Structural environment corrosion process modeling and predicting method considering damage acceleration

Abstract

The invention provides a structural environment corrosion process modeling and predicting method considering damage acceleration. The method comprises the following steps: 1, constructing a structural use risk model considering an environment damage effect; 2, quickly identifying the structure corrosion process considering the environmental damage effect; and 3, predicting the structural life considering the environmental damage acceleration effect. The method has the advantages that the type of the corrosion process can be quickly identified, so that the identification speed and accuracy of the structure corrosion process in a complex environment are effectively improved; model parameters can be accurately estimated, effective prediction of the service life of the structure can be realized, and reliable technical support is provided for safe use of the structure in a corrosion environment; the method is scientific, needed data are easy to obtain, application objects include but not limited to various mechanical structures in the corrosion environment, and the method has wide application and popularization value.

Description

Technical Field

[0001] The present invention provides a structural environmental corrosion process modeling and prediction method considering damage acceleration, that is, a structural corrosion process modeling and life prediction method based on an environmental damage acceleration effect risk model. It introduces the environmental damage acceleration effect into the structural use risk model for equipment structures that produce corrosion in complex environments, realizes rapid identification of corrosion processes based on corrosion-non-corrosion life test data, and establishes a structural life prediction method considering the environmental damage acceleration effect, providing theoretical and technical support for improving the safety and economy of structural service in complex environments such as the ocean. It is suitable for structural corrosion process identification and life prediction in corrosive environments with damage acceleration effects. Background Art

[0002] One of the main factors that cause the thickness reduction, strength reduction and even breakage of common equipment structures, such as surface corrosion of hull structures, corrosion of structural connection parts, and rust of conduit joints, which occur in complex environments such as the ocean. During service, corrosion phenomena caused by high temperature, high humidity, high salt spray, strong ultraviolet radiation, water molecule diffusion, sulfur oxide pollution and various environmental alternations will have varying degrees of impact on the service status and life of the structure. Environmental corrosion not only affects the safety and stability of the structure, but may also bring huge safety risks and cause significant economic losses. Therefore, studying the modeling and identification methods of the environmental corrosion process of the structure and predicting the safety of the structure under the influence of environmental corrosion are of great significance to helping the country develop and utilize extreme environmental resources.

[0003] However, there are still two deficiencies in the current domestic and foreign related research: on the one hand, the structural safety is judged by a single structural corrosion depth, and the structural safety is judged only based on whether the structural corrosion depth exceeds the structural tolerance threshold. This method ignores the acceleration effect of corrosion damage on the risk of structural use. On the other hand, corrosion test data such as crack expansion, coating loss, and corrosion area increase are usually difficult to measure accurately, resulting in high difficulty in testing the acceleration effect of corrosion damage and identifying the corrosion process.

[0004] To address the above problems, the present invention provides a method for identifying and predicting structural corrosion processes taking into account damage acceleration. The method introduces the environmental damage acceleration effect into the structural use risk model, realizes rapid identification of corrosion processes based on corrosion-non-corrosion life test data, and establishes a structural life prediction method taking into account the environmental damage acceleration effect. Summary of the invention

[0005] (1) The purpose of the present invention is to address the problems of structural corrosion process identification and life prediction in the presence of damage acceleration effect in a corrosive environment. For equipment structures that are corroded in a complex environment, the environmental damage acceleration effect is introduced into the structural use risk model, and the corrosion process is quickly identified based on corrosion-non-corrosion life test data. A structural life prediction method that takes into account the environmental damage acceleration effect is established, providing theoretical and technical support for improving the safety and economy of structural service in a complex environment.

[0006] (2) Technical solution:

[0007] The present invention provides a method for modeling and predicting a structural environmental corrosion process taking into account damage acceleration, which is implemented through the following three steps:

[0008] Step 1: Construct a structural use risk model considering environmental damage effects

[0009] With the accumulation of service age and the deepening of the effect of the service environment on the structure, the corrosion phenomenon caused by the alternating changes in environmental temperature, humidity, salt deposition, thermal radiation and various environments will have different degrees of impact on the service status and life of the structure, which is usually manifested as environmental corrosion accelerating the time of structural failure. Therefore, the present invention introduces the environmental damage acceleration effect into the structural use risk model, and proposes a structural use risk model considering the environmental damage effect to describe the use risk of the structure under environmental corrosion, as shown below:

[0010]

[0011] Where t is the service age of the structure, is the environmental corrosion loss of the structure at age t, h(t|l t ) is the service risk of the structure considering the accelerated environmental damage at age t, h 0 (t,ξ) is the baseline risk of the structure at age t without considering the acceleration of environmental damage, are all model parameters.

[0012] The modeling process includes the environmental corrosion loss l t According to existing literature research, the amount of environmental corrosion loss is The following three process descriptions can be used:

[0013] (1) Paik-Thayamballi process (power law type),

[0014] (2) Guedes Soares-Garbatov process (exponential type),

[0015] (3) Qin-Cui process (Weibull type),

[0016] Among them, l ∞ It means that after a structure has been subjected to long-term corrosion, the corrosion products will hinder the corrosion process, so the corrosion loss will gradually approach the limit value l ∞ ; C 1 ,C 2 ,C 3 are all model parameters.

[0017] Step 2: Rapidly identify the structural corrosion process considering environmental damage effects

[0018] During the development of the structure, a life test will be conducted to examine the law of its failure change over time and obtain failure data in a non-corrosive environment. In addition, in order to ensure that the structure does not fail due to corrosion during the manufacturing process, use, and storage process, corresponding corrosion tests will be formulated according to the environmental conditions in which the structure is located to clarify the failure data of the structure under accelerated environmental corrosion. Therefore, the present invention uses failure data in corrosive and non-corrosive environments to propose a method for quickly identifying the corrosion process.

[0019] By mathematically transforming equation (1), we can obtain:

[0020]

[0021] It can be found that the logarithmic difference between the service risk of the structure considering the acceleration of environmental damage and the baseline risk without considering the acceleration of environmental damage at the same service age is positively correlated with the amount of environmental corrosion loss. Therefore, the failure data in corrosive and non-corrosive environments can be directly used to identify the environmental corrosion process.

[0022] Since the failure data of the structure in the corrosive environment and the non-corrosive environment are known, the statistical period is marked as t 1 ,t 2 ,…,t n and t 01 ,t 02 ,…,t 0n , then the use risk h(t|l t ) is calculated as follows:

[0023]

[0024] Among them, Δr(t i ) indicates that at t i Δt after the cycle i The number of structures that fail within a certain time period; Δt i =t i+1 -t i N represents the failure time interval considering the acceleration of environmental damage;s (t i ) indicates that at t i The number of structures remaining without failure in the cycle.

[0025] Baseline risk without considering accelerated environmental damage h 0 (t,ξ) is calculated as follows:

[0026]

[0027] Among them, Δr(t 0i ) indicates that at t 0i Δt after the cycle 0i The number of structures that fail within a certain time period; Δt i =t 0i+1 -t 0i N represents the failure time interval without considering the acceleration of environmental damage; s (t 0i ) indicates that at t 0i The number of structures remaining without failure in the cycle.

[0028] Then, the following process can be followed to quickly identify the process to which the structure corrosion belongs:

[0029] 1. Based on the failure data, with the help of the data distribution fitting method in existing literature research, the survival function type S of the structure in a non-corrosive environment is obtained. 0 (t,ξ) and the estimated value of the parameter ξ;

[0030] 2. Set the period data t 1 ,t 2 ,…,t n Substitute the survival function S in a non-corrosive environment 0 (t,ξ), we get the structure at a given service age t 1 ,t 2 ,…,t n Benchmark risk value

[0031] 3. 0 (t i ,ξ) and equation (3) Substituting into equation (2), we get the log risk difference

[0032] 4. Log risk difference After the curve graph is made, trend fitting is performed with the three known corrosion processes. If the curve graph is a power law type, the Paik-Thayamballi process is selected; if the curve graph is an exponential type, the GuedesSoares-Garbatov process is selected; if the curve graph is a Weibull type, the Qin-Cui process is selected.

[0033] Step 3: Predicting the structural life considering the accelerated effect of environmental damage

[0034] The structural risk function and survival function considering the accelerated effect of environmental damage have the following relationship:

[0035]

[0036] By integrating both sides of equation (5), the structural survival function considering the accelerated effect of environmental damage can be obtained:

[0037]

[0038] By infinitely integrating equation (6), we can obtain the expected life of the structure considering the accelerated effect of environmental damage:

[0039]

[0040] Since equation (7) contains the parameter Therefore, before predicting the expected life of a structure taking into account the accelerated effect of environmental damage, all parameters need to be clearly defined. The estimated value of parameter ξ has been obtained in step 2. It is only necessary to estimate the parameter based on the failure data. The value of , so construct the likelihood function:

[0041]

[0042] Substitute the period data t obtained in step 2 1 ,t 2 ,…,t n , log risk difference data Benchmark Risk Model The log-likelihood function can be obtained By maximizing the value of You can get the parameters Estimated value:

[0043]

[0044] The parameters obtained from equation (9) Substituting the estimated value and the estimated value of parameter ξ obtained in step 2 into equation (7), the expected life of the structure considering the accelerated effect of environmental damage can be obtained, thus completing the structural life prediction considering the accelerated effect of environmental damage.

[0045] Through the above steps, the present invention realizes the construction of a structural use risk model considering environmental damage effects based on failure data obtained from life tests of structures in corrosive environments and non-corrosive environments, quickly identifies structural corrosion processes considering environmental damage effects, predicts structural life considering environmental damage acceleration effects, and solves the problem of how to scientifically identify corrosion processes and predict life for structures with damage acceleration effects.

[0046] (3) Advantages and effects:

[0047] 1. The present invention can quickly identify the type of corrosion process, thereby effectively improving the identification speed and accuracy of structural corrosion processes in complex environments;

[0048] 2. The present invention can accurately estimate model parameters, realize effective prediction of structural life, and provide reliable technical support for the safe use of structures in corrosive environments;

[0049] 3. The method described in the present invention is scientific, the required data is easy to obtain, and the application objects include but are not limited to various mechanical structures in corrosive environments, and it has broad promotion and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flow chart of the method of the present invention;

[0051] Figure 2 It is a proportional data curve diagram of the environmental corrosion loss of two hull structures;

[0052] Figure 3 These are the survivability curves of the two hull structures under accelerated environmental corrosion damage. DETAILED DESCRIPTION

[0053] The present invention will be further described below with reference to examples.

[0054] It is one of the main factors that cause the thickness reduction, strength reduction and even breakage of common equipment structures, such as surface corrosion of hull structures, corrosion of structural connection parts, and rust of conduit joints in complex environments such as the ocean. During service, corrosion caused by high temperature, high humidity, high salt spray, strong ultraviolet radiation, water molecule diffusion, sulfur oxide pollution and multiple environmental changes will have different degrees of impact on the service status and life of the structure.

[0055] When calculating the remaining life of a hull structure, it is necessary to consider the effect of corrosion on accelerated structural damage. It is generally believed that the thickness reduction of hull structural materials evolves over time, and this dynamic process can be characterized by a specific time-dependent model. However, the complexity and variability of the marine environment - including significant differences in dissolved oxygen, pH, chloride content and water conductivity between different sea areas - causes hull structures serving in different environments to follow different corrosion paths. And because indicators that characterize the degree of corrosion, such as crack expansion, coating loss, and increase in corrosion area, are difficult to measure accurately, it is difficult to test the accelerated effect of corrosion damage and identify the corrosion process.

[0056] Table 1 shows the failure data of two different structures on the hull in a corrosive environment and a non-corrosive environment, where the total number of each type of structure in each test is 50. It can be clearly seen from Table 1 that corrosion accelerates the time of structural failure, so environmental corrosion has a significant damage acceleration effect on the hull structure. The following will be based on the method of the present invention to model the corrosion process of the hull structure under environmental damage acceleration and predict the expected life.

[0057] Table 1 Failure data of two different hull structures in corrosive and non-corrosive environments

[0058]

[0059] The present invention provides a structural environmental corrosion process modeling and prediction method considering damage acceleration, that is, a structural corrosion process modeling and life prediction method based on an environmental damage acceleration effect risk model, see Figure 1 As shown, this method is implemented through the following three steps:

[0060] Step 1: Construct a structural use risk model considering environmental damage effects

[0061] The structural use risk model considering environmental damage effects is constructed as shown below, which serves as the basic model for subsequent analysis:

[0062]

[0063] The corrosion process is tentatively described by the following three processes:

[0064] (1) Paik-Thayamballi process (power law type),

[0065] (2) Guedes Soares-Garbatov process (exponential type),

[0066] (3) Qin-Cui process (Weibull type),

[0067] Step 2: Rapidly identify the structural corrosion process considering environmental damage effects

[0068] 1. Based on the failure data in Table 1, the survival function type of the structure in a non-corrosive environment is exponential S 0 (t,ξ)=exp(-ξt), and the estimated value of the parameter ξ is ξ 1 =0.10,ξ 2 =0.15;

[0069] 2. Substitute the cycle data in Table 1 into the survival function S in a non-corrosive environment 0 (t,ξ), and obtain the benchmark risk value

[0070] h 0 (t i ,ξ)=ξ;

[0071] 3. 0 (t i ,ξ) and equation (3) Substituting into equation (2), we get the log risk difference

[0072] 4. Log risk difference Made as Figure 2 As shown in the curve graph, the corrosion process is found to be the Paik-Thayamballi process through trend fitting.

[0073] Step 3: Predicting the structural life considering the accelerated effect of environmental damage

[0074] The periodic data t in Table 1 1 ,t 2 ,…,t n and the log risk difference data obtained in step 2 Benchmark risk model h under index type 0 Substituting (t,ξ)=ξ into equation (8), we can obtain the log-likelihood function The value of is maximized by numerical methods You can get the parameters The estimated value of is:

[0075]

[0076] Substituting the above data into equation (6) can obtain the structural survival function value considering the accelerated effect of environmental damage, such as Figure 3 As shown. By infinitely integrating equation (6) using the numerical integration method, the expected life of the two structures considering the accelerated effect of environmental damage can be obtained as ET 1 =6.37; ET 2 =4.49 cycles.

[0077] The results show that the present invention can construct a structural use risk model considering environmental damage effects based on failure data obtained from life tests of structures in corrosive environments and non-corrosive environments, quickly identify structural corrosion processes considering environmental damage effects, and predict structural life considering environmental damage acceleration effects. This solves the problem of how to scientifically identify corrosion processes and predict life for structures with damage acceleration effects, thereby achieving the intended purpose.

[0078] In summary, the present invention provides a structural environmental corrosion process modeling and prediction method considering damage acceleration, that is, a structural corrosion process modeling and life prediction method based on an environmental damage acceleration effect risk model. It introduces the environmental damage acceleration effect into the structural use risk model for equipment structures that produce corrosion in complex environments, realizes rapid identification of corrosion processes based on corrosion-non-corrosion life test data, and establishes a structural life prediction method considering the environmental damage acceleration effect, providing theoretical and technical support for improving the safety and economy of structural service in complex environments such as the ocean.

Claims

1. A method for modeling and predicting structural environmental corrosion processes considering damage acceleration, characterized in that: Here are the steps: Step 1: Construct a structural use risk model considering environmental damage effects The environmental damage acceleration effect is introduced into the structural use risk model to describe the use risk of the structure under environmental corrosion, as shown below: h(t|l t )=h0(t,ξ)exp(λl t )=h0(t,ξ)exp(λl(t,θ)) (1) Where t is the service age of the structure, l t = l(t,θ) is the environmental corrosion loss of the structure at age t, h(t|l t ) is the service risk of the structure at age t with consideration of accelerated environmental damage, h0(t,ξ) is the baseline risk of the structure at age t without consideration of accelerated environmental damage, ξ,λ,θ are all model parameters; Step 2: Rapidly identify the structural corrosion process considering environmental damage effects Using failure data in corrosive and non-corrosive environments, the corrosion process can be quickly identified as: By mathematically transforming equation (1), we can obtain: Step 3: Predicting the structural life considering the accelerated effect of environmental damage The structural risk function and survival function of the accelerated effect of environmental damage have the following relationship:

2. A structural environmental corrosion process modeling and prediction method considering damage acceleration according to claim 1, characterized in that: In step 1, the modeling process includes the environmental corrosion loss l t , the environmental corrosion loss l(t,θ) is described by the following three processes: (1) Paik-Thayamballi process, i.e. power law type, θ=(C1,C2,C3); (2) Guedes Soares-Garbatov process, i.e. exponential type, θ=(l ∞ ,C1,C2); (3) Qin-Cui process, also known as Weibull process, θ=(l ∞ ,C1,C2,C3); Among them, l ∞ It means that after a structure has been subjected to long-term corrosion, the corrosion products will hinder the corrosion process, so the corrosion loss will gradually approach the limit value l ∞ ; C1, C2, C3 are all model parameters.

3. The method for modeling and predicting structural environmental corrosion process considering damage acceleration according to claim 1, characterized in that: In step 2, since the failure data of the structure in the corrosive environment and the non-corrosive environment are known, the statistical periods are marked as t1, t2, …, t n and t 01 ,t 02 ,…,t 0n , considering the use risk of accelerated environmental damage h(t|l t ) is calculated as follows: Among them, Δr(t i ) indicates that at t i Δt after the cycle i The number of structures that fail within a certain time period; Δt i =t i+1 -t i Indicates the failure time interval; N s (t i ) indicates that at t i The number of structures remaining without failure in the cycle; The baseline risk h0(t,ξ) without considering the acceleration of environmental damage is calculated as follows:

4. A structural environmental corrosion process modeling and prediction method considering damage acceleration according to claim 1 or 3, characterized in that: In step 2, follow these steps to quickly identify structural corrosion: 2.1 Based on the failure data, the estimated value of the survival function type S0(t,ξ) and parameter ξ of the structure in a non-corrosive environment is obtained by using the data distribution fitting method; 2.2 The periodic data t1, t2, ..., t n Substituting the survival function S0(t,ξ) in a non-corrosive environment, we can obtain the survival rate of the structure at a given service age t1, t2,…, t n Benchmark risk value 2.3 h(t i |l ti ) into equation (2), we get the log risk difference λl(t i ,θ); 2.4 The logarithmic risk difference λl(t i ,θ) is made into a curve graph and then trend fitting is performed with the three known corrosion processes. If the curve graph is a power law type, the Paik-Thayamballi process is selected; if the curve graph is an exponential type, the Guedes Soares-Garbatov process is selected; if the curve graph is a Weibull type, the Qin-Cui process is selected.

5. The method for modeling and predicting structural environmental corrosion process considering damage acceleration according to claim 1, characterized in that: In step 3, the two sides of equation (3) are integrated to obtain the structural survival function considering the accelerated effect of environmental damage: Then infinitely integrate equation (6) to obtain the expected life of the structure considering the accelerated effect of environmental damage: Before predicting the expected life of a structure taking into account the accelerated effect of environmental damage, it is necessary to determine the estimated values ​​of all parameters ξ, λ, and θ.

6. A structural environmental corrosion process modeling and prediction method considering damage acceleration according to claim 5, characterized in that: The estimated value of parameter ξ has been obtained in step 2, and the values ​​of parameters λ and θ need to construct the likelihood function: Substitute the period data t1, t2, ..., t n , logarithmic risk difference data λl(t i ,θ), Benchmark risk model Get the value of the log-likelihood function ln L(λ,θ), and get the estimated values ​​of the parameters λ and θ by maximizing ln L(λ,θ): Substituting the estimated values ​​of parameters λ, θ and ξ into equation (7), we can obtain the expected life of the structure considering the accelerated effect of environmental damage, and complete the prediction of the structural life considering the accelerated effect of environmental damage.

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