CN-116306245-B - Three-dimensional dynamic quantitative evaluation method for stability of surrounding rock of deep hard rock tunnel

Abstract

The invention provides a three-dimensional dynamic quantitative evaluation method for surrounding rock stability of a deep hard rock tunnel, which relates to the technical field of deep tunnel surrounding rock stability evaluation and intelligent construction, and comprises the steps of dynamically determining tunnel geology and surrounding rock parameters based on a digital means and a site in-situ test means; the method comprises the steps of calculating the stress distribution of a damaged area based on GZZ three-dimensional strength criteria and considering three-dimensional complex high ground stress, and rapidly and quantitatively solving the distribution form of the damaged area based on an artificial intelligence algorithm. According to the invention, the stress precise control and the precise analysis are taken as the tunnel design concept, and on the basis of considering the joint, the fissure, the excavation disturbance, the surrounding rock strength characteristic and the mechanical mechanism of the surrounding rock of the deep tunnel, the characteristic of strong global optimizing capability of an intelligent algorithm and the characteristic of high-efficiency calculation of a traditional analysis method are utilized to obtain a programmed flow for calculating a surrounding rock damage area, so that the precise, rapid and dynamic analysis of the surrounding rock stability in the tunneling process is realized.

Inventors

• Ma Yaocai
• ZHU HEHUA
• Cai Wuqiang
• WEI XIANGYANG
• SU CHENLONG

Assignees

• 同济大学

Dates

Publication Date

20260508

Application Date

20230208

Claims (4)

1. 1. A three-dimensional dynamic quantitative evaluation method for stability of surrounding rock of a deep hard rock tunnel is characterized by comprising the following steps: s1, acquiring parameters of tunnel geology and surrounding rock through an in-situ test means and a digital means; S2, constructing a tunnel surrounding rock three-dimensional mechanical analysis model based on GZZ three-dimensional rock strength criteria by using the acquired parameters, and giving a control equation and an objective function of a damaged area; S3, packaging related parameters and target functions into an artificial intelligent algorithm, and solving the target functions by using the artificial intelligent algorithm; s4, automatically executing stability evaluation after parameter dynamic update in the tunneling process by using a packaged artificial intelligence algorithm program; the step S2 specifically comprises the following steps: S21, constructing a control equation for obtaining internal stress distribution of a surrounding rock breaking area according to static equilibrium conditions and GZZ three-dimensional strength criteria, wherein the GZZ three-dimensional strength criteria are expressed as follows: ; Wherein, the ; ; S22, giving stress distribution in an undamaged area of the surrounding rock by using two elastic complex functions; s23, giving out a control equation set for determining the damaged area according to a static balance principle, and giving out an objective function for solving the damaged area; In S21, the internal stress distribution in the surrounding rock destruction area is realized by the following steps: S211, establishing a non-associated plastic potential function Q, which is expressed as: ; Wherein beta is a volume correction coefficient reflecting the shear expansion characteristic of the rock mass; The relation of the tunnel out-of-plane plastic stress s z is obtained and determined according to the uncorrelated plastic potential function Q, the plastic flow rule and the tunnel axial strain e z , and is expressed as follows: ; wherein dl is a positive scale factor; s212, substituting the relation of the tunnel face external plastic stress S z determined in S211 into GZZ three-dimensional strength criterion to obtain an in-plane stress control equation about surrounding rock perpendicular to the tunneling direction, wherein the in-plane stress control equation is expressed as: ; Wherein, the A is determined according to the magnitude of the axial strain e z of the tunnel when The plane strain model is obtained when a is 0.5; S213, combining the control equation with a balance differential equation, and acquiring the stress distribution of surrounding rock in a damaged area by adopting a sliding line method; in S22, the stress distribution in the undamaged area of the surrounding rock is achieved by the following steps: S221, representing the boundary of a damaged area in the surrounding rock by a mapping function, wherein the mapping function is in the form of Taylor series and is expressed as follows: ; Wherein R and The mapping function coefficients are to be solved, and are real numbers; Solving the mapping function coefficient is equivalent to determining the distribution form of the damaged area, namely parameterizing and quantitatively representing the shape and the size of the damaged area; s222 the stress distribution in the undamaged area of the surrounding rock is represented using two ground-dependent complex functions in the form of Taylor series expressed as: ; ; Wherein, the And Are real numbers; 40; s223, after the mapping function coefficient is given, the stress distribution in the undamaged area of the surrounding rock is given according to the following equation: ; ; Wherein, the 、 、 A polar coordinate representation of in-plane stress components of the undamaged area of the surrounding rock; In S23, the objective function of the damaged area is specifically solved by the following steps: s231, according to the static equilibrium condition on the boundary of the damaged area, listing the equation: ; Wherein, the 、 、 A polar coordinate representation of the in-plane stress component of the surrounding rock failure area; s232, constructing the following matrix according to the equation: ; ; ; Wherein, the ; ; ; S233, listing the solving according to the matrix And Is a linear system of equations: ; Wherein the method comprises the steps of ; ; ; Wherein, the And Respectively is Real and imaginary parts of (a); And Respectively sum to Real and imaginary parts of (a); s234, giving an objective function for solving the damaged area as follows: ; Wherein, the The unit of (2) is the same as the stress component; the size of (2) reflects the degree to which the equilibrium conditions in the undamaged zone of the surrounding rock are satisfied when When the value of (2) is 0, obtaining the true solution of the damaged area; The step S3 specifically comprises the following steps: s31, setting the tunnel geology and surrounding rock parameters related to the damaged area to the known quantity capable of being dynamically assigned, and setting an objective function Setting an adaptability function of an artificial intelligent algorithm; s32 mapping function coefficients R characterizing the shape and size of the damaged area, In order to serve as a design variable, the range of the design variable in an algorithm is given, algorithm parameters are reasonably set, a population is initialized, and the fitness of each individual in the population is calculated; S33, based on the thought of biological genetic evolution, storing variant individuals favorable for adapting to the environment, and continuously breeding offspring to obtain individuals most favorable for survival to obtain the latest parameters of the most favorable individuals, namely, continuously approaching the shape and the size of a damage area in the invention; And S34, judging whether the latest variant reaches the maximum genetic algebra or satisfactory precision, if so, outputting the shape and the size of the surrounding rock destruction zone, and if not, repeating the steps S32-S34 based on the latest parameters until the judgment result is yes.
2. 2. The three-dimensional dynamic quantitative evaluation method for stability of surrounding rock of deep hard rock tunnel according to claim 1, wherein the step S1 specifically comprises the following steps: S11, carrying out in-situ acquisition of fine digital information by utilizing a digital means, and determining a geological strength index GSI and a disturbance coefficient D; S12, obtaining the rock hardness degree m i by means of rebound dynamics test or empirical statistical model, and further calculating rock strength parameters m b , S and a by combining the parameters GSI and D obtained in S11 The calculation formulas of s and a are expressed as: ; s13, acquiring uniaxial compressive strength of the rock by utilizing a field true triaxial test The horizontal ground stress p and the vertical ground stress q of the in-situ test are obtained by adopting a hydraulic fracturing method and an acoustic emission method.
3. 3. The three-dimensional dynamic quantitative evaluation method for stability of surrounding rock of deep hard rock tunnel according to claim 1, wherein in S32, the artificial intelligence algorithm is a differential evolution algorithm, and parameters of the differential evolution algorithm are set as follows: DE algorithm parameters Value taking Number of design variables m + 1 Population size 20 Crossover probability 0.5 Scaling factor 0.5 Number of iterations 200 The range of values for each design variable is as follows: R/R 0 c 0 /R 0 c 1 /R 0 c 2 /R 0 c 3 /R 0 c 4 /R 0 c 5 R 0 c 6 /R 0 [0.5,5] [-0.1,0.1] [-0.5,0.5] [-0.5,0.5] [-0.5,0.5] [-0.5,0.5] [-0.5,0.5] [-0.5,0.5] Wherein R 0 is the tunnel radius.
4. 4. The three-dimensional dynamic quantitative evaluation method for stability of surrounding rock of deep hard rock tunnel according to claim 3, wherein the step S4 specifically comprises the following steps: S41, packaging the programming flow into a differential evolution algorithm; S42, solving an objective function by using a differential evolution algorithm; and S43, based on the solution obtained in the step S42, the support structure design and construction are guided, and the steps S1-S42 are repeated in the tunneling process so as to achieve the purpose of dynamic design.

Description

Three-dimensional dynamic quantitative evaluation method for stability of surrounding rock of deep hard rock tunnel Technical Field The invention belongs to the technical field of tunnel excavation engineering, and particularly relates to a three-dimensional dynamic quantitative evaluation method for stability of surrounding rock of a deep hard rock tunnel. Background Tunnels (or roadways) are one of the most common structures in underground engineering and play a vital role in many super projects in the country. With the further western shift of the construction center of the iron (public) road network in China, the exploitation of deep mineral resources and the construction of fourteen-five planning 'traffic country' strategic projects, tunnel projects rapidly develop towards the trend of deep burial growth, and the deep march is a big theme of twenty-first century underground projects. Tunnel construction presents challenges due to the complex geological conditions in which deep tunnels are located. The deep rock mass has obvious differences with the shallow rock mass in the aspects of mechanical properties such as structure, deformation, strength and the like, and the deep tunnel disaster mechanism is more complex, wherein the collapse instability of the tunnel dangerous rock caused by the damage of the hard rock mass under the complex high-ground stress condition, the safety, the progress and the quality of tunnel engineering construction are directly related to high-strength and high-frequency rock burst, and the deep tunnel disaster mechanism is a hot spot and a difficult point of deep engineering research. The tunnel excavation disturbs the rock mass which is originally in an equilibrium state, the stress redistribution is generated on surrounding rocks of the tunnel, the surrounding rocks are extremely easy to exceed the elastic limit under the action of three-dimensional high ground stress, so that relaxation, yielding and destruction are generated, and a so-called destruction area (or a loosening ring) is formed around the tunnel. The distribution form of the damaged area plays an important reference role in the stability evaluation of the surrounding rock of the tunnel and the support design in the subsequent construction process. The formation of the fracture zone is a dynamic process that changes shape and size as the face is propelled. In the construction process, the thickness of the damaged area can be measured through an on-site in-situ device, so that the preset design of the supporting structure is corrected and perfected to achieve the purpose of dynamic design. However, for tunnels with large sections, the thickness of the surrounding rock damage area exceeds the maximum detection distance of the device, so that accurate measurement cannot be performed. The large thickness of the damaged area also leads to the inability to effectively reinforce the surrounding rock by arranging anchor rods with limited length, and the surrounding rock can be protected only by (multiple) applying measures such as a steel arch and a concrete lining. For hard surrounding rock, the hard surrounding rock is not obviously deformed before being damaged, the traditional displacement (rate) monitoring means is difficult to perform real-time early warning on the tunnel disasters, and the tunnel safety is difficult to ensure. Therefore, a rapid prediction method for developing a reasonable and effective surrounding rock damage area has important promotion significance for guiding the dynamic design of the deep tunnel. Tunnel engineering often occurs in concealed and complex geological environments, and the geological bodies to be excavated cannot be fully known through the existing exploration technology or means, so that the tunnel engineering has potential risks. The existing construction system with separated design and construction breaks the relation between the design and the construction system, and the dynamic modification and improvement of the preset design scheme are difficult to carry out according to the exposed geological conditions and various changes in construction in the construction process. The dynamic design concept of the tunnel based on digitalization emphasizes that the rationality of the design is judged in time in the construction process, and the support parameters and the construction scheme are adjusted, so that the support structure is more suitable for the actual situation of surrounding rock, and the investment benefit and the comprehensive benefit of tunnel engineering are improved. Digital dynamic designs are generally integrated based on a digital platform and a numerical analysis program, but the complexity of digital and numerical modeling and the huge time cost of numerical calculation in the prior art are not enough to meet the real-time requirement of the dynamic design. The traditional experience analogy method is weak in objectivity, is difficult to consider the influence