CN108333082B - Construction method of multi-scale prediction model for chloride ion diffusion coefficient of unsaturated concrete - Google Patents

Abstract

The invention discloses a method for constructing a multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete. Concrete is regarded as a cement-based composite material composed of materials of different scales, starting from a small-scale hardened cement paste and gradually transitioning to a large-scale The chloride ion diffusion coefficient prediction model of different scales of cement-based materials was established in turn, and then the influence of the water saturation in the concrete on its chloride ion diffusion was considered, and finally the multi-scale prediction model of the chloride ion diffusion coefficient of unsaturated concrete was established. This method takes into account the influence of the internal water saturation of concrete on its chloride ion diffusion, and can predict the chloride ion diffusion coefficient of unsaturated concrete more scientifically, reasonably and accurately. is of great significance.

Description

Construction method of multi-scale prediction model for chloride ion diffusion coefficient of unsaturated concrete

technical field

The invention belongs to a method for predicting the chloride ion diffusion coefficient of unsaturated concrete, in particular to a method for constructing a multi-scale prediction model of the chloride ion diffusion coefficient of unsaturated concrete.

Background technique

Concrete is a non-homogeneous material composed of cement, coarse aggregate and fine aggregate, and there are many pores and micro-cracks inside, which provide channels for harmful substances to enter the interior of concrete. The intrusion of chloride ions into the interior of reinforced concrete through these channels can cause severe corrosion of steel bars, thereby affecting the safety of the structure.

The transport of chloride ions in concrete is a complex process, and factors such as concrete saturation, water pressure and applied electric field have important effects on chloride ion transport. According to the power source of transmission, the mechanism of chloride ion transport in concrete is mainly divided into diffusion, osmosis, capillary action, electrochemical migration and binding.

The diffusion of chloride ions in concrete means that when the concrete is in a saturated state, the pore water does not migrate. Due to the difference in the level of chloride ions in different regions, chloride ions migrate from places with high concentrations to places with low concentrations. The diffusion of chloride ions in concrete is divided into steady-state diffusion and non-steady-state diffusion. Unsteady diffusion means that the chloride ion concentration at any point changes with time and space during the chloride ion diffusion process. Steady-state diffusion means that the chloride ion concentration at any point in the diffusion process does not change with time and space, and the parameters of each diffusion characteristic remain unchanged.

Osmosis means that when there is a pressure difference inside the concrete due to different hydrostatic pressures in different regions, the pore solution flows directionally under the action of the pressure difference, and the chloride ions migrate with the pore solution as the carrier. When the concrete is in an unsaturated state, pressure is generated due to the different humidity in different areas inside the concrete, which promotes the migration of chloride ions from the higher humidity part to the lower humidity part using water as the carrier.

The transmission of chloride ions in concrete is greatly affected by the environment, and the transmission mechanism is usually the coupling of the above-mentioned mechanisms. However, a large number of studies have shown that the transportation process of chloride ions in concrete under unsaturated state is mainly the diffusion of chloride ion concentration in pore solution and the convection process of chloride ion with pore solution. The internal water saturation of concrete has an important influence on its chloride ion diffusion characteristics. However, most of the current prediction models for the chloride ion diffusion coefficient of concrete do not consider the water saturation of concrete. In the saturated state, there are few models for predicting the chloride ion diffusion coefficient of concrete considering the influence of water saturation. At present, the relevant models mainly include the chloride ion transport model established by Sun Jicheng et al. under the coupled action of dry-wet and load. Diffusion model. Although the above two models have related concepts related to water saturation, neither of them has directly established a related model of water saturation. The foreign scholar Hall established a prediction model for the change of the chloride ion diffusion coefficient of concrete with pore saturation during the wetting process, but the model involves the uncertainty of the values of relevant empirical parameters, and the applicability needs to be further verified. The theoretical model of the change of the chloride ion diffusion coefficient of concrete with pore water saturation when the water-cement ratio is 0.6 is obtained by fitting. However, this model has relatively large limitations and cannot accurately predict the chloride ion diffusion coefficient of concrete with low water saturation. .

SUMMARY OF THE INVENTION

The technical problem to be solved by the present invention is to provide a method for constructing a multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete.

In order to solve the above-mentioned technical problems, the present invention adopts the following technical solutions:

The construction method of the multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete considers concrete as a cement-based composite material composed of materials of different scales, starting from small-scale hardened cement paste, gradually transitioning to large-scale concrete, and then building up The chloride ion diffusion coefficient prediction model of different scales of cement-based materials, and then the influence of water saturation in concrete on its chloride ion diffusion is considered, and finally the multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete is established.

The above construction method includes the following steps:

<1> Establish a prediction model for the chloride ion diffusion coefficient of cement paste;

<2> Establish a new mortar chloride ion diffusion coefficient prediction model;

<3> Establish a multi-scale prediction model for the chloride ion diffusion coefficient of ordinary concrete;

<4> Establish a prediction model of chloride ion diffusion coefficient of unsaturated concrete.

Step <1> is performed as follows:

Cement particles of different particle sizes react with water to form hardened cement paste. The composition, the volume fraction of each component in the cement paste, changes with the water-cement ratio and the development of age, and the various components in the paste are mixed with each other, which together affect the chloride ion diffusion coefficient after the cement paste is hardened. Combined with generalized self-consistent method and Mori-Tanaka method, the prediction model of chloride ion diffusion coefficient of hardened cement paste is established as follows:

的表达式为：In formula (30), φ,

The expression is:

In formula (31), D _hCSH is the diffusion coefficient of the high-density CSH gel layer in the cement; D _lCSH is the diffusion coefficient of the low-density CSH gel layer in the cement; V _α is the total density of the high-density CSH gel layer in the hardened cement paste. volume fraction of cement volume; V _β is the sum of the volume fraction of unhydrated cement particles and high-density CSH gel layer in the hardened cement paste;

The high-density CSH gel layer contains cement hydration products (such as CH, AF) and the high-density CSH gel layer matrix, when the hydration products are non-diffused and relatively uniformly distributed in the high-density CSH gel layer matrix , according to the matrix-inclusion model, the expression of D _hCSH is:

in:

为通过试验和数值计算得到的氯离子在高密度C-S-H凝胶层中的扩散系数，取

V_hCSH分别是CH、AF、高密度的C-S-H凝胶层基体在高密度C-S-H凝胶层中的体积分数；α_h、β_h为中间变量；In formulas (32) to (34),

For the diffusion coefficient of chloride ions in the high-density CSH gel layer obtained by experiment and numerical calculation, take

V _hCSH is the volume fraction of CH, AF, and high-density CSH gel layer matrix in the high-density CSH gel layer, respectively; α _h , β _h are intermediate variables;

The low-density CSH gel layer not only contains cement hydration products (such as CH, AF) and the low-density CSH gel layer matrix, but also contains many capillary pores. Considering that the hydration products and capillary pores are non-diffusive and It is relatively uniformly distributed in the matrix of the low-density CSH gel layer. According to the Mori-Tanaka method of the inclusion of multiphase materials, the expression of D _lCSH is:

in:

ζ= _{Vcap(Dcap-D'lCSH ) (} 40)

为通过试验和数值计算得到的氯离子在低密度C-S-H凝胶层中的扩散系数，取

V_cap、V_lCSH分别是CH、AF、毛细孔、低密度的C-S-H凝胶层基体在低密度C-S-H凝胶层中的体积分数；D_cap为毛细孔的有效扩散系数，取D_cap＝2.03×10^-9m²/s；α_l、β_l、ξ、ζ为中间变量；In formulas (35)-(40), D' _lCSH is the effective diffusion coefficient of the equivalent medium layer after the cement hydration products (such as CH, AF) and the low-density CSH gel layer matrix are evenly mixed;

For the diffusion coefficient of chloride ions in the low-density CSH gel layer obtained by experiment and numerical calculation, take

V _cap and V _lCSH are the volume fractions of CH, AF, capillary pores, and low-density CSH gel layer matrix in the low-density CSH gel layer, respectively; D _cap is the effective diffusion coefficient of capillary pores, taking D _cap = 2.03× 10 ^-9 m ² /s; α _l , β _l , ξ, ζ are intermediate variables;

The volume fractions of various hydration products of the hardened cement paste are V _CH , V _AF , V _CSH (V _lCSH and V _hCSH ), the volume fraction of unhydrated cement particles is V _U , and the volume fraction of capillary pores is V _cap , then there are:

V _CH + V _AF + V _lCSH + V _hCSH + V _U + V _cap = 1 (41)

and have:

The expressions of V _α and V _β in formula (31) are:

Combining formulas (30) to (44), the prediction model for the chloride ion diffusion coefficient of cement paste with each volume parameter as a variable is obtained as:

D_cap为试验和数值计算得出的实测值；假定饱和水泥浆体的质量为1g，根据普通硅酸盐水泥化学反应方程式，得到净浆中各体积分数的预测模型，为：In formula (45),

D _cap is the measured value obtained by experiment and numerical calculation; assuming that the mass of saturated cement paste is 1g, according to the chemical reaction equation of ordinary Portland cement, the prediction model of each volume fraction in the paste is obtained as:

In formulas (46) to (51), n—initial water-cement ratio of cement slurry; t—age period; ρ _c , ρ _lCSH , ρ _hCSH —density of cement, density of low-density CSH gel, low-density CSH Density of gel; mass fraction of p ₁ , p ₂ , p ₃ , p ₄ -C ₃ S, C ₂ S, C ₃ A, C ₄ AF in cement clinker.

Step <2> is performed as follows:

On the microscopic scale, the new mortar can be regarded as composed of fine aggregate (sand, which can be approximately spherical), hardened cement paste and ITZ between the two. The generalized self-consistent method is used to predict and establish the chloride ion diffusion coefficient of the new mortar. The prediction model is:

In formula (52), ξ, ζ are intermediate variables, there are:

In formula (53), D _HCP is the chloride ion diffusion coefficient of the hardened cement paste predicted in step 1; D _ITZ is the chloride ion diffusion in the interface transition zone (ITZ) between the fine aggregate in the new mortar and the hardened cement paste coefficient; VA is the volume fraction of fine aggregate in the new mortar, calculated from the mix ratio of the mortar; V _ITZ is the volume fraction of the interface transition zone ( _ITZ ) between the fine aggregate in the new mortar and the hardened cement paste , the value range is 5%-30%;

Among them, D _ITZ is related to the thickness of the interface transition zone (ITZ) between the fine aggregate and the hardened cement paste and the diffusion characteristics of the matrix material, then the expression of D _ITZ of the new mortar with cement as the matrix is:

D _ITZ = 117.563D _HCP h _ITZ ^-0.8772 (54)

In formula (54), h _ITZ is the thickness of the interface transition zone in the new mortar, which is related to the average radius of cement particles, and takes h _ITZ = 25 μm.

Step <3> is performed as follows:

For ordinary aggregate concrete, it can be regarded as composed of natural coarse aggregate, new mortar matrix and the interface transition zone between the two on the mesoscopic scale. The microstructure model of concrete can be regarded as a multiphase sphere model. Self-consistent model, the multi-scale prediction model of chloride ion diffusion coefficient of natural coarse aggregate concrete is established as follows:

In formula 55), υ, ω are intermediate variables, there are:

In formula (56), D _NM represents the chloride ion diffusion coefficient of the new mortar obtained in step 2; D _NITZ represents the chloride ion diffusion coefficient of the interface transition zone (ITZ) between the natural aggregate in the concrete and the new mortar; V _NA represents The volume fraction of natural coarse aggregate, calculated from the mix ratio of concrete; V _NITZ represents the volume fraction of the interfacial transition zone (ITZ) between natural coarse aggregate and new mortar in concrete, ranging from 0.1% to 2.0 %;

Among them, D _NITZ is related to the thickness of the interface transition zone (ITZ) between the natural aggregate and the new mortar and the diffusion characteristics of the matrix material, then the expression of D _ITZ of the ordinary concrete with the new mortar as the matrix is:

D _NITZ = 117.563D _NM h _NITZ ^-0.8772 (57)

In formula (57), h _NITZ is the thickness of the interface transition zone in the concrete, and h _NITZ = 35 μm.

Step <4> is performed as follows:

Considering the influence of water saturation in concrete, concrete age and temperature on the diffusion of chloride ions in concrete, referring to the calculation formula of chloride ion diffusion coefficient of concrete proposed by Saette, in the multi-scale prediction model of chloride ion diffusion coefficient of ordinary concrete. On this basis, the multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete is further established, as follows:

In formula (58), D _NC represents the chloride ion diffusion coefficient of the saturated concrete obtained in step 3; _te represents the age of the concrete; T is the Kelvin temperature of the concrete; θ is the water saturation of the concrete.

The application of the above construction method in the design of unsaturated concrete mix ratio, the multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete is combined with the concrete life prediction theory, and it is calculated that under different environmental use levels, it can meet different service life. The required mix ratio of unsaturated concrete.

In view of the existing problems in the prior art, based on the existing theoretical research, the inventor established a method for constructing a multi-scale prediction model for the chloride ion diffusion coefficient of unsaturated concrete, considering concrete as a cement-based composite material composed of materials of different scales. , starting from small-scale hardened cement paste, gradually transitioning to large-scale concrete, and successively establishing chloride ion diffusion coefficient prediction models for cement-based materials of different scales, and then considering the influence of water saturation in concrete on its chloride ion diffusion, and finally A multi-scale prediction model for chloride diffusion coefficient of unsaturated concrete was established. This method takes into account the influence of the internal water saturation of concrete on its chloride ion diffusion, and can predict the chloride ion diffusion coefficient of unsaturated concrete more scientifically, reasonably and accurately. is of great significance.

Compared with the existing ordinary concrete chloride ion diffusion coefficient measuring method, the outstanding advantage of the present invention is:

(1) The influence of concrete nano-, meso-, micro- and macro-structure composition on chloride ion diffusion was studied, and a multi-scale cement-based material chloride ion diffusion coefficient prediction model was constructed. It has a wide range of applications and can provide a reference for studying the durability of concrete from a microscopic perspective.

(2) The established multi-scale prediction model of unsaturated concrete analyzes the diffusion law and influencing factors of chloride ions in unsaturated concrete from the perspective of multi-scale structure of concrete materials, and establishes the relationship between water saturation in concrete and its chloride ion diffusion performance. The quantitative relationship of , further promotes related research, and can provide new reference and reference for the durability research of unsaturated concrete.

(3) Through the prediction model of the present invention, the chloride ion diffusion coefficient can be quickly and accurately predicted according to the mixing ratio of the existing cement-based materials and relevant material parameters, without the need for real-time testing by a special testing device every time, which can save Research costs, and promote the development of cement-based materials durability research.

(4) Combining the prediction model of the present invention with the existing concrete life design theory, the concrete mix ratio that meets the service requirements can be calculated and obtained according to the service life requirements of the concrete structure, which provides a new idea for the mix ratio design of the concrete structure.

Description of drawings

Fig. 1 is a flow chart of the construction of a multi-scale prediction model for the chloride ion diffusion coefficient of unsaturated concrete according to the present invention.

Figure 2 is a schematic diagram of a micro-scale structural model of hardened cement paste.

Figure 3 is the relationship curve of various volume fractions in the cement paste as a function of age t (water-cement ratio n=0.5).

Figure 4 is the relationship curve of various volume fractions in the cement paste with the water-cement ratio n (age t=28d).

Figure 5 is a schematic diagram of the mesoscale structural model of the new mortar.

Figure 6 is the relationship curve of the new mortar chloride ion diffusion coefficient _{D NM} with the volume fraction V _ITZ of the interface transition zone when the water-cement ratio is 0.5 and the sand volume fraction VA is set to 0.3, 0.42, and 0.5, respectively.

Figure 7 is a schematic diagram of a meso-scale structure model of ordinary concrete.

Figure 8 is the finished cylindrical specimen for RCM method (upper left) and the deviation relationship between the predicted value of the chloride ion diffusion coefficient of concrete and the experimental value.

Fig. 9 is the deviation relationship curve between the predicted value of the two models of chloride ion diffusion coefficient of unsaturated concrete and the experimental value.

In the figure: 1 high-density C-S-H layer; 2 low-density C-S-H layer; 3 equivalent spherical unhydrated cement particles; 4 unhydrated cement particles; 5 hardened cement paste; 6 natural sand; 7 equivalent spherical natural sand 8 ITZ between natural sand and cement paste; 9 Cement mortar; 10 Natural coarse aggregate; 11 Equivalent spherical natural coarse aggregate; 12 ITZ between natural coarse aggregate and cement mortar.

Detailed ways

In order to verify the superiority of the aforementioned construction method and its related prediction model, the inventor further designs recycled concrete with different chloride ion diffusion coefficients based on the established multi-scale prediction model, and conducts experimental verification. Select materials and mix proportions to design and prepare cement-based materials with different chloride ion diffusion coefficients. According to material parameters and mix ratio design, use the multi-scale prediction model of the present invention to calculate the predicted value of concrete chloride ion diffusion coefficient, and compare it with the measured value of the RCM method. And the prediction value of the existing theoretical model is compared and analyzed. In order to illustrate the practical engineering application significance of the model, combined with the prediction model and the existing life prediction theory of concrete structures, according to the different service life requirements of concrete structures, the concrete mix ratio that meets the actual needs is obtained. The specific implementation process is as follows:

(1) According to the established multi-scale prediction model, pre-select material parameters and design mix ratios to prepare multi-scale cement-based materials with different chloride ion diffusion coefficients

(2) Select the prepared cement paste, new mortar, ordinary concrete and concrete specimens with different water saturation, and measure their corresponding chloride ion diffusion coefficient by RCM method.

(3) The designed value of the chloride ion diffusion coefficient of cement-based materials of different scales is compared with the experimental value measured by the RCM method to illustrate the reliability of the multi-scale prediction model of the present invention for predicting the chloride ion diffusion coefficient of cement-based materials of various scales.

(4) Introduce the existing unsaturated concrete chloride ion diffusion coefficient prediction model, and compare and analyze the unsaturated concrete chloride ion diffusion coefficient prediction model established by the present invention, the introduced prediction model, and the RCM method chloride ion diffusion coefficient test value to illustrate the present invention. The excellence of the invention model.

(5) According to the existing concrete structure life prediction theory, the chloride ion diffusion coefficient of concrete required by different service life is solved, and the obtained chloride ion diffusion coefficient is substituted into the ordinary concrete chloride ion diffusion coefficient multi-scale prediction model established by the present invention. , and get the specific mix design, which can provide a reference for the actual engineering design of concrete with different durability requirements.

The following describes how to implement in detail through examples.

Example 1 Predicting the chloride ion diffusion coefficient of different cement-based materials

In order to verify the reliability of the multi-scale prediction model of the present invention, the relevant raw materials are preselected, and the relevant mix ratio design is given, and then the relevant chloride ion diffusion coefficients are calculated according to the prediction models of the chloride ion diffusion coefficients of cement materials of various scales established in steps 1 to 4. At the same time, the cement-based material was prepared according to the selected raw materials and mixing ratio, and the RCM rapid chloride ion diffusion test was carried out to obtain the experimental value of the chloride ion diffusion coefficient, which was compared with the model design value.

The selection of relevant test raw materials is as follows:

Cement: P42.5 ordinary Portland cement, the chemical composition and mineral composition of cement clinker are shown in Table 1, and the cement density is ρ _c =3.15g/cm ³ .

Fine aggregate: natural river sand, particle size is 0.16-5.00mm, fineness modulus is 3.0, gradation is middle sand in zone II;

Coarse aggregate: limestone crushed stone, the particle size is 16-20mm, and the particle shape is close to cube and spherical.

Coarse aggregate: limestone crushed stone, the particle size is 16-20mm, and the particle shape is close to cube and spherical.

Table 1 Chemical composition and mineral composition of cement clinker

Mix design:

The proposed materials are selected, and the variable parameter design is carried out. Different mix ratios are designed for three kinds of cement-based materials: cement paste, cement mortar, and ordinary concrete. The specific mix ratio design is shown in Table 2:

Table 2 The dosage of cement-based composite materials of various scales

Calculation of predicted value of chloride ion diffusion coefficient:

The process of building a multi-scale prediction model of the present invention is shown in Figure 1. The following is a transition from small-scale cement paste to large-scale ordinary concrete, and the design value of the chloride ion diffusion coefficient of each mix ratio of cement-based materials is calculated according to the prediction model value.

Figure 2 is a schematic diagram of the micro-scale structure model of the hardened cement paste. From the prediction model formula (45) of the chloride ion diffusion coefficient of the cement paste, it can be known that the chloride ion diffusion coefficient of the cement paste is related to each volume parameter. In 51), it can be known from the performance parameters of the material that ρ _c =3.15g/cm ³ , and there are ρ _lCSH =1.44g/cm ³ , ρ _hCSH =1.75g/cm ³ , p ₁ , p ₂ , p ₃ , p ₄ according to When taking 0.499, 0.243, 0.075, and 0.11 in Table 1, the volume parameters in equations (46) to (51) are only related to the water-to-binder ratio n and age t. Figure 3 shows the relationship curve of various volume parameters in the cement paste with age t when the water-cement ratio n is 0.5; Figure 4 shows the change of various volume parameters in the cement paste with water when the age t is 28 days. The relationship curve of the change of glue ratio n. In order to facilitate the comparison and analysis of subsequent experiments, the maintenance age is uniformly taken as 28 days when calculating the volume fraction of each sub-item according to the prediction model, and the predicted design value D of the chloride ion diffusion coefficient of the cement paste under different mixing ratios is calculated from the formula (45). _HCP , as shown in Table 3.

Table 3 Calculation of predicted value of chloride ion diffusion coefficient of hardened cement paste

Figure 5 is a schematic diagram of the mesoscale structure of the new mortar. From the prediction model formula (52), it can be known that the chloride ion diffusion coefficient D _NM of the new mortar is related to the volume fraction VA of the fine aggregate and the volume fraction V _ITZ of the interface transition zone ( _ITZ ) between the fine aggregate and the hardened cement paste. , when the water-cement ratio is 0.5, and the VA takes fixed values of 0.3, 0.42, and 0.5, respectively, the relationship between _{D NM} and V _ITZ is shown in Figure 6. When V _A = 0.42 and V _ITZ = _0.0991 , the value of D ITZ can be calculated by formula (54), and then D _HCP calculated in Table 1 and the set parameter values are substituted into formula (52) to calculate the new mortar The predicted value of the chloride ion diffusion coefficient D _NM , and the relevant calculation results are shown in Table 4.

Table 4 Calculation of the predicted value of chloride ion diffusion coefficient of new mortar

Figure 7 is a schematic view of the meso-scale structure of ordinary concrete. The prediction model (55) shows that the chloride diffusion coefficient D _NC of concrete is related to the volume fraction V _NA of natural coarse aggregate and the volume fraction V _NITZ of the interface transition zone (ITZ) between natural coarse aggregate and new mortar. Table 5 shows the calculation results of the predicted value of concrete chloride ion diffusion coefficient D _NC when n = 0.6, V _NA = 0.4, and V _NITZ takes different values.

Table 5 The calculation results of the predicted value of the chloride ion diffusion coefficient of concrete

From the prediction model (58), it can be known that the chloride ion diffusion coefficient D _SNC of unsaturated concrete is related to concrete age t, concrete temperature T, and concrete water saturation θ. When the age and temperature are fixed values (t=28d, T=298K), for ordinary concrete numbered NC3, when its internal water saturation is 30%, 50%, and 70%, respectively, its chloride ion diffusion coefficient is predicted The value calculation results are shown in Table 6.

Table 6 Calculation results of predicted value of chloride ion diffusion coefficient of unsaturated concrete

Cement-based material RCM rapid chloride diffusion test:

In order to verify the reliability of the design model of the present invention, according to the selected test materials and mix ratio design, the cement-based materials of various scales are prepared, and the RCM method rapid chloride ion diffusion test is carried out to measure the chloride ion diffusion coefficient of the corresponding cement-based materials. The experimental value is compared with the model design value, and the prediction error of the model is analyzed. On this basis, it is explained that the multi-scale prediction model established by the present invention can be used to design and prepare recycled concrete with different durability requirements. Research provides new references.

Test piece production. The cement-based composite materials were stirred by HJW-60 forced single-horizontal shaft concrete mixer, and the mixed mixture was put into a cylindrical PVC pipe with a size of Φ100mm × 250mm. Vibrate on the vibrating table until the specimen is densely formed. After the specimen is formed, cover the port with plastic wrap and move it to the standard curing room for curing for 24 hours. After immersing it in the pool of the curing room for 28 days, it will continue curing until 7 days before the test age. Use a stone cutter to cut the test piece into a cylindrical test piece with a diameter of (100±1) mm and a height of (50±2) mm. After the test piece is processed, it is smoothed with sandpaper, and the processed test piece continues to be immersed in water for curing. To the test age, the size and structure of the processed specimens are shown in Figure 8. In order to study the influence of the internal water saturation of concrete on its chloride ion diffusion coefficient, some ordinary concrete cylindrical specimens numbered NC3 were selected for water saturation treatment and then dried, so that the internal water saturation was 30% and 50% respectively. , 70%, respectively numbered as SNC1, SNC2, SNC3.

Rapid chloride diffusion test by RCM method. The rapid chloride ion penetration test by RCM method was carried out according to GBT50082-2009 "Standard for Long-term Performance and Durability Performance of Ordinary Concrete", which is suitable for determining the unsteady migration coefficient of chloride ion in cement-based composite materials. For each group of numbered cement-based materials, three cylindrical specimens were used to test the chloride ion diffusion coefficient. However, the average value of the three test values was taken as the chloride ion diffusion coefficient of this group of cement-based materials. The test results are shown in Table 7. .

Comparative analysis of experimental value and predicted value:

In order to illustrate the reliability of the prediction model of the present invention, the model predicted value of the chloride ion diffusion coefficient of each cement-based material is compared with the measured value of the RCM method. The comparison results between the model predicted value and the experimental value are shown in Table 7.

Table 7 The comparison results between the predicted value and the experimental value of the cement-based material model of different scales

In Table 7, the predicted and experimental values of C0.4, C0.5, and C0.6 are compared and analyzed, and it can be found that the predicted results of the chloride ion diffusion coefficient of hardened cement paste are in good agreement with the experimental results. The maximum deviation is only 5.16%, and the minimum The value is 3.28%, indicating that the method for predicting the chloride ion diffusion coefficient of hardened cement paste proposed by the present invention is effective.

From the comparison data of M0.4, M0.5 and M0.6 in Table 7, it can be shown that the maximum deviation between the predicted value and the experimental value of the chloride ion diffusion coefficient of the cement mortar designed and prepared according to the prediction model is not more than 7%. The prediction deviation of the new mortar also includes the prediction deviation of the hardened cement paste, so although the deviation value is larger than the deviation value of the cement paste, the value is still within a reasonable range, indicating the chloride ion diffusion coefficient of the new mortar proposed by the present invention. Multiscale prediction methods are effective.

In Table 7, NC1, NC 2, and NC3 represent ordinary concrete with three different mix ratio designs, respectively. From the comparison data, it can be found that the maximum deviation between the predicted value of the chloride ion diffusion coefficient of recycled concrete and its experimental value is 8.13%. Considering that the prediction deviation of the chloride ion diffusion coefficient of concrete includes both the prediction deviation of hardened cement paste and the prediction deviation of new mortar, and due to factors such as the larger dispersion and experimental error of recycled concrete itself, even if the prediction deviation is The value is larger than the prediction deviation of hardened cement paste, which is also acceptable, and the multi-scale prediction model of chloride ion diffusion coefficient of recycled concrete proposed by the present invention is also effective. The deviation relationship between the predicted value and the experimental value is shown in Figure 8.

It can be seen from the comparison results of the last three groups of data in Table 7 that the deviation between the predicted value of the chloride ion diffusion coefficient of the unsaturated concrete calculated by the prediction model and its experimental value is kept within 9%, indicating that the chloride ion diffusion of the unsaturated concrete proposed by the present invention. The coefficient prediction model is still reliable.

Comparative analysis of the existing model formula and the prediction model of the present invention:

In order to illustrate the superiority of the model prediction of the present invention, the existing unsaturated concrete chloride ion diffusion coefficient prediction model is further introduced for comparison. Through experimental research, Climent has obtained the calculation model of concrete chloride diffusion with the change of internal water saturation when the water-cement ratio is 0.6. The factors considered in this model are similar to the prediction model of the present invention, and can be used as a comparison model. Climent The established fitting formula of chloride ion diffusion coefficient of unsaturated concrete is shown in formula (59).

D _cl (θ)=D _cl,1 ·(0.04514-0.6889θ+1.6438θ ² ) (59)

In the formula: θ is the water saturation inside the concrete; D _cl (θ) is the chloride ion diffusion coefficient of the concrete when the water saturation is θ; D _cl,1 is the chloride ion diffusion coefficient of the saturated concrete.

In order to facilitate the comparative analysis, the predicted value of the chloride ion diffusion coefficient of the concrete numbered NC3 is taken as the value of D _cl,1 in formula (59), that is, D _cl,1 =5.29×10 ^-12 m ² /s, at this time Equation (59) can be abbreviated as:

D _cl (θ)=0.2387906-3.644281θ+8.695702θ ² (60)

For the prediction model of chloride ion diffusion coefficient of unsaturated concrete of the present invention, when D _NC =5.29×10 ^-12 m ² /s, t=28d, T=298K, formula (58) is simplified as:

D _SNC = 4.1515θ ² +1.137 (61)

Formulas (60) and (61) respectively represent the relationship between the chloride ion diffusion coefficient of unsaturated concrete and the change of the water saturation inside the concrete in the Climent model and the prediction model of the present invention. 3, SCN0.5, SCN0.7 three kinds of numbers of concretes of chloride ion diffusion coefficient RCM method measured value, through comparative analysis can be found that the prediction model of the present invention and the measured value have a high degree of agreement, and the Climent model and the measured value between There is a large deviation, and the Climent model cannot predict the chloride ion diffusion coefficient of concrete with any saturation, indicating that the model of the present invention is more excellent in predicting the chloride ion diffusion coefficient of unsaturated concrete.

Example 2 Designing concrete to meet the needs of different service years

The prediction model of the invention can guide engineering practice, and design concrete that meets the requirements of different service years. According to the existing concrete structure life prediction theory, combined with the prediction model of the present invention, the relationship between the chloride ion diffusion coefficient of concrete and the time change is established, and the chloride ion diffusion coefficient of concrete that meets different service life requirements is calculated. The diffusion coefficient is substituted into the multi-scale prediction model of the ordinary concrete of the present invention to obtain a specific mix ratio design, which can provide a reference for the actual engineering design of concrete with different durability requirements.

According to Fick's second diffusion law and considering the age attenuation coefficient, Yang Lufeng et al. established a formula for predicting the life of concrete chloride ion erosion:

From formula (62), the limiting expression of concrete chloride ion diffusion coefficient can be obtained:

In formulas (61) and (63), T is the design service life; D ₀ is the chloride ion diffusion coefficient of concrete at t ₀ (initial) time, which is called the initial diffusion coefficient, and the concrete specimens aged 28 days are measured by the RCM method. get; n is the diffusion coefficient age decay coefficient, which is generally taken as 0.3 for non-mineral admixture concrete; d is the thickness of the protective layer; c _s is the surface chloride ion concentration of the concrete; c ₀ is the initial chloride ion concentration; _cr is the The critical chloride ion concentration for steel deduplication; erf ^-1 (·) is the inverse function of the error function.

The design parameters of c _s , c ₀ , _cr , and d can be obtained after the chloride salt environmental action level of the concrete structure is known. If the design service life T is given again, when n=0.3, it can be obtained according to formula (63 ) Calculate the initial diffusion chloride ion diffusion coefficient limit of concrete under different design service years and different chloride salt environmental action grades, and further combine the multi-scale prediction model of recycled concrete of the present invention, this value can be the mix ratio of concrete required by different service years Design and preparation provide quantitative basis.

The design parameters such as c _s , c ₀ , _cr , and d obtained according to the relevant provisions of durability specifications and guidelines are shown in Table 8.

Table 8 Design parameters under different environmental action levels and design service years

When the design years are 30 years, 50 years, and 100 years respectively, in different environmental action levels, the limit value of the initial chloride ion diffusion coefficient of concrete at each level can be calculated from formula (63), as shown in Table 9.

Table 9 Limits of initial chloride ion diffusion coefficient D ₀ for concrete structures

Combining with the prediction model of the present invention, select the initial chloride ion diffusion coefficient limit D ₀ =5.5×10 ^-12 m ² of the concrete structure with an environmental effect grade of III-C and a design service life of 50 years (d=45mm) in Table 9. /s, to calculate the mix ratio of concrete that meets the requirements of use.

First, set the volume fraction of coarse aggregate in concrete. If V _NA = 40%, it is explained by the value of V _NITZ in formula (56), V _NITZ = 0.75%, and the particle size of natural coarse aggregate is 5 -20mm of natural graded aggregate, when the water-binder ratio is 0.4, if the concrete is completely saturated, the relevant prediction model of the present invention can be further calculated to obtain the values of the chloride ion diffusion coefficients D _ITZ and D _NM of each sub-item as shown in Table 10 As shown, by substituting each calculated value into formula (55), it can be calculated that the chloride ion diffusion coefficient of recycled concrete is D _NC =4.66×10 ^-12 m ² /s≤5.5×10 ^-12 m ² /s, which satisfies When the environmental action grade is III-C, and the design life is 50 years, the requirements for the initial diffusion coefficient of chloride ions in concrete can be designed according to the relevant assumptions. The specific mix ratio design is shown in Table 11. If the D _NC calculated by the above design is greater than the specified limit, adjust the water-binder ratio and the volume fraction of recycled aggregate according to the prediction formula until the D _RC is lower than the specified limit.

Table 10 Values and calculation results of relevant parameters in the prediction model

Table 11 Design of the mix proportion of recycled concrete with environmental action grade III-C and a design service life of 50 years

To sum up, the predicted value of the chloride ion diffusion coefficient of concrete calculated by the prediction model of the present invention is compared with the measured value of the RCM method and the predicted value of the existing model. excellence. At the same time, according to the established prediction model, combined with the theory of life prediction, taking into account the different requirements for concrete durability in actual projects, and preselecting some model parameters, the specific mix ratio of concrete that meets the requirements of different service lives can be calculated. Therefore, on the one hand, the present invention can predict the chloride ion diffusion coefficient of unsaturated concrete according to the preselected relevant materials and mix ratio design, and provide a reference for designing concrete with excellent chloride ion resistance; on the other hand, it can be combined with the concrete life prediction theory , design the concrete to meet the requirements of different service life, and provide a new reference for the research on the durability of concrete. . In addition, the model of the present invention can further characterize the relationship between the internal water saturation of concrete and the diffusion of chloride ions, which is beneficial to further explore the transmission mechanism of chloride ions in unsaturated concrete.

In a word, the present invention takes into account the multi-scale and multi-phase characteristics of concrete materials, and the established multi-scale prediction model can analyze the relevant influencing factors in detail, pre-select relevant materials, design the mix ratio, and accurately prepare different types of materials according to actual engineering needs. For concrete that needs durability, it can more accurately characterize the relationship between the water saturation in the concrete and the diffusion of chloride ions, which provides new ideas for the study of the durability of concrete.

Claims (8)

1. a construction method of a multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete, comprising the following steps: <1> Establish a prediction model for the chloride ion diffusion coefficient of cement paste; <2> Establish a new mortar chloride ion diffusion coefficient prediction model; <3> Establish a multi-scale prediction model for the chloride ion diffusion coefficient of ordinary concrete; <4> Establish a prediction model for chloride ion diffusion coefficient of unsaturated concrete; Step <1> is performed as follows: Combined with generalized self-consistent method and Mori-Tanaka method, the prediction model of chloride ion diffusion coefficient of hardened cement paste is established as follows:

In formula (1), φ,

The expression is:

In formula (2), D _hCSH is the diffusion coefficient of the high-density CSH gel layer in the cement; D _lCSH is the diffusion coefficient of the low-density CSH gel layer in the cement; V _α is the total density of the high-density CSH gel layer in the hardened cement paste. volume fraction of cement volume; V _β is the sum of the volume fraction of unhydrated cement particles and high-density CSH gel layer in the hardened cement paste; the volume fraction of unhydrated cement particles is V _U ; According to the matrix-inclusion model, the expression of D _hCSH is:

in:

In formulas (3) to (5),

is the diffusion coefficient of chloride ions in the high-density CSH gel layer obtained by experiment and numerical calculation;

V _hCSH is the volume fraction of CH, AF, and high-density CSH gel layer matrix in the high-density CSH gel layer, respectively; α _h , β _h are intermediate variables; According to the Mori-Tanaka method, the expression for D _lCSH is:

in:

ζ=V _cap (D _cap - D' _lCSH ) (11) In formulas (6) to (11), D′ _lCSH is the effective diffusion coefficient of the equivalent medium layer after the cement hydration product and the low-density CSH gel layer matrix are evenly mixed;

is the diffusion coefficient of chloride ions in the low-density CSH gel layer obtained by experiment and numerical calculation;

V _cap and V _lCSH are the volume fractions of CH, AF, capillary pores, and low-density CSH gel layer matrix in the low-density CSH gel layer, respectively; D _cap is the effective diffusion coefficient of capillary pores; α _l , β _l , ξ, ζ are intermediate variables; The volume fractions of various hydration products of hardened cement paste are V _CH , V _AF , V _CSH , the volume fraction of unhydrated cement particles is V _U , and the volume fraction of capillary pores is V _cap , there are: V _CH + V _AF + V _lCSH + V _hCSH + V _U + V _cap = 1 (12) and have:

The expressions of V _α and V _β in formula (2) are:

Combining formulas (1) to (15), the prediction model for the chloride ion diffusion coefficient of cement paste with each volume parameter as a variable is obtained as follows:

In formula (16),

D _cap is the measured value obtained by experiment and numerical calculation; assuming that the mass of the saturated cement paste is 1g, according to the chemical reaction equation of ordinary Portland cement, the prediction model of each volume fraction in the paste is obtained as follows:

In formulas (17) to (22), n—initial water-cement ratio of cement paste; t—age period; ρ _c , ρ _lCSH , ρ _hCSH —the density of cement, the density of low-density CSH gel, the density of high-density CSH Density of gel; mass fraction of p ₁ , p ₂ , p ₃ , p ₄ -C ₃ S, C ₂ S, C ₃ A, C ₄ AF in cement clinker. 2. construction method according to claim 1 is characterized in that: the diffusion coefficient of described chloride ion in high density CSH gel layer

Pick

Diffusion Coefficient of Chloride Ion in Low Density CSH Gel Layer

Pick

The effective diffusion coefficient D _cap of the capillary is taken as D _cap =2.03×10 ⁻⁹ m ² /s. 3. construction method according to claim 1 is characterized in that step <2> is carried out as follows: The generalized self-consistent method is used for prediction, and the new mortar chloride ion diffusion coefficient prediction model is established as follows:

In formula (23), ξ, ζ are intermediate variables, there are:

In formula (24), D _HCP is the chloride ion diffusion coefficient of the hardened cement paste predicted in step <1>; D _ITZ is the chloride ion diffusion in the interface transition zone ITZ between the fine aggregate in the new mortar and the hardened cement paste coefficient; VA is the volume fraction of fine aggregate in the new mortar, calculated from the mix ratio of the mortar; V _ITZ is the volume fraction of _ITZ in the interface transition zone between the fine aggregate in the new mortar and the hardened cement paste, taking The value range is 5%-30%; Among them, the expression of D _ITZ of new mortar based on cement is: D _ITZ = 117.563D _HCP h _ITZ ^-0.8772 (25) In formula (25), h _ITZ is the thickness of the interface transition zone in the new mortar. 4 . The construction method according to claim 3 , wherein the thickness h _ITZ of the interface transition zone in the new mortar is taken as h _ITZ =25 μm. 5 . 5. construction method according to claim 1 is characterized in that step <3> is carried out as follows: Using the generalized self-consistent model, the multi-scale prediction model of chloride ion diffusion coefficient of natural coarse aggregate concrete is established as follows:

In formula (26), υ, ω are intermediate variables, there are:

In formula (27), D _NM represents the chloride ion diffusion coefficient of the new mortar obtained in step <2>; D _NITZ represents the chloride ion diffusion coefficient of ITZ in the interface transition zone between the natural aggregate in the concrete and the new mortar; V _NA represents The volume fraction of natural coarse aggregate; V _NITZ represents the volume fraction of ITZ in the interface transition zone between natural coarse aggregate and new mortar in concrete, and the value ranges from 0.1% to 2.0%; Among them, the expression of D _NITZ of ordinary concrete based on new mortar is: D _NITZ = 117.563D _NM h _NITZ ^-0.8772 (28) In formula (28), h _NITZ is the thickness of the interface transition zone in the concrete. 6 . The construction method according to claim 5 , wherein the thickness h _NITZ of the interface transition zone in the concrete is taken as h _NITZ =35 μm. 7 . 7. construction method according to claim 1 is characterized in that step <4> is carried out as follows: Considering the influence of water saturation in concrete, concrete age and temperature on the diffusion of chloride ions in concrete, referring to the calculation formula of chloride ion diffusion coefficient of concrete proposed by Saette, in the multi-scale prediction model of chloride ion diffusion coefficient of ordinary concrete. On this basis, the multi-scale prediction model of chloride ion diffusion coefficient of unsaturated concrete is further established, which is:

In formula (29), D _NC represents the chloride ion diffusion coefficient of the saturated concrete obtained in step <3>; _te represents the age of the concrete; T is the Kelvin temperature of the concrete; θ is the water saturation of the concrete. 8. the application of the described construction method of claim 1 in the design of unsaturated concrete mix ratio, it is characterized in that combining described unsaturated concrete chloride ion diffusion coefficient multi-scale prediction model and concrete life prediction theory, calculated in different The mix ratio of unsaturated concrete that meets the requirements of different service years under the environmental service level.

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