CN113758839A - Large-scale rock simulation method and system based on coarse grained bonding model - Google Patents
Large-scale rock simulation method and system based on coarse grained bonding model Download PDFInfo
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Abstract
The invention relates to a large-scale rock simulation method and system based on a coarse grained bonding model, which comprises the following steps: establishing a uniaxial compression cylinder model and a Brazilian disc particle model with standard sizes based on the mechanical property information of the target rock, obtaining mesoscopic parameters for simulating the target rock in an indoor test scale, and correcting a coarse grained particle bonding model by using the mesoscopic parameters; on the basis of the corrected coarse grained particle bonding model, the tensile strength of the rock initial model and the model after the particle size scaling are equal, and the particle size of the rock model after scaling is obtained by utilizing the particle size of the initial model; and (5) completing simulation by using the particle size of the scaled rock model. The coarse grain bonding model is used for calculating by replacing the grain groups with small grain sizes with coarse grains with large diameters in rock grain simulation calculation, so that the grain number in the rock simulation calculation is reduced, and the efficient simulation calculation of the large-scale rock deformation problem is realized.
Description
Technical Field
The invention relates to the field of geotechnical engineering, in particular to a large-scale rock simulation method and system based on a coarse grained bonding model.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Engineering construction and industrial production in the geotechnical field always accompany the large deformation damage process of rocks, the large deformation damage process of rocks is the motion process of a large number of rock particles, the evolution mechanism of rock deformation damage is usually carried out by a simulation experiment in order to reveal, but the traditional laboratory scale simulation is not enough to meet the requirement of people for revealing the evolution mechanism of the engineering scale problem, the simulation of the large deformation damage process of the engineering scale accompanies the simulation calculation of a large number of small-particle-size particles, and is limited by the existing algorithm and the level of computer hardware, the parameter calibration of large-particle-size particles is difficult to carry out by utilizing the traditional discrete unit method, and the large number of small-particle-size particles is difficult to carry out high-efficiency calculation, so that the accurate discrete element simulation containing the bonding particles is only suitable for the indoor test scale at present and cannot meet the actual engineering requirement.
The discrete unit method is suitable for simulation of interaction between particle motion and particles in millimeter scale, so that when the discrete element numerical simulation of engineering scale is carried out, the numerical model is difficult to carry out original scale reduction on a real rock physical model due to the limitation of resource consumption and computing capacity.
In view of the above problems, some existing researches propose a solution using a high-performance computer and a parallel computing method.
For example, based on parallel computing of Graphics Processing Units (GPUs). Although the GPU can simulate millions or even tens of millions of rock particles at present, the particle size of the rock particles in many rock particle multiphase flow systems is very small (1-100 micrometers), which makes the number of the particles in these systems in the order of hundreds of millions or trillions, and the GPU needs a long time to develop to simulate the number of particles in the order of trillions, so that the problem of ultrahigh calculation amount caused by engineering scale calculation cannot be solved well only by the GPU technology at present.
Disclosure of Invention
In order to solve the technical problems existing in the background technology, the invention provides a large-scale rock simulation method and system based on a coarse grained bonding model, the coarse grained particle bonding model is constructed, coarse grains with large diameters are used for replacing grain groups with small grain diameters for calculation in rock grain simulation calculation by using the coarse grained particle bonding model, the number of grains in the rock simulation calculation is reduced, and efficient simulation calculation of large-scale rock deformation is realized.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a large-scale rock simulation method based on a coarse grained cementing model, which comprises the following steps:
acquiring mechanical property information of a target rock;
establishing a uniaxial compression cylinder model and a Brazilian disc particle model with standard sizes based on the mechanical property information of the target rock, obtaining mesoscopic parameters for simulating the target rock in an indoor test scale, and correcting a coarse grained particle bonding model by using the mesoscopic parameters;
based on the corrected coarse grained particle bonding model, the tensile strength of the particles of the rock initial model and the scaled model is equal, and the particle size of the rock model after scaling is obtained by using the particle size of the initial model;
and (5) completing simulation by using the particle size of the scaled rock model.
The mechanical property information of the target rock includes compressive strength, tensile strength, elastic modulus, poisson's ratio and internal friction angle.
The process of correcting the coarse grained particle bonding model by using the microscopic parameters comprises the following steps:
keeping the size and the microscopic parameters of the Brazilian disc particle model unchanged, changing the particle size of the particles in the Brazilian disc particle model, and obtaining the tensile strength corresponding to the other particle size;
based on the particle size, the model size and the microscopic parameters in the uniaxial compression cylinder model and the Brazilian disc particle model, the established coarse grained particle bonding model is utilized to keep the tensile strength equal under the condition of corresponding two particle sizes, and the calibration coefficient is obtained.
The process of obtaining the grain size of the scaled rock model based on the corrected coarse grained particle binding model comprises:
obtaining I-type fracture toughness and particle size of a rock sample, and obtaining a relational expression of the I-type fracture toughness of the rock sample, ultimate tensile strength of a rock particle bonding bond and the particle size of the rock sample by utilizing a dimensionless factor which increases along with irregularity, strength heterogeneity and bonding ductility of rock particles and a dimensionless factor of bending moment weakening action;
and replacing the particle groups with small particle sizes by using coarse particles with large diameters to ensure that the tensile strength of the rock initial model is equal to that of the rock model after scaling, and obtaining the particle sizes of the rock model after scaling by using the particle sizes of the rock initial model.
A second aspect of the present invention provides a system for implementing the above method, comprising:
a rock parameter acquisition module configured to: acquiring mechanical property information of a target rock;
a correction module configured to: establishing a uniaxial compression cylinder model and a Brazilian disc particle model with standard sizes based on the mechanical property information of the target rock, obtaining microscopic parameters for simulating the target rock at an indoor test scale, and obtaining a calibration coefficient by using the microscopic parameters to complete the correction of a coarse grained particle bonding model;
a model scaling module configured to: based on the corrected coarse grained particle bonding model, the tensile strength of the particles of the rock initial model and the scaled model is equal, and the particle size of the rock model after scaling is obtained by using the particle size of the initial model;
a simulation computation module configured to: and (5) completing simulation by using the particle size of the scaled rock model.
Compared with the prior art, the above one or more technical schemes have the following beneficial effects:
1. the method solves the difficulty that in the rock simulation calculation process aiming at rock deformation damage under the engineering scale, the calculated amount caused by the huge number of rock particles is difficult to bear by the current computer hardware level. By applying the coarse grained particle bonding model, coarse particles with large diameters are used for replacing particle groups with small particle sizes for calculation in simulation calculation, the number of particles in rock simulation calculation is reduced, and efficient simulation calculation of large-scale rock deformation is realized.
2. The problem that the tensile strength is difficult to accurately and quantitatively simulate when large-scale rocks are simulated is solved. Based on fracture mechanics and simulation experience, a construction process of a coarse grained particle bonding model is given, so that a large amount of small-particle-size particle groups can be replaced by a small amount of large-diameter coarse particles in large-scale rock simulation for simulation calculation, the calculated particle amount is reduced, and quantitative and efficient simulation of large-scale rock behaviors is realized.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a flow diagram of coarse grain computation provided by one or more embodiments of the invention;
FIG. 2 is a schematic diagram of a coarse granulation principle provided by one or more embodiments of the present invention;
FIG. 3 is a diagram of a Brazilian disc coupon provided in accordance with one or more embodiments of the present invention;
fig. 4 is a graph comparing tensile strength results before and after application of a coarse grained particle bonding model according to one or more embodiments of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As described in the background art, the evolution mechanism of the rock large deformation damage process is disclosed through the simulation of rock particles, and the existing methods are difficult to deal with due to the huge calculation amount of engineering dimension in the process of simulating the rock particles.
For example, using the principle of amplification (e.g., the Reynolds number and Stokes number are similar), a small model is used to approximately characterize the motion behavior of a large system. Or a theoretical frame, a scaling rule and a scale law of the discrete unit model established based on a similarity principle and a dimension analysis means, so that the accuracy of the discrete element model after the particles are scaled is controlled. However, these similarity criteria are generally satisfied only in a local region (e.g., an entrance) of the system under study, and complete similarity between a large system and a small system in any space and time cannot be achieved, and simulation of rock particles during rock deformation failure at an engineering scale cannot be satisfied.
The Discrete Element Method (DEM) is a Method of simulating the behavior of Discrete groups by considering a Discrete system as a set of a limited number of Discrete elements (particles or blocks) and displaying iteration through the interaction between the elements and Newton's second law, so that the problem of large computation amount of the DEM is involved when a large-scale rock mechanics problem is simulated based on the Method.
The problem of large DEM computation can be overcome with new mathematical models and numerical algorithms, which can be uniformly considered as a Coarse-grained (CG) method. The idea of the coarse-grained method is to grasp the major physical phenomena of large scale and ignore or average some minor physical phenomena of small scale. This method has been successfully used to reduce the computational load of Molecular Dynamics (MD).
For example, 3265 coarse grained particles can represent 1 million atoms to effectively simulate the curvature of a biofilm. Compared with the method of directly replacing small particles with large particles by neglecting physical reality violently, the coarse granulation theory provides a feasible method for the simulation of large-scale engineering problems.
Scholars at home and abroad carry out a lot of researches on the coarse graining theory of discrete elements. The energy minimum multiscale model (EMMS) method proposed by Lijing Haishi academy team in the Chinese academy of sciences process is a coarse graining idea, which requires that when the recovery coefficients of grains are 0.9 and 0.5 respectively, the coarse graining proportion values need to be respectively less than 5.26 and 1.33, so the idea may not be used for industrial-grade large-scale systems; the coarse graining thought proposed by the Sakai professor of the university of tokyo is that the real particles represented by coarse particles collide with each other when the coarse particles collide, and the method ensures that the collision time between the coarse particles is equal to the collision time between the real particles, and has the defect that a relatively small time step length is needed to keep the stability of calculation, so that the calculation amount is remarkably increased under the condition of a large scaling ratio; in the rough granulation thought based on impulse theorem and provided by the university of Shandong, Broussonetia papermulberry, the change of the momentum of the particles is based on the stress and the action time of the force, and the rough granulation thought can be used for the condition that the rough granulation proportion value is large; other are the coarse-grained idea based on particle stiffness and test results and the coarse-grained idea based on energy density conservation and dimensionless factor norm analysis.
The following embodiment provides a derivation and establishment process of a coarse grained particle bonding model, the coarse grained particle bonding model is used for calculating by replacing a particle group with a small particle size by coarse particles with a large diameter in rock particle simulation calculation, the number of particles in rock simulation calculation is reduced, and efficient simulation calculation of large-scale rock deformation is realized.
The first embodiment is as follows:
as shown in fig. 1 to 4, a large-scale rock simulation method based on a coarse grained cementing model comprises the following steps:
acquiring mechanical property information of a target rock;
establishing a uniaxial compression cylinder model and a Brazilian disc particle model with standard sizes based on the mechanical property information of the target rock, obtaining microscopic parameters for simulating the target rock at an indoor test scale, and obtaining a calibration coefficient by using the microscopic parameters to complete the correction of a coarse grained particle bonding model;
based on the corrected coarse grained particle bonding model, the tensile strength of the rock initial model is equal to that of the scaled rock model, and the particle size of the scaled rock model is obtained by using the particle size of the rock initial model;
the simulation was completed using the particle size of the scaled rock model.
Geological body sampling can be obtained through engineering geological research so as to obtain mechanical information of target rocks, and therefore the correction process is completed; meanwhile, geological structure information can be obtained through engineering geological research, a geometric model of the geological structure is established by utilizing Solidworks software, then particle generation and filling are carried out based on a Discrete Element Method (DEM), a model of a Discrete particle geologic body is obtained, and the geological structure is embodied in the form of a certain number of rock particles; the simulation of the rock deformation damage process is to analyze the movement and stress of each rock particle, which occupies a very large computational resource, and the coarse grained particle bonding model provided in this embodiment calculates the large number of rock particles by using large-diameter coarse particles instead of small-diameter particle clusters, so that the number of particles in the rock simulation calculation is reduced, and the efficient simulation calculation of the large-scale rock deformation problem is realized.
As shown in FIG. 2, if the deformation destruction process of the rock is simulated by using real particles, the close-to-real can be obtainedThe rock particle motion stress process of the situation can occupy very large computational resources, if a particle group with a plurality of small particle sizes is regarded as a coarse particle with a large diameter, for example, in fig. 2, the particle size R of the particle after model scaling is shown asiAnd the initial model particle diameter R0A ratio of 5 or 10 would reduce the computational load of rock destruction process simulation.
The specific process is as follows:
the coarse graining calculation method for rock simulation comprises the following steps:
step 1: for a specific rock engineering, basic mechanical tests such as uniaxial compression, Brazilian splitting, triaxial compression and the like are carried out after coring the rock on site, and the physical and mechanical properties (including but not limited to compressive strength, tensile strength, elastic modulus, Poisson's ratio, internal friction angle and the like) of the target rock are tested and obtained.
Step 2: establishing a uniaxial compression cylinder and Brazilian disc particle model with standard sizes by using a DEM model construction method (wherein the particle size needs to be close to the particle size of rock), and calibrating parameters by using a trial-and-error method to obtain microscopic parameters of the target rock which can be accurately simulated by indoor test scales;
the microscopic parameters specifically include two aspects:
and (3) particle aspect: elastic modulus, poisson's ratio, static friction coefficient, dynamic friction coefficient and collision recovery coefficient;
inter-particle bonding parameters: modulus of elasticity, normal-to-tangential stiffness ratio, normal ultimate strength, tangential ultimate strength, and internal friction angle.
And step 3: keeping the size and the microscopic parameters of the Brazilian disc model in the step 2 unchanged, and only changing the particle size of the particles used in the Brazilian disc model to obtain the tensile strength corresponding to another particle size.
And 4, step 4: the particle size, model size and microscopic parameters used in step 2 and step 3 are substituted into the coarse-grained calculation formulas (1-8) to obtain the calibration coefficient λ for the present example.
And 5: when the established particle bonding model is applied, the size of the model and the particle size can be changed at will, and only the corresponding control parameters before and after coarse graining are input into the coarse grained particle bonding model for operation.
Wherein the control parameters are as follows:
the actual particle size before coarse graining is applied;
the particle size of the coarse particles after coarse granulation is applied;
applying the characteristic length size before coarse graining;
applying the characteristic length size after coarse graining;
the calibration factor lambda.
The essence of the coarse graining calculation method is that large grains are used for replacing small grain groups for calculation, so that the number of grains is reduced, and a coarse graining bonding model is used for a simulation system of large grain composition, so that the tensile strength can be ensured to be consistent with the reality.
The derivation and establishment process of the coarse grained particle bonding model comprises the following steps:
step 1: according to the Brazilian split test results under different particle sizes mentioned in the physical test, the tensile strength of the test piece is obviously improved under the condition of keeping the size of the model and the microscopic parameters unchanged. From the knowledge of fracture mechanics, the main reason for this is the type I fracture toughness K of the samplesIcThe relationship is shown in the formula (1-1) in relation to the particle diameter R of the particles.
Wherein σt' is the breaking strength of the material.
Step 2: further, it can be deduced that the type I fracture toughness K when using the particle bonding modelIcThe relationship with the particle size R of the particles is as follows:
wherein α ≧ 1 is a dimensionless factor increasing with the irregularity, strength heterogeneity and bond ductility of the rock particles, and β <1 is a dimensionless factor representing the bending moment attenuation effect.
And step 3: the prior literature discloses:
wherein D is the characteristic length of Brazilian disc, σtIs the tensile strength of the material.
And 4, step 4: it can be inferred from the formula (1-2):
in the formula, σmaxIs the ultimate tensile strength of the bond.
And 5: combining equations (1-1) and (1-4), one can obtain:
step 6: from the above relationship, σ is knowntAnd σmaxIn positive correlation, e.g. with two models (initial model diameter D)0And particle diameter R0Scaled model diameter DiAnd particle diameter RiAnd (3) initial model: a model consisting of small particles of a true particle size; scaled model: a model consisting of large particles after coarse graining) the tensile strength relationship can be assumed as follows:
if one wants to keep the tensile strength of the two models equal, i.e. σt,0＝σt,iThen need to satisfy：
Wherein A is0And B0As initial coefficient, σt，0As initial tensile strength, σt,iTaking R for the particle sizeiTensile strength ofiAnd BiTaking R for the particle sizeiA coefficient of time;
and 7: according to the simulation experience, the empirical coefficient phi can take the following form;
where λ is the calibration coefficient, the values are different when the model uses different mesoscopic parameters. Therefore, different rocks (i.e., different microscopic parameters) need to be calibrated, and the simulation result and the microscopic parameters of any group of non-standard values are substituted into the formula (1-8) to be adjusted and compared, so that specific values can be obtained.
The process realizes that under the same model size, large particles are used for replacing small particle groups to simulate the rock destruction process, and accurate tensile strength values can be obtained.
In the embodiment, the problem that the tensile strength is increased along with the increase of the particle size of the particles in the brazilian splitting test of the rock is solved by using the coarse grained particle bonding model, so that the accuracy of the established coarse grained particle bonding model is verified.
In this embodiment, the diameter of the Brazilian disc is always constant, i.e. D0＝DiThus, equations (1-8) and (1-9) can be simplified as:
wherein σmax,stdStandard (true) tensile strength values.
In this example, the Brazilian disc dimensions are 50mm in diameter and 25mm thick. The particle size distribution was set to follow a uniform distribution with an average particle size of 0.3mm, a minimum particle size of 0.2256m, and a contact radius of 1.25R. The elastic modulus of the particles was 27.5GPa, and the contact friction coefficient was 0.5. In the particle bonding model, the normal stiffness of the bond is 6.6 × 106N/m, the tangential stiffness is 2.64 × 106N/m, the normal strength of the bond is 7.1MPa, the cohesive force is 89MPa, and the radius coefficient of the bond is 1.
To obtain a specific value for the calibration factor lambda, the particle size R is usediThe model of 1mm was used as the calibration target. The specific calibration and calibration process is as follows:
(1) as can be seen from the above, if the same microscopic parameters are used for the model having a particle size of 1mm and the standard model having a particle size of 0.3mm, the tensile strength obtained by the former is larger than the true value. Therefore, σ of the model for adjusting the particle diameter of particles to 1mmmaxKeeping the values of other mesoscopic parameters unchanged, so that the tensile strength simulation result is consistent with the real value, and the sigma in the mesoscopic parameters ismaxThe value is σ in the formula for a particle diameter of 1mmmax,new；
(2) Sigma used in Standard model with particle size of 0.3mmmax,stdAnd σ obtained by Process (1)max,newSubstituting the equations (1-10) results in the calibration factor λ for this embodiment.
Through analog calibration, the calibration coefficient λ in the present embodiment is 700, so the equations (1-10) can be embodied;
by using the calibration parameters and the microscopic parameters, Brazilian splitting simulation of different particle sizes can be carried out, the comparison effect before and after the coarse grained model is applied can be obtained as shown in figure 4, and the result of the tensile strength simulation is changed from gradually increasing with the particle size when the coarse grained model is not applied to always fluctuating near the standard value.
The method solves the difficulty that in the rock simulation calculation process aiming at rock deformation damage under the engineering scale, the calculated amount is difficult to bear by the current computer hardware level due to the huge rock particle number (calculating unit number). By applying the coarse grained particle bonding model, coarse particles with large diameters are used for replacing particle groups with small particle sizes for calculation in simulation calculation, the number of particles in rock simulation calculation is reduced, and efficient simulation calculation of large-scale rock deformation is realized.
The problem that the tensile strength is difficult to accurately and quantitatively simulate when large-scale rocks are simulated is effectively solved. Based on fracture mechanics and simulation experience, a derivation process for establishing a coarse grained particle bonding model calculation formula is provided, so that a large amount of small-particle-size particle groups can be replaced by a small amount of large-diameter coarse particles in large-scale rock simulation for simulation calculation, the calculated particle amount is reduced, quantitative and efficient simulation of large-scale rock behaviors is realized, and the method has important significance for improving rock simulation calculation efficiency.
Example two:
the embodiment provides a system for implementing the method, including:
a rock parameter acquisition module configured to: acquiring mechanical property information of a target rock;
a correction module configured to: establishing a uniaxial compression cylinder model and a Brazilian disc particle model with standard sizes based on the mechanical property information of the target rock, obtaining microscopic parameters for simulating the target rock at an indoor test scale, and obtaining a calibration coefficient by using the microscopic parameters to complete the correction of a coarse grained particle bonding model;
a model scaling module configured to: on the basis of the corrected coarse grained particle bonding model, the tensile strength of the initial rock particle model is equal to that of the scaled rock particle model, and the particle size of the scaled rock particle model is obtained by utilizing the particle size of the initial rock particle model;
a simulation computation module configured to: and completing rock simulation by using the particle size of the scaled rock particle model.
The information acquired by the rock parameter acquisition module comprises compressive strength, tensile strength, elastic modulus, Poisson's ratio and internal friction angle.
The method solves the difficulty that in the rock simulation calculation process aiming at rock deformation damage under the engineering scale, the calculated amount caused by the huge number of rock particles is difficult to bear by the current computer hardware level. By applying the coarse grained particle bonding model, coarse particles with large diameters are used for replacing particle groups with small particle sizes for calculation in simulation calculation, the number of particles in rock simulation calculation is reduced, and efficient simulation calculation of large-scale rock deformation is realized.
The problem that the tensile strength is difficult to accurately and quantitatively simulate when large-scale rocks are simulated is solved. Based on fracture mechanics and simulation experience, a construction process of a coarse grained particle bonding model is given, so that a large amount of small-particle-size particle groups can be replaced by a small amount of large-diameter coarse particles in large-scale rock simulation for simulation calculation, the calculated particle amount is reduced, and quantitative and efficient simulation of large-scale rock behaviors is realized.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A large-scale rock simulation method based on a coarse grained bonding model is characterized by comprising the following steps: the method comprises the following steps:
acquiring mechanical property information of a target rock;
establishing a uniaxial compression cylinder model and a Brazilian disc particle model with standard sizes based on the mechanical property information of the target rock, obtaining mesoscopic parameters for simulating the target rock in an indoor test scale, and correcting a coarse grained particle bonding model by using the mesoscopic parameters;
based on the corrected coarse grained particle bonding model, the tensile strength of the particles of the rock initial model and the scaled model is equal, and the particle size of the rock model after scaling is obtained by using the particle size of the initial model;
and (5) completing simulation by using the particle size of the scaled rock model.
2. The coarse grained cementing model-based large-scale rock simulation method according to claim 1, wherein: the mechanical property information of the target rock comprises compressive strength, tensile strength, elastic modulus, Poisson's ratio and internal friction angle.
3. The coarse grained cementing model-based large-scale rock simulation method according to claim 1, wherein: the process of correcting the coarse grained particle bonding model by using the microscopic parameters comprises the following steps: keeping the size and the microscopic parameters of the Brazilian disc particle model unchanged, changing the particle size of the particles in the Brazilian disc particle model, and obtaining the tensile strength corresponding to the other particle size;
4. the coarse grained cementing model-based large-scale rock simulation method according to claim 3, wherein: the process of using the microscopic parameters to correct the coarse grained particle binding model further comprises: based on the particle size, the model size and the microscopic parameters in the uniaxial compression cylinder model and the Brazilian disc particle model, the established coarse grained particle bonding model is utilized to keep the tensile strength equal under the condition of corresponding two particle sizes, and the calibration coefficient is obtained.
5. The coarse grained cementing model-based large-scale rock simulation method according to claim 1, wherein: the process of obtaining the rock model scaled grain size based on the corrected coarse grained particle bonding model comprises the following steps: and obtaining the type I fracture toughness and the grain size of the rock sample.
6. The coarse grained cementing model-based large-scale rock simulation method according to claim 5, wherein: the process of obtaining the scaled grain size of the rock model based on the corrected coarse grained particle bonding model further comprises: and obtaining the type I fracture toughness of the rock sample and a relational expression between the ultimate tensile strength of the bonding bonds of the rock particles and the particle size of the rock sample by utilizing dimensionless factors which increase along with the irregularity, the strength heterogeneity and the bonding ductility of the rock particles and dimensionless factors of the bending moment weakening effect.
7. The coarse grained cementing model-based large-scale rock simulation method according to claim 5, wherein: the process of obtaining the scaled grain size of the rock model based on the corrected coarse grained particle bonding model further comprises: and replacing the particle groups with small particle sizes by using coarse particles with large diameters to ensure that the tensile strength of the rock initial model is equal to that of the rock model after scaling, and obtaining the particle sizes of the rock model after scaling by using the particle sizes of the rock initial model.
8. A system for implementing the method of claim 1, comprising:
a rock parameter acquisition module configured to: acquiring mechanical property information of a target rock;
a correction module configured to: establishing a uniaxial compression cylinder model and a Brazilian disc particle model with standard sizes based on the mechanical property information of the target rock, obtaining microscopic parameters for simulating the target rock at an indoor test scale, and obtaining a calibration coefficient by using the microscopic parameters to complete the correction of a coarse grained particle bonding model;
a model scaling module configured to: based on the corrected coarse grained particle bonding model, the tensile strength of the particles of the rock initial model and the scaled model is equal, and the particle size of the rock model after scaling is obtained by using the particle size of the initial model;
a simulation computation module configured to: and (5) completing simulation by using the particle size of the scaled rock model.
9. The coarse grained cementing model-based large-scale rock simulation method according to claim 8, wherein: the information acquired by the rock parameter acquisition module comprises compressive strength and tensile strength.
10. The coarse grained cementing model-based large-scale rock simulation method according to claim 8, wherein: the information acquired by the rock parameter acquisition module further comprises an elastic modulus, a Poisson ratio and an internal friction angle.
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| CN108804849A (en) * | 2018-06-22 | 2018-11-13 | 西南石油大学 | A kind of rock mechanics parameters evaluation method based on structure complexity |
| CN109085321A (en) * | 2018-07-25 | 2018-12-25 | 石家庄铁道大学 | The scaling method and terminal device of Micromechanical Parameters of Rock |
| CN111488703A (en) * | 2019-01-28 | 2020-08-04 | 西南石油大学 | Method for simulating fracture toughness of layered rock based on expanded finite element |
| CN112131633A (en) * | 2020-09-04 | 2020-12-25 | 山东大学 | Fluid-solid coupling simulation method and system based on coarse graining calculation theory |
| CN112362520A (en) * | 2020-10-30 | 2021-02-12 | 武汉大学 | Finite element-discrete element coupling numerical simulation program (FDEM) input parameter rapid calibration method |
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| CN108804849A (en) * | 2018-06-22 | 2018-11-13 | 西南石油大学 | A kind of rock mechanics parameters evaluation method based on structure complexity |
| CN109085321A (en) * | 2018-07-25 | 2018-12-25 | 石家庄铁道大学 | The scaling method and terminal device of Micromechanical Parameters of Rock |
| CN111488703A (en) * | 2019-01-28 | 2020-08-04 | 西南石油大学 | Method for simulating fracture toughness of layered rock based on expanded finite element |
| CN112131633A (en) * | 2020-09-04 | 2020-12-25 | 山东大学 | Fluid-solid coupling simulation method and system based on coarse graining calculation theory |
| CN112362520A (en) * | 2020-10-30 | 2021-02-12 | 武汉大学 | Finite element-discrete element coupling numerical simulation program (FDEM) input parameter rapid calibration method |
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