Method for automatically judging site liquefaction depth

Abstract

The invention discloses a site liquefaction depth automatic determination method. The method comprises the following steps: S1, determining site numerical model parameters according to the actual situation of a site; s2, based on an OpenSees platform, establishing a three-dimensional site numerical model; s3, simulating a soil body pore water pressure response process of the three-dimensional field numerical model under the action of an earthquake load, and calculating soil body pore water pressure responses at different depth nodes; and S4, based on an MATLAB platform, performing batch processing on the pore water pressure response data output in the step S3 to judge whether liquefaction occurs, and determining a liquefaction range according to a judgment result. The method effectively overcomes the defects that a traditional liquefaction judgment method is high in cost, long in period, limited in precision and the like, the dynamic response of an actual site under the earthquake action is comprehensively simulated through a series of indoor tests and numerical simulation technologies, calculation results are processed in batches with the help of MATLAB scripts, and the liquefaction judgment efficiency and precision are effectively improved.

Description

Technical Field

[0001] The invention relates to the field of civil engineering, in particular to a method for automatically determining the liquefaction depth of a site, which is used for determining the liquefaction depth of a site under earthquake conditions. Background Art

[0002] In earthquake engineering, site liquefaction is a very destructive phenomenon. It is mainly caused by the strong dynamic action caused by earthquakes, which leads to the rearrangement of soil particles and a sharp increase in pore water pressure, which significantly reduces the strength and stiffness of the soil, and even completely loses its bearing capacity. Liquefaction can cause foundation failure, building collapse, and may also cause secondary disasters such as ground subsidence and landslides, posing a serious threat to people's lives and property. Traditional methods for determining site liquefaction mainly rely on field surveys, empirical formulas, and indoor tests. Although these methods can assess the liquefaction potential of a site to a certain extent, they have many limitations, such as: field surveys require a lot of manpower, material resources, and time, which is costly and time-consuming, and it is difficult to meet the needs of rapid assessment; empirical formulas are often based on limited test data and statistical results, and their applicability and accuracy are affected by multiple factors such as region, soil type, and seismic wave characteristics, and it is difficult to fully reflect the liquefaction behavior under complex geological conditions; although indoor tests can simulate soil response under specific conditions, it is difficult to fully reproduce the complex dynamic process of the actual site under earthquake action, and the test conditions are strictly controlled and the cost is relatively high. With the rapid development of computing technology, numerical simulation methods have gradually become an important means of earthquake liquefaction analysis. As an open-source finite element analysis platform, OpenSees has been widely used in the field of civil engineering for its powerful earthquake response analysis capabilities and flexible modeling functions. However, although simple numerical simulation can provide rich data, the processing and analysis of data are often cumbersome and time-consuming, requiring manual operation by professional technicians, and it is difficult to achieve automation and batch processing. Summary of the invention

[0003] The present invention provides a method for automatically determining the liquefaction depth of a site in order to solve the technical problems existing in the known technology. The method can determine the liquefaction risk of the site quickly, efficiently and at low cost.

[0004] The technical solution adopted by the present invention to solve the technical problems existing in the known technology is: a method for automatically determining the liquefaction depth of a site, which adopts the following steps:

[0005] S1. Determine the site numerical model parameters according to the actual site conditions;

[0006] S2, based on the OpenSees platform, establish a three-dimensional site numerical model in combination with the parameters in step S1;

[0007] S3, simulate the soil pore water pressure response process of the three-dimensional site numerical model under the action of earthquake load, and calculate the soil pore water pressure response at different depth nodes;

[0008] S4. Based on the MATLAB platform, batch process the pore water pressure response data outputted from step S3 to determine whether liquefaction occurs, and determine the liquefaction range according to the determination result.

[0009] The specific steps of step S1 are:

[0010] S1.1. Determine the dimensions of each layer and the soil materials used in the site numerical model based on the geological survey data of the actual site;

[0011] S1.2. Determine the parameters of each layer of the model material through indoor experiments, numerical calculations and consulting the OpenSees manual.

[0012] The specific steps of step S3 are:

[0013] S3.1. Call the fluid-solid coupling unit TwentyEight Node Brick up Element based on Biot porous media theory embedded in the OpenSees platform to define the soil unit of the three-dimensional site numerical model;

[0014] S3.2, assign model soil layer materials and their parameters to the corresponding positions of soil units;

[0015] S3.3, define boundary conditions for the three-dimensional numerical model;

[0016] S3.4, update the model material state to elastic state, and apply soil deadweight to the three-dimensional numerical model;

[0017] S3.5. Update the model material state to plastic state and apply soil deadweight to the three-dimensional numerical model;

[0018] S3.6. Apply seismic excitation to the base of the three-dimensional numerical model according to the acceleration time sequence, perform seismic response analysis, and output pore water pressure response data at different depth nodes.

[0019] The specific steps of step S4 are:

[0020] S4.1. Based on the MATLAB platform, batch read and store the pore water pressure response data of each node, and calculate the total stress σ0=∑λ according to the node position i ·h i , where λ i is the soil weight of the corresponding soil layer, h i is the thickness of the corresponding soil layer;

[0021] S4.2. Based on the MATLAB platform, calculate the initial pore water pressure u0=γ according to the node position w ·h w , where γ w Water density, h w Height from node to groundwater level;

[0022] S4.3. Calculate the excess pore pressure ratio of the node based on the MATLAB platform Where u is the pore water pressure response under the seismic load, which is retrieved from the calculation result of step S3;

[0023] S4.4. Based on the MATLAB platform, the changes in the excess pore pressure ratio of each node are automatically read. When the excess pore pressure ratio at the node reaches 1.0, liquefaction is determined. The range of the soil layer where liquefaction occurs is determined based on the determination results of each node.

[0024] The specific method of step S33 is: constraining the pore pressure freedom of the soil nodes at the groundwater level depth, setting the base and surrounding areas as impermeable boundaries, constraining the y-direction freedom of the four side nodes, and constraining the x, y, and z-direction freedom of the nodes at the same height.

[0025] The step S3.6 identifies and saves the node with coordinates (0, 0, z), where z is a variable, and then outputs the pore water pressure response data at different depth nodes.

[0026] In the step S1.2, it is determined that the model uses PressureDependentMultiYield to simulate the sand layer; and uses PressureIndependMultiYield to simulate the clay layer.

[0027] The advantages and positive effects of the present invention are: high-precision simulation of the site model and efficient data processing are achieved, the whole process of soil pore pressure response under earthquake load is completely simulated by OpenSees, and MATLAB accurately reads and processes the pore pressure data output by OpenSees to achieve batch processing and automatic determination. The flexibility and automation characteristics of the method make it easy to expand and improve, and users can establish complex three-dimensional site numerical models, which are suitable for sites of different types and complexity. Whether it is a single sand layer or a complex site containing a clay layer, accurate simulation and liquefaction determination can be performed. The present invention effectively overcomes the shortcomings of traditional liquefaction determination methods such as high cost, long cycle, and limited accuracy. Through a series of indoor tests and numerical simulation technologies, the dynamic response of the actual site under earthquake action is comprehensively simulated, and the calculation results are batch processed with the help of MATLAB scripts, which effectively improves the efficiency and accuracy of liquefaction determination, and has a wide range of application prospects in actual engineering, and is particularly suitable for engineering projects that require rapid, efficient, and low-cost determination of site liquefaction risks, such as earthquake disaster assessment and infrastructure construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of the numerical model of the site built based on OpenSees;

[0029] Figure 2 for Figure 1 A top view of

[0030] Figure 3 are the numbers and z coordinates of the 22 nodes recorded in this example;

[0031] Figure 4 These are the 22 pore pressure response result files output in this example;

[0032] Figure 5 This is a flowchart for building a three-dimensional site numerical model based on OpenSees;

[0033] Figure 6 It is the pore pressure response result (partial) of node 2602 in this example;

[0034] Figure 7 It is a comparison between the numerical simulation results of loose sand layer soil nodes and the Wilson centrifuge shaking table test results;

[0035] Figure 8 This is a flow chart for batch processing of pore water pressure response data based on MATLAB;

[0036] Fig. 9 It is the z coordinate, total stress and initial pore water pressure data (part) of each node output in this example;

[0037] Fig.10 This is the judgment result of this example. DETAILED DESCRIPTION

[0038] In order to further understand the content, features and effects of the present invention, the following application examples are given and described in detail with reference to the accompanying drawings:

[0039] See also Figures 1 to 10 , a method for automatically determining the liquefaction depth of a site, using the following steps:

[0040] S1. Determine the site numerical model parameters according to the actual site conditions;

[0041] S2, based on the OpenSees platform, establish a three-dimensional site numerical model in combination with the parameters in step S1;

[0042] S3, simulate the soil pore water pressure response process of the three-dimensional site numerical model under the action of earthquake load, and calculate the soil pore water pressure response at different depth nodes;

[0043] S4. Based on the MATLAB platform, batch process the pore water pressure response data outputted from step S3 to determine whether liquefaction occurs, and determine the liquefaction range according to the determination result.

[0044] In this application example, the specific steps of step S1 are:

[0045] S1.1. Determine the dimensions of each layer and the soil materials used in the site numerical model based on the geological survey data of the actual site;

[0046] S1.2. Determine the parameters of each layer of material in the model through indoor experiments, numerical calculations and reference to technical manuals, and accurately define each layer of material in the model.

[0047] It is recommended that, in step S1.2, the model adopts PressureDependentMultiYield to simulate the sand layer; and adopts PressureIndependMultiYield to simulate the clay layer.

[0048] The parameters used to define PressureDependentMultiYield materials include the following 14: 1) saturated soil mass density; 2) reference low strain shear modulus; 3) reference bulk modulus; 4) internal friction angle; 5) octahedral shear strain to achieve maximum shear strength; 6) reference average effective confining pressure; 7) constants defining the change of bulk modulus and shear modulus; 8) phase change angle; 9) constants defining the shear contraction or pore pressure accumulation rate; 10), 11) two constants defining the expansion rate; 12), 13), 14) three constants controlling the liquefaction-induced perfect plastic shear strain accumulation mechanism. Among them, 1) saturated soil mass density, the soil specific gravity G is measured by indoor experiments ss , porosity ratio e and formula ρ s =ρ water (G ss +e) / (1+e); 2) Reference low strain shear modulus, determined by small strain triaxial test or by consulting the OpenSees manual; 5) Octahedron reference shear strain, maximum shear modulus G obtained by wave velocity test s And the formula Determine; 3) refer to the bulk modulus, through formula B r,s =G s,oct (B / G); 4) internal friction angle, determined by triaxial shear test; 6)-(14), relative density measured by indoor experiments and determined by consulting OpenSees manual.

[0049] The parameters used to define PressureIndependMultiYield include the following 8: 1) saturated soil mass density; 2) reference low strain shear modulus; 3) reference bulk modulus; 4) cohesion; 5) octahedral shear strain to achieve maximum shear strength; 6) friction angle; 7) reference average effective confining pressure; 8) constant defining the change of bulk modulus and shear modulus. Among them, 4) cohesion is determined by triaxial shear test, and the determination method of other parameters is the same as that of PressureDependentMultiYield material.

[0050] The specific steps of step S3 are:

[0051] S3.1. Call the fluid-solid coupling unit TwentyEight Node Brick up Element based on Biot porous media theory embedded in the OpenSees platform to define the soil unit of the three-dimensional site numerical model;

[0052] S3.2, assign model soil layer materials and their parameters to the corresponding positions of soil units;

[0053] S3.3, define boundary conditions for the three-dimensional numerical model;

[0054] S3.4, update the model material state to elastic state, and apply soil deadweight to the three-dimensional numerical model;

[0055] S3.5. Update the model material state to plastic state and apply soil deadweight to the three-dimensional numerical model;

[0056] S3.6. Apply seismic excitation to the base of the three-dimensional numerical model according to the acceleration time sequence, perform seismic response analysis, and output pore water pressure response data at different depth nodes.

[0057] The specific steps of step S4 are:

[0058] S4.1. Based on the MATLAB platform, batch read and store the pore water pressure response data of each node, and calculate the total stress σ0=∑λ according to the node position i ·h i , where λ i is the soil weight of the corresponding soil layer, h i is the thickness of the corresponding soil layer;

[0059] S4.2. Based on the MATLAB platform, calculate the initial pore water pressure u0=γ according to the node position w ·h w , where γ w Water density, h w Height from node to groundwater level;

[0060] S4.3. Calculate the excess pore pressure ratio of the node based on the MATLAB platform Where u is the pore water pressure response under the seismic load, which is retrieved from the calculation result of step S3;

[0061] S4.4. Based on the MATLAB platform, the changes in the excess pore pressure ratio of each node are automatically read. When the excess pore pressure ratio at the node reaches 1.0, liquefaction is determined. The range of the soil layer where liquefaction occurs is determined based on the determination results of each node.

[0062] The specific method of step S33 is: constraining the pore pressure freedom of the soil nodes at the groundwater level depth, setting the base and surrounding areas as impermeable boundaries, constraining the y-direction freedom of the four side nodes, and constraining the x, y, and z-direction freedom of the nodes at the same height.

[0063] The step S3.6 identifies and saves the node with coordinates (0, 0, z), where z is a variable, and then outputs the pore water pressure response data at different depth nodes.

[0064] Application of the present invention:

[0065] The site parameters are based on the prototype site of the centrifuge vibration table test conducted by Wilson.DW et al. in 1998. The site is divided into two layers: upper loose sand and lower dense sand. In order to reduce the calculation time, the symmetry of the test body geometry is used to establish a semi-idealized three-dimensional site numerical model with a model size of 51m×10.5m×20.5m.

[0066] See also Figure 1-2 , Figure 1 and Figure 2 This is a schematic diagram of the three-dimensional site numerical model established based on OpenSees. The groundwater level is flush with the upper surface of the loose sand layer. The nodes on the coordinate (0, 0, z) column are selected for pore pressure time history measurement. The z value range is 0 to 20.5 m. In this example, the results of 22 soil nodes are extracted based on the results of grid division. The numbers and z coordinates of the 22 nodes are shown in Figure 3 txt format, and record the measurement results. The 22 text files are named as shown in Figure 4 .

[0067] The model dimensions in the centrifuge shaking table test and this application example are in meters.

[0068] See also Figure 5 , Figure 5 A flowchart for building a 3D site numerical model based on the OpenSees platform, including the following steps:

[0069] S41. Determine the model size and soil quality based on geological survey data;

[0070] S42. Determine the soil material parameters based on indoor experiments, numerical calculations and consulting the OpenSees manual;

[0071] S43, establishing a three-dimensional soil model matching the actual site;

[0072] S44, model meshing;

[0073] S45. Define boundary conditions:

[0074] In this application example, there are two types of soil nodes: three-degree-of-freedom nodes and four-degree-of-freedom nodes. The fourth degree of freedom is pore water pressure. The pore pressure degree of freedom of the four-degree-of-freedom nodes on the upper surface of the soil is constrained. The base and four sides are set as impermeable boundaries. The y-direction degree of freedom of the nodes on the four sides is constrained. The multi-point constraint command is used to constrain the x, y, and z-direction degrees of freedom of the nodes at the same height.

[0075] S46. Define soil materials and elements;

[0076] In this application example, both the loose sand and dense sand layers use PressureDependentMultiYield material and 20-8 fluid-solid coupling unit;

[0077] S47, soil self-weight analysis;

[0078] In this application example, the soil self-weight analysis includes the elastic stage and the plastic stage, and the material properties are updated through the updateMaterialStage command;

[0079] S48, Dynamic Loading Analysis

[0080] In this application example, the dynamic load is the Kobe earthquake wave, which has a peak acceleration of 0.2g and a duration of 60s.

[0081] S49. Model reliability and accuracy verification

[0082] In this application example, the pore pressure responses of 22 soil nodes are recorded after the calculation is completed. Taking node 2602 as an example, the pore pressure response data of node 2602 can be found in Figure 6 ;

[0083] See also Figure 7 , Figure 7 The numerical simulation results of the loose sand layer soil nodes were compared with the Wilson centrifuge shaking table test results to verify the reliability and accuracy of the simulation results.

[0084] See also Figure 8 , Figure 8 The flowchart for batch processing of pore water pressure response data is based on the MATLAB platform and includes the following steps:

[0085] S51, batch read pore water pressure response data output by OpenSees;

[0086] S52, calculate the total stress of each node;

[0087] S53, calculate the initial pore water pressure of each node, and output the z coordinate, total stress and initial pore water pressure of each node. Fig. 9 ;

[0088] S54, calculating the excess pore pressure ratio of each node;

[0089] S55, determining whether liquefaction occurs in the stage;

[0090] In this application example, when the excess pore pressure ratio reaches 1, it is determined that the soil layer at the height of the node has liquefied.

[0091] S56, outputting the liquefaction determination result;

[0092] In this application example, the liquefaction depth range is determined based on the judgment results of each node; if no liquefaction occurs at any height node within the loading time, then "No liquefaction occurs at the site" is output; otherwise, the depth range where liquefaction occurs is output. For the judgment results of this example, please refer to Fig.10 .

[0093] By writing TCL code, a high-precision three-dimensional site numerical model is established in OpenSees to simulate the dynamic response of soil under earthquake and output detailed pore water pressure response data. Then, combined with the powerful data processing and computing capabilities of MATLAB, a script is written to batch process and analyze the data output by OpenSees to quickly and accurately determine the depth range of liquefaction at the site. Compared with traditional methods, the present invention not only greatly improves the efficiency and accuracy of liquefaction determination, but also reduces the determination cost and shortens the cycle, providing strong technical support for engineering fields such as earthquake disaster assessment and infrastructure construction.

[0094] Although the preferred application examples of the present invention are described above in conjunction with the accompanying drawings, the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, which all fall within the scope of protection of the present invention.

Claims

1. A method for automatically determining the liquefaction depth of a site, characterized in that: Use the following steps: S1. Determine the site numerical model parameters according to the actual site conditions; S2, based on the OpenSees platform, establish a three-dimensional site numerical model in combination with the parameters in step S1; S3, simulate the soil pore water pressure response process of the three-dimensional site numerical model under the action of earthquake load, and calculate the soil pore water pressure response at different depth nodes; S4. Based on the Matlab platform, the pore water pressure response data outputted from step S3 are batch processed to determine whether liquefaction occurs, and the liquefaction range is determined according to the determination result.

2. The method for automatically determining the site liquefaction depth according to claim 1, characterized in that: The specific steps of step S1 are: S1.

1. Determine the dimensions of each layer and the soil materials used in the site numerical model based on the geological survey data of the actual site; S1.

2. Determine the parameters of each layer of the model material through indoor experiments, numerical calculations and consulting the OpenSees manual.

3. The method for automatically determining the site liquefaction depth according to claim 1, characterized in that: The specific steps of step S3 are: S3.

1. Call the Twenty Eight Node Brick up Element, a fluid-solid coupling unit based on Biot porous media theory, embedded in the OpenSees platform to define the soil unit of the three-dimensional site numerical model; S3.2, assign model soil layer materials and their parameters to the corresponding positions of soil units; S3.3, define boundary conditions for the three-dimensional numerical model; S3.4, update the model material state to elastic state, and apply soil deadweight to the three-dimensional numerical model; S3.

5. Update the model material state to plastic state and apply soil deadweight to the three-dimensional numerical model; S3.

5. Apply seismic excitation to the base of the three-dimensional numerical model according to the acceleration time sequence, perform seismic response analysis, and output pore water pressure response data at different depth nodes.

4. The method for automatically determining the site liquefaction depth according to claim 1, characterized in that: The specific steps of step S4 are: S41. Based on the MATLAB platform, batch read and store the pore water pressure response data of each node, and calculate the total stress σ0=∑λ according to the node position i ·h i , where λ i is the soil weight of the corresponding soil layer, h i is the thickness of the corresponding soil layer; S42. Based on the MATLAB platform, calculate the initial pore water pressure u0=γ according to the node position w ·h w , where γ w Water density, h w Height from node to groundwater level; S43, Calculate the excess pore pressure ratio of the node based on MATLAB platform Where u is the pore water pressure response under the seismic load, which is retrieved from the calculation result of step S3; S44. Based on the MATLAB platform, the change of the excess pore pressure ratio of each node is automatically read. When the excess pore pressure ratio at the node is greater than or equal to 1, it is determined that complete liquefaction has occurred. The range of the soil layer where liquefaction has occurred is determined by the determination results of each node.

5. The method for automatically determining the site liquefaction depth according to claim 3, characterized in that: The specific method of step S33 is: constraining the pore pressure freedom of the soil nodes at the groundwater level depth, setting the base and surrounding areas as impermeable boundaries, constraining the y-direction freedom of the four side nodes, and constraining the x, y, and z-direction freedom of the nodes at the same height.

6. The method for automatically determining the site liquefaction depth according to claim 3, characterized in that: The step S3.6 identifies and saves the node with coordinates (0, 0, z), where z is a variable, and then outputs the pore water pressure response data at different depth nodes.

7. The method for automatically determining the site liquefaction depth according to claim 2, characterized in that: In the step S1.2, it is determined that the model uses PressureDependentMultiYield to simulate the sand layer; and uses PressureIndependMultiYield to simulate the clay layer.

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