testing. Compression and tension tests are carried out on model piles jacked at 1g or at 100g in dense Fontainebleau NE34 sand. The pile total compression capacity and shaft and tip resistance are analysed and compared with the current design standards used in offshore engineering. These results show that the axial capacity of the tested piles is clearly underestimated. Pile total tension capacities are also studied. A significant increase in tension capacity is observed in cyclically jacked piles unlike piles monotonically jacked at 100g.

Numerical Evaluation of Pile Response Under Combined Lateral and Axial Loading

Piled foundations are frequently subjected to simultaneous axial and lateral loadings. However, the interaction effects of the one loading on the other are, in most cases, disregarded for the sake of simplicity. With the aim of evaluating this effect, a detailed research work on the response of a single pile under simultaneous application of axial and lateral loading was carried out. A qualitative assessment of the effect was initially attempted and the effect was afterwards quantified, based on the results of an intensive three-dimensional parametric numerical analysis. The influence arising from pile head fixity and the second order phenomenon was examined, while the post-peak behaviour was also considered using a strain hardening/softening constitutive law. Interesting conclusions have been drawn, providing a qualitative and quantitative evaluation of the effect on clayey and sandy soils. It was also found that no loading interaction effect is developed, when ultimate limit state is applied for a piled foundation design. On the contrary, when the serviceability limit state is applied and if the pile capacity in both lateral and axial loading is simultaneously reached, a reduction in the pile axial capacity is observed in the case of clayey soils. On the contrary, in the case of sandy soils the action of a lateral load is leading to an increase of pile axial capacity.

Prediction of axial capacity of piles driven in non-cohesive soils based on neural networks approach

This paper presents an application of two advanced approaches, Artificial Neural Networks (ANN) and Princi­pal Component Analysis (PCA) in predicting the axial pile capacity. The combination of these two approaches allowed the development of an ANN model that provides more accurate axial capacity predictions. The model makes use of Back-Propagation Multi-Layer Perceptron (BPMLP) with Bayesian Regularization (BR), and it is established through the incorporation of approximately 415 data sets obtained from data published in the literature for a wide range of un-cemented soils and pile configurations. The compiled database includes, respectively 247 and 168 loading tests on large-and low-displacement driven piles. The contributions of the soil above and below pile toe to the pile base resistance are pre-evaluated using separate finite element (FE) analyses. The assessment of the predictive performance of the new method against a number of traditional SPT-based approaches indicates that the developed model has attractive capabili­ties and advantages that render it a promising tool. To facilitate its use, the developed model is translated into simple design equations based on statistical approaches.