CN-122021028-A - Large-scale rock mass mechanical parameter optimization method based on multi-scale test data

CN122021028ACN 122021028 ACN122021028 ACN 122021028ACN-122021028-A

Abstract

The invention discloses a large-scale rock mass mechanical parameter optimization method based on multi-scale test data, and relates to the technical field of parameter optimization. Collecting test process data of multiple rock mass test scales, carrying out energy evolution analysis on the test process data to obtain a multi-scale abnormal path database, collecting energy path characteristic data of rock mass simulation engineering scales, carrying out multi-characteristic association analysis to obtain rock mass test scale matching evaluation values of the rock mass simulation engineering scales, carrying out deviation discriminant analysis on the rock mass test scale matching evaluation values, processing to obtain energy path matching information of the rock mass simulation engineering scales, further carrying out path correction constraint on a mechanical parameter optimization process of the rock mass simulation engineering scales, carrying out path deviation analysis on the path correction constraint process to obtain path deviation characteristic values, and carrying out updating optimization configuration on associated rock mass mechanical parameters according to the path deviation characteristic values, thereby improving reliability and engineering safety of rock mass mechanical parameter optimization.

Inventors

WANG LV
PANG BO
WANG DI
YUAN YANG
GAO YUAN
ZHANG GUANG
JIN SHUKAI
WANG HAN

Assignees

应急管理部信息研究院(煤炭信息研究院)

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (10)

1. The method for optimizing the mechanical parameters of the large-scale rock mass based on the multi-scale test data is characterized by comprising the following steps of: Collecting test process data of multiple rock mass test scales, performing energy evolution analysis on the test process data to obtain energy path characteristic data of each rock mass test scale, and performing anomaly association analysis on the energy path characteristic data of each rock mass test scale to obtain a multi-scale anomaly path database; Collecting energy path characteristic data of a rock mass simulation engineering scale, and carrying out multi-characteristic association analysis on the energy path characteristic data of the rock mass simulation engineering scale by combining a multi-scale abnormal path database to obtain each rock mass test scale matching evaluation value of the rock mass simulation engineering scale; Performing deviation discriminant analysis on each rock mass test scale matching evaluation value of the rock mass simulation engineering scale to obtain each rock mass test scale matching evaluation result of the rock mass simulation engineering scale, and processing to obtain energy path matching information of the rock mass simulation engineering scale based on each rock mass test scale matching evaluation result of the rock mass simulation engineering scale so as to perform path correction constraint on a mechanical parameter optimization process of the rock mass simulation engineering scale; And carrying out path deviation analysis on the path correction constraint process to obtain a path deviation characteristic value of the rock mass simulation engineering scale, and updating and optimizing configuration on the mechanical parameters of the associated rock mass according to the path deviation characteristic value of the rock mass simulation engineering scale.
2. The method for optimizing large-scale rock mechanical parameters based on multi-scale test data according to claim 1, wherein the method for performing energy evolution analysis on the test process data is as follows: The test process data of the multi-rock test scale comprise mechanical response data, displacement data, internal pore pressure data and energy data of each rock test scale; Performing displacement energy analysis on the displacement data of each rock mass test scale to obtain a displacement response curve of each rock mass test scale, performing pore energy dissipation analysis on the internal pore pressure data of each rock mass test scale to obtain an internal pore pressure change curve of each rock mass test scale, and performing energy dissipation integration analysis on the energy data of each rock mass test scale to obtain an energy dissipation curve of each rock mass test scale; and constructing and obtaining the energy path characteristic data of each rock mass test scale according to the mechanical response curve, the displacement response curve, the internal pore pressure change curve and the energy dissipation curve of each rock mass test scale.
3. The method for optimizing large-scale rock mechanical parameters based on multi-scale test data according to claim 2, wherein the method for performing anomaly association analysis on the energy path characteristic data of each rock test scale is as follows: and extracting energy path characteristic data of each rock mass test scale, analyzing to obtain abnormal path types of each rock mass test scale, and constructing to obtain a multi-scale abnormal path database according to the energy path characteristic data of each rock mass test scale and the corresponding abnormal path types.
4. The method for optimizing mechanical parameters of a large-scale rock mass based on multi-scale test data according to claim 1, wherein the energy path characteristic data of the rock mass simulation engineering scale comprises a mechanical response curve, a displacement response curve, an internal pore pressure change curve and an energy dissipation curve of the rock mass simulation engineering scale.
5. The method for optimizing large-scale rock mechanical parameters based on multi-scale test data according to claim 4, wherein the method for performing multi-feature correlation analysis on the energy path feature data of the rock simulation engineering scale is as follows: And performing multi-feature correlation analysis on the energy path characteristic data of the rock mass simulation engineering scale and the energy path characteristic data of all rock mass test scales in a multi-scale abnormal path database to obtain each rock mass test scale matching evaluation value of the rock mass simulation engineering scale and a corresponding abnormal path type, wherein each rock mass test scale matching evaluation value of the rock mass simulation engineering scale is used for representing a quantification result of the energy path consistency degree of the rock mass simulation engineering scale under different rock mass test scales.
6. The method for optimizing mechanical parameters of a large-scale rock mass based on multi-scale test data according to claim 5, wherein the method for performing deviation discrimination analysis on each rock mass test scale matching evaluation value of a rock mass simulation engineering scale is as follows: And comparing each rock mass test scale matching evaluation value of the rock mass simulation engineering scale with a preset corresponding rock mass test scale matching evaluation threshold value, if the corresponding rock mass test scale matching evaluation value of the rock mass simulation engineering scale is higher than the preset corresponding rock mass test scale matching evaluation threshold value, marking the corresponding rock mass test scale matching evaluation result of the rock mass simulation engineering scale as energy path matching qualified, otherwise marking the corresponding rock mass test scale matching evaluation result of the rock mass simulation engineering scale as energy path matching unqualified.
7. The method for optimizing mechanical parameters of a large-scale rock mass based on multi-scale test data according to claim 6, wherein the method for processing energy path matching information of a rock mass simulation engineering scale is as follows: And extracting each rock mass test scale matching evaluation result of the rock mass simulation engineering scale and the corresponding abnormal path type, if the rock mass test scale matching evaluation result of the rock mass simulation engineering scale corresponding to two or more abnormal path types is energy path matching qualified, marking the energy path matching information of the rock mass simulation engineering scale as cross-scale matching abnormality, otherwise, not marking.
8. The method for optimizing mechanical parameters of a large-scale rock mass based on multi-scale test data according to claim 7, wherein the method for performing path correction constraint on the mechanical parameter optimizing process of the rock mass simulation engineering scale is as follows: And extracting energy path matching information of the rock mass simulation engineering scale, if the energy path matching information of the rock mass simulation engineering scale is abnormal in trans-scale matching, sequencing corresponding rock mass test scale matching evaluation values according to a sequence from high to low, marking an abnormal path type corresponding to the highest rock mass test scale matching evaluation value as a dominant energy path type of the rock mass simulation engineering scale, and further carrying out path correction constraint on a mechanical parameter optimization process of the rock mass simulation engineering scale.
9. The method for optimizing mechanical parameters of a large-scale rock mass based on multi-scale test data according to claim 1, wherein the method for analyzing path deviation in the path correction constraint process is as follows: Carrying out path deviation analysis on the path correction constraint process to obtain path deviation characteristic data of a rock mass simulation engineering scale, wherein the path deviation characteristic data of the rock mass simulation engineering scale comprises a stress data deviation coefficient, a displacement data deviation coefficient, an internal pore pressure data deviation coefficient and an energy data deviation coefficient of the rock mass simulation engineering scale; Comprehensively analyzing the path deviation characteristic data of the rock mass simulation engineering scale to obtain a path deviation characteristic value of the rock mass simulation engineering scale, wherein the path deviation characteristic value of the rock mass simulation engineering scale is used for representing a quantification result of the severity degree of the matching deviation among different energy paths in the parameter optimization process.
10. The method for optimizing large-scale rock mechanical parameters based on multi-scale test data according to claim 9, wherein the method for updating and optimizing the associated rock mechanical parameters according to the path deviation characteristic values of the rock simulation engineering scale is as follows: Comparing the path deviation characteristic value of the rock mass simulation engineering scale with a preset path deviation characteristic threshold value, marking the path deviation result of the rock mass simulation engineering scale as path abnormality if the path deviation characteristic value of the rock mass simulation engineering scale is higher than the preset path deviation characteristic threshold value, otherwise marking the path deviation result of the rock mass simulation engineering scale as path abnormality, and updating and optimizing relevant rock mass mechanical parameters if the path deviation result of the rock mass simulation engineering scale is path abnormality.

Description

Large-scale rock mass mechanical parameter optimization method based on multi-scale test data Technical Field The invention relates to the technical field of parameter optimization, in particular to a large-scale rock mechanical parameter optimization method based on multi-scale test data. Background In the deep underground engineering construction and propulsion process, the mechanical parameters of the large-scale rock mass are basic inputs for carrying out surrounding rock stability analysis, supporting structure design and construction scheme optimization, the rationality is directly related to engineering safety and long-term service performance, as the engineering scale rock mass is difficult to directly acquire real mechanical parameters through an integral loading test, the engineering practice generally depends on multi-scale rock mass test data, and indoor small-scale tests, on-site mesoscale tests and engineering scale numerical simulation results are comprehensively utilized through parameter back-pushing and optimizing methods. However, in the advanced process of deep engineering, along with the continuous evolution of excavation disturbance, the structural surface of a rock mass is gradually exposed, the stress field and the seepage field are obviously changed, the stress state of the rock mass can be subjected to quick rearrangement in a short time, a deformation mechanism led by continuous media is converted to a destruction mechanism led by sliding of the structural surface and opening of cracks, under the specific scene, the conventional multi-scale parameter optimization algorithm mainly depends on the fitting effect of a macroscopic response curve to update parameters, and identification and constraint on the differences of energy dissipation paths and physical mechanisms implied by different scale tests are lacking, so that the energy contribution relation of different scale data in the parameter optimization process cannot be kept consistent. The fracture energy and damage evolution characteristics reflected in the small-scale test are abnormally amplified in the parameter push-back process, so that the constraint effect on the optimization result is dominant in a short time, the constraint capability of large-scale simulation on the overall deformation and stability is obviously weakened, and finally, the rock mechanical parameters obtained through inversion are abnormal. The surrounding rock stability assessment and support design developed based on the parameters deviate from the actual mechanical behavior, so that the potential instability risk is difficult to accurately identify, structural failure is possibly induced in the construction and operation stages, and great potential safety hazards are brought. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a large-scale rock mechanical parameter optimization method based on multi-scale test data, which can effectively solve the problems related to the background art. The method comprises the steps of collecting test process data of multiple rock mass test scales, carrying out energy evolution analysis on the test process data to obtain energy path characteristic data of each rock mass test scale, and carrying out anomaly association analysis on the energy path characteristic data of each rock mass test scale to obtain a multi-scale anomaly path database. And collecting energy path characteristic data of the rock mass simulation engineering scale, and carrying out multi-characteristic association analysis on the energy path characteristic data of the rock mass simulation engineering scale by combining a multi-scale abnormal path database to obtain each rock mass test scale matching evaluation value of the rock mass simulation engineering scale. Performing deviation discriminant analysis on each rock mass test scale matching evaluation value of the rock mass simulation engineering scale to obtain each rock mass test scale matching evaluation result of the rock mass simulation engineering scale, and processing to obtain energy path matching information of the rock mass simulation engineering scale based on each rock mass test scale matching evaluation result of the rock mass simulation engineering scale so as to perform path correction constraint on a mechanical parameter optimization process of the rock mass simulation engineering scale. And carrying out path deviation analysis on the path correction constraint process to obtain a path deviation characteristic value of the rock mass simulation engineering scale, and updating and optimizing configuration on the mechanical parameters of the associated rock mass according to the path deviation characteristic value of the rock mass simulation engineering scale. Further, the method for analyzing the energy evolution of the test process data comprises the step that the test process data of the multi-rock test scale comprise mechanical response data, dis