Stone content calculation method and system of accumulation body slope model and construction method of accumulation body slope model

Abstract

The invention discloses a method and system for calculating the stone content of an accumulation body slope model, and a construction method of the accumulation body slope model, and the method comprises the steps: firstly constructing an analog simulation model according to the size of the accumulation body slope model, and carrying out the grid division of the analog simulation model according to the manufacturing region of the accumulation body slope model; and then generating a stone content random field according to the spatial variability characterization parameters of the accumulation body slope model. Then, the stone content random field is mapped into an analog simulation grid model, and stone content values corresponding to different manufacturing areas are determined; then, soil-rock mixture samples in different manufacturing areas are manufactured according to the stone content values, and the complex space variability of accumulation body model material composition is depicted according to the difference of the stone content values. And finally, the soil-rock mixture samples are sequentially filled in a model box according to the positions of the manufacturing areas, an accumulation body slope model fully considering the complex spatial variation characteristics of the accumulation body is formed, and a foundation is provided for a rainfall instability test.

Description

Technical Field

[0001] The present invention relates to the technical field of testing materials by mechanical methods, and particularly relates to a method and system for calculating the stone content of a piled-up slope model, and a method for constructing a piled-up slope model. Background Art

[0002] Piled-up slopes are common geological structure types in mountainous engineering construction. They are extremely prone to instability under the action of rainfall, with the characteristics of high outbreak frequency and continuous great harm. In severe cases, they even cause huge losses of life and property. Therefore, in-depth research on the rainfall-induced instability mechanism of piled-up slopes is of great significance for disaster prevention and reduction in mountainous engineering.

[0003] Due to the influence of the genetic mechanism, the material composition of the piled-up body has complex spatial variability, that is, the material composition at a certain position is different from that at other positions, but there is also a certain correlation. This property has a significant impact on the stability and failure mode of the piled-up slope under the action of rainfall.

[0004] At present, the existing model test studies focus on homogeneous and isotropic piled-up bodies. For the complex spatial variability characteristics of the material composition of the piled-up body, there is still a lack of corresponding test means at present. Therefore, there is an urgent need for a test method for rainfall-induced instability of piled-up slopes that considers the complex spatial variability of the material composition. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technology, the present invention proposes a method and system for calculating the stone content of a piled-up slope model, and a method for constructing a piled-up slope model, which fully considers the complex spatial variability characteristics of the piled-up body. The specific technical solutions are as follows: In the first aspect, a method for calculating the stone content of a piled-up slope model is provided. In the first implementable manner of the first aspect, it includes: Construct a simulation model corresponding to the piled-up slope model, and perform grid division on the simulation model according to the production area of the piled-up slope model to obtain a corresponding simulation grid model; Obtain the spatial variability characterization parameters corresponding to the piled-up slope model, and generate a stone content random field according to the spatial variability characterization parameters; Map the stone content random field into the simulation grid model to obtain the stone content values of each grid area in the simulation grid model.

[0006] Combined with the first implementable manner of the first aspect, in the second implementable manner of the first aspect, constructing the simulation model corresponding to the piled-up slope model includes: Obtain the geometric shape of the piled-up slope model required for the slope rainfall-induced instability test, and construct the simulation model according to the geometric shape.

[0007] Combined with the first implementation manner of the first aspect, in the third implementation manner of the first aspect, obtaining the spatial variability characterization parameters corresponding to the accumulation body slope model includes: Determining the spatial variability characterization parameters according to the genetic type corresponding to the accumulation body slope model.

[0008] Combined with the first implementation manner of the first aspect, in the fourth implementation manner of the first aspect, generating a stone content random field according to the spatial variability characterization parameters, including using the following function to control the generation of the stone content random field: ; Wherein, 、 represents the relative distance between any two points in space, 、 respectively represent the maximum / minimum fluctuation ranges, represents the direction angle between the maximum fluctuation range and the minimum fluctuation range, represents the overall rotation angle of the coordinate system formed by the maximum fluctuation range and the minimum fluctuation range.

[0009] In the second aspect, a method for constructing an accumulation body slope model is provided. In the first implementation manner of the second aspect, it includes: Adopting the stone content calculation method as described in any one of the first to fourth implementation manners of the first aspect to obtain the stone content values of each grid area; Preparing corresponding mixed specimens for each sub-region in the accumulation body slope model according to the corresponding stone content values; Laying the corresponding mixed specimens layer by layer according to the positions of the sub-regions to form the accumulation body slope model.

[0010] Combined with the first implementation manner of the second aspect, in the second implementation manner of the second aspect, preparing the corresponding mixed specimens for the sub-region according to the stone content value includes: setting the water content of the mixed specimen according to the actual situation of the slope.

[0011] Combined with the first implementation manner of the second aspect, in the third implementation manner of the second aspect, laying the mixed specimens to form the accumulation body slope model includes: controlling the compaction degree of the mixed specimen during laying according to the actual situation of the slope.

[0012] Combined with the first implementation manner of the second aspect, in the fourth implementation manner of the second aspect, laying the mixed specimens to form the accumulation body slope model includes: Cutting off the redundant soil in the laid accumulation body slope model according to the slope angle corresponding to the geometric shape of the accumulation body slope model.

[0013] In a third aspect, a stone content calculation system for a stacked slope model is provided, including: A model construction module configured to construct a simulation model corresponding to the stacked slope model, and perform mesh division on the simulation model according to the production area of the stacked slope model to obtain a corresponding simulation mesh model; A random field generation module configured to obtain the spatial variability characterization parameters corresponding to the stacked slope model, and generate a stone content random field according to the spatial variability characterization parameters; A stone content calculation module configured to map the stone content random field into the simulation mesh model to obtain the stone content values of each grid area in the simulation mesh model.

[0014] Beneficial effects: By using the stone content calculation method and system for the stacked slope model of the present invention and the construction method of the stacked slope model, the stone content random field generated based on the spatial variability characterization parameters of the stacked slope model is mapped into a simulation mesh model of the same size as the stacked slope model, so as to determine the stone content values of different sub-regions in the stacked slope model, thereby establishing a connection between each sub-region of the stacked slope model and the soil-rock mixture with different stone contents, and approximately characterizing the complex spatial variability of the material composition of the stacked slope model through the difference in stone content. The stacked slope model made in this way fully considers the complex spatial variation characteristics of the stacked slope and provides a basis for the rainfall instability test method of the stacked slope. Description of the Drawings

[0015] In order to more clearly illustrate the specific embodiments of the present invention, the drawings required for the specific embodiments will be briefly introduced below. In all the drawings, the components or parts do not necessarily draw according to the actual ratio.

[0016] Figure 1 It is a flowchart of the stone content calculation method for the stacked slope model provided by an embodiment of the present invention; Figure 2 It is a flowchart of the construction method for the stacked slope model provided by an embodiment of the present invention; Figure 3 It is a system block diagram of the stone content calculation system for the stacked slope model provided by an embodiment of the present invention. Detailed Embodiments

[0017] The embodiments of the technical solutions of the present invention will be described in detail below with reference to the drawings. The following embodiments are only used to illustrate the technical solutions of the present invention more clearly, so they are only examples and cannot be used to limit the protection scope of the present invention.

[0018] Such as Figure 1Flowchart of the calculation method for the stone content of the accumulation body slope model shown, the calculation method comprising: Step 1: Construct a simulation model corresponding to the accumulation body slope model, and perform mesh division on the simulation model according to the production area of the accumulation body slope model to obtain a corresponding simulation mesh model; Step 2: Obtain the spatial variability characterization parameters corresponding to the accumulation body slope model, and generate a stone content random field according to the spatial variability characterization parameters; Step 3: Map the stone content random field into the simulation mesh model to obtain the stone content values of each grid area in the simulation mesh model.

[0019] Specifically, first, in a simulation software, such as FLAC3D numerical software, a simulation model can be constructed according to the size of the accumulation body slope model required for the rainfall-induced instability test of the accumulation body slope, and the simulation model can be meshed according to the production area of the accumulation body slope model to determine the grids corresponding to different production areas. Then, according to the spatial variability characterization parameters corresponding to the accumulation body slope model, a stone content random field adapted to the size of the accumulation body slope model can be generated using stochastic theory. Finally, the generated stone content random field can be mapped into the simulation mesh model to determine the stone content values corresponding to different grid areas in the simulation mesh model, that is, the stone content values corresponding to different production areas in the accumulation body slope model, providing data support for the subsequent production of an accumulation body slope model that fully considers the complex spatial variability characteristics of the accumulation body.

[0020] When fabricating the accumulation body slope model, the soil-rock mixture specimens for different production areas of the accumulation body slope model can be fabricated according to the calculated stone content values, and the complex spatial variability of the material composition of the accumulation body model can be approximately characterized by the difference in stone content. The fabricated soil-rock mixture specimens can be filled in the model box in sequence according to the positions of the production areas, and thus an accumulation body slope model that fully considers the complex spatial variability characteristics of the accumulation body can be fabricated, providing a basis for the rainfall-induced instability test of the accumulation body slope.

[0021] In this embodiment, optionally, constructing the simulation model corresponding to the accumulation body slope model includes: Obtain the geometric shape of the accumulation body slope model required for the rainfall-induced instability test of the slope, and construct the simulation model according to the geometric shape.

[0022] Specifically, when constructing the simulation model, it is first necessary to determine the slope rainfall instability conditions with spatial variability characteristics for the material composition simulated in this experiment, and determine the geometric shape of the accumulation body slope model under this condition, including the inclination angle of the base-cover interface and the cutting slope gradient of the accumulation body slope model. Then, according to the geometric shape, a simulation model consistent with the accumulation body slope model is constructed through simulation software, so as to subsequently convert the random stone content field generated according to the random theory into the spatial variability distribution of the accumulation body material composition of the accumulation body slope model.

[0023] In this embodiment, optionally, obtaining the spatial variability characterization parameters corresponding to the accumulation body slope model includes: determining the spatial variability characterization parameters according to the genetic type corresponding to the accumulation body slope model.

[0024] Specifically, for accumulation bodies with different genetic mechanisms, there are obvious differences in the spatial distribution of their material composition. For example, in the residual accumulation body, the stone content gradually increases along the depth of the granular material, while the landslide accumulation body shows an inverse grading structure. Therefore, there must be differences in the stability performance and failure modes of accumulation bodies with different genetic types under rainfall conditions. For this reason, when generating the random stone content field, the spatial variability characterization parameters can be determined according to the genetic type of the accumulation body slope simulated in this experiment, so as to determine the stone content values in different production areas of the accumulation body slope models formed by different genetic mechanisms, providing data support for the production of accumulation body slope models with different genetic mechanisms.

[0025] The spatial variability characterization parameters include the maximum / minimum fluctuation range, the included angle between the maximum / minimum fluctuation directions, and the overall rotation angle of the coordinate system formed by the maximum / minimum fluctuation range. Among them, the maximum / minimum fluctuation range characterizes the scale of spatial variability, the included angle between the maximum / minimum fluctuation directions characterizes the anisotropic characteristics of spatial variability, and the overall rotation angle of the coordinate system formed by the maximum / minimum fluctuation range defines the orientation of the coordinate system formed by the maximum / minimum fluctuation directions relative to the global coordinates.

[0026] According to the actual genetic type of the accumulation body slope, survey lines with a length of 5 - 10 m can be arranged along the horizontal direction, vertical depth direction, parallel to the rock layer deposition direction, and perpendicular to the rock layer deposition direction. On each survey line, on-site screening tests are carried out every 0.5 m, and geostatistical methods are used to determine the maximum / minimum fluctuation range in different directions, as well as the included angle between the maximum / minimum fluctuation ranges and the overall rotation angle of the coordinate system formed by the maximum / minimum fluctuation range.

[0027] Since the actual slope scale is much larger than the model test scale, when applying the above spatial variability parameters to the model test, scaling can be carried out according to the similarity ratio principle. The corresponding spatial variability characterization parameters in the model test (i.e., the scaled maximum / minimum fluctuation range, included angle, and rotation angle) are obtained through scaling.

[0028] In this embodiment, optionally, generating a stone content random field according to the spatial variability characterization parameter includes using the following function to control the generation of the stone content random field: ; Wherein, 、 represent the relative distance between any two points in space, 、 respectively represent the maximum / minimum fluctuation range, represents the direction angle between the maximum fluctuation range and the minimum fluctuation range, represents the overall rotation angle of the coordinate system formed by the maximum fluctuation range and the minimum fluctuation range.

[0029] Specifically, the overall rotation angle and the direction angle belong to the direction comprehensive variation index, which can accurately and quantitatively evaluate the structure and direction of the accumulation body. Among them, the overall rotation angle can be coordinated with the dip angle of the base-cover interface of the accumulation body slope. And through the direction angle the direction of the maximum fluctuation range can be controlled. Combining the overall rotation angle and the direction angle can comprehensively describe various different types of spatial variability of the accumulation body, and realize the parametric characterization of the spatial variability of the material composition of accumulation bodies of different genetic types.

[0030] Such as Figure 2 the flowchart of the construction method of the accumulation body slope model shown, the construction method includes: Step S1, using the above-mentioned stone content calculation method to obtain the stone content values of each of the grid regions; Step S2, preparing corresponding mixed specimens for each sub-region in the accumulation body slope model according to the corresponding stone content values; Step S3, layer-by-layer filling the corresponding mixed specimens into the accumulation body slope model according to the positions of the sub-regions.

[0031] Specifically, first, according to the slope rainfall instability conditions simulated in this test and the genesis types of the slope accumulation body, the stone content values corresponding to different grid regions in the simulation grid model can be obtained by using the above calculation method, that is, the stone content values corresponding to different production sub-regions of the accumulation body slope model. Then, the soil-rock mixture specimens of different sub-regions can be made respectively according to the calculated stone content values. Finally, the soil-rock mixture specimens of different sub-regions are filled into the model box in sequence from bottom to top according to the positions of each production sub-region, and finally an accumulation body slope model that fully considers the complex spatial variability characteristics of the accumulation body is formed, providing a basis for the rainfall instability test of the accumulation body slope.

[0032] In this embodiment, the soil-rock mixture specimen can be prepared by using sandy soil with a particle size less than 2 mm and gravelly soil with particle sizes of 2 - 5 mm, 5 - 10 mm, 10 - 20 mm, and 20 - 30 mm respectively, and the proportion of the gravelly soil particle groups is 4:3:2:1. In this embodiment, the stone content refers to the proportion of soil particles with a particle size greater than 2 mm.

[0033] In this embodiment, optionally, preparing the mixture specimen corresponding to the sub-region according to the stone content value includes: setting the water content of the mixture specimen according to the actual situation of the slope.

[0034] Specifically, the water content of the slope simulated in the test can be obtained through on-site measurement, and when making the mixture specimen, the water content of the mixture specimen can be set according to the actual situation of the slope simulated in the test.

[0035] In this embodiment, optionally, filling the mixture specimen into the accumulation body slope model includes: controlling the compaction degree of the mixture specimen during filling according to the actual situation of the slope.

[0036] Specifically, the compaction degree of different regions of the slope simulated in the test can be obtained through on-site measurement, and when filling the mixture specimen, the compaction degree of the filled mixture specimen can be controlled according to the actual situation of the slope simulated in the test, so that the made accumulation body slope model is more in line with the actual situation.

[0037] In this embodiment, optionally, filling the mixture specimen into the accumulation body slope model includes: Cutting off the redundant soil in the filled accumulation body slope model according to the slope angle corresponding to the geometric shape of the accumulation body slope model.

[0038] Specifically, after filling all the mixture specimens, the redundant soil in the filled accumulation body slope model can be cut off according to the slope angle corresponding to the geometric shape of the accumulation body slope model, so as to form an accumulation body slope model considering the spatial variability of the material composition.

[0039] Such as Figure 3System block diagram of the stone content calculation system for the shown accumulation body slope model. The calculation system includes: A model construction module configured to construct a simulation model corresponding to the accumulation body slope model and perform mesh division on the simulation model according to the production area of the accumulation body slope model to obtain a corresponding simulation mesh model; A random field generation module configured to obtain the spatial variability characterization parameters corresponding to the accumulation body slope model and generate a stone content random field according to the spatial variability characterization parameters; A stone content calculation module configured to map the stone content random field into the simulation mesh model to obtain the stone content values of each grid area in the simulation mesh model.

[0040] Specifically, the calculation system is composed of a model construction module, a random field generation module, and a stone content calculation module. Among them, the model construction module can use simulation software to construct a simulation model according to the size of the accumulation body slope model required for the rainfall instability test of the accumulation body slope, and perform mesh division on the simulation model according to the production area of the accumulation body slope model to determine the grids corresponding to different production areas. The random field generation module can generate a stone content random field adapted to the size of the accumulation body slope model according to the spatial variability characterization parameters corresponding to the accumulation body slope model using random theory. The stone content calculation module can map the generated stone content random field into the simulation mesh model to determine the stone content values corresponding to different production areas in the accumulation body slope model, providing data support for the subsequent production of an accumulation body slope model that fully considers the complex spatial variation characteristics of the accumulation body.

[0041] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A method for calculating the stone content of a piled slope model, characterized in that, Including: Construct a simulation model corresponding to the accumulation body slope model, and perform mesh division on the simulation model according to the production area of the accumulation body slope model to obtain a corresponding simulation mesh model; Obtain the spatial variability characterization parameters corresponding to the accumulation body slope model, and generate a stone content random field according to the spatial variability characterization parameters. The following function is used to control the generation of the stone content random field: ； Among them, , represents the relative distance between any two points in space, , respectively represent the maximum / minimum fluctuation range, represents the direction angle between the maximum fluctuation range and the minimum fluctuation range, represents the overall rotation angle of the coordinate system formed by the maximum fluctuation range and the minimum fluctuation range; Map the stone content random field into the simulation mesh model to obtain the stone content values of each grid area in the simulation mesh model.

2. The calculation method of the stone content of the accumulation body slope model according to claim 1, characterized in that Construct a simulation model corresponding to the accumulation body slope model, including: Obtain the geometric shape of the accumulation body slope model required for the slope rainfall instability test, and construct the simulation model according to the geometric shape.

3. The method for calculating the stone content of the accumulation body slope model according to claim 1, wherein Obtain the spatial variability characterization parameters corresponding to the accumulation body slope model, including: Determine the spatial variability characterization parameters according to the genetic type corresponding to the accumulation body slope model.

4. A method for constructing a piled slope model, characterized in that, Including: Adopt the stone content calculation method described in any one of claims 1-3 to obtain the stone content values of each of the grid areas; Prepare mixed specimens corresponding to each sub-region in the accumulation body slope model according to the corresponding stone content values; Layer by layer fill the corresponding mixed specimens into the accumulation body slope model according to the positions of the sub-regions.

5. The construction method of the accumulation body slope model according to claim 4, wherein Prepare the mixed specimens corresponding to the sub-regions according to the stone content values, including: setting the water content of the mixed specimens according to the actual situation of the slope.

6. The construction method of the accumulation body slope model according to claim 4, wherein, Fill the mixed specimens into the accumulation body slope model, including: controlling the compaction degree of the mixed specimens during filling according to the actual situation of the slope.

7. The method for constructing the accumulation body slope model according to claim 4, wherein Fill the mixed specimens into the accumulation body slope model, including: Cut off the redundant soil in the filled accumulation body slope model according to the slope angle corresponding to the geometric shape of the accumulation body slope model.

8. A calculation system for the stone content of a stacked slope model, characterized in that, Including: A model construction module configured to construct a simulation model corresponding to the accumulation body slope model, and perform mesh division on the simulation model according to the production area of the accumulation body slope model to obtain a corresponding simulation mesh model; A random field generation module configured to obtain the spatial variability characterization parameters corresponding to the accumulation body slope model, and generate a stone content random field according to the spatial variability characterization parameters. The following function is used to control the generation of the stone content random field: ； Among them, , represent the relative distance between any two points in space, , represent the maximum / minimum fluctuation ranges respectively, represents the direction angle between the maximum fluctuation range and the minimum fluctuation range, represents the overall rotation angle of the coordinate system formed by the maximum fluctuation range and the minimum fluctuation range; A stone content calculation module configured to map the stone content random field into the simulation mesh model to obtain the stone content values of each grid area in the simulation mesh model.

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