CN111914453A - Prediction method for large deformation of lamellar soft rock - Google Patents
Prediction method for large deformation of lamellar soft rock Download PDFInfo
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- CN111914453A CN111914453A CN202010746670.3A CN202010746670A CN111914453A CN 111914453 A CN111914453 A CN 111914453A CN 202010746670 A CN202010746670 A CN 202010746670A CN 111914453 A CN111914453 A CN 111914453A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Abstract
The invention belongs to the technical field of tunnel construction, and discloses a prediction method for large deformation of lamellar soft rock, which comprises the following steps: acquiring mechanical parameters of rocks and layers of the layered soft rock; establishing a finite element model of the layered soft rock based on the mechanical parameters, and carrying out a uniaxial compression numerical test to determine the uniaxial strength of the layered soft rock; defining a bedding factor F for a layered soft rockBPWhereinControlling the layer thickness and the layer inclination angle based on the finite element model for the strength characteristic numerical test, carrying out parameter sensitivity analysis, and obtaining the quantitative relation between the strength of the layered soft rock mass and the layer influence factor through parameter fittingDetermining rock mass strength sigma of tunnel layered soft rock based on tunnel geological conditioncm(ii) a Based onAnd (5) carrying out large deformation prediction on the layered soft rock section tunnel. The method for predicting the large deformation of the lamellar soft rock can achieve the technical effect of quantitatively predicting the large deformation of the lamellar soft rock by considering the bedding thickness, the occurrence and the shearing characteristics under the condition that the thickness of the layer is less than 10 cm.
Description
Technical Field
The invention relates to the technical field of tunnel construction, in particular to a prediction method for large deformation of lamellar soft rock.
Background
The lamellar soft rock is a soft rock type frequently encountered in the tunnel construction process, has the characteristics of extremely developed bedding, generally less than 10cm in layer thickness and low rock strength, and is very easy to cause large deformation disasters in the excavation process. In order to reduce the damage of large deformation of the tunnel, the large deformation of the tunnel needs to be reasonably predicted before construction, and scientific basis is provided for the design of the section shape, the reserved deformation and the support parameters of the tunnel. The large deformation of the lamellar soft rock is not only influenced by factors such as layer thickness and bedding attitude, but also closely related to the shearing property of the bedding, and the main numerical simulation and model test method is mainly researched aiming at the influence of the bedding on the large deformation of the soft rock at present; however, when the layer thickness is less than 10cm, numerical simulation and quantitative analysis of model test are difficult to realize due to an excessive number of layers.
Disclosure of Invention
The invention provides a method for predicting the large deformation of lamellar soft rock, which achieves the technical effect of quantitatively predicting the large deformation of lamellar soft rock by considering the bedding thickness, the occurrence and the shearing characteristics under the condition that the thickness of a layer is less than 10 cm.
In order to solve the technical problem, the invention provides a prediction method for large deformation of lamellar soft rock, which comprises the following steps:
acquiring mechanical parameters of rocks and layers of the layered soft rock;
Establishing a layered soft rock numerical test finite element model based on the mechanical parameters;
based on the numerical test finite element model, the thickness range of the control layer is 1-20 cm, the layer inclination angle range is 0-90 degrees, the lamellar soft rock uniaxial strength numerical test is carried out, and the rock mass strength sigma of the lamellar soft rock is obtainedcmWith FBPBased on the change dataFitting to obtain a quantitative relation between the intensity of the layered soft rock and the layer surface influence factor, and determining a material parameter a;
Determining self-weight stress p according to tunnel burial depthvDetermining the tunnel excavation radius r based on the design parameters of the tunnelPredicting the large deformation of the layered soft rock tunnel;
wherein the mechanical parameters include: the mechanical parameters of the rock and the bedding surface of the layered soft rock obtained by the indoor test comprise: the rock elastic modulus E, the Poisson ratio lambda, the cohesive force c and the friction angle phi of the layered soft rock, and the shear stiffness Kt, the normal stiffness Ks, the friction coefficient mu and the shear strength tau of the layer surface of the layered soft rock;
Jnrepresenting the number of joints in unit length for joint density;
n is a layer inclination angle influence coefficient, and the value of n can be taken according to the value in the table 1;
table 1: corresponding relation between bedding dip angle influence coefficient n and bedding dip angle alpha
|
0 | 10 | 20 | 30 | 40 | 50 | 60 | 70 | 80 | 90 |
n | 0.82 | 0.46 | 0.11 | 0.05 | 0.09 | 0.30 | 0.46 | 0.64 | 0.82 | 0.95 |
Wherein r is1Is rubbed on the layerCoefficient of friction, σcmRock mass strength, sigma, of stratified soft rockciThe rock strength of the layered soft rock, a is a material parameter obtained by fitting, u is a tunnel deformation, r is a tunnel excavation radius, and pvIs the dead weight stress.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the method for predicting the large deformation of the lamellar soft rock, provided by the embodiment of the application, realizes quantitative prediction of the large deformation of the lamellar soft rock by considering the bedding thickness, the occurrence and the shearing characteristics under the condition that the thickness of the layer is less than 10 cm.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a schematic view of a layered soft rock provided by an embodiment of the present invention;
FIG. 2 is a diagram of a rock mass parameter sigma obtained by parameter fitting of layered soft rock provided by the embodiment of the inventioncm/σciAnd FBPThe relationship curve of (1);
FIG. 3 is a graph showing the variation of the strength of the layered soft rock according to the thickness of the layer;
fig. 4 is a curve of the large deformation critical depth of the thin-layered soft rock segment tunnel according to the thickness of the layer provided by the embodiment of the invention.
Detailed Description
The embodiment of the application achieves the technical effect of quantitatively predicting the large deformation of the lamellar soft rock by considering the bedding thickness, the occurrence and the shearing characteristics under the condition that the thickness of the layer is less than 10cm by providing the method for predicting the large deformation of the lamellar soft rock.
In order to better understand the technical solutions, the technical solutions will be described in detail below with reference to the drawings and the specific embodiments of the specification, and it should be understood that the embodiments and specific features of the embodiments of the present invention are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features of the embodiments and examples of the present application may be combined with each other without conflict.
The embodiment provides a method for predicting large deformation of lamellar soft rock, which comprises the following steps:
acquiring mechanical parameters of rocks and layers of the layered soft rock; namely, the mechanical parameters comprise the elastoplasticity parameters of the layered soft rock determined by single-axis and three-axis compression tests: the rock elastic modulus E, the Poisson ratio lambda, the cohesive force c and the friction angle phi of the layered soft rock; and bedding mechanical parameters determined by conducting a direct shear test on bedding: shear stiffness Kt, normal stiffness Ks, friction coefficient mu and shear strength tau of the bedding plane of the layered soft rock.
Establishing a layered soft rock numerical test finite element model based on the mechanical parameters;
based on the numerical test finite element model, the thickness range of the control layer is 1-20 cm, the layer inclination angle range is 0-90 degrees, the lamellar soft rock uniaxial strength numerical test is carried out, and the rock mass strength sigma of the lamellar soft rock is obtainedcmWith FBPBased on the change dataFitting to obtain a quantitative relation between the intensity of the layered soft rock and the layer surface influence factor, and determining a material parameter a;
based on the formulaCalculating rock mass strength sigma of layered soft rock of tunnelcmDetermining the self-weight stress p according to the buried depth of the tunnelvDetermining the tunnel excavation radius r according to the tunnel design parameters;
wherein the mechanical parameters include: the rock elastic modulus E, the Poisson ratio lambda, the cohesive force c and the friction angle phi of the layered soft rock, and the shear stiffness Kt, the normal stiffness Ks, the friction coefficient mu and the shear strength tau of the layer surface of the layered soft rock;
Jnrepresenting the number of joints in unit length for joint density;
n is a layer inclination angle influence coefficient, and the value of n can be taken according to the value in the table 1;
table 1: corresponding relation between bedding dip angle influence coefficient n and bedding dip angle alpha
|
0 | 10 | 20 | 30 | 40 | 50 | 60 | 70 | 80 | 90 |
n | 0.82 | 0.46 | 0.11 | 0.05 | 0.09 | 0.30 | 0.46 | 0.64 | 0.82 | 0.95 |
Wherein r is1Is the coefficient of friction of the layers, σcmRock mass strength, sigma, of stratified soft rockciThe rock strength of the layered soft rock, a is a material parameter obtained by fitting, u is a tunnel deformation, r is a tunnel excavation radius, and pvIs the dead weight stress.
The following is a description of a specific engineering case.
Firstly, the surrounding rock of a railway tunnel mainly comprises layered slates, and basic mechanical parameters of the layered soft rock are determined by carrying out an indoor triaxial compression test and a direct shearing test of a layer surface of the rock
Secondly, establishing a finite element model containing a rock sample of the bedding surface, wherein the bedding surface rock is simulated by a solid unit in the modeling process, the bedding surface is simulated by a contact unit, the thickness of the layer is 2cm, and the dip angle of the bedding surface is 45 degrees.
Thirdly, the layer inclination angle (0-90 degrees) with the layer thickness Jn value of 1-10 (layer thickness 10-1 cm) is used as a variable, a numerical test containing the uniaxial strength of the layer sample is carried out under the condition of different parameters, and the strength sigma of the rock mass is researchedcmFactor of influence with bedding planeAnd performing parameter fitting to obtain rock mass parameter sigmacm/σciAnd FBPThe relationship of (2) is shown in FIG. 2:
fourthly, according to the actual situation of the supporting project, the layer influence coefficient r1Taking the thickness of 0.1, the bedding surface friction coefficient n as 1.0, taking the value of Jn as 10-1 when the thickness of the layer is 1-10 cm, and calculating to obtain the rock mass strength sigmacmThe change rule of (2) is shown in fig. 3.
Fifthly, when the tunnel buried depth is 300-500 m, calculating to obtain the vertical ground stress level pv7.5 to 12.5MPa, and substituting the pressure difference into the formulaThe change rule of the lamellar soft rock under different burial depths is obtained by calculation and is shown in figure 4.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the method for predicting the large deformation of the lamellar soft rock, provided by the embodiment of the application, realizes quantitative prediction of the large deformation of the lamellar soft rock by considering the bedding thickness, the occurrence and the shearing characteristics under the condition that the thickness of the layer is less than 10 cm. Meanwhile, the method provided by the application can realize reliable prediction in a larger specification range of the layered soft rock.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to examples, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (1)
1. A prediction method for lamellar soft rock large deformation is characterized by comprising the following steps:
acquiring mechanical parameters of rocks and layers of the layered soft rock;
Establishing a layered soft rock numerical test finite element model based on the mechanical parameters;
based on the numerical test finite element model, the thickness range of the control layer is 1-20 cm, the layer inclination angle range is 0-90 degrees, the lamellar soft rock uniaxial strength numerical test is carried out, and the rock mass strength sigma of the lamellar soft rock is obtainedcmWith FBPBased on the change dataFitting to obtain a quantitative relation between the intensity of the layered soft rock and the layer surface influence factor, and determining a material parameter a;
Determining self-weight stress p according to tunnel burial depthvDetermining the tunnel excavation radius r according to the tunnel design parameters based onPredicting the large deformation of the layered soft rock tunnel;
wherein the mechanical parameters include: the mechanical parameters of the rock and the bedding surface of the layered soft rock obtained by the indoor test comprise: the elastic modulus E of the rock, the Poisson ratio lambda, the cohesive force c and the friction angle phi, and the shear rigidity Kt, the normal rigidity Ks, the friction coefficient mu and the shear strength tau of the layer surface of the layered soft rock;
Jncharacterizing the number of joints per unit length for joint density;
n is a layer inclination angle influence coefficient, and the value of n can be taken according to the value in the table 1;
table 1: corresponding relation between bedding dip angle influence coefficient n and bedding dip angle alpha
Wherein r is1Is the coefficient of friction of the layers, σcmRock mass strength, sigma, of stratified soft rockciThe rock strength of the layered soft rock, a is a material parameter obtained by fitting, u is a tunnel deformation, r is a tunnel excavation radius, and pvIs the dead weight stress.
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Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20190071968A1 (en) * | 2017-09-05 | 2019-03-07 | Chang'an University | Method for Deformation Control of Large-span Tunnel in Chlorite Schist Stratum |
CN110489844A (en) * | 2019-08-09 | 2019-11-22 | 山东大学 | One kind being suitable for the uneven large deformation grade prediction technique of soft rock tunnel |
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Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20190071968A1 (en) * | 2017-09-05 | 2019-03-07 | Chang'an University | Method for Deformation Control of Large-span Tunnel in Chlorite Schist Stratum |
CN110489844A (en) * | 2019-08-09 | 2019-11-22 | 山东大学 | One kind being suitable for the uneven large deformation grade prediction technique of soft rock tunnel |
Non-Patent Citations (2)
Title |
---|
D.J. LIU等: "《Large deformation mechanism and concrete-filled steel tubular support control technology of soft rock roadway-A case study》", 《ENGINEERING FAILURE ANALYSIS》 * |
陈子全等: "《高地应力层状软岩隧道大变形预测分级研究》", 《西南交通大学学报》 * |
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