A numerical simulation method for predicting the life of freeze-thaw concrete based on the depth of spalling layer

Abstract

The present invention discloses a numerical simulation method for predicting the lifespan of freeze-thaw concrete based on the depth of the spalling layer. This method relates to the field of concrete technology and includes obtaining concrete material parameters using preset rules to establish a two-dimensional concrete numerical model; assigning material properties to the model, deleting damaged and failed portions, calculating the corresponding spalling layer limit, and meshing the processed two-dimensional concrete numerical model; calculating the temperature and stress fields based on the ambient temperature and the meshed model; performing a full numerical simulation of the two-dimensional concrete numerical model after deleting the damaged and failed portions based on the spalling layer limit, temperature field, and stress field to obtain the maximum number of freeze-thaw cycles; and predicting the lifespan of freeze-thaw concrete based on the maximum number of freeze-thaw cycles and the amplitude and rate of change of ambient temperature in the predicted area. The present invention enables lifespan prediction for freeze-thaw concrete.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete, and more particularly to a numerical simulation method for predicting the life of freeze-thaw concrete based on the depth of a spalling layer. Background Art

[0002] For a long time, people have generally focused on studying the bearing capacity of reinforced concrete structures. However, in extreme environments, the problems caused by concrete's lack of durability are even more severe, especially in the high-altitude cold regions of Northeast my country and the cold saline environment of Northwest China, where concrete durability issues are more prominent. Freeze-thaw is a long and slow process. During this process, the protective layer of concrete on the surface of the building is continuously peeled off, resulting in the internal steel bars being exposed and corroded. The bearing capacity of the components continues to decline, reducing the safety and usability of the building, and in severe cases, causing certain economic losses and casualties. Therefore, to maintain the stability and long-term applicability of concrete structures, it is crucial to ensure the durability of concrete.

[0003] In cold climates, concrete structures undergo repeated freeze-thaw cycles. When the pores within the concrete reach 75% to 90% saturation, the water within the pores freezes and expands, generating significant hydrostatic pressure and causing cracks in the surrounding concrete. Initially, tiny cracks may only appear between pores or near isolated pores. However, as the freeze-thaw cycles continue, these microcracks gradually develop and interconnect. Ultimately, after multiple freeze-thaw cycles, large areas of the concrete surface will spall, forming inward-extending cracks. Over time, these cracks continue to expand and spread deeper, destroying the integrity and continuity of the concrete, weakening its mechanical properties, and ultimately causing serious damage to the concrete structure.

[0004] Most research on concrete freeze-thaw durability, both domestically and internationally, remains limited to laboratory conditions. Systematic studies examining the effects of long-term freeze-thaw cycles on concrete structures in real-world engineering environments are insufficient. In my country, many critical infrastructure projects, including nuclear power plants and road and bridge infrastructure, are located in cold regions. These facilities face long-term freeze-thaw threats to their safe service life. However, current durability design for critical structures with a design service life exceeding 50 years largely relies on empirical data, and comprehensive methods for assessing concrete freeze-thaw durability and lifespan have yet to be established.

[0005] Therefore, how to predict the life of freeze-thaw concrete is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0006] In view of this, the present invention provides a numerical simulation method for predicting the life of freeze-thaw concrete based on the depth of the spalling layer, thereby realizing the life prediction of freeze-thaw concrete.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A numerical simulation method for predicting the life of freeze-thaw concrete based on the depth of the spalling layer includes:

[0009] Acquire concrete material parameters based on the concrete material using preset rules, and establish a two-dimensional concrete numerical model using the concrete material parameters;

[0010] Assigning material properties to the two-dimensional concrete numerical model according to the preset rules, then deleting damaged and failed parts based on the failure criterion, calculating the spalling layer limit according to the coordinates and number of damaged and failed parts, and meshing the processed two-dimensional concrete numerical model;

[0011] Calculate the temperature field based on the ambient temperature and the two-dimensional concrete numerical model divided into grids to obtain the temperature field; calculate the thermal stress according to the temperature change of the temperature field to establish the stress field;

[0012] According to the spalling layer limit, temperature field and stress field, a full-process numerical simulation of a two-dimensional concrete numerical model is performed after the damaged and failed parts are deleted to obtain the maximum freeze-thaw times;

[0013] The freeze-thaw concrete life is predicted based on the maximum freeze-thaw times, the predicted range and rate of change of the ambient temperature in the area.

[0014] Preferably, the concrete material parameters include: concrete specimen size, aggregate type, gradation, volume fraction, compressive strength, tensile strength, elastic modulus, thermal conductivity, surface heat dissipation coefficient of mortar and aggregate, elastic modulus, thermal expansion coefficient, specific heat capacity and thermal conductivity of pores.

[0015] Preferably, the establishment of the two-dimensional concrete numerical model specifically includes: establishing aggregates, pores, ITZ and mortar according to concrete material parameters in combination with the Monte Carlo method by writing Python language and randomly placing them; during the placement process, judging whether there is interference between aggregates and pores until the placement is successful and the expected aggregate volume fraction is achieved; using Boolean functions to cut out unfilled spaces in the geometric model and fill them with mortar to establish the two-dimensional concrete numerical model.

[0016] Preferably, the temperature-dependent pore equivalent expansion coefficient assigned in the material property assignment is specifically expressed as follows:

[0017]

[0018] in, is the number of freeze-thaw cycles; E is the expansion coefficient of the pores, is the current temperature; is the reference temperature.

[0019] Preferably, the failure criteria specifically include: when the tensile equivalent plastic strain of the concrete exceeds the critical value corresponding to the peak tensile stress; when the compressive equivalent plastic strain of the concrete exceeds the preset threshold corresponding to the process of decreasing from the peak stress to 40% level.

[0020] Preferably, in obtaining the temperature field and establishing the stress field, the temperature field adopts a first-order three-node linear heat transfer triangle unit under heat transfer; the stress field adopts a first-order plane stress unit, that is, a three-node linear plane strain triangle unit.

[0021] Preferably, the temperature field is applied to the model in the form of a cosine function with a freeze-thaw cycle of 4 hours, and the temperature range is +7 to -17°C.

[0022] Through the above technical solutions, it can be seen that compared with the existing technology, the present invention discloses a numerical simulation method for predicting the life of freeze-thaw concrete based on the depth of the spalling layer, establishes a two-dimensional concrete numerical model for the influence of concrete strength grade, air content and prestress on the freeze-thaw durability of concrete, can consider the time-varying characteristics of the performance of each component of concrete, and address the pain points of long cycle and high economic cost of freeze-thaw physical tests, overcome the main technical bottleneck of the homogenization assumption of existing numerical simulation technology, and provide ideas for solving the current concrete freeze-thaw durability design and evaluation methods; can more accurately predict the location of freeze-thaw concrete damage and crack development mode, can provide an effective tool for concrete life prediction, and provide reasonable suggestions for establishing and improving concrete durability design; starting from the freeze-thaw damage mechanism, focusing on the hydrostatic pressure generated by the freezing and expansion of pore water in the concrete specimen, and combining the amplitude and rate of ambient temperature changes in different regions, more accurately predict the freeze-thaw durability degradation law of concrete under different environmental action levels in different regions, and propose a life prediction model to provide a basis for actual durability design. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0024] Figure 1 A flowchart of the numerical simulation of concrete durability under freeze-thaw cycles based on the equivalent temperature method and thermal convection theory provided by the present invention;

[0025] Figure 2A diagram of a two-dimensional mesoscopic numerical simulation model and a schematic diagram of its grid division provided by the present invention;

[0026] Figure 3 A schematic diagram of the temperature load magnitude that varies with time and is consistent with the laboratory loading conditions provided by the present invention;

[0027] FIG4( a ) is a 1-hour temperature distribution diagram of concrete provided by the present invention;

[0028] FIG4( b ) is a 2 h temperature distribution diagram of the concrete provided by the present invention;

[0029] FIG4( c ) is a 3-hour temperature distribution diagram of the concrete provided by the present invention;

[0030] FIG4( d ) is a 4-hour temperature distribution diagram of the concrete provided by the present invention;

[0031] FIG4( e ) is a temperature rise curve diagram of the concrete center and surface provided by the present invention;

[0032] Figure 5 A schematic diagram of concrete damage development with increasing freeze-thaw cycles provided by the present invention;

[0033] FIG6( a ) is a first verification comparison diagram of the spalling layer depth and the relative dynamic elastic modulus provided by the present invention;

[0034] FIG6( b ) is a second verification comparison diagram of the spalling layer depth and the relative dynamic elastic modulus provided by the present invention;

[0035] FIG6( c ) is a third verification comparison diagram of the spalling layer depth and the relative dynamic elastic modulus provided by the present invention;

[0036] FIG7( a ) is a graph showing the effect of concrete strength grade on freeze-thaw durability of concrete provided by the present invention;

[0037] FIG7( b ) is a graph showing the effect of air content of C40 concrete on freeze-thaw durability of concrete provided by the present invention;

[0038] FIG7( c ) is a graph showing the effect of air content of C45 concrete on freeze-thaw durability of concrete provided by the present invention;

[0039] FIG7( d ) is a graph showing the effect of prestressing on freeze-thaw durability of concrete provided by the present invention;

[0040] FIG8( a ) is a concrete life prediction diagram for a D-1 environmental action level and a 30 mm protective layer thickness provided by the present invention;

[0041] FIG8( b ) is a concrete life prediction diagram for a D-1 environmental action level and a 35 mm protective layer thickness provided by the present invention;

[0042] FIG9( a ) is a concrete life prediction diagram for a D-2 environmental action level and a 30 mm protective layer thickness provided by the present invention;

[0043] FIG9( b ) is a concrete life prediction diagram for a D-2 environmental action level and a 35 mm protective layer thickness provided by the present invention;

[0044] FIG10( a ) is a concrete life prediction diagram for a D-3 environmental action level and a 30 mm protective layer thickness provided by the present invention;

[0045] FIG10( b ) is a graph showing the lifespan prediction of concrete with a protective layer thickness of 35 mm and a D-3 environmental action level provided by the present invention;

[0046] Figure 11 A schematic diagram of the prestressed loading method provided by the present invention;

[0047] Figure 12 This is a flow chart of the overall life prediction model provided by the present invention. DETAILED DESCRIPTION

[0048] 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.

[0049] The embodiment of the present invention discloses a numerical simulation method for predicting the freeze-thaw durability of concrete based on the depth of the spalling layer. Based on the heat transfer and heat exchange principle inside the concrete under the action of freeze-thaw cycles, the pore expansion theory, and the equivalent temperature theory, a numerical simulation method for predicting the freeze-thaw durability of concrete is provided. Figure 12 Shown, including:

[0050] Acquire concrete material parameters based on the concrete material using preset rules, and establish a two-dimensional concrete numerical model using the concrete material parameters;

[0051] Assigning material properties to the two-dimensional concrete numerical model according to the preset rules, then deleting damaged and failed parts based on the failure criterion, calculating the spalling layer limit according to the coordinates and number of damaged and failed parts, and meshing the processed two-dimensional concrete numerical model;

[0052] Calculate the temperature field based on the ambient temperature and the two-dimensional concrete numerical model divided into grids to obtain the temperature field; calculate the thermal stress according to the temperature change of the temperature field to establish the stress field;

[0053] According to the spalling layer limit, temperature field and stress field, a full-process numerical simulation of a two-dimensional concrete numerical model is performed after the damaged and failed parts are deleted to obtain the maximum freeze-thaw times;

[0054] The freeze-thaw concrete life is predicted based on the maximum freeze-thaw times, the predicted range and rate of change of the ambient temperature in the area.

[0055] The freeze-thaw concrete lifespan is predicted based on the degree of concrete damage after different freeze-thaw cycles, the average annual freeze-thaw cycles in the predicted area, and the ambient cooling rate. The average annual freeze-thaw cycles in different regions are estimated based on the average temperature of the coldest month. The concrete durability is predicted based on the proportional relationship between freeze-thaw concrete damage under indoor laboratory conditions established with the ambient cooling rate as a bridge and natural conditions on site.

[0056] The 2D concrete numerical model includes four phases: mortar, ITZ, aggregate, and pores. Based on pore expansion theory, the pores are assigned a thermal expansion coefficient, causing them to expand and contract with temperature changes, thereby simulating the freeze-thaw cycle of pore water within concrete.

[0057] In one specific embodiment, concrete material parameters are obtained using preset rules based on the concrete laboratory quick freezing method requirements and relevant data of each microscopic component and freeze-thaw cycle specified in the standard GB / T 50082-2009 "Test Methods for Long-term Properties and Durability of Ordinary Concrete." The relevant parameters of each microscopic component of the concrete are read, including the concrete specimen size, aggregate type, gradation, volume fraction, and the compressive strength, tensile strength, elastic modulus, thermal expansion coefficient, thermal conductivity, surface heat dissipation coefficient, and specific heat capacity of the mortar and aggregate. The aggregate gradation and volume fraction are determined using the Fuller gradation curve; the heat dissipation coefficient of the specimen surface is determined based on the convective heat transfer coefficient of the concrete surface. The mechanical parameters (strength, elastic modulus) and thermal parameters (specific heat capacity, thermal conductivity) of the concrete specimen obtained through testing are used.

[0058] In a specific embodiment, the material properties of a two-dimensional concrete numerical model were assigned using preset rules, taking into account the water-to-ice phase transition of water in the concrete pores under the action of freeze-thaw cycles, which in turn causes pore volume expansion and concrete damage. A systematic study of the concrete pore expansion behavior under freeze-thaw cycles was conducted and compared with the results obtained from existing experiments. After multiple attempts and analyses, a more rigorous pore expansion coefficient was finally obtained. Function, the present invention ensures the scientificity and practicality of the expansion coefficient function.

[0059] The damaged and failed parts are deleted according to the failure criteria, and the subroutine VUSDFLD is called to delete the damaged elements. To more accurately reflect the spalling of concrete, the VUSDFLD subroutine is used to define and update the state variables of the material, thereby controlling the failure mechanism of the material and deleting the failed elements as spalling layers.

[0060] The ABAQUS user subroutine VUSDFLD (User subroutine toredefine field variables at a material point) was compiled using Fortran language to improve the concrete damage plasticity model and delete the damaged elements.

[0061] The present invention uses the spalling layer depth to reflect the degree of concrete freeze-thaw damage, that is, the depth of cement mortar peeling off the surface of the concrete component due to freeze-thaw cycles. In the numerical simulation, the concrete damage unit is deleted and regarded as the spalling layer of the concrete. The spalling layer depth is calculated based on the coordinates and number of the damage units. :

[0062]

[0063] Where: is the average of the average spalling depths of all concrete surfaces, is the correction factor. Calculate according to the following formula:

[0064]

[0065]

[0066] Where: 、 are the horizontal and vertical coordinates of each peeling unit; is the number of peeling units, is the total number of units of concrete mortar and ITZ.

[0067] By comparing numerical simulation with existing experiments, the limit value of concrete spalling layer was determined:

[0068]

[0069] Where: is the concrete cover thickness.

[0070] The maximum freeze-thaw times of concrete are determined based on the limit of the concrete spalling layer. Combined with the amplitude and rate of ambient temperature changes in different regions, the freeze-thaw durability degradation law of concrete under different environmental action levels in different regions is more accurately predicted, and a life prediction model is proposed to provide a basis for actual durability design.

[0071] The two-dimensional concrete numerical model is based on ABAQUS numerical simulation software, such as Figure 1 As shown in Figure 1, the calculation process is divided into two stages: the temperature field and the stress field, respectively, using a sequential thermal-mechanical coupling approach. The first stage uses a first-order three-node linear heat transfer triangular element (DC2D3) for heat transfer; the second stage uses a first-order plane stress element, namely a three-node linear plane strain triangular element (CPE3).

[0072] The ambient temperature is also derived from the standard GB / T 50082-2009, "Test Methods for Long-term Properties and Durability of Ordinary Concrete," which defines the load input and external ambient temperature field in the 2D concrete numerical model. In the first stage, temperature is used as the concrete material load input to ensure that the temperature curve of the 2D concrete numerical model is consistent with the experimental temperature curve. In the second stage, the calculated temperature field is used as a predefined field to import into the stress field.

[0073] In one specific example, the concrete spalling layer limit was obtained during the post-processing phase of numerical simulation. Concrete specimens after different freeze-thaw cycles were analyzed. The development pattern of the spalling layer depth was extracted, and a concrete spalling layer limit was proposed. This limit was then compared with the relative dynamic elastic modulus obtained from physical experiments to verify the rationality of the spalling layer limit. A failure determination method based on the concrete spalling layer limit was proposed.

[0074] In a specific embodiment, the method further includes extracting the concrete spalling layer according to the degree of concrete damage to obtain a concrete spalling layer limit value; comparing the concrete spalling layer limit value with the relative dynamic elastic modulus obtained from physical experiments to verify the validity of the two-dimensional concrete numerical model; and considering the influence of preset influencing factors (including concrete strength grade, air content, initial crack characteristics, and prestressing force) on the two-dimensional concrete numerical model.

[0075] In a specific embodiment, the concrete material parameters include: concrete specimen size, aggregate type, gradation, volume fraction, compressive strength, tensile strength, elastic modulus, thermal conductivity, surface heat dissipation coefficient of mortar and aggregate, elastic modulus, thermal expansion coefficient, specific heat capacity and thermal conductivity of pores.

[0076] In a specific embodiment, establishing a two-dimensional concrete numerical model specifically includes: establishing aggregates, pores, ITZ, and mortar according to concrete material parameters in combination with the Monte Carlo method by writing Python language and randomly placing them; during the placement process, determining whether there is interference between aggregates and pores until the placement is successful and the expected aggregate volume fraction is achieved; using Boolean functions to cut out unfilled spaces in the geometric model and fill them with mortar to establish a two-dimensional concrete numerical model.

[0077] 1) ITZ generation: Randomly select a point in the space as a circle to generate a spherical ITZ of the required particle size (aggregate particle size + ITZ thickness), and then based on the Monte Carlo method, randomly place the physical ITZ in the space within the specimen size range according to the principle of ITZ particle size from large to small. During the placement process, interference judgment is required for the pre-delivered ITZ until the placement is successful. 2) Aggregate generation: Generate circular aggregates of the required particle size (aggregate particle size), and re-place aggregates of the corresponding particle size on the basis of the already placed ITZ, and use Boolean functions to cut out the ITZ and aggregates. 3) Pore generation: Generate circular voids of the required particle size (aggregate particle size), place pores and perform interference judgment. 4) Use Boolean functions to cut out the unfilled space of the geometric model and fill it with mortar to form a two-dimensional concrete numerical model such as Figure 2 shown.

[0078] In a specific embodiment, the present invention adopts a rigorous scientific method to systematically study the pore expansion behavior of concrete under freeze-thaw cycles and compares it with the results obtained from existing experiments. After multiple attempts and analyses, a more rigorous pore expansion coefficient is finally obtained. Function, the present invention ensures the scientificity and practicality of the expansion coefficient function. For example, the formula:

[0079]

[0080] in, is the number of freeze-thaw cycles; E is the expansion coefficient of the pores. When frozen, the pores are considered to be filled with ice, so the elastic modulus of ice is about 500. ; is the current temperature; It is the reference temperature used in ABAQUS software calculations, and the default value is usually 0.

[0081] In one specific embodiment, concrete failure is primarily categorized into two types: tensile cracking and compressive crushing. When concrete is subjected to uniaxial tension, failure begins once the tensile stress reaches its peak stress level. However, under uniaxial compression, concrete does not immediately lose its full bearing capacity after exceeding the peak compressive stress; instead, complete failure occurs when the compressive stress drops to approximately 40% of the peak stress after exceeding the peak stress. Based on this, two failure criteria are defined in the VUSDFLD user subroutine: when the concrete's equivalent plastic strain in tension exceeds the critical value corresponding to the peak tensile stress; and when the concrete's equivalent plastic strain in compression exceeds a preset threshold corresponding to the decrease from the peak stress to 40%.

[0082] In a specific embodiment, in obtaining the temperature field and establishing the stress field, the temperature field adopts a first-order three-node linear heat transfer triangle unit under heat transfer; the stress field adopts a first-order plane stress unit, that is, a three-node linear plane strain triangle unit.

[0083] In a specific embodiment, in the temperature field simulation, the laboratory quick freezing method specified in GB / T 50082 is used as the benchmark, and a freeze-thaw cycle period of 4 hours is used. Therefore, a cosine function is used to apply a cyclically changing temperature (+7 to -17°C) to the model to simulate the temperature changes inside the concrete under the action of freeze-thaw. The temperature change diagram during the freeze-thaw cycle is shown in the figure below. Figure 3 shown.

[0084] Calculate the temperature field and stress field, Figure 4(a)-Figure 4(d) is the temperature distribution diagram inside the concrete; Figure 4(e) is the temperature rise curve diagram of the concrete center and surface; Figure 5 The damage development process of concrete under freeze-thaw cycles is shown. The damage development inside concrete under freeze-thaw cycles is shown in a real and continuous manner.

[0085] In a specific embodiment, factors affecting the freeze-thaw durability of concrete include concrete strength grade, air content, initial crack characteristics, and prestressing force.

[0086] Figure 6(a)-Figure 6(c) Comparisons of the relative dynamic elastic moduli from three numerical simulations and physical tests are presented. When the concrete reaches the spalling limit (30% of the protective layer thickness, 9 mm), the freeze-thaw cycles corresponding to a decrease in the relative dynamic elastic modulus to 60% of the original value are essentially consistent, validating the rationality of the spalling limit and proposing a failure determination method based on the concrete spalling limit. The numerical simulation results are summarized in Figure 7(a), which shows the effects of concrete strength grade, air-entraining agent (AEA) (Figures 7(b) and 7(c), and prestressing force (Figure 7(d)) ​​on the freeze-thaw durability of concrete.

[0087] Prestressing:

[0088] In the numerical simulation, a reference point RP-1 is set on the top surface of the concrete, and the top surface is coupled to the reference point. A vertical downward pressure is applied to the reference point to simulate the prestress level. The loading method is as follows: Figure 11 According to the JGJ369-2016 "Design Code for Prestressed Concrete Structures", the prestress level of concrete structures should not exceed their strength standard value. 0.6 times of that, taking C40 concrete as an example, applying 0.10 , 0.20 , 0.30 and 0.40 compressive stress.

[0089] Air content (air-entraining agent):

[0090] Existing research shows that the greatest influence on concrete's frost resistance is the amount of air-entraining agent (AEA). The addition of AEA creates a certain proportion of harmless pores within the concrete, significantly reducing harmful pores and significantly improving frost resistance. However, the addition of AEA degrades the concrete's compressive strength and fluidity. Freeze-thaw resistance is best achieved when the AEA is between 4.6% and 6.5%. NB / T 20549-2019, "Code for Durability Design of Concrete Structures Related to Nuclear Safety," specifies that the AEA should be determined according to Table 1 under different environments.

[0091] Table 1 Minimum requirements for air content in concrete

[0092]

[0093] From the perspective of pore structure stress, experiments have shown that air-entraining agents reduce the frost heave force caused by frost heave of concrete pore water, and experimental research has verified that air-entraining agents can affect the frost resistance and durability of cement mortar by changing the stress characteristics of the internal pore structure.

[0094] Therefore, the influence of air content on frost resistance of concrete is considered by taking into account the different expansion coefficients of concrete with different air contents. To ensure the comparability of the calculation results, the strength grades of concrete models with different air contents should be the same in the numerical simulation.

[0095] Expansion coefficient:

[0096] Without bleed air:

[0097] 4% gas content:

[0098] 5% gas content:

[0099] 6% gas content:

[0100] Concrete strength grades are shown in Table 2:

[0101] Table 2 Model mechanical parameters

[0102]

[0103] Note: The model mechanical parameters of mortar and ITZ are the CDP model parameters of C40 concrete specified in GB / T-50010.

[0104] C45, C50, C60 concrete: the elastic modulus of mortar is 33657.4, 34500, 36000 respectively; ITZ takes 75% of the mortar, .

[0105] In this invention, the maximum freeze-thaw cycles of concrete are determined in a two-dimensional concrete numerical model in ABAQUS based on the concrete strength grade, air content, initial crack characteristics, and prestress size, combined with the concrete spalling layer limit. The concrete lifespan is then predicted under different working conditions based on the amplitude and rate of ambient temperature changes in different regions.

[0106] In one specific embodiment, the lifespan of concrete under different working conditions is predicted. The average annual number of freeze-thaw cycles in each region is estimated based on the average temperature of the coldest month in that region. Based on the relationship between the damage ratio of freeze-thaw concrete under indoor laboratory conditions and natural conditions on site, the concrete durability is predicted based on the environmental cooling rate. The specific prediction model is as follows:

[0107]

[0108] Where: The average temperature of the coldest month.

[0109]

[0110] Where: K is the proportional coefficient of the saturated water time of concrete during freeze-thaw cycles. For structures frequently exposed to water, it is approximately considered to be 1. S is the proportional coefficient of freeze-thaw damage to concrete under indoor and outdoor freeze-thaw environments. The average cooling rate of the coldest month (January) on site is used to represent the cooling rate of the on-site freeze-thaw environment. According to the laboratory quick freezing method, the indoor cooling rate can be taken as 12.5℃ / h. The highest temperature in a day occurs at 14:00 and the lowest temperature is at 2:00 am. Therefore, .

[0111]

[0112] Where: is the maximum freeze-thaw times of concrete material; is the indoor equivalent freeze-thaw times; For the design service life, Figures 8(a) and 8(b), 9(a) and 9(b), and 10(a) and 10(b) show the life prediction results of concrete with different environmental action levels and different cover thicknesses under freeze-thaw cycles.

[0113] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0114] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A numerical simulation method for predicting the life of freeze-thaw concrete based on the depth of the spalling layer, characterized in that: include: Acquire concrete material parameters based on the concrete material using preset rules, and establish a two-dimensional concrete numerical model using the concrete material parameters; Assigning material properties to the two-dimensional concrete numerical model according to the preset rules, then deleting damaged and failed parts based on the failure criterion, calculating the depth of the spalling layer according to the coordinates and number of the damaged and failed parts, determining the concrete spalling layer limit according to the thickness of the concrete cover, and meshing the processed two-dimensional concrete numerical model; ； in, is the depth of the peeling layer, is the average of the average spalling depths of all concrete surfaces, is the correction factor, calculated as follows: ； ； in, 、 are the horizontal and vertical coordinates of each peeling unit; is the number of peeling units, is the total number of units of concrete mortar and ITZ; By comparing numerical simulation with existing experiments, the limit value of concrete spalling layer was determined: ； in, is the concrete cover thickness; Calculate the temperature field based on the ambient temperature and the two-dimensional concrete numerical model divided into grids to obtain the temperature field; calculate the thermal stress according to the temperature change of the temperature field to establish the stress field; According to the spalling layer limit, temperature field and stress field, a full-process numerical simulation of a two-dimensional concrete numerical model is performed after the damaged and failed parts are deleted to obtain the maximum freeze-thaw times; The freeze-thaw concrete life is predicted based on the maximum freeze-thaw times, the predicted range and rate of change of the ambient temperature in the area.

2. The numerical simulation method for predicting the life of freeze-thaw concrete based on the depth of the spalling layer according to claim 1 is characterized in that: The concrete material parameters include: concrete specimen size, aggregate type, gradation, volume fraction, compressive strength, tensile strength, elastic modulus, thermal conductivity, surface heat dissipation coefficient of mortar and aggregate, elastic modulus, thermal expansion coefficient, specific heat capacity and thermal conductivity of pores.

3. The numerical simulation method for predicting freeze-thaw concrete life based on spalling depth according to claim 1 is characterized in that: The establishment of the two-dimensional concrete numerical model specifically includes: establishing aggregates, pores, ITZ and mortar according to concrete material parameters in combination with the Monte Carlo method by writing Python language and randomly placing them; during the placement process, determining whether there is interference between aggregates and pores until the placement is successful and the expected aggregate volume fraction is achieved; using Boolean functions to cut out unfilled spaces in the geometric model and fill them with mortar to establish the two-dimensional concrete numerical model.

4. The numerical simulation method for predicting freeze-thaw concrete life based on spalling depth according to claim 1 is characterized in that: The temperature-dependent pore equivalent expansion coefficient assigned in the material property assignment is specifically expressed as follows: ； in, is the number of freeze-thaw cycles; E is the expansion coefficient of the pores, is the current temperature; is the reference temperature.

5. The numerical simulation method for predicting freeze-thaw concrete life based on spalling depth according to claim 4 is characterized in that: The failure criteria specifically include: when the tensile equivalent plastic strain of concrete exceeds the critical value corresponding to the peak tensile stress; when the compressive equivalent plastic strain of concrete exceeds the preset threshold corresponding to the process of decreasing from the peak stress to the 40% level.

6. The numerical simulation method for predicting freeze-thaw concrete life based on spalling depth according to claim 1, characterized in that: In obtaining the temperature field and establishing the stress field, the temperature field adopts the first-order three-node linear heat transfer triangle element under heat transfer; the stress field adopts the first-order plane stress element, that is, the three-node linear plane strain triangle element.

7. The numerical simulation method for predicting freeze-thaw concrete life based on spalling depth according to claim 6, characterized in that: The temperature field is set at a freeze-thaw cycle of 4 hours, and a cosine function is used to apply a periodically changing temperature to the model, with a temperature range of +7 to -17°C.

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