Method and system for evaluating performance of concrete structure in marine environment

Abstract

The invention relates to the technical field of civil engineering evaluation, in particular to a concrete structure performance evaluation method and system in a marine environment, and the method comprises the steps: inputting engineering information and environmental parameters; determining analysis components and section parameters; establishing a probability model of the key parameters; setting an analysis age limit and a time step length; carrying out chloride ion diffusion and steel bar corrosion analysis; carrying out material performance time-varying degradation analysis; calculating the time-varying resistance of the component; establishing a structure resistance time-varying probability model; and evaluating long-term performance of the structure. By integrating chloride ion erosion, steel bar corrosion, material degradation, member resistance time variation and reliability analysis, a full-chain evaluation system from environment input to safety grade division is formed, and the evolution law of the bearing capacity of the structure in the whole life cycle can be dynamically reflected; and a quantitative basis is provided for durability design, service state evaluation and maintenance decision of reinforced concrete structures such as long-piled wharfs in a marine environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of civil engineering evaluation technology, in particular to a method and system for evaluating the performance of a concrete structure in a marine environment. BACKGROUND

[0002] With the large-scale construction of coastal ports and offshore projects, a large number of reinforced concrete high-pile wharfs and other structures are in strong chloride environments such as seawater splashing areas and tidal areas, which are prone to chloride ion erosion-induced steel corrosion and concrete strength degradation, leading to continuous degradation of the load-carrying capacity and durability of the components, which has become an important problem restricting the safe service of water transportation infrastructure. Chloride ion erosion in a chloride environment is affected by various uncertain factors such as material properties, construction details, environmental effects, and construction quality, and is essentially a random process. Accordingly, the long-term performance of concrete structures also has significant probabilistic characteristics. Currently, engineering design is mostly based on one-time structural checking according to specifications, using deterministic safety factors to control safety reserves, which cannot reflect the randomness of environmental effects, material properties, and geometric parameters, and the time-varying law of component resistance. There is a lack of unified and quantitative long-term performance evaluation methods for state evaluation, life prediction, and maintenance decision-making during the operation period, and there is an urgent need to establish a full-life performance evaluation system for concrete structures in marine environments. SUMMARY

[0003] The present application overcomes the shortcomings of the prior art and provides a method and system for evaluating the performance of a concrete structure in a marine environment.

[0004] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows: The present application discloses a method for evaluating the performance of a concrete structure in a marine environment, comprising the following steps: S1, inputting engineering information and environmental conditions: obtaining the basic information of the engineering to be analyzed and the service environmental conditions; the engineering information includes structure type, component type, cross-section size, reinforcement parameter, and material strength grade; the environmental conditions include seawater chloride concentration, environmental section, temperature, and humidity; S2, determining the analysis structure and cross-section parameters: according to the engineering layout and stress characteristics, selecting the structure components that need to be evaluated, and determining the calculation diagram, cross-section geometric parameters, steel bar arrangement, and protective layer thickness of each component; S3, establishing random variables and probability models: for the uncertain parameters of chloride ion diffusion coefficient, surface chloride ion concentration, critical chloride ion concentration, material strength, and component size, establish the corresponding random variable and probability distribution model as the input for subsequent time-varying analysis and Monte Carlo simulation; S4, setting analysis life and time step: setting analysis life according to structure design service life, and discretizing analysis life into several time steps to obtain performance evolution process of component in different time sections in whole life cycle; S5, chloride ion diffusion and steel bar corrosion analysis: performing chloride ion diffusion and steel bar corrosion analysis in set time range to obtain corrosion parameters, specifically including: obtaining steel bar rusting time, corrosion rate, corrosion rate and protective layer cracking time results of each time section by using steel bar initial corrosion time prediction model, steel bar corrosion rate time-varying model, corrosion steel bar corrosion rate prediction model and concrete cracking time prediction model; S6, time-varying degradation analysis of material performance: based on the corrosion parameters, performing time-varying degradation analysis of material performance to obtain degraded material performance parameters, specifically including: obtaining degradation values of steel bar and concrete material performance and steel bar and concrete interface bonding performance in each time section by using corrosion steel bar strength degradation model, corrosion steel bar ductility degradation model, concrete strength degradation model and steel bar concrete bonding coefficient model; S7, calculating time-varying resistance of component: in each analysis time section, substituting degraded material performance parameters into component bearing capacity calculation model to obtain resistance values of structure component changing with time, realizing calculation of time-varying resistance of component, and establishing time-varying resistance calculation model; S8, establishing time-varying resistance probability model of component: using random variables established in step S3 and time-varying resistance calculation model obtained in step S7, adopting Monte Carlo simulation probability analysis method to obtain resistance probability distribution of component in each time section, and establishing time-varying resistance probability model of component; S9, evaluating long-term performance of structure: according to the time-varying resistance probability model of component, comparing component resistance with corresponding load effect or target reliability index to evaluate safety level and performance of structure in each time section in analysis life, and obtaining structure performance evaluation results.

[0005] Preferably, in the S5, it further includes establishing chloride ion diffusion model: , In the formula, C (t, x) represents chloride ion concentration at x of concrete surface at t, unit: kg / m 3 ; t represents time, unit: year; x represents depth from concrete surface, unit: mm; C (0, x) represents chloride ion concentration of concrete surface, unit: kg / m 3 ; erfc represents error function; β represents environmental influence coefficient; α represents chloride ion diffusion coefficient detection method correction coefficient; γ represents concrete curing time correction coefficient; is the reference time for chloride diffusion coefficient, i.e. 28 days; is the chloride diffusion coefficient at the reference time; is the aging factor.

[0006] Preferably, according to the determined chloride diffusion model, when the chloride concentration on the surface of the steel bar first reaches the critical concentration, it is considered that the steel bar begins to rust, i.e. the initial corrosion time is reached t corr , and considering the uncertainty parameters in the model, the prediction model of the initial corrosion time of the steel bar is obtained: , In the formula, X1 is the uncertainty parameter of the corrosion time; C0 is the chloride concentration on the surface of the concrete; C cr is the critical chloride concentration; D is the chloride diffusion coefficient at the actual time; is the thickness of the concrete protective layer, in mm; is the sensitivity coefficient of the chloride concentration with the water-cement ratio; is the reference value of the chloride concentration on the surface of the concrete; is the water-cement ratio of the concrete; First, the corrosion current density of the steel bar is obtained i corr , and then the corrosion rate of the steel bar, i.e. the corrosion development rate, is calculated by means of the corrosion current density i corr , which is characterized by the corrosion current density i corr , then the time-varying model of the corrosion rate of the steel bar is expressed as: , In the formula, is the corrosion current density at the corrosion initiation time, in ; is the water-cement ratio ; t p represents the time experienced since the steel bar began to rust, in years; represents the thickness of the concrete protective layer, in mm; λ represents the annual corrosion rate, in mm / year; represents the corrosion influence coefficient; represents the corrosion current density, in .

[0007] Preferably, if the corrosion form of the steel bar is uniform corrosion, the corrosion of the steel bar will cause its cross-sectional diameter and mechanical properties to gradually degrade over time, and it is assumed that the steel bar begins to rust from the time t corr , then the prediction model of the corrosion rate of the corroded steel bar at any time t is expressed as: , In the formula, is the diameter of the remaining steel bar after rusting, in mm; is the original diameter of the steel bar, in mm; is the rusting rate of the steel bar, in mm / year; is the initial rusting time of the steel bar, in years; is the rusting rate of the steel bar, in %; The time when the rusting amount of the steel bar reaches the critical rusting amount is defined as the time when the initial cracking of the concrete protective layer occurs, and the concrete cracking time prediction model is expressed as: , In the formula, represents t is the rusting rate of the steel bar at time t, in mm / year; is the concrete cracking time, in years; is the initial rusting time of the steel bar, in years; is the critical rusting depth of the steel bar, in mm; is the design value of the concrete protective layer thickness, in mm; is the original diameter of the steel bar, in mm; is the standard value of the concrete compressive strength, in MPa.

[0008] Preferably, the strength degradation model of the rusted steel bar is expressed as: , In the formula, is t is the yield strength of the steel bar at time t, in MPa; is the initial yield strength of the steel bar, in MPa; is the area loss of the steel bar caused by rusting at time t, in %; t The ductility degradation model of the rusted steel bar is expressed as: , In the formula, is the initial ultimate strain of the steel bar; is the strain corresponding to the initial yield of the steel bar; is the ductility index of the steel bar at time t; t The concrete strength degradation model is expressed as: , In the formula, is the constraint coefficient; ​​This represents the peak compressive stress in ordinary concrete, expressed in MPa. The peak compressive stress in confined concrete is expressed in MPa. Limited lateral restraint for confining concrete, measured in MPa; The stress is the yield stress of the stirrup, expressed in MPa. It is the lateral effective constraint coefficient, which is the ratio of the effective core concrete area to the total core concrete area. This represents the cross-sectional area of ​​the stirrups after corrosion, in mm². 2 ; The spacing of the stirrups is in mm; d The effective width of the cross section, i.e., the cross section width of the core concrete area, is expressed in mm. To constrain the peak strain of concrete; The bond coefficient model for reinforced concrete is expressed as follows: , In the formula, These are the bonding coefficients of the protective layer before and after cracking, respectively. , where is the cross-sectional loss rate of the reinforcing steel, in units of %; and e is the base of the natural logarithm.

[0009] Preferably, for reinforced concrete slabs and beams, the stress mode is bending, and the flexural capacity of the cross section is used as the characterization index of the member's resistance. The structural resistance is calculated according to the following formula: , In the formula, Indicates the bending capacity of a component; Indicates the axial compressive strength of concrete; b Indicates the width of the component section; x Indicates the height of the pressure zone; Indicates the effective height of the component section; Indicates the yield strength of the steel reinforcement in the compression zone; Indicates the cross-sectional area of ​​the compressed reinforcing steel; This indicates the distance from the point of application of the resultant force on the compressed steel reinforcement to the edge of the member's cross-section; Indicates the bond coefficient between steel reinforcement and concrete; Indicates the strength of the reinforcement in the tension zone; Indicates the cross-sectional area of ​​the tensile reinforcement; To characterize the time-varying nature of the probability distribution of component resistance, we define the time-varying coefficient of the mean resistance and the time-varying coefficient of the standard deviation of the component resistance. The time-varying resistance calculation model is then expressed as: , In the formula, for t The mean time-varying coefficient of the component resistance over a year; For t the standard deviation of the member resistance at the year; For t the mean of the member resistance at the year; For t the standard deviation of the member resistance at the year; For the standard deviation of the member initial resistance.

[0010] Preferably, the reliability index β is used to characterize the structural reliability, and the calculation formula can be expressed as: , In the formula, is the mean of the structural resistance; is the mean of the structural load; is the standard deviation of the structural resistance; is the standard deviation of the structural load; is the mean of the safety margin; is the standard deviation of the safety margin.

[0011] The second aspect of the present application discloses a concrete structure performance evaluation system in a marine environment, the concrete structure performance evaluation system comprises a memory and a processor, the memory stores a concrete structure performance evaluation method program, when the concrete structure performance evaluation method program is executed by the processor, the steps of any one of the concrete structure performance evaluation methods are realized.

[0012] The present application solves the technical defects in the background art, and has the following beneficial effects: the present application constructs a whole-process evaluation chain from engineering information input, chloride ion diffusion and steel bar corrosion analysis, material performance time-varying degradation analysis, member time-varying resistance calculation to reliability index determination, reflecting the evolution law of the bearing capacity of the structure in the whole service life. At the same time, by introducing the reliability index and its grading threshold, a dynamic evaluation method of A-D level safety level suitable for water transportation infrastructure such as high-pile wharf is established, which can give the safety level and critical time of the member and structure at different service life, thereby providing quantitative basis for durability design, structure state evaluation and maintenance and reinforcement decision, effectively serving the design and operation management of infrastructure such as high-pile wharf of coastal port, helping engineering and technical personnel accurately master the performance degradation state of the member in the service period, and scientifically and reasonably formulating the maintenance and reinforcement scheme, so as to reduce unnecessary maintenance investment and improve the durability and service life of the structure under the premise of ensuring the safety of the structure. BRIEF DESCRIPTION OF DRAWINGS

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained from these drawings without creative effort.

[0014] Figure 1 Flowchart of concrete structure performance evaluation method; Figure 2 A diagram illustrating the stages of steel corrosion development in reinforced concrete structures in a marine environment. Figure 3 This is a time-varying law diagram of the longitudinal beam's resistance; Figure 4 This is a time-varying reliability index diagram for components. Detailed Implementation

[0015] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0016] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0017] like Figure 1 As shown, the first aspect of this invention discloses a method for evaluating the performance of concrete structures in a marine environment, comprising the following steps: S1, Engineering Information and Environmental Conditions Input: Obtain basic information and service environment conditions of the project to be analyzed; It should be noted that, by reviewing design drawings, construction records, and conducting on-site surveys, key basic information of the project to be analyzed is systematically acquired and input. This project information specifically includes, but is not limited to, the structural form, the types of components to be evaluated, the precise cross-sectional dimensions of each component, detailed reinforcement parameters, and material strength grades. Simultaneously, by using environmental monitoring data, hydrological and meteorological data, or standard data, the service environment conditions of the structure are determined, specifically including: seawater chloride concentration, environmental zoning at the structural location, annual average temperature, humidity, and other climatic parameters. All the information collected in this step constitutes the statistical basis for all deterministic initial parameters and probabilistic variables in the subsequent chloride ion transport model, material degradation model, and component resistance calculations, ensuring that the evaluation model can accurately reflect the performance evolution starting point of a specific engineering entity under specific marine environmental conditions.

[0018] S2, Determine the analysis structure and section parameters: Based on the project layout and stress characteristics, select the structural components that need to be evaluated for performance, and determine the calculation diagram and section geometry parameters, reinforcement layout and protective layer thickness of each component; It should be noted that, based on the overall engineering layout and structural form obtained in step S1, key structural components requiring performance evaluation are selected, such as components that are subjected to harsh chloride environments like splash zones and tidal zones and bear major loads, such as longitudinal beams, transverse beams, panels, or pile foundations in high-pile wharves. After selecting the components, the calculation diagrams for each component are determined. For example, beams are simplified into simply supported beams or continuous beam models, and slabs are simplified into one-way slabs or two-way slab models. This simplification must reflect their actual boundary conditions and stress characteristics. On this basis, the cross-sectional geometric parameters of the components are accurately determined, including cross-sectional width, height, effective height, area, and moment of inertia. At the same time, the reinforcement layout is determined in detail, including the type, diameter, number, spacing, and location of longitudinal reinforcing bars and stirrups, as well as the design or measured values ​​of the concrete cover thickness. The determination of these specific parameters provides deterministic input for the chloride ion transport depth calculation in step S5, the material property degradation calculation in step S6, and the component resistance calculation in step S7, ensuring that the entire time-varying reliability assessment is based on an accurate physical model of the components.

[0019] S3, Establish random variables and probability models: For the uncertain parameters of chloride ion diffusion coefficient, surface chloride ion concentration, critical chloride ion concentration, material strength, and component size, establish corresponding random variables and probability distribution models as inputs for subsequent time-varying analysis and Monte Carlo simulation; S4, Set the analysis period and time step: Set the analysis period according to the structural design service life, and discretize the analysis period into several time steps to obtain the performance evolution process of the component at different time sections during the whole life. S5, Chloride ion diffusion and steel corrosion analysis: Chloride ion diffusion and steel corrosion analysis are performed within the set time range to obtain corrosion parameters. Specifically, this includes: using the steel initial corrosion time prediction model, the steel corrosion rate time-varying model, the steel corrosion rate prediction model, and the concrete cracking time prediction model to obtain the steel rust initiation time, corrosion rate, corrosion rate, and protective layer cracking time results for each time section. S6, Time-varying degradation analysis of material properties: Based on the corrosion parameters, time-varying degradation analysis of material properties is performed to obtain the degraded material property parameters. Specifically, this includes: using the corrosion steel strength degradation model, corrosion steel ductility degradation model, concrete strength degradation model and reinforced concrete bond coefficient model to obtain the degradation values ​​of steel and concrete material properties and the bond performance of steel and concrete interface at each time section. S7, Calculate the time-varying resistance of the component: At each analysis time section, substitute the degraded material property parameters into the component bearing capacity calculation model to obtain the resistance value of the structural component as time changes, realize the calculation of the time-varying resistance of the component, and establish the time-varying resistance calculation model; S8. Establish a time-varying resistance probability model for the component: Using the random variables established in step S3 and the time-varying resistance calculation model obtained in step S7, the Monte Carlo simulation probability analysis method is used to obtain the resistance probability distribution of the component at each time section and establish a time-varying resistance probability model for the component. S9, Evaluate the long-term performance of the structure: Based on the time-varying resistance probability model of the components, compare the component resistance with the corresponding load effects or target reliability index, evaluate the safety level and performance of the structure at each time section within the analysis period, and obtain the structural performance evaluation results.

[0020] To achieve the above process, the concrete structure deterioration model used in step S5 "chloride ion diffusion and steel corrosion analysis" and step S6 "time-varying degradation analysis of material properties" is as follows: In this embodiment, chloride ion diffusion is described using Fick's second law, treating concrete as a semi-infinite, isotropic medium and assuming that chloride ions do not bind to the solid phase. In reality, during service, hydration products fill the pores of concrete, leading to a decrease in porosity; therefore, the chloride ion diffusion coefficient decays over time. This method uses the Duracrate model to correct the diffusion coefficient, considering environmental factors, experimental methods, curing, and aging effects, thus establishing a chloride ion diffusion model: , In the formula, This represents the chloride ion concentration at a distance x from the concrete surface at time t, in kg / m³. 3 ; t represents time, in years; x represents the depth from the concrete surface, in mm; This indicates the chloride ion concentration on the concrete surface, expressed in kg / m³. 3 ; It is the error function; This is the environmental impact coefficient; This is a correction factor for the chloride ion diffusion coefficient detection method; This is a correction factor for concrete curing time; The reference time for the chloride ion diffusion coefficient is 28 days. The chloride ion diffusion coefficient is the reference time. It is an aging factor.

[0021] It should be noted that in marine chloride environments, reinforced concrete structures are exposed to chloride-containing seawater and air for extended periods. Chloride ions gradually migrate into the concrete and accumulate on the surface of the reinforcing steel. When the chloride ion concentration exceeds a critical value, the passivation film is destroyed, triggering electrochemical corrosion of the steel. The onset time and development rate of steel corrosion are closely related to the integrity of the passivation film, the pore structure of the concrete, and the chloride ion concentration; therefore, the corrosion process exhibits phased characteristics. During the structural lifespan (0-...),... t s Internally, the evolution of steel reinforcement corrosion can be characterized by two key time points: the initial corrosion time of the steel reinforcement and the cracking time of the concrete cover. t cr Therefore, the steel reinforcement corrosion process can be divided into three typical stages: the corrosion induction period from the start of the structure's service life; the corrosion induction period from... t corr to t cr The rust expansion period; t > t cr The subsequent corrosion development period. Significant differences exist in the corrosion rate of reinforcing bars at different stages, and their time history can be illustrated as follows: Figure 2 As shown, this is used to guide the selection of corrosion models and parameter calculations for subsequent time periods.

[0022] Based on the established chloride ion diffusion model, the steel bar is considered to have begun to corrode when the chloride ion concentration on its surface first reaches a critical concentration, i.e., the initial corrosion time has been reached. t corr After considering the uncertain parameters in the model, and given the linear relationship between the chloride ion concentration on the concrete surface and the water-cement ratio in actual marine engineering, the following prediction model for the initial corrosion time of reinforcing steel is obtained: , In the formula, X1 is the uncertainty parameter of corrosion time; C0 is the chloride ion concentration on the concrete surface; C cr denoted as the critical chloride ion concentration; D is the chloride ion diffusion coefficient at the actual moment. This refers to the thickness of the concrete protective layer, in mm. This is the sensitivity coefficient of chloride ion concentration to changes in water-cement ratio; This serves as the baseline value for chloride ion concentration on the concrete surface. This refers to the water-cement ratio of concrete.

[0023] The corrosion rate of reinforcing steel refers to the equivalent depth of corrosion penetration into the cross-section of the reinforcing steel per unit time. It is determined by first measuring the corrosion current density of the reinforcing steel using electrochemical testing methods. i corr Then by i corrThe corrosion rate of reinforcing steel bars, i.e., the corrosion development rate, is calculated using current density. i corr By characterizing it, a time-varying model of steel corrosion rate is obtained: , In the formula, The corrosion current density at the moment of corrosion initiation, in units of ; Water-cement ratio; t p This indicates the time elapsed since the steel bars began to corrode, expressed in years. This indicates the thickness of the concrete cover, in mm. λ This indicates the annual corrosion rate, expressed in mm / year. Indicates the corrosion influence coefficient; This represents the erosion current density, in units of... .

[0024] If the corrosion of the reinforcing steel is uniform, then the corrosion will cause its cross-sectional diameter and mechanical properties to gradually degrade over time. Assuming the steel's self-degradation... t corr If corrosion begins at any given moment, then at any given moment... t The prediction model for the corrosion rate of corroded steel bars is expressed as follows: , In the formula, The diameter of the remaining steel bar after corrosion is shown in mm. This refers to the original diameter of the reinforcing bar, in mm. The rate of steel corrosion is expressed in mm / year. The initial corrosion time of the reinforcing steel is expressed in years. The percentage is the steel reinforcement corrosion rate, expressed as a percentage (%).

[0025] If the moment when the steel reinforcement corrosion reaches the critical corrosion level is defined as the time when the concrete cover begins to crack, then the concrete cracking time prediction model is expressed as follows: , In the formula, express t The rate of steel corrosion at any given time, expressed in mm / year; Indicates the time of concrete cracking, in years; The initial corrosion time of the reinforcing steel is expressed in years. This indicates the critical corrosion depth of the reinforcing steel, in mm. This indicates the design value for the thickness of the concrete cover, in mm. This indicates the original diameter of the reinforcing bar, in mm. This represents the standard value of concrete compressive strength, in MPa.

[0026] The impact of steel corrosion on the mechanical properties of steel bars is mainly reflected in two aspects: strength and ductility. The strength degradation model of corroded steel bars is expressed as follows: , In the formula, for t The yield strength of the steel reinforcement at any given time, expressed in MPa; This represents the initial yield strength of the steel reinforcement, in MPa. for t Area loss caused by steel reinforcement corrosion, expressed in % (%) The ratio of the ultimate strain to the yield strain of the steel reinforcement is used. As an index of steel reinforcement ductility, the ductility degradation model of corroded steel reinforcement is expressed as follows: , In the formula, This represents the initial ultimate strain of the reinforcing steel. This represents the strain corresponding to the initial yield of the steel reinforcement. for t The ductility index of steel reinforcement at any given time; The concrete strength degradation model is expressed as follows: , In the formula, These are constraint coefficients; This represents the peak compressive stress in ordinary concrete, expressed in MPa. The peak compressive stress in confined concrete is expressed in MPa. Limited lateral restraint for confining concrete, measured in MPa; The stress is the yield stress of the stirrup, expressed in MPa. It is the lateral effective constraint coefficient, which is the ratio of the effective core concrete area to the total core concrete area. This represents the cross-sectional area of ​​the stirrups after corrosion, in mm². 2 ; The spacing of the stirrups is in mm; d The effective width of the cross section, i.e., the cross section width of the core concrete area, is expressed in mm. To constrain the peak strain of concrete.

[0027] The bond strength between steel reinforcement and concrete is mainly provided by interfacial friction and mechanical interlocking. The bond coefficient model for reinforced concrete is expressed as follows: , In the formula, These are the bonding coefficients of the protective layer before and after cracking, respectively. , where is the cross-sectional loss rate of the reinforcing steel, in units of %; and e is the base of the natural logarithm.

[0028] For reinforced concrete slabs and beams, the stress mode is bending. The flexural capacity of the cross section is used as the characterization index of the member's resistance. The structural resistance is calculated by the following formula: , In the formula, Indicates the bending capacity of a component; Indicates the axial compressive strength of concrete; b Indicates the width of the component section; x Indicates the height of the pressure zone; Indicates the effective height of the component section; Indicates the yield strength of the steel reinforcement in the compression zone; Indicates the cross-sectional area of ​​the compressed reinforcing steel; This indicates the distance from the point of application of the resultant force on the compressed steel reinforcement to the edge of the member's cross-section; Indicates the bond coefficient between steel reinforcement and concrete; Indicates the strength of the reinforcement in the tension zone; This indicates the cross-sectional area of ​​the tensile reinforcement.

[0029] Based on the above structural resistance formula, the resistance values ​​of each component sample at the end of each time period are calculated. To characterize the time-varying nature of the component resistance probability distribution, the time-varying coefficients of the component resistance mean and standard deviation are defined. The time-varying resistance calculation model is then expressed as: , In the formula, for t The mean time-varying coefficient of the component resistance over a year; for t The time-varying coefficient of the standard deviation of the component resistance over years; for t The average resistance of components over a year; for t Standard deviation of component resistance over years; This represents the average initial resistance of the component. This represents the standard deviation of the initial resistance of the component.

[0030] After establishing a time-varying probabilistic model of structural resistance, reliability indices are used to further conduct quantitative reliability analysis of the structure. β To characterize structural reliability, the calculation formula can be expressed as: , In the formula, This represents the average structural resistance. This represents the average structural load. The standard deviation of structural resistance; The standard deviation of structural loads; The average of the safety margin; The standard deviation is the safety margin.

[0031] It should be noted that loads include permanent loads and variable loads. The standard values ​​of these loads can be determined with reference to relevant standards such as the "Code for Design of Port Engineering Loads" and the "Code for Design of Building Structures". For actual engineering projects, permanent loads generally follow a normal distribution, while variable loads generally follow an extreme value type I distribution. By combining the actual load conditions of the project, the corresponding load mean and standard deviation can be obtained.

[0032] Furthermore, the safety levels of components and structures are classified and their evolution is assessed using the reliability index values ​​of components at various time sections, specifically including: Safety level indicators were determined, and structural safety levels were divided into four levels, among which safety level indicators... β A Based on the provisions regarding target reliability indicators in reliability standards such as the "Unified Standard for Reliability of Port Engineering Structures," and considering the safety level of the proposed project, the corresponding target reliability indicators are selected as the classification indicators for Level A safety. β A ; given the limit state function Given the probability distribution types and statistical parameters of resistance and load, the limit state functions are transformed by introducing a reduction factor into the resistance term. Where g is the limit state function; R is the resistance (bearing capacity) of the structure or component; and S is the load effect acting on the structure or component. This is the modified limit state function used to classify safety level B; Here are the modified limit state functions used to classify safety level C. The reliability indices corresponding to the two limit state functions are calculated and denoted as follows: β B Used as a dividing line between grades B and C. β C The structural reliability level classification and judgment criteria are shown in Table 1, which serves as the dividing line between C and D levels.

[0033] Table 1. Principles and Evaluation Standards for Structural Safety Level Classification

[0034] Long-term structural performance assessment utilizes component reliability indices. β With grading indicators β A , β B , β CThe comparative relationship enables long-term performance evaluation and safety level classification of reinforced concrete structures in marine environments, driven by reliability indicators throughout their entire lifespan.

[0035] In a specific embodiment of the present invention, taking the longitudinal beam structure of a high-pile wharf as an example, the above method is used to evaluate the long-term performance of the structure.

[0036] The structure is designed for a 50-year service life, with a safety level of Level II. It uses C45 concrete, HPB300 steel bars with a diameter of 8mm for the stirrups (stirrup ratio of 0.764%), HRB335 steel bars with a diameter of 22mm for the longitudinal reinforcement (longitudinal reinforcement ratio of 0.075%), a protective layer thickness of 50mm, and a cross-sectional dimension of 900mm*1700mm. The corresponding probability distribution type and statistical parameters are shown in Table 2. The splash zone is selected as the most unfavorable condition for chloride salt corrosion (see Table 3) for analysis.

[0037] Table 2. Probability distribution types and statistical parameters of each random variable.

[0038] Table 3 Initial corrosion time parameters and statistical characteristics of reinforcing bars in the splash zone

[0039] (I) Chloride ion diffusion and steel corrosion analysis 1. Initial corrosion time of reinforcing steel First, based on the probability distribution of each parameter in Tables 2 and 3, 10,000 random samples were generated using the Monte Carlo method. These samples were then substituted into the initial corrosion time prediction model for steel bars for calculation and statistical analysis. The statistical parameters of the initial corrosion time of steel bars in the splash zone are shown in Table 4.

[0040] Table 4. Statistical parameters of initial corrosion time of steel reinforcement in structural members (years)

[0041] 2. Time of concrete rust expansion cracking After determining the initial corrosion time of the reinforcing steel, the thickness of the protective layer is further considered. d c , diameter of corroded steel bars d s0 Standard value of compressive strength of concrete cube f cu,k and the water-cement ratio of concrete w / c Using random variables, a concrete rust expansion cracking time prediction model was used to conduct 10,000 Monte Carlo random simulations, and the mean and standard deviation of the probability distribution of the cracking time of the concrete protective layer of the component were obtained, as shown in Table 5: Table 5 Statistical parameters of cracking time of concrete protective layer of structural members (years)

[0042] 3. Steel corrosion rate Furthermore, considering the concrete protective layer thickness in Table 2... d c Initial diameter of reinforcing bars d s0 Based on the distribution form and statistical parameters of random variables, 10,000 Monte Carlo simulations were conducted using a time-varying model of steel reinforcement corrosion rate and a steel reinforcement corrosion rate prediction model to obtain the time-varying statistical law of steel reinforcement corrosion rate of structural members, as shown in Table 6: Table 6. Time-varying statistical parameters of corrosion rate of longitudinal beam reinforcement (%)

[0043] (II) Time-varying degradation analysis of material properties 1. Strength of corroded steel bars Based on the steel section loss rate of the component at different time points and the initial yield strength of the steel, the steel strength degradation model of the corroded steel was used to conduct 10,000 Monte Carlo simulations, and the time-varying statistical parameters of the steel strength of the component were obtained, as shown in Table 7.

[0044] Table 7. Time-varying statistical parameters of longitudinal beam reinforcement strength (MPa)

[0045] (iii) Ductility of corroded steel bars In the example, all the reinforcing steel bars used in the structural members are HRB335 grade steel bars, and the yield strain of the uncorroded steel bars is 1.675 × 10⁻⁶. -3 The ultimate strain is 0.1, corresponding to an initial ultimate strain to yield strain ratio of 59.7. Based on the ductile degradation model of corroded steel bars, the ultimate strain to yield strain ratio of the main reinforcement and stirrups in the splash zone of the member at different service times was calculated, and its time-varying statistical parameters can be obtained, as shown in Table 8.

[0046] Table 8 Time-varying statistical parameters of longitudinal beam reinforcement ductility

[0047] (iv) Concrete strength By substituting the mechanical parameters of the stirrups at different times into the concrete strength degradation model for calculation, the time-varying statistical parameters of the peak compressive stress and peak compressive strain of the concrete in the wharf component can be obtained, as shown in Table 9.

[0048] Table 9 Time-varying statistical parameters of peak compressive stress and strain in concrete

[0049] (v) Bond strength coefficient between steel reinforcement and concrete Based on the determined critical time for steel reinforcement corrosion, the current corrosion stage of the steel reinforcement is first identified, and then the appropriate formula for calculating the bond coefficient is selected. Using a reinforced concrete bond coefficient model, 10,000 Monte Carlo simulations were performed to obtain the time-varying statistical parameters of the bond coefficient between the steel reinforcement and concrete in the structural member, as shown in Table 10.

[0050] Table 10 Time-varying statistical parameters of bond coefficient of reinforced concrete in structural members

[0051] (vi) Calculate the time-varying resistance of the components Based on the obtained time-varying parameters of the components, the resistance values ​​of the samples at each time point can be calculated by substituting them into the time-varying resistance calculation model. The mean, standard deviation, and time-varying coefficients of the resistance corresponding to the obtained longitudinal beam resistance probability distribution are shown in Table 11.

[0052] Table 11 Time-varying statistical parameters of longitudinal beam resistance

[0053] Based on this, curves showing the time-varying coefficients of the mean and standard deviation of the longitudinal beam resistance over time can be plotted, such as... Figure 3 As shown.

[0054] Depend on Figure 3 It can be seen that the mean resistance of the longitudinal beam gradually decreases with the service time, and drops to about 79% of the initial mean resistance at the end of 50 years of service; while the standard deviation of the resistance gradually increases with time, and is about 1.45 times the initial standard deviation at the end of 50 years of service.

[0055] (vii) Establishing a time-varying resistance probability model for components By fitting the time-varying coefficients of the mean and standard deviation of the longitudinal beam resistance using a cubic function, the following time-varying resistance probability model for the component can be obtained: , In the formula, t represents the service time in years; The time-varying coefficient of the mean longitudinal beam resistance at time t; is the time-varying coefficient of the standard deviation of the longitudinal beam resistance at time t.

[0056] (viii) Assess the long-term performance of the structure Referring to the "Port Engineering Load Specification", the standard value of the one-year cargo stacking load is determined to be 0.45, the coefficient of variation is 0.244, the distribution type is extreme value type I, the cargo stacking load is 30 kPa, and the load mean and standard deviation at each time point are determined.

[0057] Substitute the mean standard deviation of component resistance and the mean standard deviation of load into the reliability index. βThe calculation formula calculates the reliability index at each time step. β like Figure 4 As shown.

[0058] Referring to the relevant provisions in the "Unified Standard for Reliability Design of Port Engineering Structures", the reliability index for Level II safety is 3.5. β A =3.5, corresponding β B =0.95 * 3.5 = 3.325 β C =0.90 * 3.5 = 3.15.

[0059] The reliability index for 50 years is 3.239, which is at... β B and β C Between these levels, the safety level is C, indicating that the structure's safety within the target service life does not meet the requirements of current national standards and specifications, and has an adverse impact on safe use under the predetermined working conditions. Therefore, it is necessary to redesign or take corresponding measures to improve its safety.

[0060] In this embodiment, it also includes: Based on the comparison results between the component time-varying resistance probability model and the target reliability index, a sequence of safety levels (A to D) corresponding to each time segment is generated in chronological order, i.e., the time-varying safety level evolution sequence. This time-varying safety level evolution sequence is associated with a predefined maintenance measure knowledge base, in which each measure records its applicable "safety level triggering conditions" and "technical and economic characteristic parameters". For each time segment in the evolution sequence where the safety level degrades, a weighted calculation is performed based on the level change value and the expected duration of that level state to quantify and generate an intervention urgency index. Based on the current... The safety level of each time segment and the calculated intervention urgency index are used to select candidate measures from the maintenance measure knowledge base that meet all safety level trigger conditions, forming a preliminary matching measure set. For each measure in the preliminary matching measure set, its technical and economic characteristic parameters and intervention urgency index are normalized and weighted to generate a comprehensive suitability score for each measure in the current time segment. Based on the comprehensive suitability scores of all time segments and corresponding measures, a two-dimensional maintenance decision matrix is ​​constructed. By traversing this matrix and setting a scoring threshold, the recommended intervention timing and the combination of measures with the highest comprehensive suitability score at that timing are output.

[0061] It should be noted that the aforementioned steps have completed the time-varying reliability assessment and safety level classification of the structure's long-term performance. However, a deeper problem in engineering practice lies in how to automatically, scientifically, and economically transform qualitative or semi-quantitative assessment conclusions such as "safety level C" into actionable decisions on "when and what specific maintenance measures to take," thereby overcoming the shortcomings of existing technologies, such as the disconnect between assessment results and maintenance actions, reliance on subjective experience, and lack of quantitative support. Therefore, this embodiment, after generating the time-varying safety level evolution sequence, further introduces an intelligent maintenance decision generation method based on this sequence. Specifically: The time-varying safety level evolution sequence is presented through continuous safety level classification based on time intervals. For example, safety level A is for service life of 0-18 years, level B for 19-28 years, and level C for 29-50 years. Furthermore, a pre-constructed structured maintenance measure knowledge base is used to support this. Each specific maintenance measure in the knowledge base has clearly defined application conditions and evaluation parameters. The application conditions refer to the safety level triggering conditions applicable to the measure; for example, a hardening measure can be initiated when the safety registration is assessed as downgraded to level C. The evaluation parameters quantify the characteristics of the measure, including technical effectiveness coefficients, single implementation cost coefficients, and durability gain coefficients. These coefficients are normalized based on engineering practices, literature data, or existing engineering projects in the field to facilitate unified mathematical processing and comparative analysis later.

[0062] For the moment when the safety level in the evolutionary sequence is downgraded, an intervention urgency index is calculated. This index is quantified by weighting the gradient value of the level change with the expected duration of the low-level state. The longer the duration, the higher the relative weight of the urgency may be, resulting in a larger index value, indicating that attention should be paid as early as possible.

[0063] Then, based on the safety level at that moment and the calculated intervention urgency index, the screening of the maintenance measures knowledge base is initiated. By traversing the knowledge base, all candidate measures whose safety level triggering conditions are met by the current level are screened out, such as "crack pressure grouting" and "rust prevention treatment of locally corroded steel bars", forming a preliminary set of matching measures.

[0064] For each measure in the initial matching set, a refined score is performed. The technical and economic characteristics of the measure and the intervention urgency index at the current time point are normalized separately, and then a weighted combination calculation is performed. For example, the "technical effectiveness coefficient" is assigned a weight of 0.4, the "single implementation cost coefficient" a weight of 0.3 (the lower the cost, the higher the score), and the "durability gain coefficient" a weight of 0.2. The "intervention urgency index" itself is used as a demand matching weight parameter with a weight of 0.1 in the calculation. Finally, a comprehensive suitability score reflecting the overall cost-effectiveness and demand fit of the measure at this specific time is generated.

[0065] Finally, based on the comprehensive suitability scores of all time segments and corresponding measures, a two-dimensional maintenance decision matrix is ​​constructed, with "time segments" as rows and "candidate measures" as columns. By traversing this matrix and setting an acceptable comprehensive suitability score threshold, the recommended intervention time is output, which is the time segment where the first measure with a score exceeding the threshold occurs. Simultaneously, the top 1-2 measures with the highest comprehensive suitability scores at that time are output as the recommended measure combination. For example, the output might be "In year 29, the 'crack pressure grouting' measure is recommended."

[0066] In summary, this invention proposes a complete process and calculation method for long-term performance evaluation of reinforced concrete structures suitable for marine chloride environments. It constructs a comprehensive evaluation chain, from engineering information input, chloride ion diffusion and steel corrosion analysis, time-varying material property degradation analysis, component time-varying resistance calculation, to reliability index determination, systematically reflecting the evolution of the structure's load-bearing capacity throughout its lifespan. Simultaneously, by introducing reliability indices and their classification thresholds, a dynamic evaluation method for safety levels A to D, applicable to water transport infrastructure such as high-pile wharves, is established. This method can provide the safety level and critical time of components and structures at different service years, thus providing quantitative basis for durability design, structural condition assessment, and maintenance and reinforcement decisions. It can effectively serve the design and operation management of infrastructure such as high-pile wharves in coastal ports, helping engineers accurately grasp the performance degradation state of components during their service life, and scientifically and rationally formulate maintenance and reinforcement plans. This, in turn, reduces unnecessary maintenance investment and improves the durability and service life of the structure while ensuring structural safety.

[0067] The second aspect of the present invention discloses a concrete structure performance evaluation system in a marine environment. The concrete structure performance evaluation system includes a memory and a processor. The memory stores a concrete structure performance evaluation method program. When the concrete structure performance evaluation method program is executed by the processor, the steps of any of the concrete structure performance evaluation methods described in the present invention are implemented.

[0068] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0069] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0070] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0071] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0072] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0073] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the performance of concrete structures in a marine environment, characterized in that, Includes the following steps: S1, Engineering Information and Environmental Conditions Input: Obtain basic information and service environment conditions of the project to be analyzed; S2, Determine the analysis structure and section parameters: Based on the project layout and stress characteristics, select the structural components that need to be evaluated for performance, and determine the calculation diagram and section geometry parameters, reinforcement layout and protective layer thickness of each component; S3, Establish random variables and probability models: For the uncertain parameters of chloride ion diffusion coefficient, surface chloride ion concentration, critical chloride ion concentration, material strength, and component size, establish corresponding random variables and probability distribution models as inputs for subsequent time-varying analysis and Monte Carlo simulation; S4, Set the analysis period and time step: Set the analysis period according to the structural design service life, and discretize the analysis period into several time steps to obtain the performance evolution process of the component at different time sections during the whole life. S5, Chloride ion diffusion and steel corrosion analysis: Chloride ion diffusion and steel corrosion analysis are performed within a set time range to obtain corrosion parameters; S6, Time-varying degradation analysis of material properties: Based on the corrosion parameters, time-varying degradation analysis of material properties is performed to obtain the degraded material property parameters; S7, Calculate the time-varying resistance of the component: At each analysis time section, substitute the degraded material property parameters into the component bearing capacity calculation model to obtain the resistance value of the structural component as time changes, realize the calculation of the time-varying resistance of the component, and establish the time-varying resistance calculation model; S8. Establish a time-varying resistance probability model for the component: Using the random variables established in step S3 and the time-varying resistance calculation model obtained in step S7, the Monte Carlo simulation probability analysis method is used to obtain the resistance probability distribution of the component at each time section and establish a time-varying resistance probability model for the component. S9, Evaluate the long-term performance of the structure: Based on the time-varying resistance probability model of the components, compare the component resistance with the corresponding load effects or target reliability index, evaluate the safety level and performance of the structure at each time section within the analysis period, and obtain the structural performance evaluation results.

2. The method for evaluating the performance of concrete structures in a marine environment according to claim 1, characterized in that, Chloride ion diffusion and steel corrosion analysis were performed within a set time frame to obtain corrosion parameters, including: By using the steel reinforcement initial corrosion time prediction model, the steel reinforcement corrosion rate time-varying model, the steel reinforcement corrosion rate prediction model, and the concrete cracking time prediction model, the results of steel reinforcement rust initiation time, corrosion rate, corrosion rate, and protective layer cracking time at each time section were obtained.

3. The method for evaluating the performance of concrete structures in a marine environment according to claim 1, characterized in that, Based on the aforementioned corrosion parameters, time-varying degradation analysis is performed on the material properties to obtain the degraded material property parameters, specifically including: By using the strength degradation model, ductility degradation model, concrete strength degradation model, and reinforced concrete bond coefficient model, the degradation values ​​of the material properties of steel bars and concrete, as well as the bond properties of the steel bar and concrete interface, at various time sections were obtained.

4. The method for evaluating the performance of concrete structures in a marine environment according to claim 2, characterized in that, S5 also includes establishing a chloride ion diffusion model: ， In the formula, This represents the chloride ion concentration at a distance x from the concrete surface at time t, in kg / m³. 3 ; t represents time, in years; x represents the depth from the concrete surface, in mm; This indicates the chloride ion concentration on the concrete surface, expressed in kg / m³. 3 ; It is the error function; This is the environmental impact coefficient; This is a correction factor for the chloride ion diffusion coefficient detection method; This is a correction factor for concrete curing time; The reference time for the chloride ion diffusion coefficient is 28 days. The chloride ion diffusion coefficient is the reference time. It is an aging factor.

5. The method for evaluating the performance of concrete structures in a marine environment according to claim 4, characterized in that: Based on the established chloride ion diffusion model, the steel bar is considered to have begun to corrode when the chloride ion concentration on its surface first reaches a critical concentration, i.e., the initial corrosion time has been reached. t corr After considering the uncertainty parameters in the model, the prediction model for the initial corrosion time of steel bars is obtained: ， In the formula, X1 is the uncertainty parameter of corrosion time; C0 is the chloride ion concentration on the concrete surface; C cr denoted as the critical chloride ion concentration; D is the chloride ion diffusion coefficient at the actual moment. This refers to the thickness of the concrete protective layer, in mm. This is the sensitivity coefficient of chloride ion concentration to changes in water-cement ratio; This serves as the baseline value for chloride ion concentration on the concrete surface. The water-cement ratio of concrete; First, obtain the current density of steel reinforcement corrosion. i corr Then by i corr The corrosion rate of reinforcing steel bars, i.e., the corrosion development rate, is calculated using current density. i corr By characterization, the time-varying model of steel corrosion rate is expressed as: ， In the formula, The corrosion current density at the moment of corrosion initiation, in units of ; Water-cement ratio; t p This indicates the time elapsed since the steel bars began to corrode, expressed in years. This indicates the thickness of the concrete cover, in mm. λ This indicates the annual corrosion rate, expressed in mm / year. Indicates the corrosion influence coefficient; This represents the erosion current density, in units of... .

6. The method for evaluating the performance of concrete structures in a marine environment according to claim 2, characterized in that: If the corrosion of the reinforcing steel is uniform, then the corrosion will cause its cross-sectional diameter and mechanical properties to gradually degrade over time. Assuming the steel's self-degradation... t corr If corrosion begins at any given moment, then at any given moment... t The prediction model for the corrosion rate of corroded steel bars is expressed as follows: ， In the formula, The diameter of the remaining steel bar after corrosion is shown in mm. This refers to the original diameter of the reinforcing bar, in mm. The rate of steel corrosion is expressed in mm / year. The initial corrosion time of the reinforcing steel is expressed in years. The percentage of steel reinforcement corrosion is expressed as % (%). If the moment when the steel reinforcement corrosion reaches the critical corrosion level is defined as the time when the concrete cover begins to crack, then the concrete cracking time prediction model is expressed as follows: ， In the formula, express t The rate of steel corrosion at any given time, expressed in mm / year; Indicates the time of concrete cracking, in years; The initial corrosion time of the reinforcing steel is expressed in years. This indicates the critical corrosion depth of the reinforcing steel, in mm. This indicates the design value for the thickness of the concrete cover, in mm. This indicates the original diameter of the reinforcing bar, in mm. This represents the standard value of concrete compressive strength, in MPa.

7. The method for evaluating the performance of concrete structures in a marine environment according to claim 3, characterized in that: The strength degradation model of the corroded steel bars is expressed as follows: ， In the formula, for t The yield strength of the steel reinforcement at any given time, expressed in MPa; This represents the initial yield strength of the steel reinforcement, in MPa. for t Area loss caused by steel reinforcement corrosion, expressed in % (%) The ductile degradation model of the corroded steel bars is represented as follows: ， In the formula, This represents the initial ultimate strain of the reinforcing steel. This represents the strain corresponding to the initial yield of the steel reinforcement. for t The ductility index of steel reinforcement at any given time; The concrete strength degradation model is expressed as follows: ， In the formula, These are constraint coefficients; This represents the peak compressive stress in ordinary concrete, expressed in MPa. The peak compressive stress in confined concrete is expressed in MPa. Limited lateral restraint for confining concrete, measured in MPa; The stress is the yield stress of the stirrup, expressed in MPa. It is the lateral effective constraint coefficient, which is the ratio of the effective core concrete area to the total core concrete area. This represents the cross-sectional area of ​​the stirrups after corrosion, in mm². 2 ; The spacing of the stirrups is in mm; d The effective width of the cross section, i.e., the cross section width of the core concrete area, is expressed in mm. To constrain the peak strain of concrete; The bond coefficient model for reinforced concrete is expressed as follows: ， In the formula, These are the bonding coefficients of the protective layer before and after cracking, respectively. , where is the cross-sectional loss rate of the reinforcing steel, in units of %; and e is the base of the natural logarithm.

8. The method for evaluating the performance of concrete structures in a marine environment according to claim 1, characterized in that: For reinforced concrete slabs and beams, the stress mode is bending. The flexural capacity of the cross section is used as the characterization index of the member's resistance. The structural resistance is calculated by the following formula: ， In the formula, Indicates the bending capacity of a component; Indicates the axial compressive strength of concrete; b Indicates the width of the component section; x Indicates the height of the pressure zone; Indicates the effective height of the component section; Indicates the yield strength of the steel reinforcement in the compression zone; Indicates the cross-sectional area of ​​the compressed reinforcing steel; This indicates the distance from the point of application of the resultant force on the compressed steel reinforcement to the edge of the member's cross-section; Indicates the bond coefficient between steel reinforcement and concrete; Indicates the strength of the reinforcement in the tension zone; Indicates the cross-sectional area of ​​the tensile reinforcement; To characterize the time-varying nature of the probability distribution of component resistance, we define the time-varying coefficient of the mean resistance and the time-varying coefficient of the standard deviation of the component resistance. The time-varying resistance calculation model is then expressed as: ， In the formula, for t The mean time-varying coefficient of the component resistance over a year; for t The time-varying coefficient of the standard deviation of the component resistance over years; for t The average resistance of components over a year; for t Standard deviation of component resistance over years; This represents the average initial resistance of the component. This represents the standard deviation of the initial resistance of the component.

9. The method for evaluating the performance of concrete structures in a marine environment according to claim 3, characterized in that, Using reliability indicators β To characterize structural reliability, the calculation formula can be expressed as: ， In the formula, This represents the average structural resistance. This represents the average structural load. The standard deviation of structural resistance; The standard deviation of structural loads; The average of the safety margin; The standard deviation is the safety margin.

10. A performance evaluation system for concrete structures in a marine environment, characterized in that, The concrete structure performance evaluation system includes a memory and a processor. The memory stores a concrete structure performance evaluation method program. When the concrete structure performance evaluation method program is executed by the processor, the steps of the concrete structure performance evaluation method as described in claim 1 are implemented.

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