A rapid identification and classification method for large deformation in soft rock applied in construction

Abstract

This invention relates to the field of large deformation identification in soft rock, addressing the problem that existing technologies for large deformation identification in the early stages of construction rely solely on natural environmental factors while neglecting human factors, resulting in poor accuracy and difficulty in accurately guiding the improvement of plans in the later stages of construction. The invention provides a rapid identification and classification method for large deformation in soft rock applied to construction, comprising: S1: weight analysis of classification indicators; S2: selecting indicators with a large weight and easy access in the early stages of construction as characteristic indicators; S3: collecting and statistically analyzing characteristic indicators of typical sections with different degrees of large deformation and combining the large deformation degree corresponding to each characteristic indicator to derive a rapid large deformation classification table. The rapid identification and classification method for large deformation in soft rock provided by this invention can predict the large deformation of subsequent sections based on the large deformation classification method obtained from the already constructed sections and guide the improvement of subsequent construction plans.

Description

Technical Field

[0001] This invention relates to the field of large deformation identification in soft rock, and more specifically, to a rapid identification and classification method for large deformation in soft rock applied in construction. Background Technology

[0002] Currently, large deformation classification methods for soft rock tunnels are generally applicable to the exploration and design phase. These methods use relative deformation and strength stress, along with other influencing factors from the exploration and design phase, as reference indicators, such as lateral pressure coefficient, large deformation trend, rock elastic modulus, maximum principal stress, and support stiffness. However, some of these indicators, such as rock elastic modulus and maximum principal stress, are difficult to obtain accurately during the tunnel exploration and design phase. Furthermore, indicators like strength-stress ratio, relative deformation, lateral pressure coefficient, and large deformation trend require additional work on each predicted section, building upon traditional tunnel exploration reports. Therefore, current large deformation classification methods are not very practical for the construction phase. Patent CN115470553A discloses a method for predicting the classification of large deformation in soft rock tunnels. It uses burial depth and rock strata conditions as classification indicators, but the rock strength needs to be determined experimentally. Furthermore, it primarily considers the influence of environmental conditions on large deformation, neglecting the impact of artificial support during construction. Therefore, it offers limited guidance for improving construction plans in the later stages of the project. There is an urgent need for a rapid classification method applicable to construction sites, based on geological conditions and deformation patterns, to improve the accuracy of identifying large deformation in soft rock. This method would provide targeted support plans of different levels in the early stages of excavation, thus improving the problem of large deformation in the later stages of construction. Summary of the Invention

[0003] The purpose of this invention is to provide a rapid identification and classification method for large deformations in soft rock applied to construction, which solves the problem that the accuracy of large deformation judgment in the early stage of construction is poor because it only considers natural environmental factors and does not consider human factors, making it difficult to accurately guide the improvement of the scheme in the middle and later stages of construction.

[0004] This invention is achieved through the following technical solution:

[0005] A rapid identification and classification method for large deformations in soft rock applied in construction includes,

[0006] S1: Weight analysis of hierarchical indicators;

[0007] S2: Select indicators with a large weighting and easy to obtain in the early stage of construction as feature indicators;

[0008] S3: Collect and statistically analyze the characteristic indicators of typical cross sections with different degrees of large deformation, and combine the large deformation degree corresponding to each characteristic indicator to obtain a rapid classification table of large deformation.

[0009] The characteristic indexes include: lithology and geological structure, the maximum deformation rate within three days, the cumulative deformation amount of the monitoring section within 10 meters, groundwater conditions, and the deformation and failure characteristics of the supported section;

[0010] The degree of large deformation is divided into slight large deformation, medium large deformation, severe I large deformation, and severe II large deformation.

[0011] In the selection of characteristic indexes of this application, the deformation and failure characteristics of the supported section are included. The degree of large deformation that may occur in the unconstructed section is predicted based on the deformation degree of the constructed section and its corresponding characteristic data, providing an effective guidance for improving the construction plan of the unconstructed section. At the same time, the characteristic indexes selected in this application are derived from the construction site and are easy to obtain; there is a strong correlation between the characteristic indexes and the large deformation of the soft rock tunnel, which can ensure the accuracy of the large deformation classification.

[0012] Preferably, the lithology includes lithology composition and proportion, rock mass structure, and rock mass strength.

[0013] Preferably, the rock mass strength is characterized by the shape of the tunnel face; the rock mass strength is divided into relatively hard rock, relatively soft rock, soft rock, and extremely soft rock; when the rock is relatively hard, a complete tunnel face can be formed after excavation; when the rock is relatively soft, there is slight spalling on the tunnel face after excavation; when the rock is soft, there is serious spalling on the tunnel face after excavation; when the rock is extremely soft, the tunnel face is powdery after excavation.

[0014] In this application, the rock mass strength does not need to be obtained through experiments, but is creatively characterized by the situation of the tunnel face after excavation. The data is easier to obtain, which is convenient for quickly judging the large deformation situation.

[0015] Preferably, the degree of large deformation is divided according to the maximum deformation rate within three days and the cumulative deformation amount of the monitoring section within 10 meters; the cumulative deformation amount of the monitoring section within 10 meters includes the cumulative deformation amount in five days and the cumulative deformation amount in ten days.

[0016] Preferably, the maximum deformation rates within three days corresponding to the slight large deformation, the medium large deformation, the severe I large deformation, and the severe II large deformation are 5 mm / d - 10 mm / d, 10 mm / d - 20 mm / d, 20 mm / d - 30 mm / d, and greater than 30 mm / d, respectively.

[0017] Preferably, the cumulative deformation over five days corresponding to the slight large deformation, the moderate large deformation, the severe large deformation I, and the severe large deformation II are 20mm-40mm, 40mm-80mm, 80mm-120mm, and greater than 120mm, respectively; and the cumulative deformation over ten days corresponding to the slight large deformation, the moderate large deformation, the severe large deformation I, and the severe large deformation II are 30mm-80mm, 80mm-150mm, 150mm-210mm, and greater than 210mm, respectively.

[0018] Preferably, the geological structure includes the degree of tectonic influence, the degree of joint development, and the state of the surrounding rock after excavation.

[0019] Preferably, the groundwater conditions corresponding to the slight large deformation, the moderate large deformation, the severe I large deformation, and the severe II large deformation are respectively dry-seepage, seepage / dampness, seepage / dampness / dripping, and dampness / dripping / stranded.

[0020] Preferably, the deformation and failure characteristics of the supported section include the deformation characteristics of the tunnel wall and the failure characteristics of the first layer of initial support.

[0021] Based on the failure characteristics of the initial support, the direction of support improvement for subsequent sections can be determined.

[0022] Preferably, S1 specifically involves using the fuzzy evaluation matrix method to obtain the probability of influence of each graded index on large deformation.

[0023] The present invention has at least the following beneficial effects: the feature data is easy to obtain during the construction stage and includes the deformation and failure characteristics of the supported section. The large deformation classification obtained by combining natural environmental factors and human support scheme factors is more accurate. It can predict the large deformation of subsequent sections based on the large deformation classification method obtained from the constructed section and guide the improvement of subsequent construction schemes. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 A probability diagram showing the impact of each graded index on large deformation;

[0026] Figure 2 A graph showing the relationship between maximum deformation rate and tunnel mileage;

[0027] Figure 3This is a graph showing the relationship between the lithology and structural classification of the tunnel face and the maximum deformation rate. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0029] Example 1:

[0030] An analysis of various construction indicators for the Desheng Tunnel, combined with the large deformation of soft rock, yielded a large deformation classification index table, as follows:

[0031] A rapid identification and classification method for large deformations in soft rock applied in construction includes,

[0032] S1: Weight Analysis of Grading Indicators: The fuzzy evaluation matrix method was used to derive the probability diagram of the influence of each grading indicator on large deformation, see... Figure 1 ;

[0033] S2: Select indicators with a large weighting and easy to obtain in the early stage of construction as feature indicators;

[0034] To quickly determine the large deformation of the tunnel surrounding rock during construction, and considering the ease of obtaining relevant indicators, the integrity of the surrounding rock is described using lithology and geological structure. Support quality is evaluated using the initial support deformation characteristics and support failure characteristics. Monitoring parameters are based on the cumulative maximum deformation and deformation rate of the supported section within 10m. Groundwater conditions are assessed using the state of groundwater after excavation. While the strength-stress ratio also has a significant impact, it requires geodetic stress measurement and laboratory rock strength testing for calculation, which is cumbersome to obtain during the erection stage.

[0035] S3: Collect and statistically analyze the characteristic indicators of typical cross sections with different degrees of large deformation, and combine the large deformation degree corresponding to each characteristic indicator to obtain a rapid classification table of large deformation.

[0036] To analyze the relationship between various construction indicators and the large deformation of the soft rock in the Desheng Tunnel, the maximum deformation rate, maximum cumulative deformation over 5 days and 10 days for each section were plotted and analyzed (see...). Figure 2 The surrounding rock was classified into minor, moderate, severe I, and severe II large deformation categories according to the lithology of the tunnel face. This classification is in good agreement with the results of large deformation classification based on the maximum deformation rate and the cumulative deformation over 5 days / 10 days (see...). Figure 3 ).

[0037] By analyzing information from several construction sections, including face sketches, deformation rates, maximum cumulative deformation, and failure modes of supported sections, a rapid classification method for large deformations in soft rock applicable to construction was finally derived, as shown in Table 1.

[0038] Table 1

[0039]

[0040]

[0041] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A rapid identification and classification method for large deformations in soft rock applied in construction, characterized in that, Includes the following steps: S1: Use the fuzzy evaluation matrix method to analyze the weights of the hierarchical indicators; S2: Select indicators with high weighting and easy to obtain in the early stages of construction as characteristic indicators. These characteristic indicators include lithology and geological structure, maximum deformation rate within three days, cumulative deformation of the monitoring section within 10 meters, groundwater conditions, and deformation and failure characteristics of the supported section. Among them, lithology includes lithological composition and proportion, rock mass structure, and rock mass strength. Rock mass strength is characterized by the morphology of the tunnel face. Rock mass strength is divided into relatively hard rock, relatively soft rock, soft rock, and extremely soft rock. When the rock is relatively hard, a complete tunnel face can be formed after excavation. When the rock is relatively soft, the tunnel face will experience slight spalling after excavation. When the rock is soft, the tunnel face will experience severe spalling after excavation. When the rock is extremely soft, the tunnel face will be powdery after excavation. Geological structure includes the degree of structural influence, the degree of joint development, and the state of the surrounding rock after excavation. The cumulative deformation of the monitoring section within 10 meters includes the cumulative deformation over five days and the cumulative deformation over ten days. The deformation and failure characteristics of the supported section include the tunnel wall deformation characteristics and the failure characteristics of the first layer of initial support. S3: Collect and statistically analyze the characteristic indicators of typical cross-sections with different degrees of large deformation, and combine the large deformation degree corresponding to each characteristic indicator to derive a rapid classification table for large deformation; the large deformation degree is divided into slight large deformation, moderate large deformation, severe I large deformation, and severe II large deformation; among them, the maximum deformation rate within three days corresponding to slight large deformation, moderate large deformation, severe I large deformation, and severe II large deformation is 5mm / d-10mm / d, 10mm / d-20mm / d, 20mm / d-30mm / d, and greater than 30mm / d, respectively; the corresponding cumulative deformation over five days is 20mm-40mm, 40mm-80mm, 80mm-120mm, and greater than 120mm, respectively; the corresponding cumulative deformation over ten days is 30mm-80mm, 80mm-150mm, 150mm-210mm, and greater than 210mm, respectively; the corresponding groundwater conditions are dry-seepage, seepage / dampness, seepage / dampness / dripping, and dampness / dripping / strips, respectively.

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