Embedded part bearing capacity analysis method based on analog simulation technology

Abstract

The invention belongs to the technical field of embedded part bearing capacity simulation analysis, and discloses an embedded part bearing capacity analysis method based on an analog simulation technology, which comprises the following steps of: arranging a plurality of layers of latticed detection point arrays from the connecting position between a steel beam main body and a concrete main body to the tail end point of an embedded part in a concrete block; collecting response data of the detection points; and in combination with stress space distribution, response duration and microscopic evolution data of early cracks on the concrete surface, carrying out comprehensive data analysis and judgment on the bearing capacity under the load influence range. According to the method, the multi-layer latticed detection point array is arranged at the tail end point, extending to the embedded part in the concrete block, of the connecting position, and multi-dimensional data fusion analysis is performed, so that the accuracy and reliability of bearing capacity evaluation are improved, and the defects of insufficient local detection and single-dimensional evaluation of a traditional method are overcome.

Description

Technical Field

[0001] The invention belongs to the technical field of embedded part bearing capacity simulation analysis, and relates to an embedded part bearing capacity analysis method based on simulation technology. Background Art

[0002] In many fields of modern engineering construction, embedded parts are widely used. They usually refer to components pre-buried during the construction of concrete structures or other foundation structures. Their main function is to provide reliable anchor points for subsequent structural connections, equipment fixation, component support, etc., to ensure the stability and safety of the entire engineering structure.

[0003] In order to ensure that these embedded parts can effectively play the role of connection and support in actual application, it is particularly important to accurately evaluate their bearing capacity. Traditional embedded part bearing capacity assessment mainly relies on physical testing, which has significant drawbacks such as high cost, long cycle time, and high destructiveness. With the rapid development of computer technology, the application of simulation technology in the engineering field is becoming increasingly widespread. The embedded part bearing capacity analysis method based on simulation technology, by establishing precise mathematical models and numerical calculation methods, can identify potential weak points in the design stage, avoid structural risks caused by design defects, and can efficiently and non-destructively predict structural performance. It has gradually become an important research direction in the engineering field.

[0004] Despite this, existing simulation and analysis methods for embedded component bearing capacity have the following shortcomings: First, the rationality and density of the detection point layout directly affect the accuracy of bearing capacity assessment. Existing methods only set up a single layer of detection points near the connection, resulting in the bearing capacity analysis being limited to a local area and ignoring the stress propagation effect in concrete under load. The actual range affected by the load has a certain spatial distribution. Relying solely on local single-point data for analysis makes it difficult to fully reflect the true bearing capacity of the structure, which in turn affects the accuracy and reliability of the ultimate bearing capacity assessment.

[0005] Secondly, after the detection points are arranged, the load responses of the detection points need to be collected to evaluate the bearing performance. In the existing technology, the evaluation dimension of the load response only focuses on the stress value of the embedded parts themselves as the only criterion for bearing performance, ignoring the coordinated analysis of key factors such as the response time and the microevolution of early cracks. It cannot fully reflect the overall response behavior of the embedded parts and the surrounding concrete under load, resulting in limitations in the evaluation of the ultimate bearing capacity. Summary of the Invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a method for analyzing the bearing capacity of embedded parts based on simulation technology is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a method for analyzing the bearing capacity of embedded parts based on simulation technology, including: S1. Obtaining the material structure, three-dimensional geometric parameters and bolt connection specifications of the steel beam body and the concrete body containing embedded parts, thereby establishing a simulation model including steel beams, embedded parts and concrete structures.

[0008] S2. In the established simulation model, a multi-layer grid-like detection point array is formed by extending and expanding along the periphery at preset intervals with the connection position between the steel beam body and the concrete body as the center.

[0009] S3. Determine the allowable load range based on the material structure of the concrete containing embedded parts. Divide the allowable load range into increasing load levels. Apply loads step by step in the simulation model. After each load application, synchronously collect response data from the detection point array, including the stress, response time, and an image of the concrete surface state.

[0010] S4. Calculate the stress spatial distribution of each test point based on the response data of each test point under each load level, thereby determining the load influence range.

[0011] S5. Determine the critical bearing capacity based on the response data of the test points under different loads within the load influence range, and integrate the critical values ​​of all test points to generate the ultimate bearing capacity envelope diagram of the steel beam and concrete embedded parts.

[0012] S6. After determining the critical bearing capacity of the detection point, monitor the concrete crack growth to determine the direction of concrete collapse.

[0013] Compared with the prior art, the present invention has the following beneficial effects: (1) By arranging a multi-layer grid-like detection point array extending from the connection position between the steel beam body and the concrete body to the end point of the embedded part in the concrete block, the present invention fully considers the propagation effect of stress in the concrete under the action of load, and the spatial distribution characteristics of the actual range affected by the load, and more accurately reflects the actual bearing performance of the entire structure based on the data of the multi-layer detection point array.

[0014] (2) The present invention combines the spatial distribution of stress, response time and the microscopic evolution data of early cracks on the concrete surface to conduct a comprehensive data analysis to determine the bearing capacity under the load influence range, thereby achieving a comprehensive evaluation of the overall response behavior of the embedded parts and the surrounding concrete under load, and improving the accuracy and reliability of the judgment of the ultimate bearing capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 The present invention is a flowchart of the steps for implementing the method.

[0017] Figure 2 This is a modeling effect diagram of the present invention on simulation software.

[0018] Figure 3 This is a flow chart for determining the load influence range of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] See also Figure 1 As shown, the present invention provides a method for analyzing the bearing capacity of embedded parts based on simulation technology, including: S1. obtaining the material structure, three-dimensional geometric parameters and bolt connection specifications of the steel beam body and the concrete body containing embedded parts, thereby establishing a simulation model including steel beams, embedded parts and concrete structures.

[0021] It should be noted that the material structure of the steel beam body includes the steel type and mechanical properties, including yield strength, tensile strength, elastic modulus, etc. The material structure of the concrete body with embedded parts includes the concrete grade and the steel type and mechanical properties of the embedded parts.

[0022] The three-dimensional geometric parameters of the steel beam body include cross-sectional shape and dimensional parameters, including height, width, flange thickness, web thickness, etc. The three-dimensional geometric parameters of the concrete body with embedded parts include the overall dimensions of the concrete component, including length, width, and height, the location, orientation, and number of embedded parts, and the specific geometric dimensions of each embedded part, including diameter and length, etc.

[0023] The bolt connection specifications are diameter, length, and thread type and pitch.

[0024] Obtaining the material structure, three-dimensional geometric parameters, and connection specifications of the above materials can ensure that the simulation model is consistent with its actual shape and size, and reflects the actual engineering structure as accurately as possible.

[0025] Use modeling software to perform three-dimensional geometric modeling of the steel beam body and the concrete body including embedded parts to generate a modeling body consistent with its actual shape and size.

[0026] Import the 3D geometric models of the steel beam body and the concrete body with embedded parts into the finite element analysis software, model the bolt connections based on the bolt connection specifications, and import them into the finite element model as separate components.

[0027] Visualize embedded parts within the host concrete model.

[0028] By visualizing the embedded parts, it is possible to ensure that the relative relationship of the position, orientation, and arrangement of the embedded parts in the concrete body is reflected in the simulation model, and the hierarchical division of the detection point array of the concrete body containing the embedded parts is more intuitive.

[0029] Based on accurate simulation models, different design schemes can be tested and optimized in a virtual environment, and the impact of various factors on structural performance can be evaluated, thereby achieving safer and more economical design schemes, shortening the development cycle, and reducing R&D costs.

[0030] S2. In the established simulation model, a multi-layer grid-like detection point array is formed by extending and expanding along the periphery at preset intervals with the connection position between the steel beam body and the concrete body as the center.

[0031] See Figure 2 As shown in the figure, the bolt connection position is taken as the starting point, and the end point of the embedded part in the concrete block is defined as the end point.

[0032] On the straight line from the starting point to the end point, a series of level points are evenly distributed according to the length of the straight line.

[0033] It should be noted that the equidistant distribution ensures that the spacing between the points at each level is consistent, so that there is a certain regularity and comparability when collecting the response data of each detection point. By setting the level points at equal intervals on the straight line from the starting point to the end point, it can ensure comprehensive coverage along the distribution path of the embedded parts in the concrete.

[0034] For each level point, a rectangular grid-shaped detection point array is evenly distributed on the concrete plane where it is located.

[0035] Specifically, the grid size of the rectangular grid detection point array can be obtained by dividing the level point spacing by an integer factor. This integer factor determines the number of grids set within the influence range of a level point. For example, if the level point spacing is 100mm and you want to set 10 grids within this distance, the size of each grid will be 10mm.

[0036] More specifically, a detection point is set at the center of each rectangular grid to record response data, which can ensure the uniformity and representativeness of data collection.

[0037] This arrangement helps to evaluate the load transfer path from the steel beam to the concrete and its efficiency.

[0038] S3. Determine the allowable load range based on the material structure of the concrete containing embedded parts. Divide the allowable load range into increasing load levels. Apply loads step by step in the simulation model. After each load application, synchronously collect response data from the detection point array, including the stress, response time, and an image of the concrete surface state.

[0039] It should be noted that the allowable load range is determined as follows: basic structural data of the concrete material containing embedded parts is obtained, including the number of anchor bars, the cross-sectional area of ​​a single anchor bar, the yield strength of the anchor bar, the compressive strength of the concrete, and the tensile strength of the concrete;

[0040] The pull-out bearing capacity of embedded parts is calculated based on the structural foundation data of concrete materials containing embedded parts. In the formula, represents the number of anchor bars, represents the cross-sectional area of ​​a single anchor bar, represents the yield strength of the anchor bar, and represents the safety reduction factor for factors such as the quality of the concrete cover and the anchorage length.

[0041] Calculate the maximum allowable load N based on the pull-out bearing capacity of embedded parts u =e*A s *d y *η*υ, where e represents the number of anchor bars, A s Represents the cross-sectional area of ​​a single anchor bar, d y It represents the yield strength of the anchor bar, η represents the safety reduction factor for factors such as the quality of the concrete cover and the anchorage length, and its value generally ranges from 0.7 to 0.9, and υ represents the safety factor, which is usually 0.8 to 0.9, to ensure that there is still sufficient safety margin under extreme conditions.

[0042] In the specific embodiment of the above formula, the number of anchor bars is 4, the diameter of a single anchor bar is 20 mm, and the cross-sectional area of ​​a single anchor bar is 314 mm according to the area formula of a circle. 2 If the anchor material is HRB400, its yield strength is 400MPa, the safety reduction factor is 0.85, and the safety factor is 0.85. According to the above formula, the allowable maximum value of the embedded part in the concrete structure containing embedded parts is approximately 363.6kN.

[0043] The initial stress state caused by the deadweight of the steel beam is taken as the lower limit of the allowable load range.

[0044] Specifically, the initial stress state caused by the deadweight of the steel beam body is calculated based on the specific size of the steel beam and the density of the steel used. The calculated deadweight of the steel beam is evenly distributed over the entire steel beam according to its length, and the finite element method is used to calculate the stress distribution caused by the deadweight.

[0045] The entire allowable load range is divided into two ranges: low load response area and high load response area.

[0046] Specifically, the allowable load range is divided according to the yield strength of the anchor bar. The low load response zone is defined as the range from the lower limit of the allowable load range to the yield strength of the anchor bar, and the high load response zone is defined as the range from the yield strength of the anchor bar to the maximum allowable load.

[0047] Different load change sensitive parameters are used for different load response areas, as follows: a) In the low load response area, the preset load change sensitive parameters are used; b) In the high load response area, a multiple of the preset load change sensitive parameters in the low load response area is selected as its load change sensitive parameter.

[0048] Different load change sensitive parameters are used according to different load response areas to correspond to a predetermined number of load levels.

[0049] It should be noted that the load in the low-load response area responds more slowly and has smaller differences to the concrete body containing embedded parts, which makes the load change perception in the low-load response area relatively slow, and avoids frequent unnecessary adjustments due to slight fluctuations in the load. The load in the high-load response area responds more quickly and has larger differences to the concrete body containing embedded parts, and makes a more refined response to the load change in the high-load response area.

[0050] The high load response area and low load response area are divided into various load levels using the exponential function formula Where i represents the load level number, i=1,2,......,n, L i Indicates the i-th load level, L min Indicates the minimum load value in the load response area, L max It represents the maximum load value of the load response area, n represents the number of load levels predetermined in the load response area, and a represents the load change sensitive parameter.

[0051] The exponential part of the formula Controls the rate at which the load level increases.

[0052] In one example, the allowable load range is 50N-200N, and the low load response area is divided into 50N-100N and the high load response area is divided into 100N-200N.

[0053] Since the load in the low load response area responds slowly and has a smaller difference to the concrete body containing embedded parts, while the load in the high load response area responds quickly and has a larger difference to the concrete body containing embedded parts, the number of load levels set in the low load response area is lower than that in the high load response area. Specifically, the number of load levels set in the low load response area is 4, and the load change sensitive parameter is 0.5. The number of load levels set in the high load response area is 5, and the load change sensitive parameter can be set to 2.

[0054] The load levels calculated using the above formula are shown in Table 1.

[0055] Table 1: Load level classification results

[0056]

[0057] The load levels obtained by dividing the high load response area and the low load response area are summarized and formed into increasing load levels in order from small to large.

[0058] It should be noted that by subdividing the allowable load range into different load levels and using different load change sensitivity parameters, a refined analysis of the structure's behavior under different load levels can be achieved, which helps to more accurately identify the structure's performance under different stress states.

[0059] Start the simulation run and start the timing function each time a new load level is applied.

[0060] During the simulation process, the stress data of each detection point is collected in real time, and the stress data at the current moment is compared with the data at the previous moment. If the difference between the stress data at the current moment and the data at the previous moment in two consecutive time steps is less than the preset limit difference, the stress data at the current moment is determined as the stable stress value under the load level.

[0061] It should be noted that in the initial stage of load application, the structure may exhibit transient responses. These transient effects may cause large fluctuations in stress data. After the structure reaches a stable state, its stress distribution and magnitude tend to be stable, which improves the reliability and accuracy of the collected stress data.

[0062] For each detection point, the time difference from the moment the load is applied to the moment the stress stabilizes is recorded, and this is used as the response duration of the detection point at that load level.

[0063] By recording the time required for stress to stabilize, we can understand the dynamic response characteristics of materials or structures under different loads, which helps to analyze the internal structural changes and stress propagation of the material.

[0064] The concrete surface state image is generated synchronously when the stress is determined to be stable.

[0065] It should be noted that compared with pure numerical data, images provide a more intuitive way to display information. Concrete surface state images can help capture early signs of damage. Under different load levels, by comparing the grayscale value changes in the concrete surface state images, it is possible to identify whether the target detection point has reached its critical bearing capacity.

[0066] By applying loads in increasing levels, we can simulate the gradual loads a structure will experience during actual use. This helps to more accurately assess the performance of the structure at different load levels and avoid structural damage or simulation failure caused by applying excessive loads all at once. Simultaneously collecting stress, response time, and concrete surface condition images at the test points comprehensively captures the structure's response characteristics under different load levels.

[0067] S4. Calculate the stress spatial distribution of each test point based on the response data of each test point under each load level, thereby determining the load influence range.

[0068] After each load is applied, the stress and response time of each test point are marked in the model.

[0069] Use cloud charts to display the stress distribution of each test point under different levels of load.

[0070] Specifically, the simulation data results are imported into the drawing tool provided by the simulation software, and the appropriate drawing type is selected as "cloud map". The color mapping rules are set as needed, and different colors are usually used to represent different stress intervals.

[0071] It should be noted that by analyzing the generated cloud map, observing the stress concentration area, maximum and minimum stress values ​​and their locations, and combining the response time, a comprehensive judgment can be made on the performance of the structure under different loads.

[0072] See also Figure 3 As shown, a stress threshold and a response time threshold are defined. When the stress of a detection point exceeds the stress threshold, the detection point is considered to be affected by the load. When the response time of a detection point is lower than the response time threshold, the detection point is considered to be affected by the load.

[0073] It should be noted that stress thresholds identify critical areas that may be damaged by overload and are usually set based on the yield strength or safety factor of the material. For example, if the yield strength of a material is known to be d y , the stress threshold can be set to 0.6d y ~0.8d y After multiple simulation experiments, it was found that the stress at the detection point tends to stabilize within approximately 5 to 15 seconds after the load is applied. Therefore, an intermediate value of 10 seconds can be selected as the response time threshold.

[0074] The determination of the response time threshold and the stress threshold can quickly determine the load influence of each detection point, that is, the shorter the response time, the more significant the influence, otherwise it is not affected; the greater the stress, the more significant the influence, otherwise it is not affected.

[0075] The two indicators of stress and response time can more comprehensively reflect the impact of load on the monitoring point, thereby effectively avoiding the one-sidedness of the test that may be caused by a single influencing indicator.

[0076] The ratio of the number of affected detection points to the total number of detection points in each layer of the detection point array is calculated to obtain the proportion of stress-affected points and the proportion of response time-affected points in each layer.

[0077] It should be noted that by calculating the proportion of stress influencing points and the proportion of response time influencing points, the load influence index of each layer is calculated, which makes the judgment of the load influence range more data-supported.

[0078] The load influence index of each layer is calculated based on the proportion of stress influence points of each layer and the proportion of response time influence points of each layer. Where k represents the level number, k=1,2,......,N,t k Indicates the proportion of response time influencing points in the kth layer, f k It represents the proportion of stress influencing points in the kth layer, μ represents the weight coefficient of the proportion of response time influencing points, θ represents the weight coefficient of the proportion of stress influencing points, and N represents the number of layers.

[0079] It should be noted that for each layer, the weighted sum of the response time influencing point ratio and the stress influencing point ratio is calculated. The weight coefficient reflects the relative importance of the response time influencing point ratio and the stress influencing point ratio. The weighted sum of all layers is added and divided by the total number of layers to obtain the load influence index for each layer.

[0080] Suppose there is a structure with three layers, and the proportion of response time influencing points and stress influencing points of each layer are as follows: first layer: the proportion of response time influencing points and the proportion of stress influencing points are 0.2 and 0.4 respectively, second layer: the proportion of response time influencing points and the proportion of stress influencing points are 0.3 and 0.5 respectively, third layer: the proportion of response time influencing points and the proportion of stress influencing points are 0.1 and 0.6 respectively.

[0081] Assuming that the weight coefficients are 0.5 and 0.5 respectively, the load influence index of the structure is 0.35 according to the above formula.

[0082] Through the load influence index of each layer, the overall response of the structure under different load conditions can be quantitatively evaluated, providing a scientific basis for engineering design, maintenance and optimization.

[0083] The load influence index of each layer is compared with the preset influence threshold. If the load influence index of a layer is greater than the preset influence threshold, the layer is considered to be affected by the load.

[0084] It should be noted that the impact threshold is set according to the safety specifications and standards in the industry to ensure that the structure can withstand the expected maximum load without failure throughout its service life, and reliably determine that the layer is indeed affected by the load.

[0085] Select all levels affected by the load and arrange them in order from the starting point to the end point, and then take the embedded parts range between these levels as the load influence range.

[0086] This approach allows precise identification of critical areas of the structure that are significantly affected by the loads.

[0087] By statistically analyzing the stress spatial distribution of each test point, we can clearly see the areas that are subjected to greater stress under different load conditions, providing data support for subsequent bearing capacity analysis.

[0088] S5. Determine the critical bearing capacity based on the response data of the test points under different loads within the load influence range, and integrate the critical values ​​of all test points to generate the ultimate bearing capacity envelope diagram of the steel beam and concrete embedded parts.

[0089] The same detection points within the load influence range under different load levels are selected as common detection points.

[0090] By screening common inspection points, the same location under different load conditions can be accurately evaluated. This not only ensures the comparability of the data, but also significantly improves the consistency of the data, ultimately making the obtained critical bearing capacity more accurate and reliable.

[0091] Collect the concrete surface state image corresponding to each common detection point.

[0092] Each collected concrete surface state image is denoised and converted into a grayscale image. The grayscale value of each pixel is extracted and compared with the set grayscale threshold. If the grayscale value of a pixel in the concrete surface state image of a common detection point under a certain load level reaches the grayscale threshold, the detection point is recorded as the target detection point, the load level is recorded as the target load level, and the pixel is recorded as the target pixel.

[0093] It should be noted that for applications such as crack detection, grayscale images can better highlight texture changes and defects on the material surface. The visibility of these features can be enhanced by adjusting the grayscale level. Crack-free areas usually present a relatively uniform grayscale distribution, while cracks will cause obvious grayscale jumps due to changes in depth and width.

[0094] Specifically, cracks typically appear as a series of continuous pixels in an image, whose grayscale values ​​differ significantly from those of the surrounding intact areas. By setting a reasonable grayscale threshold, pixels that may represent cracks can be distinguished, effectively locating the crack location. The grayscale threshold can be set by observing the peaks or valleys between crack pixels and non-crack pixels in the grayscale histogram of the image as the grayscale threshold. For example, using an 8-bit grayscale representation (grayscale values ​​range from 0 to 255), a threshold between 50 and 100 can be selected as a preliminary attempt.

[0095] Analyze whether the grayscale value of the target pixel point in the concrete surface state image of the next load level corresponding to the target load level of the target detection point continues to exceed the grayscale threshold. If it continues to exceed the grayscale threshold, the target load level is used as the critical bearing capacity of the target detection point, thereby obtaining the critical bearing capacity of each detection point.

[0096] It should be noted that if the grayscale value of a certain pixel exceeds the set grayscale threshold under two or more consecutive load levels, it indicates that cracks at that location are initiating, that is, cracks have begun to form, and the generated cracks have reached the critical bearing capacity.

[0097] On the concrete plane corresponding to each level point, the detection points belonging to the same critical bearing capacity are connected to form a smooth ultimate bearing capacity envelope diagram.

[0098] It should be noted that by drawing the ultimate bearing capacity envelope diagram, the maximum bearing capacity of the entire structure or a specific area at different locations can be intuitively displayed.

[0099] S6. After determining the critical bearing capacity of the detection point, monitor the concrete crack growth to determine the direction of concrete collapse.

[0100] Each concrete surface state image collected after the common detection point corresponds to the critical bearing capacity is converted into a grayscale image, and the edge detection algorithm is used to obtain the extension direction and crack width of the concrete crack.

[0101] It should be noted that each concrete surface state image after the critical bearing capacity is collected to analyze the extension direction and width of the cracks, evaluate the health status of the concrete structure, and identify possible safety hazards.

[0102] Specifically, the edge detection algorithm is a technology used to identify the boundaries of objects in an image. The Sobel operator focuses on calculating the gradient value in the horizontal or vertical direction, and determines the crack width by measuring the distance between the edge points on both sides of the crack.

[0103] The coordinates of the edge points of the concrete crack are used as sample data, its covariance matrix is ​​calculated, and the eigenvalues ​​and eigenvectors of the covariance matrix are obtained. The eigenvector corresponding to the largest eigenvalue is the main direction of the concrete crack.

[0104] Obtain the extension direction of concrete cracks to quantitatively determine the main expansion direction of cracks on the structure surface.

[0105] Taking a reference direction on the concrete surface as a reference, the angle between the main direction of the concrete crack and the reference direction is calculated and recorded as the extension direction of the concrete crack.

[0106] When the extension direction of concrete cracks mainly extends rapidly in a certain direction and the crack width in this direction continues to increase, the direction of final concrete collapse is obtained.

[0107] It's important to note that cracks begin to form and grow in areas of concentrated stress within a structure. Once a crack begins to expand, it continues along the direction of greatest stress. Concrete has limited fracture toughness. When a crack expands in its most vulnerable direction and increases in width, it indicates that the material in that direction can no longer withstand the additional stress and is approaching its ultimate bearing capacity.

[0108] When the extension direction of concrete cracks mainly extends rapidly in a certain direction and the crack width in that direction continues to increase, this usually means that factors such as stress concentration, material weakening and energy release in that direction work together, causing the stability of the structure in that direction to drop sharply, and may eventually lead to the collapse of the structure in this direction.

[0109] By monitoring the direction of crack development, it is possible to identify in advance the specific location and method where the structure may fail first, and formulate a more effective maintenance plan.

[0110] The parameters involved in the above formula are all dimensionless and calculated numerically. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0111] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0112] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0113] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0114] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0115] Finally, 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 in the scope of protection of the present invention.

Claims

1. A method for analyzing the bearing capacity of embedded parts based on simulation technology, characterized in that: The steps include: S1. Obtain the material structure, three-dimensional geometric parameters, and bolt connection specifications of the steel beam body and the concrete body including embedded parts, thereby establishing a simulation model including the steel beam, embedded parts, and concrete structure; S2. In the established simulation model, a multi-layer grid array of detection points is formed, with the connection position between the steel beam body and the concrete body as the center and extending along its periphery at a preset interval; S3. Determine the allowable load range based on the material structure of the concrete containing embedded components, divide the allowable load range into increasing load levels, apply loads step by step in the simulation model, and synchronously collect response data from the detection point array after each load application, including the stress, response time, and an image of the concrete surface condition; S4. Calculate the stress spatial distribution of each test point based on the response data of each test point under each load level, thereby determining the load influence range; S5. Determine the critical bearing capacity based on the response data of the test points under different loads within the load influence range, and integrate the critical values ​​of all test points to generate the ultimate bearing capacity envelope diagram of the steel beam and concrete embedded parts.

2. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 1, characterized in that: The specific contents of establishing the simulation model including steel beams, embedded parts and concrete structure are as follows: Use modeling software to perform three-dimensional geometric modeling of the steel beam body and the concrete body including embedded parts to generate a modeling body consistent with its actual shape and size; Import the 3D geometric models of the steel beam body and the concrete body with embedded parts into the finite element analysis software, model the bolt connections based on the bolt connection specifications, and import them into the finite element model as separate components; Visualize embedded parts within the host concrete model.

3. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 1, characterized in that: In the established simulation model, a multi-layer grid-like detection point array is formed with the connection position between the steel beam body and the concrete body as the center and extended along the periphery at a preset interval. The specific contents are as follows: Taking the bolt connection position as the starting point, the end point of the embedded part in the concrete block is defined as the end point; On the straight line from the starting point to the end point, a series of level points are evenly distributed according to the length of the straight line; For each level point, a rectangular grid-shaped detection point array is evenly distributed on the concrete plane where it is located.

4. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 1, characterized in that: The allowable load range is determined based on the material structure of the concrete containing embedded parts, and the allowable load range is divided into increasing load levels. The specific contents are as follows: The entire allowable load range is divided into two ranges: low load response range and high load response range; Different load change sensitivity parameters are used for different load response areas, as follows: a) Corresponding to the preset load change sensitive parameters in the low load response area; b) selecting, in the high load response area, a multiple of the load change sensitive parameter preset in the low load response area as its load change sensitive parameter; Different load change sensitive parameters are used according to different load response areas to correspond to the predetermined number of load levels; The low load response area and high load response area are divided into various load levels using the exponential function formula Where i represents the load level number, i=1,2,......,n, L i Indicates the i-th load level, L min Indicates the minimum load value in the load response area, L max represents the maximum load value of the load response area, n represents the number of load levels predetermined in the load response area, and a represents the load change sensitive parameter; The load levels obtained by dividing the low load response area and the high load response area are summarized and formed into increasing load levels in order from small to large.

5. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 4 is characterized in that: The response data of each detection point is collected synchronously after each load is applied, including the stress, response time and concrete surface state image. The specific contents are as follows: Start the simulation and start the timing function each time a new load level is applied; During the simulation process, the stress data of each detection point is collected in real time, and the stress data at the current moment is compared with the data at the previous moment. If the difference between the stress data at the current moment and the data at the previous moment within two consecutive time steps is less than the preset limit difference, the stress data at the current moment is determined as the stable stress value under the load level; For each test point, record the time difference from the moment the load is applied to the moment the stress stabilizes, and use this as the response time of the test point at that load level; The concrete surface state image is generated synchronously when the stress is determined to be stable.

6. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 1, characterized in that: The specific content of the stress spatial distribution statistics of each detection point based on the response data of each detection point under each load level is as follows: After each load is applied, the stress and response time of each detection point are marked in the model; Use cloud charts to display the stress distribution of each test point under different levels of load.

7. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 1, characterized in that: The specific contents of determining the load influence range based on the response data of each detection point under each load level are as follows: Define a stress threshold and a response time threshold. When the stress at a detection point exceeds the stress threshold, the detection point is considered to be affected by the load. When the response time of a detection point is lower than the response time threshold, the detection point is considered to be affected by the load. Count the ratio of the number of affected detection points to the total number of detection points in each layer of the detection point array to obtain the proportion of stress-affected points and the proportion of response time-affected points in each layer; The load influence index of each layer is calculated based on the proportion of stress influence points of each layer and the proportion of response time influence points of each layer. Where k represents the level number, k=1,2,......,N,t k Indicates the proportion of response time influencing points in the kth layer, f k represents the proportion of stress influencing points in the kth layer, μ represents the weight coefficient of the proportion of response time influencing points, θ represents the weight coefficient of the proportion of stress influencing points, and N represents the number of layers; Compare the load influence index of each layer with the preset influence threshold. If the load influence index of a layer is greater than the preset influence threshold, the layer is considered to be affected by the load. Select all levels affected by the load and arrange them in order from the starting point to the end point, and then take the embedded parts range between these levels as the load influence range.

8. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 1, characterized in that: The specific content of determining the critical bearing capacity based on the response data of the detection points under different loads within the load influence range is as follows: The same detection points within the load influence range under different load levels are selected as common detection points; Collect the concrete surface state image corresponding to each common detection point; Each collected concrete surface state image is denoised and converted into a grayscale image. The grayscale value of each pixel is extracted and compared with the set grayscale threshold. If the grayscale value of a pixel in the concrete surface state image at a common detection point under a certain load level reaches the grayscale threshold, the detection point is recorded as the target detection point, the load level is recorded as the target load level, and the pixel is recorded as the target pixel. Analyze whether the grayscale value of the target pixel point in the concrete surface state image of the next load level corresponding to the target load level of the target detection point continues to exceed the grayscale threshold. If it continues to exceed the grayscale threshold, the target load level is used as the critical bearing capacity of the target detection point, thereby obtaining the critical bearing capacity of the common detection point.

9. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 3, characterized in that: The specific steps of integrating the critical values ​​of all detection points to generate the ultimate bearing capacity envelope diagram of steel beams and concrete embedded parts are as follows: On the concrete plane corresponding to each level point, the detection points belonging to the same critical bearing capacity are connected to form a smooth ultimate bearing capacity envelope diagram.

10. The method for analyzing the bearing capacity of embedded parts based on simulation technology according to claim 8, characterized in that: The method further includes S6. After determining the critical bearing capacity of the detection point, monitoring the growth of concrete cracks is performed to determine the direction of concrete collapse. The specific contents are as follows: Each concrete surface state image collected after the common detection point corresponds to the critical bearing capacity is converted into a grayscale image, and the extension direction and crack width of the concrete crack are obtained using the edge detection algorithm; The coordinates of the edge points of the concrete crack are used as sample data to calculate its covariance matrix, and the eigenvalues ​​and eigenvectors of the covariance matrix are obtained. The eigenvector corresponding to the largest eigenvalue is the main direction of the concrete crack. Taking a reference direction on the concrete surface as a reference, the angle between the main direction of the concrete crack and the reference direction is calculated and recorded as the extension direction of the concrete crack; When the extension direction of concrete cracks mainly extends rapidly in a certain direction and the crack width in this direction continues to increase, the direction of final concrete collapse is obtained.

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