A method for predicting atmospheric environmental corrosion loss considering change of metal active area

Abstract

The present application provides a kind of atmospheric environmental corrosion loss prediction method considering the change of metal active area, steps are as follows: step one: determining indoor metal material accelerated corrosion curve;Step two: establish active area and corrosion loss relationship model;Step three: determine corrosion current under different environmental factors;Step four: build the connection function of corrosion current and environmental factors;Step five: use Runge-Kutta algorithm to predict field environment metal corrosion.The present application establishes the correlation model of environmental factors, metal material surface active area and time variable as a whole to describe the quantitative model method of metal material atmospheric corrosion rate;Compared with traditional modeling method, the prediction of metal material atmospheric corrosion is more accurate and reasonable through active area function and connection function;The present application selects corrosion weight loss as basic physical parameter, test method is simple, easy to calculate, and data processing algorithm complexity is lower;Method is scientific and reasonable, and process is good, with wide popularization and application value.

Description

TECHNICAL FIELD

[0001] The present application relates to a method for predicting atmospheric environmental corrosion loss considering the change of metal active area, namely a method for predicting atmospheric uniform corrosion loss of metal materials in variable environment considering the active area of metal material surface, time dynamics, rust layer corrosion inhibition and environmental difference, which is a long-term prediction method for metal atmospheric corrosion loss based on comprehensive environmental corrosion model, metal material surface active area model and Runge-Kutta algorithm. It establishes a correlation model of environmental factors, metal material surface active area and time variable for describing the quantitative model method of metal material atmospheric corrosion rate in the whole according to different time information and regional information of environmental factor observation data and metal accelerated corrosion curve characteristics. It maps the time dynamics of environmental factors to the parameters of connection function, which is convenient for environmental factor quantization in time scale and further carries out shallow metal atmospheric corrosion loss prediction through Runge-Kutta algorithm. It is suitable for the fields of metal material corrosion prevention and maintenance considering the physical relationship, mathematical statistical relationship between various corrosion products, environmental factors and metal corrosion current density, and is an effective method for predicting metal material corrosion data in dynamic environment. BACKGROUND

[0002] Uniform corrosion refers to corrosion occurring on the entire surface of metal material, and the thinning rate of each part of the metal surface is the same, which results in overall thinning of the metal material. The corrosion of steel components in atmospheric and seawater media generally belongs to general corrosion. Among them, atmospheric corrosion is the most common, the most widely covered, and the most destructive type of corrosion in metal corrosion. According to statistics, the economic loss caused by atmospheric corrosion of metal materials accounts for more than half of the total corrosion loss each year. The types of atmospheric natural environment are diverse, and different atmospheric natural environment factors change significantly and differ greatly. Therefore, the environmental conditions of metal materials serving in atmospheric natural environment are multi-factor and non-constant. The natural environmental factors affecting the atmospheric corrosion of metal materials have the characteristics of diversity, dynamics, randomness and regional difference. In addition, the rust layer produced in long-term atmospheric corrosion also affects the corrosion rate of metal. However, in the current atmospheric corrosion research work, the environmental and metal material surface active area influence law of many metal materials atmospheric corrosion is still not very clear, especially in the aspect of corrosion prediction, there is no systematic and perfect scientific method. Therefore, it is a very practical research work to deeply understand the influencing factors and corrosion law of metal materials in atmospheric environment and establish an effective model for predicting the change law of atmospheric corrosion performance.

[0003] The existing atmospheric corrosion loss prediction model usually uses mean value approximation instead of the average level of environmental factors as the variable of the atmospheric corrosion influence law model, and does not consider the change of the use site of the metal material, and cannot completely and accurately describe all the information of the natural environment profile and the corrosion influence law under the complex atmospheric natural environment condition. In addition, the existing metal atmospheric long-term corrosion loss prediction uses the corrosion kinetics model which cannot effectively reflect the influence of the dynamic nature of the natural environment and the regional difference. By combining the natural atmospheric environment data of different time information and regional information, the accelerated corrosion test data and the corrosion loss and rust layer relationship model, a dynamic atmospheric natural environment corrosion loss prediction method is established, which is closer to the actual service condition.

[0004] Based on this, the application combines the natural atmospheric environment data of different time information and regional information, the accelerated corrosion data of the metal material and the surface active area model of the metal material, establishes a correlation model of the environmental factors, the surface active area of the metal material and the time variable for describing the quantitative model method of the atmospheric corrosion rate of the metal material, and realizes effective prediction of the corrosion data of the metal material in the predicted dynamic environment. SUMMARY

[0005] (1) Objectives of the application:

[0006] In view of the problems that the change rule of the corrosion loss of the metal material with time and environment is relatively complex, and there is no accurate and reasonable prediction of the atmospheric corrosion loss of the metal material, a metal atmospheric corrosion loss prediction method considering the surface active area of the metal material is provided, that is, a metal atmospheric corrosion loss prediction method considering the time dynamics, rust layer corrosion resistance and environmental difference based on the electrochemical polarization theory. It is a long-term metal atmospheric corrosion loss prediction method based on a comprehensive environmental corrosion model, a metal material surface active area model and a Runge-Kutta algorithm. It establishes a correlation model of the environmental factors, the surface active area of the metal material and the time variable for describing the quantitative model method of the atmospheric corrosion rate of the metal material in the whole according to the environmental factor observation data of different time information and regional information and the metal accelerated corrosion curve characteristics.

[0007] (2) Technical solutions:

[0008] The application needs to establish the following basic settings:

[0009] Setting 1: When modeling the surface active area of the metal material, the corrosion products produced in the similar corrosion environment are regarded as having the same physicochemical properties, and the corrosion resistance of the metal material is consistent in mechanism;

[0010] Setting 2: The coverage degree of the rust layer on the active area of the metal material is only related to the current rust layer accumulation, and is irrelevant to the environmental factors;

[0011] Setting 3: the main influencing factors of atmospheric corrosion of metal materials are atmospheric temperature, atmospheric humidity, and sulfur dioxide concentration, and other environmental factors have little effect on metal atmospheric corrosion and can be ignored and simplified;

[0012] Setting 4: the environmental factors affecting the atmospheric corrosion of metal materials are not considered to have interactive effects, and the effects of atmospheric temperature, atmospheric humidity, and sulfur dioxide concentration on metal materials are considered to be independent of each other;

[0013] The method provided by the present application mainly includes natural atmospheric environment data and metal material accelerated corrosion data for different time information and regional information, and a metal material surface active area model, a correlation model of environmental factors, metal material surface active area and time variable is established to describe the quantitative model method of metal material atmospheric corrosion rate, and the effective prediction of metal material corrosion data in a dynamic environment is realized.

[0014] Based on the above assumptions and ideas, the present application provides a shallow seawater temperature spatiotemporal prediction method, i.e., a metal atmospheric corrosion loss prediction method considering the surface active area of metal materials, i.e., a metal atmospheric corrosion loss prediction method based on electrochemical polarization theory considering time dynamics, rust layer corrosion resistance, and environmental differences, which is realized through the following steps:

[0015] Step 1: Determining the indoor metal material accelerated corrosion curve

[0016] The metal material corrosion curve is the basis for establishing the metal material surface active area model and serves as a support for the subsequent steps. Although outdoor natural exposure test can truly and reliably reflect the corrosion behavior of metal in natural atmosphere, the test period is too long. Therefore, indoor simulation accelerated corrosion test is adopted as an alternative. According to the different actual service environments of metal materials, different indoor accelerated corrosion tests are adopted. For metal materials serving in marine atmospheric environment, salt spray test or dry-wet alternating cycle corrosion test can be selected, and the specific test steps can be referred to in GB / T 32065.10-2020 Marine Instrument Environmental Test Methods Part 10: Salt Spray Test. For metal materials serving in humid tropical environments, constant temperature and humidity or variable temperature and humidity can be used for wet heat test, and the specific test steps can be referred to in GB / T 2423.3-2016 Environmental Test Part 2: Test Method Constant Humidity Heat Test. For metal materials serving in industrial pollution areas, corrosive gas media such as sulfur dioxide can be introduced into the temperature and humidity environment. For metal materials serving in seawater environment, artificial simulated seawater immersion test can be used, and the specific test steps can be referred to in GB / T 38269-2019 Corrosion of Metals and Alloys Containing Artificial Seawater Deposition Salt Process Cycle Accelerated Corrosion Test.

[0017] When the above test is performed, the corrosion time t1, t2,..., t nThen, the metal sample is taken out, where n is the total number of samplings. After removing the corrosion products, it is weighed, and the corrosion weight loss d1, d2, ..., d is calculated based on the weight of the uncorroded sample. n Plot the accelerated corrosion curves of metallic materials;

[0018] Step 2: Establish a model relating active area to corrosion loss

[0019] Estimating the corrosion rate at each time point based on the accelerated corrosion curve of the metallic material:

[0020]

[0021] Among them, v i At time t i The corrosion rate of the metal at time d i+1 It is in t i+1 The weight loss of metal due to corrosion at any given time.

[0022] The covering effect of rust on metallic materials can be considered as reducing the active area of ​​the metallic material. Assuming the initial area of ​​the metallic material is S0, due to the covering effect of the rust, the active area of ​​the metallic material at the i-th time point is S. i ,but:

[0023]

[0024] Obviously, the active area S i The range of S is [0, S0]. When corrosion just occurs, S i =S0, as corrosion continues, S i The value of continuously decreases, approaching 0.

[0025] The calculated n active areas S i By corroding the rate at a given point and corresponding to the n corrosion weight losses d in the accelerated corrosion curve of the metallic material, we can obtain n-1 corrosion rate ratios and corrosion losses. Data pairs. Observe the trend of the data pair curves and choose an appropriate function to describe it. The relationship between the two can be modeled by fitting the data using the least squares method:

[0026]

[0027] If no suitable function is available to describe The relationship between them can also be obtained by interpolation to obtain the surface active area of ​​the metal material corresponding to different corrosion weight loss;

[0028] Step 3: Measure corrosion current under different environmental factors

[0029] In the laboratory environment, the laboratory simulation corrosion test is carried out on the metal material studied, and the environmental factors and levels are designed according to the type of test carried out in step one without considering the mutual influence of various environmental factors, which are as follows:

[0030] For the salt spray test or dry-wet alternating cycle corrosion test simulating the marine atmospheric environment, the selected environmental factors are salt spray concentration Cl, temperature T, humidity RH or alternating cycle period. For the constant temperature and humidity or variable temperature and humidity of the wet heat test simulating the humid tropical environment, the selected environmental factors are temperature T, humidity RH or variable temperature and humidity cycle period. For the temperature and humidity environment with the introduction of corrosive gas medium simulating the industrial pollution in serious areas, the selected environmental factors are temperature T, humidity RH and pollutant concentration. For the artificial simulation of seawater immersion test simulating the seawater environment, the selected environmental factors are temperature T and salinity Cl.

[0031] In each test, the data of each environmental factor should not deviate too much from the actual environment, so as not to change the corrosion mechanism. The concentration of sodium chloride for generating salt spray is controlled at 40-60 grams per liter, the environmental temperature is controlled at 30-80 degrees Celsius, and the humidity is controlled at 40%-100%.

[0032] After determining the test environmental factors, the level of each environmental factor is controlled at three or more levels, that is, each environmental factor is designed to have three or more values. The initial corrosion current of the metal material without rust layer is measured by an atmospheric corrosion sensor. The atmospheric corrosion sensor can be an electrochemical impedance atmospheric corrosion sensor. The specific measurement method is as follows: first, measure the high frequency and low frequency electrochemical impedance, and calculate the difference between the two as the polarization resistance value R p of the metal material. Then, the electrochemical polarization curve of the metal is measured, and the sensitivity of the response of the cathode and anode current to the applied potential is calculated, that is, the slope of the logarithm of the response cathode and anode current with respect to the change of potential, and the Tafel cathode and anode slope β a and β c are calculated. Finally, the corrosion current i corr is estimated according to the linear polarization method.

[0033]

[0034] Step four: constructing the connection function of corrosion current and environmental factors

[0035] On the basis of the corrosion current data measured under different environmental factors and different levels obtained in step three, the connection function of the corrosion current density of the metal material and the environmental factors is further constructed. Different environmental factors have different effects on corrosion, so different corrosion models are selected, which are as follows:

[0036] For relative humidity, the selected accelerated corrosion models include the following three:

[0037] ξ(RH)=α·RH β (4)

[0038] Here, α and β are parameters characterizing the relationship between relative humidity and corrosion, and RH is the relative humidity.

[0039] The effect of temperature on the corrosion of metallic materials can be described using the Arrhenius model:

[0040]

[0041] Where δ and ε are parameters characterizing the relationship between temperature and corrosion, and T is the Kelvin temperature.

[0042] The effects of sulfur dioxide and chloride ions on the corrosion of metallic materials can be described using a power function model:

[0043] ξ(S)=(1+η·S) τ (6)

[0044]

[0045] Wherein, η and τ are parameters characterizing the relationship between sulfur dioxide concentration and corrosion effect. κ and κ are parameters characterizing the relationship between chloride ion concentration and corrosion effect, S is sulfur dioxide concentration, and Cl is chloride ion concentration.

[0046] Based on the corrosion current data obtained in step three under different environmental factors, the above model is fitted using the least squares method to obtain the parameters α, β, δ, ε, η, τ of each connection function. And κ. Specifically, taking relative humidity as an example, keeping other factors constant, we set three conditions with relative humidity RH of 40%, 60%, and 80%, and measured the corrosion current ξ(RH) of the metal material under the three conditions using the method in step three. Based on the three ξ(RH) values ​​and the three RH values, we fitted the parameters α and β in the connection function.

[0047] Step 5: Predict metal corrosion in the external environment using the Runge-Kutta algorithm.

[0048] Before conducting field corrosion prediction, it is necessary to collect environmental factor monitoring data of the field environment as input to the connection function model. Field atmospheric environmental data can be obtained from two sources: meteorological station monitoring data and publicly available environmental database data. Currently, publicly available environmental databases include the World Ocean Database (WOD), the Array for Real-Time Geostrophic Oceanography (ARGO), and the World Data Center for Climate (WDCC). Each data point collected from these databases must include the atmospheric or seawater temperature, atmospheric humidity, sulfur dioxide pollutant concentration, chloride ion deposition rate, seawater salinity, and time-specific indicators (accurate to year, month, day, or year, month).

[0049] After obtaining the field environment data, let ξ(·) be the product of all connectivity functions. The rust coverage function and connectivity function are then transformed into corrosion loss through integration.

[0050]

[0051] Where v(d) represents the corrosion rate when the corrosion weight loss is d, and f(d,t) is the functional relationship between v(d) and corrosion weight loss and corrosion time, the specific form of which is determined according to the trend of corrosion data.

[0052] Since field environmental data are generally discrete, the Runge-Kutta numerical integration method can be used to calculate corrosion loss.

[0053] The initial value of corrosion loss is expressed as follows:

[0054] v(t)=d'=f(d,t)·ξ(·),d(t0)=0 (9)

[0055] Where d' represents the derivative of corrosion weight loss with respect to corrosion time.

[0056] Therefore, the amount of corrosion at time t is given by the following equation:

[0057]

[0058] Where l is the time interval between two observations, let m1 = f(d) i ,t i ), m4=f(d i ·l·m3,t i +l). d(t) i+1 ) and d(t i ) represent t respectivelyi+1 and t i Corrosion weight loss at the moment.

[0059] The above-mentioned "WOD, ARGO, WDCC" refers to three representative public marine environment observation data sets, which are applied to observe and evaluate marine environment changes.

[0060] The metal atmospheric corrosion loss prediction method considering the active surface area of the metal material maps the time dynamics of the environmental factors onto the parameters of the connection function, facilitates the quantification of the environmental factors on the time scale, and further carries out the shallow metal atmospheric corrosion loss prediction through the Runge-Kutta algorithm; is suitable for the fields of metal material corrosion prevention and maintenance considering the physical relationship, mathematical statistical relationship between various corrosion products, environmental factors and metal corrosion current density, and is an effective method for predicting metal material corrosion data in dynamic environment.

[0061] Through the above steps, the effect of mapping the time dynamics of the environmental factors onto the parameters of the connection function, facilitating the quantification of the environmental factors on the time scale, and further carrying out the shallow metal atmospheric corrosion loss prediction through the Runge-Kutta algorithm is achieved, the problem that the existing method cannot completely and accurately describe all information of the natural environment profile and the corrosion influence law under complex atmospheric natural environment conditions is solved, and the function of predicting metal material corrosion data in dynamic environment is realized.

[0062] (3) Advantages and effects:

[0063] The present application is a metal atmospheric corrosion loss prediction method considering the active surface area of the metal material, that is, a metal atmospheric corrosion loss prediction method considering time dynamics, rust layer corrosion inhibition and environmental differences based on the electrochemical polarization theory, which has the following advantages:

[0064] ①The present application establishes a correlation model of environmental factors, active surface area of metal material and time variable for describing the quantitative model method of the atmospheric corrosion rate of metal material as a whole;

[0065] ②The present application considers the physical relationship and mathematical statistical relationship between the active surface area of the metal material and the corrosion rate, and compared with the traditional modeling method, the prediction of the atmospheric corrosion of the metal material is more accurate and reasonable through the active surface area function and the connection function;

[0066] ③The present application selects corrosion weight loss as the basic physical parameter, the test method is simple, convenient for calculation, and the data processing algorithm has low complexity;

[0067] ④The prediction method is scientific and reasonable, has good processability, and has wide popularization and application value. BRIEF DESCRIPTION OF DRAWINGS

[0068] Figure 1 is the flow chart of the method of the present application.

[0069] Figure 2 is a schematic diagram of the fitting curve of the relative corrosion rate and the corrosion weight loss in the case.

[0070] Figure 3a and Figure 3b is a schematic diagram of the corrosion current of zinc metal under different environmental factors in the case.

[0071] Figure 4 is a schematic diagram of the environmental factor monitoring data in Beijing in the case.

[0072] Figure 5 is a schematic diagram of the long-term atmospheric corrosion loss prediction of zinc metal in Beijing in the case. DETAILED DESCRIPTION

[0073] The application will be further described in detail below with reference to the examples;

[0074] Metallic zinc is a widely used metal material, and its world production and consumption rank fourth. Atmospheric corrosion is a common form of corrosion of zinc. When zinc is in contact with dry air, a dense ZnO corrosion product film is rapidly formed on the surface. In the marine atmospheric environment rich in chloride ions, the main corrosion product of zinc is Zn5(OH)8Cl2·H2O. These corrosion products of zinc have a significant inhibitory effect on the atmospheric corrosion process of zinc. The corrosion resistance of zinc alloy is positively correlated with the relative content of Zn5(OH)8Cl2·H2O. In addition, the corrosion behavior of zinc is significantly related to the concentration of chloride ions, temperature and humidity, so the corrosion behavior of zinc in the marine atmospheric environment is selected as an example for illustration;

[0075] The application relates to a method for predicting atmospheric corrosion loss of a metal material considering the change of the active area of the metal, i.e. a method for predicting uniform atmospheric corrosion loss of a metal material in a variable environment considering the surface active area of the metal material, time dynamics, rust layer corrosion inhibition and environmental differences, as shown in the accompanying drawings. Figure 1 The method is realized through the following steps:

[0076] Step 1: Determining the indoor accelerated corrosion curve of the metal material

[0077] Pure zinc metal was selected as the research object in this case. The sample size for indoor accelerated corrosion test was 50 mm x 25 mm x 3 mm. The surface of the zinc metal sample was polished to 400#. After polishing, the zinc metal sample was cleaned, alcohol was dropped, and then dried in a drying oven for 2 days. The initial weight was measured. The accelerated corrosion environment was a high-low humidity alternating environment, and the test temperature was set to 30 degrees Celsius. The high-low humidity alternating cycle was 3 hours, of which 1 hour was 90% relative humidity and 2 hours was 60% relative humidity. To simulate the high salinity in the marine atmosphere, NaCl solution was applied to the surface of the zinc metal sample using a microsyringe before the experiment, and then evenly spread with a nylon rope, and then placed in a heating oven for drying, and finally placed in the corrosion test box for testing. The sample was taken out every 24 hours, and then salted and dried according to the above steps, and then placed in the test box for further corrosion test. The sampling period was set to 48, 96, 144, 240, and 336 hours. After sampling, the rust removal liquid was prepared to remove the corrosion products, and the sample surface was cleaned with distilled water and dried before weighing. The corrosion weight loss data of zinc in the simulated tropical marine atmosphere is shown in Table 1.

[0078] Table 1 Corrosion weight loss of zinc in simulated tropical marine atmosphere

[0079]

[0080] Step two: Establish the relationship model between active area and corrosion loss

[0081] According to formula (1), the corrosion rate of each time point of the zinc metal accelerated corrosion curve in Table 1 was calculated, and the results are shown in Table 2.

[0082] Table 2 Corrosion rate of zinc in simulated tropical marine atmosphere

[0083]

[0084] In this case, a power function model was used to represent the relationship between relative corrosion rate and corrosion weight loss, and good fitting results were obtained, as shown in Figure 2 The fitting result is shown in formula (13).

[0085]

[0086] According to formula (13), the corrosion rate under different corrosion loss is:

[0087] v(d) = v0- 0.4371 · v0· d 0.3437 (12)

[0088] Equation (14) is a model that uses corrosion rate to represent the relationship between the active area of the metal and the corrosion loss.

[0089] Step three: Measure the corrosion current under different environmental factors

[0090] To measure the corrosion current density of zinc metal under different environmental factors, laboratory simulation accelerated tests are needed. In this case, the laboratory accelerated environmental temperature is set to 285 K, 300 K, and 308 K, and the relative humidity is set to 53%, 84%, and 92%. Corrosion current data is measured continuously by atmospheric corrosion sensors. The test results are shown in Figure 3a and Figure 3b For the corrosion model of zinc metal in a sulfur dioxide environment, there is a lack of laboratory measured data, so the international standard ISO-9223-2012 is referenced, and η = 0.43, τ = 0.86 are set;

[0091] Step four: Build a connection function between corrosion current and environmental factors

[0092] This case mainly considers the effects of temperature, humidity, and sulfur dioxide on zinc metal corrosion in natural atmospheric environments. Without considering the interactive effects of the three environmental factors, a connection function model is established between the corrosion current of zinc metal and the three environmental factors.

[0093] Combining Equations (4) to (5), we get

[0094]

[0095] where λ is a constant obtained by combining the constant coefficients of the three connection function models.

[0096] Using the corrosion current data of zinc metal under different temperature and humidity, the connection function model parameters of the three environmental factors are fitted according to the least squares method. The estimation results of all model parameters are shown in Table 3;

[0097] Table 3: Estimation results of connection function parameters

[0098]

[0099] Step five: Use the Runge-Kutta algorithm to predict metal corrosion in field environments

[0100] The environmental data used in this case is the meteorological environmental data of Beijing, China. Temperature and humidity data come from the online database of the United States National Oceanic and Atmospheric Administration, and sulfur dioxide data come from the China Environmental Monitoring Center. Temperature, relative humidity, and sulfur dioxide concentration are recorded every three hours, and the average value of data from 2009 to 2018 is used. The environmental data is shown in Figure 4 .

[0101] According to formula (9), the initial value of zinc corrosion loss is expressed as:

[0102]

[0103] According to formula (12), the corrosion rate of zinc containing rust is:

[0104] v(t,d)=v0(t)-0.4371·v0(t)·d 0.3437 (15)

[0105] Since the corrosion rate of zinc metal in Beijing is given by formula (15), the long-term cumulative loss of zinc metal due to atmospheric corrosion in Beijing can be calculated using the Runge-Kutta method with formulas (9) to (10), such as... Figure 5 As shown.

[0106] The results show that the method of this invention can map the temporal dynamics of environmental factors onto the parameters of the connection function by analyzing the characteristics of the accelerated corrosion curve of metals, and further use the Runge-Kutta numerical integration algorithm to predict the atmospheric corrosion loss of shallow metals, thus achieving the expected goal.

[0107] In summary, this invention relates to a method for predicting atmospheric corrosion loss considering changes in the active area of ​​metals. Specifically, it is a method for predicting uniform atmospheric corrosion loss of metal materials under varying environmental conditions, considering the surface active area of ​​metal materials, temporal dynamics, rust layer corrosion inhibition, and environmental differences. It is a long-term prediction method for atmospheric corrosion loss of metals based on a comprehensive environmental corrosion model, a metal material surface active area model, and the Runge-Kutta algorithm. It comprehensively establishes a correlation model between environmental factors, the surface active area of ​​metal materials, and time variables, using environmental factor observation data with different time and geographical information, as well as the characteristics of accelerated metal corrosion curves, to quantitatively describe the atmospheric corrosion rate of metal materials. It maps the temporal dynamics of environmental factors to the parameters of the connection function, facilitating the quantification of environmental factors over time. Furthermore, it uses the Runge-Kutta numerical integration algorithm to predict shallow atmospheric corrosion loss of metals.

[0108] The specific steps of this method are as follows: 1. Measure the accelerated corrosion curve of indoor metal materials; 2. Measure the corrosion current under different environmental factors; 3. Establish a model of the relationship between active area and corrosion loss; 4. Construct a connection function between corrosion current and environmental factors; 5. Use the Runge-Kutta algorithm to predict metal corrosion in the outdoor environment.

[0109] This invention is applicable to the fields of corrosion prevention and maintenance of metallic materials that consider the physical and mathematical statistical relationships between various corrosion products, environmental factors and metal corrosion current density. It features simple testing methods, low model complexity, good data fitting effect, and low data processing algorithm complexity, and has broad application value.

Claims

1. A method for predicting atmospheric environmental corrosion loss considering the change of metal active area, which needs to be set as follows: Setting 1: When modeling the active area of the surface of a metal material, it is considered that the corrosion products produced in a similar corrosion environment have the same physicochemical properties and play a consistent corrosion inhibition role on the metal material; Setting 2: The coverage degree of the rust layer on the active area of the metal material is only related to the current rust layer accumulation and is independent of environmental factors; Setting 3: The influencing factors of atmospheric corrosion of the metal material are atmospheric temperature, atmospheric humidity, and sulfur dioxide concentration, and other environmental factors are ignored and simplified; Setting 4: The environmental factors affecting the atmospheric corrosion of the metal material are not considered to interact with each other, and it is considered that the effects of atmospheric temperature, atmospheric humidity, and sulfur dioxide concentration on the metal material are independent of each other; Based on the above settings, the method comprises the following steps: Step 1: Determining the accelerated corrosion curve of the metal material in the laboratory; Step 2: Establishing a model of the relationship between the active area and the corrosion loss; According to the different actual service environment of metal materials, different indoor accelerated corrosion tests are taken; when the test is carried out, the metal samples are taken out after corrosion time t1, t2,..., t n n is the total sampling number, the weight is weighed after removing the corrosion product, and then the corrosion weight loss d1, d2,..., d n of the metal is calculated according to the weight of the uncorroded sample, and the accelerated corrosion curve of the metal material is drawn; According to the accelerated corrosion curve of the metal material, the corrosion rate at each time point is estimated: Step 3: Measuring the corrosion current under different environmental factors wherein v i is the corrosion rate of the metal at time t i is the corrosion rate of the metal at time t i+1 is the corrosion weight loss of the metal at time t i+1 is the corrosion weight loss of the metal at time t Let the initial area of the metal material be S0, and due to the covering effect of the rust layer, the active area of the metal material at the ith time point is S i Then: Obviously, the active area S i has a value range of [0, S0], when the corrosion just occurs, S i = S0, with the continuous corrosion time, the value of S i continuously decreases and tends to 0; The calculated n active area S i Corrosion rate under the n corresponding to the metal material accelerated corrosion curve of n corrosion weight loss d, get n-1 corrosion rate ratio and corrosion loss Data pairs; observe the trend of the data pairs curve, select the appropriate function to describe The relationship between the two is obtained by least square fitting: In a laboratory environment, laboratory simulation corrosion tests are carried out on the metal material under study, without considering the mutual influence of various environmental factors, and the corrosion environment factors and levels are designed according to the type of test; Step 4: Building a connection function between corrosion current and environmental factors Based on the obtained corrosion current data measured under different environmental factors and different levels, a connection function between the corrosion current density of the metal material and the environmental factors is further built; different environmental factors have different effects on corrosion, so different corrosion models are selected; Step 5: Using the Runge-Kutta algorithm to predict the corrosion of the metal in the field environment In step five, before carrying out the field environment corrosion prediction, the environmental factor monitoring data of the field environment need to be collected as the input of the connection function model; After obtaining the field environment data, let ξ(·) be the product of all connection functions, and the rust layer coverage function and the connection function are converted into corrosion loss by integration: where v(d) represents the corrosion rate when the corrosion weight loss is d, f(d, t) is a function relationship between v(d) and the corrosion weight loss and the corrosion time, and the specific form is determined according to the trend of the corrosion data; Since the field environment data is discrete, the Runge-Kutta numerical integration method is used to calculate the corrosion loss; The initial value of the corrosion loss is expressed as: v(t)=d'=f(d,t)·ξ(·),d(t0)=0 (9) where d' represents the derivative of the corrosion weight loss with respect to the corrosion time. ​ 2. The method of predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1, characterized in that: In step one, for metal materials serving in marine atmospheric environment, choose salt spray test or dry-wet alternating cycle corrosion test, refer to GB / T 32065.10-2020 for specific steps; for metal materials serving in humid tropics, use constant temperature and humidity or variable temperature and humidity for wet heat test, refer to GB / T 2423.3-2016 for specific steps; for metal materials serving in industrial pollution areas, introduce corrosive gas medium into the temperature and humidity environment; for metal materials serving in seawater environment, use artificial simulation seawater immersion test, refer to GB / T 38269-2019 for specific steps.

3. The method of predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1, characterized in that: In step two, if there is no suitable function to describe the relationship between the corrosion weight loss and the surface active area of the metal material, the surface active area corresponding to different corrosion weight loss is obtained by interpolation method. In step two, if there is no suitable function to describe the relationship between the corrosion weight loss and the surface active area of the metal material, the surface active area corresponding to different corrosion weight loss is obtained by interpolation method.

4. The method of predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1, characterized in that: In step three, for salt spray test or dry-wet alternating cycle corrosion test simulating marine atmospheric environment, the selected environmental factors are salt spray concentration Cl, temperature T, humidity RH or alternating cycle period; for constant temperature and humidity or variable temperature and humidity wet heat test simulating humid tropical environment, the selected environmental factors are temperature T, humidity RH or variable temperature and humidity cycle period; for temperature and humidity environment with corrosive gas medium simulating industrial pollution areas, the selected environmental factors are temperature T, humidity RH and pollutant concentration; for artificial simulation seawater immersion test simulating seawater environment, the selected environmental factors are temperature T and salinity Cl.

5. The method for predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1 or 4, characterized in that: In step three, the data of each environmental factor should not deviate too much from the actual environment, so as not to change the corrosion mechanism. The concentration of sodium chloride for generating salt spray is controlled at 40-60 grams per liter, the environmental temperature is controlled at 30-80 degrees Celsius, and the humidity is controlled at 40%-100%.

6. The method of predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 5, characterized in that: In step three, after determining the test environmental factors, the number of levels of each environmental factor is more than three, i.e. each environmental factor is designed to have more than three values, and the initial corrosion current of the metal material without rust layer is measured by the atmospheric corrosion sensor; the atmospheric corrosion sensor is selected to be an electrochemical impedance atmospheric corrosion sensor; the specific measurement method is as follows: first, the electrochemical impedance at high frequency and low frequency is measured, and the difference between the two is calculated as the polarization resistance value R p of the metal material; then the electrochemical polarization curve of the metal is measured, and the sensitivity of the response of the cathode and anode current to the applied potential, i.e. the slope of the logarithm of the response of the cathode and anode current to the change of the potential, is calculated, and the Tafel cathode and anode slope β a and β c are calculated; finally, the corrosion current i corr is estimated according to the linear polarization method.

7. The method of predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1, characterized in that: In step four, for relative humidity, the selected accelerated corrosion model includes the following three: ξ(RH) = a - RH β (4) Where α and β are parameters representing the relationship between relative humidity and corrosion, and RH is relative humidity; The influence of temperature on metal material corrosion is described by Arrhenius model: Where δ and ε are parameters representing the relationship between temperature and corrosion, and T is Kelvin temperature; The influence of sulfur dioxide pollutants and chloride ions on metal material corrosion is described by power function model: ξ(S) = (1 + η-S) τ (6) wherein η and τ are parameters characterizing the relationship between the sulfur dioxide concentration and the corrosion effect, and κ is a parameter characterizing the relationship between the chloride ion concentration and the corrosion effect, S is the sulfur dioxide concentration and Cl is the chloride ion concentration.

8. The method of predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1, characterized in that: In step four, on the basis of the corrosion current data under different environmental factors obtained in step three, the parameters a, β, δ, ε, η, τ, and κ of each connection function are obtained by fitting the above model by the least square method. and κ.

9. The method of predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1, characterized in that: In step five, the external field atmospheric environment data is obtained from two channels, meteorological station monitoring data and public environmental database data; the public environmental database data currently includes World Ocean Database WOD, Global Ocean Observing Network ARGO, and World Climate Data Center WDCC, and each piece of data collected from the database includes the predicted external field environment atmospheric or seawater temperature, atmospheric humidity, sulfur dioxide pollutant concentration, chloride ion deposition rate, seawater salinity and time index.

10. The method for predicting atmospheric environmental corrosion loss considering the change of metal active area according to claim 1 or 9, characterized in that: In step five, the corrosion amount at time t is given by the following equation: where l is the time interval between two observations, let ml = f(d i ,t i ) and m2 = f(d i ,t i + l), d(t i+1 ) and d(t i ) represent the corrosion weight loss at t i+1 and t i respectively. i i i i i+1 i i+1 i m4 = f(d i · l · m3, t i + l); d(t i+1 ) and d(t i ) represent the corrosion weight loss at t i+1 and t i respectively.

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