Macro-meso based method for predicting freeze-thaw damage of recycled coarse-voided concrete

Abstract

The application discloses a macro-micro-based freeze-thaw damage prediction method for macroporous recycled concrete, and comprises the following steps: selecting the same composition as the slurry of the concrete to be predicted, preparing at least six groups of slurry samples and ITZ samples with certain different mixing proportions, and calculating the damage degree of each group by using the initial mesoscopic parameters of the slurry, ITZ and recycled aggregate and the freeze-thaw times; selecting 3-6 kinds of mixing proportions from the at least six groups, preparing macroporous recycled concrete with certain different porosities, and defining the damage degree by using the macro-micro performance parameters and freeze-thaw times; and performing regression analysis on the damage degree of all groups of prepared macroporous recycled concrete, the corresponding filling rate and the damage degrees of the corresponding slurry, ITZ and recycled aggregate, and predicting the damage degree of macroporous recycled concrete with any mixing proportion under any freeze-thaw times by using the regression equation. The freeze-thaw damage prediction method for macroporous recycled concrete has good universality and accuracy.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of recycled concrete, and particularly relates to a macroscopic-mesoscopic-based freeze-thaw damage prediction method for large-pore recycled concrete. BACKGROUND

[0002] At present, there are only freeze-thaw damage degree judgment methods for ordinary concrete at home and abroad. 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, the 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 the functional requirements such as water permeability and sound absorption, the change of the pore structure under the freeze-thaw cycle is also an important freeze-thaw damage feature. Therefore, when judging the freeze-thaw damage degree, not only the macroscopic features such as strength should be considered, but also the mesoscopic features such as porosity and pore structure should be considered. However, there are few studies at home and abroad.

[0003] For the freeze-thaw damage prediction of large-pore recycled concrete, the regression equation of damage degree and freeze-thaw cycle number is directly used at present, or the factors such as mix proportion and paste porosity are indirectly considered. There is a lack of systematic theoretical support, and the prediction formula has poor universality. 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 temperature difference between the inside and outside, and cannot adopt the idea of “first separate research and then integrated analysis”. However, large-pore concrete can adopt this idea, but no scholar has explored it yet. SUMMARY

[0004] The purpose of the present application is to provide a macroscopic-mesoscopic-based freeze-thaw damage prediction method for large-pore recycled concrete, so as to improve the design efficiency of large-pore recycled concrete under freeze-thaw environment and realize the residual life prediction of its bearing capacity and functionality.

[0005] To achieve the above purpose, the present application adopts the following technical solutions:

[0006] A macroscopic-mesoscopic-based freeze-thaw damage prediction method for large-pore recycled concrete, comprising the following steps:

[0007] (1) Select the same composition as the paste of the macroporous recycled concrete to be predicted, design at least 6 mix proportions, wherein the content of any two mix proportions at least changes by 20% or the water-binder ratio differs by at least 0.02; prepare corresponding paste specimens and ITZ specimens using the designed at least 6 mix proportions; select recycled aggregates of the same batch as the recycled aggregates of the macroporous recycled concrete to be predicted to prepare recycled aggregate specimens;

[0008] (2) Perform freeze-thaw test on the paste specimens and ITZ specimens and the recycled aggregate specimens together, and the test method is the same as that of the macroporous recycled concrete to be predicted; according to the freeze-thaw test, three equations are established for calculating the damage degree of the paste using the mesoscopic parameters of the paste at 0 freeze-thaw cycles and the freeze-thaw cycles, for calculating the damage degree of the ITZ using the mesoscopic parameters of the ITZ at 0 freeze-thaw cycles and the freeze-thaw cycles, and for calculating the damage degree of the recycled aggregate using the freeze-thaw cycles; wherein the damage degree calculation equations of the paste and the ITZ have an overall error of less than 10% when calculating the damage degrees of the paste and the ITZ of the 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);

[0009] (3) Design 3-6 porosities of the macroporous recycled concrete, wherein any two porosities differ by at least 5%; select any 3-6 mix proportions from the at least 6 mix proportions designed in step (1), and the number of the selected mix proportions is the same as the number of the designed porosities; use the recycled aggregates of the same batch as the recycled aggregates of the macroporous recycled concrete to be predicted to combine the designed porosities and the selected mix proportions in any order to prepare 3-6 groups of macroporous recycled concrete;

[0010] (4) Perform freeze-thaw test on the prepared 3-6 groups of macroporous recycled concrete, and the test method is the same as that of the macroporous recycled concrete to be predicted; according to the freeze-thaw test, an equation is established for defining the damage degree of all groups of macroporous recycled concrete prepared in step (3) using the mechanical properties, pore structure parameters and freeze-thaw cycles of the macroporous recycled concrete at 0 freeze-thaw cycles; regression analysis is performed on the damage degrees of all groups of macroporous recycled concrete prepared in step (3), the corresponding filling rates and the damage degrees of the paste, the ITZ and the recycled aggregate, and a regression equation is obtained, which has an absolute error of less than 0.1 when calculating the damage degrees of all groups of macroporous recycled concrete prepared in step (3) at any freeze-thaw cycles;

[0011] (5) Test the mesoscopic parameters of the paste and ITZ of the macropore recycled concrete to be predicted under 0 freeze-thaw cycles, input the measured mesoscopic parameters and the paste filling rate and freeze-thaw cycles of the macropore 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 macropore recycled concrete to be predicted under any freeze-thaw cycles without any freeze-thaw test on the macropore recycled concrete to be predicted.

[0012] In step (2), the establishment method of the three equations is as follows:

[0013] (21) Perform multiple function linear regression on the mesoscopic parameters of at least 6 groups of paste test pieces under 0 freeze-thaw cycles and all coefficients of the fitting equation of the compressive strength F c of the paste varying with freeze-thaw cycles n, to obtain a general regression equation f c (n) of the compressive strength F c-paste .

[0014] (22) Perform multiple function linear regression on the mesoscopic parameters of at least 6 groups of ITZ test pieces under 0 freeze-thaw cycles and all coefficients of the fitting equation of the ITZ shear strength F s varying with freeze-thaw cycles n, to obtain a general regression equation f s-ITZ (n) of the ITZ shear strength F s .

[0015] (23) Take the fitting equation of the old paste shedding rate R e varying with freeze-thaw cycles n as the general regression equation r e-aggregate (n) of the shedding rate R e .

[0016] (24) Substitute the general regression equations in steps (21), (22) and (23) into the following formula respectively, to obtain three damage degree calculation equations:

[0017]

[0018] Wherein, 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 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 loss rate of old paste of recycled aggregate under n times of freeze-thaw, respectively; r is the old paste wrapping rate of recycled aggregate.

[0019] In step (4), the establishment method of the regression equation is:

[0020] The fitting equations F(n), W(n) and S(n) of the compressive strength F, pore parameter W and average pore diameter S of macroporous recycled concrete changing with freeze-thaw times n are substituted into the following formula:

[0021]

[0022] wherein, D defined-original is the original definition value of the damage degree of macroporous recycled concrete under n times of freeze-thaw; F(0) and F(n) are the compressive strengths of macroporous recycled concrete under 0 times and n times of freeze-thaw, respectively; W(i) and W(0) are the pore parameters of macroporous recycled concrete under i times and 0 times of freeze-thaw, respectively; S(i) and S(0) are the average pore diameters of macroporous recycled concrete under i times and 0 times of freeze-thaw, respectively.

[0023] In step (4), the regression analysis method is:

[0024] (41) The parameters k and c are calculated by regression as follows:

[0025] D defined-original (n) = R filling D paste (n) = arctanR filling -1 D ITZ (n) = karctanR filling - 1 D aggregate (n) + c

[0026] wherein, R filling is the paste filling rate, i.e. the ratio of the volume of new paste in macroporous recycled concrete to the volume of the gap when the aggregate is tightly packed;

[0027] (42) The damage degree prediction equation is:

[0028] D predicted (n) = R filling D paste (n) + arctanR filling -1 D ITZ (n) + karctanR filling -1 D aggregate (n)

[0029] wherein, D predicted(n) is the predicted value of the freeze-thaw damage degree of the macroporous recycled concrete under n freeze-thaw cycles.

[0030] The compressive strength F c The general regression equation f c-paste (n) is expressed as:

[0031]

[0032] wherein f c-paste (n) is the regression calculated value of the compressive strength of the paste under n freeze-thaw cycles; Minput-c is the mesoscopic parameter matrix of the paste under 0 freeze-thaw cycles; X c is a 4x3 coefficient matrix.

[0033] The shear strength F s The general regression equation f s-ITZ (n) is expressed as:

[0034]

[0035] wherein f s-ITZ (n) is the regression calculated value of the shear strength of the ITZ under n freeze-thaw cycles; Minput-s is the mesoscopic parameter matrix of the ITZ under 0 freeze-thaw cycles; X s is a 3x3 coefficient matrix.

[0036] The spalling rate R e The general regression equation r e-aggregate (n) is expressed as:

[0037]

[0038] wherein re-aggregate(n) is the regression calculated value of the old paste spalling rate of the recycled aggregate under n freeze-thaw cycles; K e is a 3x1 coefficient matrix.

[0039] In step (2), the mesoscopic parameters of the paste include: average pore diameter, pore parameter, indentation elastic modulus; and the mesoscopic parameters of the ITZ include: ITZ thickness, ITZ indentation elastic modulus.

[0040] In step (4), the pore parameter W is:

[0041]

[0042] wherein m and v are the mean value and variance of the pore diameter on the central cross section of the test piece, respectively.

[0043] In step (1), the preparation requirements and methods of the test pieces of the paste, the ITZ and the recycled aggregate are:

[0044] (1) Paste and ITZ specimens: the size is not greater than 20mm*20mm*20mm;

[0045] (2) Recycled aggregate specimen: the recycled aggregate with a particle size of 9.5mm-26.5mm is tightly stacked in a plastic box as a recycled aggregate specimen; wherein the internal size of the plastic box is 100mm*100mm*100mm, and the wall thickness is not greater than 1.5mm;

[0046] The test and calculation method of the old paste shedding rate is as follows:

[0047] After the recycled aggregate after freezing and thawing is placed in a Los Angeles abrasion testing machine, the recycled aggregate is abraded for 100 times under its own weight without steel balls, and then the recycled aggregate is taken out and sieved through a 9.5mm square hole sieve, and the shedding rate is calculated according to the following formula:

[0048]

[0049] Wherein, B is the shedding rate; m0 is the initial mass of the recycled aggregate; m 100 is the sieve residue mass of the recycled aggregate after being abraded for 100 times.

[0050] The advantages of the present application are as follows:

[0051] 1. The prediction method of the present application is divided into three steps, including "calculation of damage degree of paste, ITZ and recycled aggregate", "calculation of damage degree of macroporous recycled concrete" and "regression combination of macro and micro damage", which is clear in organization and perfect in system. The idea of the method is "from local to whole" of multi-scale research. Ordinary concrete is limited by the temperature difference between the inside and outside of the specimen, and cannot directly substitute the freeze-thaw characteristics of paste, ITZ and recycled aggregate into the whole concrete. Macroporous concrete has almost no temperature difference between the inside and outside due to its porous structure, and the idea can be used, but no scholars have explored it. The present application successfully applies the idea to macroporous concrete, decomposes the freeze-thaw damage of macroporous concrete into the damage of micro components, has a systematic theoretical basis, is easy to understand, and is also convenient to find micro weak points.

[0052] 2. The calculation of freeze-thaw damage degree of paste, ITZ and recycled aggregate has not yet been systematically done at home and abroad, and there is almost no combination of micro factors. The concept of freeze-thaw damage degree has not even been established for ITZ and recycled aggregate. The present application proposes the concept of freeze-thaw damage degree of ITZ and recycled aggregate and related algorithms, and uses reasonable and appropriate mechanical and pore micro parameters to calculate the micro mechanical properties and freeze-thaw damage degree of paste and ITZ, successfully establishes the relationship between micro parameters and micro properties, and realizes intuitive explanation of the freeze-thaw damage of paste and ITZ at the micro level, and perfects the idea and method of micro analysis.

[0053] 3. Previous definitions only considered freeze-thaw damage to ordinary concrete, focusing solely on mechanical properties. This invention defines freeze-thaw damage to macroporous recycled concrete. Based on its unique structure, it abandons the traditional mechanical factor of "dynamic elastic modulus," which is untestable in macroporous recycled concrete, and simultaneously considers damage to both its mechanical properties and pore structure. This allows the prediction equation to be successfully applied not only to the mechanical property design of macroporous recycled concrete but also to its permeability and sound absorption performance design. The prediction equation uses the "filling ratio" factor, also considering the unique porosity effect of macroporous recycled concrete, without specifying the porosity value.

[0054] 4. After obtaining the regression equation, this invention can predict the damage degree of macroporous recycled concrete under any number of freeze-thaw cycles using only the microscopic parameters of the paste and ITZ at 0 freeze-thaw cycles, and the filling ratio of the macroporous recycled concrete at 0 freeze-thaw cycles, without requiring any further freeze-thaw tests or consideration of specific mix proportions. If the paste composition of the macroporous recycled concrete changes, only the regression equation needs to be redefined, and this invention remains applicable. This greatly improves the freeze-thaw design efficiency of macroporous recycled concrete.

[0055] 5. The prediction equation for freeze-thaw damage of macroporous recycled concrete simultaneously considers the effects of paste, ITZ, recycled aggregate, and filling ratio, integrating macro- and micro-scale factors. It has systematic theoretical support and is comprehensive and intuitive. The prediction equation only includes three terms: paste damage, ITZ damage, and recycled aggregate damage. The filling ratio appears as a coefficient, which is scientifically reasonable and consistent with reality. This is because the paste damage, ITZ damage, and recycled aggregate damage constitute a "maximum linearly independent set," and other micro-level factors affecting the freeze-thaw damage of macroporous recycled concrete are numerically related to these three terms. The filling ratio, however, affects the damage ratio of paste, ITZ, and recycled aggregate. Therefore, this invention uses the theoretically fewest micro-level factors to obtain the prediction equation.

[0056] 6. Traditional prediction equations rely on factors such as mix proportions, neglecting the uncontrollability of material properties and experimental conditions. The damage degrees of the slurry, ITZ, and recycled aggregates used in this invention must be re-determined by the user based on the measured properties of the materials used and the experimental conditions. This makes the prediction equations universal; regardless of fluctuations in raw material properties or the presence of systematic errors in the testing equipment, the prediction method described in this patent can be used successfully.

[0057] 7. By comparing the paste damage degree, ITZ damage degree, recycled aggregate damage degree and the damage degree of macroporous recycled concrete under different grouting rates, the freeze-thaw weak factors in the paste, ITZ and recycled aggregate under different grouting rates can be found, so not only can the macroporous recycled concrete be designed as ordinary concrete from the aspect of mix proportion, but also its specific "structure" design can be realized by adjusting the grouting rate.

[0058] 8. The regression model used in the freeze-thaw damage degree prediction equation of macroporous recycled concrete is more reasonable, which is specifically reflected in: (1) When the grouting rate decreases, the coefficient of paste damage degree decreases, indicating that the damage contribution of paste damage to the whole concrete decreases, while the coefficients of ITZ and recycled aggregate damage degrees increase, indicating that the damage contribution of ITZ and recycled aggregate damage to the whole concrete increases, which is consistent with the actual situation, because when there is less paste, ITZ and recycled aggregate are less protected and more prone to freeze damage, so the damage proportion is larger, and vice versa; (2) The paste damage degree coefficient is in the range of (0, 1) and changes synchronously with the grouting rate, which is also consistent with the actual situation, and the minimum grouting rate is 0, at which there is no paste, and the contribution of paste damage degree to the overall damage degree is 0; (3) When the paste damage degree coefficient reaches 1, the ITZ damage degree coefficient is 0.785, which is also consistent with the actual situation, because at this time it is ordinary concrete, and ITZ is better protected, so the damage degree contribution is lower than that of paste; (4) The damage degrees of paste and ITZ are strongly bound values, which is also consistent with the actual situation, because ITZ is an extension of paste, and the performance of ITZ is strongly related to the performance of paste; (5) The damage degree of recycled aggregate is always the largest, which is also consistent with the actual situation, because the recycled aggregate has more micro-cracks on its surface, and its frost resistance is usually the worst. DETAILED DESCRIPTION

[0059] The application will be further described below according to specific embodiments.

[0060] In the following examples, the mix proportion and initial grouting rate of the macroporous recycled concrete to be predicted are shown in Table 1. The percentage in the group name is the porosity.

[0061] Table 1

[0062]

[0063] In the following examples, the pore parameter W is:

[0064]

[0065] In the following examples, the paste specimen is a cubic neat paste specimen prepared from cementitious materials, with a size of 10 mm x 10 mm x 10 mm.

[0066] In the following examples, the ITZ test piece is a cube test piece bonded by paste and natural stone, with a size of 10 mm x 10 mm x 10 mm. The paste part and the natural stone part are both cuboids with a size of 10 mm x 10 mm x 5 mm, and the bonding surface is a plane with a size of 10 mm x 10 mm. The composition of the paste is the same as that of the corresponding paste test piece, and the natural stone is cut from granite.

[0067] In the following examples, the recycled aggregate test piece is prepared by tightly stacking recycled aggregate with a particle size of 9.5 mm-26.5 mm in a plastic box as a recycled aggregate test piece. The internal dimensions of the plastic box are 100 mm x 100 mm x 100 mm, and the wall thickness is 1.0 mm.

[0068] In the following examples, the compressive strength, pore parameters, average pore size, and indentation modulus of the paste are tested by the paste test piece. The compressive strength test method is in accordance with the "Standard Test Methods for Basic Properties of Building Mortar" JGJ / T 70-2009.

[0069] In the following examples, the ITZ shear strength, ITZ indentation modulus, and ITZ thickness are tested by the ITZ test piece. The ITZ shear strength test is performed using a self-made shear clamp to test the shear strength of the bonding surface between the paste and the natural stone.

[0070] In the following examples, the old paste shedding rate of the recycled aggregate is tested by the recycled aggregate test piece. The specific testing and calculation method is as follows: after freeze-thaw, the recycled aggregate is placed in a Los Angeles abrasion testing machine without steel balls, and the recycled aggregate is abraded for 100 times under its own weight. Then the recycled aggregate is taken out and passed through a 9.5 mm square hole sieve, and the shedding rate is calculated according to the formula .

[0071] In the following examples, the freeze-thaw test methods for the paste test piece, the ITZ test piece, the recycled aggregate test piece, and the macroporous recycled concrete test piece are the same, and are in accordance with the "Standard Test Methods for Long-term Performance and Durability of Ordinary Concrete" GB / T50082-2009.

[0072] The specific prediction steps are as follows:

[0073] (1) The composition of the paste of the concrete to be predicted is cement, silica fume, and water, so 6 kinds of mix proportions are designed using the same raw materials, as shown in Table 2. Among them, the content of any two kinds of mix proportions changes by at least 50%, or the water-cement ratio differs by at least 0.05. The corresponding paste test pieces and ITZ test pieces are prepared using the 6 kinds of mix proportions. The recycled aggregate test piece is prepared using the same batch of recycled aggregate as the recycled aggregate of the macroporous recycled concrete to be predicted.

[0074] Table 2

[0075]

[0076]

[0077] (2) Freeze-thaw tests were conducted on six groups of slurry specimens, ITZ specimens, and recycled aggregate specimens. The compressive strength F of the six groups of slurry specimens was tested. c By fitting a quadratic function to the number of freeze-thaw cycles (n), a system of six equations, F, is obtained. c The shear strength F of the six groups of ITZ were compared. s By fitting a quadratic function to the number of freeze-thaw cycles (n), a system of six equations, F, is obtained. s ; Regarding the old slurry loss rate R of recycled aggregate e By fitting a quadratic function to the number of freeze-thaw cycles n, we obtain the equation R. e .

[0078] F c =K c [n 2 n 1] T

[0079] F s =K s [n 2 n 1] T

[0080] R e =K e [n 2 n 1] T

[0081] Among them, K c The coefficient matrix is ​​6×3, K s The coefficient matrix is ​​6×3, K e It is a 1×3 coefficient matrix;

[0082] The average pore size, pore parameters, and indentation modulus of the six groups of slurry specimens under zero freeze-thaw cycles were compared with the corresponding group's "slurry compressive strength F". c The compressive strength F is obtained by performing a multivariate linear regression on all coefficients of the fitted equation that varies with the number of freeze-thaw cycles n. c The general regression equation f c-paste (n), this equation is used to calculate the compressive strength of a slurry with any mix ratio under n freeze-thaw cycles:

[0083]

[0084] Among them, f c-paste (n) represents the regression calculation value of the compressive strength of the slurry under n freeze-thaw cycles; M input-c X represents the microscopic parameter matrix of the slurry under zero freeze-thaw cycles; c It is a 4×3 coefficient matrix;

[0085] The ITZ thickness and ITZ indentation modulus of the 6 groups of ITZ specimens under 0 freeze-thaw cycles were compared with the corresponding group's "ITZ shear strength F". s The shear strength F is obtained by performing multivariate linear regression on all coefficients of the fitted equation that varies with the number of freeze-thaw cycles n. s The general regression equation f s-ITZ (n), this equation is used to calculate the ITZ shear strength of a slurry with any mix ratio under n freeze-thaw cycles:

[0086]

[0087]

[0088] Among them, f s-ITZ (n) represents the regression calculation value of the shear strength of the ITZ under n freeze-thaw cycles; Minput-s is the mesoscopic parameter matrix of the ITZ under 0 freeze-thaw cycles; X s It is a 3×3 coefficient matrix;

[0089] The "old slurry shedding rate R" e The fitted equation for the change of freeze-thaw cycles n is directly used as the shedding rate R. e The general regression equation r e-aggregate (n), this equation is used to calculate the old paste loss rate of the only type of recycled aggregate used in this paper:

[0090]

[0091] Where, re-aggregate(n) is the regression calculation value of the old paste loss rate of recycled aggregate under n freeze-thaw cycles; K e It is a 3×1 coefficient matrix;

[0092] Substitute the above three general regression equations into the following formula to calculate the slurry damage degree D under n freeze-thaw cycles. paste (n), ITZ damage degree D ITZ (n) and the degree of damage of recycled aggregate D aggregate (n):

[0093]

[0094] Among them, D paste (n), D ITZ (n) and D aggregate (n) represents the damage degree of the slurry, ITZ, and recycled aggregate under n freeze-thaw cycles, respectively; f c-paste (0) and f c-paste (n) represents the compressive strength of the slurry after 0 and n freeze-thaw cycles, respectively, in 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) is the old paste shedding rate of recycled aggregate under 0 and n freeze-thaw cycles, %; r is the old paste wrapping rate of recycled aggregate, %.

[0095] The overall errors of the three equations are 2.7%, 6.6% and 3.6% respectively, all less than 10%.

[0096] (3) Design three kinds of macroporous recycled concretes with porosities of 20%, 25% and 30%, and any two of the porosities differ by at least 5%. Select M1, M2 and M5 in (1) as the three mix proportions, and use the same batch of recycled aggregate as that of the macroporous recycled concrete to be predicted to prepare M1-20%, M2-25% and M5-30%, three groups of macroporous recycled concretes.

[0097] (4) Perform multiple freeze-thaw tests on the three groups of macroporous recycled concretes 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 and average pore diameter S and freeze-thaw cycles n to obtain fitting equations F(n), W(n) and S(n);

[0098] Substitute the fitting equations F(n), W(n) and S(n) into the damage degree definition formula of macroporous recycled concrete:

[0099]

[0100] wherein, D defined-original (n) is the original definition value of damage degree of macroporous recycled concrete under n freeze-thaw cycles; F(0) and F(n) are the compressive strengths of macroporous recycled concrete under 0 and n freeze-thaw cycles, MPa; W(i) and W(0) are the pore parameters of macroporous recycled concrete under i and 0 freeze-thaw cycles; S(i) and S(0) are the average pore diameters of macroporous recycled concrete under i and 0 freeze-thaw cycles, mm.

[0101] Then substitute the original definition value of damage degree D defined-original (n) into the following formula to calculate the damage proportion coefficient k and the test error value c:

[0102] D defined-original (n)-R filling D paste (n)-arctanR filling -1 D ITZ (n)=karctanR filling -1 D aggregate (n)+c

[0103] wherein R filling is the filling rate;

[0104] According to the calculated damage ratio coefficient k, and in order to simplify the prediction equation, the test error value c is ignored, and the freeze-thaw damage degree prediction equation of the large-pore recycled concrete is obtained:

[0105] D predicted (n) = R filling D paste (n) + arctan R filling -1 D ITZ (n) + k arctan R filling -1 D aggregate (n)

[0106] wherein D predicted (n) is the damage degree prediction value of the large-pore recycled concrete under n freeze-thaw cycles.

[0107] 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:

[0108]

[0109] wherein D defined-final (n) is the corrected value of D defined-original (n), that is, the final definition value of the damage degree of the large-pore recycled concrete under n freeze-thaw cycles; and sgn(n) is a sign function.

[0110] At this time, the prediction equation has been established. In order to check the accuracy of the prediction equation in M1-20%, M2-25%, and M5-30% three groups of test specimens, first, the D defined-final of the large-pore recycled concrete in Table 3 under 0, 40, 80, 120, and 160 freeze-thaw cycles is calculated, and this value is the true value of the damage degree obtained by the test. Then, the corresponding D predicted is calculated, and this value is the prediction value. After comparison, it is found that the absolute error is less than 0.1, so the prediction equation has good accuracy in M1-20%, M2-25%, and M5-30% three groups of test specimens.

[0111] Table 3

[0112]

[0113] (5) The freeze-thaw damage degree of the test pieces in Table 1 which have not been subjected to freeze-thaw test is predicted. The average pore diameter, pore parameter and indentation elastic modulus of the slurry and ITZ of each group of test pieces in Table 1 are tested under 0 freeze-thaw, and the ITZ thickness and ITZ indentation elastic modulus are also tested. The measured micro parameters and the corresponding filling rate in Table 1 are input into the prediction equation in (4), and the predicted damage degree D of each group of test pieces in Table 1 under different freeze-thaw times is calculated predicted As shown in Table 4.

[0114] Table 4

[0115]

[0116] In order to verify the accuracy of the predicted value, the freeze-thaw test is performed on the test pieces in Table 1, and the related performance is tested. The quadratic function fitting of the compressive strength F, pore parameter W and average pore diameter S and freeze-thaw times n is performed respectively, and the fitting equations F(n), W(n) and S(n) are substituted into the above related formula to calculate the real damage degree D defined-final The predicted value D predicted is compared with the real value D As shown in Table 4, the error value is within 0.048, and the prediction method proposed in the present application has certain accuracy and use value.

[0117] The above is only an example for clearly illustrating the present application, and is not a limitation on the embodiments of the present application. For those skilled in the art, some improvements and replacements can be made without departing from the technical principles of the present application, and these improvements and replacements should also be considered as the protection scope of the present application.

Claims

1. A method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective, characterized in that: Includes the following steps: (1) Select the same composition as the paste of the macroporous recycled concrete to be predicted, and design at least 6 mix proportions, wherein the content of at least one component varies by at least 20% in any two mix proportions, or the water-cement ratio differs by at least 0.02; prepare corresponding paste specimens and ITZ specimens using at least 6 designed mix proportions; prepare recycled aggregate specimens using recycled aggregate from the same batch as the recycled aggregate of the macroporous recycled concrete to be predicted. (2) Freeze-thaw tests were conducted on the slurry specimens, ITZ specimens, and recycled aggregate specimens together. The test method was the same as that for the macroporous recycled concrete to be predicted. Based on the freeze-thaw test, three equations were established to calculate the damage degree of the slurry using the microstructure parameters and number of freeze-thaw cycles of the slurry under 0 freeze-thaw cycles, to calculate the damage degree of the ITZ using the microstructure parameters and number of freeze-thaw cycles of the ITZ under 0 freeze-thaw cycles, and to calculate the damage degree of the recycled aggregate using the number of freeze-thaw cycles. The overall error of the equations for calculating the damage degree of the slurry and ITZ was less than 10% when calculating the damage degree of the slurry and ITZ for at least 6 mix proportions designed in step (1). The overall error of the equations for calculating the damage degree of the recycled aggregate was less than 10% when calculating the damage degree of the recycled aggregate in step (1). (3) Design 3-6 types of porosity for large-pore recycled concrete, wherein any two porosities differ by at least 5%; select 3-6 mix proportions from the at least 6 mix proportions designed in step (1), the number of which is the same as the number of designed porosities; use recycled aggregate from the same batch as the recycled aggregate of the large-pore recycled concrete to be predicted, and combine the designed porosity and the arbitrarily selected mix proportions in any order to prepare 3-6 groups of large-pore recycled concrete; (4) Freeze-thaw tests were conducted on the 3-6 groups of macroporous recycled concrete prepared. The test method was the same as that for the macroporous recycled concrete to be predicted. Based on the freeze-thaw test, an equation was established to define the damage degree of all groups of macroporous recycled concrete prepared in step (3) using their mechanical properties, pore structure parameters and number of freeze-thaw cycles under zero freeze-thaw cycles. Regression analysis was performed on the damage degree of all groups of macroporous recycled concrete prepared in step (3) and their corresponding filling ratio and the corresponding damage degree of grout, ITZ and recycled aggregate to obtain the regression equation. The absolute error of the regression equation was less than 0.1 when calculating the damage degree of all groups of macroporous recycled concrete prepared in step (3) under any number of freeze-thaw cycles. (5) Test the microstructure of the slurry and ITZ of the macroporous recycled concrete to be predicted under 0 freeze-thaw cycles. Input the measured microstructure and the slurry ratio and number of freeze-thaw cycles of the macroporous recycled concrete to be predicted under 0 freeze-thaw cycles into the regression equation in step (4). Thus, without conducting any freeze-thaw tests on the macroporous recycled concrete to be predicted, the damage degree of the macroporous recycled concrete with any mix proportion under any number of freeze-thaw cycles can be calculated.

2. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 1, characterized in that: In step (2), the three equations are established as follows: (21) Compare the microstructure parameters of at least 6 groups of slurry specimens under 0 freeze-thaw cycles with the corresponding group's "compressive strength". With the number of freeze-thaw cycles The compressive strength is obtained by performing multivariate linear regression on all coefficients of the fitted equation. The general regression equation ; (22) Compare the microstructure parameters of at least 6 groups of ITZ specimens under 0 freeze-thaw cycles with the corresponding group's "ITZ shear strength". With the number of freeze-thaw cycles The ITZ shear strength is obtained by performing multivariate linear regression on all coefficients of the fitted equation. The general regression equation ; (23) "Old slurry shedding rate" With the number of freeze-thaw cycles The fitting equation for the change is directly used as the shedding rate. The general regression equation ; (24) Substitute the general regression equations from steps (21), (22), and (23) into the following equations to obtain three damage calculation equations: in, , and They are slurry, ITZ and recycled aggregate respectively. n Damage under freeze-thaw cycles; and 0 times and n Compressive strength of slurry under freeze-thaw cycles; and 0 times and n ITZ shear strength under freeze-thaw cycles; and 0 times and n The rate of old slurry loss in recycled aggregates under secondary freeze-thaw cycles; The old slurry coating rate of recycled aggregate.

3. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 2, characterized in that: In step (4), the method for establishing the equation is defined as follows: The compressive strength of macroporous recycled concrete Hole parameters and average aperture With the number of freeze-thaw cycles The fitting equation of the change , and Substitute into the following formula: in, for n Original definition of damage degree of macroporous recycled concrete under secondary freeze-thaw cycles; and 0 times and n Compressive strength of macroporous recycled concrete under secondary freeze-thaw cycles; and They are respectively i Pore ​​parameters of macroporous recycled concrete under 0 and 1 freeze-thaw cycles; and They are respectively i Average pore size of macroporous recycled concrete under 0 and 1 freeze-thaw cycles.

4. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 3, characterized in that: In step (4), the regression analysis method is as follows: (41) Calculate the parameters by regression according to the following formula. and : in, The filling ratio is the ratio of the volume of fresh paste in large-pore recycled concrete to the volume of voids when the aggregate is tightly packed. (42) The damage prediction equation is: in, for n Predicted freeze-thaw damage values ​​for macroporous recycled concrete under multiple freeze-thaw cycles.

5. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 2, characterized in that: compressive strength The general regression equation Represented as: in, for Regression calculation value of compressive strength of slurry under freeze-thaw cycles; The microscopic parameter matrix of the slurry under zero freeze-thaw cycles; It is a 4×3 coefficient matrix.

6. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 2, characterized in that: Shear strength The general regression equation Represented as: in, for Regression calculation of the shear strength of ITZ under two freeze-thaw cycles; The mesoscopic parameter matrix of ITZ under zero freeze-thaw cycles; It is a 3×3 coefficient matrix.

7. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 2, characterized in that: shedding rate The general regression equation Represented as: in, for Regression calculation value of old paste loss rate of recycled aggregate under secondary freeze-thaw conditions; It is a 3×1 coefficient matrix.

8. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 1, characterized in that: In step (2), the microscopic parameters of the slurry include: average pore diameter, pore parameters, and indentation modulus; the microscopic parameters of the ITZ include: ITZ thickness and ITZ indentation modulus.

9. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 3, characterized in that: In step (4), the hole parameters for: = + in, and These represent the mean and variance of the aperture on the central section of the specimen, respectively.

10. The method for predicting freeze-thaw damage of macroporous recycled concrete based on macro-microscopic perspective as described in claim 2, characterized in that: In step (1), the preparation requirements and methods for the test specimens of the slurry, ITZ, and recycled aggregate are as follows: (1) Slurry specimens and ITZ specimens: The size of both specimens shall not exceed 20mm×20mm×20mm; (2) Recycled aggregate specimens: Recycled aggregates with a particle size of 9.5mm-26.5mm are tightly packed in a plastic box as recycled aggregate specimens; the internal dimensions of the plastic box are 100mm×100mm×100mm, and the wall thickness is not greater than 1.5mm. The testing and calculation methods for the old slurry shedding rate are as follows: The freeze-thawed recycled aggregate was placed in a Los Angeles abrasion tester without steel balls, and allowed to abrade under its own weight for 100 cycles. Afterward, the recycled aggregate was removed and passed through a 9.5mm square-hole sieve. The shedding rate was calculated using the following formula: in, The shedding rate; The initial mass of the recycled aggregate; The residue quality of recycled aggregate after 100 abrasion cycles.

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