Freeze-thaw damage prediction method for macropore recycled concrete based on macroscopes and microscopes

Abstract

The invention discloses a macroscopic-mesoscopic-based macropore recycled concrete freeze-thaw damage prediction method, which comprises the following steps: selecting the same components as the slurry of to-be-predicted concrete, and preparing at least six groups of slurry test pieces and ITZ test pieces with certain difference mixing ratios, respectively calculating respective damage degrees by using the initial mesoscopic parameters and the freeze-thaw times of the slurry, the ITZ and the recycled aggregate; 3-6 kinds of materials are selected from at least 6 groups of mixing ratios to respectively prepare macroporous recycled concrete with certain different porosity, and the damage degree is defined by macro-micro performance parameters and freeze-thaw times of the macroporous recycled concrete; and carrying out regression analysis on the damage degrees of all the prepared groups of macroporous recycled concrete, the corresponding slurry filling rates and the damage degrees of the corresponding slurry, ITZ and recycled aggregate, and predicting the damage degree of the macroporous recycled concrete at any mixing ratio under any freezing and thawing times by using a regression equation. The macropore recycled concrete freeze-thaw damage prediction method provided by the invention has relatively good universality and accuracy.

Description

Technical Field

[0001] The present invention belongs to the technical field of recycled concrete, and particularly relates to a prediction method for freeze-thaw damage of large-pore recycled concrete based on macro-meso scale. Background Technique

[0003] At present, there are only methods for judging the freeze-thaw damage degree of ordinary concrete at home and abroad. In the "Standard Test Method for Long-Term Performance and Durability of Ordinary Concrete" GB / T 50082-2009, the strength loss rate, mass loss rate and relative dynamic elastic modulus are used for judgment. In the "Standard Test Method for Resistance of Concrete to Rapid Freezing and Thawing" ASTM C 666 / C666M–03, the relative dynamic elastic modulus and transverse fundamental frequency are used for judgment. The above methods cannot be used for large-pore concrete. On the one hand, large-pore recycled concrete has a large porosity, and it is almost impossible to accurately measure its dynamic elastic modulus and transverse fundamental frequency. On the other hand, due to functional requirements such as water permeability and sound absorption, the change of pore structure under freeze-thaw cycles is also an important freeze-thaw failure characteristic. Therefore, when judging its freeze-thaw damage degree, not only macroscopic characteristics such as strength should be considered, but also mesoscopic characteristics such as porosity and pore structure should be considered, but there is little research at home and abroad.

[0004] For the prediction of freeze-thaw damage of large-pore recycled concrete, at present, the regression equation between the damage degree and the number of freeze-thaw cycles is mostly directly used, or factors such as mix ratio and paste porosity are indirectly considered, lacking systematic theoretical support, and the prediction formula has poor versatility. In fact, the damage degree of large-pore recycled concrete is jointly determined by the damage degrees of mesoscopic components such as paste, ITZ and recycled aggregate. Ordinary concrete is limited by the internal and external temperature difference and cannot adopt the idea of "studying separately first and then integrating and analyzing", while large-pore concrete can adopt this idea, but no scholar has explored it yet. Summary of the Invention

[0005] The purpose of the present invention is to provide a prediction method for freeze-thaw damage of large-pore recycled concrete based on macro-meso scale, so as to improve the design efficiency of large-pore recycled concrete in a freeze-thaw environment and realize the prediction of the remaining service life of its load-bearing capacity and functionality.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions:

[0007] A prediction method for freeze-thaw damage of large-pore recycled concrete based on macro-meso scale, comprising the following steps:

[0008] (1) Select the same composition as the paste of the large-pore recycled concrete to be predicted, and design at least 6 mix proportions. For any two mix proportions, there is at least one component with a content change of at least 20%, or the water-binder ratio difference is at least 0.02. Prepare the corresponding paste specimens and ITZ specimens using at least 6 designed mix proportions. Select recycled aggregate specimens prepared from the same batch of recycled aggregate as the recycled aggregate of the large-pore recycled concrete to be predicted.

[0009] (2) Conduct freeze-thaw tests on the paste specimens, ITZ specimens, and recycled aggregate specimens together. The test method is the same as that of the large-pore recycled concrete to be predicted. Based on the freeze-thaw tests, establish three equations for calculating the damage degree of the paste using the mesoscopic parameters of the paste at 0 freeze-thaw cycles and the number of freeze-thaw cycles, calculating the damage degree of the ITZ using the mesoscopic parameters of the ITZ at 0 freeze-thaw cycles and the number of freeze-thaw cycles, and calculating the damage degree of the recycled aggregate using the number of freeze-thaw cycles. When calculating the damage degrees of the paste and ITZ with at least 6 mix proportions designed in step (1), the overall error of the damage degree calculation equations for the paste and ITZ is less than 10%. When calculating the damage degree of the recycled aggregate in step (1), the overall error of the damage degree calculation equation for the recycled aggregate is less than 10%.

[0010] (3) Design 3 - 6 porosity rates of the large-pore recycled concrete. For any two porosity rates, they differ by at least 5%. Arbitrarily select 3 - 6 mix proportions from at least 6 mix proportions designed in step (1), and the number is the same as the number of designed porosity rates. Use the recycled aggregate from the same batch as the recycled aggregate of the large-pore recycled concrete to be predicted, and combine the designed porosity rates and the arbitrarily selected mix proportions one by one in any order to prepare 3 - 6 groups of large-pore recycled concrete.

[0011] (4) Conduct freeze-thaw tests on the 3 - 6 groups of large-pore recycled concrete prepared. The test method is the same as that of the large-pore recycled concrete to be predicted. Based on the freeze-thaw tests, establish an equation for defining the damage degree of all groups of large-pore recycled concrete prepared in step (3) using its mechanical properties, pore structure parameters, and the number of freeze-thaw cycles at 0 freeze-thaw cycles. Conduct a regression analysis on the damage degrees of all groups of large-pore recycled concrete prepared in step (3), their corresponding grouting rates, and the damage degrees of the corresponding paste, ITZ, and recycled aggregate to obtain a regression equation. When calculating the damage degrees of all groups of large-pore recycled concrete prepared in step (3) at any number of freeze-thaw cycles, the absolute error is less than 0.1.

[0012] (5) Test and measure the mesoscopic parameters of the paste and ITZ of the large-pore recycled concrete to be predicted under 0 freeze-thaw cycles. Input the measured mesoscopic parameters, the paste filling rate and the number of freeze-thaw cycles of the large-pore recycled concrete to be predicted at 0 freeze-thaw cycles into the regression equation in step (4), so as to calculate the damage degree of the large-pore recycled concrete with any mix ratio at any number of freeze-thaw cycles without conducting any freeze-thaw tests on the large-pore recycled concrete to be predicted.

[0013] In step (2), the establishment methods of the three equations are as follows:

[0014] (21) Perform multiple linear regression on all the coefficients of the "fitting equation of the compressive strength F c varying with the number of freeze-thaw cycles n" corresponding to at least 6 groups of paste specimens under 0 freeze-thaw cycles and the mesoscopic parameters of the corresponding groups, and obtain the general regression equation f c (n) of the compressive strength F c-paste ;

[0015] (22) Perform multiple linear regression on all the coefficients of the "fitting equation of the ITZ shear strength F s varying with the number of freeze-thaw cycles n" corresponding to at least 6 groups of ITZ specimens under 0 freeze-thaw cycles and the mesoscopic parameters of the corresponding groups, and obtain the general regression equation f s (n) of the ITZ shear strength F s-ITZ ;

[0016] (23) Take the "fitting equation of the old paste shedding rate R e varying with the number of freeze-thaw cycles n" directly as the general regression equation r e (n) of the shedding rate R e-aggregate ;

[0017] (24) Substitute the general regression equations in steps (21), (22), and (23) into the following formula respectively to obtain three damage degree calculation equations:

[0018]

[0019] where D paste (n), D ITZ (n), and D aggregate (n) are the damage degrees of the paste, ITZ, and recycled aggregate under n freeze-thaw cycles respectively; f c-paste (0) and f c-paste (n) are the compressive strengths of the paste at 0 and n freeze-thaw cycles respectively; f s-ITZ (0) and f s-ITZ (n) are the ITZ shear strengths at 0 and n freeze-thaw cycles respectively; r e-aggregate (0) and r e-aggregate(n) is the exfoliation rate of the old paste of recycled aggregates under 0 and n freeze-thaw cycles respectively; r is the wrapping rate of the old paste of recycled aggregates.

[0020] In step (4), the method for establishing the regression equation is as follows:

[0021] Substitute the fitting equations F(n), W(n), and S(n) of the compressive strength F, pore parameter W, and average pore diameter S of the large-pore recycled concrete varying with the freeze-thaw cycles n into the following formula:

[0022]

[0023] where D defined-original is the original defined value of the damage degree of the large-pore recycled concrete under n freeze-thaw cycles; F(0) and F(n) are the compressive strengths of the large-pore recycled concrete under 0 and n freeze-thaw cycles respectively; W(i) and W(0) are the pore parameters of the large-pore recycled concrete under i and 0 freeze-thaw cycles respectively; S(i) and S(0) are the average pore diameters of the large-pore recycled concrete under i and 0 freeze-thaw cycles respectively.

[0024] In step (4), the regression analysis method is as follows:

[0025] (41) Calculate the parameters k and c by regression according to the following formula:

[0026] D defined-original (n) - R filling D paste (n) - arctanR filling -1 D ITZ (n) = karctanR filling - 1 D aggregate (n) + c

[0027] where R filling is the grouting rate, that is, the ratio of the volume of the new paste in the large-pore recycled concrete to the void volume when the aggregates are tightly packed;

[0028] (42) The damage degree prediction equation is:

[0029] D predicted (n) = R filling D paste (n) + arctanR filling -1 D ITZ (n) + karctanR filling -1 D aggregate (n)

[0030] where D predicted(n) is the predicted value of the freeze-thaw damage degree of macro-porous recycled concrete under n cycles of freeze-thaw.

[0031] Compressive strength F c The general regression equation f c-paste (n) is expressed as:

[0032]

[0033] Among them, f c-paste (n) is the regression calculated value of the compressive strength of the paste under n cycles of freeze-thaw; Minput-c is the mesoscopic parameter matrix of the paste under 0 cycles of freeze-thaw; X c is a 4×3 coefficient matrix.

[0034] Shear strength F s The general regression equation f s-ITZ (n) is expressed as:

[0035]

[0036] Among them, f s-ITZ (n) is the regression calculated value of the shear strength of the ITZ under n cycles of freeze-thaw; Minput-s is the mesoscopic parameter matrix of the ITZ under 0 cycles of freeze-thaw; X s is a 3×3 coefficient matrix.

[0037] Debonding rate R e The general regression equation r e-aggregate (n) is expressed as:

[0038]

[0039] Among them, re-aggregate(n) is the regression calculated value of the old paste debonding rate of recycled aggregates under n cycles of freeze-thaw; K e is a 3×1 coefficient matrix.

[0040] In step (2), the mesoscopic parameters of the paste include: average pore diameter, pore parameter, indentation elastic modulus; the mesoscopic parameters of the ITZ include: ITZ thickness, ITZ indentation elastic modulus.

[0041] In step (4), the pore parameter W is:

[0042]

[0043] Among them, m and v are respectively the mean and variance of the pore diameters on the central cross-section of the specimen.

[0044] In step (1), the preparation requirements and methods for the test specimens of the paste, ITZ and recycled aggregates are:

[0045] (1) Paste specimens and ITZ specimens: The size is not more than 20mm×20mm×20mm;

[0046] (2) Recycled aggregate specimens: The recycled aggregates with a particle size of 9.5mm - 26.5mm are tightly stacked in a plastic box as recycled aggregate specimens; the internal size of the plastic box is 100mm×100mm×100mm, and the wall thickness is not more than 1.5mm;

[0047] The test and calculation method of the old paste shedding rate is as follows:

[0048] Put the freeze-thawed recycled aggregates into the Los Angeles abrasion testing machine without steel balls in the machine, and let the recycled aggregates abrade under their own weight for 100 times. Then take out the recycled aggregates and pass them through a 9.5mm square-hole sieve. The shedding rate is calculated according to the following formula:

[0049]

[0050] Among them, B is the shedding rate; m 0 is the initial mass of the recycled aggregates; m 100 is the remaining mass of the recycled aggregates after 100 times of abrasion.

[0051] The advantages of the present invention are as follows:

[0052] 1. The prediction method of the present invention is divided into 3 steps, including "calculation of the damage degrees of paste, ITZ and recycled aggregates", "calculation of the damage degree of large-pore recycled concrete" and "regression combination of macro-mesoscopic damage". It is well-organized and systematically perfect. The idea of this method is "from local to whole" for multi-scale research. Ordinary concrete is limited by the internal and external temperature difference of the specimens and cannot directly substitute the freeze-thaw characteristics of paste, ITZ and recycled aggregates into the concrete as a whole. However, due to its porous structure characteristics, there is almost no temperature difference inside and outside large-pore concrete, and this idea can be adopted, but no scholars have explored it yet. The present invention successfully applies this idea to large-pore concrete, decomposes the freeze-thaw damage of large-pore concrete into the damage of mesoscopic components, has a systematic theoretical basis, is easy to understand, and is also convenient to find mesoscopic weak points.

[0053] 2. There is no systematic method for calculating the freeze-thaw damage degrees of paste, ITZ and recycled aggregates at home and abroad, and there is almost none considering mesoscopic factors. There is even no concept of freeze-thaw damage degree for ITZ and recycled aggregates. The present invention proposes the concept and related algorithms of the freeze-thaw damage degree for ITZ and recycled aggregates, and at the same time adopts reasonable and appropriate mechanical and pore mesoscopic parameter factors to calculate the mesoscopic mechanical properties and their freeze-thaw damage degrees of paste and ITZ, successfully establishing the relationship between mesoscopic parameters and mesoscopic properties, realizing an intuitive explanation for the freeze-thaw damage of paste and ITZ at the mesoscopic level, and perfecting the ideas and methods of mesoscopic analysis.

[0054] 3. In the past, there was only a definition of the freeze-thaw damage degree of ordinary concrete, which only considered mechanical property factors. The present invention defines the freeze-thaw damage degree of large-pore recycled concrete. Based on its special structure, it abandons the traditional mechanical factor of "dynamic elastic modulus" that cannot be tested in large-pore recycled concrete, and at the same time considers the damage of its mechanical properties and pore structure, so that the prediction equation can not only be successfully used for the mechanical property design of large-pore recycled concrete, but also for its water permeability and sound absorption property design. The prediction equation adopts the factor of "grout filling rate", also considers the influence of the unique porosity of large-pore recycled concrete, and has no requirement for the size of the porosity.

[0055] 4. After obtaining the regression equation, when the paste composition of large-pore recycled concrete remains unchanged, the present invention can predict the damage degree of large-pore recycled concrete at any number of freeze-thaw cycles only by using the mesoscopic parameters of the paste and ITZ at 0 freeze-thaw cycles, and the grout filling rate of large-pore recycled concrete at 0 freeze-thaw cycles, without the need to conduct any freeze-thaw tests and without considering the specific mix proportion. If the paste composition of large-pore recycled concrete changes, only the regression equation needs to be re-determined, and the present invention can still be used. This greatly improves the freeze-thaw design efficiency of large-pore recycled concrete.

[0056] 5. The prediction equation of the freeze-thaw damage degree of large-pore recycled concrete considers the influences of the paste, ITZ, recycled aggregate and grout filling rate at the same time, integrates macro-mesoscopic multi-scale factors, and has systematic theoretical support, which is comprehensive and intuitive. The prediction equation only contains three items: the damage degree of the paste, the damage degree of ITZ and the damage degree of the recycled aggregate. The grout filling rate appears as part of the coefficient, which is scientific and reasonable and conforms to the actual situation, because the three items of the damage degree of the paste, the damage degree of ITZ and the damage degree of the recycled aggregate constitute a "maximal linearly independent group", and other mesoscopic factors that will affect the freeze-thaw damage degree of large-pore recycled concrete have numerical relationships with these three items, while the grout filling rate will affect the damage ratios of the paste, ITZ and recycled aggregate. Therefore, the present invention obtains the prediction equation with the theoretically fewest mesoscopic factors.

[0057] 6. Traditional prediction equations adopt factors such as mix proportion, ignoring the uncontrollability of material properties and test conditions. The damage degrees of the paste, ITZ and recycled aggregate adopted by the present invention need to be re-determined by the user of the invention based on the measured properties of the materials used and the test conditions, so that the prediction equation has universality. No matter how the properties of the raw materials fluctuate and no matter whether there are systematic errors in the test equipment, the prediction method described in this patent can be successfully used.

[0058] 7. By comparing the damage degrees of the paste, ITZ, recycled aggregates, and the damage degree of large-pore recycled concrete under different grouting ratios, the weak factors of freeze-thaw in the paste, ITZ, and recycled aggregates under different grouting ratios can be found. Thus, not only can the "material" design of large-pore recycled concrete similar to that of ordinary concrete be carried out from the perspective of mix proportion, but also its unique "structural" design can be achieved by adjusting the grouting ratio.

[0059] 8. The regression model adopted for the prediction equation of the freeze-thaw damage degree of large-pore recycled concrete is more reasonable, specifically manifested as follows: (1) When the grouting ratio decreases, the coefficient of the paste damage degree decreases, indicating that the contribution of the paste damage to the overall damage of the concrete decreases. At this time, the coefficients of the ITZ and recycled aggregate damage degrees increase, indicating that the contributions of the ITZ and recycled aggregate damage to the overall damage of the concrete increase. This is in line with the actual situation because when there is less paste, the ITZ and recycled aggregates are less protected and are more likely to be damaged by freezing and thawing, so the damage proportion is larger, and vice versa; (2) The coefficient of the paste damage degree changes synchronously with the grouting ratio within the range of (0, 1), which also conforms to the actual situation. The minimum grouting ratio is 0, and at this time there is no paste, and the contribution of the paste damage degree to the overall damage degree is 0; (3) When the coefficient of the paste damage degree reaches 1, the coefficient of the ITZ damage degree is 0.785 at this time, which also conforms to the actual situation because at this time it is ordinary concrete, and the ITZ is better protected, and the damage degree contribution is lower than that of the paste; (4) The damage degrees of the paste and ITZ are strongly bound values, which also conforms to the actual situation because the ITZ is an extension of the paste, and the performance of the ITZ is strongly correlated with the performance of the paste; (5) The damage degree of the recycled aggregates is always the largest, which also conforms to the actual situation because there are more microcracks in the old paste on the surface of the recycled aggregates, and its frost resistance is usually the worst. Detailed implementation manners

[0060] The present invention will be further described below according to specific embodiments.

[0061] In the following embodiments, the mix proportions and initial grouting ratios of the large-pore recycled concrete to be predicted are shown in Table 1. The percentages in the group names are the porosity.

[0062] Table 1

[0063]

[0064] In the following embodiments, the pore parameter W is:

[0065]

[0066] In the following embodiments, the paste specimens are cube-shaped neat paste specimens prepared from cementitious materials, with dimensions of 10 mm × 10 mm × 10 mm.

[0067] In the following examples, the ITZ specimens are cube specimens formed by bonding paste and natural stone, with dimensions of 10 mm × 10 mm × 10 mm. Both the paste part and the natural stone part are cuboids with dimensions of 10 mm × 10 mm × 5 mm, and the bonding surface is a plane of 10 mm × 10 mm. The composition of the paste is the same as that of the paste specimens in the corresponding groups, and the natural stone is cut from granite.

[0068] In the following examples, the preparation method of the recycled aggregate specimens is as follows: The recycled aggregates with a particle size of 9.5 mm - 26.5 mm are tightly stacked in a plastic box to serve as the recycled aggregate specimens. The internal dimensions of the plastic box are 100 mm × 100 mm × 100 mm, and the wall thickness is 1.0 mm.

[0069] In the following examples, the compressive strength, pore parameters, average pore diameter, and indentation modulus of the paste are tested using paste specimens. The test method for compressive strength is carried out with reference to the "Standard Test Method for Basic Properties of Building Mortars" JGJ / T 70 - 2009.

[0070] In the following examples, the shear strength, indentation elastic modulus, and thickness of the ITZ are tested using ITZ specimens. The ITZ shear strength test is carried out using a self - made shear fixture to test the shear strength of the bonding surface between the paste and the natural stone.

[0071] In the following examples, the old paste shedding rate of the recycled aggregates is tested using recycled aggregate specimens. The specific test and calculation method are as follows: The frozen - thawed recycled aggregates are put into a Los Angeles abrasion testing machine without steel balls, and the recycled aggregates are allowed to abrade under their own weight for 100 times. Then the recycled aggregates are taken out and passed through a 9.5 - mm square - hole sieve. The shedding rate is calculated according to the formula Calculate.

[0072] In the following examples, the freeze - thaw test methods for paste specimens, ITZ specimens, recycled aggregate specimens, and large - pore recycled concrete specimens are the same, and all refer to the rapid freeze - thaw method in the "Standard Test Method for Long - Term Performance and Durability of Ordinary Concrete" GB / T50082 - 2009.

[0073] The specific prediction steps are as follows:

[0074] (1) The paste composition of the concrete to be predicted is: cement, silica fume, and water. Therefore, 6 mix proportions are designed using the same raw materials, as shown in Table 2. Among them, for any two mix proportions, there is at least one component with a content change of at least 50%, or the water - binder ratio difference is at least 0.05. Corresponding paste specimens and ITZ specimens are prepared using 6 mix proportions. Recycled aggregate specimens are prepared using recycled aggregates from the same batch as the recycled aggregates of the large - pore recycled concrete to be predicted.

[0075] Table 2

[0076]

[0077]

[0078] (2) Conduct freeze-thaw tests on 6 groups of paste specimens, ITZ specimens, and recycled aggregate specimens together. Respectively, perform quadratic function fitting on the compressive strength F of the 6 groups of pastes c and the number of freeze-thaw cycles n to obtain a system of equations with 6 equations F c ; respectively, perform quadratic function fitting on the shear strength F of the 6 groups of ITZs s and the number of freeze-thaw cycles n to obtain a system of equations with 6 equations F s ; for the old paste shedding rate R of recycled aggregates e and the number of freeze-thaw cycles n, perform quadratic function fitting to obtain the equation R e .

[0079] F c = K c [n 2 n1] T

[0080] F s = K s [n 2 n1] T

[0081] R e = K e [n 2 n1] T

[0082] Among them, K c is a 6×3 coefficient matrix, K s is a 6×3 coefficient matrix, K e is a 1×3 coefficient matrix;

[0083] Perform multiple linear regression on the average pore diameter, pore parameters, and indentation elastic modulus of the 6 groups of paste specimens under 0 freeze-thaw cycles and all the coefficients of the "fitting equation of the compressive strength F of the paste c varying with the number of freeze-thaw cycles n" of the corresponding group to obtain the general regression equation f c of the compressive strength F c-paste (n), which is used to calculate the compressive strength of the paste with any ratio under n freeze-thaw cycles:

[0084]

[0085] Among them, f c-paste (n) is the regression calculated value of the compressive strength of the paste under n freeze-thaw cycles; M input-c is the mesoscopic parameter matrix of the paste under 0 freeze-thaw cycles; X c is a 4×3 coefficient matrix;

[0086] The ITZ thickness and ITZ indentation elastic modulus of 6 groups of ITZ specimens under 0 freeze-thaw cycles and all coefficients of the "ITZ shear strength F s fitting equation varying with the number of freeze-thaw cycles n" were subjected to multiple linear regression to obtain the general regression equation f s of the shear strength F s-ITZ (n), which is used to calculate the ITZ shear strength of paste with any mix ratio under n freeze-thaw cycles:

[0087]

[0088]

[0089] where f s-ITZ (n) is the regression calculated value of the ITZ shear strength under n freeze-thaw cycles; Minput-s is the mesoscopic parameter matrix of the ITZ under 0 freeze-thaw cycles; X s is a 3×3 coefficient matrix;

[0090] The "fitting equation of the old paste shedding rate R e varying with the number of freeze-thaw cycles n" was directly used as the general regression equation r e of the shedding rate R e-aggregate (n), which is used to calculate the old paste shedding rate of the only type of recycled aggregate used in this paper:

[0091]

[0092] where re-aggregate(n) is the regression calculated value of the old paste shedding rate of recycled aggregate under n freeze-thaw cycles; K e is a 3×1 coefficient matrix;

[0093] The above 3 general regression equations were respectively substituted into the following formula to calculate the paste damage degree D paste (n), ITZ damage degree D ITZ (n) and recycled aggregate damage degree D aggregate (n):

[0094]

[0095] where D paste (n), D ITZ (n) and D aggregate (n) are respectively the damage degrees of paste, ITZ and recycled aggregate under n freeze-thaw cycles; f c-paste (0) and f c-paste are respectively the compressive strengths of paste at 0 and n freeze-thaw cycles, MPa; f s-ITZ (0) and fs-ITZ \((n)\) is the ITZ shear strength under 0 and \(n\) freeze - thaw cycles, MPa; \(r\) e-aggregate (0) and \(r\) e-aggregate (n) are the old paste shedding rates of recycled aggregates under 0 and \(n\) freeze - thaw cycles, %; \(r\) is the old paste wrapping rate of recycled aggregates, %.

[0096] After inspection, the overall errors of the three equations are 2.7%, 6.6% and 3.6% respectively, all less than 10%.

[0097] (3) Design the porosity of three kinds of large - pore recycled concrete as 20%, 25% and 30%, and the porosity difference between any two of them is at least 5%. Select three mix ratios M1, M2 and M5 in (1), use recycled aggregates from the same batch as those of the large - pore recycled concrete to be predicted, and prepare three groups of large - pore recycled concrete, namely M1 - 20%, M2 - 25% and M5 - 30%.

[0098] (4) Conduct multiple freeze - thaw tests on the three groups of large - pore recycled concrete respectively, and obtain the compressive strength \(F\), pore parameter \(W\) and average pore diameter \(S\) under different freeze - thaw cycles. According to the obtained experimental results, perform quadratic function fitting on the compressive strength \(F\), pore parameter \(W\), average pore diameter \(S\) and freeze - thaw cycle number \(n\) to obtain the fitting equations \(F(n)\), \(W(n)\) and \(S(n)\);

[0099] Substitute the fitting equations \(F(n)\), \(W(n)\) and \(S(n)\) into the damage degree definition formula of large - pore recycled concrete:

[0100]

[0101] where \(D\) defined-original (n) is the original definition value of the damage degree of large - pore recycled concrete under \(n\) freeze - thaw cycles; \(F(0)\) and \(F(n)\) are the compressive strengths of large - pore recycled concrete under 0 and \(n\) freeze - thaw cycles respectively, MPa; \(W(i)\) and \(W(0)\) are the pore parameters of large - pore recycled concrete under \(i\) and 0 freeze - thaw cycles respectively; \(S(i)\) and \(S(0)\) are the average pore diameters of large - pore recycled concrete under \(i\) and 0 freeze - thaw cycles respectively, mm.

[0102] Then substitute the original definition value of the damage degree \(D\) defined-original (n) into the following formula to calculate the damage proportion coefficient \(k\) and the test error value \(c\):

[0103] \(D\) defined-original (n)-R filling \(D\) paste (n)-arctanR filling -1 \(D\) ITZ (n)=karctanR filling -1 D aggregate (n) + c

[0104] Among them, R filling is the grouting rate;

[0105] According to the calculated damage proportion coefficient k, and in order to simplify the prediction equation, the test error value c is ignored, and the prediction equation of the freeze-thaw damage degree of large-pore recycled concrete is obtained:

[0106] D predicted (n) = R filling D paste (n) + arctanR filling -1 D ITZ (n) + karctanR filling -1 D aggregate (n)

[0107] Among them, D predicted (n) is the predicted value of the freeze-thaw damage degree of large-pore recycled concrete under n freeze-thaw cycles.

[0108] Since the test error value c is ignored in the prediction equation, D defined-original (n) needs to be corrected, and the correction formula is as follows:

[0109]

[0110] Among them, D defined-final (n) is the value after D defined-original (n) is corrected, that is, the final defined value of the freeze-thaw damage degree of large-pore recycled concrete under n freeze-thaw cycles; sgn(n) is the sign function.

[0111] At this time, the prediction equation has been established. In order to verify the accuracy of the prediction equation in the three groups of specimens M1-20%, M2-25% and M5-30%, first calculate D defined-final of the large-pore recycled concrete in all groups in Table 3 under 0, 40, 80, 120 and 160 freeze-thaw cycles. This value is the true value of the damage degree obtained from the test. Then calculate the corresponding D predicted , which is the predicted value. After comparison, it is found that the absolute error is less than 0.1. Therefore, the prediction equation has good accuracy in the three groups of specimens M1-20%, M2-25% and M5-30%.

[0112] Table 3

[0113]

[0114] (5) Predict the freeze-thaw damage degree of the specimens to be pre-tested in Table 1 that have not undergone freeze-thaw tests. Test the average pore diameter, pore parameters, and indentation elastic modulus of the paste and ITZ of each group of specimens to be pre-tested in Table 1 under 0 freeze-thaw cycles, as well as the ITZ thickness and ITZ indentation elastic modulus. Input the measured mesoscopic parameter results, the corresponding grouting rate in Table 1, and the target number of freeze-thaw cycles into the prediction equation in (4) to calculate the predicted damage degree D of each group of specimens in Table 1 under different numbers of freeze-thaw cycles predicted , as shown in Table 4.

[0115] Table 4

[0116]

[0117] To verify the accuracy of the predicted values, conduct freeze-thaw tests on the specimens to be predicted in Table 1, test the relevant properties, perform quadratic function fitting on the compressive strength F, pore parameters W, and average pore diameter S with the number of freeze-thaw cycles n respectively, substitute the fitting equations F(n), W(n), and S(n) into the above relevant formulas, and calculate the true damage degree D defined-final , compare it with the predicted value D predicted . As shown in Table 4, it can be seen that the error value is within 0.048, and the prediction method proposed by the present invention has a certain degree of accuracy and application value.

[0118] The above are only examples for clearly explaining the present invention, and are not limitations on the embodiments of the present invention. For those of ordinary skill in the art in this technical field, without departing from the technical principle of the present invention, several improvements and substitutions can be made, and these improvements and substitutions should also be regarded as the protection scope of the present invention.

Claims

1. A macro-microscopic freeze-thaw damage prediction method for macroporous recycled concrete, characterized by: The following steps are involved: (1) Select the same composition as the paste of the macroporous recycled concrete to be predicted, design at least 6 mix ratios, among which any two mix ratios have at least one component whose content varies by at least 20%, or whose water-binder ratio differs by at least 0.02; prepare corresponding paste specimens and ITZ specimens using the designed at least 6 mix ratios; select recycled aggregate from the same batch as the recycled aggregate of the macroporous recycled concrete to be predicted to prepare recycled aggregate specimens; (2) freeze-thaw tests are performed on the slurry specimens, ITZ specimens and recycled aggregate specimens together, and the test method is the same as the test method for the large-pore recycled concrete to be predicted; based on the freeze-thaw test, three equations are established to calculate the damage degree of the slurry using the microscopic parameters of the slurry under 0 freeze-thaw cycles and the number of freeze-thaw cycles, to calculate the damage degree of the ITZ using the microscopic parameters of the ITZ under 0 freeze-thaw cycles and the number of freeze-thaw cycles, and to calculate the damage degree of the recycled aggregate using the number of freeze-thaw cycles; wherein the damage degree calculation equations of the slurry and ITZ have an overall error of less than 10% when calculating the damage degree of the slurry and ITZ of at least 6 mix proportions designed in step (1), and the damage degree calculation equation of the recycled aggregate has an overall error of less than 10% when calculating the damage degree of the recycled aggregate in step (1); (3) designing 3-6 porosities of large-pore recycled concrete, wherein any two porosities differ by at least 5%; randomly selecting 3-6 mix ratios from the at least 6 mix ratios designed in step (1), the number of which is the same as the number of designed porosities; using recycled aggregates from the same batch as the recycled aggregates of the large-pore recycled concrete to be predicted, combining the designed porosities and the randomly selected mix ratios one by one in any order, to prepare 3-6 groups of large-pore recycled concrete; (4) freeze-thaw tests are performed on the prepared 3-6 groups of macroporous recycled concrete, and the test method is the same as the test method of the macroporous recycled concrete to be predicted; based on the freeze-thaw test, an equation for defining the damage degree of all groups of macroporous recycled concrete prepared in step (3) is established using its mechanical properties, pore structure parameters and freeze-thaw times under 0 freeze-thaw cycles; regression analysis is performed on the damage degree of all groups of macroporous recycled concrete prepared in step (3) and its corresponding grouting ratio and the corresponding damage degree of slurry, ITZ and recycled aggregate to obtain a regression equation, and the absolute error of the regression equation when calculating the damage degree of all groups of macroporous recycled concrete prepared in step (3) under any freeze-thaw times is less than 0.1; (5) The mesoscopic parameters of the slurry and ITZ of the macroporous recycled concrete to be predicted under zero freeze-thaw cycles are tested experimentally, and the measured mesoscopic parameters and the grouting ratio and freeze-thaw cycles of the macroporous recycled concrete to be predicted under zero freeze-thaw cycles are input into the regression equation in step (4), thereby calculating the damage degree of the macroporous recycled concrete to be predicted with any mix ratio under any freeze-thaw cycles without conducting any freeze-thaw tests on the macroporous recycled concrete to be predicted.

2. According to claim 1, a macro-microscopic freeze-thaw damage prediction method for macroporous recycled concrete is characterized by: In step (2), the three equations are established as follows: (21) The microscopic parameters of at least six groups of slurry specimens under zero freeze-thaw cycles were compared with the compressive strength F c All coefficients of the fitting equation "varying with the number of freeze-thaw times n" were subjected to multivariate linear regression to obtain the compressive strength F c The general regression equation f c-paste (n); (22) The microscopic parameters of at least 6 groups of ITZ specimens under 0 freeze-thaw cycles were compared with the corresponding groups' "ITZ shear strength F s All coefficients of the fitting equation "varying with the number of freeze-thaw times n" were subjected to multivariate linear regression to obtain the ITZ shear strength F s The general regression equation f s-ITZ (n); (23) The old slurry shedding rate R e The fitting equation that changes with the number of freeze-thaw cycles n is directly used as the shedding rate R e The general regression equation r e-aggregate (n); (24) Substitute the general regression equations in step (21), step (22), and step (23) into the following equations to obtain three damage degree calculation equations: Among them, D paste (n), D ITZ (n) and D aggregate (n) are the damage degrees of paste, ITZ and recycled aggregate under n freeze-thaw cycles; f c-paste (0) and f c-paste (n) is the compressive strength of the paste under 0 and n freeze-thaw cycles respectively; f s-ITZ (0) and f s-ITZ (n) are the ITZ shear strengths under 0 and n freeze-thaw cycles, respectively; r e-aggregate (0) and r e-aggregate (n) is the shedding rate of old slurry of recycled aggregate under 0 and n freeze-thaw cycles respectively; r is the wrapping rate of old slurry of recycled aggregate.

3. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 2 is characterized by: In step (4), the method for establishing the definition equation is: Substitute the fitting equations F(n), W(n) and S(n) of the compressive strength F, pore parameter W and average pore size S of macroporous recycled concrete with the number of freeze-thaw cycles n into the following formula: Among them, D defined-original is the original definition value of the damage degree of macroporous recycled concrete under n freeze-thaw cycles; F(0) and F(n) are the compressive strength of macroporous recycled concrete under 0 and n freeze-thaw cycles, respectively; W(i) and W(0) are the pore parameters of macroporous recycled concrete under i and 0 freeze-thaw cycles, respectively; S(i) and S(0) are the average pore sizes of macroporous recycled concrete under i and 0 freeze-thaw cycles, respectively.

4. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 3 is characterized by: In step (4), the regression analysis method is: (41) The parameters k and c are calculated by regression according to the following formula: D defined-original (n)-R filling D paste (n)-arctanR filling -1 D ITZ (n) = karctanR filling -1 D aggregate (n)+c, where R filling is the grouting ratio, which is the ratio of the new slurry volume in the macroporous recycled concrete to the void volume when its aggregates are tightly packed; (42) The damage degree prediction equation is: <h2 style=";text-align:left;direction:ltr">D<h2 style=";text-align:left;direction:ltr"> predicted <h2 style=";text-align:left;direction:ltr"> (n)=R<h2 style=";text-align:left;direction:ltr"> filling <h2 style=";text-align:left;direction:ltr"> D<h2 style=";text-align:left;direction:ltr"> paste <h2 style=";text-align:left;direction:ltr"> (n)+arctanR<h2 style=";text-align:left;direction:ltr"> filling <h2 style=";text-align:left;direction:ltr"> -1 <h2 style=";text-align:left;direction:ltr"> D<h2 style=";text-align:left;direction:ltr"> ITZ <h2 style=";text-align:left;direction:ltr"> (n)+karctanR<h2 style=";text-align:left;direction:ltr"> filling <h2 style=";text-align:left;direction:ltr"> -1 <h2 style=";text-align:left;direction:ltr"> D<h2 style=";text-align:left;direction:ltr"> aggregate <h2 style=";text-align:left;direction:ltr"> (n) Among them, D predicted (n) is the predicted value of freeze-thaw damage of macroporous recycled concrete after n freeze-thaw cycles.

5. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 2 is characterized by: Compressive strength F c The general regression equation f c-paste (n) is expressed as: Among them, f c-paste (n) is the regression calculation value of the compressive strength of the slurry after n freeze-thaw cycles; M input-c is the microscopic parameter matrix of the slurry under 0 freeze-thaw cycles; X c is a 4×3 coefficient matrix.

6. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 2 is characterized by: Shear strength F s The general regression equation f s-ITZ (n) is expressed as: Among them, f s-ITZ (n) is the regression calculation value of the shear strength of ITZ under n freeze-thaw cycles; M input-s is the microscopic parameter matrix of ITZ under 0 freeze-thaw cycles; X s is a 3×3 coefficient matrix.

7. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 2 is characterized by: Dropout rate R e The general regression equation r e-aggregate (n) is expressed as: Where, re-aggregate(n) is the regression calculation value of the old slurry shedding rate of recycled aggregate under n freeze-thaw cycles; K e is a 3×1 coefficient matrix.

8. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 1 is characterized by: In step (2), the microscopic parameters of the slurry include: average pore size, pore parameters, and indentation modulus; the microscopic parameters of the ITZ include: ITZ thickness and ITZ indentation modulus.

9. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 3 is characterized by: In step (4), the hole parameter W is: Where m and v are the mean and variance of the pore diameter on the central section of the specimen, respectively.

10. The freeze-thaw damage prediction method of macroporous recycled concrete based on macro-micro perspective according to claim 1 is characterized by: In step (1), the preparation requirements and methods of the test specimens of the slurry, ITZ and recycled aggregate are as follows: (1) Slurry specimens and ITZ specimens: the size shall not exceed 20 mm × 20 mm × 20 mm; (2) Recycled aggregate specimen: Recycled aggregate with a particle size of 9.5 mm to 26.5 mm was tightly stacked in a plastic box as a recycled aggregate specimen; the internal dimensions of the plastic box were 100 mm × 100 mm × 100 mm, and the wall thickness was no more than 1.5 mm; The test and calculation method of the old slurry shedding rate is: The recycled aggregate after freezing and thawing was put into the Los Angeles abrasion tester without steel balls. The recycled aggregate was abraded 100 times under its own weight. After that, the recycled aggregate was taken out and passed through a 9.5mm square hole sieve. The shedding rate was calculated as follows: Where B is the shedding rate; m0 is the initial mass of recycled aggregate; m 100 It is the sieve residue mass of recycled aggregate after 100 times of attrition.

Images