A method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation

Abstract

The application provides a kind of concrete chloride ion diffusion coefficient prediction method based on aggregate gradation, comprising the following steps: obtaining the chloride ion diffusion coefficient D ref Of cement paste;Obtaining the specific surface area s i Of aggregate in each particle size interval;Obtaining the thickness of concrete interfacial transition zone;Calculating the chloride ion diffusion coefficient of concrete.The application considers the influence of all components (cement paste, aggregate, interfacial transition zone) on chloride ion diffusion coefficient from the composition of concrete, and the influence of aggregate particle size on the thickness of interfacial transition zone, and the prediction result has high accuracy, which can provide effective reference for the evaluation of concrete resistance to chloride ion erosion.

Description

Technical Field

[0001] This invention belongs to the technical field of cement concrete durability evaluation, specifically involving a method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation. The chloride ion diffusion coefficient of concrete can be predicted by the aggregate gradation and volume ratio in the concrete. Background Technology

[0002] In marine environments, chloride ions readily penetrate concrete, causing steel reinforcement corrosion and expansion, which in turn leads to concrete cracking and spalling. This results in buildings failing to meet their designed service life and further increases the environmental impact of cement concrete throughout its lifecycle. The chloride ion diffusion coefficient is the most critical evaluation indicator for concrete's resistance to chloride ion attack. Currently, the chloride ion diffusion coefficient of concrete is mainly obtained through experimental testing, such as the rapid chloride ion migration coefficient method, the natural immersion method, and electrical flux. However, these experimental methods are usually cumbersome and time-consuming, making it difficult to achieve a rapid evaluation of concrete's resistance to chloride ion attack.

[0003] The cement paste and interfacial transition zone is the main channel for chloride ion diffusion. Its intrinsic diffusion coefficient is mainly affected by the water-cement ratio and the composition of cementitious materials. Therefore, current chloride ion diffusion coefficient prediction models mostly study the effects of water-cement ratio and the dosage of various mineral admixtures on the chloride ion diffusion coefficient of concrete. However, the aggregate gradation and proportion in concrete significantly affect the content of cement paste and interfacial transition zone in concrete, making it difficult for such prediction models to assess the impact of aggregate gradation and proportion on the chloride ion diffusion coefficient. Concrete can be considered as composed of cement paste, aggregate, and interfacial transition zone. The diffusion of chloride ions in concrete follows Fick's second law. Based on this, numerous simulation models for chloride ion prediction based on the three-dimensional structure of concrete have been proposed. After establishing a three-dimensional concrete structural model, the coefficients of the chloride ion diffusion equation are determined by analyzing the physical and chemical properties of concrete. Then, by calculating the movement speed and direction of chloride ions in concrete, the concentration change of chloride ions in concrete is calculated according to Fick's second law, thereby accurately predicting the chloride ion diffusion coefficient of concrete. However, the above process not only requires complex theoretical derivation and finite element modeling, but its accuracy also depends on factors such as the type of aggregate used in the concrete, the accuracy of experimental data, and the parameter settings of the model. In addition, during the modeling process, concrete aggregates are often simplified into spherical or other regular polygons, but the particle shape of the aggregate has a great influence on the surface area. Inaccurate assessment of the surface area will be transmitted to the interface transition zone, thus affecting the accuracy of the chloride ion diffusion coefficient prediction.

[0004] Gu Chunping et al. disclosed a "Prediction Method for Chloride Ion Diffusion Coefficient of Concrete Based on Micro and Mesoscopic Structural Parameters" in CN109211750A. This method treats the thickness of the interfacial transition zone of aggregates with different particle size ranges as the same value and does not consider the surface area change caused by the change of aggregate gradation, resulting in low accuracy of the obtained results. Wu Linjian et al. disclosed a "Construction of Three-Phase Mesoscopic Model of Concrete and Numerical Simulation Method of Internal Chloride Ion Erosion Based on Polygonal Random Aggregates" in CN110706352A. This method simulates the chloride ion erosion process through finite element simulation, but the calculation process is extremely complex and cumbersome and cannot reflect the true morphology of the aggregates. Yuanzhan Wang et al. disclosed a scheme in "Effects of coarse aggregates on chloride diffusion coefficients of concrete and interfacial transition zone under experimental drying-wetting cycles" that did not consider the deflection of chloride ion transport path in the interfacial transition zone by aggregates (did not consider the influence of tortuosity effect on the interfacial transition zone), did not evaluate the volume of the interfacial transition zone in concrete by the actual specific surface area of ​​the aggregates, and did not consider the influence of aggregate particle size on the thickness of the interfacial transition zone. In summary, existing prediction methods either yield results with low accuracy or involve extremely cumbersome processes. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation. Starting from the concrete composition, it considers the influence of all components (cement paste, aggregate, and interfacial transition zone) on the chloride ion diffusion coefficient, as well as the influence of aggregate particle size on the thickness of the interfacial transition zone. The prediction results are highly accurate and can provide an effective reference for evaluating the chloride ion erosion resistance of concrete.

[0006] To achieve the objective of this invention, a method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation is provided, comprising the following steps:

[0007] Obtain the chloride ion diffusion coefficient D of cement paste ref ;

[0008] Obtain the specific surface area s of aggregates in each particle size range. i ;

[0009] Obtain the thickness of the concrete interface transition zone;

[0010] The formula for calculating the chloride ion diffusion coefficient of concrete is as follows:

[0011] D = D ref ·[f(di)+f(ITZ)]·f(tor)

[0012] In the formula, D ref denoted as the chloride ion diffusion coefficient of cement paste, and f(di), f(ITZ), and f(tor) are the influence factors of aggregate dilution effect, ITZ effect, and tortuosity effect on the chloride ion diffusion coefficient of concrete, respectively.

[0013] Furthermore, the chloride ion diffusion coefficient of the cement paste is obtained by either the natural soaking method or the rapid chloride ion migration coefficient method.

[0014] The natural immersion method and the rapid chloride ion migration method are experimental testing methods, conducted according to ASTM C1556-2013 and GBT50082-2009 standards. It should be clarified that the method for obtaining the chloride ion diffusion coefficient of cement paste should be consistent with the method for verifying the accuracy of the predicted chloride ion diffusion coefficient of concrete.

[0015] Preferably, the method for obtaining the chloride ion diffusion coefficient of the cement slurry is the natural soaking method.

[0016] Furthermore, the specific surface area of ​​aggregates in each interval is obtained by using any one of the following methods: image analysis, three-dimensional reconstruction, and experimental coating method.

[0017] Image analysis mainly relies on image processing algorithms to process aggregate images. The steps are as follows: first, Gaussian blur is used to denoise the aggregate image, then the edge information of the aggregate samples in the binarized image is extracted to form a two-dimensional projection image. The area covered by the aggregate projection pixels is calculated according to the scale. The surface area of ​​the aggregate is calculated by summing the different projection areas according to the shape of the aggregate and the projection angle.

[0018] The method for calculating aggregate surface area using the 3D reconstruction method is as follows: First, surface point cloud data is collected by scanning with a laser scanner. Then, the 3D mesh model is reconstructed using the Delaunay triangulation algorithm. Finally, the surface area of ​​the 3D mesh model is calculated using the triangle area calculation method to calculate the aggregate surface area.

[0019] The steps for obtaining the specific surface area of ​​aggregates using the grouting method include: mixing the aggregates with cement grout with a water-cement ratio of 0.55, drying the mixture, removing any interfering cement grout from the bottom surface, measuring the mass of the cement grout coating the aggregate surface, and then calculating the aggregate surface area based on the coating thickness.

[0020] Preferably, the method for obtaining the specific surface area is a three-dimensional reconstruction method.

[0021] Preferably, the aggregate particle size range can be divided into 0.075-1.18mm, 1.18-2.36mm, 2.36-4.75mm, 4.75-9.50mm, 9.50-13.2mm, 13.2-19mm, and 19-26mm.

[0022] Furthermore, the step of obtaining the thickness of the concrete interface transition zone includes:

[0023] Aggregates of the largest particle size range were cut from cured concrete specimens and polished to obtain sample images, which were then binarized. The aggregate edges in the images were captured, and the cement paste area was divided along these edges. The porosity of each area was calculated. When the porosity variation rate of five consecutive areas was less than a preset value, the first area in the five consecutive areas (the one closest to the aggregate) was selected, and the distance from the aggregate edge to this area was defined as the interface transition zone thickness h. max .

[0024] Preferably, a depth-first search algorithm is used to obtain the aggregate edges in the image.

[0025] The preferred dilution effect, ITZ effect, and tortuosity effect influencing factors are calculated using the following formulas.

[0026] f(di) = 1 - V a -V ITZ

[0027]

[0028] f(ITZ)=n·V ITZ

[0029] Among them, V a V represents the volume percentage of aggregate in concrete. ITZ denoted as , where is the volume percentage of the interfacial transition zone in the concrete, and n is the ratio of the ITZ chloride ion diffusion coefficient to the chloride ion diffusion coefficient of the cement paste.

[0030] The preferred method for calculating the volume ratio of the interface transition zone is as follows:

[0031] V ITZ =V a ∑s i ·y i ·h i

[0032]

[0033]

[0034] Among them, s i With y i h represents the ratio of the specific surface area of ​​aggregate in particle size range i to the total volume of aggregate; i with h max These represent the average thicknesses of the transition zones between aggregates in the max (maximum particle size) range and aggregates in the i-size range in concrete, respectively; d i d imin With d imaxThese represent the characteristic particle size, minimum particle size, and maximum particle size of aggregates in the i-th interval, respectively.

[0035] Compared to existing concrete aggregate designs, this invention can achieve at least the following beneficial effects:

[0036] (1) The present invention provides a method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation. It considers the influence of all components (cement paste, aggregate, and interface transition zone) on the chloride ion diffusion coefficient and the influence of aggregate particle size on the thickness of the interface transition zone from the perspective of concrete composition. The prediction results are highly accurate and can provide an effective reference for evaluating the chloride ion erosion resistance of concrete.

[0037] (2) The present invention provides a method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation. Its input parameters (the volume ratio of concrete aggregate and the gradation composition) are easy to obtain, while the fixed parameters (the diffusion coefficient of cement paste, the thickness of the interface transition zone, and the specific surface area of ​​aggregate) have good transferability and reusability. The numerical model is simple to calculate and does not require complex modeling, which can realize the rapid evaluation of the chloride ion diffusion coefficient of concrete.

[0038] (3) Compared with finite element simulation inventions, the advantages of this invention are that the calculation process is simple and there is no complicated modeling. The aggregate surface area is measured by experiment, which directly eliminates the aggregate generation step in the modeling process.

[0039] (4) This invention takes into account the relationship between aggregate particle size and interface transition zone thickness. Starting from the actual surface area of ​​the aggregate and combining the thickness, the volume fraction of the interface transition zone is directly calculated. This can accurately assess the volume of the interface transition zone in concrete and adapt to various changes in aggregate gradation. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the sample image after binarization processing in an embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of the distance from aggregate and porosity distribution obtained in an embodiment of the present invention.

[0042] Figure 3 This is a schematic diagram showing the relationship between the chloride ion diffusion coefficient obtained by natural immersion test in an embodiment of the present invention and the chloride ion diffusion coefficient predicted by the method of the present invention.

[0043] Figure 4 The flowchart illustrates the steps of a method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation, as provided in this embodiment of the invention. Detailed Implementation

[0044] The invention will now be described in detail with reference to specific embodiments, so that those skilled in the art can refer to it.

[0045] This invention provides a method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation, comprising the following steps:

[0046] Step S1: Obtain the chloride ion diffusion coefficient D of the cement paste. ref .

[0047] In this step, the chloride ion diffusion coefficient of the cement paste can be obtained using either the natural immersion method or the rapid chloride ion migration coefficient method. Both the natural immersion method and the rapid chloride ion migration method are experimental testing methods, conducted according to ASTM C1556-2013 and GBT 50082-2009 standards. It should be noted that the method for obtaining the chloride ion diffusion coefficient of the cement paste should be consistent with the method used to verify the accuracy of the predicted chloride ion diffusion coefficient of concrete.

[0048] In some embodiments of the present invention, a cement paste is provided, the cementitious material of which is PII 52.5 cement, and the water-cement ratio is 0.41. The chloride ion diffusion coefficient of the cement paste was tested using the natural immersion method and found to be 15.3 × 10⁻⁶. -12 m 2 / s.

[0049] Step S2: Divide the particle size range and obtain the specific surface area s of the aggregate in each particle size range. i .

[0050] In this step, you can choose any one of the following methods to obtain the specific surface area: image analysis, three-dimensional reconstruction, or experimental coating.

[0051] Image analysis mainly relies on image processing algorithms to process aggregate images. The steps are as follows: first, Gaussian blur is used to denoise the aggregate image, then the edge information of the aggregate samples in the binarized image is extracted to form a two-dimensional projection image. The area covered by the aggregate projection pixels is calculated according to the scale. The surface area of ​​the aggregate is calculated by summing the different projection areas according to the shape of the aggregate and the projection angle.

[0052] The method for calculating aggregate surface area using the 3D reconstruction method is as follows: First, surface point cloud data is collected by scanning with a laser scanner. Then, the 3D mesh model is reconstructed using the Delaunay triangulation algorithm. Finally, the surface area of ​​the 3D mesh model is calculated using the triangle area calculation method to calculate the aggregate surface area.

[0053] The steps for obtaining the specific surface area of ​​aggregates using the grouting method include: mixing the aggregates with cement grout with a water-cement ratio of 0.55, drying the mixture, removing any interfering cement grout from the bottom surface, measuring the mass of the cement grout coating the aggregate surface, and then calculating the aggregate surface area based on the coating thickness.

[0054] In some embodiments of the present invention, the specific surface area of ​​aggregates in each particle size range is characterized by a three-dimensional reconstruction method, and the results are shown in Table 1. In Table 1, the particle size ranges A1 to A7 are 0.075-1.18 mm, 1.18-2.36 mm, 2.36-4.75 mm, 4.75-9.50 mm, 9.50-13.2 mm, 13.2-19 mm, and 19-26 mm, respectively.

[0055] Table 1. Specific surface area of ​​aggregate in each interval

[0056] Particle size range A1 A2 A3 A4 A5 A6 A7 <![CDATA[Specific surface area (m 2 / m 3 )]]> 19260 3300 1980 1050 580 470 320

[0057] Step S3: Obtain the thickness of the concrete interface transition zone.

[0058] Specifically, in some embodiments of the present invention, aggregates with a particle size range of 19-26 mm are cut from cured concrete specimens and polished. Images of the samples are acquired using a scanning electron microscope in backscatter mode and binarized. A depth-first search algorithm is used to obtain the aggregate edges in the images. The cement paste region is divided along the aggregate edges at 5 μm intervals, and the porosity of each region is calculated. When the porosity variation rate of a continuous 25 μm region is less than 5-15% (preferably 10%), the distance from the first 5 μm region to the aggregate edge is defined as the thickness h of the interface transition zone. max Specifically, the result of binarization processing of the sample image in this embodiment can be found in [reference needed]. Figure 1 The distance from aggregate to porosity distribution is as follows: Figure 2 As shown, the thickness of the interfacial transition zone of concrete with 19-26mm aggregate is 95μm.

[0059] Step S4: Calculate the chloride ion diffusion coefficient of concrete.

[0060] The formula for calculating the chloride ion diffusion coefficient of concrete is as follows:

[0061] D = D ref ·[f(di)+f(ITZ)]·f(tor)

[0062] Among them, D ref denoted as the chloride ion diffusion coefficient of cement paste, and f(di), f(ITZ), and f(tor) are the influence factors of aggregate dilution effect, ITZ effect, and tortuosity effect on the chloride ion diffusion coefficient of concrete, respectively.

[0063] The factors influencing the dilution effect, ITZ effect, and tortuosity effect are calculated using the following formulas:

[0064] f(di) = 1 - V a -V ITZ

[0065]

[0066] f(ITZ)=n·V ITZ

[0067] Among them, V a V represents the volume percentage of aggregate in concrete. ITZ Let n be the volume percentage of the interfacial transition zone in the concrete, and n be the ratio of the chloride ion diffusion coefficient of the interfacial transition zone to the chloride ion diffusion coefficient of the cement paste. In some embodiments of the present invention, n is taken as 8.

[0068] Among them, the volume ratio V of the interfacial transition zone in concrete ITZ The calculation formula is:

[0069] V ITZ =V a ∑s i ·y i ·h i

[0070]

[0071]

[0072] In the formula, s i Let y be the specific surface area of ​​aggregate in particle size range i. i h represents the proportion of aggregate in particle size range i to the total aggregate volume. i h represents the thickness of the interfacial transition zone for aggregates in particle size range i; max d represents the ITZ thickness of aggregates in the largest particle size range. i d imin With d imax These represent the characteristic particle size, minimum particle size, and maximum particle size of aggregates in particle size range i, respectively.

[0073] The calculation model for the chloride ion diffusion coefficient is as follows:

[0074] D = 15.3·[1-V a -V ITZ +8·V ITZ ] / [1-0.5·ln(1-V a )]

[0075] Among them, V a With V ITZ and represent the volume percentages of aggregate and the interface transition zone in concrete, respectively.

[0076] In some embodiments of the present invention, the aggregate gradation characteristics of concrete are shown in Table 2.

[0077] Table 2

[0078]

[0079] In some embodiments of the present invention, the calculated chloride ion diffusion coefficient of concrete is shown in Table 3.

[0080] Table 3

[0081]

[0082]

[0083] In some embodiments of the present invention, the relationship between the chloride ion diffusion coefficient obtained by natural immersion test and the chloride ion diffusion coefficient predicted by the method of the present invention is as follows: Figure 3 As can be seen, the predicted value of the chloride ion diffusion coefficient of concrete by the present invention is in good agreement with the experimental value, which demonstrates the superiority of the present invention.

[0084] Given a fixed chloride ion diffusion coefficient in cement paste, the chloride ion diffusion coefficient in concrete is mainly determined by aggregate characteristics. The influence of aggregate on the chloride ion diffusion coefficient mainly includes dilution effect, tortuosity effect, and ITZ effect. The degree of influence of dilution effect and ITZ effect corresponds to the migration of chloride ions in cement paste and ITZ, respectively. Tortuosity effect, in turn, affects the migration path of chloride ions. Therefore, the chloride ion diffusion coefficient of concrete can be calculated based on the dilution effect, tortuosity effect, and ITZ effect caused by concrete aggregate.

[0085] The prediction method provided in the foregoing embodiments of this invention has easily obtainable input parameters, a simple calculation process, and requires no complex modeling. It can accurately assess the influence of aggregate particle shape, gradation, and volume fraction on the chloride ion diffusion coefficient of concrete. This method is of paramount importance in the field of concrete durability technology.

[0086] The above-described embodiments are merely preferred embodiments of the present invention. The present invention is not limited to the above embodiments, and the steps can be flexibly modified to produce other variations. Any direct adoption, indirect reference, or equivalent substitution by those skilled in the art based on the disclosure of the present invention is within the scope of protection of the present invention.

Claims

1. A method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation, characterized in that, Includes the following steps: Obtain the chloride ion diffusion coefficient of cement paste D ref ; Obtain the specific surface area of ​​aggregates in each particle size range. s i ; Obtain the thickness of the concrete interface transition zone; The formula for calculating the chloride ion diffusion coefficient of concrete is as follows: In the formula, D ref The chloride ion diffusion coefficient of cement paste. f(di) , f(ITZ) and f(tor) These are the factors influencing the chloride ion diffusion coefficient of concrete, namely, the aggregate dilution effect, the ITZ effect, and the tortuosity effect. The influence factors of dilution effect, ITZ effect, and tortuosity effect on the chloride ion diffusion coefficient of concrete are calculated by the following formulas: in, V a This represents the volume percentage of aggregate in concrete. V ITZ This represents the volume percentage of the interfacial transition zone in concrete. n This is the ratio of the chloride ion diffusion coefficient in the interface transition zone to the chloride ion diffusion coefficient in the cement paste. The formula for calculating the volume ratio of the interface transition zone is: in, s i Let be the ratio of the specific surface area of ​​aggregate in particle size range i to the total specific surface area of ​​aggregate. y i Let be the ratio of the volume of aggregate in particle size range i to the total volume of aggregate. h i Let be the average thickness of the interface transition zone of aggregate in particle size range i. h max This represents the average thickness of the interfacial transition zone for aggregates in the largest particle size range within the concrete. d i Let i be the characteristic particle size of the aggregate in the i-th interval. d imin Let be the minimum particle size of the aggregate in the i-th interval. d imax is the maximum particle size of aggregate in the i-th particle size range.

2. The method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation according to claim 1, characterized in that, The chloride ion diffusion coefficient of cement paste can be obtained by either the natural soaking method or the rapid chloride ion migration coefficient method.

3. The method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation according to claim 1, characterized in that, The specific surface area of ​​aggregate in each interval can be obtained by using any one of the following methods: image analysis, three-dimensional reconstruction, or experimental slurry coating.

4. The method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation according to claim 3, characterized in that, The steps for obtaining the specific surface area of ​​aggregates in each interval using the image analysis method include: denoising the aggregate image, extracting the edge information of the aggregate samples in the binarized image to form a two-dimensional projection image, calculating the area covered by the aggregate projection pixels, and summing the different projection areas according to the aggregate shape and projection angle to calculate the aggregate surface area.

5. The method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation according to claim 3, characterized in that, The steps for obtaining the specific surface area of ​​aggregates in each interval using the three-dimensional reconstruction method include: firstly, collecting surface point cloud data; then, using the Delaunay triangulation algorithm to reconstruct a three-dimensional mesh model; and finally, calculating the surface area of ​​the aggregate by calculating the surface area of ​​the three-dimensional mesh model using the triangle area calculation method.

6. The method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation according to claim 3, characterized in that, The steps for obtaining the specific surface area of ​​aggregates in each interval using the experimental slurry coating method include: mixing aggregates with cement slurry, drying the mixture, removing interfering cement slurry from the bottom surface, measuring the mass of cement slurry coating the surface of the aggregates, and then calculating the aggregate surface area based on the coating thickness.

7. The method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation according to claim 1, characterized in that, The step of obtaining the thickness of the concrete interface transition zone includes: Aggregates of the largest particle size range were cut from the cured concrete specimens and polished to obtain sample images, which were then binarized. Obtain the aggregate edge in the image, divide the cement paste area along the aggregate edge, and calculate the porosity of each area; When the porosity change rate of five consecutive regions is less than the preset value, the distance from the aggregate edge to the region closest to the aggregate is the thickness of the interface transition zone. h max .

8. The method for predicting the chloride ion diffusion coefficient of concrete based on aggregate gradation according to claim 7, characterized in that, A depth-first search algorithm is used to obtain the edges of the aggregate in the image.

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