Interpretation of Load Tests on High-Capacity Driven Piles

2009 ◽  
pp. 388-388-28 ◽  
Author(s):  
GA Leonards ◽  
D Lovell
Keyword(s):  
High Capacity ◽  
Driven Piles ◽  
Load Tests

scholarly journals Limitations of the Danish driving formula for short piles

2021 ◽  
Vol 44 (2) ◽  
pp. 1-6
Author(s):  
Silvio Heleno de Abreu Vieira ◽  
Francisco R. Lopes
Keyword(s):  
Load Capacity ◽  
Precast Concrete ◽  
Free Fall ◽  
Technical Note ◽  
Driven Piles ◽  
Concrete Piles ◽  
Load Tests ◽  
Semi Empirical ◽  
The City ◽  
Pile Length

Dynamic formulae are a widely used expedient for the control of driven piles to ensure load capacity. These formulae have considerable limitations when used in the prediction of the load capacity on their own, but are very useful in the control of a piling when combined with other tests. This technical note presents an evaluation of the Danish Formula for 54 precast concrete piles, comparing its results with High Strain Dynamic Tests (HSDTs), Static Load Tests (SLTs) and predictions by a semi-empirical static method (Aoki & Velloso, 1975). The data used in the comparison come from three works in the city of Rio de Janeiro, Brazil. All piles were driven with free-fall hammers and in one particular work the piles were relatively short. The predictions of the Danish Formula were evaluated in relation to the pile length/diameter ratio. It was concluded that for short piles - with lengths less than 30 times the diameter - this formula indicates bearing capacities higher than the actual ones. A correction for a safe use of the Danish Formula for short piles is suggested.

scholarly journals Empirical Shaft Resistance of Driven Piles Penetrating Weak Rock

2020 ◽  
Vol 53 (12) ◽  
pp. 5531-5543
Author(s):  
John W. Barrett ◽  
Luke J. Prendergast
Keyword(s):  
Empirical Relationship ◽  
Empirical Relation ◽  
Driven Piles ◽  
Case Histories ◽  
Pile Capacity ◽  
Shaft Resistance ◽  
Fatigue Model ◽  
Load Tests ◽  
Pile Load Tests ◽  
Engineering Projects

AbstractIn this paper, an empirical relationship between the Unconfined Compressive Strength (UCS) of intact rock and the unit shaft resistance of piles penetrating rock is investigated. A growing number of civil engineering projects are utilizing steel piles driven into rock where a significant portion of the pile capacity is derived from the shaft resistance. Despite the growing number of projects utilizing the technology, little to no guidance is offered in the literature as to how the shaft resistance is to be calculated for such piles. A database has been created for driven piles that penetrate bedrock. The database consists of 42 pile load tests of which a majority are steel H-piles. The friction fatigue model is applied to seven of the pile load tests for which sufficient UCS data exists in order to develop an empirical relation. The focus of this paper is on case histories that include driven pipe piles with at least 2 m penetration into rock.

Full-Scale Lateral Load Tests of Driven Piles in Bangkok Clay

IFCEE 2018 ◽  
2018 ◽  
Author(s):  
Gong Chaosittichai ◽  
Pongpipat Anantanasakul
Keyword(s):  
Lateral Load ◽  
Full Scale ◽  
Driven Piles ◽  
Load Tests

Characterization of model uncertainty in predicting axial resistance of piles driven into clay

2019 ◽  
Vol 56 (8) ◽  
pp. 1098-1118 ◽  
Author(s):  
Chong Tang ◽  
Kok-Kwang Phoon
Keyword(s):  
Model Uncertainty ◽  
Driven Piles ◽  
Resistance Factors ◽  
Reliability Based Design ◽  
Pile Diameter ◽  
Measured Resistance ◽  
Load Tests ◽  
Similar Accuracy ◽  
Load And Resistance Factor ◽  
Axial Resistance

This paper summarizes 239 static load tests to evaluate the performance of four static design methods for axial resistance of driven piles in clay. The methods are ISO 19901-4:2016, SHANSEP, ICP-05, and NGI-05. The database is categorized into four groups depending on the load type (compression or uplift) and pile tip condition (open or closed end). The model uncertainty in resistance prediction is quantified as a ratio between measured and calculated resistance, which is called a model factor. The measured resistance is interpreted as a load producing a settlement level of 10% pile diameter. Database studies show that the four methods present a similar accuracy, where the mean and coefficient of variation (COV) of the model factor are around 1 and 0.3, respectively. The COV values are smaller than those for driven piles in sand available in literature. The model statistics determined from the database are applicable to a simplified or full probabilistic form of reliability-based design (RBD) of driven piles in clay. As an illustration, the resistance factors in load and resistance factor design (LRFD, a simplified form of RBD) are calibrated by Monte Carlo simulations.

scholarly journals Intelligent computing for modeling axial capacity of pile foundations

2010 ◽  
Vol 47 (2) ◽  
pp. 230-243 ◽  
Author(s):  
Mohamed A. Shahin
Keyword(s):  
Pile Foundations ◽  
Driven Piles ◽  
Cone Penetration ◽  
Intelligent Computing ◽  
Axial Capacity ◽  
Ann Models ◽  
Load Tests ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

In the last few decades, numerous methods have been developed for predicting the axial capacity of pile foundations. Among the available methods, the cone penetration test (CPT)-based models have been shown to give better predictions in many situations. This can be attributed to the fact that CPT-based methods have been developed in accordance with the CPT results, which have been found to yield more reliable soil properties; hence, more accurate axial pile capacity predictions. In this paper, one of the most commonly used artificial intelligence techniques, i.e., artificial neural networks (ANNs), is utilized in an attempt to develop artificial neural network (ANN) models that provide more accurate axial capacity predictions for driven piles and drilled shafts. The ANN models are developed using data collected from the literature and comprise 80 driven pile and 94 drilled-shaft load tests, as well as CPT results. The predictions from the ANN models are compared with those obtained from the most commonly used available CPT-based methods, and statistical analyses are carried out to rank and evaluate the performance of the ANN models and CPT methods. To facilitate the use of the developed ANN models, they are translated into simple design equations suitable for hand calculations.

scholarly journals Improving The Prediction For The Ultimate Axial Capacity Of Driven Piles In Ontario Soils With A Genetic Algorithm

2021 ◽  
Author(s):  
Markus Jesswein
Keyword(s):  
Genetic Algorithm ◽  
Influential Factors ◽  
Design Methods ◽  
Driven Piles ◽  
Compression Load ◽  
Axial Capacity ◽  
Side Resistance ◽  
Ground Conditions ◽  
Load Tests ◽  
Soil Measurements

A genetic algorithm (GA) was developed to improve predictions for the ultimate axial capacity of driven piles in Ontario soils. Challenges arise to accurately predict the ultimate capacity due to many influential factors, such as the ground conditions, installation method, and pile geometry. A total of 43 piles (H or pipe piles) were collected from the Ministry of Transportation of Ontario. Side and tip resistances were extracted from piles subjected to extension and compression load tests. The soil measurements and pile resistances were regressed with a statistical analysis and GA, and the developed relationships were compared to existing design methods. On average, existing design methods overestimated the capacity by a factor of 1.16 to 3.00. The proposed correlations were slightly conservative with the capacity but provided errors within ± 30 % of the measured side resistance. The new design methods from the GA offer substantial improvements for pile design

Estimating static tip resistance of driven piles with bottom pile instrumentation

2012 ◽  
Vol 49 (4) ◽  
pp. 381-393 ◽  
Author(s):  
Khiem T. Tran ◽  
Michael McVay ◽  
Rodrigo Herrera ◽  
Peter Lai
Keyword(s):  
Static Load ◽  
Accelerometer Data ◽  
Driven Piles ◽  
Unknown Parameters ◽  
Single Degree Of Freedom ◽  
Tip Resistance ◽  
Load Tests ◽  
Energy Equilibrium ◽  
Static Resistance ◽  
Time Assessment

A technique is presented to estimate static tip resistance of a pile during driving from embedded strain and accelerometer data located one diameter (D) from the bottom of the pile. The approach uses a nonlinear single degree of freedom system to satisfy force and energy equilibrium with a global genetic inversion approach. By balancing force and energy from inertia, damping, and stiffness against the measured tip data, the unknown parameters (mass, damping, and nonlinear stiffness) are estimated. Requiring a few seconds for analysis for each blow, the algorithm ensures a real-time assessment of static tip resistance as a function of displacement, which is important when setting pile lengths. The proposed approach was applied to four test piles at two bridge sites (Florida and Louisiana). Mobilized static tip resistances ranging from 400 to 1500 kN as a function of displacement were predicted. The predicted static resistance versus displacements compared favorably with measured values from static load tests. Interestingly, the maximum recorded increase in tip resistance in silty to clayey sands was less than 20% when piles were re-struck at times ranging from 2 to 30 days after initial drive.

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