CN117313456A - Method and device for predicting correlation between tunnel water inflow and fracture width - Google Patents
Method and device for predicting correlation between tunnel water inflow and fracture width Download PDFInfo
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Abstract
The invention relates to a method and a device for predicting the correlation between tunnel water inflow and fracture width, wherein the method comprises the following steps: acquiring target rock mass data, arranging nodes on the target rock mass data based on a Monte Carlo method, obtaining triangular grids of a target rock mass, obtaining fracture width based on the triangular grids of the target rock mass, acquiring target rock mass boundary conditions, establishing a boundary seepage model based on the target rock mass boundary conditions, and carrying out finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of tunnel water inflow and fracture width. The method and the device can be used for predicting the correlation between the tunnel water inflow and the fracture width.
Description
Technical Field
The invention relates to the technical field of rock mass engineering, in particular to a method and a device for predicting the correlation between tunnel water inflow and fracture width.
Background
The natural rock mass has a large number of cracks and pores, and stress fields and seepage fields formed by the cracks and the pores are mutually influenced, so that the stability of the engineering (side slope, underground cavern and tunnel) of various rock mass engineering and the engineering operation is greatly restricted. In the prior art, research on correlation prediction between tunnel water inflow and fracture width is lacking.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method, apparatus, electronic device and storage medium for predicting the correlation between the tunnel water inflow and the fracture width.
In order to achieve the above object, the present invention provides the following technical solutions:
in a first aspect, a method for predicting correlation between tunnel water inflow and fracture width includes:
acquiring target rock mass data, and arranging nodes on the target rock mass data based on a Monte Carlo method to obtain a triangular grid of a target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
obtaining fracture surface crack width based on the triangular grid of the target rock mass;
and obtaining a target rock mass boundary condition, establishing a boundary seepage model based on the target rock mass boundary condition, and carrying out finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of tunnel water inflow and the fracture width.
Further, the method for arranging nodes on the target rock mass data based on the Monte Carlo method, to obtain a triangular grid of the target rock mass, includes:
and processing the target rock mass data based on the Monte Carlo method to obtain a rock mass fracture network, and arranging nodes based on the rock mass fracture network to obtain a triangular network of the target rock mass.
Further, the establishing a boundary seepage model based on the boundary condition of the target rock mass comprises the following steps:
and obtaining a seepage statistical theoretical model, and establishing a boundary seepage model for the boundary condition of the target rock mass based on the seepage statistical theoretical model.
Further, the method comprises the steps of,
the control equation of the boundary seepage model of the rock is as follows:
wherein: p is the pressure of the fluid in the pores, θ s Is of porosity, x f And x s Compression coefficients, K, of liquid and solid respectively m Is the permeability parameter of the target rock mass, t is time, eta is the viscosity coefficient of liquid and C 1 And controlling the first preset constant parameters of the equation for the boundary seepage model of the rock.
Further, the method comprises the steps of,
the control equation of the seepage model of the fracture is as follows:
wherein: d, d frac For the layer width of the fracture, K frac For the permeability of the fracture, eta is the viscosity coefficient of the liquid, p is the pressure of the fluid in the pores, t is the time and S frac Is the surface area of the fracture.
Further, the method comprises the steps of,
the calculation formula of the bedding permeability of the fracture is as follows:
wherein: k (K) frac D, the permeability of the fracture surface is the permeability of the fracture surface frac For the layer width of the fracture surface crack, C 2 A second preset constant parameter for the surface permeability of the fracture and C 3 And (3) presetting constant parameters for the third preset constant parameters of the surface permeability of the fracture.
Further, the method comprises the steps of,
the calculation formula of the correlation prediction result of the tunnel water inflow and the fracture width is as follows:
wherein: c (C) 4 C, a fourth preset constant parameter for the correlation prediction result of the tunnel water inflow and the fracture width is obtained 5 And a fifth preset constant parameter for the correlation prediction result of the tunnel water inflow and the fracture width is obtained, wherein y is the tunnel water inflow, and x is the fracture width.
In a second aspect, the present invention also provides a device for correlating a tunnel inflow with a fracture width, comprising:
the triangular network module of the rock mass is used for acquiring target rock mass data, and nodes are arranged on the target rock mass data based on a Monte Carlo method to obtain triangular grids of the target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
the fracture width module is used for obtaining fracture width based on the triangular grid of the target rock mass;
the correlation prediction result module is used for acquiring target rock mass boundary conditions, establishing a boundary seepage model based on the target rock mass boundary conditions, and carrying out finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of tunnel water inflow and the fracture width.
In a third aspect, the present invention further provides an electronic device, configured to execute the program stored in the memory, so as to implement a step in a method for predicting correlation between a tunnel water inflow and a fracture width in any one of the foregoing implementations.
In a fourth aspect, the present invention further provides a non-transitory computer readable storage medium storing a computer program, capable of implementing the steps in a method for predicting correlation between tunnel water inflow and fracture width in any one of the above implementations.
The invention provides a method, a device, electronic equipment and a storage medium for predicting the correlation between tunnel water inflow and fracture width, wherein a triangular grid of a target rock mass is obtained by acquiring target rock mass data and arranging nodes on the target rock mass data based on a Monte Carlo method; the target rock mass data includes: and (3) obtaining fracture width based on triangular grids of the target rock, obtaining target rock boundary conditions, establishing a boundary seepage model based on the target rock boundary conditions, and carrying out finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of tunnel water inflow and the fracture width. According to the method, a set of correlation prediction methods for tunnel water inflow and fracture width are established through mutual verification of experiments and numerical simulation, the fracture equivalent fracture width is researched mainly through a numerical analysis method in mechanical aspects, the boundary seepage model is established based on the boundary condition of a target rock body by acquiring the boundary condition of the target rock body, and finally, finite element calculation is carried out based on the boundary seepage model, so that a correlation prediction result for tunnel water inflow and fracture width is obtained. Compared with the prior art, the method and the device can be used for predicting the correlation between the tunnel water inflow and the fracture width.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may 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 predicting the correlation between the water inflow of a tunnel and the fracture width according to an embodiment of the present invention;
FIG. 2 is a graph of distribution of rock mass and triangular mesh division of a tunnel fracture at K48+860 according to an embodiment of a method for predicting correlation between water inflow and fracture width of a tunnel;
FIG. 3 is a graph of a 1-hour and 2-hour variation cloud for a tunnel at K48+860 according to an embodiment of a method for predicting correlation between water inflow and fracture width of a tunnel according to the present invention;
FIG. 4 is a graph showing a 5-hour and 10-hour variation cloud of a tunnel at K48+860 according to an embodiment of the method for predicting correlation between water inflow and fracture width of a tunnel according to the present invention;
FIG. 5 is a graph of a 15-hour and 24-hour variation cloud of a tunnel at K48+860 according to an embodiment of a method for predicting correlation between water inflow and fracture width of a tunnel according to the present invention;
FIG. 6 is a graph showing the water inflow of surrounding rock over time within 24 hours of a tunnel at K48+860 according to an embodiment of the method for predicting the correlation between the water inflow of the tunnel and the fracture width provided by the invention;
FIG. 7 is a graph of water inflow rules obtained at K48+860 based on finite element computation according to an embodiment of a method for predicting correlation between water inflow and fracture width of a tunnel provided by the present invention;
FIG. 8 is a graph of distribution of rock mass and triangular mesh division of a tunnel fracture at K49+505 according to an embodiment of a method for predicting correlation between water inflow and fracture width of a tunnel;
FIG. 9 is a graph of a 1-hour and 2-hour variation cloud for a tunnel at K49+505 according to one embodiment of the method for predicting correlation between water inflow and fracture width of a tunnel provided by the present invention;
FIG. 10 is a graph of a 5 hour and 10 hour variation cloud of a tunnel at K49+505 according to one embodiment of a method for predicting correlation between tunnel water inflow and fracture width provided by the present invention;
FIG. 11 is a graph of a 15-hour and 24-hour variation cloud for a tunnel at K49+505 according to one embodiment of a method for predicting correlation between tunnel water inflow and fracture width provided by the present invention;
FIG. 12 is a graph showing the water inflow of surrounding rock over time within 24 hours of a tunnel at K49+505 according to an embodiment of the method for predicting the correlation between the water inflow of the tunnel and the fracture width provided by the invention;
FIG. 13 is a graph of water inflow rules obtained at K49+505 based on finite element calculation according to an embodiment of the method for predicting correlation between tunnel water inflow and fracture width provided by the present invention;
FIG. 14 is a schematic view of an apparatus according to an embodiment of a method for predicting correlation between water inflow and fracture width of a tunnel according to the present invention;
fig. 15 is a schematic structural diagram of an embodiment of an electronic device according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. 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 the description of the embodiments of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or modules is not necessarily limited to those steps or modules that are expressly listed or inherent to such process, method, article, or device.
The naming or numbering of the steps in the embodiments of the present invention does not mean that the steps in the method flow must be executed according to the time/logic sequence indicated by the naming or numbering, and the named or numbered flow steps may change the execution order according to the technical purpose to be achieved, so long as the same or similar technical effects can be achieved.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention provides a method, a device, electronic equipment and a storage medium for correlation between tunnel water inflow and fracture width, which are respectively described below.
FIG. 1 is a flowchart of a method for predicting correlation between water inflow and fracture width of a tunnel according to an embodiment of the present invention, including:
s110, acquiring target rock mass data, and arranging nodes on the target rock mass data based on a Monte Carlo method to obtain a triangular grid of the target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
s120, obtaining fracture width based on the triangular grid of the target rock mass;
s130, acquiring boundary conditions of the target rock mass, establishing a boundary seepage model based on the boundary conditions of the target rock mass, and performing finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of the tunnel water inflow and the fracture width.
It can be understood that the invention mainly establishes a set of prediction method for the correlation between the tunnel water inflow and the fracture width according to the mutual verification of the test and the numerical simulation.
Further, the method comprises the steps of,
and processing the target rock mass data based on the Monte Carlo method to obtain a rock mass fracture network, and arranging nodes based on the rock mass fracture network to obtain a triangular network of the target rock mass.
It can be appreciated that the formation steps of the rock mass network of tunnel rock mass and fissures are: firstly, generating an engineering rock mass fracture network within a certain range by using a Monte Carlo method according to geometric parameter statistical information such as on-site rock mass fracture length, inclination angle and interval, then arranging nodes on the fracture geometric line, and finally generating a triangular network of tunnel rock.
Further, establishing a boundary seepage model based on the boundary condition of the target rock mass comprises the following steps:
and obtaining a seepage statistical theoretical model, and establishing a boundary seepage model for the boundary condition of the target rock mass based on the seepage statistical theoretical model.
It can be understood that the rock obtained by the method is an isotropic porous medium, the width of each crack is equal, and a boundary seepage model is established by utilizing a related theory, so that the model not only solves the problem that an equivalent medium model can not correctly reflect crack seepage, but also overcomes the defect of large calculated amount of a double-hole double-seepage crack medium model.
Further, the method comprises the steps of,
the boundary seepage model control equation of the rock is as follows:
wherein: p is the pressure of the fluid in the pores, θ s Is of porosity, x f And x s Compression coefficients, K, of liquid and solid respectively m Is the permeability parameter of the target rock mass, t is time, eta is the viscosity coefficient of liquid and C 1 And controlling the first preset constant parameters of the equation for the boundary seepage model of the rock.
It will be appreciated that from the continuity equation, momentum equation and state equation of the fluid, a partial differential equation of fluid seepage can be derived.
Further, the method comprises the steps of,
the seepage control equation of the fracture is as follows:
wherein: d, d frac Layer width of fracture surface, K frac The permeability of the fracture surface is determined by eta being the viscosity coefficient of the liquid, p being the pressure of the fluid in the pores, t being the time and S frac Is the surface area of the fracture;
still further still, the method comprises the steps of,
the calculation formula of the permeability of the bedding surface is as follows:
wherein: k (K) frac Layer permeability d is the fracture surface frac Layer width of fracture surface, C 2 A second preset constant parameter for the surface permeability of the fracture and C 3 The third preset constant parameter is the layer permeability of the fracture;
still further still, the method comprises the steps of,
the flow rate of the fluid in the fracture is calculated as follows:
wherein: q is the volumetric flow rate in the fracture, A is the flow rate of the fluid in the fracture, K frac Is the permeability of the layer, d frac Is the width of the layer and η is the viscosity coefficient of the liquid.
It will be appreciated that the fracture in the tunnel rock mass is taken as a series of internal boundaries, unlike conventional boundary conditions: while conventional boundaries can only define the passage of fluid across (perpendicular to) the boundary, the boundary conditions presented herein suggest that fluid can flow along the boundary.
Further, the method comprises the steps of,
the calculation formula of the correlation prediction result of the tunnel water inflow and the fracture width is as follows:
wherein: c (C) 4 C, a fourth preset constant parameter for a predicted result of the correlation between the tunnel water inflow and the fracture width 5 And a fifth preset constant parameter for a correlation prediction result of the tunnel water inflow and the fracture width is obtained, wherein y is the tunnel water inflow, and x is the fracture width.
It is understood that the tunnel water inflow and the fracture width exhibit a power exponent relationship.
In the embodiment of the present invention, the scheme of the present invention is further described in detail by a specific embodiment:
two large water inflow sections K48+860 and K49+505 are selected in the tunnel construction period, and the method is adopted to establish a prediction method for the correlation between the water inflow quantity of the tunnel and the fracture width of the fracture. Through the execution process as in steps S110-S130, a k48+860 water inflow and fracture width correlation prediction and a k49+505 water inflow and fracture width correlation prediction are determined, respectively.
In one embodiment K48+860 flush profile, an explanation is provided in connection with FIGS. 2-7.
FIG. 2 is a graph of distribution of rock mass and triangular mesh division of a tunnel fracture at K48+860 according to an embodiment of the method for predicting correlation between water inflow and fracture width of a tunnel, comprising:
in combination with the embodiment, according to the on-site investigation data, the Ga Long La tunnel has a burial depth of 390m at the section K48+860, and the water head surface 20m away from the mountain surface is taken out, and according to the value of the calculated parameter, wherein the porosity of the rock is 0.0067, and the compression coefficients of the rock and water are 4.4X10 respectively -10 And 1.0X10 -11 The permeability of the rock is 1.0X10-15 m 2 The density of water is 1000kg/m 3 The viscosity coefficient of water is 0.001 and the water storage coefficient of the crack is 4.4X10 -10 Since the lower left corner coordinates of the finite element model are (-50 ), the calculation boundary conditions are set as: the left and right boundaries are hydrostatic head boundaries, h=370-y; the upper boundary is a constant head boundary, h=320 m, and the lower boundary is a constant head boundary, h=420 m. The initial condition is h (x, y) | t＝0 ＝370-y。
Fig. 3 is a change cloud image of a tunnel at k48+860 for 1 hour and 2 hours according to an embodiment of a method for predicting the correlation between the water inflow and the fracture width of a tunnel according to the present invention, fig. 4 is a change cloud image of a tunnel at k48+860 for 5 hours and 10 hours according to an embodiment of a method for predicting the correlation between the water inflow and the fracture width of a tunnel according to the present invention, and fig. 5 is a change cloud image of a tunnel at k48+860 for 15 hours and 24 hours according to an embodiment of a method for predicting the correlation between the water inflow and the fracture width of a tunnel according to the present invention, including:
in combination with the embodiment, fig. 3-5 are cloud diagrams of the change of the surrounding rock water head pressure with the excavation time within 24 hours of the tunnel when the surrounding rock equivalent fracture width is 3.6mm, and it can be seen from fig. 3-5: after the tunnel, the water head pressure in the cracks is rapidly reduced, which indicates that the cracks are main water guide channels, so that the size of the equivalent crack width of the surrounding rock can be predicted, and the decisive effect on the water inflow of the tunnel can be achieved; because the surrounding rock cracks of the Gal Long La tunnel are very developed and have large crack density and more through cracks, the water head drops very quickly after the tunnel is excavated, the water inflow reaches a stable state in a short time, and particularly, the pressure distribution of the water head in the surrounding rock tends to be stable after the tunnel is excavated for 8 hours.
FIG. 6 is a graph showing the time-dependent change of the water inflow of surrounding rock within 24 hours of a tunnel at K48+860 according to an embodiment of the method for predicting the correlation between the water inflow of a tunnel and the fracture width, comprising:
in combination with the embodiment, as can be seen from fig. 6, under the condition that the width of the fissure is certain, the water inflow of the surrounding rock is firstly reduced rapidly and then gradually becomes stable along with the increase of the excavation time, because the pressure of the rock head around the hole is larger at the beginning, a temporary surface is formed after the tunnel is excavated, so that the pressure of the water head in the surrounding rock is reduced rapidly, and accordingly, the water head pressure is redistributed in a shorter time along with a large amount of water inflow, the water inflow is stable soon, and from the technical result, the water inflow is not changed greatly along with the time after the tunnel is excavated for more than 8 hours; the water inflow under the condition of different effective fracture widths is compared, and the water inflow of surrounding rock is gradually increased along with the increase of the fracture width.
FIG. 7 is a graph of water inflow law calculated at K48+860 based on finite elements, according to an embodiment of a method for predicting correlation between water inflow and fracture width of a tunnel, comprising:
the power exponent relation between the surrounding rock water inflow and the equivalent fracture width is as follows:
y＝0.016e 0.967x ；
wherein: y is water inflow and x is equivalent crack width.
In combination with the embodiment, in order to better reveal the relation between the water inflow of surrounding rock and the equivalent fracture width, the equivalent fracture width of the surrounding rock with the section K48+860 is inversely analyzed by comparing with the water inflow actually measured on site, the total water inflow within 1 day of tunnel excavation is obtained by integrating each water inflow with time according to a time change rule curve in FIG. 6, a specific calculation result is shown in FIG. 7, in addition to more intuitively reflecting the increase of the water inflow with the increase of the fracture width, the fact that the surrounding rock water inflow and the equivalent fracture width have a power exponent relation can be found by fitting, the water inflow rule based on finite element calculation can be reflected by the above formula, and meanwhile, the equivalent fracture width of the section K48+860 can be reversely calculated to be 4.2mm.
In an example K49+505 flush section, the explanation is made in connection with FIGS. 8-12.
FIG. 8 is a graph of distribution of rock mass and triangular mesh division of a tunnel fracture at K49+505 according to an embodiment of the method for predicting correlation between water inflow and fracture width of a tunnel, comprising:
in combination with the present embodiment, according to the on-site survey data, the depth of the Gal Long La tunnel at the section K49+505 is 710m, the water head surface 20m from the mountain surface is taken out, and since the left lower corner coordinates of the finite element model are (-50 ), the calculation boundary conditions are set as: the left boundary and the right boundary are hydrostatic pressure water head boundaries, and h=690-y; the upper boundary is a constant head boundary, h=640 m, and the lower boundary is a constant head boundary, h=740 m. The initial condition is h (x, y) | t＝0 ＝690-y。
Fig. 9 is a graph showing a change cloud for 1 hour and 2 hours of a tunnel at k49+505, fig. 10 is a graph showing a change cloud for 5 hours and 10 hours of a tunnel at k49+505, and fig. 11 is a graph showing a change in water inflow of 24 hours of a surrounding rock at k49+505, according to an embodiment of the present invention, comprising:
in combination with the embodiment, fig. 9 to 11 are cloud diagrams of the change of the surrounding rock water head pressure with the excavation time within 24 hours of the tunnel when the surrounding rock equivalent fracture width is 3mm, and fig. 9 to 11 can show that: after the tunnel is excavated, the water head pressure in the cracks is rapidly reduced, and the water inflow reaches a stable state in a short time; the water head in surrounding rock is directly influenced by crack distribution after tunnel excavation, and when the crack distribution forms are different, the water head distribution rules are also greatly different.
FIG. 12 is a graph showing the water inflow of surrounding rock over time within 24 hours of a tunnel at K49+505 according to an embodiment of the method for predicting the correlation between the water inflow of the tunnel and the fracture width provided by the invention;
in combination with the embodiment, as can be seen from fig. 12, under the condition that the width of the fissure is certain, the water inflow of the surrounding rock is firstly reduced rapidly and then gradually becomes stable along with the increase of the excavation time, because the pressure of the rock head around the hole is larger at the beginning, a temporary surface is formed after the tunnel is excavated, so that the pressure of the water head in the surrounding rock is reduced rapidly, and accordingly, the water head pressure is redistributed in a shorter time along with a large amount of water inflow, the water inflow is stable soon, and from the technical result, the water inflow is not changed greatly along with the time after the tunnel is excavated for more than 10 hours; the water inflow under the condition of different effective fracture widths is compared, and the water inflow of surrounding rock is gradually increased along with the increase of the fracture width.
FIG. 13 is a graph of water inflow rules obtained at K49+505 based on finite element calculation according to an embodiment of the method for predicting correlation between tunnel water inflow and fracture width provided by the present invention;
the power exponent relation between the surrounding rock water inflow and the equivalent fracture width is as follows:
y＝0.049e 1.144x ；
wherein: y is water inflow and x is equivalent crack width.
In combination with the embodiment, in order to better reveal the relation between the water inflow of the surrounding rock and the equivalent fracture width, the equivalent fracture width of the surrounding rock with the section K49+505 is inversely analyzed by comparing with the water inflow actually measured on site, the total water inflow within 1 day of tunnel excavation is obtained by integrating each water inflow with time according to a time change rule curve in FIG. 12, a specific calculation result is shown in FIG. 13, in addition to the fact that the water inflow can be more intuitively reflected to increase along with the increase of the fracture width, the fact that the power exponent relation exists between the water inflow of the surrounding rock and the equivalent fracture width can be found by fitting, the water inflow rule obtained based on finite element calculation can be reflected by the formula, and meanwhile, the equivalent fracture width of the section K49+505 can be reversely calculated to be 3.2mm.
In order to better implement the method of correlation between the tunnel inflow and the fracture width in the embodiment of the present invention, referring to fig. 14, fig. 14 is a schematic structural diagram of an embodiment of an apparatus 1400 provided in the present invention, which includes:
the triangular network module 1401 of the rock mass is used for acquiring target rock mass data, and arranging nodes on the target rock mass data based on a Monte Carlo method to obtain a triangular grid of the target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
a fracture width module 1402 for obtaining a fracture width based on a triangular mesh of the target rock mass;
the correlation prediction result module 1403 is configured to obtain a target rock boundary condition, establish a boundary seepage model based on the target rock boundary condition, and perform finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of the tunnel water inflow and the fracture width.
The device for correlating the tunnel water inflow with the fracture width provided in the foregoing embodiment may implement the technical solution described in the foregoing embodiment of the method for correlating the tunnel water inflow with the fracture width, and the specific implementation principle of each module or unit may refer to the corresponding content in the foregoing embodiment of the method for correlating the tunnel water inflow with the fracture width, which is not described herein again.
As shown in fig. 15, the present invention further provides an electronic device 1500 accordingly. The electronic device 1500 includes a processor 1501, memory 1502 and a display 1503. Fig. 15 shows only some of the components of the electronic device 1500, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead.
The memory 1502 may be an internal storage unit of the electronic device 1500 in some embodiments, such as a hard disk or memory of the electronic device 1500. The memory 1502 may also be an external storage device of the electronic device 1500 in other embodiments, such as a plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card) or the like, which are provided on the electronic device 1500.
Further, the memory 1502 may also include both internal storage units and external storage devices of the electronic device 1500. The memory 1502 is used for storing application software and various types of data for installing the electronic device 1500.
The processor 1501 may be a central processing unit (Central Processing Unit, CPU), microprocessor or other data processing chip in some embodiments for executing program code or processing data stored in the memory 1502, such as a tunnel water inflow and fracture width correlation prediction method of the present invention.
The display 1503 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like in some embodiments. The display 1503 is used for displaying information at the electronic device 1500 and for displaying a visual user interface. Components 1501-1503 of electronic device 1500 communicate with each other over a system bus.
In some embodiments of the present invention, when the processor 1501 executes the tunnel inflow and fracture width correlation prediction program in the memory 1502, the following steps may be implemented:
acquiring target rock mass data, and arranging nodes on the target rock mass data based on a Monte Carlo method to obtain a triangular grid of the target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
obtaining fracture width based on the triangular grid of the target rock mass;
and obtaining a target rock mass boundary condition, establishing a boundary seepage model based on the target rock mass boundary condition, and performing finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of the tunnel water inflow and the fracture width.
It should be understood that: the processor 1501, when executing the tunnel inflow and fracture width correlation prediction program in the memory 1502, may perform other functions in addition to the above functions, and specific reference may be made to the description of the corresponding method embodiments above.
Further, the type of the electronic device 1500 is not particularly limited in the embodiments of the present invention, and the electronic device 1500 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (personal digitalassistant, PDA), a wearable device, a laptop computer (laptop), etc. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices that carry IOS, android, microsoft or other operating systems. The portable electronic device described above may also be other portable electronic devices, such as a laptop computer (laptop) or the like having a touch-sensitive surface, e.g. a touch panel. It should also be appreciated that in other embodiments of the invention, electronic device 1500 may not be a portable electronic device, but rather a desktop computer having a touch-sensitive surface (e.g., a touch panel).
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform a method of predicting a correlation between a tunnel water inflow and a fracture width provided by the above methods, the method comprising:
acquiring target rock mass data, and arranging nodes on the target rock mass data based on a Monte Carlo method to obtain a triangular grid of the target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
obtaining fracture width based on the triangular grid of the target rock mass;
and obtaining a target rock mass boundary condition, establishing a boundary seepage model based on the target rock mass boundary condition, and performing finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of the tunnel water inflow and the fracture width.
Those skilled in the art will appreciate that all or part of the flow of the methods of the embodiments described above may be accomplished by way of a computer program that instructs associated hardware, and that the program may be stored in a computer readable storage medium. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The method, the device, the electronic equipment and the storage medium for predicting the correlation between the tunnel water inflow and the fracture width are provided in the invention, and specific examples are applied to explain the principle and the implementation mode of the invention, and the description of the examples is only used for helping to understand the method and the core idea of the invention; meanwhile, as those skilled in the art will vary in the specific embodiments and application scope according to the ideas of the present invention, the present description should not be construed as limiting the present invention in summary.
Claims (10)
1. A method for predicting the correlation between the water inflow amount of a tunnel and the width of a fracture is characterized by comprising the following steps:
acquiring target rock mass data, and arranging nodes on the target rock mass data based on a Monte Carlo method to obtain a triangular grid of a target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
obtaining fracture surface crack width based on the triangular grid of the target rock mass;
and obtaining a target rock mass boundary condition, establishing a boundary seepage model based on the target rock mass boundary condition, and carrying out finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of tunnel water inflow and the fracture width.
2. The method for predicting the correlation between the tunnel water inflow and the fracture width according to claim 1, wherein the method for arranging nodes on the target rock mass data based on the monte carlo method to obtain a triangular grid of the target rock mass comprises the following steps:
and processing the target rock mass data based on the Monte Carlo method to obtain a rock mass fracture network, and arranging nodes on the rock mass fracture network to obtain a triangular network of the target rock mass.
3. The method for predicting the correlation between the tunnel inflow and the fracture width according to claim 1, wherein the establishing a boundary seepage model based on the boundary condition of the target rock mass comprises:
and obtaining a seepage statistical theoretical model, and establishing a boundary seepage model for the boundary condition of the target rock mass based on the seepage statistical theoretical model.
4. The method for predicting the correlation between the tunnel water inflow and the fracture width according to claim 1, wherein,
the control equation of the boundary seepage model of the rock is as follows:
wherein: p is the fluid in the poresPressure, θ of s Is of porosity, x f And x s Compression coefficients, K, of liquid and solid respectively m Is the permeability parameter of the target rock mass, t is time, eta is the viscosity coefficient of liquid and C 1 And controlling the first preset constant parameters of the equation for the boundary seepage model of the rock.
5. The method for predicting the correlation between the tunnel water inflow and the fracture width according to claim 4, wherein,
the control equation of the seepage model of the fracture is as follows:
wherein: d, d frac For the layer width of the fracture, K frac For the permeability of the fracture, eta is the viscosity coefficient of the liquid, p is the pressure of the fluid in the pores, t is the time, S frac Is the surface area of the fracture.
6. The method for predicting the correlation between the tunnel water inflow and the fracture width according to claim 5, wherein,
the calculation formula of the bedding permeability of the fracture is as follows:
wherein: k (K) frac D, the permeability of the fracture surface is the permeability of the fracture surface frac For the layer width of the fracture surface crack, C 2 A second preset constant parameter for the surface permeability of the fracture and C 3 And (3) presetting constant parameters for the third preset constant parameters of the surface permeability of the fracture.
7. The method for predicting the correlation between the tunnel water inflow and the fracture width according to claim 1, wherein,
the calculation formula of the correlation prediction result of the tunnel water inflow and the fracture width is as follows:
wherein: c (C) 4 C, a fourth preset constant parameter for the correlation prediction result of the tunnel water inflow and the fracture width is obtained 5 And a fifth preset constant parameter for the correlation prediction result of the tunnel water inflow and the fracture width is obtained, wherein y is the tunnel water inflow, and x is the fracture width.
8. The device for predicting the correlation between the water inflow amount of the tunnel and the fracture width of the fracture is characterized by comprising the following components:
the triangular network module of the rock mass is used for acquiring target rock mass data, and nodes are arranged on the target rock mass data based on a Monte Carlo method to obtain triangular grids of the target rock mass; the target rock mass data includes: rock mass fracture length data, rock mass fracture dip angle data and rock mass fracture spacing data;
the fracture width module is used for obtaining fracture width based on the triangular grid of the target rock mass;
the correlation prediction result module is used for acquiring target rock mass boundary conditions, establishing a boundary seepage model based on the target rock mass boundary conditions, and carrying out finite element calculation based on the boundary seepage model and the fracture width to obtain a correlation prediction result of tunnel water inflow and the fracture width.
9. An electronic device comprising a memory and a processor, wherein,
the memory is used for storing programs;
the processor is coupled to the memory for executing the program stored in the memory to implement the steps in a tunnel water inflow and fracture width correlation prediction method as claimed in any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements a tunnel water inflow and fracture width correlation prediction method according to any one of claims 1 to 7.
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