Method for predicting diffusion of chloride ions in concrete structure of port infrastructure

Abstract

The invention discloses a chloride ion diffusion prediction method in a port infrastructure concrete structure, relates to the technical field of chloride ion diffusion prediction, and aims at executing a series of data driving-based modes to update the rationality of existing initial condition setting. Particularly, a series of analysis is carried out on the initial chloride ion concentration in the existing initial conditions to obtain the final initial chloride ion concentration, the process particularly relates to compensation treatment, specifically, the compensation treatment on the initial chloride ion concentration is particularly carried out, and after two times of compensation treatment are carried out, an initial chloride ion concentration compensation value and a final chloride ion concentration compensation value are obtained respectively; the final chloride ion initial concentration is effectively obtained according to the final chloride ion concentration compensation value, through the compensation analysis method, the accuracy, scientificity and rationality of initial condition setting can be effectively improved, and therefore the credibility of subsequent simulation results is improved; and the deviation between the prediction result and the actual condition can be reduced to the greatest extent.

Description

Technical Field

[0001] The invention relates to the technical field of chloride ion diffusion prediction, and in particular to a method for predicting chloride ion diffusion in a concrete structure of a port infrastructure. Background Art

[0002] Port infrastructure such as docks and breakwaters are exposed to chloride-rich marine environments for a long time. Chloride ion penetration has become one of the main factors affecting their durability. In order to effectively manage and extend the service life of these important assets, a variety of methods have been developed to predict the diffusion process of chloride ions in concrete structures. Among them, numerical calculation analysis has become a widely used technical means.

[0003] Specifically, with the advancement of computer technology and numerical methods, numerical calculation and analysis has become an important tool for predicting chloride ion diffusion. This method mainly includes finite element analysis, finite difference method, etc. Numerical calculation and analysis can more accurately simulate complex geometric shapes and boundary conditions, as well as the heterogeneity and anisotropy of concrete materials. It can also consider the influence of environmental factors such as temperature and humidity changes on chloride ion diffusion. By setting appropriate initial conditions and boundary conditions, combined with specific parameters of concrete materials such as diffusion coefficient, porosity, etc., the numerical model can provide a detailed chloride ion concentration distribution map, thereby helping engineers evaluate the durability of concrete structures.

[0004] Although numerical calculation analysis brings many advantages to the prediction of chloride ion diffusion, it still faces a series of problems and challenges in practical applications: In the prior art, the setting of initial conditions is often only done after a simple test of existing values. Specifically, it especially includes the estimation of the initial chloride ion concentration of concrete. This estimation is usually based on experience or the results of standard tests, for example, determined by laboratory tests, such as using titration, potentiometric titration or ion chromatography to measure the chloride ion concentration in fresh concrete or initial curing concrete samples. However, such a setting method lacks further detailed calculation and analysis process, which poses a challenge to the scientificity and accuracy of the initial condition setting. The accuracy of the initial conditions directly affects the credibility of subsequent simulation results. Therefore, when the initial conditions are set unreasonably, it is very easy to cause a large deviation between the predicted results and the actual situation.

[0005] Therefore, the prior art urgently needs a technical solution for a method for predicting chloride ion diffusion in concrete structures of port infrastructure. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides a method for predicting chloride ion diffusion in a concrete structure of a port infrastructure, which specifically comprises the following steps: Step S1, setting the initial conditions and boundary conditions of the numerical model, and obtaining the parameters of the concrete material; Step S2, analyzing the initial concentration of chloride ions in the initial conditions to obtain a final initial concentration of chloride ions; Step S2a, performing compensation processing on the initial concentration of chloride ions in the initial condition to obtain a compensation value of the initial chloride ion concentration; Step S2a1, obtaining chloride ion concentrations in at least two groups of concrete samples by a laboratory test method, and taking the average as a first initial chloride ion concentration; Step S2a2, obtaining chloride ion concentrations in at least two groups of concrete samples by measuring with a sensor, and taking an average value as a second initial chloride ion concentration; Step S2a3, obtaining the predicted chloride ion concentration in the concrete sample through a preset prediction model; Step S2a31, repeatedly executing step S2a1 to step S2a2 to obtain at least N groups of first initial chloride ion concentrations and second initial chloride ion concentrations; Step S2a32, constructing at least N groups of first initial chloride ion concentrations, at least N groups of second initial chloride ion concentrations and parameters of concrete materials into a data set, and performing preprocessing on the data set; Step S2a33, dividing the preprocessed data set according to a preset ratio, and obtaining any part of the divided data set as a training set; Step S2a34, constructing a prediction model, and using the training set to train the prediction model to obtain a trained prediction model; The prediction model adopts a neural network model; Step S2a35, determining the chloride ion concentration to be input, and inputting the chloride ion concentration to be input into the trained prediction model to obtain the predicted chloride ion concentration in the concrete sample; Step S2a4, obtaining an initial chloride ion concentration compensation value according to the first initial chloride ion concentration, the second initial chloride ion concentration and the predicted chloride ion concentration; Step S2a41, obtaining a first difference between the second initial chloride ion concentration and the first initial chloride ion concentration; Step S2a42, obtaining a second difference between the predicted chloride ion concentration and the first initial chloride ion concentration; Step S2a43, obtaining a third difference between the predicted chloride ion concentration and the second initial chloride ion concentration; Step S2a44, obtaining an initial chloride ion concentration compensation value according to the first difference, the second difference and the third difference; The calculation formula for obtaining the initial chloride ion concentration compensation value is:

[0007] in, Represents the initial chloride ion concentration compensation value; represents a first difference between the second initial chloride ion concentration and the first initial chloride ion concentration; a second difference representing the predicted chloride ion concentration and the first initial chloride ion concentration; represents a third difference between the predicted chloride ion concentration and the second initial chloride ion concentration; Step S2b, performing compensation processing on the initial chloride ion concentration compensation value to obtain a final chloride ion concentration compensation value; Step S2b1, repeating step S2a to obtain at least three sets of initial chloride ion concentration compensation values; Step S2b2, obtaining the absolute value of the difference between each group of initial chloride ion concentration compensation values; Step S2b3, combining the absolute value of the difference with the initial chloride ion concentration compensation value to obtain a final chloride ion concentration compensation value; Step S2c, obtaining a final chloride ion initial concentration according to the final chloride ion concentration compensation value; combining the final chloride ion concentration compensation value with the first initial chloride ion concentration to obtain a final chloride ion initial concentration; Step S3, updating the initial conditions of the numerical model according to the final initial chloride ion concentration, and inputting the boundary conditions of the numerical model, the updated initial conditions of the numerical model and the parameters of the concrete material into the preset numerical model to obtain a chloride ion concentration diffusion distribution map; Step S4: evaluating the durability of the concrete structure according to the chloride ion concentration diffusion distribution diagram.

[0008] The embodiments of the present invention have the following technical effects: The present invention aims to perform a series of data-driven updates on the rationality of the existing initial condition settings, especially to perform a series of analyses on the initial chloride ion concentration in the existing initial conditions to obtain the final initial chloride ion concentration. The process particularly involves compensation processing, specifically, particularly involves compensation processing for the initial chloride ion concentration, and after performing two compensation processings, the initial and final chloride ion concentration compensation values ​​are obtained respectively, and the final chloride ion concentration compensation value is used to effectively obtain the final initial chloride ion concentration. Through the above-mentioned compensation analysis method, the accuracy, scientificity and rationality of the initial condition setting can be effectively improved, so as to improve the simulation results of the subsequent numerical model, that is, the credibility of the chloride ion concentration diffusion distribution map, and thus can minimize the deviation between the predicted results and the actual situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0010] Figure 1 The present invention provides a flowchart of a method for predicting chloride ion diffusion in a concrete structure of a port infrastructure. DETAILED DESCRIPTION

[0011] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0012] Embodiment 1: Figure 1 As shown, the present invention provides a method for predicting chloride ion diffusion in a concrete structure of a port infrastructure, comprising the following steps: Step S1, setting the initial conditions and boundary conditions of the numerical model, and obtaining the parameters of the concrete material.

[0013] Initial conditions refer to the description of the state of the system at the beginning of the numerical simulation (t=0). For the prediction of chloride ion diffusion, the initial conditions mainly include the initial concentration of chloride ions in concrete, the initial moisture saturation of concrete, and the initial temperature. The initial concentration of chloride ions in concrete can be obtained by laboratory testing, such as measuring the chloride ion content in fresh concrete or initial concrete samples using titration, potentiometric titration, or ion chromatography. The initial moisture saturation of concrete can be obtained by indirectly estimating the moisture content through resistivity testing. The initial temperature can be obtained by setting it based on the climate data of the construction site, installing temperature sensors at different locations on the construction site, and recording the temperature changes over a period of time, thereby determining a reasonable average initial temperature.

[0014] Boundary conditions are conditions imposed on the model boundaries during the simulation process. They reflect the impact of the external environment on the concrete structure. For chloride ion diffusion prediction, common boundary conditions include surface chloride ion concentration, water evaporation rate, and temperature gradient. The surface chloride ion concentration can be obtained by regularly collecting samples on the surface of the concrete structure and measuring the surface chloride ion concentration through chemical analysis methods such as potentiometric titration. The water evaporation rate can be estimated using meteorological data and evaporation models. The temperature gradient can be obtained by using the air temperature data provided by the meteorological station combined with a heat conduction model to calculate the temperature distribution inside the concrete.

[0015] Step S2, analyzing the initial concentration of chloride ions in the initial conditions to obtain the final initial concentration of chloride ions, specifically comprising the following steps: Step S2a, performing compensation processing on the initial chloride ion concentration in the initial condition to obtain an initial chloride ion concentration compensation value, wherein the specific process of how to obtain the initial chloride ion concentration compensation value includes the following steps: Step S2a1, obtaining chloride ion concentrations in at least two groups of concrete samples by a laboratory test method, and taking the average as a first initial chloride ion concentration.

[0016] Step S2a2: obtaining chloride ion concentrations in at least two groups of concrete samples by measuring with a sensor, and taking an average value as a second initial chloride ion concentration.

[0017] It is worth mentioning that when the chloride ion concentration in the concrete sample is measured by the sensor, the chloride ion concentration in the concrete sample is determined mainly by sampling and analyzing on-site with the optical fiber sensor. Furthermore, the optical fiber sensor is specifically a chloride ion optical fiber sensor based on detecting the refractive index of the environment. The principle is as follows: when the refractive index of the external medium changes, the central wavelength of the long-period fiber grating will shift, and when the chloride ion concentration changes, it will cause the refractive index in the solution to change. Therefore, the concentration of chloride ions can be detected by observing and recording the change in the central wavelength of the long-period grating. Since the optical fiber sensor is extremely sensitive to temperature, when using a chloride ion concentration sensor based on an optical fiber sensor in actual engineering, a temperature compensation sensor must be used.

[0018] Step S2a3, obtaining the predicted chloride ion concentration in the concrete sample through a preset prediction model, specifically comprising the following steps: Step S2a31, repeatedly executing step S2a1 to step S2a2 to obtain at least N groups of first initial chloride ion concentrations and second initial chloride ion concentrations; It is worth noting that the purpose of step S2a31 is to collect data of multiple concrete samples with known chloride ion concentrations to ensure the generalization ability of the model. The data sources include the laboratory test data in step S2a1 and the field monitoring data in step S2a2.

[0019] Step S2a32: construct at least N groups of first initial chloride ion concentrations, at least N groups of second initial chloride ion concentrations and parameters of concrete materials into a data set, and perform preprocessing on the data set.

[0020] During the preprocessing process, outliers and missing values ​​are first removed to ensure the integrity and accuracy of the data. The data should then be standardized so that all features have the same scale to avoid certain features dominating the model due to their large numerical range. Feature extraction is then performed, and features related to chloride ion concentration are given priority, such as the diffusion coefficient, porosity, water saturation, temperature, and the first initial chloride ion concentration and the second initial chloride ion concentration of concrete materials.

[0021] Step S2a33: Divide the preprocessed data set according to a preset ratio, and obtain any part of the divided data set as a training set.

[0022] It is worth mentioning that the preset ratio should usually be 8 / 2, or 7 / 3, and 8 of them can be selected as training sets, and the remaining 2 correspond to validation sets, which are used to verify the accuracy of the trained model; the basis for the preset ratio is that, under normal circumstances, if the preset ratio is 8 / 2, 80% of the data is used for training to provide enough samples for the model to learn, and the remaining 20% ​​of the data is used for validation, which can effectively evaluate the generalization ability of the model. This is a division basis based on practice.

[0023] Step S2a34, constructing a prediction model, and using the training set to train the prediction model to obtain a trained prediction model; In terms of the selection of prediction models, neural network models are preferred; Step S2a35, determining the chloride ion concentration to be input, and inputting the chloride ion concentration to be input into the trained prediction model to obtain the predicted chloride ion concentration in the concrete sample; When determining the chloride ion concentration to be input, priority is given to obtaining the chloride ion concentration by laboratory testing methods and sensor measurement, and using it as the chloride ion concentration to be input.

[0024] Step S2a4, obtaining an initial chloride ion concentration compensation value according to the first initial chloride ion concentration, the second initial chloride ion concentration and the predicted chloride ion concentration, specifically comprising the following steps: Step S2a41, obtaining a first difference between the second initial chloride ion concentration and the first initial chloride ion concentration.

[0025] Step S2a42, obtaining a second difference between the predicted chloride ion concentration and the first initial chloride ion concentration.

[0026] Step S2a43, obtaining a third difference between the predicted chloride ion concentration and the second initial chloride ion concentration.

[0027] Step S2a44, obtaining an initial chloride ion concentration compensation value according to the first difference, the second difference and the third difference.

[0028] The calculation formula for obtaining the initial chloride ion concentration compensation value is:

[0029] in, Represents the initial chloride ion concentration compensation value; represents the first difference; represents the second difference; Represents the third difference.

[0030] It is worth noting that the above-mentioned method of obtaining the initial chloride ion concentration compensation value through the first, second and third differences can more comprehensively reflect the changing trend of the chloride ion concentration, and can reduce the fluctuation caused by measurement errors or environmental changes, making the results more stable and reliable; at the same time, based on statistical principles, the average value of multiple differences can reduce the impact of random errors and improve the statistical reliability of the results. According to the central limit theorem, the average value of multiple independent samples will approach the normal distribution, thereby improving the stability and accuracy of obtaining the initial chloride ion concentration compensation value.

[0031] Step S2b, performing compensation processing on the initial chloride ion concentration compensation value to obtain a final chloride ion concentration compensation value, specifically comprising the following steps: Step S2b1, repeat step S2a to obtain at least three sets of initial chloride ion concentration compensation values.

[0032] Step S2b2, obtaining the absolute value of the difference between each group of initial chloride ion concentration compensation values.

[0033] Step S2b3, combining the absolute value of the difference with the initial chloride ion concentration compensation value to obtain a final chloride ion concentration compensation value.

[0034] It is worth further explaining that by combining the absolute value of the difference with the initial chloride ion concentration compensation value, the fluctuation caused by measurement error or environmental change can be further reduced, so that the acquisition of the final chloride ion concentration compensation value can be more stable and more accurate.

[0035] Step S2c, obtaining the final chloride ion initial concentration according to the final chloride ion concentration compensation value.

[0036] The final chloride ion concentration compensation value is combined with the first initial chloride ion concentration to obtain a final chloride ion initial concentration.

[0037] It is worth noting that the method of combining the final chloride ion concentration compensation value with the first initial chloride ion concentration can correct the deviation caused by measurement error or environmental change, so that the final chloride ion initial concentration can be closer to the true value.

[0038] Step S3, updating the initial conditions of the numerical model according to the final initial chloride ion concentration, and inputting the boundary conditions of the numerical model, the updated initial conditions of the numerical model and the parameters of the concrete material into the preset numerical model to obtain a chloride ion concentration diffusion distribution diagram.

[0039] In terms of the selection of numerical models, finite element analysis or finite difference method can be selected; the input parameters should include the updated initial conditions, boundary conditions and parameters of concrete materials, among which the updated initial conditions should include the final initial chloride ion concentration, the initial moisture saturation of concrete and the initial temperature; the boundary conditions should include the surface chloride ion concentration, moisture evaporation rate, and temperature gradient; the parameters of concrete materials should include diffusion coefficient, porosity and moisture saturation, etc.

[0040] Then set the simulation parameters: set the simulation time step, grid division and other parameters; then start the numerical model to perform simulation calculations on chloride ion diffusion; finally, after the numerical model is completed, output the chloride ion concentration diffusion distribution map, which shows the concentration distribution of chloride ions in the concrete structure, including the chloride ion concentrations at different locations and time points.

[0041] Step S4: evaluating the durability of the concrete structure according to the chloride ion concentration diffusion distribution diagram.

[0042] Analyze the chloride ion concentration diffusion distribution diagram, determine the diffusion path and speed of chloride ions in concrete, evaluate the corrosion risk of chloride ions to the steel bars inside the concrete, and then evaluate the durability of the concrete structure.

[0043] It should be noted that the terms used in the present invention are only for describing specific embodiments, rather than limiting the scope of the present application. As shown in the present specification, unless the context clearly indicates an exception, the words "one", "a", "a kind of" and / or "the" do not specifically refer to the singular, but may also include the plural. The terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method or device. In the absence of more restrictions, the elements defined by the sentence "include one..." do not exclude the presence of other identical elements in the process, method or device including the elements.

[0044] It should also be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", etc. should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting chloride ion diffusion in concrete structures of port infrastructure, characterized in that: The following steps are involved: Step S1, setting the initial conditions and boundary conditions of the numerical model, and obtaining the parameters of the concrete material; Step S2, analyzing the initial concentration of chloride ions in the initial conditions to obtain a final initial concentration of chloride ions; Step S2a, performing compensation processing on the initial concentration of chloride ions in the initial condition to obtain a compensation value of the initial chloride ion concentration; Step S2a1, obtaining chloride ion concentrations in at least two groups of concrete samples by a laboratory test method, and taking the average as a first initial chloride ion concentration; Step S2a2, obtaining chloride ion concentrations in at least two groups of concrete samples by measuring with a sensor, and taking an average value as a second initial chloride ion concentration; Step S2a3, obtaining the predicted chloride ion concentration in the concrete sample through a preset prediction model; Step S2a4, obtaining an initial chloride ion concentration compensation value according to the first initial chloride ion concentration, the second initial chloride ion concentration and the predicted chloride ion concentration; Step S2b, performing compensation processing on the initial chloride ion concentration compensation value to obtain a final chloride ion concentration compensation value; Step S2b1, repeating step S2a to obtain at least three sets of initial chloride ion concentration compensation values; Step S2b2, obtaining the absolute value of the difference between each group of initial chloride ion concentration compensation values; Step S2b3, combining the absolute value of the difference with the initial chloride ion concentration compensation value to obtain a final chloride ion concentration compensation value; Step S2c, obtaining a final chloride ion initial concentration according to the final chloride ion concentration compensation value; Step S3, updating the initial conditions of the numerical model according to the final initial chloride ion concentration, and inputting the boundary conditions of the numerical model, the updated initial conditions of the numerical model and the parameters of the concrete material into the preset numerical model to obtain a chloride ion concentration diffusion distribution map; Step S4: evaluating the durability of the concrete structure according to the chloride ion concentration diffusion distribution diagram.

2. The method for predicting chloride ion diffusion in a port infrastructure concrete structure according to claim 1, characterized in that: The step S2c, according to the final chloride ion concentration compensation value, obtains the final chloride ion initial concentration, specifically: The final chloride ion concentration compensation value is combined with the first initial chloride ion concentration to obtain a final chloride ion initial concentration.

3. The method for predicting chloride ion diffusion in a port infrastructure concrete structure according to claim 1, characterized in that: The step S2a3, obtaining the predicted chloride ion concentration in the concrete sample by using a preset prediction model, specifically includes: Step S2a31, repeatedly executing step S2a1 to step S2a2 to obtain at least N groups of first initial chloride ion concentrations and second initial chloride ion concentrations; Step S2a32, constructing at least N groups of first initial chloride ion concentrations, at least N groups of second initial chloride ion concentrations and parameters of concrete materials into a data set, and performing preprocessing on the data set; Step S2a33, dividing the preprocessed data set according to a preset ratio, and obtaining any part of the divided data set as a training set; Step S2a34, constructing a prediction model, and using the training set to train the prediction model to obtain a trained prediction model; Step S2a35, determining the chloride ion concentration to be input, and inputting the chloride ion concentration to be input into the trained prediction model to obtain the predicted chloride ion concentration in the concrete sample.

4. The method for predicting chloride ion diffusion in a port infrastructure concrete structure according to claim 1, characterized in that: The step S2a4, obtaining the initial chloride ion concentration compensation value according to the first initial chloride ion concentration, the second initial chloride ion concentration and the predicted chloride ion concentration, specifically comprises: Step S2a41, obtaining a first difference between the second initial chloride ion concentration and the first initial chloride ion concentration; Step S2a42, obtaining a second difference between the predicted chloride ion concentration and the first initial chloride ion concentration; Step S2a43, obtaining a third difference between the predicted chloride ion concentration and the second initial chloride ion concentration; Step S2a44, obtaining an initial chloride ion concentration compensation value according to the first difference, the second difference and the third difference.

5. The method for predicting chloride ion diffusion in a port infrastructure concrete structure according to claim 4, characterized in that: The calculation formula for obtaining the initial chloride ion concentration compensation value is: in, Represents the initial chloride ion concentration compensation value; represents a first difference between the second initial chloride ion concentration and the first initial chloride ion concentration; a second difference representing the predicted chloride ion concentration and the first initial chloride ion concentration; Represents a third difference between the predicted chloride ion concentration and the second initial chloride ion concentration.

6. A method for predicting chloride ion diffusion in a port infrastructure concrete structure according to any one of claims 1 to 5, characterized in that: The prediction model adopts a neural network model.

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