Spatiotemporal stability analysis method for landslides considering in-situ creep microstructure of slip zone

Abstract

This invention provides a method for analyzing the spatiotemporal stability of landslides considering the microscopic characteristics of in-situ creep of the slip zone. The method involves identifying the landslide geological conditions, conducting in-situ direct shear creep tests, microscopic scanning tests, and numerical tests to reveal the influence of microstructural changes on the in-situ shear creep mechanical properties. It defines and quantifies microstructural factors, constructs an evolution model of the slip zone's microstructure and mechanical properties, and then establishes a constitutive model of in-situ shear creep of the slip zone incorporating microstructural factors. Based on landslide monitoring data, the time history of the landslide displacement field is obtained. A dynamic spatial weight matrix is ​​introduced and corrected using slip zone and slip body constitutive models to establish a spatiotemporal evolution model of the landslide with the dynamic spatial weight matrix as its core. A displacement field prediction platform based on a displacement field database and the spatiotemporal evolution model is built to predict the displacement field, thereby enabling real-time searching of the slip surface. Combined with mechanical calculations, this achieves stability analysis of the landslide at both spatiotemporal scales.

Description

Technical Field

[0001] This invention relates to the field of geological disaster prediction technology, and in particular to a method for analyzing the spatiotemporal stability of landslides that takes into account the microscopic characteristics of in-situ creep of the slip zone. Background Technology

[0002] For large landslides, the slip zone plays a controlling role in landslide stability, and it is often in a creep state before landslide instability. Slip zone creep is the result of continuous adjustment of landslide stress, accompanied by continuous changes in the microstructure. Revealing the evolution of the microstructure and mechanical properties during slip zone shearing will help to elucidate the landslide deformation evolution mechanism and serve the stability assessment of large landslides. Previous studies have made significant progress in single-medium slip zone and soil-rock interaction, slip zone microstructure and its connection with macroscopic mechanics, slip zone direct shear creep characteristics and creep constitutive models, and temporal or spatial single-scale landslide stability assessment. However, these studies still have the following shortcomings:

[0003] (1) The effect of the microstructural evolution of the shearing process on mechanical properties has not been fully explored.

[0004] (2) The commonly used indoor creep test method fails to fully guarantee the in-situ properties of the slip belt, which means that the test results may not truly reflect the mechanical properties.

[0005] (3) Methods that can realize the spatiotemporal dual-scale stability evaluation of landslides that take into account the structural-mechanical evolution characteristics of the slip zone are relatively scarce. Summary of the Invention

[0006] In view of this, the present invention provides a method for analyzing the spatiotemporal stability of landslides that considers the microscopic characteristics of in-situ creep of the slip zone. This method can effectively improve the accuracy of landslide disaster prediction and forecasting.

[0007] This invention provides a method for analyzing the spatiotemporal stability of landslides considering the microscopic characteristics of in-situ creep of the slip zone, comprising the following steps:

[0008] S1: Based on the identified geological background and engineering geological conditions of the landslide area, conduct in-situ direct shear creep tests on the slip zone to determine the in-situ mechanical parameter values ​​of the slip zone;

[0009] S2: Based on the in-situ mechanical parameter values ​​of the sliding belt, conduct microscopic scanning tests and numerical tests to obtain the microstructural characteristics of the sliding belt before and after the in-situ direct shear creep test, reveal the effect of changes in the microstructural characteristics of the sliding belt on the shear creep mechanical properties, quantify the microstructural characteristics, define the microstructural factor, and construct an evolution model of the microstructural-mechanical properties of the sliding belt during the shear process.

[0010] S3: Combine the in-situ shear creep constitutive model of the sliding belt with the evolution model of microstructure-mechanical properties constructed in step S2 to establish an in-situ shear creep constitutive model of the sliding belt that incorporates microstructure factors.

[0011] S4: By monitoring data of landslide surface displacement and deep landslide displacement, the time history of landslide displacement field is obtained, revealing the law of landslide displacement field change with time. Combined with the in-situ shear creep constitutive model of slip zone and the shear creep constitutive model of slip body with the introduction of microstructure factor, the time history curve of landslide displacement field considering the in-situ shear creep constitutive model of slip zone and the shear creep constitutive model of slip body is obtained.

[0012] S5: Introduce a spatial weight matrix, and correct the spatial weight matrix according to the landslide displacement field time history curve obtained in step S4 to obtain a dynamic spatial weight matrix. Establish a spatiotemporal evolution model of landslide displacement field with the dynamic spatial weight matrix of landslide as the core.

[0013] S6: Build a displacement field prediction platform based on a displacement field database and a landslide displacement field spatiotemporal evolution model as the core, carry out displacement field prediction, and then search for the sliding surface in real time. Combine mechanical calculations to realize the stability analysis of landslides under spatiotemporal dual scales.

[0014] Furthermore, in step S1, the specific process is as follows:

[0015] S1-1: Investigate the geological background and engineering geological conditions of the landslide area;

[0016] S1-2: Conduct in-situ rapid direct shear tests and in-situ direct shear creep tests on the landslide slip zone to determine the mechanical parameters of the slip zone, i.e., the long-term strength τ' of the slip zone. ∞ Ultimate long-term strength τ ∞ The shear stress τ along the slip band, the shear strain γ along the slip band, the instantaneous shear modulus G1, the long-term shear modulus G2, the viscosity coefficient η1 of the initial creep stage and the viscosity coefficient η2 of the stable creep stage, and the shear strength parameters of the slip band: internal friction angle. And cohesion C.

[0017] Furthermore, in step S2, the specific process is as follows:

[0018] S2-1: Conduct a microscopic scanning test on the sliding belt to obtain the microstructural characteristics of the sliding belt before and after the in-situ direct shear creep test: unit cell characteristics, microstructure characteristics, surface morphology, porosity, and particle connection medium characteristics. Based on the microstructural characteristics, reveal the effect of microstructural changes on shear creep mechanical properties, quantify the microstructural characteristics, and define the microstructural factors: microstructure parameter z, surface roughness undulation d, porosity ratio n, and particle connection medium parameter c.

[0019] S2-2: Based on the above microstructure characteristics and microstructure factors, and combined with PFC3D numerical experiments to deduce the particle fracture, grinding, shearing, overturning and transport processes, an evolution model of microstructure-mechanical properties of the sliding belt shearing process is established.

[0020] Furthermore, in step S3, the specific process is as follows:

[0021] S3-1: Establish an in-situ shear creep constitutive model for the sliding belt;

[0022] The in-situ shear creep constitutive model of the sliding belt (Burgers creep constitutive model) can be simplified to Equation 3-2:

[0023]

[0024] S3-2: Introducing the microstructure factor into the constitutive model of in-situ shear creep of the slip zone;

[0025] S3-2-1: Determine the functional form of the relationship between the parameters G1, G2, η1, η2, τ of the in-situ shear creep constitutive model of the slip zone and the mesostructure factor, perform regression analysis, and establish the empirical relationship between the parameters of the in-situ shear creep constitutive model of the slip zone and the mesostructure factor, i.e., the system of equations:

[0026]

[0027] Where z is the microstructure parameter; d is the surface roughness; n is the porosity ratio; and c is the particle bonding medium parameter.

[0028] Combining the creep equation shown in formula (3-2) with the above equation set (3-3), we obtain the in-situ shear creep constitutive model of the slip zone incorporating the microstructure factor (3-4):

[0029]

[0030] Where δ is the reduction factor and t is time.

[0031] Meanwhile, by conducting shear creep tests on the sliding body, the constitutive model δ(t) of the sliding body shear creep can be obtained, i.e., formula (3-5):

[0032]

[0033] Where δ is the reduction factor, τ is the shear stress, G1 and G2 are the shear moduli of Maxwell and Kelvin bodies respectively, η1 and η2 are the viscosity coefficients of Maxwell and Kelvin bodies respectively, and t is time.

[0034] Furthermore, in step S4, the specific process for obtaining the landslide displacement field time history curve considering the in-situ shear creep constitutive model of the slip zone and the shear creep constitutive model of the slip body is as follows:

[0035] S4-1: Obtain surface and deep displacement monitoring data of the landslide;

[0036] S4-2: Then, the time history curve of the landslide displacement field is obtained:

[0037] Y i =S(t) j 4-1

[0038] Combining the established in-situ shear creep constitutive models of the slip zone and the slip body with microstructure factors, the time history curves of the landslide displacement field considering the in-situ shear creep constitutive models of the slip zone and the slip body are obtained:

[0039] Y i =S i [γ(t i ),δ(t i ),t j ] 4-2

[0040] In the formula, i is the monitoring point number; Y i S(t) represents the displacement of monitoring point i; j ) represents the displacement-time mapping relationship; S i For landslide strain; γ(t) i ) represents the constitutive model of shear creep in a sliding belt; δ(t) i ) represents the shear creep constitutive model of a sliding body; t i The time consumed by creep; t j For monitoring time.

[0041] Furthermore, in step S5, the specific process is as follows:

[0042] S5-1: Introduce the spatial weight matrix shown below to express the influence of the displacement at a certain monitoring point on the displacement of adjacent monitoring points:

[0043]

[0044] Among them, Y i and Y j Let |Y| represent the displacement of any two monitoring points i and j. i -Y j | represents the displacement distance between the two monitoring points, when |Y i -Y j The smaller the value of |, the closer the displacement distance between the two monitoring points i and j is, and the more likely it is to cause... The larger the value, the larger the spatial weight coefficient between monitoring points i and j, and the stronger the spatial correlation between the two monitoring points; the specific process of establishing the spatial weight matrix is ​​as follows:

[0045] S5-1-1: Based on the landslide displacement field time history curve, the density-based clustering algorithm (DBSCAN) is used to perform cluster analysis of monitoring points. The sample set with the highest density is derived from the density reachability relationship, which is the cluster sample of displacement data of each monitoring point, thereby quantitatively analyzing the spatial relationship of displacement field between each monitoring point of the landslide.

[0046] S5-1-2: The spatial weight matrix of the landslide displacement field is calculated based on the spatial point clustering results, which effectively expresses the spatial relationship of monitoring points;

[0047] S5-2: Using the established in-situ shear creep constitutive models of the slip zone and the slip body with microstructure factors, the spatial weight matrix is ​​modified. The landslide displacement field time history curve formula is substituted into the spatial weight matrix W to obtain the formula for the landslide dynamic spatial weight matrix:

[0048]

[0049] S5-3: Based on formula 5-2, establish a spatiotemporal evolution model of landslide displacement field.

[0050] Furthermore, in step S6, the specific process is as follows:

[0051] S6-1: Establish a landslide displacement field database based on landslide displacement field monitoring data;

[0052] S6-2: Based on the landslide displacement field database and with the spatiotemporal evolution model as the core, a displacement field prediction platform is built;

[0053] S6-3: Predict displacement field changes through a displacement field prediction platform, and search for landslide sliding surfaces in real time based on the predicted displacement field;

[0054] S6-4: Based on the landslide sliding surface found, the stability analysis of the landslide under both temporal and spatial scales is carried out by combining mechanical calculations.

[0055] Compared with the prior art, the beneficial effects of this invention are:

[0056] (1) The present invention adopts the method of using in-situ direct shear creep test and microscopic scanning test as the main methods, supplemented by indoor test and numerical test, and in-situ test combined with indoor test and numerical test, so that the evaluation results are true and reliable.

[0057] (2) This invention realizes the stability evaluation of landslides at both time and space scales, breaks through the technical bottleneck of time and space stability evaluation of large landslides, and can be promoted to serve the effective prevention and control of large landslides. Attached Figure Description

[0058] Figure 1 This is a flowchart of the landslide spatiotemporal stability analysis method that considers the microscopic characteristics of in-situ creep of the slip zone, as described in this invention.

[0059] Figure 2 It is a spatiotemporal evolution model of landslide displacement field.

[0060] Figure 3 This is a schematic diagram of an empirical graphical method for determining the pre-consolidation pressure value of the sliding belt. Detailed Implementation

[0061] A method for analyzing the spatiotemporal stability of landslides considering the microscopic characteristics of in-situ creep of the slip zone includes the following steps:

[0062] S1. Investigate the geological background and engineering geological conditions of the landslide area, conduct in-situ direct shear creep tests on the slip zone, and determine the in-situ mechanical parameter values ​​of the slip zone;

[0063] S1-1, investigate the geological background and engineering geological conditions of the landslide area, specifically including topography, geochemistry, geophysics, surface geological processes, geological structure, hydrogeological conditions, landslide geometry, landslide soil and rock types, hydrological characteristics and basic mechanical properties;

[0064] S1-2, in-situ rapid direct shear tests and in-situ direct shear creep tests were conducted on the landslide slip zone to determine the mechanical parameters of the slip zone, namely the long-term strength τ' of the slip zone. ∞ Ultimate long-term strength τ ∞ The shear stress τ along the slip band, the shear strain γ along the slip band, the instantaneous shear modulus G1, the long-term shear modulus G2, the viscosity coefficient η1 of the initial creep stage and the viscosity coefficient η2 of the stable creep stage, and the shear strength parameters of the slip band: internal friction angle. And cohesion C, to prepare for the subsequent construction of the in-situ shear creep constitutive model of the sliding belt;

[0065] The in-situ direct shear creep test procedure is as follows:

[0066] S1-2-1, Determine the normal stress σ value required to carry out the in-situ direct shear creep test. Specifically, select the pre-consolidation pressure of the slip zone as the normal stress σ value. The method of obtaining the value is to first use a consolidation test, and the consolidation time lasts for one week to ensure that the soil sample is completely consolidated.

[0067] The calculation method for the pre-consolidation pressure of the sliding belt is as follows: (The method is described in the original text.) Figure 3The empirical graphical method shown is used to determine the preconsolidation pressure of the slip zone. Find the point m with the minimum radius of curvature on the e-log P curve. Draw a horizontal line A through point m, the tangent B and the bisector C of ∠AMB. C intersects the extension of the straight line segment below the curve at point O. The pressure value corresponding to point O is the preconsolidation pressure of the undisturbed soil sample.

[0068] S1-2-2, Determine the shear stress gradient τ required for the in-situ direct shear creep test. Specifically, obtain the shear stress-shear displacement curve through an in-situ rapid direct shear test; the peak value of the curve represents the shear strength τ. s , with τ s Plot a curve showing the relationship between the two, with σ as the ordinate and σ as the abscissa. The angle of inclination of the tangent to the curve is the angle of internal friction. The intercept of the tangent line on the curve on the ordinate is the cohesion C, which is determined by Coulomb's law. The shear strength τ can be obtained f According to τ f Determine the shear stress gradient τ required for in-situ direct shear creep testing;

[0069] S1-2-3, Conduct in-situ direct shear creep tests on the sliding belt. The specific method is as follows: using τ... f The value is the peak shear stress. The shear stress is applied in stages according to a gradient, and an in-situ direct shear creep test is conducted on the sliding belt. For decaying creep, the test is generally continued until deformation stops, while for non-decaying creep, the test is continued until the deformation reaches a stable creep state.

[0070] S1-2-4, the in-situ mechanical parameters of the sliding belt are determined through in-situ direct shear creep tests. The specific method is as follows:

[0071] (1) Record the creep deformation γ-time t data of the in-situ direct shear creep test of the sliding belt, draw the superposition curve of shear strain under the same shear duration under each stress, and draw the isochronous cluster of shear stress τ and shear strain γ.

[0072] (2) Calculate the shear rate Plot the flow curve with shear strain γ as the ordinate and shear stress τ as the abscissa; where τ is the shear stress, γ is the shear strain, and t is the time.

[0073] (3) Calculate the ultimate long-term strength τ of the slip band ∞i

[0074] In the isochronous line cluster of shear stress τ and shear strain γ obtained in step (1), those with obvious inflection points are directly selected, while those with indistinct inflection points are selected using interpolation. Four pairs of corresponding normal stresses σ are selected. i The ultimate long-term strength τ of the slip band ∞i Using Coulomb's law Regression analysis can yield the ultimate long-term strength cohesion C of the sliding belt. ∞ and internal friction angle

[0075] (4) Calculate the shear modulus G of the sliding belt

[0076] The formula for calculating instantaneous shear modulus is: The formula for calculating long-term shear modulus is:

[0077] In the formula, τ i γ is the instantaneous shear stress at the start of the creep test; i τ is the corresponding shear line strain. j γ represents the shear stress at a certain time after the creep test has stabilized; j This represents the corresponding shear line strain.

[0078] After calculating the shear modulus G, plot the Gt relationship curve with the shear modulus G of the sliding belt as the ordinate;

[0079] (5) Calculate the viscosity coefficient η of the sliding belt

[0080] Select initial times t1 and t2 for the creep test, calculate the viscosity coefficient η1 of the initial creep stage, and calculate the shear strain rate based on the initial time period t1-t2 after each loading stage of the creep test. Then calculate

[0081] In the formula, The shear strain at t1 and t2 after each loading stage in the creep test;

[0082] γ1 is the initial shear strain rate of the creep segment;

[0083] τ i This represents shear stress, measured in kPa.

[0084] Select the later time periods t3 and t4 of the creep test, calculate the viscosity coefficient η2 of the stable creep stage, and calculate the shear strain rate based on the later time period t3-t4 after each loading stage of the creep test. Then calculate

[0085] In the formula, The shear strain at t1 and t2 after each loading stage in the creep test;

[0086] γ2 is the shear strain rate of the steady creep segment;

[0087] τ i This represents shear stress, measured in kPa.

[0088] S2. Based on the in-situ mechanical parameter values ​​of the sliding belt, conduct microscopic scanning tests and numerical tests to obtain the microstructural characteristics of the sliding belt before and after the in-situ direct shear creep test, reveal the role of microstructural changes on shear creep mechanical properties, define and quantify the microstructural factor, and construct an evolution model of microstructural-mechanical properties during the sliding belt shear process.

[0089] S2-1, a microscopic scanning test was conducted on the sliding belt to obtain the structural characteristics of the sliding belt before and after the in-situ direct shear creep test (unit characteristics, microstructure characteristics, surface morphology, porosity, and particle connection medium characteristics). Based on the microstructure characteristics, the effect of changes in microstructure characteristics on shear creep mechanical properties was revealed. The microstructure characteristics were quantified, and the microstructure factors were defined as: microstructure parameter z, surface roughness undulation d, porosity ratio n, and particle connection medium parameter c.

[0090] S2-1-1 utilizes scanning electron microscopy (SEM) images and image processing software (Image-Pro Plus, IPP) to perform quantitative analysis of the microstructure of the sliding band, including image segmentation, image morphological processing, size measurement and counting of sliding band units and pores, and three-dimensional simulation of the sliding band microstructure.

[0091] S2-1-2, Since the edges of the slip zone soil unit and the pores are very complex and difficult to distinguish, the visual segmentation method in digital image processing technology can be used to determine the threshold to ensure the accuracy of image analysis.

[0092] S2-1-3, Regarding the characteristics of slip zone units, the watershed segmentation method of IPP morphological processing can be selected to identify and separate the boundaries of slip zone soil units in SEM images, thereby achieving accurate measurement of slip zone soil units;

[0093] S2-1-4 Regarding the porosity of the sliding belt, IPP image technology can be used to quickly measure the size and number of sliding belt units and pores, and automatically classify and count them based on the measurement results; at the same time, spatial transformation and three-dimensional digital simulation operations can be performed on SEM images to realistically display the microscopic pore structure characteristics of the sliding belt.

[0094] S2-1-5 Regarding the characteristics of the particle bonding medium, energy dispersive X-ray spectroscopy (EDX) can be used in conjunction with SEM images to determine the chemical composition of the cementitious material between particles, which can indirectly reflect the characteristics of the particle bonding medium in the sliding belt.

[0095] S2-2, constructing an evolution model of the microstructure and mechanical properties of the sliding belt shear process;

[0096] S2-2-1, combined with the particle flow analysis program (PFC3D) numerical experiment, the particle fracture, grinding, shearing, overturning and transport process is deduced, and the evolution model of the microstructure-mechanical properties of the sliding belt shear process is established.

[0097] S3 combines the in-situ shear creep constitutive model of the sliding belt with the evolution model of microstructure-mechanical properties to establish an in-situ shear creep constitutive model of the sliding belt that incorporates microstructure factors.

[0098] S3-1, Establish the in-situ shear creep constitutive model of the sliding belt;

[0099] When the shear force is small, the creep curve of the slip band exhibits instantaneous and decelerating deformation stages, approaching a certain asymptote in a negative exponential manner. As the shear force increases, the curve will show a uniform creep stage and quickly enter an accelerated stage. In rheology, the instantaneous and decelerating deformation process of a sample can be simulated by connecting a Kelvin body and an elastic element in series. By connecting a viscous element in series, the constant-rate creep of the curve can be simulated. A combination of an elastic element and a viscous element is called a Maxwell body, which constitutes the Burgers creep constitutive model, as shown in Equation 3-1.

[0100]

[0101] In the formula: γ is the shear strain, τ is the shear stress, G1 and G2 are the shear moduli of Maxwell and Kelvin bodies respectively, η1 and η2 are the viscosity coefficients of Maxwell and Kelvin bodies respectively, γ1 and γ2 are the shear strains of Maxwell and Kelvin bodies respectively, and τ1 and τ2 are the shear stresses of Maxwell and Kelvin bodies respectively.

[0102] When the shear stress τ is constant, the in-situ shear creep constitutive model of the sliding belt (Burgers creep constitutive model) can be simplified to Equation 3-2:

[0103]

[0104] In the formula: δ is the reduction coefficient. For decaying creep, since the deformation is mainly instantaneous, the time has little effect on the deformation, so δ = 0 is taken; for non-decaying creep with an accelerated creep stage, the deformation increases significantly with time, so δ = 1 is taken.

[0105] S3-2, introduces the microstructure factor into the constitutive model of in-situ shear creep of the slip zone;

[0106] S3-2-1, determine the functional form of the relationship between the parameters G1, G2, η1, η2, τ of the in-situ shear creep constitutive model of the slip zone and the mesostructure factor, perform regression analysis, and establish the empirical relationship between the model parameters and the mesostructure factor, i.e., the system of equations (Formula 3-3):

[0107]

[0108] Where z is the microstructure parameter of the sliding belt; d is the surface roughness undulation; n is the porosity ratio; c is the particle bonding medium parameter; and f1, f2, f3, f4, and f5 are empirical relationships between the model parameters and the microstructure factor of the sliding belt.

[0109] By combining the creep equation (Equation 3-2) with the system of equations (Equation 3-3), we obtain the in-situ shear creep constitutive model of the slip zone that incorporates a microstructure factor (Equation 3-4):

[0110]

[0111] Meanwhile, by conducting shear creep tests on the sliding body, the constitutive model δ(t) of the sliding body shear creep can be obtained, i.e., formula (3-5):

[0112]

[0113] In the formula: δ is the reduction factor, τ is the shear stress, G1 and G2 are the shear moduli of Maxwell and Kelvin bodies respectively, η1 and η2 are the viscosity coefficients of Maxwell and Kelvin bodies respectively, and t is time.

[0114] S4. By using monitoring data of landslide surface displacement and deep landslide displacement, the time history of the landslide displacement field is obtained, revealing the law of landslide displacement field variation over time. Combined with the established in-situ shear creep constitutive models of the slip zone and the slip body incorporating mesoscopic structure factors, the time history curves of the landslide displacement field considering these models are derived. The specific steps are as follows:

[0115] S4-1, to obtain monitoring data on landslide surface displacement and deep landslide displacement. Global Positioning System (GPS) deformation monitoring piles were used to obtain landslide surface displacement data; micro-electromechanical systems (MEMS) monitoring technology was used to obtain landslide deep displacement data.

[0116] S4-2, monitoring points include the landslide surface and deep landslide areas. The monitoring data mainly reflects the time displacement curve, i.e., the Yt curve. The displacement of the landslide surface and the displacement of the deep landslide both refer to Y. Using regression analysis, the specific functional relationship of the Yt curve can be obtained, that is, the time history curve of the landslide displacement field can be obtained (Formula 4-1):

[0117] Y i =S(t) j 4-1

[0118] In the formula, i is the monitoring point number; Y i t represents the displacement of monitoring point i; jFor monitoring time; S(t) j () represents the displacement-time mapping relationship.

[0119] Based on Equation 4-1, and combined with the established in-situ shear creep constitutive models of the slip zone (Equation 3-4) and the slip body (Equation 3-5) incorporating mesostructure factors, the time history curves of the landslide displacement field considering the in-situ shear creep constitutive models of the slip zone and the slip body are obtained:

[0120] Y i =S i [γ(t i ),δ(t i ),t j ] 4-2

[0121] In the formula, i is the monitoring point number; S i For landslide strain; γ(t) i ) represents the constitutive model of shear creep in a sliding belt; δ(t) i ) represents the shear creep constitutive model of a sliding body; t i The time consumed by creep; t j For monitoring time.

[0122] S5. Introducing a spatial weight matrix, the landslide displacement field time history curves of the in-situ shear creep constitutive model of the slip zone and the shear creep constitutive model of the slip body are used to correct the spatial weight matrix, thereby obtaining a dynamic spatial weight matrix. A spatiotemporal evolution model of the landslide displacement field with the dynamic spatial weight matrix as the core is established.

[0123] S5-1, Introducing the spatial weight matrix;

[0124] S5-1-1, based on the displacement field data obtained from the landslide displacement field time history curve, uses the density-based clustering algorithm (DBSCAN) to perform cluster analysis of monitoring points. The set of samples connected by the maximum density derived from the density reachability relationship is the cluster sample of displacement data of each monitoring point, thereby quantitatively analyzing the spatial relationship of displacement field between each monitoring point of the landslide.

[0125] The specific steps are as follows:

[0126] Step 1: Input two parameters: radius (Eps) and minimum number of samples (MinPts), and dataset U; output the results using the DBSCAN algorithm: each disjoint cluster;

[0127] Step 2: Check the data p in the database that has not yet been checked. If p has not been processed, it is assigned to cluster C. At the same time, check its neighborhood. If the number of objects contained is not less than MinPts, then p is the kernel object. Then, a new cluster C is created and the samples in its neighborhood are added to the new cluster C.

[0128] Step 3: For all unprocessed objects q in the new cluster C, check their neighborhoods. If they contain at least MinPts objects, then include all samples in their neighborhoods into the cluster.

[0129] Step 4: Repeat Step 2 to continue checking unprocessed objects in cluster C until no new samples are added to cluster C.

[0130] Step 5: Repeat Steps 1 through 3 until all objects are assigned to a cluster.

[0131] S5-1-2 calculates the spatial weight matrix of the landslide displacement field based on the spatial point clustering results, effectively expressing the spatial relationship of monitoring points.

[0132] The spatial weight matrix represents the influence of the displacement at a certain monitoring point on the displacements of neighboring monitoring points, and can be described using a distance matrix. Let Y... i and Y j Let |Y| represent the displacement of any two monitoring points i and j. i -Y j | represents the displacement distance between the two monitoring points, when |Y i -Y j The smaller the value of |, the closer the displacement distance between the two monitoring points i and j is, and the more likely it is to cause... The larger the value of , the greater the spatial weight coefficient between monitoring points i and j, thus the stronger the spatial correlation between the two monitoring points. The spatial weight matrix is ​​constructed as follows (Formula 5-1):

[0133]

[0134] S5-2, using the landslide displacement field time history curves of the established in-situ shear creep constitutive models of the slip zone and the slip body, the spatial weight matrix is ​​modified. Substituting Formula 4-2 into the spatial weight matrix W (Formula 5-1), the dynamic spatial weight matrix formula (5-2) is obtained:

[0135]

[0136] S5-3, as Figure 2 As shown, a spatiotemporal evolution model of landslide displacement field is established with Equation 5-2 as the core.

[0137] S6 establishes a displacement field prediction platform based on a displacement field database and with a spatiotemporal evolution model as its core. It conducts displacement field prediction, searches for the sliding surface in real time, and combines mechanical calculations to realize the stability analysis of landslides at both spatiotemporal scales.

[0138] S6-1. Based on existing landslide displacement field monitoring data, establish a landslide displacement field database;

[0139] S6-2, Build a displacement field prediction platform based on landslide displacement field database and spatiotemporal evolution model;

[0140] S6-3, predicts displacement field changes through a displacement field prediction platform, and searches for landslide sliding surfaces in real time based on the predicted displacement field;

[0141] S6-4, based on the search results of the sliding surface, combined with mechanical calculations, a landslide stability analysis was carried out, thereby constructing a spatiotemporal dual-scale stability evaluation and analysis method for large landslides that considers the microscopic creep characteristics of the slip zone.

[0142] This invention starts from the structural-mechanical evolution characteristics of the slip zone, conducts in-situ shear creep tests, microstructural scanning tests before and after shear creep, and supplements them with numerical tests of microstructure during the shear process. It explores in depth the role of microstructural evolution during the slip zone shear process on the creep mechanical properties of the slip zone, and then develops a slip zone shear creep constitutive model that can take into account the effect of microstructural evolution. It organically integrates and expresses spatial relationships, and finally constructs a landslide spatiotemporal dual-scale stability evaluation method that can take into account the structural-mechanical evolution characteristics, providing a new approach for achieving precise stability evaluation of large landslides.

[0143] Where there is no conflict, the above embodiments and features described herein can be combined with each other.

[0144] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing the spatiotemporal stability of landslides considering the microscopic characteristics of in-situ creep of the slip zone, characterized in that, Includes the following steps: S1: Based on the identified geological background and engineering geological conditions of the landslide area, conduct in-situ direct shear creep tests on the slip zone to determine the in-situ mechanical parameter values ​​of the slip zone; S2: Based on the in-situ mechanical parameter values ​​of the sliding belt, conduct microscopic scanning tests and numerical tests to obtain the microstructural characteristics of the sliding belt before and after the in-situ direct shear creep test, reveal the effect of changes in the microstructural characteristics of the sliding belt on the shear creep mechanical properties, quantify the microstructural characteristics, define the microstructural factor, and construct an evolution model of the microstructural-mechanical properties of the sliding belt during the shear process. S3: Combine the in-situ shear creep constitutive model of the sliding belt with the evolution model of microstructure-mechanical properties constructed in step S2 to establish an in-situ shear creep constitutive model of the sliding belt that incorporates microstructure factors. S4: By monitoring data of landslide surface displacement and deep landslide displacement, the time history of landslide displacement field is obtained, revealing the law of landslide displacement field change with time. Combined with the in-situ shear creep constitutive model of slip zone and the shear creep constitutive model of slip body with the introduction of microstructure factor, the time history curve of landslide displacement field considering the in-situ shear creep constitutive model of slip zone and the shear creep constitutive model of slip body is obtained. S5: Introduce a spatial weight matrix, and correct the spatial weight matrix according to the landslide displacement field time history curve obtained in step S4 to obtain a dynamic spatial weight matrix. Establish a spatiotemporal evolution model of landslide displacement field with the dynamic spatial weight matrix of landslide as the core. S6: Build a displacement field prediction platform based on a displacement field database and a landslide displacement field spatiotemporal evolution model as the core, carry out displacement field prediction, and then search for the sliding surface in real time. Combine mechanical calculations to realize the stability analysis of landslides under spatiotemporal dual scales. In step S3, the specific process is as follows: S3-1: Establish an in-situ shear creep constitutive model for the sliding belt; The constitutive model of in-situ shear creep of the sliding belt is shown in Equation 3-2: S3-2: Introducing the microstructure factor into the constitutive model of in-situ shear creep of the slip zone; S3-2-1: Determine the parameters of the constitutive model for in-situ shear creep of the sliding belt , , , , By performing regression analysis on the functional form of the relationship between the microstructure factor and the sliding zone in situ shear creep constitutive model parameters, an empirical relationship between the microstructure factor and the parameters is established, i.e., a system of equations: in, To examine the structural parameters in detail; Surface roughness undulation; Pore ​​morphology ratio; For parameters of the particle-bonded medium; Combining the creep equation shown in Equation 3-2 with the system of equations shown in Equation 3-3, we obtain the in-situ shear creep constitutive model of the slip zone incorporating a microstructure factor, as shown in Equation 3-4: in, δ This is the reduction factor. t For time; Simultaneously, by conducting shear creep tests on the sliding body, a constitutive model of the sliding body's shear creep can be obtained. That is, formula (3-5): in, δ This is the reduction factor. τ For shear stress, G 1 and G 2 represents the shear modulus of Maxwell and Kelvin bodies, respectively. η 1 and η 2 represents the viscosity coefficients of Maxwell and Kelvin volumes, respectively. t For time.

2. The landslide spatiotemporal stability analysis method considering the microscopic characteristics of in-situ creep of the slip zone as described in claim 1, characterized in that, In step S1, the specific process is as follows: S1-1: Investigate the geological background and engineering geological conditions of the landslide area; S1-2: Conduct in-situ rapid direct shear tests and in-situ direct shear creep tests on the landslide slip zone to determine the mechanical parameters of the slip zone, i.e., the long-term strength of the slip zone. Ultimate long-term strength Shear stress along the slip band τ Shear strain along the sliding belt Instantaneous shear modulus Long-term shear modulus Initial creep stage viscosity coefficient and viscosity coefficient of the stable creep segment And the shear strength parameters of the sliding belt: internal friction angle and cohesion .

3. The landslide spatiotemporal stability analysis method considering the microscopic characteristics of in-situ creep of the slip zone as described in claim 1, characterized in that, In step S2, the specific process is as follows: S2-1: Conduct a microstructural scanning test on the sliding belt to obtain its microstructural characteristics before and after the in-situ direct shear creep test: unit cell characteristics, microstructure characteristics, surface morphology, porosity, and particle bonding medium characteristics. Based on the microstructural characteristics, reveal the effect of microstructural changes on shear creep mechanical properties, quantify the microstructural characteristics, and define the microstructural factor: microstructure parameter. Surface roughness Pore ​​morphology ratio Parameters of particle-connected media ; S2-2: Based on the above microstructure characteristics and microstructure factors, and combined with PFC3D numerical experiments to deduce the particle fracture, grinding, shearing, overturning and transport processes, an evolution model of microstructure-mechanical properties of the sliding belt shearing process is established.

4. The landslide spatiotemporal stability analysis method considering the microscopic characteristics of in-situ creep of the slip zone as described in claim 1, characterized in that, In step S4, the specific process of obtaining the landslide displacement field time history curve considering the in-situ shear creep constitutive model of the slip zone and the shear creep constitutive model of the slip body is as follows: S4-1: Obtain surface and deep displacement monitoring data of the landslide; S4-2: Then, the time history curve of the landslide displacement field is obtained: Combining the established in-situ shear creep constitutive models of the slip zone and the slip body with microstructure factors, the time history curves of the landslide displacement field considering the in-situ shear creep constitutive models of the slip zone and the slip body are obtained: In the formula, For monitoring point number; For monitoring points i The amount of displacement; This represents the displacement-time mapping relationship. For landslide strain; For the shear creep constitutive model of the sliding band; For the constitutive model of sliding body shear creep; Time consumed for creep; For monitoring time.

5. The landslide spatiotemporal stability analysis method considering the microscopic characteristics of in-situ creep of the slip zone as described in claim 1, characterized in that, In step S5, the specific process is as follows: S5-1: Introduce the spatial weight matrix shown below to express the influence of the displacement at a certain monitoring point on the displacement of adjacent monitoring points: in, and Represent any two monitoring points i and j The displacement, then This represents the displacement distance between the two monitoring points. The smaller the value, the better the relationship between the two monitoring points. and The displacement distance is closer, which leads to The larger the value, the more monitoring points and The larger the spatial weight coefficient between the two monitoring points, the stronger the spatial correlation between them. The process of establishing the spatial weight matrix is ​​as follows: S5-1-1: Based on the landslide displacement field time history curve, a density-based clustering algorithm is used to perform cluster analysis of monitoring points. The set of samples connected by the maximum density is derived from the density reachability relationship, which yields the clustered samples of displacement data of each monitoring point, thereby quantitatively analyzing the spatial relationship of displacement field between each monitoring point of the landslide. S5-1-2: The spatial weight matrix of the landslide displacement field is calculated based on the spatial point clustering results, which effectively expresses the spatial relationship of monitoring points; S5-2: Using the established in-situ shear creep constitutive models of the slip zone and the slip body that incorporate mesostructure factors, the spatial weight matrix is ​​modified, and the landslide displacement field time history curve formula is substituted into the spatial weight matrix. From this, the formula for the dynamic spatial weight matrix of landslides is derived: S5-3: Based on the formula of the dynamic spatial weight matrix of landslides, a spatiotemporal evolution model of landslide displacement field is established.

6. The landslide spatiotemporal stability analysis method considering the microscopic characteristics of in-situ creep of the slip zone as described in claim 1, characterized in that, In step S6, the specific process is as follows: S6-1: Establish a landslide displacement field database based on landslide displacement field monitoring data; S6-2: Based on the landslide displacement field database and with the spatiotemporal evolution model as the core, a displacement field prediction platform is built; S6-3: Predict displacement field changes through a displacement field prediction platform, and search for landslide sliding surfaces in real time based on the predicted displacement field; S6-4: Based on the landslide sliding surface found, the stability analysis of the landslide under both temporal and spatial scales is carried out by combining mechanical calculations.

Images