Modular concrete member durability evaluation method based on big data

Abstract

The invention relates to the field of durability evaluation of concrete members, and particularly discloses a modular concrete member durability evaluation method based on big data, which analyzes the heat resistance of a concrete member in a high-temperature environment by comparing the performance of the concrete member and a simulation model thereof in the same high-temperature environment. Comparing the performance of the concrete member and the simulation model thereof in the same freezing and thawing environment, and analyzing the freezing resistance of the concrete member in the freezing and thawing environment; comparing the performance of the concrete member and the simulation model thereof in the same permeation environment, and analyzing the impermeability of the concrete member in the permeation environment; comparing the performance of the concrete member and the simulation model thereof under the same external force, and analyzing the wear resistance of the concrete member under the external force; and the concrete member durability is further comprehensively evaluated, and a theoretical model of the concrete member is combined with field detection, so that the rationality and credibility of a durability evaluation result of the concrete member are improved.

Description

Technical Field

[0001] The present invention relates to the field of durability performance evaluation of concrete components, and in particular to a modular concrete component durability performance evaluation method based on big data. Background Art

[0002] Concrete components refer to building components made of concrete. They have high compressive strength and are widely used in many infrastructures such as buildings, bridges, and water conservancy.

[0003] The evaluation of the durability of concrete components is of great significance as it can provide guidance for the design stage, ensure construction quality, predict the service life of buildings, and provide reference for building maintenance strategies.

[0004] However, the existing concrete component durability evaluation methods still have some limitations and shortcomings in practical applications.

[0005] For example, the existing Chinese patent with publication number CN113987814A discloses a method for evaluating the performance of concrete structures of existing nuclear safety-related plants, including the following steps: (1) dividing the existing nuclear safety-related plants into structural areas with different seismic requirements based on the safety risk of plant failure, and formulating different structural review standards; (2) conducting durability evaluation and strength analysis on the plants to determine the current mechanical properties and bearing capacity of the existing plant structural components; (3) determining the numerical calculation model of the existing nuclear safety-related plants, applying loads to the model, and then performing performance simulation calculations; (4) macroscopically evaluating the overall seismic performance of the existing nuclear safety-related plants based on the performance simulation calculation results. The method in this invention applies the concept of structural performance design to the greatest extent, so that the existing plants can continue to be put into use as much as possible, and plays a role in promoting the improvement of nuclear safety-related plant structural design technology.

[0006] The above patent uses theoretical models to deduce and evaluate, and conducts durability evaluation and strength analysis on factory buildings, but there are some shortcomings: First, the dimensions for evaluating the durability of concrete components are not diverse enough, and the durability of concrete components in various usage environments, such as temperature resistance, frost resistance, impermeability and wear resistance, are not analyzed, which makes the durability performance evaluation system of concrete components not perfect, and the reliability of the durability performance evaluation results is insufficient.

[0007] Secondly, the durability of concrete components is predicted only based on theoretical models, without combining the theoretical models with on-site tests. When evaluating the durability of concrete components, commonly used or fixed standards are used as the basis for evaluation. It is not considered that the requirements for the durability of concrete components vary depending on the severity of the use environment and the strength of concrete components. If it is impossible to know the expected durability performance of a concrete component under a certain use environment and compare it with the actual durability performance, it is impossible to make a reasonable and reliable evaluation of the durability of the concrete component. Summary of the invention

[0008] In view of the above problems, the present invention proposes a modular concrete component durability performance evaluation method based on big data. The specific technical scheme is as follows: A modular concrete component durability performance evaluation method based on big data comprises the following steps:

[0009] Step 1: Acquire concrete component information and build a simulation model: Obtain basic information about the concrete component, including information related to material properties, geometric shape and size information, boundary conditions and load information, and reinforcement information, and further build a simulation model of the concrete component.

[0010] Step 2. Heat resistance test of concrete components under high temperature environment: obtain the color change coefficient, crack development coefficient, and mass loss ratio of each module of the concrete component under various high temperature test experimental conditions, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding high temperature test experimental conditions to analyze the heat resistance evaluation coefficient of the concrete component under high temperature environment.

[0011] Step 3. Frost resistance test of concrete components under freeze-thaw environment: obtain the measured spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio of each module of the concrete component under each freeze-thaw test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding freeze-thaw test experimental conditions to analyze the frost resistance evaluation coefficient of the concrete component under the freeze-thaw environment.

[0012] Step 4. Test the impermeability of concrete components under a permeable environment: obtain the measured seepage area, seepage depth, and seepage form of each module of the concrete component under each permeability test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding permeability test experimental condition, and analyze the impermeability evaluation coefficient of the concrete component under the permeability environment.

[0013] Step 5. Wear resistance test of concrete components under external forces: obtain the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction of each module of the concrete component under each external force test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding external force test experimental conditions to analyze the wear resistance evaluation coefficient of the concrete component under external forces.

[0014] Step 6. Comprehensive evaluation and feedback on the durability performance of concrete components: Comprehensively evaluate the durability performance evaluation index of concrete components and provide feedback.

[0015] Compared with the prior art, the modular concrete component durability evaluation method based on big data described in the present invention has the following beneficial effects:

[0016] 1. The present invention collects various detailed information of concrete components and then constructs a simulation model of the concrete component, thereby improving the accuracy of the simulation model of the concrete component, so that the performance of the simulation model of the concrete component under the same environmental conditions as a basis for evaluating durability performance is more reliable.

[0017] 2. The present invention obtains multiple groups of experimental test data of concrete components under various use environment conditions, analyzes the heat resistance of concrete components in high temperature environment, frost resistance in freeze-thaw environment, impermeability in penetration environment, and wear resistance under external force, and then comprehensively evaluates the durability of concrete components, thereby improving the durability performance evaluation system of concrete components and improving the reliability of evaluation results.

[0018] 3. The present invention tests the actual durability performance of concrete components under various usage environments and compares it with the ideal durability performance of concrete component simulation models under the same usage environments, further comprehensively evaluates the durability performance of concrete components, combines the theoretical model of concrete components with on-site testing, and thus improves the rationality and credibility of the durability evaluation results of concrete components. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0020] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0021] Figure 2 This is a flow chart of the heat resistance test of concrete components under high temperature environment of the present invention.

[0022] Figure 3 The present invention is a flow chart of the frost resistance test of concrete components under freeze-thaw environment.

[0023] Figure 4 It is a flow chart of the test of the impermeability of concrete components under a permeable environment of the present invention.

[0024] Figure 5 The present invention is a flow chart of the wear resistance test of concrete components under external force. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0026] See also Figure 1 As shown, the present invention provides a modular concrete component durability performance evaluation method based on big data, comprising the following steps: Step 1, concrete component information acquisition and simulation model construction: obtain basic information of the concrete component, wherein the basic information includes information related to material properties, geometric shape and size information, boundary conditions and load information, and steel bar information, and further construct a simulation model of the concrete component.

[0027] It should be noted that the material properties of the concrete components include mechanical properties, stress-strain constitutive relationship, creep and shrinkage characteristics, material mix ratio, and water-cement ratio. Among them, mechanical properties include compressive strength, tensile strength, and elastic modulus; there are many stress-strain constitutive relationship models, such as linear elastic model, nonlinear elastic model, elastic-plastic model, etc.; material mix ratio refers to the ratio of cement, sand, gravel, water, and admixtures.

[0028] It should be noted that the geometric shape and size information of the concrete component includes the overall shape and size parameters, wherein the size parameters include length, width, height, thickness, etc.

[0029] It should be noted that the boundary conditions of the concrete component include but are not limited to fixed end constraints, hinge constraints, elastic support conditions, etc., and the loads of the concrete component include but are not limited to static loads, live loads, dynamic loads, cyclic loads, etc.

[0030] It should be noted that the steel bar information of the concrete component includes the steel bar arrangement method and the steel bar mechanical properties, wherein the steel bar arrangement method includes the position, spacing, number of limbs, etc. of various forms of steel bars, and the steel bar mechanical properties include the yield strength, ultimate strength and elastic modulus of the steel bars, etc.

[0031] It should be noted that the concrete component is a reinforced concrete component.

[0032] It should be noted that the simulation model of the concrete component is constructed using finite element analysis technology, micro-numerical simulation technology, computer graphics technology, etc.

[0033] It should be noted that the method of constructing a simulation model of a concrete component is an existing relatively mature technology and will not be described in detail here.

[0034] It should be noted that the concrete components subjected to high temperature test, freeze-thaw test, penetration test and external force test are not the same concrete components, but the parameters are exactly the same.

[0035] In this embodiment, the present invention collects various detailed information of concrete components and then constructs a simulation model of the concrete component, thereby improving the accuracy of the simulation model of the concrete component, so that the performance of the simulation model of the concrete component under the same environmental conditions is more referenceable as a basis for evaluating durability performance.

[0036] Step 2. Heat resistance test of concrete components under high temperature environment: obtain the color change coefficient, crack development coefficient, and mass loss ratio of each module of the concrete component under various high temperature test experimental conditions, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding high temperature test experimental conditions to analyze the heat resistance evaluation coefficient of the concrete component under high temperature environment.

[0037] As a preferred option, see Figure 2 As shown, the specific analysis process of step 2 includes: A1: setting the temperature ranges, heating rates, high temperature impact durations, and high temperature diffusion modes of the high temperature environment for testing the heat resistance of concrete components according to preset principles, and selecting and combining them to obtain various high temperature test experimental conditions.

[0038] It should be noted that the heat resistance test of concrete components in high temperature environment uses heating equipment that can provide a stable heat source.

[0039] In a specific embodiment, the temperature ranges of the high temperature environment may be 20°C-50°C, 50°C-100°C, 100°C-200°C, 200°C-500°C, etc.

[0040] It should be noted that the heating rate of the high temperature environment refers to the speed at which the temperature rises from the lower limit value to the upper limit value of the temperature range. In a specific embodiment, the heating rates of the high temperature environment can be 4°C, 6°C, 8°C, 10°C, etc. per minute.

[0041] It should be noted that the high temperature impact duration of the high temperature environment refers to the duration during which the temperature is maintained within the temperature range. In a specific embodiment, the high temperature impact duration of the high temperature environment can be 2 hours, 4 hours, 6 hours, 8 hours, etc.

[0042] It should be noted that the high temperature diffusion mode of the high temperature environment refers to the diffusion mode of the heat source in the concrete component. In a specific embodiment, the high temperature diffusion modes of the high temperature environment can be point diffusion mode, surface diffusion mode, overall diffusion mode, etc.

[0043] A2: Divide the concrete components according to the preset principles to obtain modules of the concrete components.

[0044] It should be noted that modular division of concrete components can be based on function or production method.

[0045] In a specific embodiment, the concrete components are divided into modules such as beams, slabs, columns, etc.

[0046] A3: Collect images of each module of the concrete component before and after the temperature change under each high temperature test experimental condition and compare and analyze them to obtain the color difference and discoloration area of ​​each module of the concrete component under each high temperature test experimental condition, and record them as i represents the number of the i-th module of the concrete component, i=1,2,...,n, j1 represents the number of the j1-th high temperature test experimental condition, j1=1,2,...,m1.

[0047] By analyzing the formula Obtain the color change coefficient of each module of the concrete component under various high temperature test conditions where δ Δα ,δ′ Δs They respectively represent the influence factors corresponding to the preset unit color difference and unit color change area.

[0048] It should be noted that as the temperature rises, the color of the concrete component will gradually change. In a specific embodiment, when the temperature reaches 100-200°C, the surface of the concrete component turns slightly white due to the evaporation of water; when the temperature reaches 300-400°C, the color of the concrete component will turn light gray, which is because the calcium hydroxide and other components in the concrete begin to decompose; when the temperature reaches 600-800°C, the concrete component will turn dark gray or even black, which is due to the large-scale decomposition of hydration products in the cement stone and the intensification of carbonization.

[0049] A4: Set each sampling time point during the high temperature test according to the preset equal time interval principle, obtain the maximum crack length, maximum crack width, and number of cracks at each sampling time point of each module of the concrete component under each high temperature test experimental condition, analyze the average growth rate of the crack length, crack width, and crack number of each module of the concrete component under each high temperature test experimental condition, and record them as By analyzing the formula The crack development coefficient of each module of the concrete component under various high temperature test conditions is obtained where v l ′、v′ w , v′ q They respectively represent the thresholds of the growth rate of the preset crack length, crack width, and crack number.

[0050] It should be noted that as the temperature continues to rise, the cracks on the surface of concrete components will gradually expand, widen and increase.

[0051] In a specific embodiment, the high temperature test of the concrete component starts from room temperature and the temperature is increased. At a lower temperature stage, such as 100-300°C, tiny cracks begin to appear in the concrete component in the form of hairlines and are mainly distributed on the surface of the component. At a higher temperature stage, such as 400-600°C, the cracks in the concrete component penetrate the entire surface of the component and the depth also increases.

[0052] A5: Obtain the mass loss ratio of each module of the concrete component under various high temperature test conditions through the detection instrument, and record it as

[0053] It should be noted that the mass loss ratio refers to the ratio between the mass loss amount and the initial mass.

[0054] It should be noted that as the temperature rises, concrete components will lose mass due to the evaporation of water and the decomposition of some chemical components. For example, at around 100°C, the mass loss is mainly caused by the evaporation of free water, and the mass loss ratio reaches 1%-3%; when the temperature rises to 300-500°C, the chemically bound water in the concrete begins to escape, and at the same time, components such as calcium hydroxide decompose, and the mass loss rate accelerates, reaching a mass loss ratio of 5%-10%.

[0055] As a preferred solution, the specific analysis process of step 2 further includes: converting each high temperature test experimental condition into a corresponding stress and applying it to the simulation model of the concrete component, analyzing the color change coefficient, crack development coefficient, and mass loss ratio predicted by each module in the simulation model of the concrete component under each high temperature test experimental condition, and recording them as

[0056] It should be noted that the method for analyzing the color change coefficient, crack development coefficient, and mass loss ratio predicted by each module in the concrete component simulation model under various high temperature test experimental conditions is the same as the method for analyzing the color change coefficient, crack development coefficient, and mass loss ratio actually measured by each module in the concrete component under various high temperature test experimental conditions. The heat resistance evaluation coefficient ξ1 of concrete components under high temperature environment is obtained, where ε i represents the weight of the preset concrete component module i, represents the weight of the preset j1th high temperature test experimental condition, They represent the preset color change coefficient, crack development coefficient, and weighting factor of mass loss ratio, respectively.

[0057] Step 3. Frost resistance test of concrete components under freeze-thaw environment: obtain the measured spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio of each module of the concrete component under each freeze-thaw test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding freeze-thaw test experimental conditions to analyze the frost resistance evaluation coefficient of the concrete component under the freeze-thaw environment.

[0058] As a preferred option, see Figure 3 As shown, the specific analysis process of step three includes: B1: taking the mass fraction of freeze-thaw medium, the temperature range of the freezing stage, the temperature range of the melting stage, the cooling rate of the freezing stage, the heating rate of the melting stage, the duration of freeze-thaw, and the number of freeze-thaw cycles as the variables of the freeze-thaw environment, and adjusting and setting the variables of the freeze-thaw environment multiple times according to the preset principles to obtain the experimental conditions of each freeze-thaw test.

[0059] It should be noted that the frost resistance test of concrete components in a freeze-thaw environment uses special equipment that can automatically control the freeze-thaw cycle process. The equipment should be able to make the concrete components cycle in the specified low and high temperature ranges.

[0060] In a specific embodiment, the mass fraction of the freeze-thaw medium may be 3%, 4%, or 5%.

[0061] In a specific embodiment, the lowest temperature in the freezing stage may be -20°C, -18°C, or -16°C, and the highest temperature in the melting stage may be 3°C, 5°C, or 7°C.

[0062] In a specific embodiment, the temperature reduction rate or the temperature increase rate may be 0.2° C. / h, 0.5° C. / h, or 1° C. / h.

[0063] In a specific embodiment, the freeze-thaw duration can be 8 hours, 12 hours, or 16 hours.

[0064] In a specific embodiment, the number of freeze-thaw cycles can be 25 times, 50 times, or 100 times.

[0065] B2: Obtain the measured spalling area of ​​each module of the concrete component under each freeze-thaw test experimental condition and record it as j2 represents the number of the j2th freeze-thaw test experimental condition, j2=1,2,...,m2.

[0066] B3: Obtain the mass loss ratio of each module of the concrete component under each freeze-thaw test experimental condition through the detection instrument, and record it as

[0067] B4: The relative dynamic elastic modulus reduction ratio of each module of the concrete component under each freeze-thaw test experimental condition is detected by ultrasonic instrument and recorded as

[0068] It should be noted that the relative dynamic elastic modulus reduction ratio refers to the ratio between the decrease in the relative dynamic elastic modulus and the initial relative dynamic elastic modulus.

[0069] In a specific embodiment, when the relative dynamic elastic modulus decreases to 60% of the initial value, the frost resistance of the concrete member is considered to have failed.

[0070] As a preferred solution, the specific analysis process of step three also includes: converting each freeze-thaw test experimental condition into a corresponding stress and applying it to the simulation model of the concrete component, analyzing the spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio predicted by each module in the concrete component simulation model under each freeze-thaw test experimental condition, and recording them as

[0071] It should be noted that the method of analyzing the predicted spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio of each module in the concrete component simulation model under each freeze-thaw test experimental condition and the method of analyzing the measured spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio of each module of the concrete component under each freeze-thaw test experimental condition have the same principle.

[0072] By analyzing the formula

[0073]

[0074] The frost resistance evaluation coefficient ξ2 of concrete components under freeze-thaw environment is obtained, where represents the weight of the preset j2th freeze-thaw test experimental condition, e represents a natural constant, γ1, γ2, and γ3 represent weight factors of preset spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio, respectively, and γ1+γ2+γ3=1.

[0075] Step 4. Test the impermeability of concrete components under a permeable environment: obtain the measured seepage area, seepage depth, and seepage form of each module of the concrete component under each permeability test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding permeability test experimental condition, and analyze the impermeability evaluation coefficient of the concrete component under the permeability environment.

[0076] As a preferred option, see Figure 4 As shown, the specific analysis process of step four includes: C1: taking the seepage pressure and the seepage time as the variables of the seepage environment, and adjusting and setting the variables of the seepage environment multiple times according to the preset principles to obtain the experimental conditions of each seepage test.

[0077] It should be noted that the concrete impermeability tester is used in the permeability test of concrete components under permeable environment.

[0078] In a specific embodiment, the water seepage pressure can be 0.1 MPa, 0.2 MPa, 0.3 MPa, 0.4 MPa, 0.5 MPa, 0.6 MPa, 0.7 MPa, 0.8 MPa, 0.9 MPa, 1.0 MPa, etc.

[0079] In a specific embodiment, the water seepage time can be 1h, 2h, 3h, 4h, 5h, 6h, 7h, 8h, 9h, 10h, etc.

[0080] C2: Obtain the water seepage area and water seepage depth of each module of the concrete component under each permeability test experimental condition, and record them as j3 represents the number of the j3th penetration test experimental condition, j3=1,2,...,m3.

[0081] C3: Obtain the water seepage forms measured for each module of the concrete component under each permeability test experimental condition, set the influencing factors corresponding to each water seepage form, and screen out the influencing factors corresponding to the water seepage forms measured for each module of the concrete component under each permeability test experimental condition, and record them as

[0082] It should be noted that the water seepage forms include but are not limited to point, line or surface shapes.

[0083] As a preferred solution, the specific analysis process of step 4 also includes: converting each penetration test experimental condition into a corresponding stress and applying it to the simulation model of the concrete component, analyzing the influencing factors corresponding to the water seepage area, water seepage depth, and water seepage morphology predicted by each module in the concrete component simulation model under each penetration test experimental condition, and recording them as

[0084] It should be noted that the method of analyzing the influencing factors corresponding to the seepage area, seepage depth, and seepage morphology predicted by each module in the concrete component simulation model under each penetration test experimental condition and the method of analyzing the influencing factors corresponding to the measured seepage area, seepage depth, and seepage morphology of each module in the concrete component under each penetration test experimental condition have the same principle.

[0085] By analyzing the formula

[0086]

[0087] The evaluation coefficient ξ3 of the impermeability of concrete components under the permeability environment is obtained, where Represents the weight of the preset j3rd penetration test experimental condition, λ1, λ2, and λ3 represent weight factors corresponding to preset seepage area, seepage depth, and seepage form, respectively, and λ1+λ2+λ3=1.

[0088] Step 5. Wear resistance test of concrete components under external forces: obtain the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction of each module of the concrete component under each external force test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding external force test experimental conditions to analyze the wear resistance evaluation coefficient of the concrete component under external forces.

[0089] As a preferred option, see Figure 5 As shown, the specific analysis process of step five includes: D1: taking the loading force, friction speed, action time, and friction medium particle size as the variables of the external force, and adjusting and setting the variables of the external force for multiple times according to the preset principles to obtain the experimental conditions for each external force test.

[0090] It should be noted that an abrasion testing machine is used to test the wear resistance of concrete components under external forces.

[0091] In a specific embodiment, the loading force may be 120N, 130N, 140N, 150N, 160N, etc.

[0092] In a specific embodiment, the friction speed may be 68 rpm, 70 rpm, 72 rpm, 74 rpm, etc.

[0093] In a specific embodiment, the duration of action can be 1h, 2h, 3h, 4h, 5h, etc.

[0094] In a specific embodiment, the particle size of the friction medium can be 0.1 mm, 0.5 mm, 1.0 mm, 1.5 mm, 2.0 mm, etc.

[0095] D2: Obtain the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction of each module of the concrete component under each external force test experimental condition, and record them as j4 represents the number of the j4th external force test experimental condition, j4=1,2,...,m4.

[0096] As a preferred solution, the specific analysis process of step 5 further includes: converting each external force test experimental condition into a corresponding stress and applying it to the simulation model of the concrete component, analyzing the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction predicted by each module in the concrete component simulation model under each external force test experimental condition, and recording them as

[0097] It should be noted that the method for analyzing the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction predicted by each module in the concrete component simulation model under each external force test experimental condition is the same as the method for analyzing the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction measured by each module in the concrete component under each external force test experimental condition.

[0098] The wear resistance evaluation coefficient ξ4 of the concrete component under external force is obtained, where represents the weight of the preset j4th external force test experimental condition,

[0099] Step 6. Comprehensive evaluation and feedback on the durability performance of concrete components: Comprehensively evaluate the durability performance evaluation index of concrete components and provide feedback.

[0100] As a preferred solution, the specific analysis process of step six is: weighted average calculation of the heat resistance evaluation coefficient of concrete components in high temperature environment, the frost resistance evaluation coefficient of concrete components in freeze-thaw environment, the impermeability evaluation coefficient of concrete components in permeable environment, and the wear resistance evaluation coefficient of concrete components under external force are performed to obtain the durability performance evaluation index of the concrete components and provide feedback.

[0101] It should be noted that the weights of the heat resistance evaluation coefficient of concrete components in high temperature environment, the frost resistance evaluation coefficient of concrete components in freeze-thaw environment, the impermeability evaluation coefficient of concrete components in permeable environment, and the wear resistance evaluation coefficient of concrete components under external force are set values, and the cumulative sum is 1.

[0102] It should be noted that the heat resistance evaluation coefficient, frost resistance evaluation coefficient, impermeability evaluation coefficient, wear resistance evaluation coefficient and durability performance evaluation index of the concrete component are sent during feedback.

[0103] In this embodiment, the present invention obtains multiple groups of experimental test data of concrete components under various usage environment conditions, analyzes the heat resistance of concrete components in a high temperature environment, the frost resistance in a freeze-thaw environment, the impermeability in a penetration environment, and the wear resistance under external forces, and then comprehensively evaluates the durability of concrete components, thereby improving the durability evaluation system of concrete components and improving the reliability of the evaluation results.

[0104] In this embodiment, the present invention further comprehensively evaluates the durability of concrete components by testing the actual durability performance of concrete components under various usage environments and comparing it with the ideal durability performance of a simulation model of the concrete components under the same usage environment, and combines the theoretical model of concrete components with on-site testing, thereby improving the rationality and credibility of the durability evaluation results of concrete components.

[0105] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A modular concrete component durability evaluation method based on big data, characterized in that: The steps include: Step 1: Acquisition of concrete component information and construction of simulation model: Acquisition of basic information of concrete components, including information related to material properties, geometric shape and size information, boundary conditions and load information, and reinforcement information, and further construction of a simulation model of the concrete component; Step 2: Heat resistance test of concrete components under high temperature environment: obtain the color change coefficient, crack development coefficient, and mass loss ratio of each module of the concrete component under each high temperature test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding high temperature test experimental condition, and analyze the heat resistance evaluation coefficient of the concrete component under high temperature environment; Step 3: Frost resistance test of concrete components under freeze-thaw environment: obtain the measured spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio of each module of the concrete component under each freeze-thaw test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding freeze-thaw test experimental condition, and analyze the frost resistance evaluation coefficient of the concrete component under the freeze-thaw environment; Step 4: Test the impermeability of concrete components under a permeable environment: Obtain the water seepage area, water seepage depth, and water seepage form of each module of the concrete component under each permeability test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding permeability test experimental condition, and analyze the impermeability evaluation coefficient of the concrete component under the permeability environment; Step 5. Wear resistance test of concrete components under external force: obtain the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction of each module of the concrete component under each external force test experimental condition, and compare them with the corresponding information predicted by the concrete component simulation model under the corresponding external force test experimental condition, and analyze the wear resistance evaluation coefficient of the concrete component under external force; Step 6. Comprehensive evaluation and feedback on the durability performance of concrete components: Comprehensively evaluate the durability performance evaluation index of concrete components and provide feedback.

2. The method for evaluating the durability of modular concrete components based on big data according to claim 1 is characterized in that: The specific analysis process of step 2 includes: A1: According to the preset principles, various temperature ranges, various heating rates, various high temperature impact durations, and various high temperature diffusion modes of the high temperature environment for testing the heat resistance of concrete components are set, and selected and combined to obtain various high temperature test experimental conditions; A2: Divide the concrete components according to the preset principles to obtain modules of the concrete components; A3: Collect images of each module of the concrete component before and after the temperature change under each high temperature test experimental condition and compare and analyze them to obtain the color difference and discoloration area of ​​each module of the concrete component under each high temperature test experimental condition, and record them as i represents the number of the i-th module of the concrete component, i=1,2,...,n, j1 represents the number of the j1-th high temperature test experimental condition, j1=1,2,...,m1; By analyzing the formula Obtain the color change coefficient of each module of the concrete component under various high temperature test conditions where δ Δα , δ Δ ' s Respectively represent the influence factors corresponding to the preset unit color difference and unit color change area; A4: Set each sampling time point during the high temperature test according to the preset equal time interval principle, obtain the maximum crack length, maximum crack width, and number of cracks at each sampling time point of each module of the concrete component under each high temperature test experimental condition, analyze the average growth rate of the crack length, crack width, and crack number of each module of the concrete component under each high temperature test experimental condition, and record them as By analyzing the formula The crack development coefficient of each module of the concrete component under various high temperature test conditions is obtained where v l ′、v′ w , v′ q Respectively represent the thresholds of the growth rate of the preset crack length, crack width, and crack number; A5: Obtain the mass loss ratio of each module of the concrete component under various high temperature test conditions through the detection instrument, and record it as 3. The method for evaluating the durability of modular concrete components based on big data according to claim 2 is characterized by: The specific analysis process of step 2 also includes: Each high temperature test experimental condition is converted into corresponding stress and applied to the simulation model of the concrete component. The color change coefficient, crack development coefficient and mass loss ratio predicted by each module in the simulation model of the concrete component under each high temperature test experimental condition are analyzed and recorded as By analyzing the formula The heat resistance evaluation coefficient ξ1 of concrete components under high temperature environment is obtained, where ε i represents the weight of the preset concrete component module i, represents the weight of the preset j1th high temperature test experimental condition, They represent the preset color change coefficient, crack development coefficient, and weighting factor of mass loss ratio, respectively.

4. The method for evaluating the durability of modular concrete components based on big data according to claim 3 is characterized by: The specific analysis process of step three includes: B1: The mass fraction of freeze-thaw medium, the temperature range of the freezing stage, the temperature range of the melting stage, the cooling rate of the freezing stage, the heating rate of the melting stage, the duration of freeze-thaw, and the number of freeze-thaw cycles are taken as the variables of the freeze-thaw environment, and the variables of the freeze-thaw environment are adjusted and set multiple times according to the preset principles to obtain the experimental conditions of each freeze-thaw test; B2: Obtain the measured spalling area of ​​each module of the concrete component under each freeze-thaw test experimental condition and record it as j2 represents the number of the j2th freeze-thaw test experimental condition, j2=1,2,...,m2; B3: Obtain the mass loss ratio of each module of the concrete component under each freeze-thaw test experimental condition through the detection instrument, and record it as B4: The relative dynamic elastic modulus reduction ratio of each module of the concrete component under each freeze-thaw test experimental condition is detected by ultrasonic instrument and recorded as 5. The method for evaluating the durability of modular concrete components based on big data according to claim 4 is characterized by: The specific analysis process of step three also includes: Each freeze-thaw test experimental condition is converted into corresponding stress and applied to the simulation model of the concrete component. The spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio predicted by each module in the concrete component simulation model under each freeze-thaw test experimental condition are analyzed and recorded as By analyzing the formula The frost resistance evaluation coefficient ξ2 of concrete components under freeze-thaw environment is obtained, where represents the weight of the preset j2th freeze-thaw test experimental condition, e represents a natural constant, γ1, γ2, and γ3 represent weight factors of preset spalling area, mass loss ratio, and relative dynamic elastic modulus reduction ratio, respectively, and γ1+γ2+γ3=1.

6. The modular concrete component durability evaluation method based on big data according to claim 3 is characterized by: The specific analysis process of step 4 includes: C1: Taking the seepage pressure and seepage duration as the variables of the seepage environment, and adjusting and setting the variables of the seepage environment multiple times according to the preset principles, to obtain the experimental conditions of each seepage test; C2: Obtain the water seepage area and water seepage depth of each module of the concrete component under each permeability test experimental condition, and record them as j3 represents the number of the j3th penetration test experimental condition, j3=1,2,...,m3; C3: Obtain the water seepage forms measured for each module of the concrete component under each permeability test experimental condition, set the influencing factors corresponding to each water seepage form, and screen out the influencing factors corresponding to the water seepage forms measured for each module of the concrete component under each permeability test experimental condition, which are recorded as η ij3 .

7. The method for evaluating the durability of modular concrete components based on big data according to claim 6 is characterized by: The specific analysis process of step 4 also includes: Each penetration test experimental condition is converted into corresponding stress and applied to the simulation model of the concrete component. The influencing factors corresponding to the water seepage area, water seepage depth and water seepage morphology predicted by each module in the simulation model of the concrete component under each penetration test experimental condition are analyzed and recorded as By analyzing the formula The evaluation coefficient ξ3 of the impermeability of concrete components under the permeability environment is obtained, where Represents the weight of the preset j3rd penetration test experimental condition, λ1, λ2, and λ3 represent weight factors corresponding to preset seepage area, seepage depth, and seepage form, respectively, and λ1+λ2+λ3=1.

8. The modular concrete component durability evaluation method based on big data according to claim 3 is characterized by: The specific analysis process of step 5 includes: D1: The loading force, friction speed, action time, and friction medium particle size are used as variables of external force, and the variables of external force are adjusted and set multiple times according to the preset principles to obtain the experimental conditions of each external force test; D2: Obtain the wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction of each module of the concrete component under each external force test experimental condition, and record them as j4 represents the number of the j4th external force test experimental condition, j4=1,2,...,m4.

9. The method for evaluating the durability of modular concrete components based on big data according to claim 8, characterized in that: The specific analysis process of step 5 also includes: Each external force test experimental condition is converted into corresponding stress and applied to the simulation model of the concrete component. The wear mark depth, mass loss ratio, compressive strength reduction, and tensile strength reduction predicted by each module in the concrete component simulation model under each external force test experimental condition are analyzed and recorded as By analyzing the formula The wear resistance evaluation coefficient ξ4 of the concrete component under external force is obtained, where represents the weight of the preset j4th external force test experimental condition, 10. The modular concrete component durability evaluation method based on big data according to claim 1, characterized in that: The specific analysis process of step six is: weighted average calculation of the heat resistance evaluation coefficient of concrete components in high temperature environment, the frost resistance evaluation coefficient of concrete components in freeze-thaw environment, the impermeability evaluation coefficient of concrete components in permeable environment, and the wear resistance evaluation coefficient of concrete components under external force are performed to obtain the durability performance evaluation index of concrete components and provide feedback.

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