CN109085321B - Calibration method of rock mesomechanics parameters and terminal equipment - Google Patents

Calibration method of rock mesomechanics parameters and terminal equipment Download PDF

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CN109085321B
CN109085321B CN201810828299.8A CN201810828299A CN109085321B CN 109085321 B CN109085321 B CN 109085321B CN 201810828299 A CN201810828299 A CN 201810828299A CN 109085321 B CN109085321 B CN 109085321B
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袁维
王伟
许成帮
孙浩洋
戴维森
闻磊
常江芳
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Shijiazhuang Tiedao University
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Abstract

本发明适用于岩石标定技术领域，提供了一种岩石细观力学参数的标定方法及终端设备。所述方法包括：确定目标岩石的宏观力学参数和颗粒粒径，根据预存的细观力学参数确定正交试验方案，根据正交试验方案和颗粒粒径确定细观力学参数数值式样模型，根据细观力学参数数值式样模型确定正交试验方案对应的试验宏观力学参数，根据试验宏观力学参数和正交试验方案中的细观力学参数建立宏观力学参数与细观力学参数的表征关系，再确定目标岩石的宏观力学参数对应的最优细观力学参数，并根据最优细观力学参数对所述目标岩石进行标定。采用上述方案后，极大的降低了标定过程的计算量，构建的工程模型精度高，为实际工程的构建提供了准确的理论依据。

Figure 201810828299

The invention is applicable to the technical field of rock calibration, and provides a calibration method and terminal equipment for rock meso-mechanical parameters. The method includes: determining the macro-mechanical parameters and particle size of the target rock, determining an orthogonal test scheme according to the pre-existing meso-mechanical parameters, determining a numerical model of the meso-mechanical parameters according to the orthogonal test scheme and the particle size, and The macroscopic mechanical parameters of the test corresponding to the orthogonal test plan are determined by the numerical model of the macroscopic mechanical parameters, and the characterization relationship between the macroscopic mechanical parameters and the microscopic mechanical parameters is established according to the experimental macroscopic mechanical parameters and the microscopic mechanical parameters in the orthogonal test plan, and then the target is determined. The optimal micro-mechanical parameters corresponding to the macro-mechanical parameters of the rock, and the target rock is calibrated according to the optimal micro-mechanical parameters. After the above scheme is adopted, the calculation amount of the calibration process is greatly reduced, and the constructed engineering model has high precision, which provides an accurate theoretical basis for the construction of practical projects.

Figure 201810828299

Description

Calibration method of rock mesomechanics parameters and terminal equipment
Technical Field
The invention belongs to the technical field of rock calibration, and particularly relates to a calibration method of rock mesomechanics parameters and terminal equipment.
Background
During actual engineering construction, an actual engineering model needs to be constructed firstly to provide construction basis for construction workers, the particle discrete element method is widely applied to rock mechanics and construction of the actual engineering model, the core idea is to regard rocks as particle aggregates consisting of round particles, stress deformation, damage and motion states of the rocks are simulated on a microscopic level, and the precision of particle flow simulation mainly depends on the determination of microscopic parameters.
However, the physical meaning of the mesoscopic mechanical parameters is unclear, and the mesoscopic parameters cannot be determined through direct indoor tests or field tests, so that the macroscopic mechanical parameter values of the rock patterns can only be determined through the indoor tests, then the corresponding mesoscopic mechanical parameters are inverted based on the macroscopic mechanical parameters of the rock patterns, the process is called as the calibration of the mesoscopic parameters, the calibration of the mesoscopic parameters usually adopts a conventional trial and error method, namely, the mesoscopic parameter values are continuously changed until the simulation values are basically consistent with the test values of the rock patterns, the contingency is higher, the theoretical deficiency is large, the calculated amount is large, the constructed engineering model is low in precision, and the construction of actual engineering is influenced.
Disclosure of Invention
In view of this, the embodiment of the invention provides a calibration method for rock mesomechanics parameters and a terminal device, so as to solve the problems that in the prior art, the calibration calculation amount of the mesomechanics parameters is large, so that the accuracy of a constructed engineering model is low, and the actual engineering construction is affected.
The first aspect of the embodiments of the present invention provides a method for calibrating a rock mesomechanics parameter, including:
determining macroscopic mechanical parameters and particle sizes of target rocks;
determining an orthogonal test scheme according to prestored mesoscopic mechanical parameters;
determining a mesomechanics parameter numerical pattern model based on said orthogonal test protocol and said particle size;
determining test macroscopic mechanical parameters corresponding to the orthogonal test scheme according to the microscopic mechanical parameter numerical style model;
establishing a characterization relation between macroscopic mechanical parameters and microscopic mechanical parameters according to the macroscopic mechanical parameters and the microscopic mechanical parameters in the orthogonal test scheme, determining the optimal microscopic mechanical parameters corresponding to the macroscopic mechanical parameters of the target rock by using an optimization algorithm, and calibrating the target rock according to the optimal microscopic mechanical parameters.
As a further technical solution, the determining the macroscopic mechanical parameters of the target rock includes:
obtaining uniaxial compressive strength of macroscopic mechanical parameters of the target rock according to a prestored uniaxial compression test
Figure BDA0001742989080000021
And modulus of elasticity Et；
Obtaining the tensile strength of the macroscopic mechanical parameters of the target rock according to the prestored Brazilian split test
Figure BDA0001742989080000022
Acquiring the cohesive force c of macroscopic mechanical parameters of the target rock according to a prestored conventional triaxial compression testtAnd internal coefficient of friction tan phit。
As a further technical solution, the method further comprises: according to the expression
Figure BDA0001742989080000023
Determining the particle size d of the target rock, wherein Num represents the number of particles of the target rock, and X, Y represents the length and width of the maximum horizontal section of the target rock, respectively.
As a further technical solution, the determining an orthogonal test scheme according to the pre-stored mesoscopic mechanical parameters includes:
determining mesoscopic mechanical parameters pbm _ emod, pbm _ fric, pbm _ bemod, pbm _ ten _ m, pbm _ coh _ m and pbm _ fa from a pre-stored parallel bond model, wherein pbm _ emod represents the effective modulus and pbm _ fric represents the coefficient of friction; pbm _ bemod represents contact effective modulus, pbm _ ten _ m represents contact average tensile strength, pbm _ coh _ m represents contact average adhesive force, and pbm _ fa represents contact friction angle;
determining an orthogonal experimental scheme according to the pbm _ emod, the pbm _ fric, the pbm _ bemod, the pbm _ ten _ m, the pbm _ coh _ m, and the pbm _ fa.
As a further technical scheme, the establishing a characterization relationship between macroscopic mechanical parameters and microscopic mechanical parameters according to the macroscopic mechanical parameters of the test and the microscopic mechanical parameters in the orthogonal test scheme, determining the optimal microscopic mechanical parameters corresponding to the macroscopic mechanical parameters of the target rock by using an optimization algorithm, and calibrating the target rock according to the optimal microscopic mechanical parameters includes:
determining expressions of the combination of the macroscopic mechanical parameters and the different microscopic mechanical parameters in the orthogonal test scheme according to a prestored multivariate linear fitting analysis method:
Figure BDA0001742989080000031
wherein, aijDenotes the undetermined constant, i is 1-5, j is 0-6, σcDenotes uniaxial compressive strength of numerical value, E denotes elastic modulus of numerical value, σtThe tensile strength of the numerical value pattern, c the adhesion force of the numerical value pattern,
Figure BDA0001742989080000032
a rubbing angle representing a numerical pattern;
determining an optimization objective function according to the macroscopic mechanical parameters and the test macroscopic mechanical parameters:
Figure BDA0001742989080000033
wherein δ represents an optimization objective function;
determining optimal mesoscopic mechanical parameters according to a pre-stored nonlinear programming algorithm;
and calibrating the target rock according to the optimal mesomechanics parameters.
A second aspect of an embodiment of the present invention provides a device for calibrating a rock mesomechanics parameter, including:
the macroscopic mechanical parameter determining module is used for determining the macroscopic mechanical parameters and the particle size of the target rock;
the orthogonal test scheme determining module is used for determining an orthogonal test scheme according to the pre-stored mesomechanics parameters;
a numerical pattern model determination module for determining a mesomechanics parameter numerical pattern model based on the orthogonal test protocol and the particle size;
the test macro mechanical parameter determining module is used for determining the test macro mechanical parameters corresponding to the orthogonal test scheme according to the micro mechanical parameter numerical style model;
and the target rock calibration module is used for establishing a characterization relation between the macroscopic mechanical parameters and the mesoscopic mechanical parameters according to the macroscopic mechanical parameters and the mesoscopic mechanical parameters in the orthogonal test scheme, determining the optimal mesoscopic mechanical parameters corresponding to the macroscopic mechanical parameters of the target rock by using an optimization algorithm, and calibrating the target rock according to the optimal mesoscopic mechanical parameters.
As a further technical solution, the macro-mechanical parameter determining module further includes:
a uniaxial compressive strength determination module for obtaining the uniaxial compressive strength of the macroscopic mechanical parameters of the target rock according to the prestored uniaxial compression test
Figure BDA0001742989080000041
And modulus of elasticity Et；
The tensile strength determining module is used for acquiring the tensile strength of the macroscopic mechanical parameters of the target rock according to the prestored Brazilian split test
Figure BDA0001742989080000042
The cohesive force determining module is used for acquiring the cohesive force c of macroscopic mechanical parameters of the target rock according to the prestored conventional triaxial compression testtAnd internal coefficient of friction tan phit。
As a further technical solution, the apparatus further includes:
a particle size determination module for determining the particle size of the particles based onExpression formula
Figure BDA0001742989080000043
Determining the particle size d of the target rock, wherein Num represents the number of particles of the target rock, and X, Y represents the length and width of the maximum horizontal section of the target rock, respectively.
A third aspect of the embodiments of the present invention provides a calibration terminal device for rock mesomechanics parameters, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the method according to the first aspect when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method according to the first aspect.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: after the scheme is adopted, firstly, determining macroscopic mechanical parameters and particle sizes of target rocks, then, determining orthogonal test schemes of the microscopic mechanical parameters, generating different orthogonal test schemes according to microscopic mechanical parameter values and particle sizes of different schemes, then, obtaining test macroscopic mechanical parameters of test patterns under different orthogonal test schemes, finally, determining optimal microscopic mechanical parameters according to the macroscopic mechanical parameters, the test macroscopic mechanical parameters and the orthogonal test schemes, and calibrating the target rocks according to the optimal microscopic mechanical parameters to ensure that corresponding macroscopic mechanical parameter calculation values are as close to the test macroscopic mechanical parameter values of the target rocks as possible, thereby ensuring that the calibration of the microscopic parameters has a solid theoretical basis, rapidly and accurately determining the microscopic parameters required by particle flow simulation, greatly reducing the calculation amount of a calibration process and ensuring high precision of a constructed engineering model, provides an accurate theoretical basis for the construction of practical engineering.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a flow chart illustrating steps of a method for calibrating mesomechanics parameters of a rock according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating steps of a method for calibrating mesomechanic parameters of a rock according to another embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a device for calibrating mesomechanics parameters of a rock provided by an embodiment of the present invention;
fig. 4 is a schematic diagram of a terminal device for calibrating a rock mesomechanics parameter according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
As shown in fig. 1, a flowchart of steps of a method for calibrating a rock mesomechanics parameter provided in an embodiment of the present invention includes:
and step S101, determining macroscopic mechanical parameters and particle sizes of the target rock.
And S102, determining an orthogonal test scheme according to the pre-stored mesoscopic mechanical parameters.
Specifically, mesoscopic parameters in a Parallel bonding model (Parallel-bonded model) are selected as influence factors, each influence factor takes n horizontal values, an orthogonal test scheme is determined according to the mesoscopic parameters and the n horizontal values, preferably, 6 mesoscopic parameters are selected as the influence factors, each influence factor takes 5 horizontal values, and 25 groups of orthogonal test schemes are determined.
Step S103, determining a mesoscopic parameter numerical pattern model according to the orthogonal test scheme and the particle size.
Specifically, a mesomechanics parameter numerical pattern model is generated according to the mesoscopic parameters and the particle sizes in the orthogonal test scheme, preferably, 25 groups of mesomechanics parameter numerical pattern models are generated, the number of particles in the uniaxial and conventional triaxial compression tests is not less than 2000, the length-width ratio is 2.0, and the diameter of the Brazilian cleavage test disc is equal to the width of the uniaxial compression test pattern.
And step S104, determining the macroscopic mechanical parameters of the test corresponding to the orthogonal test scheme according to the microscopic mechanical parameter numerical style model.
Preferably, the numerical test is carried out on the mesoscopic mechanical parameter numerical model, the numerical test comprises uniaxial compression, triaxial compression and Brazilian splitting, and the corresponding macroscopic mechanical parameters under different mesoscopic parameter combination conditions are obtained.
And S105, establishing a characterization relation between the macroscopic mechanical parameters and the mesoscopic mechanical parameters according to the macroscopic mechanical parameters and the mesoscopic mechanical parameters in the orthogonal test scheme, determining the optimal mesoscopic mechanical parameters corresponding to the macroscopic mechanical parameters of the target rock by using an optimization algorithm, and calibrating the target rock according to the optimal mesoscopic mechanical parameters.
Specifically, in the value range of the mesoscopic parameters, the optimal mesoscopic mechanical parameter combination is solved through a nonlinear programming algorithm, so that the optimal objective function takes the minimum value, namely the optimal mesoscopic mechanical parameters, and the target rock is calibrated according to the determined optimal mesoscopic mechanical parameters.
After the scheme is adopted, firstly, determining macroscopic mechanical parameters and particle sizes of target rocks, then, determining orthogonal test schemes of the microscopic mechanical parameters, generating different orthogonal test schemes according to microscopic mechanical parameter values and particle sizes of different schemes, then, obtaining test macroscopic mechanical parameters of test patterns under different orthogonal test schemes, finally, determining optimal microscopic mechanical parameters according to the macroscopic mechanical parameters, the test macroscopic mechanical parameters and the orthogonal test schemes, and calibrating the target rocks according to the optimal microscopic mechanical parameters to ensure that corresponding macroscopic mechanical parameter calculation values are as close to the test macroscopic mechanical parameter values of the target rocks as possible, thereby ensuring that the calibration of the microscopic parameters has a solid theoretical basis, rapidly and accurately determining the microscopic parameters required by particle flow simulation, greatly reducing the calculation amount of a calibration process and ensuring high precision of a constructed engineering model, provides an accurate theoretical basis for the construction of practical engineering.
Furthermore, as shown in fig. 2, in a specific example, the determining the macro-mechanical parameters of the target rock includes:
step S201, obtaining uniaxial compressive strength of macroscopic mechanical parameters of the target rock according to a prestored uniaxial compression test
Figure BDA0001742989080000072
And modulus of elasticity Et。
Step S202, obtaining the tensile strength of the macroscopic mechanical parameters of the target rock according to the prestored Brazilian split test
Figure BDA0001742989080000073
Step S203, acquiring the cohesion c of the macroscopic mechanical parameters of the target rock according to the prestored conventional triaxial compression testtAnd internal coefficient of friction tan phit。
Specifically, the uniaxial compression test, the brazilian split test and the conventional triaxial compression test are all existing test methods, and before the test, the test methods are stored in corresponding servers, and the servers can be directly called.
In addition, in a specific case, the method also comprises the step of expressing
Figure BDA0001742989080000071
Determining the particle size d of the target rock, wherein Num represents the number of particles of the target rock, and X, Y represents the length and width of the maximum horizontal section of the target rock, respectively.
Specifically, when measuring the target rock, it is necessary to first determine the horizontal maximum cross section and the vertical maximum cross section of the target rock, compare the areas of the horizontal maximum cross section and the vertical maximum cross section, take the cross section with a larger area as the maximum horizontal section, and place the target rock in a state where the maximum horizontal section is placed parallel to the horizontal plane. Preferably, the particle size d is taken to be a range of values, the range of particle sizes being taken as a 0.1 cm fluctuation up and down.
In addition, in a specific example, the determining the orthogonal test scheme according to the pre-stored mesoscopic mechanical parameters includes:
determining mesoscopic mechanical parameters pbm _ emod, pbm _ fric, pbm _ bemod, pbm _ ten _ m, pbm _ coh _ m and pbm _ fa from a pre-stored parallel bond model, wherein pbm _ emod represents the effective modulus and pbm _ fric represents the coefficient of friction; pbm _ bemod represents the contact effective modulus, pbm _ ten _ m represents the contact average tensile strength, pbm _ coh _ m represents the contact average adhesive force, and pbm _ fa represents the contact friction angle.
Determining an orthogonal experimental scheme according to the pbm _ emod, the pbm _ fric, the pbm _ bemod, the pbm _ ten _ m, the pbm _ coh _ m, and the pbm _ fa.
In addition, in a specific example, the determining an optimal mesoscopic mechanical parameter according to the macroscopic mechanical parameter, the experimental macroscopic mechanical parameter and the orthogonal test scheme, and calibrating the target rock according to the optimal mesoscopic mechanical parameter includes:
determining expressions of the combination of the macroscopic mechanical parameters and the different microscopic mechanical parameters in the orthogonal test scheme according to a prestored multivariate linear fitting analysis method:
Figure BDA0001742989080000081
wherein, aijDenotes the undetermined constant, i is 1-5, j is 0-6, σcDenotes uniaxial compressive strength of numerical value, E denotes elastic modulus of numerical value, σtTensile strength of numerical value patternStrength, c represents a numerical value of the adhesive force,
Figure BDA0001742989080000082
the friction angle is shown in numerical form.
And determining an optimization objective function according to the macroscopic mechanical parameters and the test macroscopic mechanical parameters.
Figure BDA0001742989080000091
Where δ represents the optimization objective function.
And determining the optimal mesoscopic mechanical parameters according to a pre-stored nonlinear programming algorithm.
And calibrating the target rock according to the optimal mesomechanics parameters.
In addition, in a specific example, the crack propagation law of a target rock of 6m × 6m under the action of explosive load is simulated, and the macroscopic mechanical parameters of the rock are obtained by performing an indoor uniaxial compression test and a Brazilian splitting test on a rock block as follows: compressive strength of single axis
Figure BDA0001742989080000092
Uniaxial tensile strength
Figure BDA0001742989080000093
Mpa, modulus of elasticity EtAnd (3) calibrating the mesomechanics parameters based on the three macroscopic mechanics parameters, namely 19.9 GPa.
The bench top station ideally simulates a particle count of about 4 x 106Each having an average particle diameter of about d
Figure BDA0001742989080000094
Preferably, the particle size of the particles ranges from 0.2 cm to 0.4cm, and the particles are uniformly distributed;
the values of the 6 mesoscopic mechanical parameters are respectively as follows:
pbm_emod：5.0GPa、1.0GPa、1.5GPa、2.0GPa、2.5GPa；
pbm_fric：0.2、0.4、0.6、0.8、1.0；
pbm_bemod：7.0GPa、12.0GPa、17.0GPa、22.0GPa、27.0GPa；
pbm_ten_m：0.8MPa、1.6MPa、2.4MPa、3.2MPa、4.0MPa；
pbm_coh_m：30MPa、60MPa、90MPa、120MPa、150MPa；
pbm_fa：20°、30°、40°、50°、60°。
the orthogonal test protocol is as follows:
Figure BDA0001742989080000095
Figure BDA0001742989080000101
establishing 25 groups of numerical test patterns according to an orthogonal test scheme, obtaining macroscopic mechanical parameters of the 25 groups of test patterns through a numerical loading destructive test, and establishing 25 groups of microscopic mechanical parameter numerical pattern models as shown in the following table:
Figure BDA0001742989080000111
Figure BDA0001742989080000121
establishing a function expression of the three macroscopic mechanical parameters about 6 microscopic parameters by adopting a multivariate linear fitting analysis method, namely:
Figure BDA0001742989080000122
obtaining the optimal combination of the microscopic parameters when the objective function takes the minimum value by a nonlinear programming method, namely: pbm _ emod 6.01GPa, pbm _ fric 0.28, pbm _ bemod 9.0GPa, pbm _ ten _ m 0.968MPa, pbm _ coh _ m 30.0MPa, pbm _ fa 60 °; based on the microscopic viewNumerical value test patterns are established, and numerical value loading failure tests are carried out to obtain the following macroscopic parameters: uniaxial compressive strength sigmac21.3MPa uniaxial tensile strength σt1.93MPa, and 24.2GPa of elastic modulus E, which is close to the macroscopic mechanical parameters of the target, and calibrating the target rock according to the optimal microscopic mechanical parameters.
As shown in fig. 3, a schematic structural diagram of a device for calibrating a rock mesomechanics parameter provided in an embodiment of the present invention includes:
and the macroscopic mechanical parameter determining module 301 is used for determining the macroscopic mechanical parameters and the particle size of the target rock.
An orthogonal test scheme determining module 302, configured to determine an orthogonal test scheme according to a pre-stored mesoscopic mechanical parameter.
A numerical pattern model determining module 303 for determining a mesomechanics parameter numerical pattern model based on said orthogonal test protocol and said particle size.
And a test macro mechanical parameter determining module 304, configured to determine a test macro mechanical parameter corresponding to the orthogonal test scheme according to the micro mechanical parameter numerical pattern model.
The target rock calibration module 305 is configured to establish a characterization relationship between macro mechanical parameters and micro mechanical parameters according to the macro mechanical parameters and the micro mechanical parameters in the orthogonal test scheme, determine optimal micro mechanical parameters corresponding to the macro mechanical parameters of the target rock by using an optimization algorithm, and calibrate the target rock according to the optimal micro mechanical parameters.
In addition, in a specific example, the macro-mechanical parameter determining module further includes:
a uniaxial compressive strength determination module for obtaining the uniaxial compressive strength of the macroscopic mechanical parameters of the target rock according to the prestored uniaxial compression test
Figure BDA0001742989080000131
And modulus of elasticity Et。
A tensile strength determination module for performing Brazilian split test according to the pre-stored testObtaining tensile strength of macroscopic mechanical parameters of target rock
Figure BDA0001742989080000132
The cohesive force determining module is used for acquiring the cohesive force c of macroscopic mechanical parameters of the target rock according to the prestored conventional triaxial compression testtAnd internal coefficient of friction tan phit。
After the scheme is adopted, firstly, determining macroscopic mechanical parameters and particle sizes of target rocks, then, determining orthogonal test schemes of the microscopic mechanical parameters, generating different orthogonal test schemes according to microscopic mechanical parameter values and particle sizes of different schemes, then, obtaining test macroscopic mechanical parameters of test patterns under different orthogonal test schemes, finally, determining optimal microscopic mechanical parameters according to the macroscopic mechanical parameters, the test macroscopic mechanical parameters and the orthogonal test schemes, and calibrating the target rocks according to the optimal microscopic mechanical parameters to ensure that corresponding macroscopic mechanical parameter calculation values are as close to the test macroscopic mechanical parameter values of the target rocks as possible, thereby ensuring that the calibration of the microscopic parameters has a solid theoretical basis, rapidly and accurately determining the microscopic parameters required by particle flow simulation, greatly reducing the calculation amount of a calibration process and ensuring high precision of a constructed engineering model, provides an accurate theoretical basis for the construction of practical engineering.
In addition, in a specific example, the method further comprises the following steps:
a particle size determination module for determining the particle size according to the expression
Figure BDA0001742989080000133
Determining the particle size d of the target rock, wherein Num represents the number of particles of the target rock, and X, Y represents the length and width of the maximum horizontal section of the target rock, respectively.
Further, in one specific example, the orthogonal test protocol determination module includes:
a mesomechanics parameter determination module for determining mesomechanics parameters pbm _ emod, pbm _ fric, pbm _ bemod, pbm _ ten _ m, pbm _ coh _ m, and pbm _ fa from a pre-stored parallel bond model, wherein pbm _ emod represents the effective modulus and pbm _ fric represents the coefficient of friction; pbm _ bemod represents the contact effective modulus, pbm _ ten _ m represents the contact average tensile strength, pbm _ coh _ m represents the contact average adhesive force, and pbm _ fa represents the contact friction angle.
An orthogonal trial scheme determination sub-module for determining an orthogonal trial scheme based on the pbm _ emod, the pbm _ fric, the pbm _ bemod, the pbm _ ten _ m, the pbm _ coh _ m, and the pbm _ fa.
Further, in one particular example, the target rock calibration module includes:
the expression determination module is used for determining the expressions of the combination of the macroscopic mechanical parameters and the different microscopic mechanical parameters in the orthogonal test scheme according to a prestored multivariate linear fitting analysis method:
Figure BDA0001742989080000141
wherein, aijDenotes the undetermined constant, i is 1-5, j is 0-6, σcDenotes uniaxial compressive strength of numerical value, E denotes elastic modulus of numerical value, σtThe tensile strength of the numerical value pattern, c the adhesion force of the numerical value pattern,
Figure BDA0001742989080000142
the friction angle is shown in numerical form.
An optimization objective function determination module, configured to determine an optimization objective function according to the macro-mechanical parameters and the test macro-mechanical parameters:
Figure BDA0001742989080000143
where δ represents the optimization objective function.
And the optimal mesoscopic mechanical parameter determining module is used for determining the optimal mesoscopic mechanical parameters according to a pre-stored nonlinear programming algorithm.
And the target rock calibration submodule is used for calibrating the target rock according to the optimal mesomechanics parameter.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 4 is a schematic diagram of a calibration terminal device for rock mesomechanics parameters provided in an embodiment of the present invention, where the calibration terminal device 4 for rock mesomechanics parameters includes: a processor 40, a memory 41 and a computer program 42 stored in said memory 41 and executable on said processor 40, such as a calibration program of rock micro-mechanical parameters. The processor 40, when executing the computer program 42, implements the steps in the above-described embodiments of the method for calibration of rock mesomechanics parameters, such as the steps 101 to 105 shown in fig. 1. Alternatively, the processor 40, when executing the computer program 42, implements the functions of each module/unit in the above-mentioned device embodiments, for example, the functions of the modules 301 to 305 shown in fig. 3.
Illustratively, the computer program 42 may be partitioned into one or more modules/units that are stored in the memory 41 and executed by the processor 40 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 42 in the calibration terminal device 4 for the rock micro-mechanical parameters. For example, the computer program 42 may be divided into a synchronization module, a summary module, an acquisition module, and a return module (a module in a virtual device), and each module has the following specific functions:
determining the macroscopic mechanical parameters and the particle size of the target rock.
And determining an orthogonal test scheme according to the prestored mesoscopic mechanical parameters.
And determining a mesomechanics parameter numerical pattern model according to the orthogonal test scheme and the particle size.
And determining the macroscopic mechanical parameters of the test corresponding to the orthogonal test scheme according to the microscopic mechanical parameter numerical style model.
Establishing a characterization relation between macroscopic mechanical parameters and microscopic mechanical parameters according to the macroscopic mechanical parameters and the microscopic mechanical parameters in the orthogonal test scheme, determining the optimal microscopic mechanical parameters corresponding to the macroscopic mechanical parameters of the target rock by using an optimization algorithm, and calibrating the target rock according to the optimal microscopic mechanical parameters.
The determining macro mechanical parameters of the target rock comprises:
obtaining uniaxial compressive strength of macroscopic mechanical parameters of the target rock according to a prestored uniaxial compression test
Figure BDA0001742989080000151
And modulus of elasticity Et。
Obtaining the tensile strength of the macroscopic mechanical parameters of the target rock according to the prestored Brazilian split test
Figure BDA0001742989080000161
Acquiring the cohesive force c of macroscopic mechanical parameters of the target rock according to a prestored conventional triaxial compression testtAnd internal coefficient of friction tan phit。
According to the expression
Figure BDA0001742989080000162
Determining the particle size d of the target rock, wherein Num represents the number of particles of the target rock, and X, Y represents the length and width of the maximum horizontal section of the target rock, respectively.
The method for determining the orthogonal test scheme according to the pre-stored mesoscopic mechanical parameters comprises the following steps:
mesoscopic parameters pbm _ emod, pbm _ fric, pbm _ bemod, pbm _ ten _ m, pbm _ coh _ m and pbm _ fa were determined from pre-stored parallel bond models, wherein pbm _ emod represents the effective modulus and pbm _ fric represents the coefficient of friction. pbm _ bemod represents the contact effective modulus, pbm _ ten _ m represents the contact average tensile strength, pbm _ coh _ m represents the contact average adhesive force, and pbm _ fa represents the contact friction angle.
Determining an orthogonal experimental scheme according to the pbm _ emod, the pbm _ fric, the pbm _ bemod, the pbm _ ten _ m, the pbm _ coh _ m, and the pbm _ fa.
The determining an optimal mesoscopic mechanical parameter according to the macroscopic mechanical parameter, the experimental macroscopic mechanical parameter and the orthogonal test scheme, and the calibrating the target rock according to the optimal mesoscopic mechanical parameter comprises:
determining expressions of the combination of the macroscopic mechanical parameters and the different microscopic mechanical parameters in the orthogonal test scheme according to a prestored multivariate linear fitting analysis method:
Figure BDA0001742989080000163
wherein, aijDenotes the undetermined constant, i is 1-5, j is 0-6, σcDenotes uniaxial compressive strength of numerical value, E denotes elastic modulus of numerical value, σtThe tensile strength of the numerical value pattern, c the adhesion force of the numerical value pattern,
Figure BDA0001742989080000171
the friction angle is shown in numerical form.
Determining an optimization objective function according to the macroscopic mechanical parameters and the test macroscopic mechanical parameters:
Figure BDA0001742989080000172
where δ represents the optimization objective function.
And determining the optimal mesoscopic mechanical parameters according to a pre-stored nonlinear programming algorithm.
And calibrating the target rock according to the optimal mesomechanics parameters.
The calibration terminal device 4 for the rock mesomechanics parameters may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The calibration terminal device of the rock mesomechanics parameter can include, but is not limited to, a processor 40 and a memory 41. It will be understood by those skilled in the art that fig. 4 is merely an example of the calibration terminal device 4 for the rock mesomechanics parameter, and does not constitute a limitation of the calibration terminal device 4 for the rock mesomechanics parameter, and may include more or less components than those shown, or some components in combination, or different components, for example, the calibration terminal device for the rock mesomechanics parameter may further include an input-output device, a network access device, a bus, etc.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the calibration terminal device 4 for the rock mesomechanics parameters, such as a hard disk or a memory of the calibration terminal device 4 for the rock mesomechanics parameters. The memory 41 may also be an external storage device of the rock microscopic mechanical parameter calibration terminal device 4, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, which is equipped on the rock microscopic mechanical parameter calibration terminal device 4. Further, the memory 41 may also include both an internal memory unit and an external memory device of the calibration terminal device 4 for the rock mesomechanics parameters. The memory 41 is used for storing the computer program and other programs and data required for the calibration of the end devices of the rock mesomechanics parameters. The memory 41 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same. Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: modifications of the technical solutions described in the embodiments or equivalent replacements of some technical features may still be made. Such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims (6)

1.一种岩石细观力学参数的标定方法，其特征在于，包括：1. a calibration method of rock meso-mechanical parameters, is characterized in that, comprises: 确定目标岩石的宏观力学参数和颗粒粒径；Determine the macro-mechanical parameters and particle size of the target rock; 根据预存的细观力学参数确定正交试验方案，具体包括：根据预存的平行粘结模型确定细观力学参数pbm_emod、pbm_fric、pbm_bemod、pbm_ten_m、pbm_coh_m和pbm_fa，其中，pbm_emod表示有效模量，pbm_fric表示摩擦系数；pbm_bemod表示接触有效模量，pbm_ten_m表示接触平均抗拉强度，pbm_coh_m表示接触平均黏结力，pbm_fa表示接触摩擦角；根据所述pbm_emod、所述pbm_fric、所述pbm_bemod、所述pbm_ten_m、所述pbm_coh_m和所述pbm_fa确定正交试验方案；Determine the orthogonal test plan according to the pre-stored meso-mechanical parameters, including: determining the meso-mechanical parameters pbm_emod, pbm_fric, pbm_bemod, pbm_ten_m, pbm_coh_m and pbm_fa according to the pre-stored parallel bonding model, where pbm_emod represents the effective modulus and pbm_fric represents the effective modulus Friction coefficient; pbm_bemod represents the contact effective modulus, pbm_ten_m represents the contact average tensile strength, pbm_coh_m represents the contact average bond force, pbm_fa represents the contact friction angle; according to the pbm_emod, the pbm_fric, the pbm_bemod, the pbm_ten_m, the pbm_coh_m and the pbm_fa determine the orthogonal test plan; 根据所述正交试验方案和所述颗粒粒径确定细观力学参数数值式样模型；Determine the numerical model of the meso-mechanical parameters according to the orthogonal test scheme and the particle size; 根据所述细观力学参数数值式样模型确定所述正交试验方案对应的试验宏观力学参数；Determine the test macro-mechanical parameters corresponding to the orthogonal test plan according to the meso-mechanical parameter numerical model; 根据预存的多元线性拟合分析方法，确定所述试验宏观力学参数和所述正交试验方案中不同细观力学参数组合的表达式：According to the pre-stored multivariate linear fitting analysis method, the expressions of the macro-mechanical parameters of the experiment and the combinations of different meso-mechanical parameters in the orthogonal experiment scheme are determined:
Figure FDA0003031837640000011
Figure FDA0003031837640000011
 其中，aij表示待定常数，i＝1-5，j＝0-6，σc表示数值式样的单轴抗压强度，E表示数值式样的弹性模量，σt表示数值式样的抗拉强度，c表示数值式样的黏结力，
Figure FDA0003031837640000012
表示数值式样的摩擦角；Among them, a ij represents an undetermined constant, i=1-5, j=0-6, σ c represents the uniaxial compressive strength of the numerical model, E represents the elastic modulus of the numerical model, σ t represents the tensile strength of the numerical model , c represents the adhesive force of the numerical model,
Figure FDA0003031837640000012
represents the friction angle of the numerical style; 根据所述宏观力学参数和所述试验宏观力学参数确定优化目标函数：Determine the optimization objective function according to the macroscopic mechanical parameters and the experimental macroscopic mechanical parameters:
Figure FDA0003031837640000021
其中，δ表示优化目标函数；
Figure FDA0003031837640000021
Among them, δ represents the optimization objective function; 根据预存的非线性规划算法确定最优细观力学参数；Determine the optimal meso-mechanical parameters according to the pre-stored nonlinear programming algorithm; 根据所述最优细观力学参数对所述目标岩石进行标定；calibrating the target rock according to the optimal meso-mechanical parameters; 其中，所述确定目标岩石的宏观力学参数包括：Wherein, the macroscopic mechanical parameters of the determined target rock include: 根据预存的单轴压缩试验获取目标岩石的宏观力学参数的单轴抗压强度
Figure FDA0003031837640000023
和弹性模量Et；Obtain the uniaxial compressive strength of the macro-mechanical parameters of the target rock according to the pre-existing uniaxial compression test
Figure FDA0003031837640000023
and elastic modulus E t ; 根据预存的巴西劈裂试验获取目标岩石的宏观力学参数的抗拉强度
Figure FDA0003031837640000024
Obtain the tensile strength of the macro-mechanical parameters of the target rock according to the pre-existing Brazilian splitting test
Figure FDA0003031837640000024
 根据预存的常规三轴压缩试验获取目标岩石的宏观力学参数的黏聚力ct和内摩擦系数tanφt。The macroscopic mechanical parameters of the target rock, cohesion c t and internal friction coefficient tanφ t , are obtained according to the pre-existing conventional triaxial compression test. 2.如权利要求1所述的岩石细观力学参数的标定方法，其特征在于，还包括：根据表达式
Figure FDA0003031837640000022
确定目标岩石的颗粒粒径d，其中，Num表示目标岩石的颗粒数目，X、Y分别表示目标岩石的最大水平截面的长和宽。2. The method for calibrating rock meso-mechanical parameters as claimed in claim 1, further comprising: according to the expression
Figure FDA0003031837640000022
Determine the particle size d of the target rock, where Num represents the particle number of the target rock, and X and Y represent the length and width of the maximum horizontal section of the target rock, respectively. 3.一种岩石细观力学参数的标定装置，其特征在于，包括：3. A calibration device for rock meso-mechanical parameters, characterized in that, comprising: 宏观力学参数确定模块，用于确定目标岩石的宏观力学参数和颗粒粒径；The macro-mechanical parameter determination module is used to determine the macro-mechanical parameters and particle size of the target rock; 正交试验方案确定模块，用于根据预存的细观力学参数确定正交试验方案，具体包括：根据预存的平行粘结模型确定细观力学参数pbm_emod、pbm_fric、pbm_bemod、pbm_ten_m、pbm_coh_m和pbm_fa，其中，pbm_emod表示有效模量，pbm_fric表示摩擦系数；pbm_bemod表示接触有效模量，pbm_ten_m表示接触平均抗拉强度，pbm_coh_m表示接触平均黏结力，pbm_fa表示接触摩擦角；根据所述pbm_emod、所述pbm_fric、所述pbm_bemod、所述pbm_ten_m、所述pbm_coh_m和所述pbm_fa确定正交试验方案；The orthogonal test plan determination module is used to determine the orthogonal test plan according to the pre-stored meso-mechanical parameters, including: determining the meso-mechanical parameters pbm_emod, pbm_fric, pbm_bemod, pbm_ten_m, pbm_coh_m and pbm_fa according to the pre-stored parallel bonding model, where , pbm_emod represents the effective modulus, pbm_fric represents the friction coefficient; pbm_bemod represents the contact effective modulus, pbm_ten_m represents the contact average tensile strength, pbm_coh_m represents the contact average bond force, pbm_fa represents the contact friction angle; The pbm_bemod, the pbm_ten_m, the pbm_coh_m and the pbm_fa determine an orthogonal test scheme; 数值式样模型确定模块，用于根据所述正交试验方案和所述颗粒粒径确定细观力学参数数值式样模型；a numerical style model determination module, used for determining a numerical style model of meso-mechanical parameters according to the orthogonal test scheme and the particle size; 试验宏观力学参数确定模块，用于根据所述细观力学参数数值式样模型确定所述正交试验方案对应的试验宏观力学参数；a test macro-mechanical parameter determination module, used for determining the test macro-mechanical parameters corresponding to the orthogonal test scheme according to the meso-mechanical parameter numerical model; 目标岩石标定模块，用于根据预存的多元线性拟合分析方法，确定所述试验宏观力学参数和所述正交试验方案中不同细观力学参数组合的表达式：The target rock calibration module is used to determine the expression of the test macro-mechanical parameters and the combination of different meso-mechanical parameters in the orthogonal test scheme according to the pre-existing multivariate linear fitting analysis method:
Figure FDA0003031837640000031
Figure FDA0003031837640000031
 其中，aij表示待定常数，i＝1-5，j＝0-6，σc表示数值式样的单轴抗压强度，E表示数值式样的弹性模量，σt表示数值式样的抗拉强度，c表示数值式样的黏结力，
Figure FDA0003031837640000032
表示数值式样的摩擦角；Among them, a ij represents an undetermined constant, i=1-5, j=0-6, σ c represents the uniaxial compressive strength of the numerical model, E represents the elastic modulus of the numerical model, σ t represents the tensile strength of the numerical model , c represents the adhesive force of the numerical model,
Figure FDA0003031837640000032
represents the friction angle of the numerical style; 根据所述宏观力学参数和所述试验宏观力学参数确定优化目标函数：Determine the optimization objective function according to the macroscopic mechanical parameters and the experimental macroscopic mechanical parameters:
Figure FDA0003031837640000033
其中，δ表示优化目标函数；
Figure FDA0003031837640000033
Among them, δ represents the optimization objective function; 根据预存的非线性规划算法确定最优细观力学参数；Determine the optimal meso-mechanical parameters according to the pre-stored nonlinear programming algorithm; 根据所述最优细观力学参数对所述目标岩石进行标定；calibrating the target rock according to the optimal meso-mechanical parameters; 其中，所述宏观力学参数确定模块还包括：Wherein, the macroscopic mechanical parameter determination module further includes: 单轴抗压强度确定模块，用于根据预存的单轴压缩试验获取目标岩石的宏观力学参数的单轴抗压强度
Figure FDA0003031837640000041
和弹性模量Et；The uniaxial compressive strength determination module is used to obtain the uniaxial compressive strength of the macro-mechanical parameters of the target rock according to the pre-existing uniaxial compression test
Figure FDA0003031837640000041
and elastic modulus E t ; 抗拉强度确定模块，用于根据预存的巴西劈裂试验获取目标岩石的宏观力学参数的抗拉强度
Figure FDA0003031837640000042
Tensile Strength Determination Module for obtaining the tensile strength of the macro-mechanical parameters of the target rock based on the pre-existing Brazilian splitting test
Figure FDA0003031837640000042
 黏聚力确定模块，用于根据预存的常规三轴压缩试验获取目标岩石的宏观力学参数的黏聚力ct和内摩擦系数tanφt。The cohesion determination module is used to obtain the cohesion c t and the internal friction coefficient tanφ t of the macro-mechanical parameters of the target rock according to the pre-existing conventional triaxial compression test. 4.如权利要求3所述的岩石细观力学参数的标定装置，其特征在于，还包括：4. The calibration device of rock meso-mechanical parameters as claimed in claim 3, characterized in that, further comprising: 颗粒粒径确定模块，用于根据表达式
Figure FDA0003031837640000043
确定目标岩石的颗粒粒径d，其中，Num表示目标岩石的颗粒数目，X、Y分别表示目标岩石的最大水平截面的长和宽。Particle size determination module for
Figure FDA0003031837640000043
Determine the particle size d of the target rock, where Num represents the particle number of the target rock, and X and Y represent the length and width of the maximum horizontal section of the target rock, respectively. 5.一种岩石细观力学参数的标定终端设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如权利要求1至2任一项所述方法的步骤。5. A calibration terminal device for rock meso-mechanical parameters, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the A computer program implementing the steps of the method as claimed in any one of claims 1 to 2. 6.一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至2任一项所述方法的步骤。6. A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented .
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN111766304B (en) * 2020-07-13 2023-05-09 北京建筑大学 Method for judging macro-micro behavior relation of brittle rock based on compression test
CN113758839B (en) * 2021-07-19 2022-12-16 山东大学 Large-scale rock simulation method and system based on coarse graining bonding model
CN114021417A (en) * 2021-11-05 2022-02-08 辽宁工程技术大学 Relevance between each microscopic parameter and macroscopic mechanical parameter of PFC3D built-in linear contact model
CN114117879B (en) * 2021-12-02 2024-11-08 中铁十九局集团有限公司 A method for calibrating micro-parameters of triaxial shear discrete element model for sandy gravel soil
CN115828747B (en) * 2022-12-01 2023-09-26 山东大学 Intelligent calibration method and system for fractured rock mass parameters considering particle interlocking effect
CN119180202B (en) * 2024-09-05 2025-04-25 江西理工大学 Parallel bonding model microscopic parameter calibration method, system, equipment and medium

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1619294A (en) * 2004-11-30 2005-05-25 中国科学院武汉岩土力学研究所 Mesomechanical loading system for rock fracture process coupled with stress-water flow-chemical
CN102262011A (en) * 2011-04-19 2011-11-30 长安大学 Method for constructing graded crushed rock micro-mechanical model and calibrating micro-mechanical parameter
CN102564855A (en) * 2011-12-31 2012-07-11 长安大学 Numerical method for graded crushed stone dynamic triaxial test
CN103197042A (en) * 2013-02-27 2013-07-10 北京科技大学 Computing method for representative elementary volume of jointed rock
CN103605841A (en) * 2013-11-07 2014-02-26 河海大学 Method for building numerical simulation model of hydraulic engineering asphalt concrete
CN103940666A (en) * 2014-03-18 2014-07-23 中国矿业大学 Determination method for mesoscopic parameters simulating mechanical properties of intermittent crack rock
CN106706884A (en) * 2017-01-11 2017-05-24 北京科技大学 Method and apparatus for determining development degree of rock cracks

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1619294A (en) * 2004-11-30 2005-05-25 中国科学院武汉岩土力学研究所 Mesomechanical loading system for rock fracture process coupled with stress-water flow-chemical
CN102262011A (en) * 2011-04-19 2011-11-30 长安大学 Method for constructing graded crushed rock micro-mechanical model and calibrating micro-mechanical parameter
CN102564855A (en) * 2011-12-31 2012-07-11 长安大学 Numerical method for graded crushed stone dynamic triaxial test
CN103197042A (en) * 2013-02-27 2013-07-10 北京科技大学 Computing method for representative elementary volume of jointed rock
CN103605841A (en) * 2013-11-07 2014-02-26 河海大学 Method for building numerical simulation model of hydraulic engineering asphalt concrete
CN103940666A (en) * 2014-03-18 2014-07-23 中国矿业大学 Determination method for mesoscopic parameters simulating mechanical properties of intermittent crack rock
CN106706884A (en) * 2017-01-11 2017-05-24 北京科技大学 Method and apparatus for determining development degree of rock cracks

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
基于Flatjoint接触模型的岩石单轴压缩和巴西劈裂颗粒流模拟研究;刘富有 等;《长江科学院院报》;20160930;第33卷(第9期);第60-65页 *
基于正交设计的颗粒流模型宏细观参数相关分析-以岩石单轴压缩数值试验为例;牛林新 等;《人民长江》;20150831;第46卷(第16期);第53-57页 *
节理岩体力学特征及隧道施工力学行为研究;袁维;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20140515(第5期);第C034-593页 *

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