CN116579146A - Tunnel rock mass dynamic grading method based on drilling process of rock drill - Google Patents
Tunnel rock mass dynamic grading method based on drilling process of rock drill Download PDFInfo
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- 238000012669 compression test Methods 0.000 description 3
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Abstract
The invention discloses a tunnel rock mass dynamic grading method based on a drilling process of a rock drill, which comprises the following steps: s1, acquiring drilling tool response information of a field drilling test of a rock drill; s2, obtaining discrete element numerical simulation result information of a drilling process of the rock drill; and S3, obtaining a surrounding rock dynamic classification database according to the drilling tool response information and the discrete element numerical simulation result information. By adopting the technical scheme of the invention, the problem that the dynamic grading of rock mass quality of the rock drill during rock breaking cannot be realized in the prior art is solved.
Description
Technical Field
The invention belongs to the technical field of geotechnical engineering, and particularly relates to a tunnel rock mass dynamic grading method based on a drilling process of a rock drill.
Background
The current tunnel often encounters bad geological phenomena such as fault development, surrounding rock weakness and the like in the process of excavation, the conventional rock mass classification step is complicated, and the surrounding rock cannot be classified accurately and dynamically in real time through data acquired through disturbed rock samples. The method of combining qualitative and quantitative classification of surrounding rock of tunnels in China is mainly adopted, but the surrounding rock classification in the design stage has a larger difference from the surrounding rock condition in the actual construction of tunnels due to various reasons, and the problem that the dynamic classification of rock mass quality in the rock breaking process of a rock drill cannot be realized exists.
Disclosure of Invention
The invention aims to solve the defects of the prior art, and provides a tunnel rock mass dynamic grading method based on a drilling process of a rock drill so as to solve the problem that the dynamic grading of rock mass quality of the rock drill during rock breaking cannot be realized in the prior art.
In order to achieve the above object, the present invention provides the following solutions:
a dynamic grading method of tunnel rock mass based on the drilling process of a rock drill comprises the following steps:
s1, acquiring drilling tool response information of a field drilling test of a rock drill;
s2, obtaining discrete element numerical simulation result information of a drilling process of the rock drill;
and S3, obtaining a surrounding rock dynamic classification database according to the drilling tool response information and the discrete element numerical simulation result information.
Preferably, in step S3, the theoretical drilling speed prediction result, the drilling tool response information and the discrete element numerical simulation result information are compared and verified, so as to obtain the surrounding rock dynamic classification database.
Preferably, the database includes: drilling speed, impact section acceleration, impact section dominant frequency and drilling thrust.
Preferably, the main frequency of the impact segment is obtained by performing fourier transform on the acceleration of the impact segment.
Preferably, the rock mass classification in the surrounding rock dynamic classification database adopts a BQ classification method.
Preferably, the basic quality index of the rock mass is according to the formula bq=100+3 r c +250K v Calculating; wherein R is c Is rock saturated uniaxial compressive strength, K v Is the rock integrity coefficient; if the rock mass structural plane is produced and the burying condition is complex, the quality index of the underground engineering rock mass passes the [ BQ]＝BQ-100(K 1 +K 2 +K 3 ) Calculating, wherein K 1 、K 2 、K 3 Correction values for the groundwater state, the structural plane occurrence and the initial ground stress state are respectively obtained.
Preferably, R is when the measured value is obtained unconditionally c By rock point load intensity index I s(50) Converted value of (a), i.e
Preferably, K v Is the wave velocity v of the rock mass longitudinal wave pm And rock longitudinal wave velocity v pr Squaring the ratio, i.e.
Compared with the prior art, the invention has the beneficial effects that:
the method is mainly based on a discrete element method, combines theoretical analysis and field test monitoring assistance, and can determine the basic quality grade of the surrounding rock by virtue of the database, thereby being convenient and efficient. Compared with the traditional surrounding rock classification method, the method does not need to measure and calculate the uniaxial compressive strength R in detail c Degree of rock integrity K v The required equipment is easy to obtain, the operation is convenient and fast, and the economy is better.
According to the method, the surrounding rock grade of the newly excavated section can be determined in real time along with the construction of the tunnel, the timeliness is good, a calculation basis is conveniently provided for changing the support design parameters, and the dynamic design of the surrounding rock support is realized.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed in the embodiments are briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for dynamically classifying a rock mass of a tunnel based on a drilling process of a rock drill in an embodiment of the invention
FIG. 2 is a flow chart of another method for dynamically grading a rock mass of a tunnel based on a drilling process of a rock drill in accordance with an embodiment of the present invention;
FIG. 3 is a schematic diagram of a drilling tool impact rotation indentation test in accordance with an embodiment of the present invention;
FIG. 4 is a model diagram of a rock drill rock breaking process in an in situ drilling test in accordance with an embodiment of the present invention;
FIG. 5 is a diagram of a discrete primitive model in an embodiment of the present invention;
FIG. 6 is a diagram of a discrete meta-model test in an embodiment of the present invention;
FIG. 7 is a diagram of a model of a discrete element device for breaking rock of a drill bit and a fracture distribution diagram in an embodiment of the invention;
wherein, in fig. 3: 1-dynamic pressure sensor, 2-laser displacement sensor, 3-drill bit, 4-rock, 5-rotary system, 6-piston, 7-cylinder, 8-air pipe;
in fig. 4: 3-drill bit, 9-drill rod, 5-rotary system, 6-piston, 10-air leg, 8-air pipe and 11-handle; 12-unidirectional acceleration sensor, 2-laser displacement sensor, 1-dynamic pressure sensor, 13-monitoring unit, 14-receiving unit;
in fig. 7: 3-drill bit, 15-wall, 16-rock mass sample, 17-joint.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1:
the existing surrounding rock classification method is mostly calculated based on formulas provided by related specifications, and calculated data sources are indoor experimental data or data collected on a tunnel construction site, so that engineering information communication and visual and effective surrounding rock classification results are not facilitated. In order to solve the problem, a novel and effective method is to build an empirical model of rock-machine mutual feedback by collecting drilling tool response information, so that the visualization, informatization and digitization degree of geotechnical engineering are effectively improved. In order to solve the defects in the prior art, the invention provides a dynamic grading method for a tunnel rock mass based on the drilling process of a rock drill, which takes discrete element analysis as a main part and theoretical analysis and field test monitoring as an auxiliary part, thereby realizing accurate and rapid evaluation of the rock mass level in the tunnel excavation process.
As shown in fig. 1, an embodiment of the present invention provides a method for dynamically classifying a rock mass of a tunnel based on a drilling process of a rock drill, including the steps of:
s1, acquiring drilling tool response information of a field drilling test of a rock drill;
s2, obtaining discrete element numerical simulation result information of a drilling process of the rock drill;
and S3, obtaining a surrounding rock dynamic classification database according to the drilling tool response information and the discrete element numerical simulation result information.
In step S2, the discrete element numerical simulation result information includes average drilling speed, impact section drilling acceleration, drilling thrust, etc. of the drilling process of the rock mass with different quality grades, and is used for comparing and perfecting the drilling tool response information acquired by the experiment. The discrete element numerical simulation result information has the advantages that the uniaxial compressive strength or the integrity coefficient of the rock mass can be adjusted according to research requirements, so that the drilling and rock breaking process with the same quality grade but different rock mass structures is simulated, and the data volume of the surrounding rock dynamic classification database is enriched.
In step S3, the theoretical drilling speed prediction result, the drilling tool response information and the discrete element numerical simulation result information are compared and verified to obtain the surrounding rock dynamic classification database.
As an implementation of the embodiment of the present invention, the database includes: drilling speed, impact section acceleration, impact section main frequency and drilling thrust; the main frequency of the impact section is obtained by Fourier transformation of the acceleration of the impact section.
As an implementation mode of the embodiment of the invention, the rock mass classification in the surrounding rock dynamic classification database adopts a BQ classification method; basic quality index of rock mass is represented by formula bq=100+3 r c +250K v Calculating; wherein R is c Is rock saturated uniaxial compressive strength, K v Is the rock integrity coefficient; if the rock mass structural plane is produced and the burying condition is complex, the quality index of the underground engineering rock mass passes the [ BQ]＝BQ-100(K 1 +K 2 +K 3 ) Calculating, wherein K 1 、K 2 、K 3 Correction values for the groundwater state, the structural plane occurrence and the initial ground stress state are respectively obtained.
Example 2:
as shown in fig. 2, the embodiment of the invention further provides a dynamic grading method for a tunnel rock mass based on the drilling process of the rock drill, which comprises the following steps:
a. deducing the drilling speed of the rock drill through theoretical analysis, and providing a prediction formula of the drilling speed;
b. collecting drilling tool response information by developing a drilling test of the on-site drilling machine;
c. selecting a proper discrete element constitutive model, and enabling the discrete element constitutive model to accord with actual conditions of a construction site through parameter calibration;
d. establishing and adjusting a rock machine mutual feed discrete element model, and calculating and analyzing to obtain a numerical simulation result;
e. comparing and verifying a drilling speed formula result deduced by theoretical analysis and drilling tool response information of a drilling test of the on-site drilling machine with a discrete element numerical simulation result;
f. establishing a surrounding rock dynamic grading database to guide engineering practice;
g. and adopting experience summarized by engineering practice to continuously correct the surrounding rock dynamic classification database so as to achieve the effect of virtuous circle.
As an implementation mode of the embodiment of the invention, in the step a, rock breaking specific work in a prediction formula of drilling speed is obtained through a drilling tool impact rotation indentation test.
As an implementation mode of the embodiment of the invention, compared with the traditional signal acquisition equipment, the components in the step b are compared and optimized in terms of selection and arrangement modes, and the requirements of stability and durability of the sensor under severe environments such as high-intensity vibration, humidity and the like can be met.
As an implementation manner of the embodiment of the present invention, the parameter calibration process in step c includes: the constitutive model in the discrete meta-software PFC adopts a parallel bonding model for simulating contact and bonding behaviors among particles. The parameter calibration process is as follows: 1. and (3) collecting experimental data: firstly, the physical and mechanical parameters of the rock sample are collected by means of compression tests, shearing tests and the like. 2. Model parameter setting: according to experimental data, the order of magnitude of parameters of the parallel bonding model are determined, including the elastic modulus, bonding strength, friction angle and the like among particles. 3. Simulation verification: and (3) performing simulation verification by using discrete meta software to design a compression test, a shearing test and the like, and comparing the simulation result with the coincidence degree of experimental data. If the simulation result accords with the experimental data, the model parameter setting is correct; if not, the model parameters need to be readjusted. In order to more quickly and accurately determine the relation between the discrete element mesoscopic parameters and the macroscopic mechanical parameters, an orthogonal test of a discrete element model can be designed, sensitivity analysis is carried out on test results, and finally a relational expression between the macroscopic and the microscopic parameters is obtained through fitting. 4. Parameter adjustment: and according to a fitting relation between the simulation result and the macro-micro parameters, adjusting the model parameters, and carrying out simulation verification again until the simulation result accords with the experimental data. Through the steps, parameters of the parallel bonding model can be calibrated, so that accuracy and reliability of a simulation result are improved.
As an implementation manner of the embodiment of the present invention, the database established in step f includes: drilling tool response information, the drilling tool response information comprising: drilling speed, impact section acceleration, impact section main frequency and drilling thrust; the main frequency of the impact section is obtained by carrying out Fourier transformation on the acceleration of the impact section.
As an implementation of the embodiment of the invention, the rock mass classification in step f adopts BQ classification. Basic quality index of rock mass is represented by formula bq=100+3r c +250K v Calculating and correcting index pass [ BQ]＝BQ-100(K 1 +K 2 +K 3 ) Calculation [ BQ]K in the formula 1 、K 2 、K 3 Correction values for the groundwater state, the structural plane attitude and the initial ground stress state respectively; wherein R is c For the saturated uniaxial compressive strength of the rock, when the measured value is obtained unconditionally, the rock point load strength index I can be adopted s(50) Is converted according to the following formula:K v is rock mass integrity coefficient, which means square (unit: km/s) of rock mass longitudinal wave velocity and rock mass longitudinal wave velocity ratio, namely +.>When the actual measurement value is unconditionally obtained, the actual measurement value can be determined according to the rock volume adjustment number in table 1.
TABLE 1
As an implementation mode of the embodiment of the invention, the surrounding rock dynamic classification database established in the step f can be continuously corrected and perfected in the step g, so that the accuracy of the surrounding rock dynamic classification database is improved, and the resolution capability of the surrounding rock dynamic classification database facing complex surrounding rock conditions is enhanced.
Further, as shown in fig. 3, the drill 3 was mounted on the dynamic pressure sensor 1 during the test, the pressure on the drill 3 was recorded, and the laser displacement sensor 2 was mounted in parallel beside the drill, and the displacement of the rock mass was recorded. The rock 4 is perpendicular to the ram axis and an air cylinder 7 is used to compress air in an air tube 8 to apply an impact load through a piston 6. Measuring and recording the pressure F of the drill bit and the depth h of the drill bit rock, calculating the work W of the drill bit under the action of external force, observing the rock change, and measuring and calculating the rock breaking volume V after loading. The process can also be simulated from the discrete meta model of fig. 7, and by changing the mesoscopic parameters of the rock mass 3, the rock breaking specific work of different types of rock can be obtained. The rock breaking specific work a can be calculated by the formula (1):
impact energy consumed in the rock breaking process (2)
Γ＝ηH (2)
Wherein: Γ is the impact energy consumed by a single impact rock breaking, η is the energy transfer coefficient, and h is the single impact energy.
By conservation of energy during drilling
Va＝Γft (3)
Wherein: v is total volume of rock mass breaking, a is rock breaking specific work (rock mass breaking work per unit volume), f is impact frequency, and t is drilling time.
The total volume of broken rock is mainly controlled by the bottom area A of the drill bit, the drilling speed v and the drilling time t, and has
V＝Avt (4)
The combined type (2), (3) and (4) can be obtained:
in the rock breaking process of the rock drill, eta, H, f and A are determined by the rock drill itself, and can be calculated by parameters of the rock drill, and a is closely related to the mass of the rock. Theoretically, the better the mass of the rock mass, the greater the breaking work per unit volume of rock mass, i.e. the greater a. As can be obtained from equation (5), v is inversely proportional to a, and v decreases as a increases. That is, the rate of penetration is closely related to the mass of the rock mass, and is approximately inversely related. Substituting the rock breaking specific work a calculated in the formula (1) to obtain the theoretical drilling speed.
Further, as shown in fig. 4, a unidirectional acceleration sensor 12 is installed on a handle 11 at the tail of the rock drill, a laser displacement sensor 2 is installed below the drill head, a dynamic pressure sensor 1 is installed below a gas leg 10 of the rock drill, a monitoring unit 13 is installed on a gas pipe 8 of the rock drill, and a receiving unit 14 (notebook computer) is placed at a distance of not more than 20 meters from the rock drill in the field. The laser displacement sensor 2 and the monitoring unit 13 are installed in a mode of binding air pipes, and the unidirectional acceleration sensor 12 is installed on a handle 11 at the tail of the rock drill in a fastening mode by additionally installing a metal fixing support. When the pneumatic rock drill works, compressed gas entering the air pipe 8 pushes the piston 6 to do high-speed reciprocating motion to continuously impact the tail part of the drill rod 9, the rotary system 5 applies drilling speed to the drill rod 9, after the piston 6 retreats, the drill rod 9 rotates by a certain angle, the piston 6 continues to move forwards, the tail part of the drill rod 9 is impacted again, and the drill bit 3 impacts rotary rock breaking under the action of the drill rod 9 to form round drilling holes with a certain depth. The unidirectional acceleration sensor 12, the laser displacement sensor 2 and the dynamic pressure sensor 1 monitor the impact acceleration, the drilling displacement and the drilling reaction force in the drilling process of the rock drill, and transmit signals to the receiving unit 14 through the monitoring unit 13. The drill bit impact period and the maximum acceleration and average acceleration of the impact section can be obtained according to the acceleration curve monitored by the unidirectional acceleration sensor 12; fourier analysis is carried out on the acceleration curve, so that the main frequency range of the impact section can be reached; the drilling rate v can be calculated from the displacement Δl monitored by the laser displacement sensor 2 from v=Δl/Δt.
Further, as shown in fig. 5, in the discrete element method, the rock mass constitutive model is selected as a parallel bond model, i.e., inter-particle contact is connected using parallel bonds. The parallel keys can be regarded as a series of springs with rigidity, act on contact surfaces among particles, can transmit force and moment at the same time, and have certain tensile strength and shear strength. When it bonds, it resists torque and exhibits linear elasticity until the force or moment exceeds its strength limit, the bonding pattern is broken and cracks begin to initiate. Tension cracks are created because the force is greater than its tensile strength, and shear cracks are created if the force is greater than its shear strength.
As shown in fig. 6, a numerical simulation virtual test was established, and the mesoscopic parameters were adjusted by trial and error. And comparing and analyzing the results obtained in the virtual test with the indoor test until the requirements are met. The numerical simulation test selects a uniaxial compression test and a conventional triaxial test. Parallel bond models were chosen to simulate the contact between particles. The rock mass sample sizes are shown in table 2.
TABLE 2
As shown in fig. 7, the diameter of the drill bit was 0.04m. The rock mass is simulated by using a tiny particle aggregate, a parallel bonding model is adopted for contact among particles, and the size of a rock mass sample 3 is 0.4mX0.4mX0.4m. Taking into account joints and cracks which can exist in an actual rock mass, a smooth joint model is adopted in discrete meta-software to generate a discrete crack grid (DFN). BQ value and uniaxial compressive strength R through surrounding rock of each level c Calculating the rock integrity coefficient K v . Basic quality index of rock mass is represented by formula bq=100+3r c +250K v Calculating R c For the saturated uniaxial compressive strength of the rock, when the measured value is obtained unconditionally, the rock point load strength index I can be adopted s(50) Is converted according to the following formula:K v is rock mass integrity coefficient, which means square (unit: km/s) of rock mass longitudinal wave velocity and rock mass longitudinal wave velocity ratio, namely +.>When the actual measurement value is unconditionally obtained, the actual measurement value can be determined according to the rock volume adjustment number in table 1. If the rock mass is of complex shape and the burying condition, K needs to be estimated according to the corrected BQ value v . The corrected BQ value calculation formula is: [ BQ]＝BQ-100(K 1 +K 2 +K 3 ) K in the formula 1 、K 2 、K 3 Respectively correcting the groundwater state, the structural surface occurrence and the initial ground stress state according to the workCheng Yanti (GB/T50218-2014) to take the value.
TABLE 1J v And K is equal to v Comparison table
Engineering rock mass grading standard (GB/T50218-2014) is adopted to round in an interpolation mode, and Violet mountain tunnel III-level surrounding rock J passing through three high speeds in Guizhou can be calculated v (volume of rock mass rational number) of 2-20 pieces/m 3 Level IV surrounding rock J of Rogpine tunnel v 18-43 bars/m 3 Lophanite fault V-stage surrounding rock J v Is that>45 strips/m 3 。
If the joints and the cracks are correspondingly reduced according to the sizes of the rock formation body samples, the difference of the volume joint numbers between different levels of rock bodies is very small, and the real rock body condition is hard to represent. Thus generating the joint 17 at 1m 3 In the middle of which the rock mass specimen 16 falls with a part of the joints 17 inside the rock mass specimen and another part of the rock mass joints 17 outside the specimen. The method is more convincing to obtain rock mass samples. And c, applying the pressure and the drilling rate of each stage of rock mass monitored by the dynamic pressure sensor 1 in the step a to the drill bit 3 as initial conditions, applying constant confining pressure to the wall 15 through servo, obtaining microscopic parameters matched with macroscopic mechanical properties by parameter calibration of the rock mass sample 16, and recording the drilling rate and the vibration acceleration of the drill bit 3 for drilling into the III-V rock mass.
And finally, according to results obtained by theoretical calculation, field test and discrete element numerical simulation comprehensive evaluation, a dynamic rock mass grading standard database of the YT-28 type airleg rock drill when drilling III-V surrounding rock is provided, as shown in table 3. In the future engineering practice, if more tunnels are excavated, such as rock mass data and drilling machine data, the database can be corrected and perfected by adopting the method, otherwise, the more perfected database can guide engineering practice more economically and effectively, and the effect of virtuous circle is achieved.
TABLE 3 Table 3
The above embodiments are merely illustrative of the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, but various modifications and improvements made by those skilled in the art to which the present invention pertains are made without departing from the spirit of the present invention, and all modifications and improvements fall within the scope of the present invention as defined in the appended claims.
Claims (8)
1. The dynamic grading method for the tunnel rock mass based on the drilling process of the rock drill is characterized by comprising the following steps of:
s1, acquiring drilling tool response information of a field drilling test of a rock drill;
s2, obtaining discrete element numerical simulation result information of a drilling process of the rock drill;
and S3, obtaining a surrounding rock dynamic classification database according to the drilling tool response information and the discrete element numerical simulation result information.
2. The method for dynamically classifying tunnel rock mass based on the drilling process of a rock drill as recited in claim 1, wherein in step S3, the theoretical drilling speed prediction result and the drilling tool response information are compared and verified with discrete element numerical simulation result information to obtain a surrounding rock dynamic classification database.
3. A method of dynamically grading a rock mass of a tunnel based on the drilling process of a rock drill as recited in claim 2, wherein the database comprises: drilling speed, impact section acceleration, impact section dominant frequency and drilling thrust.
4. A method for dynamically grading a rock mass of a tunnel based on a drilling process of a rock drill according to claim 3, wherein the dominant frequency of the impact segment is obtained by fourier transforming the acceleration of the impact segment.
5. The dynamic grading method for tunnel rock mass based on the drilling process of a rock drill according to claim 4, wherein the rock mass grading in the surrounding rock dynamic grading database adopts BQ classification method.
6. A method for dynamically grading a rock mass of a tunnel based on the drilling process of a rock drill according to claim 5, characterized in that the basic quality index of the rock mass is expressed according to the formula BQ = 100+3r c +250K v Calculating; wherein R is c Is rock saturated uniaxial compressive strength, K v Is the rock integrity coefficient; if the rock mass structural plane is produced and the burying condition is complex, the quality index of the underground engineering rock mass passes the [ BQ]＝BQ-100(K 1 +K 2 +K 3 ) Calculating, wherein K 1 、K 2 、K 3 Correction values for the groundwater state, the structural plane occurrence and the initial ground stress state are respectively obtained.
7. The dynamic grading method for tunnel rock mass based on drilling process of rock drill according to claim 6, wherein R is when measured value is unconditionally obtained c By rock point load intensity index I s(50) Converted value of (a), i.e
8. The dynamic grading method for tunnel rock mass based on the drilling process of a rock drill according to claim 6, wherein K is v Is the wave velocity v of the rock mass longitudinal wave pm And rock longitudinal wave velocity v pr Squaring the ratio, i.e.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117290928A (en) * | 2023-09-25 | 2023-12-26 | 西南交通大学 | Inversion method and device for mechanical parameters of tunnel surrounding rock based on while-drilling parameters |
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| CN117290928A (en) * | 2023-09-25 | 2023-12-26 | 西南交通大学 | Inversion method and device for mechanical parameters of tunnel surrounding rock based on while-drilling parameters |
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