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

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

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CN108333082B
CN108333082B CN201810063437.8A CN201810063437A CN108333082B CN 108333082 B CN108333082 B CN 108333082B CN 201810063437 A CN201810063437 A CN 201810063437A CN 108333082 B CN108333082 B CN 108333082B
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应敬伟
沈小俊
欧阳楚才
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Guangxi University
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Abstract

The invention discloses a construction method of a chloride ion diffusion coefficient multi-scale prediction model of unsaturated concrete, which comprises the steps of regarding concrete as a cement-based composite material consisting of materials with different scales, gradually transitioning from hardened cement slurry with small scales to concrete with large scales, sequentially establishing chloride ion diffusion coefficient prediction models of the cement-based materials with different scales, considering the influence of the water saturation inside the concrete on the chloride ion diffusion of the concrete, and finally establishing the chloride ion diffusion coefficient multi-scale prediction model of the unsaturated concrete. The method considers the influence of the internal water saturation of the concrete on the chloride ion diffusion of the concrete, can scientifically, reasonably and accurately predict the chloride ion diffusion coefficient of the unsaturated concrete, and has very important significance on the chloride ion permeation resistance research and durability design of the concrete under the unsaturated condition.

Description

Construction method of unsaturated concrete chloride ion diffusion coefficient multi-scale prediction model
Technical Field
The invention belongs to a prediction method of a non-saturated concrete chloride ion diffusion coefficient, and particularly relates to a construction method of a non-saturated concrete chloride ion diffusion coefficient multi-scale prediction model.
Background
The concrete is a non-homogeneous material consisting of cement, coarse aggregate, fine aggregate and the like, and a plurality of pores and microcracks exist in the concrete, and the pores provide passages for harmful substances to enter the concrete. The chloride ions intrude into the reinforced concrete through the channels to cause severe corrosion of the steel bars, thereby affecting the structural safety.
The transmission of chloride ions in concrete is a complex process, and factors such as the saturation degree, water pressure and an external electric field of the concrete have important influence on the transmission of the chloride ions. According to the power source of transmission, the action mechanism of chloride ion transmission in concrete is mainly divided into diffusion action, osmosis action, capillary action, electrochemical migration and combination action.
The chlorine ion diffusion in the concrete means that when the concrete is in a saturated state, pore water does not migrate, and the chlorine ions migrate from a place with high concentration to a place with low concentration due to the difference of the chlorine ions in different areas. The diffusion of chloride ions in concrete is divided into steady diffusion and unsteady diffusion. Unsteady diffusion refers to the change of the chloride ion concentration in any point along with time and space in the diffusion process. The steady diffusion means that the concentration of the chloride ions at any point in the diffusion process does not change along with time and space, and parameters of each diffusion characteristic are kept unchanged.
The osmosis refers to that when pressure difference exists in the concrete due to different hydrostatic pressures of different areas, the pore solution flows directionally under the action of the pressure difference, and chloride ions migrate by taking the pore solution as a carrier. When the concrete is in an unsaturated state, pressure action is generated due to different humidity in different areas in the concrete, and chloride ions are promoted to migrate from a position with higher humidity to a position with lower humidity by taking water as a carrier.
The transport of chloride ions in concrete is greatly influenced by the environment, and the transport mechanism is also generally a coupling of the above mechanisms. However, numerous studies have shown that: the transportation process of chloride ions in the concrete under the unsaturated state is mainly the diffusion of the concentration of the chloride ions in the pore solution and the convection process of the chloride ions along with the pore solution. The water saturation degree of concrete is not considered in most of the existing concrete chloride diffusion coefficient prediction models, the concrete is generally in a water saturation state by default when the models are established, and the concrete chloride diffusion coefficient prediction models considering the influence of the water saturation degree are few. The existing related models mainly include a chloride ion transmission model under the coupling action of dry and wet and load, which is established by Sun Severe et al, and a convection-diffusion model of chloride ions in an unsaturated state is established by Jinweiliang et al based on the nonlinear relation between the water diffusion coefficient and the water saturation. A prediction model of concrete chloride ion diffusion coefficient changing along with pore saturation in a wetting process is established by Hall of foreign scholars, but the model relates to the problem that values of relevant empirical parameters are uncertain, the applicability is further verified, Clime obtains a theoretical model of concrete chloride ion diffusion coefficient changing along with pore water saturation when the water cement ratio is 0.6 through regression fitting of relevant test data, but the model has large limitation and cannot accurately predict the chloride ion diffusion coefficient of concrete with low water saturation.
Disclosure of Invention
The invention aims to provide a construction method of a unsaturated concrete chloride ion diffusion coefficient multi-scale prediction model.
In order to solve the technical problems, the invention adopts the following technical scheme:
the method for constructing the unsaturated concrete chloride ion diffusion coefficient multi-scale prediction model comprises the steps of regarding concrete as a cement-based composite material consisting of materials with different scales, gradually transitioning from hardened cement slurry with small scales to concrete with large scales, sequentially establishing chloride ion diffusion coefficient prediction models of cement-based materials with different scales, considering the influence of the water saturation inside the concrete on the chloride ion diffusion of the concrete, and finally establishing the chloride ion diffusion coefficient multi-scale prediction model of the unsaturated concrete.
The construction method comprises the following steps:
establishing a prediction model of the chloride ion diffusion coefficient of the cement paste;
establishing a new mortar chloride ion diffusion coefficient prediction model;
establishing a common concrete chloride ion diffusion coefficient multi-scale prediction model;
and 4, establishing a chloride ion diffusion coefficient prediction model of unsaturated concrete.
The step <1> is performed as follows:
the cement particles with different particle sizes react with water to generate hardened cement paste, the hardened cement paste consists of various hydration products (C-S-H, CH, AF), unhydrated cement particles (which can be approximately spherical) and a plurality of pores, the volume fraction of each component in the cement paste changes along with the water cement ratio and the age development, the components in the paste are mixed with each other to jointly influence the chloride ion diffusion coefficient of the hardened cement paste, and the hardened cement paste chloride ion diffusion coefficient prediction model is established by combining a generalized self-consistent method and an M ori-Tanaka method and is as follows:
Figure GDA0001671493950000021
in the formula (30), phi,
Figure GDA0001671493950000022
the expression of (a) is:
Figure GDA0001671493950000023
in the formula (31), DhCSHThe diffusion coefficient of a high-density C-S-H gel layer in the cement is shown; dlCSHThe diffusion coefficient of the low-density C-S-H gel layer in the cement is shown; vαThe volume fraction of the high-density C-S-H gel layer in the hardened cement paste in the total cement volume is adopted; vβIs the sum of the volume fractions of unhydrated cement particles and a high-density C-S-H gel layer in the hardened cement paste;
a high density C-S-H gel layer comprises cement hydration products (such as CH and AF) and a high density C-S-H gel layer matrix, and when the hydration products are non-diffused and relatively uniformly distributed in the high density C-S-H gel layer matrix, the matrix-inclusion model has DhCSHThe expression of (a) is:
Figure GDA0001671493950000031
wherein:
Figure GDA0001671493950000032
Figure GDA0001671493950000033
in the formulae (32) to (34),
Figure GDA0001671493950000034
taking the diffusion coefficient of the chloride ions in the high-density C-S-H gel layer obtained through tests and numerical calculation
Figure GDA0001671493950000035
Figure GDA0001671493950000036
VhCSHThe volume fractions of the CH, AF, respectively, high density C-S-H gel layer matrix in the high density C-S-H gel layer αh、βhIs an intermediate variable;
the low-density C-S-H gel layer comprises cement hydration products (such as CH and AF) and a low-density C-S-H gel layer matrix and a plurality of capillary pores, and considering that the hydration products and the capillary pores are non-diffused and relatively uniformly distributed in the low-density C-S-H gel layer matrix, the Mori-Tanaka method of multi-phase material inclusion has DlCSHThe expression of (a) is:
Figure GDA0001671493950000037
wherein:
Figure GDA0001671493950000039
Figure GDA00016714939500000310
Figure GDA00016714939500000311
ζ＝Vcap(Dcap-D'lCSH) (40)
d 'in formulae (35) to (40)'lCSHThe effective diffusion coefficient of the equivalent dielectric layer after the cement hydration products (such as CH and AF) and the low-density C-S-H gel layer matrix are uniformly mixed;
Figure GDA0001671493950000041
taking the diffusion coefficient of the chloride ions in the low-density C-S-H gel layer obtained by tests and numerical calculation
Figure GDA0001671493950000042
Figure GDA0001671493950000043
Vcap、VlCSHThe volume fractions of the CH, AF, capillary and low-density C-S-H gel layer matrix in the low-density C-S-H gel layer respectively; dcapTaking D as the effective diffusion coefficient of capillary porescap＝2.03×10-9m2/s；αl、βlξ, ζ are intermediate variables;
the volume fractions of various hydration products of the hardened cement paste are respectively VCH、VAF、VCSH(VlCSHAnd VhCSH) Volume fraction of unhydrated cement particles of VUVolume fraction of capillary pores is VcapThen, there are:
VCH+VAF+VlCSH+VhCSH+VU+Vcap＝1 (41)
and has the following components:
Figure GDA0001671493950000044
v in formula (31)α、VβAre respectively:
Figure GDA0001671493950000045
Figure GDA0001671493950000046
and (6) integrating the models (30) to (44) to obtain a cement paste chloride ion diffusion coefficient prediction model with each volume parameter as a variable, wherein the model comprises the following steps:
Figure GDA0001671493950000047
in the formula (45), the reaction mixture is,
Figure GDA0001671493950000048
Dcapmeasured values calculated for the tests and values; assuming that the mass of the saturated cement paste is 1g, obtaining a prediction model of each volume fraction in the clean paste according to a chemical reaction equation of ordinary portland cement, wherein the prediction model comprises the following steps:
Figure GDA0001671493950000049
Figure GDA00016714939500000410
Figure GDA0001671493950000051
Figure GDA0001671493950000052
Figure GDA0001671493950000053
in the formulas (46) to (51), n is the initial water cement ratio of the cement paste; t-age; rhoc、ρlCSH、ρhCSH-the density of the cement, the density of the low-density C-S-H gel; p is a radical of1、p2、p3、p4—C3S、C2S、 C3A、C4Mass fraction of AF in cement clinker.
The step <2> is performed as follows:
the new mortar can be regarded as comprising fine aggregate (sand, which can be approximately spherical), hardened cement paste and ITZ between the fine aggregate and the hardened cement paste on the microscopic scale, the prediction is carried out by adopting a generalized self-consistent method, and the model for predicting the chloride ion diffusion coefficient of the new mortar is established as follows:
Figure GDA0001671493950000054
ξ in formula (52), ζ is an intermediate variable, having:
Figure GDA0001671493950000055
d in formula (53)HCPPredicting the chloride ion diffusion coefficient of the hardened cement paste obtained in the step 1; dITZThe diffusion coefficient of chloride ions in an Interface Transition Zone (ITZ) between fine aggregate and hardened cement paste in the new mortar; vAThe volume fraction of the fine aggregate in the new mortar is calculated by the mixing proportion of the mortar; vITZThe volume fraction of an Interface Transition Zone (ITZ) between fine aggregate and hardened cement paste in the new mortar is 5-30%;
wherein D isITZD of the new mortar based on cement, depending on the thickness of the Interfacial Transition Zone (ITZ) between the fine aggregate and the hardened cement paste and on the diffusion properties of the matrix materialITZThe expression of (a) is:
DITZ＝117.563DHCP·hITZ -0.8772(54)
h in formula (54)ITZTaking h as the thickness of the interface transition zone in the new mortar and relating to the average radius of the cement particlesITZ＝25μm。
The step <3> is performed as follows:
for common aggregate concrete, the micro-scale prediction model can be regarded as a multi-phase sphere model, and the multi-scale prediction model for the chloride ion diffusion coefficient of the natural coarse aggregate concrete is established by adopting a generalized self-consistent model, wherein the micro-scale prediction model comprises a natural coarse aggregate, a new mortar matrix and an interface transition region between the natural coarse aggregate and the new mortar matrix on the micro-scale:
Figure GDA0001671493950000061
formula 55), v, ω are intermediate variables, having:
Figure GDA0001671493950000062
in the formula (56), DNMRepresenting the diffusion coefficient of chloride ions of the new mortar obtained in the step 2; dNITZRepresents the diffusion coefficient of chloride ions in the Interfacial Transition Zone (ITZ) between the natural aggregate and the new mortar in the concrete; vNAThe volume fraction of the natural coarse aggregate is expressed and calculated by the mixing proportion of the concrete; vNITZThe volume fraction of an Interface Transition Zone (ITZ) between natural coarse aggregate and new mortar in the concrete is represented, and the value range is 0.1% -2.0%;
wherein D isNITZD of ordinary concrete based on the new mortar, depending on the thickness of the Interfacial Transition Zone (ITZ) between the natural aggregate and the new mortar and on the diffusion characteristics of the matrix materialITZThe expression of (a) is:
DNITZ＝117.563DNM·hNITZ -0.8772(57)
h in formula (57)NITZTaking the thickness of an interface transition area in concrete as hNITZ＝35μm。
The step <4> is performed as follows:
considering that the internal water saturation of the concrete, the age and the temperature of the concrete can influence the diffusion of chloride ions in the concrete, the chloride ion diffusion coefficient calculation formula of the concrete proposed by Saette is referred, and on the basis of the common chloride ion diffusion coefficient multi-scale prediction model of the concrete, the chloride ion diffusion coefficient multi-scale prediction model of the unsaturated concrete is further established, and the chloride ion diffusion coefficient multi-scale prediction model is as follows:
Figure GDA0001671493950000071
in formula (58), DNCRepresenting the chloride ion diffusion coefficient of the saturated concrete obtained in the step 3; t is teIndicating the age of the concrete; t is the Kelvin temperature of the concrete; theta is the water saturation of the concrete.
The construction method is applied to the aspect of designing the mix proportion of unsaturated concrete, the non-saturated concrete chloride ion diffusion coefficient multi-scale prediction model is combined with the concrete life prediction theory, and the mix proportion of the unsaturated concrete meeting the requirements of different service lives under different environmental service levels is calculated.
Aiming at the problems in the prior art, based on the existing theoretical research, the inventor establishes a construction method of a unsaturated concrete chloride ion diffusion coefficient multi-scale prediction model, takes concrete as a cement-based composite material consisting of materials with different scales, gradually transits from hardened cement slurry with small scale to concrete with large scale, sequentially establishes chloride ion diffusion coefficient prediction models of cement-based materials with different scales, considers the influence of the internal water saturation of the concrete on the chloride ion diffusion, and finally establishes the chloride ion diffusion coefficient multi-scale prediction model of unsaturated concrete. The method considers the influence of the internal water saturation of the concrete on the chloride ion diffusion of the concrete, can scientifically, reasonably and accurately predict the chloride ion diffusion coefficient of the unsaturated concrete, and has very important significance on the chloride ion permeation resistance research and durability design of the concrete under the unsaturated condition.
Compared with the existing common concrete chloride ion diffusion coefficient determination method, the method has the outstanding advantages that:
(1) the influence of the nano, microscopic and macroscopic structure composition of the concrete on the diffusion of the chloride ions of the concrete is researched, a chloride ion diffusion coefficient prediction model of the multi-scale cement-based material is constructed, the model is comprehensive in analysis from the microscopic to the macroscopic level and wide in application range, and reference can be provided for researching the durability of the concrete from the microscopic level.
(2) The established unsaturated concrete multi-scale prediction model analyzes the diffusion rule and the influence factors of the chloride ions in the unsaturated concrete from the multi-scale structure of the concrete material, establishes the quantitative relation between the water saturation and the chloride ion diffusion performance of the concrete, further promotes the research of relevant aspects, and can provide new reference and reference for the durability research of the unsaturated concrete.
(3) The prediction model can quickly and accurately predict the chloride ion diffusion coefficient according to the matching ratio of the existing cement-based materials and related material parameters without the need of real-time testing by a special testing device every time, so that the research cost can be saved, and the development of the durability research of the cement-based materials is promoted.
(4) The prediction model is combined with the existing concrete life design theory, the concrete mix proportion meeting the use requirement can be calculated according to the service life requirement of the concrete structure, and a new thought is provided for the mix proportion design of the concrete structure.
Drawings
FIG. 1 is a flow chart of the construction of a non-saturated concrete chloride ion diffusion coefficient multi-scale prediction model according to the present invention.
FIG. 2 is a schematic view of a micro-scale structural model of hardened cement paste.
FIG. 3 is a graph of the volume fraction of cement paste as a function of age t (water-cement ratio n is 0.5).
FIG. 4 is a graph of the relationship between various volume fractions in cement paste and the variation of water-cement ratio n (age t 28 d).
FIG. 5 is a schematic view of a microscopic scale structural model of the new mortar.
FIG. 6 shows a water-cement ratio of 0.5 and a sand volume fraction VATaking the diffusion coefficients D of chloride ions of the new mortar at fixed values of 0.3, 0.42 and 0.5 respectivelyNMVolume fraction V along interface transition zoneITZA relationship curve of change.
Fig. 7 is a schematic diagram of a common concrete mesoscale structural model.
FIG. 8 is a graph showing the deviation of the predicted value of the diffusion coefficient of chlorine ions from the test value of the concrete and the processed cylindrical test piece for RCM (upper left).
FIG. 9 is a deviation curve of the predicted value and the test value of two models of the non-saturated concrete chloride ion diffusion coefficient.
In the figure: 1 a high density C-S-H layer; 2 a low density C-S-H layer; 3 equivalent spherical unhydrated cement particles; 4 unhydrated cement particles; 5 hardening the cement paste; 6, natural sand grains; 7 equivalent spherical natural sand grains; ITZ between natural sand and cement slurry; 9, cement mortar; 10 natural coarse aggregate; 11 natural coarse aggregate in equivalent spherical shape; 12 ITZ between natural coarse aggregate and cement mortar.
Detailed Description
In order to verify the superiority of the construction method and the related prediction model, the inventor further designs the recycled concrete with different chloride ion diffusion coefficients according to the established multi-scale prediction model, and performs experimental verification. The cement-based materials with different chloride ion diffusion coefficients are prepared by selecting materials and mixing proportion design, the multi-scale prediction model is used for calculating the predicted value of the chloride ion diffusion coefficient of the concrete according to the material parameters and the mixing proportion design, and the predicted value is compared and analyzed with the measured value of the RCM method and the predicted value of the existing theoretical model. In order to explain the practical engineering application significance of the model, the mix proportion of the concrete meeting the practical requirement is solved according to the different annual service life requirements of the concrete structure by combining the prediction model and the existing concrete structure life prediction theory. The specific implementation process comprises the following steps:
(1) according to the established multi-scale prediction model, preselecting material parameters and designing the mixing proportion to prepare the multi-scale cement-based material with different chloride ion diffusion coefficients
(2) Selecting prepared cement paste, new mortar, common concrete and concrete samples with different water saturations, and determining the corresponding chloride ion diffusion coefficients by an RCM method.
(3) Comparing the design values of the diffusion coefficients of the chloride ions of the cement-based materials with different scales with the test values measured by the RCM method, the reliability of the multi-scale prediction model for predicting the diffusion coefficients of the chloride ions of the cement-based materials with different scales is demonstrated.
(4) The existing unsaturated concrete chloride ion diffusion coefficient prediction model is introduced, and the unsaturated concrete chloride ion diffusion coefficient prediction model, the introduced prediction model and the RCM method chloride ion diffusion coefficient test value which are established by the invention are compared and analyzed, so that the model has the advantages.
(5) According to the existing concrete structure life prediction theory, the chloride ion diffusion coefficients of concrete with different service life requirements are solved, the obtained chloride ion diffusion coefficients are substituted into the common concrete chloride ion diffusion coefficient multi-scale prediction model established by the invention to obtain a specific mix proportion design, and reference can be provided for designing concrete with different durability requirements in actual engineering.
The following examples illustrate how this can be carried out.
Example one prediction of chloride ion diffusion coefficients for different cement-based materials
In order to verify the reliability of the multi-scale prediction model, relevant raw materials are preselected, relevant mix proportion design is given, then relevant chloride ion diffusion coefficients are calculated according to the cement material chloride ion diffusion coefficient prediction models of all scales established in the steps 1 to 4, meanwhile, a cement-based material is prepared according to the selected raw materials and the mix proportion, an RCM rapid chloride ion diffusion test is carried out, a chloride ion diffusion coefficient test value is obtained, and the chloride ion diffusion coefficient test value is compared with the model design value.
The relevant test raw materials were selected as follows:
cement: the chemical components and mineral compositions of the P42.5 ordinary Portland cement and the cement clinker are shown in Table 1, and the density of the cement is rhoc＝3.15g/cm3。
Fine aggregate: the natural river sand has the particle size of 0.16-5.00 mm, the fineness modulus of 3.0, and the gradation belongs to the sand in the area II;
coarse aggregate: the limestone macadam has the particle size of 16-20 mm and the particle shape close to a cube and a sphere.
Coarse aggregate: the limestone macadam has the particle size of 16-20 mm and the particle shape close to a cube and a sphere.
TABLE 1 chemical composition and mineral composition of Cement Clinker
Figure GDA0001671493950000091
The mix proportion design:
selecting a proposed material, performing variable parameter design, and designing different mix proportions aiming at three cement-based materials of cement paste, cement mortar and common concrete, wherein the specific mix proportion design is shown in table 2:
TABLE 2 dosage of cement-based composites for each scale
Figure GDA0001671493950000101
Calculating a predicted value of the diffusion coefficient of the chloride ions:
the process of the multi-scale prediction model construction is shown in figure 1, the process is sequentially changed from small-scale cement paste to large-scale common concrete, and the chloride ion diffusion coefficient design value of each mix proportion cement-based material is calculated according to the prediction model value.
FIG. 2 is a schematic view of a micro-scale structural model of a hardened cement paste. The cement paste chlorine ion diffusion coefficient is related to each volume parameter according to the prediction model formula (45), the calculation formula of each volume parameter is shown in formulas (46) to (51), and rho is known from the performance parameter of the material in the formulas (46) to (51)c＝3.15g/cm3And has ρlCSH＝1.44g/cm3、ρhCSH＝1.75g/cm3、p1、p2、p3、p4When 0.499, 0.243, 0.075, 0.11 are taken according to table 1, each volume parameter in equations (46) - (51) is only related to the water-gel ratio n and the age t. FIG. 3 is a graph showing the relationship between the variation of various volume parameters in the cement paste with age t when the water-cement ratio n is 0.5; FIG. 4 is a graph showing the variation of various volume parameters in cement paste with water-to-gel ratio n when the age t is 28 days. In order to facilitate the comparative analysis of subsequent tests, the maintenance age is uniformly taken as 28 days when the volume fraction of each item is calculated according to a prediction model, and the prediction design value D of the chloride ion diffusion coefficient of the cement paste under different mix proportions is calculated by the formula (45)HCPAs shown in table 3.
TABLE 3 calculation of the prediction value of the chloride ion diffusion coefficient of the hardened cement paste
Figure GDA0001671493950000102
FIG. 5 is a schematic view of the microscopic scale structure of the new mortar. The chloride ion diffusion coefficient D of the new mortar can be known from the prediction model formula (52)NMVolume fraction V with fine aggregateAAnd the volume fraction V of the Interfacial Transition Zone (ITZ) between the fine aggregate and the hardened cement pasteITZIn connection with this, when the water-cement ratio is 0.5, VAD is respectively set at 0.3, 0.42 and 0.5NMFollowing VITZThe relationship of the changes is shown in fig. 6. When setting VA＝0.42，VITZWhen 0.0991, D can be calculated from equation (54)ITZAnd then D calculated from Table 1HCPAnd the set parameter value is substituted into formula (52) to calculate to obtain the new mortar chloride ion diffusion coefficient predicted value DNMThe results of the correlation calculations are shown in Table 4.
TABLE 4 calculation of new mortar chloride ion diffusion coefficient prediction value
Figure GDA0001671493950000111
Fig. 7 is a schematic view of a microscopic structure of general concrete. The chloride ion diffusion coefficient D of the concrete can be known from the prediction model (55)NCVolume fraction V of natural coarse aggregateNAAnd the volume fraction V of the Interfacial Transition Zone (ITZ) between the natural coarse aggregate and the virgin mortarNITZIt is related. Table 5 shows that when n is 0.6, VNA＝0.4，VNITZWhen different values are taken, the concrete chloride ion diffusion coefficient predicted value DNCThe calculation result of (2).
TABLE 5 concrete chloride ion diffusion coefficient prediction value calculation results
Figure GDA0001671493950000112
The chloride ion diffusion coefficient D of the unsaturated concrete can be known from the prediction model (58)SNCThe age T of the concrete, the temperature T of the concrete and the concreteIs related to the water saturation theta. The calculation results of the predicted values of the diffusion coefficients of chloride ions are shown in table 6 when the internal water saturations of the ordinary concrete numbered NC3 are 30%, 50% and 70%, respectively, when the age and temperature are constant (T28 d, T298K).
TABLE 6 calculation results of the non-saturated concrete chloride ion diffusion coefficient prediction values
Figure GDA0001671493950000113
Figure GDA0001671493950000121
RCM rapid chloride ion diffusion test of cement-based materials:
in order to verify the reliability of the design model, cement-based materials of all scales are prepared according to the selected test materials and the mix proportion design, an RCM method rapid chloride ion diffusion test is carried out, chloride ion diffusion coefficient test values of the corresponding cement-based materials are measured, the chloride ion diffusion coefficient test values are compared with the model design values, and model prediction errors are analyzed.
And (5) manufacturing a test piece. The cement-based composite material is stirred by adopting a HJW-60 forced single-horizontal-shaft concrete stirring machine, the stirred mixture is filled into a cylindrical PVC pipe with the size of phi 100mm multiplied by 250mm, 6 standard test pieces are manufactured according to each group of mixing ratio, the mixture is vibrated on a vibration table until the test pieces are densely formed, after the test pieces are formed, a preservative film is covered on a port, the port is moved to a standard curing room for curing for 24 hours, then the test pieces are immersed in a water pool of the curing room for continuous curing to 28 days, when the test period reaches the first 7 days of the test period, a stone cutter is adopted to cut the test pieces into cylindrical test pieces with the diameter of (100 +/-1) mm and the height of (50 +/-2) mm, the test pieces are taken and processed, then are polished by using abrasive paper, the processed test pieces are continuously immersed in water for curing to the test period, and the size. In order to research the influence of the internal water saturation of the concrete on the chloride ion diffusion coefficient of the concrete, a common concrete cylindrical test piece with the part number of NC3 is selected, is subjected to water saturation treatment and then is subjected to drying treatment, so that the internal water saturation of the concrete cylindrical test piece is respectively 30%, 50% and 70%, and is respectively numbered as SNC1, SNC2 and SNC 3.
RCM method rapid chloride ion diffusion test. The RCM method rapid chloride ion penetration test is carried out according to GBT50082-2009 test method standard for long-term performance and durability performance of ordinary concrete, and the method is suitable for measuring the unsteady state migration coefficient of chloride ions in the cement-based composite material. The cement-based material with each group number takes 3 cylindrical test pieces to test the chloride ion diffusion coefficient, however, the average value of the 3 test values is taken as the chloride ion diffusion coefficient of the cement-based material, and the test results are shown in Table 7.
And (3) comparing and analyzing the test value and the predicted value:
in order to illustrate the reliability of the prediction model of the invention, the model predicted value of the chloride ion diffusion coefficient of each cement-based material is compared with the RCM measured value, and the comparison result of the model predicted value and the test value is shown in Table 7.
TABLE 7 comparison of predicted values and test values of cement-based material models of different scales
Figure GDA0001671493950000122
Figure GDA0001671493950000131
In table 7, by comparing and analyzing the predicted values and the test values of C0.4, C0.5 and C0.6, it can be found that the hardened cement paste chloride ion diffusion coefficient prediction results are better in degree of coincidence with the test, the maximum deviation value is only 5.16%, and the minimum deviation value is 3.28%, which indicates that the hardened cement paste chloride ion diffusion coefficient prediction method provided by the present invention is effective.
The three groups of comparison data of M0.4, M0.5 and M0.6 in the table 7 can show that the maximum deviation of the predicted value and the test value of the chloride ion diffusion coefficient of the cement mortar prepared according to the design of the prediction model is not more than 7%, and the prediction deviation of the new cement mortar also comprises the prediction deviation of the hardened cement mortar, so that the deviation value is larger than the deviation value of the cement mortar, but the value is still in a reasonable range, and the new cement mortar chloride ion diffusion coefficient multi-scale prediction method provided by the invention is effective.
NC1, NC2 and NC3 in Table 7 respectively represent common concrete designed by three different mix proportions, and the maximum deviation of the predicted value of the chloride ion diffusion coefficient of the recycled concrete and the test value thereof can be found to be 8.13 percent from the comparative data. Considering that the prediction deviation of the concrete chloride ion diffusion coefficient comprises the prediction deviation of the hardened cement paste and the prediction deviation of the new mortar, and because the factors such as greater discreteness, test errors and the like of the recycled concrete, the prediction deviation value is acceptable even if the prediction deviation value is larger than the prediction deviation of the hardened cement paste, and the recycled concrete chloride ion diffusion coefficient multi-scale prediction model provided by the invention is also effective. The deviation relationship between the predicted value and the test value is shown in fig. 8.
The comparison results of the last three groups of data in the table 7 show that the deviation between the predicted value of the unsaturated concrete chloride ion diffusion coefficient calculated by the prediction model and the test value is kept within 9 percent, which indicates that the unsaturated concrete chloride ion diffusion coefficient prediction model provided by the invention is still reliable.
The existing model formula is compared with the prediction model of the invention for analysis:
in order to illustrate the superiority of the model prediction of the invention, the existing unsaturated concrete chloride ion diffusion coefficient prediction model is further introduced for comparison. Clime obtains a calculation model of concrete chloride ion diffusion changing along with internal water saturation when the water-cement ratio is 0.6 through experimental study by fitting, the considered factors of the model are similar to the prediction model of the invention and can be used as a comparison model, and the fitting formula of unsaturated concrete chloride ion diffusion coefficient established by Clime is shown as a formula (59).
Dcl(θ)＝Dcl,1·(0.04514-0.6889θ+1.6438θ2) (59)
In the formula, theta is the water saturation inside the concrete; dclConcrete with water saturation thetaThe chloride ion diffusion coefficient of (a); dcl,1The chloride ion diffusion coefficient of saturated concrete.
For the convenience of comparative analysis, the predicted value of the chloride ion diffusion coefficient of the concrete with the number NC3 is taken as D in the formula (59)cl,1A value of, i.e. take Dcl,1＝5.29×10-12m2In this case, formula (59) can be abbreviated as:
Dcl(θ)＝0.2387906-3.644281θ+8.695702θ2(60)
for the model for predicting the diffusion coefficient of the chloride ions in the unsaturated concrete, when D isNC＝5.29×10-12m2When T is 28d and T is 298K, formula (58) is simplified as follows:
DSNC＝4.1515θ2+1.137 (61)
the formulas (60) and (61) respectively represent the relation between the unsaturated concrete chloride ion diffusion coefficient in the Client model and the prediction model of the invention and the change of the internal water saturation of the concrete, the specific relation curve is shown in FIG. 9, the RCM method measured values of the chloride ion diffusion coefficient of the concrete with three numbers of SCN0.3, SCN0.5 and SCN0.7 are added in FIG. 9, the comparison analysis can find that the prediction model of the invention is higher in coincidence degree with the measured values, but the Client model has larger deviation with the measured values, and the Client model can not predict the chloride ion diffusion coefficient of the concrete with any saturation degree, which shows that the model of the invention is more excellent in predicting the unsaturated concrete chloride ion diffusion coefficient.
Concrete meeting different service life requirements in design in embodiment two
The prediction model can guide the actual engineering and design concrete meeting the requirements of different service lives. According to the existing concrete structure life prediction theory and by combining the prediction model, the relation of the concrete chloride ion diffusion coefficient changing along with time is established, the chloride ion diffusion coefficient of the concrete meeting different service life requirements is solved, the solved chloride ion diffusion coefficient is substituted into the common concrete multi-scale prediction model, a specific mix proportion design is obtained, and references can be provided for designing the concrete with different durability requirements in actual engineering.
The Yanglang peak and the like are based on the second fick diffusion law, age attenuation coefficients are considered, and the established concrete chloride ion erosion life prediction formula is as follows:
Figure GDA0001671493950000141
from the formula (62), the limiting expression of the concrete chloride ion diffusion coefficient can be obtained:
Figure GDA0001671493950000142
in the formulas (61) and (63), T is the design service life; d0For concrete at t0The diffusion coefficient of chloride ions at the (initial) time is called as the initial diffusion coefficient and is obtained by measuring a concrete sample with the age of 28d by an RCM method; n is the age-stage attenuation coefficient of the diffusion coefficient, and is generally 0.3 for non-mineral admixture concrete; d is the thickness of the protective layer; c. CsThe concentration of the surface chloride ions of the concrete; c. C0Is the initial chloride ion concentration; c. CrThe critical chloride ion concentration for the passivation of the reinforcing steel bars; erf-1(. cndot.) is the inverse of the error function.
C is obtained after the chlorine salt environmental action grade of the concrete structure is knowns、c0、crAnd d, if the design service life T is given, when n is 0.3, the initial diffusion chloride ion diffusion coefficient limit values of the concrete under different design service lives and different chlorine salt environmental action grades can be calculated according to the formula (63), and the value can provide quantitative basis for the design and preparation of the mix proportion of the concrete required by different service lives by further combining the recycled concrete multi-scale prediction model.
C obtained according to the relevant provisions of the endurance code and guideliness、c0、crDesign parameters such as d are shown in Table 8.
TABLE 8 design parameters for different environmental impact levels and design lifetimes
Figure GDA0001671493950000151
When the design years are 30 years, 50 years and 100 years respectively, the limit value of the initial chloride ion diffusion coefficient of the concrete at each level can be calculated by the formula (63) under different environmental action grades, as shown in table 9.
TABLE 9 initial chloride ion diffusion coefficient D of concrete structure0Limit of (2)
Figure GDA0001671493950000152
The initial chloride ion diffusion coefficient limit value D of the concrete structure with the environmental action grade of III-C and the design service life of 50 years (D is 45mm) in the table 9 is selected by combining the prediction model of the invention0＝5.5×10-12m2And/s, calculating the mixing proportion of the concrete meeting the use requirement.
Firstly, setting the volume fraction of coarse aggregate in concrete, and taking V NA40%, is represented by formula (56) for VNITZIs given by the value of VNITZWhen the water-gel ratio is 0.4, if the concrete is completely saturated, the diffusion coefficient D of each branch chloride ion can be further calculated by using the related prediction model of the inventionITZ、DNMThe values of (A) are shown in Table 10, and the respective calculated values are substituted into the formula (55), whereby the chloride ion diffusion coefficient of the recycled concrete can be calculated as DNC＝4.66×10-12m2/s≤5.5×10-12m2The value of the concrete chlorine ion diffusion coefficient meets the requirements on the initial diffusion coefficient limit of the concrete when the environmental effect grade is III-C and the design age is 50 years, the mixing ratio can be designed according to relevant assumptions, and the specific mixing ratio is designed as shown in Table 11. E.g. calculated if the above designNCIf the ratio is larger than the specified limit value, the water-cement ratio and the volume fraction of the recycled aggregate are adjusted according to a prediction formula until DRCBelow a specified limit.
TABLE 10 values and calculations of various relevant parameters in the prediction model
Figure GDA0001671493950000161
TABLE 11 recycled concrete mix design with environmental impact rating of III-C and design service life of 50 years
Figure GDA0001671493950000162
In conclusion, the predicted value of the diffusion coefficient of the concrete chloride ions calculated by the prediction model is compared with the actual measured value of the RCM method and the predicted value of the existing model, the coincidence degree of the predicted value of the model and the test value is good, and the superiority of the model is illustrated. Meanwhile, according to the established prediction model and the life prediction theory, different requirements of actual engineering on the durability of the concrete are considered, partial model parameters are preselected, and concrete mixing ratios meeting the requirements of different service lives can be calculated. Therefore, on one hand, the method can well predict the chloride ion diffusion coefficient of the unsaturated concrete according to the pre-selected related materials and the mixing proportion, and provides reference for designing concrete with excellent chloride ion resistance; on the other hand, the concrete can be designed to meet the requirements of different service lives by combining the concrete life prediction theory, and a new reference is provided for the research and research on the durability of the concrete. . In addition, the model can further represent the relation rule between the water saturation inside the concrete and the diffusion of the chloride ions, and is favorable for further researching the transmission mechanism of the chloride ions in the unsaturated concrete.
In short, the multi-scale and multi-phase characteristics of the concrete material are considered, the established multi-scale prediction model can finely analyze all relevant influence factors, preselect relevant materials, design the mix proportion, accurately prepare the concrete with different durability requirements according to the actual engineering requirements, accurately represent the relation rule between the water saturation inside the concrete and the chloride ion diffusion of the concrete, and provide a new thought for the durability research of the concrete.

Claims (8)

1. A construction method of a unsaturated concrete chloride ion diffusion coefficient multi-scale prediction model comprises the following steps:
establishing a prediction model of the chloride ion diffusion coefficient of the cement paste;
establishing a new mortar chloride ion diffusion coefficient prediction model;
establishing a common concrete chloride ion diffusion coefficient multi-scale prediction model;
establishing a chloride ion diffusion coefficient prediction model of unsaturated concrete;
the step <1> is performed as follows:
and (3) establishing a hardened cement paste chloride ion diffusion coefficient prediction model by combining a generalized self-consistent method and a Mori-Tanaka method, wherein the model comprises the following steps:
Figure FDA0002358979900000011
in the formula (1), phi,
Figure FDA0002358979900000012
the expression of (a) is:
Figure FDA0002358979900000013
in the formula (2), DhCSHThe diffusion coefficient of a high-density C-S-H gel layer in the cement is shown; dlCSHThe diffusion coefficient of the low-density C-S-H gel layer in the cement is shown; vαThe volume fraction of the high-density C-S-H gel layer in the hardened cement paste in the total cement volume is adopted; vβIs the sum of the volume fractions of unhydrated cement particles and a high-density C-S-H gel layer in the hardened cement paste; volume fraction of unhydrated cement particles is VU；
According to the matrix-inclusion model having DhCSHThe expression of (a) is:
Figure FDA0002358979900000014
wherein:
Figure FDA0002358979900000015
Figure FDA0002358979900000016
in the formulae (3) to (5),
Figure FDA0002358979900000017
the diffusion coefficient of the chloride ions in the high-density C-S-H gel layer is obtained through tests and numerical calculation;
Figure FDA0002358979900000018
VhCSHthe volume fractions of the CH, AF, respectively, high density C-S-H gel layer matrix in the high density C-S-H gel layer αh、βhIs an intermediate variable;
according to the Mori-Tanaka method there is DlCSHThe expression of (a) is:
Figure FDA0002358979900000021
wherein:
Figure FDA0002358979900000022
Figure FDA0002358979900000023
Figure FDA0002358979900000024
Figure FDA0002358979900000025
ζ＝Vcap(Dcap-D′lCSH) (11)
d 'in formulae (6) to (11)'lCSHThe effective diffusion coefficient of the equivalent dielectric layer is formed by uniformly mixing cement hydration products and a low-density C-S-H gel layer matrix;
Figure FDA0002358979900000026
the diffusion coefficient of the chloride ions in the low-density C-S-H gel layer is obtained through tests and numerical calculation;
Figure FDA0002358979900000027
Vcap、VlCSHthe volume fractions of the CH, AF, capillary and low-density C-S-H gel layer matrix in the low-density C-S-H gel layer respectively; dcapα effective diffusion coefficient of capillaryl、βlξ, ζ are intermediate variables;
the volume fractions of various hydration products of the hardened cement paste are respectively VCH、VAF、VCSHVolume fraction of unhydrated cement particles of VUVolume fraction of capillary pores is VcapThen, there are:
VCH+VAF+VlCSH+VhCSH+VU+Vcap＝1 (12)
and has the following components:
Figure FDA0002358979900000028
v in formula (2)α、VβAre respectively:
Figure FDA0002358979900000029
Figure FDA00023589799000000210
and (3) integrating the formulas (1) to (15) to obtain a cement paste chloride ion diffusion coefficient prediction model with each volume parameter as a variable, wherein the model comprises the following steps:
Figure FDA0002358979900000031
in the formula (16), the compound represented by the formula,
Figure FDA0002358979900000032
Dcapmeasured values calculated for the tests and values; assuming that the mass of the saturated cement paste is 1g, according to a chemical reaction equation of ordinary portland cement, a prediction model of each volume fraction in the clean paste is obtained as follows:
Figure FDA0002358979900000033
Figure FDA0002358979900000034
Figure FDA0002358979900000035
Figure FDA0002358979900000036
Figure FDA0002358979900000037
Figure FDA0002358979900000038
in the formulas (17) to (22), n is the initial water cement ratio of the cement paste; t-age; rhoc、ρlCSH、ρhCSH-density of cement, density of low density C-S-H gel, density of high density C-S-H gel; p is a radical of1、p2、p3、p4—C3S、C2S、C3A、C4Mass fraction of AF in cement clinker.
2. The construction method according to claim 1, characterized in that: diffusion coefficient of the chloride ions in the high density C-S-H gel layer
Figure FDA0002358979900000039
Get
Figure FDA00023589799000000310
Diffusion coefficient of chloride ions in low density C-S-H gel layer
Figure FDA00023589799000000311
Get
Figure FDA00023589799000000312
Effective diffusion coefficient of capillary pores DcapGet Dcap＝2.03×10-9m2/s。
3. The method of construction according to claim 1, wherein the step <2> is performed by:
adopting a generalized self-consistent method to predict, and establishing a new mortar chloride ion diffusion coefficient prediction model as follows:
Figure FDA0002358979900000041
ξ in formula (23), ζ is an intermediate variable, having:
Figure FDA0002358979900000042
in the formula (24) DHCPIs the step of<1>Predicting the chloride ion diffusion coefficient of the obtained hardened cement paste; dITZThe diffusion coefficient of chloride ions in an ITZ interface transition zone between fine aggregate and hardened cement paste in the new mortar; vAThe volume fraction of the fine aggregate in the new mortar is calculated by the mixing proportion of the mortar; vITZIs new medium fine mortarThe volume fraction of an interface transition zone ITZ between the aggregate and the hardened cement paste ranges from 5% to 30%;
wherein D is the new mortar with cement as the matrixITZThe expression of (a) is:
DITZ＝117.563DHCP·hITZ -0.8772(25)
h in formula (25)ITZThe thickness of the interface transition zone in the new mortar.
4. The construction method according to claim 3, wherein: thickness h of the interfacial transition zone in the new mortarITZGet hITZ＝25μm。
5. The method of construction according to claim 1, wherein step <3> is performed by:
adopting a generalized self-consistent model, and establishing a chloride ion diffusion coefficient multi-scale prediction model of the natural coarse aggregate concrete as follows:
Figure FDA0002358979900000043
in the formula (26), v and ω are intermediate variables, and there are:
Figure FDA0002358979900000044
in the formula (27), DNMPresentation step<2>The chloride ion diffusion coefficient of the obtained new mortar; dNITZRepresenting the diffusion coefficient of chloride ions in an ITZ (interface transition zone) between natural aggregate and new mortar in concrete; vNARepresents the volume fraction of the natural coarse aggregate; vNITZThe volume fraction of an ITZ (interface transition zone) between natural coarse aggregate and new mortar in the concrete is represented, and the value range is 0.1-2.0%;
wherein, D of the common concrete taking the new mortar as the matrixNITZThe expression of (a) is:
DNITZ＝117.563DNM·hNITZ -0.8772(28)
h in formula (28)NITZIs the thickness of the interfacial transition zone in the concrete.
6. The construction method according to claim 5, wherein: thickness h of the interfacial transition zone in the concreteNITZGet hNITZ＝35μm。
7. The method of construction according to claim 1, wherein step <4> is performed by:
considering that the internal water saturation of the concrete, the age and the temperature of the concrete can influence the diffusion of chloride ions in the concrete, the chloride ion diffusion coefficient calculation formula of the concrete proposed by Saette is referred, and on the basis of the common chloride ion diffusion coefficient multi-scale prediction model of the concrete, the chloride ion diffusion coefficient multi-scale prediction model of the unsaturated concrete is further established, and the chloride ion diffusion coefficient multi-scale prediction model is as follows:
Figure FDA0002358979900000051
in formula (29), DNCPresentation step<3>The chloride ion diffusion coefficient of the obtained saturated concrete; t is teIndicating the age of the concrete; t is the Kelvin temperature of the concrete; theta is the water saturation of the concrete.
8. The application of the construction method in designing the mix proportion of unsaturated concrete according to claim 1, wherein the mix proportion of unsaturated concrete meeting the requirements of different service lives under different environmental service levels is calculated by combining the unsaturated concrete chloride ion diffusion coefficient multi-scale prediction model and the concrete life prediction theory.
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