CN110568165A - Concrete mesoscopic chloride ion diffusion coefficient prediction method - Google Patents
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- 239000004567 concrete Substances 0.000 title claims abstract description 99
- VEXZGXHMUGYJMC-UHFFFAOYSA-M Chloride anion Chemical compound [Cl-] VEXZGXHMUGYJMC-UHFFFAOYSA-M 0.000 title claims abstract description 88
- 238000009792 diffusion process Methods 0.000 title claims abstract description 66
- 238000000034 method Methods 0.000 title claims abstract description 36
- 150000002500 ions Chemical class 0.000 claims abstract description 60
- 239000011148 porous material Substances 0.000 claims abstract description 57
- 230000005540 biological transmission Effects 0.000 claims abstract description 32
- 238000003384 imaging method Methods 0.000 claims abstract description 8
- 239000004568 cement Substances 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 12
- 238000006703 hydration reaction Methods 0.000 claims description 12
- 239000002002 slurry Substances 0.000 claims description 12
- 230000036571 hydration Effects 0.000 claims description 11
- 230000004907 flux Effects 0.000 claims description 9
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 claims description 8
- 229910052753 mercury Inorganic materials 0.000 claims description 8
- 238000012360 testing method Methods 0.000 claims description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 230000001133 acceleration Effects 0.000 abstract description 2
- 238000010998 test method Methods 0.000 abstract description 2
- 239000000047 product Substances 0.000 description 8
- 238000010586 diagram Methods 0.000 description 6
- 239000000463 material Substances 0.000 description 6
- 239000000523 sample Substances 0.000 description 3
- 229910000831 Steel Inorganic materials 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000037427 ion transport Effects 0.000 description 2
- 238000013508 migration Methods 0.000 description 2
- 230000005012 migration Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 239000010959 steel Substances 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 238000004836 empirical method Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000011545 laboratory measurement Methods 0.000 description 1
- 239000010410 layer Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000012466 permeate Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 239000011241 protective layer Substances 0.000 description 1
- 239000011150 reinforced concrete Substances 0.000 description 1
- 230000002787 reinforcement Effects 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- 239000013535 sea water Substances 0.000 description 1
- 238000001179 sorption measurement Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000032258 transport Effects 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N13/00—Investigating surface or boundary effects, e.g. wetting power; Investigating diffusion effects; Analysing materials by determining surface, boundary, or diffusion effects
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
- G01N15/088—Investigating volume, surface area, size or distribution of pores; Porosimetry
- G01N15/0886—Mercury porosimetry
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/22—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material
- G01N23/225—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion
- G01N23/2251—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion using incident electron beams, e.g. scanning electron microscopy [SEM]
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0003—Composite materials
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/38—Concrete; Lime; Mortar; Gypsum; Bricks; Ceramics; Glass
- G01N33/383—Concrete or cement
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N13/00—Investigating surface or boundary effects, e.g. wetting power; Investigating diffusion effects; Analysing materials by determining surface, boundary, or diffusion effects
- G01N2013/003—Diffusion; diffusivity between liquids
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2223/00—Investigating materials by wave or particle radiation
- G01N2223/07—Investigating materials by wave or particle radiation secondary emission
- G01N2223/09—Investigating materials by wave or particle radiation secondary emission exo-electron emission
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2223/00—Investigating materials by wave or particle radiation
- G01N2223/10—Different kinds of radiation or particles
- G01N2223/102—Different kinds of radiation or particles beta or electrons
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2223/00—Investigating materials by wave or particle radiation
- G01N2223/60—Specific applications or type of materials
- G01N2223/649—Specific applications or type of materials porosity
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Abstract
The invention discloses a method for predicting a mesoscopic chloride ion diffusion coefficient of concrete, which comprises the steps of obtaining the information of a pore structure, the porosity and the pore size distribution of the concrete; determining the volume distribution of aggregates in the concrete by combining a microscopic imaging technology with porosity and pore size distribution, and constructing a two-dimensional microscopic structure of the concrete; determining the concentration and distribution of ions on the surface of the pores of the concrete on the basis of the two-dimensional microscopic structure; constructing a multi-ion transmission model according to a mass conservation law, ion concentration, ion flow, an ion apparent diffusion coefficient, ion charge and the like; calculating the transmission concentration distribution of chloride ions in the concrete according to the law and the multi-ion transmission model; and calculating the diffusion coefficient of the chloride ions in the concrete according to the transmission concentration distribution of the chloride ions. The method considers the influence of micro and microscopic structures of the concrete and surface ions on the diffusion of the chloride ions when predicting the diffusion coefficient of the chloride ions of the concrete, and is more accurate and scientific compared with the conventional electric acceleration test method.
Description
Technical Field
the invention belongs to the field of cement-based composite materials, and particularly relates to a method for predicting a mesoscopic chloride ion diffusion coefficient of concrete.
Background
Chloride-induced corrosion of steel reinforcement is a major cause of deterioration of failure of reinforced concrete structures in most cases, especially in cases where contact with chloride is frequent (e.g., when using deicing salt or a seawater environment). Therefore, from the viewpoint of service life and maintenance work, it is very important to design a concrete protective layer (concrete layer covering steel bars) having a sufficient thickness and excellent permeation resistance. The most important index for quantifying the rate of chloride ion intrusion into concrete is the chloride ion diffusion coefficient. Various laboratory measurement methods are used for determining the diffusion/migration coefficient of chloride ions, and in the past, a natural diffusion experimental method is mainly used, so that a concrete sample is exposed in a chloride solution for a long time, chloride ions permeate the sample under the action of concentration gradient, and the diffusion coefficient is calculated through a Fick diffusion theory.
The traditional rapid chloride ion migration test is predicated on a single ion Nernst-Planck equation, a theoretical model is excessively simplified, and the deviation between a measured chloride ion diffusion concentration curve and the theoretical model is large after the test. The main reasons are two major reasons, on one hand, the concrete material is a multiphase material, has a complex pore structure and pore distribution, and changes along with continuous hydration reaction, the transmission process of chloride ions in the concrete is influenced by the pore connectivity, and meanwhile, a part of chloride ions react with cement hydration products in the transmission process to be adsorbed. On the other hand, many ions exist in the concrete pore solution, the ions can generate mutual influence due to electric field force, a theoretical model cannot only consider single transmission of chloride ions, and simultaneously, surface ions can be formed on cement hydration products due to physical and chemical adsorption, and the ions also can generate influence on the chloride ions transmitted in the pore solution.
the current common concrete chloride ion diffusion coefficient prediction method comprises an empirical method and a theoretical calculation method. However, the input parameters of the existing numerical method are still too simplified, and the experimental result cannot be accurately predicted.
Disclosure of Invention
The invention mainly aims to provide a method for predicting the mesoscopic chloride ion diffusion coefficient of concrete, which can accurately predict the chloride ion diffusion coefficient of the concrete.
In order to achieve the above object, the present invention provides a method for predicting a microscopic chloride ion diffusion coefficient of concrete, the method comprising the steps of:
acquiring pore structure information of a microstructure in concrete;
determining the porosity and pore size distribution of cement slurry in the concrete according to the pore structure information;
Determining the volume distribution of the aggregates in the concrete by combining a microscopic imaging technology with porosity and pore size distribution, and constructing a two-dimensional microscopic structure of the concrete based on an aggregate random distribution model;
Determining the surface ion concentration of the concrete according to the two-dimensional microscopic structure; constructing a multi-ion transmission model based on Nernst-Planck/Poisson equation set according to ion concentration, ion flow, ion apparent diffusion coefficient and ion charge;
Calculating the transmission concentration distribution of chloride ions in the concrete according to the mass conservation law and the multi-ion transmission model;
And calculating the diffusion coefficient of the chloride ions in the concrete according to the transmission concentration distribution of the chloride ions.
Further, the step of determining the porosity and pore size distribution of the cement slurry in the concrete according to the pore structure information includes:
and measuring the porosity and pore size distribution of the cement slurry in the concrete by a mercury intrusion method according to the pore structure information of the microstructure.
Further, the step of determining the aggregate volume distribution in the concrete by microscopic imaging technique comprises:
And determining the volume distribution of the aggregate in the concrete by adopting a scanning electron microscope technology.
Further, the multi-ion transmission model is as follows:
Formula (2)
Wherein Jkis the ion flux, Dkis the apparent diffusion coefficient of ion, Ckis the ion concentration, ZkF is 96480C/mol, faraday constant, Φ is local potential, R is 8.314J/(mol · K) is ideal gas constant, T is 298K is absolute temperature, subscript K represents kth pore solution ion of cement slurry, and N is the number of pore solution ions in the model.
further, the local potential Φ is determined by all ions in the pore solution and the hydration product surface ions in the relationship:
Formula (2)
Wherein epsilono＝8.854×10-12C/(V.m) is the dielectric constant in vacuum, εr78.3 is the relative dielectric constant of water at 298K, ZsThe ionic charge on the surface of the hydration product, CsIs the hydration product surface ion concentration.
further, according to the mass conservation law, the concentration of each ion in the pore solution satisfies the following conditions:
Formula (3)
Where t is time.
Further, the step of calculating the diffusion coefficient of chloride ions in concrete according to the chloride ion transmission concentration distribution comprises:
calculating the average diffusion flux JCl -：
Formula (4)
Wherein L is the concrete test speed thickness, x is the calculation direction along the chloride ion transmission in the model, and y is the calculation direction vertical to the chloride ion transmission in the model;
According to the average diffusion flux JCl -Calculation of the chloride diffusion coefficient Deff：
formula (5)
wherein C isbthe boundary chloride ion concentration.
The invention discloses a method for predicting the mesoscopic chloride ion diffusion coefficient of concrete, which comprises the steps of obtaining the pore structure information of a microstructure in the concrete; determining the porosity and pore size distribution of cement slurry in the concrete according to the pore structure information; determining the volume distribution of the aggregates in the concrete by combining a microscopic imaging technology with porosity and pore size distribution, and constructing a two-dimensional microscopic structure of the concrete based on an aggregate random distribution model; determining the concentration and distribution of ions on the surface of the pores of the concrete on the basis of the two-dimensional microscopic structure; constructing a multi-ion transmission model based on Nernst-Planck/Poisson equation set according to the mass conservation law, ion concentration, ion flow, ion apparent diffusion coefficient, ion charged quantity and the like; calculating the transmission concentration distribution of chloride ions in the concrete according to the law and the multi-ion transmission model; and calculating the diffusion coefficient of the chloride ions in the concrete according to the transmission concentration distribution of the chloride ions. The method considers the influence of micro and microscopic structures of the concrete and surface ions on the diffusion of the chloride ions when predicting the diffusion coefficient of the chloride ions of the concrete, and is more accurate and scientific compared with the conventional electric acceleration test method.
Drawings
FIG. 1 is a schematic flow chart of a method for predicting the mesoscopic chloride diffusion coefficient of concrete according to the invention;
FIG. 2 is a schematic diagram of an experiment for simulating rapid chloride ions based on a two-dimensional mesoscopic model in an embodiment of the method for predicting the mesoscopic chloride ion diffusion coefficient of concrete according to the invention;
FIG. 3 is a schematic diagram of mesh division in an embodiment of the method for predicting the mesoscopic chloride ion diffusion coefficient of concrete according to the present invention;
Fig. 4 is a schematic diagram illustrating a chloride ion concentration distribution when t is 1800s in an embodiment of the method for predicting a microscopic chloride ion diffusion coefficient of concrete according to the present invention;
Fig. 5 is a schematic diagram illustrating a chloride ion concentration distribution when t is 3600s in an embodiment of the method for predicting a microscopic chloride ion diffusion coefficient of concrete according to the present invention;
Fig. 6 is a schematic diagram illustrating a chloride ion concentration distribution when t is 5400s in an embodiment of the method for predicting a microscopic chloride ion diffusion coefficient of concrete according to the present invention;
Fig. 7 is a schematic diagram illustrating a chloride ion concentration distribution when t is 7200s in an embodiment of the method for predicting a microscopic chloride ion diffusion coefficient of concrete according to the present invention;
fig. 8 is a schematic view of the flow rate of chloride ions when t is 7200s in an embodiment of the method for predicting the mesoscopic chloride ion diffusion coefficient of concrete of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
in the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., which refer to the orientation or positional relationship, are only used for convenience of description and simplification of the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" as appearing herein are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The specific meaning of the above terms in the present invention can be understood in specific cases for those skilled in the art.
Referring to fig. 1 to 8 (the arrow direction in fig. 8 represents the chloride ion transport direction, and the arrow length represents the relative flow value), the embodiment of the present invention provides a method for predicting the mesoscopic chloride ion diffusion coefficient of concrete, the method comprising the steps of:
S10, acquiring the pore structure information of the microstructure in the concrete;
S20, determining the porosity and pore size distribution of the cement slurry in the concrete according to the pore structure information;
S30, determining the volume distribution of the aggregates in the concrete by combining the microscopic imaging technology with the porosity and the pore size distribution, and constructing a two-dimensional microscopic structure of the concrete based on an aggregate random distribution model;
S40, determining the surface ion concentration of the concrete according to the two-dimensional microscopic structure; constructing a multi-ion transmission model based on Nernst-Planck/Poisson equation set according to ion concentration, ion flow, ion apparent diffusion coefficient and ion charge;
S50, calculating the chloride ion transmission concentration distribution in the concrete according to the mass conservation law and the multi-ion transmission model;
And S60, calculating the diffusion coefficient of the chloride ions in the concrete according to the transmission concentration distribution of the chloride ions.
In the embodiment, the concrete chloride ion diffusion system is an important parameter for measuring the diffusion of chloride ions in concrete, is a key parameter for determining the service life of a concrete structure, and plays an important role in the durability evaluation and design of the concrete structure. When the chloride ion diffusion coefficient in concrete is calculated, the two-dimensional microscopic structure of the pores, the surface ions of the cement paste and the influence of the multi-ion pore solution on the chloride ion diffusion are considered, and compared with the traditional chloride ion diffusion coefficient calculation method, the chloride ion diffusion coefficient can be more accurately measured.
In one embodiment, the step of determining the porosity and pore size distribution of the cement slurry in the concrete comprises:
and measuring the porosity and pore size distribution of the cement slurry in the concrete by a mercury intrusion method according to the pore structure information of the microstructure.
in this embodiment, the mercury intrusion method refers to a method of measuring pore size and pore distribution of a material by allowing mercury to enter pores of the material against surface tension by means of an applied pressure. The additional pressure is increased to allow mercury to enter the smaller pores and the amount of mercury entering the pores of the material is increased. According to the principle that the surface tension of mercury in the air hole is balanced with the applied pressure, the calculation method of the aperture of the material can be obtained. Optionally, the concrete implementation manner of determining the porosity and the pore size distribution of the concrete may also be based on the mixture ratio of the concrete, a three-dimensional microstructure of the concrete at the mixture ratio is simulated, and the porosity and the pore size distribution of the concrete are determined through the three-dimensional microstructure.
In one embodiment, the step of determining the aggregate volume distribution in the concrete by microscopic imaging techniques comprises:
and determining the volume distribution of the aggregate in the concrete by adopting a scanning electron microscope technology.
In the embodiment, the volume distribution of the aggregates in the concrete is determined by adopting a scanning electron microscope technology, wherein the volume distribution of the aggregates mainly comprises the area percentage of the aggregates, an aggregate morphology system, the maximum aggregate diameter and aggregate gradation; alternatively, the aggregate volume distribution may also be determined by an electron probe, an electron spectrometer, or the like.
in one embodiment, the multiple ion transport model is:
formula (3)
Wherein Jkis the ion flux, DkIs the apparent diffusion coefficient of ion, CkIs the ion concentration, Zkfor the ionic charge, F-96480C/mol is the faraday constant, Φ is the local potential, R-8.314J/(mol · K) is the ideal gas constant, T-298K is the absolute temperature, subscript K represents the kth pore solution ion, and N is the number of pore solution ions considered in the model.
in one embodiment, the local potential Φ is determined by all ions in the pore solution and the hydration product surface ions in the relationship:
Formula (2)
wherein epsilono＝8.854×10-12C/(V.m) is the dielectric constant in vacuum, εr78.3 is the relative dielectric constant of water at 298K, Zsthe ionic charge on the surface of the hydration product, Csis the hydration product surface ion concentration.
in one embodiment, the obtaining of the concentration of each ion according to the mass conservation law satisfies:
Formula (3)
where t is time.
In one embodiment, the step of calculating the chloride diffusion coefficient in concrete from the chloride transport concentration profile comprises:
Calculating the average diffusion flux JCl -：
Formula (4)
Wherein L is the concrete test speed thickness, x is the calculation direction along the chloride ion transmission in the model, and y is the calculation direction vertical to the chloride ion transmission in the model;
According to the average diffusion flux JCl -Calculation of the chloride diffusion coefficient Deff：
Formula (5)
wherein C isbthe boundary chloride ion concentration.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (7)
1. A concrete mesoscopic chloride ion diffusion coefficient prediction method is characterized by comprising the following steps:
Acquiring pore structure information of a microstructure in concrete;
Determining the porosity and pore size distribution of cement slurry in the concrete according to the pore structure information;
Determining the volume distribution of the aggregates in the concrete by combining a microscopic imaging technology with porosity and pore size distribution, and constructing a two-dimensional microscopic structure of the concrete based on an aggregate random distribution model;
determining the surface ion concentration of the concrete according to the two-dimensional microscopic structure; constructing a multi-ion transmission model based on Nernst-Planck/Poisson equation set according to ion concentration, ion flow, ion apparent diffusion coefficient and ion charge;
Calculating the transmission concentration distribution of chloride ions in the concrete according to the mass conservation law and the multi-ion transmission model;
And calculating the diffusion coefficient of the chloride ions in the concrete according to the transmission concentration distribution of the chloride ions.
2. The method for predicting the mesoscopic chloride ion diffusion coefficient of concrete according to claim 1, wherein said step of determining the porosity and pore size distribution of the cement slurry in said concrete based on said pore structure information comprises:
and measuring the porosity and pore size distribution of the cement slurry in the concrete by a mercury intrusion method according to the pore structure information of the microstructure.
3. The method for predicting the mesoscopic chloride ion diffusion coefficient of concrete according to claim 1, wherein the step of determining the volume distribution of the aggregates in the concrete by using a microscopic imaging technique comprises:
And determining the volume distribution of the aggregate in the concrete by adopting a scanning electron microscope technology.
4. The method for predicting the mesoscopic chloride ion diffusion coefficient of concrete according to claim 1, wherein the multi-ion transmission model is as follows:
Formula (1)
Wherein JkIs the ion flux, DkIs the apparent diffusion coefficient of ion, Ckis the ion concentration, ZkF is 96480C/mol, faraday constant, Φ is local potential, R is 8.314J/(mol · K) is ideal gas constant, T is 298K is absolute temperature, subscript K represents kth pore solution ion of cement slurry, and N is the number of pore solution ions in the model.
5. the method for predicting the mesoscopic chloride ion diffusion coefficient of concrete according to claim 4, wherein the local potential Φ is determined by all ions in the pore solution and the ions on the surface of the hydration product, and the relationship is as follows:
formula (2)
Wherein epsilono＝8.854×10-12C/(V.m) is the dielectric constant in vacuum, εr78.3 is the relative dielectric constant of water at 298K, ZsThe ionic charge on the surface of the hydration product, Csis the hydration product surface ion concentration.
6. The method for predicting the mesoscopic chloride ion diffusion coefficient of concrete according to claim 4, wherein the concentration of each ion in the pore solution obtained according to the mass conservation law satisfies the following conditions:
Formula (3)
where t is time.
7. The method for predicting the mesoscopic chloride diffusion coefficient of concrete according to claim 6, wherein the step of calculating the chloride diffusion coefficient in concrete according to the chloride transport concentration distribution comprises:
Calculating the average diffusion flux JCl -：
formula (4)
wherein L is the concrete test speed thickness, x is the calculation direction along the chloride ion transmission in the model, and y is the calculation direction vertical to the chloride ion transmission in the model;
According to the average diffusion flux JCl -Calculation of the chloride diffusion coefficient Deff：
formula (5)
wherein C isbThe boundary chloride ion concentration.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112364411A (en) * | 2020-08-07 | 2021-02-12 | 南京理工大学 | Method for simulating seismic performance of concrete cylinder in calcium corrosion and chloride corrosion environments |
| CN113376061A (en) * | 2021-05-21 | 2021-09-10 | 青岛理工大学 | Device and method for monitoring chloride ion permeation state in concrete |
| CN113533199A (en) * | 2021-08-02 | 2021-10-22 | 北京大学 | Method for regulating and controlling hydrogel interface bonding strength |
| CN117686442A (en) * | 2024-02-02 | 2024-03-12 | 广东省有色工业建筑质量检测站有限公司 | Method, system, medium and equipment for detecting diffusion concentration of chloride ions |
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