Analytic Method of Load-Displacement Curve for Tension Anchors Based on Hyperbolic Load-Transfer Function

2010 ◽  
Author(s):  
Wei Liu ◽  
Long-zhu Chen ◽  
Xiao-zhou Xi
Keyword(s):  
Transfer Function ◽  
Load Transfer ◽  
Displacement Curve ◽  
Analytic Method ◽  
Load Transfer Function ◽  
Load Displacement

Normalized Numerical Analysis for Load-Displacement Curve of Uplift Pile in Soft Soil

2012 ◽  
Vol 446-449 ◽  
pp. 1462-1467 ◽  
Author(s):  
Xiao Bing Li ◽  
Jie Wei ◽  
Yi Pin Li ◽  
Bei Zhu
Keyword(s):  
Test Data ◽  
Load Transfer ◽  
Soft Soil ◽  
Displacement Curve ◽  
Analysis Method ◽  
Regression Formula ◽  
Calculation Results ◽  
Load Transfer Function ◽  
Load Displacement ◽  
Uplift Pile

On the basis of Hsiung’s normalization analysis method, the soil is assumed to be in accordance with the elastic-plastic model. Some normalized parameters are selected to normalize different load-displacement curves to a single one, which is obtained by using the parabolic load transfer function. At last, we get a regression formula of the single curve with the regression analysis method. By comparing the results of regression formula with the practical test data of projects, the fact that the calculation results of regression formula coincide well with test data show that this analysis method is correct and it can provide reference for the research and application of uplift pile.

scholarly journals Proposed point bearing load transfer function in jointed rock-socketed drilled shafts

2013 ◽  
Vol 53 (4) ◽  
pp. 596-606 ◽  
Author(s):  
Jaehwan Lee ◽  
Kwangho You ◽  
Sangseom Jeong ◽  
Jaeyoung Kim
Keyword(s):  
Transfer Function ◽  
Load Transfer ◽  
Jointed Rock ◽  
Drilled Shafts ◽  
Bearing Load ◽  
Load Transfer Function

scholarly journals Studi Daya Dukung Fondasi Tiang Pada Tanah Lempung Teguh Berdasarkan Pembebanan Kepala Tiang Dan Pergerakan Ujung Tiang Metode T-Z

2020 ◽  
Vol 3 (2) ◽  
pp. 88
Author(s):  
Mochamad fikri firmansyah Fikri Firmansyah ◽  
Rakha Fausta ◽  
Helmy Darjanto
Keyword(s):  
Shear Strength ◽  
Transfer Function ◽  
Bearing Capacity ◽  
Surface Properties ◽  
Pile Foundation ◽  
Load Transfer ◽  
Load Transfer Function

Developments in the calculation of foundation planning today have produced many methods and formulas for calculating the bearing capacity of foundations, such as the T-Z method, the Tezaghi method, the Mayerhof method, the Tomlison method, and other methods. So the purpose of this study was to determine the bearing capacity from tip movement of the foundation of each load with the T-Z method. The T-Z method explains rationally the mechanism of load transfer using a load transfer function commonly called TZ. In this method the pile foundation will be divided into several segments and the transfer function on each side segment which is a function of the shear strength of the soil and the surface properties of the side pile. From the analysis results of the TZPILE application, the bearing capacity is due to the settlement. At a settlement of 0,0001m; 0.001m; 0.0015m; 0.0025m; and 0.005m get a bearing capacity of 4.31kN; 31.69 kN; 35.6 kN; 43.44 kN; and 60.10kN. And on the reduction of permits on the foundation that occurs according to SNI 8460 - 2017 is 25mm, so the analysis obtained 12mm which still meets the requirements, 12mm get a bearing capacity of 1200kN at the tip of the pile. At a load of 600 kn the head of the pile can be held at a depth 4 meters. And for the maximum bearing capacity of the 18 meter pole, it can whitstand a bearing capacity of 1200 kn.

scholarly journals Analytical Model and Back-Analysis for Pile-Soil System Behavior under Axial Loading

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Hong-Fa Xu ◽  
Ji-Xiang Zhang ◽  
Xin Liu ◽  
Han-Sheng Geng ◽  
Ke-Liang Li ◽  
...  
Keyword(s):  
Transfer Function ◽  
Analytical Model ◽  
Axial Force ◽  
Load Transfer ◽  
Back Analysis ◽  
Axial Loading ◽  
Distribution Functions ◽  
Soil System ◽  
Relationship Model ◽  
Load Transfer Function

The interaction mechanism between piles and soils is very complicated. The load transfer function is generally nonlinear and is affected by factors such as pile side roughness, soil characteristics, section depth, and displacement. Therefore, it is difficult to solve the pile-soil system based on load transfer function. This paper presents a new method to study the soil-pile interaction problem with respect to axial loads. First, the shapes of the axial force-displacement curves at different depths and the displacement distribution curves along pile axis at different pile-top displacements were analyzed. A simple exponential function was taken as relationship model to express the relationship curves between two distribution functions of axial force and displacement along pile shaft obtained by using the geometric drawing method. Second, a new analytical model of the pile-soil system was established based on the basic differential equations for pile-soil load transfer theory and the relationship model and was used to derive the mathematical expressions on the distribution functions of the axial force, the lateral friction, and the displacement along pile shaft and the load transfer function of pile-side. We wrote the MATLAB program for the analytical model to analyze the influence laws of the parameters u and m on the pile-soil system characteristics. Third, the back-analysis method and steps of the pile-soil system characteristics were proposed according to the analytical model. The back-analysis results were in good agreement with the experimental results for the examples. The analysis model provides an effective way for the accurate design of piles under axial loading.

scholarly journals Random Forest-Based Ensemble Machine Learning Data-Optimization Approach for Smart Grid Impedance Prediction in the Powerline Narrowband Frequency Band

2020 ◽  
Author(s):  
Emmanuel Oyekanlu ◽  
Jia Uddin
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Transfer Function ◽  
Smart Grid ◽  
Load Transfer ◽  
Transfer Functions ◽  
Optimization Approach ◽  
Powerline Communication ◽  
Load Transfer Function ◽  
Ensemble Regression

In this chapter, the random forest-based ensemble regression method is used for the prediction of powerline impedance at the powerline communication (PLC) narrowband frequency range. It is discovered that while PLC load transfer function, phase, and frequency are crucial to powerline impedance estimation, the problem of data multicollinearity can adversely impact accurate prediction and lead to excessive mean square error (MSE). High MSE is obtained when multiple transfer functions corresponding to different PLC load transfer functions are used for random forest ensemble regression. Low MSE indicating more accurate impedance prediction is obtained when PLC load transfer function data is selectively used. Using data corresponding to 200, 400, 600, 800, and 1000 W PLC load transfer functions together led to poor impedance prediction, while using lesser amount of carefully selected data led to better impedance prediction. These results show that artificial intelligence (AI) methods such as random forest ensemble regression and deterministic data-optimization approach can be utilized for smart grid (SG) health monitoring applications using PLC-based sensors. Machine learning can also be applied to the design of better powerline communication signal transceivers and equalizers.

scholarly journals Simulation Research on the Load Transfer Mechanism of Anchoring System in Soft and Hard Composite Rock Strata under Tensile Loading Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Ning Li ◽  
Zhanguo Ma ◽  
Peng Gong ◽  
Fuzhou Qi ◽  
Tuo Wang ◽  
...  
Keyword(s):  
Load Transfer ◽  
Hard Rock ◽  
Peak Load ◽  
Thickness Ratio ◽  
Displacement Curve ◽  
Initial Stiffness ◽  
Bond Slip ◽  
Anchoring System ◽  
Load Displacement ◽  
Rock Strata

Soft and hard composite rock strata are frequently encountered in transportation, geotechnical, and underground engineering. However, most of the current support is designed for homogeneous rock masses, which ignores the different anchoring effect in soft and hard composite rock strata. A numerical study is presented in this paper on the pull-out behavior of fully grouted rock bolts in soft and hard composite rock strata. The nonlinear bond-slip relationship of bolt-grout interface that is anchored in soft rock and hard rock is obtained from laboratory test, respectively. Then, the nonlinear bond-slip relationship is put into the numerical model. The numerical result shows a close match with the experiment tests and the proposed model. Lithological sequence, layer thickness ratio, and layer numbers are taken into consideration in numerical simulation models. Under the same layer number, the shallower-soft and deeper-hard composite rock strata (SHCRS) have a higher bearing capacity and deformation resistance than the shallower-hard and deeper-soft composite rock strata (HSCRS). As the soft-to-hard thickness ratio in SHCRS increases, the initial stiffness of the load-displacement curve and peak load decreases continuously. The load-displacement curve shows the same initial stiffness for different hard to soft thickness ratios in HSCRS. As the hard to soft thickness ratio increases, the load peak and the displacement at the peak load increase. Therefore, the closer the hard rock is to the loading end, the greater the initial stiffness of the load-displacement curve is. The greater the hard rock thickness, the larger the peak load. Under the same anchor length, the peak load and the displacement at the peak load decrease with the increase of layer numbers, but the reduction magnitude decreases. This paper leads to a better understanding of the load transfer mechanism for the anchoring system in soft and hard composite strata and provides a reference for scientific support design and evaluation method.

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