Concrete cast-in-place pile bearing characteristic simulation method suitable for electric power engineering construction

Abstract

The application relates to the technical field of model simulation, and proposes a concrete pouring pile bearing characteristic simulation method suitable for electric power engineering construction, which comprises the following steps: installing stress pieces on a concrete pouring pile, collecting strain data of the stress pieces, and dividing jurisdictions of different stress pieces; determining first, second, third and fourth characteristic values of the stress pieces at a collection moment, and calculating complexity of the stress pieces at the collection moment; carrying out grid division on the jurisdictions of the stress pieces according to the complexity, and completing simulation of the bearing characteristics of the concrete pouring pile. The application aims to accurately capture the mechanical responses of different positions in the concrete pouring pile, and improve the accuracy of simulation results.

Description

Technical Field

[0001] This application relates to the field of model simulation technology, specifically to a simulation method for the bearing characteristics of cast-in-place concrete piles applicable to power engineering construction. Background Technology

[0002] The geological conditions of power engineering construction sites are complex and diverse, such as soft soil, rock strata, and fill. Simulation can be used to simulate the bearing characteristics of cast-in-place concrete piles under different geological conditions in advance, formulate reasonable construction steps and processes, predict potential problems during construction, and take corresponding measures for prevention and control to ensure the smooth progress of the design and construction process.

[0003] Generally, the bearing characteristics of cast-in-place concrete piles are simulated using the ABAQUS finite element software. A fixed mesh is used to numerically simulate the bearing characteristics of cast-in-place concrete piles. However, the stress of the material at different locations within the cast-in-place concrete pile is different, and a uniform meshing strategy is difficult to accurately capture the mechanical response of different key parts. At the same time, it also leads to a waste of computational resources. Summary of the Invention

[0004] This application provides a simulation method for the bearing characteristics of cast-in-place concrete piles applicable to power engineering construction, in order to solve the problem of inaccurate capture of the mechanical response at different locations within the cast-in-place concrete pile during the simulation of its bearing characteristics, resulting in inaccurate simulation results. The specific technical solution adopted is as follows: One embodiment of this application provides a simulation method for the bearing characteristics of cast-in-place concrete piles applicable to power engineering construction. The method includes the following steps: Stress gauges are installed at different locations on the concrete pile, and strain data of the stress gauges are collected at different collection times. A strain data sequence of the stress gauges at the collection times is established, and the jurisdiction area is divided according to the spatial distribution of the stress gauges on the concrete pile. Any stress gauge on the concrete cast-in-place pile is designated as the target stress gauge, the column containing the target stress gauge is designated as the target column, and the row containing the target stress gauge is designated as the target row. Adjacent columns are labeled as "one column" and "two columns". Based on the difference in similarity between the strain data sequences of stress gauge positions in the same row within the target column, the one adjacent column, and the two adjacent columns, the first characteristic value of the target stress gauge in the target column at the acquisition time is determined. Based on the difference in the variation trend between the strain data sequences of stress gauge positions in the same row within the target column and the one adjacent column, the second characteristic value of the target stress gauge in the target column at the acquisition time is determined. Based on the differences between strain data sequences of the target stress gauge at adjacent acquisition times, the third characteristic value of the target stress gauge at each acquisition time is determined. Based on the changing trend of stress data of the stress gauge at adjacent acquisition times, the predicted sequence of the stress gauge at each acquisition time is determined. Based on the differences between the predicted sequences of all stress gauges in the same row at the same acquisition time, the fourth characteristic value of each stress gauge in the same row at the acquisition time is determined. Based on the first, second, third, and fourth characteristic values ​​of the stress gauge at the acquisition time, the complexity of the stress gauge at the acquisition time is calculated. Based on the complexity of the stress gauge at the time of acquisition, the area under the jurisdiction of the stress gauge is divided into grids, and the bearing characteristics of the concrete cast-in-place pile are simulated.

[0005] Furthermore, adjacent stress plates are symmetrical about the boundaries of their respective jurisdictional areas.

[0006] Furthermore, the specific marking method for adjacent columns and adjacent two columns is as follows: The first adjacent column of the target column in a clockwise direction is called the adjacent column, and the second adjacent column of the target column in a clockwise direction is called the adjacent column.

[0007] Furthermore, the specific method for determining the first characteristic value of the target stress plate at the acquisition time is as follows: Based on the strain data sequences of all stress gauges contained in the target column, the adjacent column, and the two adjacent columns at the acquisition time, the first sequence of the target column, the adjacent column, and the two adjacent columns at the acquisition time is established respectively. The similarity between the target column and the first sequence of the adjacent column at the time of collection is denoted as the first similarity of the target column at the time of collection. The similarity between the first sequence of the adjacent column and the first sequence of the two adjacent columns at the time of collection is denoted as the second similarity of the target column at the time of collection. The absolute value of the difference between the first similarity and the second similarity of the target column at the time of collection is denoted as the first difference of the target column at the time of collection. Based on the strain data sequences of all stress plates in the target column (excluding the target stress plate) and the stress plates in the target row of the adjacent column at the acquisition time, a second sequence of the target stress plate at the acquisition time is established. The similarity between the second sequence of the target stress plate at the acquisition time and the first sequence of the adjacent column at the acquisition time is denoted as the third similarity of the target stress plate at the acquisition time. The absolute value of the difference between the first similarity of the target column at the acquisition time and the third similarity of the target stress plate at the same acquisition time is denoted as the second difference of the target stress plate at the acquisition time. The absolute value of the difference between the first difference of the target list at the acquisition time and the second difference of the target stress sheet at the same acquisition time is denoted as the first characteristic value of the target stress sheet at the acquisition time.

[0008] Furthermore, the specific method for determining the second characteristic value of the target stress plate at the acquisition time is as follows: A linear fit is performed on the stress data sequence of the target stress piece at the acquisition time, and the slope of the fitted line is recorded as the stress slope of the target stress piece at the acquisition time. Based on the stress slopes of all stress pieces in the same column at the same acquisition time, a stress slope sequence of the same column at the same acquisition time is established. The sum of the absolute values ​​of the differences between the target column and the stress slope sequence of the adjacent column at the same acquisition time is recorded as the first slope difference of the target column at the same acquisition time. Based on the stress slopes of all stress plates in the target column (excluding the target stress plate) and the stress plates in the target row of the adjacent column at the acquisition time, a stress slope replacement sequence for the target stress plate at the acquisition time is established. The sum of the absolute values ​​of the differences between the stress slope replacement sequence for the target stress plate at the acquisition time and the corresponding stress slopes in the stress slope sequence of the adjacent column at the same acquisition time is recorded as the second slope difference of the target stress plate at the same acquisition time. The absolute value of the difference between the first slope difference of the target array at the acquisition time and the second slope difference of the target stress plate at the same acquisition time is denoted as the second characteristic value of the target stress plate at the acquisition time.

[0009] Furthermore, the specific method for determining the third characteristic value of the target stress plate at each acquisition time is as follows: The DTW distance between strain data sequences of the target stress gauge at adjacent acquisition times is denoted as the third characteristic value of the target stress gauge at the next acquisition time in adjacent acquisition times.

[0010] Furthermore, the specific method for determining the fourth characteristic value of the stress plate at the acquisition time is as follows: Based on the stress data collected by the stress plate at the acquisition time and at a first preset number of adjacent acquisition times before the acquisition time, a prediction benchmark sequence of the stress plate at the acquisition time is established. The predicted values ​​of the stress data of the stress plate at a second preset number of adjacent acquisition times after the acquisition time are obtained, and a prediction sequence of the stress plate at the acquisition time is established. The sum of the DTW distances between the target stress patch and all other stress patches in the target row at the acquisition time is denoted as the fourth characteristic value of the target stress patch at the acquisition time.

[0011] Furthermore, the formula for calculating the complexity of the stress plate at the time of acquisition is as follows: ; in, Indicates stress sheet The complexity at acquisition time t; These represent stress sheets. The first, second, third, and fourth eigenvalues ​​at acquisition time t; These represent the preset first weighting coefficient, second weighting coefficient, and third weighting coefficient, respectively. This represents the hyperbolic tangent function.

[0012] Furthermore, the specific methods for meshing the stress zone under the jurisdiction of the stress zone based on the complexity of the stress zone at the time of acquisition and simulating the bearing characteristics of the cast-in-place concrete pile include: Calculate the partitioning weight of the stress gauge at the acquisition time based on the complexity of the stress gauge at the acquisition time; The division weight of the stress plate at the acquisition time is used as the weight for meshing the area under the jurisdiction of the stress plate. The mesh of the area under the jurisdiction of the stress plate is divided using the mesh in the ABAQUS finite element model. Based on the bearing characteristics of the concrete cast-in-place pile, the bearing characteristics simulation of the concrete cast-in-place pile is completed.

[0013] Furthermore, the formula for calculating the partitioning weight is: ; in, Indicates stress sheet The partitioning weights at acquisition time t; Indicates stress sheet The complexity at acquisition time t; This indicates the preset upper limit of the partition weight; This indicates the preset lower limit of the partition weight.

[0014] The beneficial effects of this application are: This application considers that the stress data of stress gauges in the same column of a cast-in-place concrete pile should decrease with increasing depth of the stress gauge, and that the strain data of corresponding stress gauges in adjacent columns of the cast-in-place concrete pile show similar trends. Therefore, it evaluates the overall variation amplitude and stability of the strain data of the stress gauges at different depths at the time of acquisition, obtaining the first and second characteristic values ​​of the stress gauges at the time of acquisition. Based on the similarity of the strain data of the corresponding stress gauge with that of stress gauges at the same depth at the time of acquisition, a third characteristic value of the stress gauges at the time of acquisition is obtained. Based on the similarity between the strain data of the corresponding stress gauge and that of adjacent stress gauges at the time of acquisition, a fourth characteristic value of the stress gauges at the time of acquisition is obtained. Finally, based on the first, second, and third characteristic values ​​of the stress gauges at the same acquisition time, and... The fourth eigenvalue accurately captures the mechanical response at different locations within the concrete pile and obtains the complexity of the stress patch at the same acquisition time. The greater the complexity of the stress patch at the acquisition time, the denser the mesh should be when dividing the stress patch's domain region using the ABAQUS finite element model, and the smaller the weight of the mesh division for the stress patch's domain region should be. Finally, based on the complexity of the stress patch at the acquisition time, the domain region of the stress patch is meshed, and the simulation of the concrete pile's bearing characteristics is completed. This solves the problem of inaccurate capture of the mechanical response at different locations within the concrete pile during the simulation of the concrete pile's bearing characteristics, leading to inaccurate simulation results, avoiding waste of computational resources, and improving the accuracy of the simulation results. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A schematic diagram of a simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction, provided as an embodiment of this application; Figure 2 This is a schematic diagram of the stress sheet installation position provided in one embodiment of this application; Figure 3 This is a schematic diagram of the jurisdiction provided for one embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0018] Please see Figure 1 The diagram illustrates a flowchart of a simulation method for the bearing characteristics of cast-in-place concrete piles applicable to power engineering construction, provided by an embodiment of this application. The method includes the following steps: Step S001: Install stress gauges at different locations on the concrete cast-in-place pile, collect strain data of the stress gauges at different collection times, establish a strain data sequence of the stress gauges at the collection times, and divide the jurisdiction area of ​​different stress gauges according to the spatial distribution of the stress gauges on the concrete cast-in-place pile.

[0019] Stress gauges were installed at different locations on each concrete pile, and strain data were collected at each stress gauge location.

[0020] Preferably, as an embodiment of this application, four sampling points are evenly set in the same vertical direction from the bottom to the top of the concrete pile, and four sampling points are evenly set at the edge of the horizontal plane where each sampling point of the concrete pile is located, that is, a total of sixteen sampling points are set on each concrete pile, and stress plates are installed at each sampling point.

[0021] A diagram showing the installation location of the stress plate is shown below. Figure 2 As shown, in Figure 2 In the diagram, cylinders represent cast-in-place concrete piles, and solid dots represent the locations of stress plates. The red solid dots indicate the locations of stress plates on the surface of the cast-in-place concrete pile. It can be understood that the distance between different stress plates is the same in every vertical direction of the cast-in-place concrete pile, and the distance between different stress plates is also the same in every horizontal direction.

[0022] Preferably, as an embodiment of this application, the time interval for collecting strain data is 1 second. All strain data collected within 20 seconds before the collection time are arranged in the order of collection to obtain the strain data sequence at the collection time. The collection of strain data continues until the end of the entire static load process of concrete.

[0023] In this embodiment, Gaussian filtering is used to denoise the strain data. Gaussian filtering is a well-known technique and will not be described further. As other embodiments, while achieving the goal of denoising strain data, implementers may employ other methods in the prior art, such as statistical filtering, for strain data denoising. This application does not impose any special limitations.

[0024] In static load tests of cast-in-place concrete piles, when the pile top is subjected to a uniformly distributed load, the pile stress will decrease regularly along the depth direction. Specifically, from the pile top to the pile bottom, the pile side friction will gradually share the pile axial force, causing the pile axial force to decrease with increasing depth. This results in a stable decreasing trend in the strain data measured by stress gauges. Therefore, the variation trend of strain data at corresponding rows of stress gauge positions in adjacent columns of the cast-in-place concrete pile should be similar. At the same time, the cast-in-place concrete pile has obvious circumferential uniformity in space, that is, the variation trend of strain data at stress gauge positions in the same row of the cast-in-place concrete pile should be similar.

[0025] Therefore, the mesh generation strategy in the ABAQUS finite element model can be dynamically determined based on the distribution characteristics of strain data from stress plates at different spatial locations on the concrete cast-in-place pile.

[0026] Based on the spatial distribution of stress plates on the concrete cast-in-place pile, the concrete cast-in-place pile is divided into the jurisdiction areas of different stress plates, and the boundaries of the jurisdiction areas of adjacent stress plates are symmetrical.

[0027] A map showing the jurisdiction is shown below. Figure 3 As shown, the area governed by each stress plate is a fan-shaped cylinder. Figure 3 In the diagram, the cylinder represents a cast-in-place concrete pile, the red dot indicates the location of the stress plate on the surface of the cast-in-place concrete pile, the fan-shaped column divided by the green edge on the left is the area governed by stress plate 1 at the bottom of the cast-in-place concrete pile, and the fan-shaped column divided by the green edge on the right is the area governed by stress plate 2.

[0028] Thus, strain data of the stress gauge at different acquisition times, strain data sequences at acquisition times, and the area under the jurisdiction of the stress gauge are obtained.

[0029] Step S002: Designate any stress gauge on the concrete pile as the target stress gauge, the column containing the target stress gauge as the target column, and the row containing the target stress gauge as the target row. Mark adjacent columns one and two adjacent columns based on their proximity. Determine the first characteristic value of the target stress gauge in the target column at the acquisition time based on the difference in similarity between the strain data sequences of stress gauge positions in the same row within the target column, adjacent columns one, and adjacent columns one. Determine the target stress gauge's value at the acquisition time based on the difference in the changing trends of the strain data sequences of stress gauge positions in the same row within the target column and adjacent columns one. The second characteristic value is determined based on the difference between the strain data sequences of the target stress plate at adjacent acquisition times. The third characteristic value of the target stress plate at each acquisition time is determined based on the change trend of the stress data of the stress plate at adjacent acquisition times. The fourth characteristic value of each stress plate in the same row at the acquisition time is determined based on the difference between the prediction sequences of all stress plates in the same row at the same acquisition time. The complexity of the stress plate at the acquisition time is calculated based on the first, second, third and fourth characteristic values ​​of the stress plate at the acquisition time.

[0030] Any stress plate on the concrete cast-in-place pile is designated as the target stress plate, the column containing the target stress plate is designated as the target column, the row containing the target stress plate is designated as the target row, the first adjacent column of the column containing the target stress plate along the clockwise direction is designated as the adjacent column, and the second adjacent column of the column containing the target stress plate along the clockwise direction is designated as the adjacent column.

[0031] Since the stress data of stress gauges in the same column of a concrete cast-in-place pile should decrease with the increase of the depth of the stress gauge, and the strain data of stress gauges in corresponding rows of adjacent columns of a concrete cast-in-place pile have similar trends, the first characteristic value of the target stress gauge in the target column at the time of acquisition is determined based on the difference in the similarity between the strain data sequences of stress gauges in the same row in the target column, the adjacent column, and the two adjacent columns.

[0032] Preferably, in one embodiment of this application, the strain data sequences of all stress plates included in the target column at the acquisition time are arranged sequentially according to the spatial position of the stress plates from top to bottom to obtain the first sequence of the target column at the acquisition time. The strain data sequences of all stress plates included in an adjacent column at the acquisition time are arranged sequentially according to the spatial position of the stress plates from top to bottom to obtain the first sequence of the adjacent column at the acquisition time. The strain data sequences of all stress plates included in two adjacent columns at the acquisition time are arranged sequentially according to the spatial position of the stress plates from top to bottom to obtain the first sequence of the two adjacent columns at the acquisition time. The similarity between the first sequence of the target column and the first sequence of the adjacent column at the acquisition time is recorded as the first similarity of the target column at the acquisition time. The similarity between the first sequence of the adjacent column and the first sequence of the two adjacent columns at the acquisition time is recorded as the second similarity of the target column at the acquisition time. The absolute value of the difference between the first similarity and the second similarity of the target column at the acquisition time is recorded as the first difference of the target column at the acquisition time.

[0033] The strain data sequences of all stress plates in the target column (excluding the target stress plate) and the stress plates in the target row of the adjacent column at the acquisition time are arranged sequentially according to the spatial position of the stress plates from top to bottom. The second sequence of the target stress plate at the acquisition time is obtained. The similarity between the second sequence of the target stress plate at the acquisition time and the first sequence of the adjacent column at the acquisition time is recorded as the third similarity of the target stress plate at the acquisition time. The absolute value of the difference between the first similarity of the target column at the acquisition time and the third similarity of the target stress plate at the same acquisition time is recorded as the second difference of the target stress plate at the acquisition time.

[0034] The absolute value of the difference between the first difference of the target list at the acquisition time and the second difference of the target stress sheet at the same acquisition time is denoted as the first characteristic value of the target stress sheet at the acquisition time.

[0035] Preferably, as an embodiment of this application, cosine similarity is selected as the similarity measure of sequences. Implementers may use other methods of the prior art, such as Pearson correlation coefficient, to measure the similarity of different sequences. This application does not impose any special restrictions.

[0036] Based on the difference in the variation trend between the strain data sequence of the target column and the stress gauge position in the same row of the adjacent column, the second characteristic value of the target stress gauge in the target column at the acquisition time is determined.

[0037] Preferably, as an embodiment of this application, the stress data sequence of the target stress piece at the acquisition time is linearly fitted to obtain the slope of the fitted line, which is recorded as the stress slope of the target stress piece at the acquisition time. The stress slope of any stress piece at the acquisition time can be obtained using the same method. The stress slopes of all stress pieces in the same column at the same acquisition time are arranged sequentially according to their spatial position from top to bottom to obtain the stress slope sequence of the same column at the same acquisition time. The sum of the absolute values ​​of the differences between the target column and the corresponding stress slopes in the stress slope sequence of the adjacent column at the same acquisition time is recorded as the first slope difference of the target column at the same acquisition time. The stress slopes of all stress plates in the target column (excluding the target stress plate) and the stress plates in the target row of the adjacent column at the acquisition time are arranged sequentially according to the spatial position of the stress plates from top to bottom. The replacement sequence of the stress slope of the target stress plate at the acquisition time is obtained. The sum of the absolute values ​​of the differences between the replacement sequence of the stress slope of the target stress plate at the acquisition time and the corresponding stress slope in the stress slope sequence of the adjacent column at the same acquisition time is recorded as the second slope difference of the target stress plate at the same acquisition time.

[0038] The absolute value of the difference between the first slope difference of the target array at the acquisition time and the second slope difference of the target stress plate at the same acquisition time is denoted as the second characteristic value of the target stress plate at the acquisition time.

[0039] The difference between the strain data sequences of the target stress gauge at adjacent acquisition times is used to determine the third characteristic value of the target stress gauge at each acquisition time.

[0040] Preferably, in one embodiment of this application, the DTW distance between the strain data sequences of the target stress plate at adjacent acquisition times is denoted as the third characteristic value of the target stress plate at the later acquisition time among adjacent acquisition times. The calculation of the DTW distance is a well-known technique and will not be described in detail here.

[0041] Based on the changing trend of stress data of stress plates at adjacent first preset number of acquisition times, the prediction sequence of stress plates at each acquisition time is determined. Based on the difference between the prediction sequences of all stress plates in the same row at the same acquisition time, the fourth characteristic value of each stress plate in the same row at the acquisition time is determined.

[0042] The sequence of stress data collected by the stress gauge at the acquisition time and at a first preset number of adjacent acquisition times before the acquisition time is denoted as the prediction baseline sequence of the stress gauge at the acquisition time. A prediction algorithm is used to process the prediction baseline sequence of the stress gauge at the acquisition time to obtain the predicted values ​​of the stress data at the second preset number of adjacent acquisition times after the acquisition time. All predicted values ​​are then arranged sequentially according to the order of their corresponding acquisition times to obtain the prediction sequence of the stress gauge at the acquisition time. The sum of the DTW distances between the target stress gauge and the prediction sequences of all other stress gauges in the target row at the acquisition time is denoted as the fourth feature value of the target stress gauge at the acquisition time.

[0043] Specifically, in this embodiment, the first preset number is 400, and the second preset number is 20.

[0044] In this embodiment, the EMA algorithm is used for data prediction to obtain the predicted values ​​of stress data. The use of the EMA algorithm for data prediction is a well-known technique and will not be elaborated further. In practical applications, as other implementation methods, based on achieving the purpose of data prediction, implementers may use other existing methods such as the Autoregressive Model (AR), Moving Average Model (MA), Autoregressive Moving Average Model, Autoregressive Integral Moving Average Model (ARIMA), Seasonal Autoregressive Integral Moving Average Model (SARIMA), and exponential smoothing to achieve data prediction. This application does not impose any special limitations.

[0045] Based on the first, second, third, and fourth characteristic values ​​of the stress gauge at the same acquisition time, the complexity of the stress gauge at that same acquisition time is calculated. The formula for calculating the complexity is: ; in, Indicates stress sheet The complexity at acquisition time t; Indicates stress sheet The first characteristic value at acquisition time t; Indicates stress sheet The second characteristic value at acquisition time t; Indicates stress sheet The third characteristic value at acquisition time t; Indicates stress sheet The fourth characteristic value at acquisition time t; , These represent the preset first weight coefficient, second weight coefficient, and third weight coefficient, respectively. The sum of the first weight coefficient, second weight coefficient, and third weight coefficient is 1. In this embodiment, the values ​​of the first weight coefficient, second weight coefficient, and third weight coefficient are 0.3, 0.4, and 0.3, respectively. This represents the hyperbolic tangent function, which is used to normalize the values.

[0046] It should be noted that in the process of calculating complexity, only the values ​​of the first, second, third, and fourth characteristic values ​​of the stress plate at the same acquisition time are substituted into the above formula for calculation. That is, the result of the complexity calculation is a numerical value and is dimensionless.

[0047] It is important to understand that the first and second eigenvalues ​​are used to evaluate the overall variation and stability of the strain data of the corresponding stress gauge at different depths at the time of acquisition; the third eigenvalue is used to evaluate the similarity of the strain data of the corresponding stress gauge with that of the stress gauge at the same depth at the time of acquisition; the fourth eigenvalue is used to evaluate the similarity between the strain data of the corresponding stress gauge and that of the adjacent stress gauge at the time of acquisition. When the complexity of the stress gauge at the time of acquisition is greater, the mesh of the stress gauge's jurisdiction should be divided more densely when using the ABAQUS finite element model to divide the stress gauge's jurisdiction, and the weight of the mesh division of the stress gauge's jurisdiction should be smaller.

[0048] Thus, the complexity of each stress plate at each acquisition moment is obtained.

[0049] Step S003: Based on the complexity of the stress gauge at the time of acquisition, the area under the jurisdiction of the stress gauge is divided into grids, and the simulation of the bearing characteristics of the concrete cast-in-place pile is completed.

[0050] Based on the complexity of the stress gauge at the acquisition time, the partitioning weight of the stress gauge at the acquisition time is calculated. The formula for calculating the partitioning weight is: ; in, Indicates stress sheet The partitioning weights at acquisition time t; Indicates stress sheet The complexity at acquisition time t; This indicates the preset upper limit of the partitioning weight. In this embodiment, the upper limit of the partitioning weight is set to 0.8. This represents the preset lower limit of the partitioning weight. In this embodiment, the lower limit of the partitioning weight is set to 0.2.

[0051] The division weight of the stress plate at the acquisition time is used as the weight for meshing the area under the jurisdiction of the stress plate. The mesh of the area under the jurisdiction of the stress plate is divided using the mesh in the ABAQUS finite element model. Based on the bearing characteristics of the concrete cast-in-place pile, the bearing characteristics simulation of the concrete cast-in-place pile is completed.

[0052] When simulating the bearing characteristics of cast-in-place concrete piles using the mesh in the ABAQUS finite element model, it is also necessary to input material parameters and geometric parameters into the ABAQUS finite element model. Material parameters include soil density, Poisson's ratio, Young's modulus, internal friction angle, and cohesion, while geometric parameters include the diameter and length of the cast-in-place concrete pile. The acquisition of material and geometric parameters, as well as the meshing of the stress zone in the ABAQUS finite element model to simulate the bearing characteristics of cast-in-place concrete piles, are all well-known techniques and will not be elaborated further.

[0053] This completes the simulation of the bearing characteristics of cast-in-place concrete piles.

[0054] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A simulation method for the bearing characteristics of cast-in-place concrete piles applicable to power engineering construction, characterized in that, The method includes the following steps: Stress gauges are installed at different locations on the concrete pile, and strain data of the stress gauges are collected at different collection times. A strain data sequence of the stress gauges at the collection times is established, and the jurisdiction area is divided according to the spatial distribution of the stress gauges on the concrete pile. Any stress gauge on the concrete cast-in-place pile is designated as the target stress gauge, the column containing the target stress gauge is designated as the target column, and the row containing the target stress gauge is designated as the target row. Adjacent columns are labeled as "one column" and "two columns". Based on the difference in similarity between the strain data sequences of stress gauge positions in the same row within the target column, the one adjacent column, and the two adjacent columns, the first characteristic value of the target stress gauge in the target column at the acquisition time is determined. Based on the difference in the variation trend between the strain data sequences of stress gauge positions in the same row within the target column and the one adjacent column, the second characteristic value of the target stress gauge in the target column at the acquisition time is determined. Based on the differences between strain data sequences of the target stress gauge at adjacent acquisition times, the third characteristic value of the target stress gauge at each acquisition time is determined. Based on the changing trend of stress data of the stress gauge at adjacent acquisition times, the predicted sequence of the stress gauge at each acquisition time is determined. Based on the differences between the predicted sequences of all stress gauges in the same row at the same acquisition time, the fourth characteristic value of each stress gauge in the same row at the acquisition time is determined. Based on the first, second, third, and fourth characteristic values ​​of the stress gauge at the acquisition time, the complexity of the stress gauge at the acquisition time is calculated. Based on the complexity of the stress gauge at the time of acquisition, the area under the jurisdiction of the stress gauge is divided into grids, and the bearing characteristics of the concrete cast-in-place pile are simulated. The formula for calculating the complexity of the stress gauge at the time of data acquisition is: ； in, Indicates stress sheet The complexity at acquisition time t; These represent stress sheets. The first, second, third, and fourth eigenvalues ​​at acquisition time t; These represent the preset first weighting coefficient, second weighting coefficient, and third weighting coefficient, respectively. Represents the hyperbolic tangent function; The formula for calculating the partition weight is: ； in, Indicates stress sheet The partitioning weights at acquisition time t; Indicates stress sheet The complexity at acquisition time t; This indicates the preset upper limit of the partition weight; This indicates the preset lower limit of the partition weight.

2. The simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction according to claim 1, characterized in that, The boundaries of adjacent stress plates are symmetrical about the jurisdiction of adjacent stress plates.

3. The simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction according to claim 1, characterized in that, The specific marking method for adjacent columns and adjacent two columns is as follows: The first adjacent column of the target column in a clockwise direction is called the adjacent column, and the second adjacent column of the target column in a clockwise direction is called the adjacent column.

4. The simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction according to claim 1, characterized in that, The specific method for determining the first characteristic value of the target stress plate at the acquisition time is as follows: Based on the strain data sequences of all stress gauges contained in the target column, the adjacent column, and the two adjacent columns at the acquisition time, the first sequence of the target column, the adjacent column, and the two adjacent columns at the acquisition time is established respectively. The similarity between the target column and the first sequence of the adjacent column at the time of collection is denoted as the first similarity of the target column at the time of collection. The similarity between the first sequence of the adjacent column and the first sequence of the two adjacent columns at the time of collection is denoted as the second similarity of the target column at the time of collection. The absolute value of the difference between the first similarity and the second similarity of the target column at the time of collection is denoted as the first difference of the target column at the time of collection. Based on the strain data sequence of all stress gauges except the target stress gauge contained in the target column and the stress gauges in the target row in the adjacent column at the time of acquisition, a second sequence of the target stress gauge at the time of acquisition is established. The similarity between the second sequence of the target stress sheet at the acquisition time and the first sequence of the adjacent column at the acquisition time is denoted as the third similarity of the target stress sheet at the acquisition time. The absolute value of the difference between the first similarity of the target column at the acquisition time and the third similarity of the target stress sheet at the same acquisition time is denoted as the second difference of the target stress sheet at the acquisition time. The absolute value of the difference between the first difference of the target list at the acquisition time and the second difference of the target stress sheet at the same acquisition time is denoted as the first characteristic value of the target stress sheet at the acquisition time.

5. The simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction according to claim 1, characterized in that, The specific method for determining the second characteristic value of the target stress plate at the acquisition time is as follows: A linear fit is performed on the stress data sequence of the target stress plate at the acquisition time, and the slope of the fitted line is recorded as the stress slope of the target stress plate at the acquisition time; based on the stress slopes of all stress plates in the same column at the same acquisition time, a stress slope sequence of the same column at the same acquisition time is established. The sum of the absolute values ​​of the differences between the target column and the corresponding stress slope in the stress slope sequence at the same acquisition time is denoted as the first slope difference of the target column at the same acquisition time. Based on the stress slopes of all stress plates in the target column (excluding the target stress plate) and the stress plates in the target row of the adjacent column at the acquisition time, a stress slope replacement sequence for the target stress plate at the acquisition time is established. The sum of the absolute values ​​of the differences between the stress slope replacement sequence for the target stress plate at the acquisition time and the corresponding stress slopes in the stress slope sequence of the adjacent column at the same acquisition time is recorded as the second slope difference of the target stress plate at the same acquisition time. The absolute value of the difference between the first slope difference of the target array at the acquisition time and the second slope difference of the target stress plate at the same acquisition time is denoted as the second characteristic value of the target stress plate at the acquisition time.

6. The simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction according to claim 1, characterized in that, The specific method for determining the third characteristic value of the target stress plate at each acquisition time is as follows: The DTW distance between strain data sequences of the target stress gauge at adjacent acquisition times is denoted as the third characteristic value of the target stress gauge at the next acquisition time in adjacent acquisition times.

7. The simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction according to claim 1, characterized in that, The specific method for determining the fourth characteristic value of the stress plate at the acquisition time is as follows: Based on the stress data collected by the stress plate at the acquisition time and at a first preset number of adjacent acquisition times before the acquisition time, a prediction benchmark sequence of the stress plate at the acquisition time is established. The predicted values ​​of the stress data of the stress plate at a second preset number of adjacent acquisition times after the acquisition time are obtained, and a prediction sequence of the stress plate at the acquisition time is established. The sum of the DTW distances between the target stress patch and all other stress patches in the target row at the acquisition time is denoted as the fourth characteristic value of the target stress patch at the acquisition time.

8. The simulation method for bearing characteristics of cast-in-place concrete piles applicable to power engineering construction according to claim 1, characterized in that, The method for meshing the stress zone under the stress gauge's jurisdiction based on the complexity of the stress gauge at the time of acquisition and simulating the bearing characteristics of the concrete cast-in-place pile includes the following specific methods: Calculate the partitioning weight of the stress gauge at the acquisition time based on the complexity of the stress gauge at the acquisition time; The division weight of the stress plate at the acquisition time is used as the weight for meshing the area under the jurisdiction of the stress plate. The mesh of the area under the jurisdiction of the stress plate is divided using the mesh in the ABAQUS finite element model. Based on the bearing characteristics of the cast-in-place concrete pile, the bearing characteristics simulation of the cast-in-place concrete pile is completed.

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