An Analysis of the Impact Exerted on Bearing Capacity of Pier and Pile after Increasing Pile Cap Height

Huang, Xianbin; Liu, Chenyang; Hou, Shengqi; Chen, Chunyang; Wangren, Yahong; Xu, Jialin

doi:10.1155/2018/9867897

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…With the lower natural ground elevation, the bearing capacity is higher. These behavior are concluded by Coyle et Sulaiman [ 63 ] and Liu et al [ 64 ]. The lowest impact on the pile bearing capacity is pile top elevation which has a positive effect.…”

Section: Resultssupporting

confidence: 62%

Developing random forest hybridization models for estimating the axial bearing capacity of pile

Pham

Tran

2022

PLoS ONE

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Accurate determination of the axial load capacity of the pile is of utmost importance when designing the pile foundation. However, the methods of determining the axial load capacity of the pile in the field are often costly and time-consuming. Therefore, the purpose of this study is to develop a hybrid machine-learning to predict the axial load capacity of the pile. In particular, two powerful optimization algorithms named Herd Optimization (PSO) and Genetic Algorithm (GA) were used to evolve the Random Forest (RF) model architecture. For the research, the data set including 472 results of pile load tests in Ha Nam province—Vietnam was used to build and test the machine-learning models. The data set was divided into training and testing parts with ratio of 80% and 20%, respectively. Various performance indicators, namely absolute mean error (MAE), mean square root error (RMSE), and coefficient of determination (R2) are used to evaluate the performance of RF models. The results showed that, between the two optimization algorithms, GA gave superior performance compared to PSO in finding the best RF model architecture. In addition, the RF-GA model is also compared with the default RF model, the results show that the RF-GA model gives the best performance, with the balance on training and testing set, meaning avoiding the phenomenon of overfitting. The results of the study suggest a potential direction in the development of machine learning models in engineering in general and geotechnical engineering in particular.

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Section: Resultssupporting

confidence: 62%

Developing random forest hybridization models for estimating the axial bearing capacity of pile

Pham

Tran

2022

PLoS ONE

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“…e centroid of the bottom compression area is at 1/2 of the effective height, so the dimension of strut perpendicular to tie bar is D + 0.5h a . e calculation of strut height along tie bar cannot consider diffusion range due to the anchorage of steel bar; strut height can be calculated according to (3). erefore, the cross-sectional area of strut in the cap is calculated as Note.…”

Section: Bearing Capacity Of Strutmentioning

confidence: 99%

“…Guo [1] and Souza et al [2], respectively, introduced punchingspan ratio and shear span-depth ratio to distinguish the different failure forms of the caps. Huang et al [3] analyzed the impact exerted on bearing capacity of pier and pile after increasing pile cap height by using the standard formula and numerical simulation method. Bloodworth et al [4] studied the effects of shear span, cap width, and reinforcement ratio on the shear behavior of the cap under full-width wall loading, observed strut-and-tie model (STM), and thereby proposed an improved modified strut-and-tie method which gives more accurate predictions for the analysis of a four-pile cap.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Behavior and Calculation Method for RC Fifteen‐Pile Cap of Mixed Passenger and Freight Railway Bridge

Huang

Cui²,

2020

Advances in Civil Engineering

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The thickness, reinforcement, and concrete strength grade of railway caps in China are generally determined according to the force, yet the method for calculating the force is unclear. To date, there is no desirable calculation method for analyzing the caps. Based on the fifteen-pile thick cap of mixed passenger and freight railway, the influencing factors on cap bearing capacity were analyzed using finite element method (FEM). The variations of load-bearing capacity and mechanical behavior of thick cap were characterized by introducing rigid angle α. Results indicated that ultimate load-bearing value of the cap increased linearly with the increase of concrete strength grade, and an increasing load-bearing capacity of the reinforcement distributed in the pile diameter range was larger than that of the uniform reinforcement; when the reinforcement ratio was 0.15%, it increased by 9.3%. The cap showed punching failure when α < 45°. The reaction force at each pile top under vertical load was not equal; thereby, the cap was not absolutely rigid. The principal compressive stress trajectories in the concrete were distributed in the range of connecting the pile and the outer edge of the pier, and the effective tensile stresses in the reinforcement were mainly distributed in the diameter range of pile and pile connection, which is in accord with the stress mode of the ordinary spatial truss model. Based on this, a spatial truss model applicable to the design of railway caps is proposed, and a method for calculating reaction force at pile top and formulas for calculating the bearing capacity of strut and tie were presented. The feasibility of the proposed method was also verified by comparison with FEM results.

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An Analysis of the Impact Exerted on Bearing Capacity of Pier and Pile after Increasing Pile Cap Height

Cited by 2 publications

References 18 publications

Developing random forest hybridization models for estimating the axial bearing capacity of pile

Developing random forest hybridization models for estimating the axial bearing capacity of pile

Mechanical Behavior and Calculation Method for RC Fifteen‐Pile Cap of Mixed Passenger and Freight Railway Bridge

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