Pile Geometry Research Articles

Analysis of the screw pile group subjected to combined V–H loading for energy application

ABSTRACT The present study investigates the behaviour of screw piles in very stiff clay under the combined vertical and horizontal loads using a three-dimensional finite element analysis. The soil is modelled using the Mohr–Coulomb elastic, perfectly plastic material, whereas the pile shaft and helices are modelled as a linear elastic material. This study examines the effect of the number of helices, helix diameter, inter-helix spacing, and pile spacing on the performance of screw piles under both vertical compression and lateral loads. The study shows that the effect of the number of helices is negligible under the combined load. The increase in the helix diameter (D h) improves the pile performance. The results also reveal that the optimum interhelix spacing is 3D h, and the optimum pile spacing is 2D h. Thus, the present study demonstrates that optimizing the geometry of the screw pile enhances its performance, making it suitable for offshore wind turbines.

Optimising the embodied carbon of laterally loaded piles using a genetic algorithm and finite element simulation

With the need to cut embodied carbon from the construction industry, there has been a growing interest in optimising the design of different structural elements. This paper, for the first time, minimises the embodied carbon of laterally-loaded piles using a hybrid genetic algorithm. The research is split into four stages. Firstly, the optimisation algorithm is set and run to produce the optimal piles of lateral capacity 0.5 MN at a 25 mm lateral displacement limit, the embodied carbon of solid cylindrical and hollow cylindrical optimised pile designs is compared showing a significant reduction in the embodied carbon when the hollow geometry is used. Then an analysis is presented to test the effect of different displacement limits on the resulting embodied carbon, showing that the lateral displacement limit has a significant effect on the overall embodied carbon of the pile designs, highlighting a scope for reducing the embodied carbon if more pile displacement is permissible. A finite element model is built using ABAQUS simulation package to investigate the soil-pile interaction and compare the two optimal pile designs. Finally, the lateral load capacity of four different pile geometries is calculated to demonstrate the effect of pile geometry on its lateral load capacity, hollow cylindrical piles, showed to have the highest lateral load capacity compared to the other pile types. We conclude that the opportunity for significant carbon savings exists in laterally loaded piles through both optimisation and careful consideration of performance criteria.

Hyperbolic load–displacement analysis of helical and expanded piles: database approach

Recent years have witnessed a focus on improving geotechnical systems by implementing and constructing new deep foundations such as helical and expanded piles. In this study, the effects of parameters such as embedment depth, pile geometry and axial loading direction on the load–displacement behaviour of these piles were examined. To this end, a database was compiled consisting of 80 axial loading test records for different piles. The embedment depth of the piles was in the range 2.4–36.8 m and the diameter of the helices (DH) or expanded parts (DEP) was in the range 254–1500 mm. The ultimate load of the piles was determined using the 2.5% and 5% displacement ratio criteria and the Brinch Hansen 80% method. Hyperbolic functions were fitted to the load–displacement curves, allowing for consistent estimation of the limit load and the initial tangent modulus. Analysis of the results from the database revealed that the dominant factors influencing the ultimate load, limit load, maximum measured load, initial stiffness and load–displacement behaviour were the ratio of DH or DEP to the shaft diameter, the shaft area and the toe area, and the load direction. Correlations derived from the database were validated using measurements from eight full-scale helical and expanded piles.

Life-cycle-based considerations in design of driven piles in sand

This study conducts a life-cycle assessment to evaluate the environmental impacts of driven shafts across 12 different siliceous sand sites, selected from a database of static load pile tests. Through parametric studies, this paper investigates the influence of soil properties, pile geometry and on-site activities on environmental impacts. For a single pile, the findings demonstrate that material production is the most impactful phase, contributing 88.4% of global warming potential (GWP) per unit capacity, while on-site operations contribute minimally at 1%. Sensitivity analyses show that variations in fuel consumption by ±25% and linear interpolations of blow counts result in negligible difference in GWP (less than 0.1 and 1%, respectively). On average, the total GWPs for steel and concrete piles are approximately 4.3 and 0.92 kg carbon dioxide (CO2) equivalent per kilonewton capacity, respectively. Although various factors influence pile design and installation, the results presented herein provide a foundational framework for geotechnical engineers to integrate environmental impacts into project planning, design and construction considerations.

Performance of unequal piled raft under vertical loading in cohesionless medium

The performance of piled rafts with unequal pile lengths in cohesionless soil under vertical loading was investigated in the present study through experimental and numerical analysis. A pattern function is used to define the pile length arrangement. The motivation for considering such a function is to ensure that the varying pile lengths follow a suitable geometric pattern, and it does not obstruct the construction practice in field applications. The piles at different locations within the raft were equipped with strain gauges to observe the strain distribution along their lengths during the static load test. Load sharing was evaluated by placing an earth pressure cell beneath the raft. A three-dimensional finite element analysis was used to simulate the experimental results aimed at assessing the load settlement and load-sharing responses. A comparison was conducted to verify the reliability of the tests. Subsequently, a detailed parametric study was conducted in accordance with different pattern functions, pile spacing, and pile locations in the piled rafts. The load settlement, load sharing, and bending moment of the raft were evaluated. An understanding of the pile behavior at different locations within the group will be helpful in selecting the suitable pile geometry during actual construction in the field. A foundation designed by considering the optimized pile length will be helpful in developing a more economical and resilient foundation system.

Methodology for geometry assessment of self-drilling micropiles using distributed fibre optic sensors

Self-drilling micropiles (SDMs) are gaining popularity as bearing foundation elements, as this construction technique allows for considerable time and cost savings. However, the irregular geometry and variability in the bearing capacity present uncertainty and a significant risk that has limited SDM deployment. To date, no reliable technology has been used to measure the SDM geometry. This paper proposes a methodology that uses distributed fibre optics (DFO), heat conduction modelling and inverse analysis to measure the pile geometry, and could also be extended to assess its bearing capacity. The temperature distribution during cement hydration was measured using two DFO investigative technologies and was compared to traditional temperature measurements using point sensors. An inverse analysis of SDM geometry was subsequently carried out based on the DFO measurement of temperature, a finite-element heat conduction model and a calibration pile. Finally, the calculated pile geometry was compared to the geometry of an excavated pile in the uppermost part. The methodology presented here is not only intended as a tool for designing SDMs but can also be deployed as a structural health monitoring system to detect and monitor crack formation.

Local scour depth at piles group exposed to regular waves: On the assessment of expressions based on classification concepts and evolutionary algorithms

An accurate estimation of local scour depth around piles group is inevitably essential to provide stability of marine structures. Over the past decades, many investigations have been made to understand the scouring process at piles group exposed to waves for field and experimental scales. This study aims to predict the wave-induced local scour depth by various robust Data Driven Models (DDMs) and Machine Learning Models (MLMs) developed by classification and evolutionary concepts: Model Tree (MT), Evolutionary Polynomial Regression (EPR), Multivariate Adaptive Regression Spline (MARS), and Gene-Expression Programming (GEP). From relevant literature, 125 data series were employed to provide empirical relationships for scour depth predictions. The raw variables were related to bed sediment, pile configuration, pile geometry, approaching flow, and wave characteristics. Non-dimensional parameters have been obtained through the Buckingham theorem in order to control local scour depth. In this way, the ratio of spacing between piles to pile diameter (G/D), sediment number (Ns), pile arrangement number (ratio of the number of piles parallel to the flow; m; to the number of piles normal to the flow; n), Shields parameter (θ), and Keulegan-Carpenter (KC) were considered. From the training and testing stages of Artificial Intelligence Models (AIMs), it was found that regression equation given by MARS model provided better performance (e.g., Correlation Coefficient [R] = 0.9297, Root Mean Square Error [RMSE] = 0.3489, and Scatter Index [SI] = 0.2765) than other AI models’ efficiency. Additionally, the performance of AI models was assessed for various ranges of dimensionless parameters (i.e., G/D, Ns, and θ) versus KC variation. MARS model had the best performance for G/D = 0–1 and KC < 10 (R = 0.9917 and RMSE = 0.2198) and 0.4≤θ < 0.5 and 15 < KC < 25 whereas EPR model had promising efficiency in the its highest level for Ns = 1–3 and 10 < KC ≤ 15 (R = 0.9941 and RMSE = 0.0771) than other AI models. For the sensitivity analysis, the mutation rate and number of chromosomes are examined for the GEP model, the K-fold number and number of parameters for the MARS model, and the number of algebraic terms and number of chromosomes for the EPR model. Furthermore, ranking analysis of AI models indicated that MARS model had the best performance (Ranking Performance Index [RPI] = 0.7348) and followed by GEP (0.3412), M5MT (0.2999), and EPR (0.2848).

Soil plugging of open-ended steel piles during impact driving

During the driving process of an open-ended steel pile, soil is allowed to enter the pile’s core until partial or complete plugging occurs. Once this phenomenon is activated, soil resistance to driving (SRD) increases, which can prevent further soil introduction inside the pile, and in turn halt installation works under similar conditions. In this paper, we demonstrate the relationship between the plugging phenomenon, pile geometry, and driving acceleration by comparing literature with some conducted experiments (Paikowsky, 1990; Magroun, 2012), which show that the risk of plugging decreases mainly with an increase in both pile diameter and driving acceleration. A verification study of plugging occurrence in terms of depth is conducted on an open-ended driven pile at a Moroccan port terminal crossing predominantly sandy layers before anchoring in a lower marl layer. The pile’s bearing capacity is evaluated in both plugged and unplugged cases using the SRD method following the processes of Toolan &amp; Fox (1977) and Alm &amp; Hamre (2001), and based on cone penetration test (CPT) results. The pile is thus found unlikely to plug during driving. As a general rule, we found that the plugging phenomenon must be controlled to avoid any interruption in the pile driving process.

Comparative Analysis of Bearing Capacity of Pile Foundation Using Van Der Ween, Philipponnat, and Meyerhof Methods

Soil has different characteristics so that it becomes a lot of problems in Civil Engineering construction, especially in foundation planning, it must be done carefully and use several methods as a comparison. This research is to compare the three methods of calculating the bearing capacity of bored pile foundations: Van Der Ween, Phillipponnat, and Meyerhof. The selection of an apposite method in bearing capacity analysis is important to confirm the safety of the building structure. The Van Der Ween Method is a more modern and detailed approach compared to the Meyerhof Method, it takes into account the negative impact of the lateral deformation of the pile, which improves the accuracy of its calculation. The Philipponnat Method is a method that combines aspects of both the Meyerhof Method and the Van der Ween Method, it considers load characteristics and soil properties like Meyerhof, while also accounting for lateral deflection of the piles like Van der Ween. The results show that each method has advantages and disadvantages in determining the bearing capacity of bored pile foundations. Analysis revealed factors such as pile diameter, soil depth, and maximum applied load affect the accuracy of the three methods. This research provides important insights for construction planners in selecting a suitable method for bored pile foundation bearing capacity analysis. It is recommended that soil characteristics and pile geometry be considered before selecting the most appropriate calculation method. This research can be extended by considering other methods and conducting validation through experimental analysis.

Improving thermal storage of energy screw pile groups with phase change materials

To achieve affordable housing in a carbon-neutral society, new buildings require a dual-purpose approach that comprises efficient construction and a green energy supply. Energy screw piles [1, 7] meet this demand as they combine the agility of screw pile drilling with the capability of extracting clean shallow geothermal energy. Moreover, the screw piles can be filled with phase change materials (PCM) to provide latent thermal storage. Studies regarding the use of PCMs as borehole backfill in a ground source heat pump system (GSHP) conclude that PCM implementation can improve GSHP performance. However, most commercially available PCMs have low thermal conductivities (λ) which undermine heat exchange rates [5, 10]. Besides, using PCMs as a composition of a concrete energy pile can reduce the pile structural performance since PCMs usually have a low mechanical capacity [2, 8]. The authors recently introduced PCM-sand mixtures as a core in the central hollow part of an energy screw pile, which does not impact the pile structural capacity [6]. The mixtures with a higher PCM content benefit the pile heat exchange through its latent heat, but only when the PCM does not reduce the mixture’s λ. To overcome this problem, this work tests a new underground heat exchange system where instead of mixing the PCM in the energy screw pile filling material, regular screw piles (i.e., without the heat exchange tubes) are filled with pure PCM, acting as thermal storage piles. A numerical model built via COMSOL [4] is used to evaluate how this combination of screw piles performs thermally when supplying/rejecting heat for a GSHP system operating for a whole year.&#x0D; This work uses a validated numerical model [3, 9] to simulate a grid of evenly distributed screw piles, where Energy Piles (EP) and Thermal Storage Piles (TSP) are positioned interspersed, evenly spaced 0.7 m apart. Inside the EPs, an U-loop pipe is inserted in the pile steel case and the remaining is filled with grout. In contrast, the steel case of the TSPs is filled with only PCM [11]. All other material properties and the screw pile geometry are based on [1]. The thermal load is based on the design of a building located in Melbourne, Australia (Figure 1(a)). The model considers the hourly operation of a GSHP for one year, calculating the GSHP Coefficient of performance (COP) at every time step and adjusting the ground thermal load. For comparison, two simulations (one where the TSPs are filled with PCM and a reference where they are filled with only air) are undertaken. Besides the energy stored, the COPs of both cases are compared as a relative increase/decrease percentage (COPchange = (COPPCM / COPReference) – 1).&#x0D; Figure 1(b) presents the energy stored by the PCM and its corresponding percentage in a solid state over the simulation. As the EPs reject heat underground due to GSHP summer operation for cooling, the TSPs temperature rise and store sensible heat, until they reach their phase change temperature (Tpc), when the PCM melts to store significantly more heat energy in a shorter time window due to latent heat. Conversely, the PCM solidifies when EPs extract more heat than reject due to GSHP winter operation (heating) for a certain period. The PCM melts again on the following summer, restarting the whole process. The peak energy stored in the TSPs is 190.3 MJ/m3. Even though the thermal load varies hourly, the PCM phase change process happens without immediate responses to the load variation. Figure 1(c) presents the resulting change in the hourly COP considering cooling (CCOP) and heating (HCOP) from implementing PCM in the TSPs, compared to the reference scenario (empty TSPs). The extra heat stored by the PCM lowers the circulating fluid temperature while the latent heat is engaged (months 2 to 7 and 12), which results in a higher CCOP and a lower HCOP. By plotting a monthly average of the COPchange (grey markers), it is clear that the impact of the PCM on the COP is positive when cooling is dominant and slightly negative when heating becomes dominant while the latent heat is engaged. When the PCM is implemented in the EP [6, 10], the heat exchanged by the EP drops once the phase change process is over due to the low λ of the PCM, but by positioning it outside the EP the higher CCOP is sustained even after the phase change ends. However, lowering the fluid temperature increases CCOP while lowering HCOP at the same time, which can harm thermal performance if not designed properly. The results underlie the thermal storage potential available not only in screw piles, but also in any hollow pile foundation, by simply implementing PCM in the hollow case.&#x0D;

Predicting friction capacity of driven piles using new combinations of neural networks and metaheuristic optimization algorithms

Friction capacity is a principal characteristic in designing driven piles. Considering the complexities in analyzing the behavior of piles, many studies have recommended the use of machine learning for this purpose. However, the used methodologies need to be updated and improved with respect to recent computational advances such as the development of optimization algorithms. In this work, three metaheuristic algorithms, namely equilibrium optimizer (EO), biogeography-based optimization (BBO), and salp swarm algorithm (SSA) are deployed to optimize an artificial neural network (ANN) for predicting pile friction capacity based on pile geometry, effective stress, and shear strength. The findings indicate the suitability of the proposed algorithms. More specifically, in the training phase, the ANN supervised by SSA yielded the most accurate results, whereas in the testing phase, the BBO-ANN outperformed the two other models. The calculated mean absolute error, Pearson correlation coefficient, and root mean square error for the models are as follows: 6.0740, 0.9385, and 7.0678 for the EO-ANN, 6.1450, 0.9440, and 6.7343 for the BBO-ANN, and 5.9684, 0.9395, and 7.1322 for the SSA-ANN. It is shown that both SSA-ANN and BBO-ANN can serve as efficient tools for the reliable design of driven piles, providing efficient computational intelligence alternatives to traditional design methods.

Capacity prediction and design optimization for laterally loaded monopiles in sandy soil using hybrid neural network and sequential quadratic programming

Data driven methods have gained momentum in recent years in solving highly non-linear engineering problems that are challenging to solve using conventional methods. In this paper, we present a hybrid neural network model to predict the lateral response of large-diameter monopiles in multi-layered soil. The hybrid neural network consists of a mixture of convolutional and fully-connected layers, which capture the impacts of the soil profile, the pile geometry, and loading conditions on the lateral load response of monopiles. To train the neural network model, we produced data from high-fidelity three-dimensional (3D) finite element (FE) models that are validated against full-scale pile load tests. To ensure consistent model performance across the entire range of pile capacities considered in the dataset (ranging from approximately 100 kN to 100,000 kN), we utilize the relative error (percentage error) as the criterion for training the model. To achieve this goal, we explored six different combinations of data transformation methods (i.e., natural logarithm and root transformations) and cost functions. Among these models, the model trained with Mean Squared Error (MSE) using natural logarithm transformation yielded the most accurate and consistent predictions of the lateral capacities of monopiles. To demonstrate the strengths of the developed neural network model, it was used as a surrogate model to perform pile design optimization using sequential quadratic programming. In addition, a design example is provided to show how the developed method can be easily implemented.

Evaluation of Sustainable Slope Stability with Anti-Slide Piles Using an Integrated AHP-VIKOR Methodology

The sustainable design of major civil engineering projects, such as landslide management and slope stability, provides new opportunities for our society regarding the global energy crisis. These sources offer an effective solution to environmental issues and human energy needs. Slope stability, as a critical aspect of ensuring public safety and protection of infrastructure, often leads to disastrous consequences, highlighting the significance of designing effective and sustainable measures to mitigate the risks associated with landslides. Although anti-slide piles have become a widely used method to enhance slope stability, this paper investigates how the Analytic Hierarchy Process (AHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodologies can be combined to achieve a sustainable design for anti-slide piles, simultaneously considering environmental, economic, safety, and technical factors. Through the integration of AHP-VIKOR and a case study, this paper demonstrates an effective approach to prioritizing sustainability in the design process of anti-slide pile systems, evaluating five main criteria—slope stability, sustainability, anti-slide pile capacity, cost, and ease of construction—and five sub-criteria. The proposed methodology is validated through a case study, wherein various design alternatives for anti-slide piles are evaluated based on sustainable requirements. The results indicate that the slope stability criterion has the highest weight of 0.404, followed by anti-slide pile capacity (0.283), sustainability (0.129), and cost (0.146) criteria. The ease of construction has the lowest weight of 0.038. As a result of the evaluations, it has been seen that, if the sustainability criteria are included in the analyses, the anti-slide pile alternatives are determined in the range of ξ = 0.1–0.3 and s/D = 2.0–3.0, compared to the scenarios where only the economic and technical criteria are satisfied. A pile geometry of diameter, D = 1.00 m, is the most sustainable value within the selected pile spacing intervals, meeting the criteria of slope safety, pile capacity, cost, and ease of construction. This hybrid approach allows for a more balanced consideration of a multi-criteria decision, while considering the sustainability aspects of anti-slide pile selection.

Experimental study on partially tapered belled piles subjected to inclined load in sand

ABSTRACT In the present investigation, several experiments are carried out on statically inclined compressive loads on model aluminium partially tapered belled piles (PTBP) and bored piles (BP). The partially tapered bell is formed by providing outer extension angle alpha (α) as 3°, 5° and 7° at the middle of every model pile. These tests are carried out on 1 × 1and 1 × 2 pile groups having L/D of 12, 17, and 22. The model piles tested in the relative density of medium dense (Rd = 39.5%) and dense sand (Rd = 70%) with spacing to diameter ratio (S/D) of 3, 4, and 5 to both BP and PTBP. The comparisons between PTBP and BP test results are expressed in the form of load-deflection curves. The effect of pile geometry, outer extension angle, pile spacing, and influence of relative density are carefully investigated. From the investigation, it is found that the optimum value of the L/D ratio is 22, α is 7° and the S/D ratio is 5Db, (Db is PTBP base diameter) this configuration achieved 41.46% greater load carrying capacity in the dense state of sand bed as compared with the medium dense state of sand bed with the same configuration.

Evaluation of Bearing Capacity for Cast In-Situ Bored Piles

Abstract: Pile is a structural element constructed to overcome heavy loads from super structure, when proper bearing strata is not available at shallow depth. The prediction of bearing capacity of a bored cast in-situ pile is a complex problem, as it depends on installation method, concrete quality, ground condition and pile geometry. It is considered that the reliable method for finding bearing capacity is pile load test, which is time consuming and costly. The bearing capacity can also be analysed by empirical and analytical methods using soil data and SPT data. In this paper, empirical methods and graphical methods are used to evaluate beating capacity of cast in-situ bored piles. For empirical methods - IS code method, Meyerhof method, Bazaraa and Kurkur method are employed and for graphical methods - Hansen’s method, Chin-Kondner’s method, Decourt’s Extrapolation method are employed. All these methods are summarized for comparison with the pile load test values. A database of 3 bored piles is collected from different sites in Kerala. The above chosen SPT methods are calibrated by trial and error method to propose a new formula. A pile structural design also proposed.

Data-driven ensemble learning approach for optimal design of cantilever soldier pile retaining walls

Cantilever soldier pile retaining walls are used to ensure the stability of excavations. This paper deploys ensemble machine learning algorithms towards achieving optimum design of these structures. A large dataset was developed consisting of 40,569 combinations of pile geometry, external loading, soil properties, and concrete unit cost, with two different values of soil reaction coefficient. Optimum pile diameter that minimizes the total cost of the retaining wall was computed considering the structural load-carrying capacity as the optimization constraint. The dataset was split into training and testing sets at 70% to 30% ratio. The predictive accuracy of the ensemble machine learning models was appraised on the testing dataset using various statistical metrics. Model performance was also evaluated for its ability in predicting the optimum pile diameter. The developed models demonstrated excellent predictive accuracy. Furthermore, the effect of different input variables on the model predictions was explained using the SHapely Additive exPlanations (SHAP) approach. Through the SHAP algorithm, the pile length was identified as the design variable having the most significant effect on the optimum pile diameter. The study demonstrates ensemble learning techniques as a viable alternative to the traditional techniques in the optimum design of cantilever soldier pile retaining walls.

Experimental Work on the Effect of Under-reamed Pile Geometry on the Pullout Capacity of Sand

Experimental Work on the Effect of Under-reamed Pile Geometry on the Pullout Capacity of Sand

Simulation of cyclic laterally-loaded piles in undrained clays accounting for soil small-strain characteristics

The performance of pile foundations subjected to cyclic lateral loading is central to offshore geotechnical engineering. Although non-linearity and path-dependence of soil mechanical behavior at small strains are widely recognized, the influences of these local behavior on global response of pile foundations are less explored. This work presents numerical analyses of cyclically-loaded piles in undrained clays that explicitly account for soil small-strain characteristics. By using intergranular strain (IGS) elasticity method, a soil model proposed by the authors for undrained clays during cyclic loading is extended to include non-linear small-strain behavior. Via comparing against element tests, the constitutive relation is shown capable of representing the observed variation of soil stiffness and damping with strain magnitudes, as well as the dependence of such non-linearity on stress paths. Based on the above soil model, finite element simulations are performed to interpret the response of laterally loaded piles from geotechnical centrifuge tests. The impacts of soil small-strain behavior on pile force–displacement relations, hysteric loops, and the ability of a pile–soil system to dissipate energy are investigated. This work highlights that the sensitivity of these foundation responses to small-strain non-linearity of soils can vary considerably, depending on pile geometry features and head constraint conditions.

Effects of axial loading on dynamic response of laterally loaded single piles in liquefiable layered soil of Kolkata city considering nonlinearity of soil

In the present study, an advanced nonlinear finite-element based 3D numerical study has been carried out to investigate the effects of axial loading on dynamic response of soil-pile system in liquefiable layered soil deposits of Kolkata city. An advanced soil constitutive law based on multi-yield surface plasticity model implemented in fully-coupled u-p formulation is adopted for soil-fluid interaction and pore water pressure development reasonably. The present model is validated with the past experimental results. Then, a detailed systematic parametric study is performed for numerical simulation of pile failures in layered soil deposit under axial loading by taking into account various soil conditions, pile and ground motion parameters. It is seen that the depth of liquefaction (DL) is decreased from 11.5 to 1.5 m adjacent to the pile when the axial load on pile increases from 0 to 1327 kN. Parametric studies also reveal that the bending moment response of pile under axial loading can be higher in non-liquefiable condition, with reference to the liquefiable condition. The peak lateral displacement decreases by 83.2% in non-liquefiable condition and 60.71% in liquefiable condition due to decrease of axial load from 1327 to 0 kN. Also, peak bending moment developed in the pile decreases by 97.2% in non-liquefiable condition and 82.7% in liquefiable condition when the axial load reduces from 1327 to 0 kN. So, the designer should be considered both extreme scenarios for safe and economical design. Also, it is noticed that the buckling capacity of pile is improved significantly by using larger diameter pile and the bending capacity is increased by selecting higher grade of concrete. It is concluded that the bending and buckling failure mode may be avoided by selecting a suitable combination of material strength and pile geometry.

The Performance of Helical Pile under Cyclic Load Using 3D-Finite Element Analysis

Helical piles are a kind of foundation that can withstand compression, tension, and lateral stresses. However, this kind of pile was utilized extensively globally for almost 25 years. Its behavior, particularly in Iraq, is uncertain and frightening. The current research used the finite element technique to analyze this kind of pile. The helical pile geometry was suggested to be modeled using the finite element method using the computer software Plaxis 3D The soil used is medium sandy soil. Additionally, parametric analyses were conducted. The primary parametric research examines the impact of helix number, helix spacing, helix diameter, and helix configuration under cyclic load. The main results are more helices in a pile, the lower the amplitude of settlement (in the direction of z) compared to a pile without helices. As a result, the amplitude of settlement in the case of two helices decreased by 81.6 %, while the amplitude of settlement in the case of three-helix decreased by 77.74 %. In the case of three helices, the higher spacing between the helices, the lower the value of the amplitude of settlement (in the direction of z). The effect of the number of helices in the hardening soil model is more than the effect of the number of helices in the Mohr-Coulomb. As a final result, increasing the number of helices in a pile has a more significant effect in reducing the amplitude of settlement than increasing the between the helices.