Uneven large deformation grade prediction method suitable for soft rock tunnel

A prediction method and large deformation technology, applied in the field of high-level prediction, can solve problems such as difficult to predict the uneven degree of tunnel deformation, and achieve unique advantages, good deformation control, and high accuracy.

Active Publication Date: 2019-11-22
SHANDONG UNIV +1
View PDF7 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] According to the inventor's understanding, the traditional hierarchical prediction of tunnel deformation mainly adopts empirical formulas and numerical simulation methods, but because the uneven large deformation of soft rock tunnels is affected by various factors such as engineering geological factors and construction factors, it is a nonlinear solution problem. Traditional empirical formulas and numerical simulation methods have certain limitations, and it is difficult to predict the unevenness of tunnel deformation

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Uneven large deformation grade prediction method suitable for soft rock tunnel

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0034] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0035] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides an uneven large deformation grade prediction method suitable for a soft rock tunnel. The method comprises the following steps: acquiring geological conditions, construction conditions and deformation data of each existing soft rock tunnel, grading the non-uniform deformation degree into a basic deformation grade and a deformation non-uniform grade, classifying and quantifying main influence factors, and establishing a non-uniform large-deformation initial sample database of the soft rock tunnel; calculating subjective and objective weights of the main factors by adoptingdifferent methods to obtain a comprehensive weight, respectively calculating the correlation degree between each influence factor and the deformation grade and the deformation non-uniformity grade ofthe soft rock tunnel foundation by adopting a grey correlation degree theory, and reducing the influence factors of which the correlation degree is smaller than a set value; constructing a soft rocktunnel non-uniform large deformation artificial neural network prediction model by taking the reduced influence factor indexes as input parameters and taking the basic deformation grade and the deformation non-uniform grade as output parameters; and inputting the acquired data of the to-be-predicted soft rock tunnel into the artificial neural network prediction model to obtain a prediction result.

Description

technical field [0001] The disclosure belongs to the field of rock and soil deformation prediction, and relates to a method for predicting uneven large deformation levels of soft rock tunnels. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] Soft rock has the characteristics of low strength, large porosity, poor cementation degree, significantly affected by structure and weathering, and contains a large amount of expansive clay minerals. It will produce significant plastic deformation and rheology under the interference of engineering construction. Due to the defects in soft rock structure and strength, as well as the influence of factors such as ground stress, groundwater conditions, and construction, the surrounding rock strength and stress distribution of soft rock tunnels are different, resulting in uneven deformation, resulting in loc...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06Q10/04G06Q50/08
CPCG06Q10/04G06Q50/08
Inventor 薛翊国马新民张馨赵素志郭创科邱道宏李国勇王鹏李鹏飞
Owner SHANDONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products