A method for analyzing the service performance of reinforced concrete in chloride-salt environment based on microscopic fine model

Abstract

The present invention provides a numerical simulation method for concrete cracking failure modes in a chloride environment at a mesoscale, applying phase field theory to mesoscale numerical simulations. The method comprises the following steps: 1) introducing aggregates for mesoconcrete to achieve fully automatic modeling of mesoheterogeneous concrete; 2) verifying the mechanical properties of the mesoconcrete and the diffusion of chloride ions in the mesoconcrete, confirming the effectiveness of a coupled analysis method for simulating chloride ion transport in saturated concrete at the mesoscale; 3) conducting numerical simulations of the cracking and durability degradation processes of single-reinforced concrete in a chloride environment at a mesoscale; and 4) conducting numerical simulations of the failure of multi-reinforced concrete in a chloride environment due to rust expansion, and simulating and analyzing the effects of factors such as different steel bar positions and aggregate distribution on concrete cracking and durability degradation.

Description

Technical Field

[0001] The present invention belongs to the field of concrete numerical simulation at a microscopic scale, and relates to a method for analyzing the service performance of reinforced concrete in a chloride-salt environment based on a microscopic fine model. Background Art

[0002] Concrete is an alkaline, porous material. The widely used silicate concrete has a pH above 12.5. Embedded rebar forms a protective passivation film on its surface, significantly enhancing the rebar's oxidation resistance. Rebar corrosion is primarily caused by chloride attack, such as from deicing salts, inland salt lake environments, and coastal environments.

[0003] Early numerical studies on chloride ion diffusion in concrete mesoscopic models considered concrete as a two-phase model consisting of coarse aggregate and cement mortar. However, the chloride ion diffusion behavior in this two-phase model lags behind that in equivalent homogeneous concrete. Furthermore, due to the heterogeneity and complexity of concrete, the chloride ion diffusion coefficient in the interfacial zone (ITZ), also known as the interfacial transition zone, is difficult to express with a single, intuitive value.

[0004] Liu Xiaoting's invention, patented in China under publication number CN115712993A, improves upon earlier simulation methods by using a one-dimensional fractal derivative diffusion equation to derive chloride ion corrosion. However, the technical approach disclosed in this patent still fails to express the chloride ion diffusion coefficient as a constant. Summary of the Invention

[0005] Purpose of the Invention: To overcome the deficiencies in the prior art, this invention considers that the material parameters and physical properties of the ITZ are difficult to obtain through experimental measurement. To facilitate numerical calculations and reduce finite element calculation costs, this paper assumes that the ITZ has homogeneous characteristics. Based on research on existing concrete materials, and on the basis of unified phase field theory, Fuller gradation curves, fracture mechanics theory, and finite element simulation technology, this invention adopts a microscopic scale and uses phase field theory to analyze the cracking failure mode of concrete in a chloride environment. It also simulates and analyzes the effects of factors such as different steel bar positions and aggregate distribution on concrete cracking and durability degradation. The concrete cracking pattern simulated using this method is more consistent with actual experimental results than the macroscopic scale, and can better simulate the concrete cracking process and the interaction between cracks within the concrete.

[0006] Technical solution: In order to achieve the above technical objectives, the present invention adopts the following technical means:

[0007] A method for analyzing the service performance of reinforced concrete in a chloride-salt environment based on a microscopic fine model includes the following steps:

[0008] 1) Add aggregates for micro-concrete to achieve fully automatic modeling of micro-heterogeneous concrete;

[0009] 2) Verify the mechanical properties of meso-concrete and the diffusion of chloride ions in meso-concrete, and confirm the effectiveness of the coupled analysis method in simulating the chloride ion transport in saturated concrete at the meso-scale;

[0010] The specific method for verifying the mechanical properties of the meso-concrete is: obtaining the influence of the peak strength and failure mode of the meso-concrete through displacement loading and different aggregate distribution, thereby verifying the mechanical properties of the meso-concrete;

[0011] The specific method for verifying the diffusion of chloride ions in meso-concrete is as follows: a homogenization method is used to inversely obtain the chloride ion diffusion coefficients of each phase of the meso-concrete material, that is, firstly, the coarse aggregate and the interface layer ITZ are regarded as equivalent aggregates, and the equivalent chloride ion diffusion coefficient of the equivalent aggregate is calculated. Then, the equivalent diffusion coefficient of the mortar is obtained based on the equivalent diffusion coefficient of the entire concrete.

[0012] 4) using the chloride ion diffusion coefficient and displacement increment of the concrete obtained in step 2), numerically simulating the cracking and durability degradation process of single-reinforced concrete in a chloride environment at a mesoscale;

[0013] 4) Based on step 3), single-reinforced concrete is replaced with multi-reinforced concrete. At the same time, the steel bar position and aggregate distribution are changed. Numerical simulation of the failure of multi-reinforced concrete in a chloride environment due to rust expansion is carried out. The influence of different steel bar positions and aggregate distribution factors on concrete cracking and durability degradation is simulated and analyzed.

[0014] The specific method of adding aggregates for the meso-concrete in step 1) is as follows: in order to obtain aggregates with maximum density and minimum voids, solid particles are matched according to particle size using a parabolic grading curve, and the maximum density is achieved at this time, which is expressed as:

[0015]

[0016] Where, P i The aperture is d i The passing rate of the sieve of mm, d i is the particle size of each level of aggregate, in mm; D is the maximum aggregate particle size, in mm.

[0017] The specific steps for achieving fully automatic modeling of microscopic heterogeneous concrete in step 1) are:

[0018] 1A) Using a circle to approximate the actual aggregate shape and randomly generating aggregate particle size data;

[0019] 1B) Randomly generate the coordinates of the center of an aggregate. Use the distance between the center of one aggregate and the center of another aggregate to determine whether the two overlap or interfere. If not, place the aggregate.

[0020] 1C) Determine the particle size and volume ratio of coarse aggregate in mesoscale concrete based on the Fuller gradation curve. Fully automate the aggregate placement, ITZ generation, interference determination between aggregates, mesoscale concrete assembly, and the assignment of unit and material properties on the Abaqus platform.

[0021] In the specific method of verifying the diffusion of chloride ions in micro-concrete in step 2), the concrete is regarded as a two-phase material consisting of equivalent aggregate and mortar, and the chloride ion diffusion coefficient expression of the equivalent aggregate is obtained:

[0022]

[0023] Where, μ is the ratio of the major axis to the minor axis of the elliptical aggregate, and μ=1 for circular aggregate;

[0024] f agg and f ITZ is the volume fraction of aggregate and ITZ of interface layer;

[0025] μ is the ratio of the major axis to the minor axis of the elliptical aggregate, and μ=1 for circular aggregate;

[0026] D ea is the equivalent diffusion coefficient of chloride ions of equivalent aggregate;

[0027] D ITZ is the diffusion coefficient of the ITZ phase in the interface layer;

[0028] The chloride ion diffusion coefficient expression of two-phase concrete is obtained:

[0029] D ITZ =αD cp

[0030]

[0031] Where α is the ratio of the diffusion coefficient of the ITZ phase in the interface layer to the diffusion coefficient of the mortar phase, and its value ranges from 2 to 12;

[0032] D eff is the overall equivalent diffusion coefficient of concrete;

[0033] D cp is the equivalent diffusion coefficient of mortar.

[0034] In step 3), the specific steps of numerically simulating the cracking and durability degradation process of single-reinforced concrete in a chloride environment at a microscopic scale are as follows:

[0035] 3A) Conduct microscopic simulation of concrete damage caused by corrosion and expansion of central steel bars;

[0036] 3B) Conduct microscopic simulation of the effect of aggregate distribution on concrete damage;

[0037] 3C) Microscopic simulation of concrete damage caused by corrosion and expansion of corner steel bars.

[0038] The specific steps of carrying out the numerical simulation of the failure of multi-reinforced concrete due to rust expansion at the microscopic scale in step 4) are:

[0039] 4A) A mesoscopic concrete model containing multiple parallel steel bars was established. The steel bar corrosion was loaded using equivalent displacement and the lower boundary was fixed.

[0040] 4B) Numerical simulation of concrete cracking failure caused by uneven chloride corrosion of multiple reinforcement bars;

[0041] 4C) Simulate the effect of different clear distances between steel bars on the concrete cracking failure process.

[0042] Beneficial effects:

[0043] Compared with the prior art, the present invention has the following advantages:

[0044] The present invention solves the technical problem that the existing technology cannot accurately and scientifically predict the cracking and durability degradation process of concrete in a chloride environment. A parametric analysis method is used to study the influence of different clear distances between steel bars on the shedding of the concrete cover.

[0045] Furthermore, the cracking failure modes of concrete in chloride environments at the mesoscale are more consistent with actual experimental results than the macroscopic homogenization model, better simulating the concrete cracking process and the interactions between cracks within the concrete. When predicting the damage and service life of concrete structures in complex environments, it is necessary to consider the influence of mesostructural characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A comparison chart of the simulation results of the present invention, the test results, and the damage mechanics mesoscopic simulation results;

[0047] Figure 2 Implement aggregate placement and meso-concrete modeling flow chart for Python;

[0048] Figure 3a Schematic diagram of the meso-concrete model, aggregate distribution mode A1;

[0049] Figure 3b Schematic diagram of the meso-concrete grid division, aggregate distribution mode A1;

[0050] Figure 4Schematic diagram of the geometric conditions and boundaries of meso-concrete, aggregate distribution mode A1;

[0051] Figure 5 The stress-strain curves of meso-concrete under uniaxial tension at different loading steps;

[0052] Figure 6 Comparison of stress-strain curves of meso-concrete under uniaxial tension with different aggregate distributions;

[0053] Figure 7a Schematic diagram of the mesoscopic concrete failure mode under coupling conditions;

[0054] Figure 7b Schematic diagram of the mesoscopic concrete failure mode without considering coupling conditions;

[0055] Figure 8 Comparison of concrete failure modes and test results for three aggregate distribution methods;

[0056] Figure 9a Schematic diagram of concrete failure mode in the corner area;

[0057] Figure 9b Schematic diagram of the critical rust expansion concentration on the steel bar surface;

[0058] Figure 10 A comparison chart of the simulation results of the present invention, the test results, and the damage mechanics simulation results;

[0059] Figure 11 Schematic diagram of the geometry and boundary conditions of multi-reinforced concrete;

[0060] Figure 12a Schematic diagram of failure mode of multi-reinforced meso-concrete with clear distance between steel bars S = 32mm;

[0061] Figure 12b Schematic diagram of the failure mode of multi-reinforced meso-concrete with a clear distance between steel bars S = 64mm.

[0062] Figure 12c Schematic diagram of the failure mode of multi-reinforced meso-concrete with a clear distance between steel bars S = 96mm.

[0063] Figure 13 This is a flow chart of the service performance analysis method of reinforced concrete in chloride salt environment based on the microscopic fine model of the present invention. DETAILED DESCRIPTION

[0064] The technical solution of the present invention is further described in detail below with reference to specific embodiments and the accompanying drawings.

[0065] The service performance analysis method of reinforced concrete in chloride salt environment based on microscopic fine model of the present invention applies phase field theory to numerical simulation at microscopic scale, and includes the following steps:

[0066] 1) Add aggregates for micro-concrete to achieve fully automatic modeling of micro-heterogeneous concrete;

[0067] 2) Verify the mechanical properties of meso-concrete and the diffusion of chloride ions in meso-concrete, and confirm the effectiveness of the coupled analysis method in simulating chloride ion transport in saturated concrete at the mesoscale;

[0068] 3) Numerical simulation of the cracking and durability degradation process of single-reinforced concrete in a chloride environment at a mesoscale;

[0069] 4) Carry out numerical simulation of the failure of multi-reinforced concrete due to rust expansion in a chloride environment at a mesoscale, and simulate and analyze the effects of factors such as different steel bar positions and aggregate distribution on concrete cracking and durability degradation.

[0070] As an example, Figure 1 A comparison chart comparing the mesoscopic simulation results of the present invention with the experimental results and the damage mechanics mesoscopic simulation results is provided. It can be seen that three main cracks appeared in the concrete around the rebar: crack path 1, crack path 2, and crack path 3. This is consistent with the three obvious cracks around the rebar in the experimental results.

[0071] In the above embodiment, although the crack propagation angle is somewhat different from the test results, the reason for the difference is that the randomly placed aggregates in the meso-concrete numerical model cannot be consistent with the concrete aggregate distribution in the test. The aggregate distribution affects the propagation direction of the cracks around the steel bars. However, the evolution trend of the cracks is still consistent with the test results. It can still be considered that the calculated meso-concrete cracking pattern is in good agreement with the test results.

[0072] In addition, it can be seen that the phase-field fracture model adopted can better simulate the complex crack propagation path inside the concrete, showing the twists and turns of the cracks in the actual propagation process, revealing the failure process of reinforced concrete components in chloride environments more delicately at the microscopic scale, and being able to more accurately predict the spalling pattern of the concrete cover.

[0073] As a further preferred method of the above embodiment of the present invention, the specific method of adding the aggregate for the meso-concrete in step 1) is: to obtain aggregate with maximum density and minimum voids, solid particles are arranged according to particle size using a parabolic grading curve. When the grading curve is a parabola, the maximum density can be achieved, which is expressed as:

[0074]

[0075] Where, Pi The aperture is d i mm sieve passing rate (%), d i is the particle size of each level of aggregate (mm), and D is the maximum aggregate particle size (mm).

[0076] The specific steps for achieving fully automatic modeling of microscopic heterogeneous concrete in step 1) are as follows:

[0077] 1A) Using a circle to approximate the actual aggregate shape and randomly generating aggregate particle size data;

[0078] 1B) Randomly generate the coordinates of the center of an aggregate. Use the distance between the center of one aggregate and the center of another aggregate to determine whether the two overlap or interfere. If not, place the aggregate.

[0079] 1C) As attached Figure 2 As shown, the particle size and volume ratio of coarse aggregate in meso-scale concrete are determined based on the Fuller gradation curve. The Abaqus platform fully automates the processes of aggregate placement, ITZ generation, interference determination between aggregates, meso-scale concrete assembly, and the assignment of unit and material properties. As an example, Figure 3 shows the established meso-scale concrete model.

[0080] The specific method for verifying the mechanical properties of the meso-concrete in step 2) is to study the effects of displacement loading and different aggregate distributions on the peak strength and failure mode of the meso-concrete, thereby verifying the mechanical properties of the meso-concrete.

[0081] The geometric model and boundary conditions of the reinforced concrete are shown in the attached figure. Figure 4 As shown in the figure, the left boundary of the concrete block is fixed in the x direction and the bottom boundary is fixed in the y direction. The load adopts uniformly distributed displacement and the displacement increment Δu is constant. Δu is 10 - 2 mm, 10 -3 mm, 10 -4 mm, phase field length parameter l = 2.5 mm.

[0082] Attachment Figure 5The stress-strain curves of meso-concrete under uniaxial (X and Y axis) loading, obtained from numerical simulation results, are shown. It can be seen that under the same displacement increment, the stress-strain curves of meso-concrete subjected to X and Y axis tension are nearly identical. Although the concrete stress-strain curve is somewhat sensitive to the increment, it stabilizes as the displacement increment decreases. The macro-concrete tensile strength is approximately 1.71 MPa, and the slopes of the rising segments of all stress-strain curves remain essentially consistent, indicating that the macro-equivalent elastic modulus is unaffected by the displacement increment. However, calculation time increases when the displacement increment is too small. Based on the above analysis, it is concluded that when using the phase-field fracture model to simulate the failure process of meso-concrete, the smallest possible displacement increment should be selected based on the operating conditions.

[0083] Attachment Figure 6 The failure mode of meso-concrete under uniaxial tension for the A2 aggregate distribution is presented. It can be seen that there is no significant difference in the crack propagation path, indicating that aggregate distribution has little effect on the cracking and failure mode of meso-concrete, indicating that aggregate distribution does not affect the peak strength and mechanical properties of meso-concrete.

[0084] The specific method for verifying the diffusion of chloride ions in meso-concrete described in step 2) is: using a homogenization method to inversely obtain the chloride ion diffusion coefficient of each phase of the meso-concrete material, that is, first treating the coarse aggregate and the ITZ layer as equivalent aggregates, calculating the equivalent chloride ion diffusion coefficient of the equivalent aggregate, and then obtaining the equivalent diffusion coefficient of the mortar based on the overall equivalent diffusion coefficient of the concrete.

[0085] The chloride ion diffusion coefficient in concrete is related to the aggregate area fraction, maximum aggregate particle size, ITZ thickness, aggregate gradation, and aggregate shape. Due to the heterogeneity and complexity of concrete materials, the chloride ion diffusion coefficient of the ITZ is difficult to express with a single intuitive value. Considering that the material parameters and physical properties of the ITZ are difficult to obtain through experimental measurement, and to facilitate numerical calculations and reduce finite element calculation costs, this paper assumes that the ITZ has homogeneous characteristics. Concrete is considered to be a two-phase material consisting of equivalent aggregate and mortar, and the chloride ion diffusion coefficient expression for the equivalent aggregate is obtained:

[0086]

[0087] Where μ is the ratio of the major axis to the minor axis of the elliptical aggregate, μ is 1 for circular aggregate, and f is agg and f ITZ is the volume fraction of aggregate and ITZ, D ea is the equivalent diffusion coefficient of chloride ions of equivalent aggregate.

[0088] The chloride ion diffusion coefficient expression of two-phase concrete is obtained:

[0089] D ITZ =αD cp

[0090]

[0091] Where α is the ratio of the diffusion coefficient of the ITZ phase to the diffusion coefficient of the mortar phase, and its value is usually between 2 and 12. eff is the equivalent diffusion coefficient of concrete, D cp is the equivalent diffusion coefficient of mortar.

[0092] The specific steps of numerically simulating the cracking and durability degradation process of single-reinforced concrete in a chloride environment at a mesoscale as described in step 3) are as follows:

[0093] 3A) A microscopic simulation of concrete damage caused by corrosion and expansion of the central steel bar is performed. Taking the microscopic concrete geometric model shown in FIG3 as an example, the concrete cover thickness De = 30 mm, the central steel bar diameter d = 16 mm, and the chloride ion concentration boundary C only on the surface of the concrete slab s =3%, critical rust expansion concentration of steel bar C r =0.1%, the steel bar corrosion process adopts the equivalent displacement loading method, and the specific numerical simulation parameters are shown in Table 1.

[0094] Table 1 Material parameters and diffusion coefficients of each phase in micro-concrete

[0095]

[0096] Attachment Figure 7a and attached Figure 7b The process of concrete cracking caused by chloride ion corrosion at a microscopic scale under coupled conditions is presented. After 38 months of exposure to a chloride ion environment, damage occurred at the interface between the aggregate and mortar above the steel bars. As time went by, the corrosion of the steel bars deepened, and the concrete around the steel bars was subjected to increasing tension. Three major damage zones radiated from the steel bars and gradually evolved into cracks. Among them, the cracks above the steel bars and the cracks extending inward from the upper surface of the concrete formed through cracks, as shown in the attached figure. Figure 7a The crack on the right side of the bar expanded outward, as shown in crack path 2, causing the concrete cover to fall off in the upper right corner. Simultaneously, the crack that initiated on the lower left side of the bar expanded, as shown in crack path 3.

[0097] It is worth noting that in addition to the cracks around the three steel bars, cracks appeared on the left boundary surface of the concrete, extending from the outside to the inside, as shown in crack path 4 in the figure, eventually causing the upper left protective layer of the concrete to fall off.

[0098] 3B) Conduct microscopic simulation of the effect of aggregate distribution on concrete damage.

[0099] Attachment Figure 8 A comparison of the chloride ion concentration on the steel bar surface and the outer contour of the steel bar corrosion after exposure to concrete with three different aggregate distributions for the same time is shown. It can be seen that the chloride ion concentration at each point on the steel bar surface and the outer contour of the corrosion products in Aggregate Distribution A1 are significantly higher than those in the other two cases. This is because Aggregate Distribution A1 has less aggregate directly above the steel bar, so the chloride ion concentration on the steel bar surface reaches the critical corrosion expansion concentration earlier, resulting in a faster corrosion rate. After nearly 54.0 months of exposure, cracks had essentially penetrated the protective layer of Aggregate Distribution A1, nearly 3.1 months earlier than the other two cases, Aggregate Distribution A2 and Aggregate Distribution A3. This preemptively formed a transport channel for external chloride ions to reach the surrounding steel bars, accelerating the chloride ion erosion rate in the concrete. Therefore, after the same exposure time, the chloride ion concentration at each point on the steel bar surface was higher than that in the other two cases, Aggregate Distribution A2 and Aggregate Distribution A3, and the steel bars had more corrosion products.

[0100] 3C) Microscopic simulation of concrete damage caused by corrosion and expansion of corner steel bars.

[0101] Figure 9 shows the crack propagation and failure process of concrete in the corner area. It can be seen that after nearly 38.1 months of exposure, the surface of the concrete cover on the right side was the first to crack, while the upper cover was almost undamaged. This is because during the random placement of aggregate, more aggregate was placed on the upper side of the steel bar than on the right side. After nearly 15.0 months of exposure, the chloride ion concentration on the right side of the steel bar reached the critical corrosion concentration, and the right side of the steel bar began to rust and expand first, while the chloride ion concentration on the upper side lagged behind by nearly 1.3 months. Therefore, there were more rust products on the right side of the steel bar, causing the tension on the surface of the concrete cover to be greater than the tensile strength of the concrete, and the right side surface cracked first. As time passed and chloride ion erosion occurred, the chloride ion concentration on the upper side of the steel bar reached the critical corrosion concentration, and the interface between the aggregate and mortar above the steel bar gradually became damaged and evolved into cracks. Based on the above analysis, it can be concluded that when the chloride ion diffusion time is short, the aggregate has a certain barrier effect on the diffusion of chloride ions, which to a certain extent affects the time when the steel bar begins to rust and the crack propagation inside the concrete.

[0102] As attached Figure 10As shown, the mesoscopic simulation results of the present invention are compared with the existing experimental observation results and the mesoscopic numerical simulation results based on damage mechanics. Three main cracks appeared in the concrete around the corner steel bars. It can be seen that the simulated crack propagation paths and angles of the corner area concrete are basically consistent with the experimental results. In addition, compared with the corner area concrete damage simulation results based on damage mechanics, it can be seen that the coupling analysis method proposed in the present invention can better reproduce the complex processes of crack initiation, expansion, and tortuosity in concrete, and the direction and trend of crack expansion are more consistent with the experimental results. Although the computational efficiency of the coupling analysis using the concrete mesoscopic model is low in the numerical calculation process, compared with the concrete cracking and protective layer shedding states obtained by the concrete macroscopic model, the mesoscopic concrete model can better simulate the tortuosity of crack propagation in concrete, which is more in line with the actual destruction mode of concrete in a chloride environment.

[0103] The specific steps of carrying out the numerical simulation of the failure of multi-reinforced concrete due to rust expansion at the microscopic scale in step 4) are as follows:

[0104] 4A) Create a mesoscopic concrete model containing multiple steel bars arranged side by side.

[0105] As attached Figure 11 As shown, the total volume of coarse aggregate accounts for 45%, the thickness of the concrete cover De = 30 mm, the diameter of the steel bar d = 16 mm, and the net distance between the steel bars S = 32 mm (2d), 64 mm (4d), and 96 mm (6d) respectively.

[0106] The steel bar corrosion adopts the equivalent displacement loading method, and there is a chloride ion concentration boundary C on the surface of the concrete slab. s =3%, the chloride ion concentration flux at other boundaries is 0, and the critical rust expansion concentration of steel bars C r = 0.1%, the lower boundary is fixed, and the numerical simulation parameters are as shown in the attached Figures 12a to 12c shown.

[0107] 4B) Numerical simulation of concrete cracking failure caused by uneven chloride corrosion of multiple reinforcements. When the net distance between reinforcements S = 32mm, as shown in the attached Figure 12aIt can be seen that the mortar interface between the aggregate and the concrete is the first to be damaged. As the degree of steel bar corrosion deepens, the continuous expansion of the corrosion products causes surface deformation, resulting in surface cracks that first begin to initiate at the top of the two corner steel bars and extend into the interior of the concrete. The concrete protective layer in the corner area first shows a tendency to peel off. Subsequently, the cracks in the middle steel bar extend toward the corner steel bar, while the cracks around the corner steel bar extend toward the steel bar in the middle position. As the steel bar corrosion intensifies, cracks appear on both sides of the concrete protective layer and extend to the left and right surfaces. The concrete corners peel off, and cracks penetrate between the steel bars inside the concrete, resulting in concrete delamination. Finally, cracks that evolve to the side and downward also initiate near the corner steel bar, causing the concrete protective layer to further fall off and serious structural damage. It is not difficult to find that the cracking of the concrete in the corner area is more serious than that in the central area.

[0108] 4C) Simulate the effect of different clear distances between steel bars on the concrete cracking failure process.

[0109] Attachment Figure 12b and attached Figure 12c The cracking and failure modes of multi-reinforced concrete with clear reinforcement spacings of 64mm and 96mm are presented. Comparison with the results for a clear reinforcement spacing of S = 32mm reveals that in all three cases, surface cracks first appear on the concrete surface above the two corner bars, leading to corner shedding. Furthermore, lateral cracks in the bars connect to form horizontal through-cracks, causing delamination of the reinforced concrete and failure of the cover layer.

Claims

1. A method for analyzing the service performance of reinforced concrete in chloride salt environment based on a microscopic fine model, characterized in that: The following steps are involved: 1) Add aggregates for micro-concrete to achieve fully automatic modeling of micro-heterogeneous concrete; 2) Verify the mechanical properties of meso-concrete and the diffusion of chloride ions in meso-concrete, and confirm the effectiveness of the coupled analysis method in simulating chloride ion transport in saturated concrete at the meso-scale; The specific method for verifying the mechanical properties of the meso-concrete is: obtaining the influence of the peak strength and failure mode of the meso-concrete through displacement loading and different aggregate distribution, thereby verifying the mechanical properties of the meso-concrete; The specific method for verifying the diffusion of chloride ions in meso-concrete is as follows: a homogenization method is used to inversely obtain the chloride ion diffusion coefficients of each phase of the meso-concrete material, that is, firstly, the coarse aggregate and the interface layer ITZ are regarded as equivalent aggregates, and the equivalent chloride ion diffusion coefficient of the equivalent aggregate is calculated. Then, the equivalent diffusion coefficient of the mortar is obtained based on the equivalent diffusion coefficient of the entire concrete. 3) using the chloride ion diffusion coefficient and displacement increment of the concrete obtained in step 2), numerically simulate the cracking and durability degradation process of single-reinforced concrete in a chloride environment at a mesoscale; 4) Based on step 3), the single-reinforced concrete was replaced with multi-reinforced concrete. At the same time, the steel bar position and aggregate distribution were varied. Numerical simulations were conducted on the failure of multi-reinforced concrete in a chloride environment due to rust expansion at a mesoscale. The effects of different steel bar positions and aggregate distributions on concrete cracking and durability degradation were simulated and analyzed. In the specific method of verifying the diffusion of chloride ions in meso-concrete in step 2), concrete is regarded as a two-phase material consisting of equivalent aggregate and mortar, and the chloride ion diffusion coefficient expression of the equivalent aggregate is obtained: Where, is the ratio of the major axis to the minor axis of the elliptical aggregate, and the circular aggregate ; and is the volume fraction of aggregate and ITZ of interface layer; is the ratio of the major axis to the minor axis of the elliptical aggregate, and the circular aggregate ; is the equivalent diffusion coefficient of chloride ions of equivalent aggregate; is the diffusion coefficient of the ITZ phase in the interface layer; The chloride ion diffusion coefficient expression of two-phase concrete is obtained: Where, is the ratio of the diffusion coefficient of the ITZ phase in the interface layer to the diffusion coefficient of the mortar phase, and its value ranges from 2 to 12; is the overall equivalent diffusion coefficient of concrete; is the equivalent diffusion coefficient of mortar.

2. The service performance analysis method of reinforced concrete in chloride environment based on microscopic fine model according to claim 1 is characterized in that: The specific method of adding aggregates for meso-concrete in step 1) is as follows: to obtain aggregates with maximum density and minimum voids, solid particles are matched according to particle size using a parabolic grading curve. At this point, the maximum density is achieved, which is expressed as: ， Where, The aperture is The passing rate of the sieve of mm, is the particle size of aggregate at each level, in mm, The maximum aggregate particle size, unit: mm.

3. The service performance analysis method of reinforced concrete in chloride environment based on microscopic fine model according to claim 1 is characterized in that: The specific steps for achieving fully automatic modeling of microscopic heterogeneous concrete in step 1) are: 1A) Using a circle to approximate the actual aggregate shape and randomly generating aggregate particle size data; 1B) Randomly generate the coordinates of the center of an aggregate. Use the distance between the center of one aggregate and the center of another aggregate to determine whether they overlap or interfere. If not, place the aggregate. 1C) Determine the particle size and volume ratio of coarse aggregate in meso-scale concrete based on the Fuller gradation curve. Fully automate the aggregate placement, ITZ generation, interference determination between aggregates, meso-scale concrete assembly, and the assignment of unit and material properties on the Abaqus platform.

4. The method for analyzing the service performance of reinforced concrete in chloride salt environment based on a microscopic fine model according to claim 1, characterized in that: In step 3), the specific steps for numerically simulating the cracking and durability degradation process of single-reinforced concrete in a chloride environment at a mesoscopic scale are as follows: 3A) Conduct microscopic simulation of concrete damage caused by corrosion and expansion of central reinforcement; 3B) Conduct microscopic simulation of the effect of aggregate distribution on concrete damage; 3C) Microscopic simulation of concrete damage caused by corrosion and expansion of corner steel bars.

5. The method for analyzing the service performance of reinforced concrete in chloride salt environment based on a microscopic fine model according to claim 1, characterized in that: The specific steps of carrying out the numerical simulation of the failure of multi-reinforced concrete due to rust expansion at the microscopic scale in step 4) are as follows: 4A) Establish a mesoscopic concrete model containing multiple parallel steel bars. The steel bar corrosion is loaded using equivalent displacement and the lower boundary is fixed. 4B) Numerical simulation of concrete cracking failure caused by uneven chloride corrosion of multiple reinforcement bars; 4C) Simulate the effect of different clear distances between steel bars on the concrete cracking failure process.

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