A Bayesian Learning Method of p-y Curve Based on Pile Monitoring Data

A technology of Bayesian learning and monitoring data, which is applied in infrastructure testing, special data processing applications, infrastructure engineering, etc.

Active Publication Date: 2022-04-15
WUHAN UNIV
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Problems solved by technology

And limited by the load of the test, only the scatter diagram of the p-y curve at different depths can be obtained instead of the complete p-y curve, and interpolation processing is required when applying

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  • A Bayesian Learning Method of p-y Curve Based on Pile Monitoring Data
  • A Bayesian Learning Method of p-y Curve Based on Pile Monitoring Data
  • A Bayesian Learning Method of p-y Curve Based on Pile Monitoring Data

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Embodiment example

[0043]Implementation case data source: Zhu Bin, Xiong Gen, Liu Jinchao, et al. Centrifugal model test of large-diameter single pile under horizontal load in sandy soil[J]. Journal of Geotechnical Engineering, 2013(10):1807-1815.

[0044] Self-weight stress has a great influence on geotechnical engineering. At present, the indoor geotechnical centrifuge test technology is an effective geotechnical physical model test method, which can help researchers better understand the pile-soil interaction mechanism. Table 1 shows the basic parameters of the model test standard sand in the implementation case, and Table 2 shows the corresponding parameters between the model pile and the prototype pile. figure 2 It is a schematic diagram of the pile load test model of this implementation case. In this case, two laser displacement measurement points were set above the mud surface to verify the applicability of the method.

[0045] Table 1 Basic parameters of standard sand for model test

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Abstract

The invention discloses a p-y curve Bayesian learning method based on test pile monitoring data. The method makes full use of the strain data recorded during the pile load test, adopts a suitable p-y curve model, and selects a method corresponding to the properties of the soil. The parameters of the p-y curve model, while considering the unknown model error parameters, construct the likelihood function based on the p-y curve finite difference method, use the Bayesian learning framework to obtain the estimated value of the model parameters, and obtain the most likely p-y curve of the test pile site y-curve. It has guiding significance for the design of large-scale horizontal bearing piles around the site, and promotes the designer's in-depth understanding of the mechanism of pile-soil interaction.

Description

technical field [0001] The invention belongs to the field of geotechnical engineering parameter learning, and relates to a method for obtaining p-y curves of pile foundations, in particular to a Bayesian learning method for p-y curves based on test pile monitoring data, which can obtain complete data at each depth of test pile sites p-y curve. Background technique [0002] With the rapid and continuous development of my country's economy, horizontal bearing piles have been widely used in construction engineering, geotechnical engineering, railway engineering, bridge engineering, marine engineering and other major projects, such as: foundation treatment around subway stations, building foundation pit support, Mountain slope reinforcement, offshore oil platform wind and wave design, etc. Therefore, how to conduct reasonable structural analysis of horizontal bearing piles at different sites has become a problem worthy of attention, which directly affects the design of horizonta...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/23G06F30/13G06K9/62E02D33/00
CPCG06F30/23G06F30/13E02D33/00G06F18/29
Inventor 曹子君唐畅李典庆
Owner WUHAN UNIV
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