A method and system for evaluating the performance of a concrete structure in a marine environment

Abstract

The present application relates to the technical field of civil engineering evaluation, and particularly relates to a method and system for evaluating performance of a concrete structure in a marine environment, which comprises the following steps: inputting engineering information and environmental parameters; determining analysis components and section parameters; establishing a probability model of key parameters; setting an analysis period and a time step; performing chloride ion diffusion and steel corrosion analysis; carrying out time-varying degradation analysis of material performance; calculating time-varying resistance of components; establishing a time-varying probability model of structural resistance; and evaluating long-term performance of the structure. The present application integrates chloride ion erosion, steel corrosion, material degradation, time-varying resistance of components and reliability analysis to form a whole-chain evaluation system from environmental input to safety grade division, which can dynamically reflect the evolution law of the bearing capacity of the structure in the whole life cycle and provide quantitative basis for durability design, service state evaluation and maintenance decision of reinforced concrete structures such as high-pile wharfs in the marine environment.

Description

TECHNICAL FIELD

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

[0002] With the construction of a large number of coastal ports and marine projects, a large number of reinforced concrete high-pile wharfs and the like are in a strong chloride salt environment such as a seawater splashing area and a tidal area for a long time, and are prone to corrosion of steel bars and degradation of concrete strength caused by chloride ion erosion, which leads to continuous attenuation of the bearing capacity and durability of the components, which has become an important problem restricting the safe service of water transportation infrastructure. The chloride ion erosion in the chloride salt environment is affected by various uncertain factors such as material performance, construction details, environmental effects, and construction quality, and is essentially a random process. Accordingly, the long-term performance of the concrete structure also has significant probabilistic characteristics. At present, engineering design is mostly based on the specification for one-time structure checking, and a deterministic safety factor is used to control the safety reserve, which is difficult to reflect the randomness of environmental effects, material performance, and geometric parameters and the time-varying law of the component resistance, and lacks a unified and quantitative long-term performance evaluation method in the aspects of operational state evaluation, life prediction, and maintenance decision-making, and it is urgent to establish a full-life performance evaluation system suitable for concrete structures in a marine environment. SUMMARY

[0003] The present application overcomes the shortcomings of the prior art and provides a method and system for evaluating 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:

[0005] The present application discloses a method for evaluating performance of a concrete structure in a marine environment, comprising the following steps:

[0006] S1, inputting engineering information and environmental conditions: obtaining basic information of an engineering to be analyzed and service environmental conditions; the engineering information includes structure form, component type, cross-section size, reinforcement parameter, and material strength grade; the environmental conditions include seawater chloride salt concentration, environmental section, temperature, and humidity;

[0007] S2, determining analysis structure and cross-section parameters: according to engineering layout and stress characteristics, selecting a structure component that needs to be evaluated in performance, and determining a calculation diagram, cross-section geometric parameters, steel bar arrangement, and protective layer thickness of each component;

[0008] S3, establishing random variables and probability models: for uncertain parameters of chloride ion diffusion coefficient, surface chloride ion concentration, critical chloride ion concentration, material strength, and component size, establishing corresponding random variables and probability distribution models as inputs for subsequent time-varying analysis and Monte Carlo simulation;

[0009] 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;

[0010] 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;

[0011] 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;

[0012] 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;

[0013] 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;

[0014] 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.

[0015] Preferably, in the S5, it further includes establishing chloride ion diffusion model:

[0016] ,

[0017] 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 (t, 0) represents chloride ion concentration of concrete surface, unit: kg / m 3 ; is the error function; is the environmental influence coefficient; is the chloride diffusion coefficient detection method correction coefficient; is the concrete curing time correction coefficient; is the reference time of chloride diffusion coefficient, i.e. 28 days; is the chloride diffusion coefficient at the reference time; is the aging factor.

[0018] Preferably, according to the determined chloride diffusion model, when the chloride ion 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 steel bar initial corrosion time prediction model is obtained:

[0019] ,

[0020] In the formula, X1 is the corrosion time uncertainty parameter; C0 is the chloride ion concentration on the surface of the concrete; C cr is the critical chloride ion concentration; D is the chloride ion diffusion coefficient at the actual time; is the concrete cover thickness, in mm; is the sensitivity coefficient of chloride ion concentration with water-cement ratio; is the reference value of the chloride ion concentration on the surface of the concrete; is the water-cement ratio of the concrete;

[0021] First, the steel bar corrosion current density is obtained i corr Then, the corrosion rate of the steel bar, i.e. the corrosion development rate, is calculated by means of the current density i corr characterized, the time-varying model of the steel bar corrosion rate is expressed as: i corr

[0022] ,

[0023] In the formula, is the corrosion current density at the corrosion initiation time, in A / m2; is the water-cement ratio ; t p represents the time experienced since the steel bar began to rust, in years; represents the concrete cover thickness, in mm; λ represents the annual corrosion rate, in mm / year; represents the corrosion influence coefficient; ​denotes the corrosion current density, and the unit is .

[0024] Preferably, if the steel bar corrosion is in the form of uniform corrosion, the steel bar corrosion will cause its cross-sectional diameter and mechanical properties to gradually degrade over time, assuming that the steel bar begins to corrode at time t corr , the corrosion steel bar corrosion rate prediction model at any time t is expressed as:

[0025] ,

[0026] In the formula, is the diameter of the remaining steel bar after corrosion, with the unit of mm; is the original diameter of the steel bar, with the unit of mm; is the corrosion rate of the steel bar, with the unit of mm / year; is the initial corrosion time of the steel bar, with the unit of year; is the corrosion rate of the steel bar, with the unit of %;

[0027] The time when the steel bar corrosion amount reaches the critical corrosion 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:

[0028] ,

[0029] In the formula, denotes the corrosion rate of the steel bar at time t , with the unit of mm / year; denotes the concrete cracking time, with the unit of year; is the initial corrosion time of the steel bar, with the unit of year; denotes the critical corrosion depth of the steel bar, with the unit of mm; denotes the design value of the concrete protective layer thickness, with the unit of mm; denotes the original diameter of the steel bar, with the unit of mm; denotes the standard value of the concrete compressive strength, with the unit of Mpa.

[0030] Preferably, the corrosion steel bar strength degradation model is expressed as:

[0031] ,

[0032] In the formula, is the yield strength of the steel bar at time t , with the unit of MPa; is the initial yield strength of the steel bar, with the unit of MPa; is the area loss caused by the corrosion of the steel bar at time t , with the unit of %;

[0033] The ductility degradation model of the corroded steel bar is expressed as:

[0034] ,

[0035] 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 initial yield stress of the steel bar; t is the ductility index of the steel bar at the moment;

[0036] The concrete strength degradation model is expressed as:

[0037] ,

[0038] In the formula, is the constraint coefficient; is the peak compressive stress of ordinary concrete, with the unit of MPa; is the peak compressive stress of confined concrete, with the unit of MPa; is the lateral constraint of the confined concrete, with the unit of MPa; is the yield stress of the stirrup, with the unit of MPa; is the effective lateral constraint coefficient, i.e. the ratio of the effective core concrete area to the total core concrete area; is the cross-sectional area of the corroded stirrup, with the unit of mm 2 ; is the spacing of the stirrup, with the unit of mm; d is the effective cross-sectional width, i.e. the cross-sectional width of the core concrete area, with the unit of mm; is the peak strain of the confined concrete;

[0039] The bond coefficient model of the reinforced concrete is expressed as:

[0040] ,

[0041] In the formula, are the bond coefficients before and after the cracking of the protective layer, respectively; is the cross-sectional loss rate of the steel bar, with the unit of %; e is the base of natural logarithm.

[0042] Preferably, for the reinforced concrete slab and beam members, the force form is bending action, the normal section bending capacity is used as the representation index of the member resistance, and the structural resistance is calculated according to the following formula:

[0043] ,

[0044] In the formula, represents the bending capacity of the member; f'c represents the concrete axial compressive strength; b b represents the member cross-sectional width; x h represents the compressive zone height; h' represents the effective member cross-sectional height; fy represents the compressive reinforcement yield strength; As represents the compressive reinforcement cross-sectional area; d represents the distance from the point of application of the resultant compressive force to the edge of the member cross-section; μ represents the bond coefficient between the reinforcement and the concrete; ft represents the tensile reinforcement strength; At represents the tensile reinforcement cross-sectional area;

[0045] To depict the time variability of the member resistance probability distribution, the mean time variability coefficient and the standard deviation time variability coefficient of the member resistance are defined, and the time-variant resistance calculation model is represented as:

[0046] ,

[0047] wherein, μr represents the mean time variability coefficient of the member resistance; t μr represents the mean time variability coefficient of the member resistance at the year t; σr represents the standard deviation time variability coefficient of the member resistance; t σr represents the standard deviation time variability coefficient of the member resistance at the year t; μ0 represents the mean of the initial member resistance; t μ0 represents the mean of the initial member resistance at the year t; σ0 represents the standard deviation of the initial member resistance; t σ0 represents the standard deviation of the initial member resistance at the year t; μ0 represents the mean of the initial member resistance; σ0 represents the standard deviation of the initial member resistance.

[0048] Preferably, the reliability index β is used to represent the structural reliability, and the calculation formula can be represented as: β

[0049] ,

[0050] wherein, μ represents the mean of the structural resistance; μ represents the mean of the structural load; σ represents the standard deviation of the structural resistance; σ represents the standard deviation of the structural load; μ represents the mean of the safety margin; σ represents the standard deviation of the safety margin.

[0051] ​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.

[0052] 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, component time-varying resistance calculation to reliability index determination, reflecting the evolution law of the bearing capacity of the structure in the whole life cycle. 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 component 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 coastal port high-pile wharf and other infrastructure, helping engineering and technical personnel accurately master the performance degradation state of the component in the service period, and scientifically and reasonably formulating the maintenance and reinforcement scheme, thereby reducing unnecessary maintenance investment and improving the durability and service life of the structure under the premise of ensuring the safety of the structure. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings of embodiments according to these drawings without creative labor.

[0054] Figure 1 The flow chart of the concrete structure performance evaluation method is shown in Figure 1.

[0055] Figure 2 The steel bar corrosion development stage diagram of the reinforced concrete structure in the marine environment is shown in Figure 2.

[0056] Figure 3 The longitudinal beam resistance time-varying law diagram is shown in Figure 3.

[0057] Figure 4 The component time-varying reliability index diagram is shown in Figure 4. DETAILED DESCRIPTION

[0058] In order to enable a more clear understanding of the above-mentioned objects, features and advantages of the present application, the present application will be further described below in conjunction with the drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict, if necessary.

[0059] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application, but the present application can also be implemented in other manners different from those described herein, and therefore, the scope of protection of the present application is not limited to the specific embodiments disclosed below.

[0060] As shown in Figure 1 The first aspect of the present application discloses a method for evaluating the performance of a concrete structure in a marine environment, comprising the following steps:

[0061] S1, inputting engineering information and environmental conditions: obtaining the basic information of the engineering to be analyzed and the service environmental conditions;

[0062] It should be noted that by consulting design drawings, construction records and on-site investigation, the key basic information of the engineering to be analyzed is systematically obtained and input, and the engineering information specifically includes but is not limited to: structure form, type of component to be evaluated, accurate cross-sectional size of each component, detailed reinforcement parameters and material strength grade, etc. At the same time, by using environmental monitoring data, hydrological and meteorological data or standard value, the service environmental conditions of the structure are determined, which specifically include: seawater chloride concentration, environmental zoning at the structure site, annual average temperature and humidity, etc. All the information collected in this step constitutes the statistical basis of all the deterministic initial parameters and probability variables of the subsequent chloride ion transport model, material degradation model and component resistance calculation, which ensures that the evaluation model can truly reflect the performance evolution starting point of the specific engineering entity under the action of the specific marine environment.

[0063] S2, determining the analysis structure and section parameters: according to the engineering layout and stress characteristics, the structure component that needs to be evaluated is selected, and the calculation diagram, section geometric parameters, reinforcement arrangement and protective layer thickness of each component are determined;

[0064] It should be noted that based on the overall arrangement and structural form obtained in step S1, key structural members that need to be evaluated for performance are selected, such as members that are in a harsh chloride environment such as a splash zone, a tidal zone, etc. and bear main loads, for example, longitudinal beams, cross beams, panels or pile foundations in high-pile wharfs; after the members are selected, the calculation diagrams of the members are determined, for example, beams are simplified as simply supported beam or continuous beam models, and plates are simplified as one-way plate or two-way plate models, which need to reflect the true boundary conditions and stress characteristics; on this basis, the sectional geometric parameters of the members are accurately determined, including sectional width, height, effective height, area, moment of inertia, etc.; at the same time, the steel bar arrangement is determined in detail, including the type, diameter, number, spacing, position of longitudinal stress reinforcement and stirrups, and the design value or measured value of the concrete cover thickness. The determination of these specific parameters provides deterministic input for the chloride ion transmission depth calculation in step S5, the material performance degradation calculation in step S6 and the member resistance calculation in step S7, ensuring that the entire time-varying reliability evaluation is based on an accurate physical model of the member.

[0065] 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 member size, corresponding random variables and probability distribution models are established as input for subsequent time-varying analysis and Monte Carlo simulation;

[0066] S4, setting analysis period and time step: according to the design service life of the structure, the analysis period is set, and the analysis period is discretized into several time steps to obtain the performance evolution process of the member at different time sections in the whole life cycle;

[0067] S5, chloride ion diffusion and steel bar corrosion analysis: within the set time range, chloride ion diffusion and steel bar corrosion analysis is performed to obtain corrosion parameters, including: using steel bar initial corrosion time prediction model, steel bar corrosion rate time-varying model, steel bar corrosion rate prediction model and concrete cracking time prediction model to obtain steel bar rusting time, corrosion rate, corrosion rate and protective layer cracking time results at each time section;

[0068] S6, time-varying degradation analysis of material performance: based on the corrosion parameters, time-varying degradation analysis of material performance is performed to obtain the degraded material performance parameters, including: using the corrosion steel bar strength degradation model, the corrosion steel bar ductility degradation model, the concrete strength degradation model and the steel reinforced concrete bond coefficient model to obtain the degradation values of steel bar and concrete material performance and steel bar and concrete interface bond performance at each time section;

[0069] S7, calculating time-varying resistance of the component: in each analysis time section, the material performance parameters after degradation are substituted into the calculation model of the bearing capacity of the component to obtain the resistance value of the structural component varying with time, realize the calculation of the time-varying resistance of the component, and establish a time-varying resistance calculation model;

[0070] S8, establishing a time-varying resistance probability model of 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 adopted to obtain the resistance probability distribution of the component in each time section, and a time-varying resistance probability model of the component is established;

[0071] S9, evaluating long-term performance of the structure: according to the time-varying resistance probability model of the component, the resistance of the component is compared with the corresponding load effect or target reliability index to evaluate the safety level and performance of the structure in each time section within the analysis period, and the performance evaluation result of the structure is obtained.

[0072] To realize 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 performance" is as follows:

[0073] In this embodiment, the chloride ion diffusion is described by Fick's second law, the concrete is regarded as a semi-infinite and isotropic medium, and it is assumed that the chloride ion does not combine with the solid phase material. In practice, the hydration product fills the pores during the service of the concrete, resulting in a decrease in porosity, so the chloride ion diffusion coefficient decays with time. This method uses the Duracrete model to modify the diffusion coefficient, considering the environment, test method, curing and aging effects, thereby establishing a chloride ion diffusion model:

[0074] ,

[0075] In the formula, C (t, x) represents the chloride ion concentration at x from the concrete surface at time t, with the unit of kg / m 3 ; t represents time, with the unit of year; x represents the depth from the concrete surface, with the unit of mm; C (0, x) represents the chloride ion concentration on the surface of the concrete, with the unit of kg / m 3 ; erfc represents the error function; β represents the environmental influence coefficient; α represents the chloride ion diffusion coefficient test method correction coefficient; γ represents the concrete curing time correction coefficient; t0 represents the reference time of the chloride ion diffusion coefficient, i.e. 28 days; D0 represents the chloride ion diffusion coefficient at the reference time; η represents the aging factor.

[0076] It should be noted that in the marine chloride environment, reinforced concrete structures are exposed to seawater and sea air containing chloride ions for a long time. Chloride ions gradually migrate to the interior of the concrete and accumulate on the surface of the steel bars. When the concentration of chloride ions exceeds the critical value, the passivation film is destroyed, triggering the electrochemical corrosion of the steel bars. The initiation time and development rate of steel bar corrosion are closely related to the integrity of the passivation film, the pore structure of the concrete, and the concentration of chloride ions, so the corrosion process has a stage characteristic. In the whole life cycle of the structure, the evolution of steel bar corrosion can be characterized by two key time points: the initial corrosion time of the steel bar and the cracking time of the concrete protective layer t s . Accordingly, the steel bar corrosion process can be divided into three typical stages: the corrosion induction period from the beginning of the structure service to the initial corrosion time of the steel bar; the corrosion expansion period from the initial corrosion time of the steel bar to the cracking time of the concrete protective layer t cr ; and the corrosion development period after the cracking time of the concrete protective layer. The steel bar corrosion rate in different stages is significantly different, and its time course can be illustrated as shown in t corr , which is used to guide the selection and parameter calculation of the corrosion model in each period. t cr t > t cr . Figure 2

[0077] According to the determined chloride ion diffusion model, when the chloride ion concentration on the surface of the steel bar first reaches the critical concentration, it is considered that the steel bar begins to corrode, i.e., the initial corrosion time t corr of the steel bar is reached. Considering the uncertainty parameters in the model and the linear relationship between the chloride ion concentration on the surface of the concrete and the water-cement ratio of the concrete in actual marine engineering, the prediction model of the initial corrosion time of the steel bar is obtained:

[0078] ,

[0079] where X1 is the uncertainty parameter of the corrosion time; C0 is the chloride ion concentration on the surface of the concrete; C cr is the critical chloride ion concentration; D is the chloride ion diffusion coefficient at the actual time; f is the thickness of the concrete protective layer, in mm; is the sensitive coefficient of the chloride ion concentration with the water-cement ratio; C is the reference value of the chloride ion concentration on the surface of the concrete; and w is the water-cement ratio of the concrete.

[0080] The steel bar corrosion rate refers to the equivalent depth of steel bar section corrosion invasion per unit time. The steel bar corrosion current density i corr is first measured by electrochemical testing means, and then the steel bar corrosion rate i ​​​​​corr The corrosion rate of steel bar, i.e. the corrosion development rate, is calculated by means of the current density i corr The time-varying model of the corrosion rate of steel bar is obtained by characterization:

[0081] ,

[0082] In the formula, is the corrosion current density at the corrosion initiation time, with the unit of A / cm2; ; is the water-cement ratio; t p represents the time experienced since the steel bar began to corrode, with the unit of year; represents the thickness of the concrete protective layer, with the unit of mm; λ represents the annual corrosion rate, with the unit of mm / year; represents the corrosion influence coefficient; represents the corrosion current density, with the unit of A / cm2. .

[0083] If the corrosion form of steel bar is uniform corrosion, the corrosion of steel bar will cause its cross-sectional diameter and mechanical properties to gradually degrade over time. It is assumed that the steel bar begins to corrode at time t corr , then the corrosion rate prediction model of the corroded steel bar at any time t is expressed as:

[0084] ,

[0085] In the formula, is the diameter of the remaining steel bar after corrosion, with the unit of mm; is the original diameter of the steel bar, with the unit of mm; is the corrosion rate of the steel bar, with the unit of mm / year; is the initial corrosion time of the steel bar, with the unit of year; is the corrosion rate of the steel bar, with the unit of %.

[0086] The time when the corrosion amount of steel bar reaches the critical corrosion 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:

[0087] ,

[0088] In the formula, represents the corrosion rate of the steel bar at time t , with the unit of mm / year; represents the concrete cracking time, with the unit of year; is the initial corrosion time of the steel bar, with the unit of year; Dcr represents the critical corrosion depth of steel bar, unit: mm; Dc represents the design value of concrete cover thickness, unit: mm; D0 represents the original diameter of steel bar, unit: mm; fc represents the standard value of concrete compressive strength, unit: MPa.

[0089] The influence of steel bar corrosion on the mechanical properties of steel bar mainly reflects in two aspects of strength and ductility, and the strength degradation model of the corroded steel bar is represented as:

[0090] ,

[0091] In the formula, Yield strength of steel bar at time t, unit: MPa; t Initial yield strength of steel bar, unit: MPa; Area loss of steel bar caused by corrosion at time t, unit: %; t The ratio of ultimate strain to yield strain of steel bar is used as the ductility index of steel bar, and the ductility degradation model of the corroded steel bar is represented as:

[0092] ,

[0093] In the formula, Initial ultimate strain of steel bar;

[0094] Strain corresponding to the initial yield of steel bar; Ductility index of steel bar at time t; t The concrete strength degradation model is represented as:

[0095]

[0096] ,

[0097] In the formula, Constraint coefficient; Peak compressive stress of ordinary concrete, unit: MPa; Peak compressive stress of confined concrete, unit: MPa; Limited lateral constraint of confined concrete, unit: MPa; Yield stress of stirrup, unit: MPa; Lateral effective constraint coefficient, i.e. the ratio of effective core concrete area to total core concrete area; Sectional area of stirrup after corrosion, unit: mm 2 ; Spacing of stirrup, unit: 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.

[0098] 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:

[0099] ,

[0100] 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.

[0101] 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:

[0102] ,

[0103] 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.

[0104] 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:

[0105] ,

[0106] 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 a year; for t The average resistance of components over a year; fort the standard deviation of the initial resistance of the component; the mean value of the initial resistance of the component; the standard deviation of the initial resistance of the component.

[0107] After the time-varying probability model of the structural resistance is established, in order to further quantitatively analyze the reliability of the structure, the reliability index β is used to represent the reliability of the structure, and the calculation formula can be expressed as:

[0108]

[0109] In the formula, is the mean value of the structural resistance; is the mean value of the structural load; is the standard deviation of the structural resistance; is the standard deviation of the structural load; is the mean value of the safety margin; is the standard deviation of the safety margin.

[0110] It should be noted that the load includes permanent load and variable load, and the standard value of such load can be determined by referring to the corresponding specifications in the field, such as the “Code for Loads of Port Engineering” and the “Code for Loads of Building Structure”. For actual engineering, the permanent load of the structure generally obeys the normal distribution, and the variable load generally obeys the extreme value type I distribution. By combining the load conditions of the actual engineering, the corresponding mean value and standard deviation of the load can be obtained.

[0111] Further, by using the reliability index value of each time section component, the safety level of the component and the structure is divided and evolutionally evaluated, which specifically includes:

[0112] The safety level index is determined, and the safety level of the structure is divided into four levels, wherein the safety level index β A According to the provisions of the target reliability index in the reliability specifications such as the “Unified Standard for Reliability of Port Engineering Structure”, combined with the safety level of the proposed project, the corresponding target reliability index is selected as the division index of the A-level safety β A ; under the premise that the limit state function and the probability distribution type and statistical parameters of the resistance and load are given, the limit state function is converted into , wherein g is the limit state function; R is the resistance (carrying capacity) of the structure or component; S is the load effect acting on the structure or component; is the modified limit state function for dividing the B-level safety level; ​The limit state function is used for dividing the revised limit state function of the C-level safety level. β B The limit state function is used for dividing the revised limit state function of the C-level safety level. β C The limit state function is used for dividing the revised limit state function of the C-level safety level.

[0113] Table 1: Principles and evaluation criteria of structure safety level division

[0114]

[0115] The structure long-term performance evaluation utilizes the component reliability index β The structure long-term performance evaluation utilizes the component reliability index β A , β B , β C The comparison relationship of the structure long-term performance evaluation utilizes the component reliability index

[0116] In one specific embodiment of the present application, the longitudinal beam structure in a certain high-pile wharf is taken as an example, and the above method is used to evaluate the long-term performance of the structure.

[0117] The structure design service period is 50 years, the safety level is two, C45 concrete is used, the stirrup uses HPB300 steel with a diameter of 8mm, the stirrup ratio is 0.764%, the longitudinal reinforcement uses HRB335 steel with a diameter of 22mm, the longitudinal reinforcement ratio is 0.075%, the protective layer thickness is 50mm, the cross-sectional size is 900mm*1700mm, the corresponding probability distribution type and statistical parameters are shown in Table 2, and the splash zone is selected as the most unfavorable chloride salt erosion working condition (see Table 3) for analysis.

[0118] Table 2: Probability distribution type and statistical parameters of each random variable

[0119]

[0120] Table 3: Initial corrosion time parameters and statistical characteristics of steel bars in splash zone

[0121]

[0122] (1) Chloride ion diffusion and steel bar corrosion analysis

[0123] 1. Initial corrosion time of steel bar

[0124] Firstly, according to the probability distribution of each parameter in Table 2 and Table 3, 10000 groups of random samples are generated by Monte Carlo method, which are substituted into the steel initial corrosion time prediction model for calculation and statistical analysis. The statistical parameters of the initial corrosion time of the steel in the splash zone component are shown in Table 4.

[0125] Table 4 Statistical parameters of the initial corrosion time of the steel in the component (years)

[0126]

[0127] 2. Concrete corrosion cracking time

[0128] After obtaining the initial corrosion time of the steel, further consider the thickness of the protective layer d c , the diameter of the corroded steel d s0 , the standard value of the compressive strength of concrete cube f cu,k , and the water-cement ratio of concrete w / c , etc. random variables, 10000 groups of Monte Carlo random simulation are carried out by using the concrete corrosion cracking time prediction model, and the probability distribution mean and standard deviation of the cracking time of the concrete protective layer of the component are shown in Table 5:

[0129] Table 5 Statistical parameters of the cracking time of the concrete protective layer of the component (years)

[0130]

[0131] 3. Steel corrosion rate

[0132] Further, combined with the distribution form and statistical parameters of the random variables such as the thickness of the concrete protective layer d c , the initial diameter of the steel d s0 , 10000 groups of Monte Carlo simulation are carried out by using the time-varying model of steel corrosion rate and the prediction model of steel corrosion rate, and the time-varying statistical law of the steel corrosion rate of the component is obtained, as shown in Table 6:

[0133] Table 6 Time-varying statistical parameters of the steel corrosion rate of the longitudinal beam (%)

[0134]

[0135] (II) Time-varying degradation analysis of material performance

[0136] 1. Corroded steel strength

[0137] According to the reinforcement cross-section loss rate of the component at different time points and the initial yield strength of the reinforcement, the time-varying statistical parameters of the reinforcement strength of the component can be obtained by using the corrosion reinforcement strength degradation model for 10,000 groups of Monte Carlo simulation, as shown in Table 7.

[0138] Table 7 Time-varying statistical parameters of longitudinal beam reinforcement strength (MPa)

[0139]

[0140] (Three) Corroded reinforcement ductility

[0141] In the example, the force-bearing reinforcement of the component uses HRB335 grade reinforcement, and the yield strain of the uncorroded reinforcement is 1.675x10 -3 , and the ultimate strain is 0.1, and the ratio of the initial ultimate strain to the yield strain is 59.7. According to the corrosion reinforcement ductility degradation model, the ultimate strain to yield strain ratio of the main reinforcement and the stirrup in the splash zone of the component at different service times can be calculated, and the time-varying statistical parameters are shown in Table 8.

[0142] Table 8 Time-varying statistical parameters of longitudinal beam reinforcement ductility

[0143]

[0144] (Four) Concrete strength

[0145] By substituting the mechanical parameters of the stirrup at different times into the concrete strength degradation model, the time-varying statistical parameters of the peak compressive stress and strain of the concrete of the wharf component can be obtained, as shown in Table 9.

[0146] Table 9 Time-varying statistical parameters of concrete peak compressive stress and strain

[0147]

[0148] (Five) Steel and concrete bond strength coefficient

[0149] According to the determined critical time of reinforcement corrosion, the corrosion stage of the reinforcement is first judged, and then the corresponding bond coefficient calculation formula is selected. By using the steel and concrete bond coefficient model for 10,000 groups of Monte Carlo simulation, the time-varying statistical parameters of the bond coefficient of the reinforcement and the concrete of the component can be obtained, as shown in Table 10.

[0150] Table 10 Time-varying statistical parameters of the bond coefficient of the reinforcement and the concrete of the component

[0151]

[0152] (Six) Calculate the time-varying resistance of the component

[0153] According to the time-varying parameters of the obtained component, the resistance values of the samples at each time can be calculated by substituting the time-varying resistance calculation model. The mean resistance, standard deviation and time-varying coefficient corresponding to the resistance probability distribution of the longitudinal beam are shown in Table 11.

[0154] Table 11 Time-varying statistical parameters of longitudinal beam resistance

[0155]

[0156] Accordingly, the curves of the time-varying coefficient of the mean resistance of the longitudinal beam and the time-varying coefficient of the standard deviation with time can be drawn, as shown in Figure 3

[0157] As can be seen from Figure 3 , the mean resistance of the longitudinal beam gradually decreases with the service time, and at the end of the 50-year service, it is about 79% of the initial mean resistance; the standard deviation of the resistance gradually increases with time, and at the end of the 50-year service, it is about 1.45 times of the initial standard deviation.

[0158] (Seven) Establishing a time-varying resistance probability model of the component

[0159] The time-varying coefficients of the mean resistance and the standard deviation of the longitudinal beam are fitted by using a cubic function, and the time-varying resistance probability model of the component is as follows:

[0160] ,

[0161] In the formula, t is the service time, the unit is year; is the time-varying coefficient of the mean resistance of the longitudinal beam at time t; is the time-varying coefficient of the standard deviation of the longitudinal beam resistance at time t.

[0162] (Eight) Evaluation of long-term performance of the structure

[0163] Referring to the "Code for Loads of Port Engineering", the standard value of the one-year stacking load is determined to be 0.45, the variation coefficient is 0.244, the distribution type is extreme value type I, and the stacking load is 30 kPa. The mean value and standard deviation of the load at each time are determined.

[0164] Substituting the mean value and standard deviation of the component resistance and the mean value and standard deviation of the load into the reliability index β , the reliability index of the structure at each time can be calculated by the formula β , as shown in Figure 4 .

[0165] Referring to the relevant provisions in the "Unified Standard for Reliability Design of Port Engineering Structures", the reliability index of the second safety level is 3.5, then β A = 3.5, the corresponding β B = 0.95 * 3.5 = 3.325, β ​C = 0.90 * 3.5 = 3.15.

[0166] The reliability index of 50 years is 3.239, which is between β B and β C and the safety level is C, which indicates that the safety performance of the structure in the target service life cannot meet the requirements of the current national standards and specifications, and has an adverse effect on the safe use under the predetermined working conditions, and it is necessary to re-optimize the design or take appropriate measures to improve its safety.

[0167] In this embodiment, it also includes:

[0168] According to the comparison result of the time-varying resistance probability model of the component and the target reliability index, a sequence arranged in time sequence and containing the safety levels (A-D levels) corresponding to each time section, i.e. the time-varying safety level evolution sequence, is generated, the time-varying safety level evolution sequence is associated with a pre-defined maintenance measure knowledge base, and each measure in the knowledge base records the "safety level triggering condition" and "technical and economic characteristic parameter" applicable to it; for each time section in which the safety level in the evolution sequence is degraded, a weighted operation is performed to quantitatively generate an intervention urgency index according to the level change value and the predicted duration of the level state; according to the safety level of the current time section and the calculated intervention urgency index, all candidate measures whose safety level triggering conditions are met are screened out from the maintenance measure knowledge base to form a preliminary matching measure set; for each measure in the preliminary matching measure set, the technical and economic characteristic parameters and the intervention urgency index are normalized and weighted combined to generate a comprehensive adaptation score of each measure at the current time section; a two-dimensional maintenance decision matrix is constructed according to the comprehensive adaptation scores of all time sections and corresponding measures, and by traversing the matrix and setting a score threshold, a recommended intervention opportunity and the measure combination with the highest comprehensive adaptation score at the opportunity are output.

[0169] It should be noted that the aforementioned steps complete the time-varying reliability evaluation and safety level division of the long-term performance of the structure. However, a deeper problem faced in engineering practice is: how to automatically, scientifically and economically transform the qualitative or semi-quantitative evaluation conclusion such as "the safety level is C" into an executable decision of "when and what specific maintenance measures to take", so as to overcome the disadvantages in the prior art that the evaluation result is disconnected from the maintenance action, the decision relies on subjective experience and lacks quantitative support. Therefore, after generating the time-varying safety level evolution sequence, the embodiment further introduces an intelligent maintenance decision generation method based on the sequence, specifically:

[0170] The form of the time-varying safety level evolution sequence is divided by consecutive safety levels identified by time intervals, for example, the safety level is A for 0-18 years of service, B for 19-28 years, and C for 29-50 years. In addition, a structured maintenance measure knowledge base is constructed in advance to match it. Each specific maintenance measure in the maintenance measure knowledge base corresponds to a clear application condition and evaluation parameter. The application condition refers to the safety level trigger condition that the measure is applicable to, for example, a certain reinforcement measure can be started when the safety registration is reduced to C level. The evaluation parameter is used to quantify the characteristics of the measure, including the technical effectiveness coefficient, the single implementation cost coefficient, and the durability gain coefficient, etc. These coefficients are normalized calibrated according to the engineering practice, literature data or existing engineering projects in the field, so as to facilitate subsequent unified mathematical processing and comparative analysis.

[0171] For the moment when the safety level in the evolution sequence is degraded, the intervention urgency index is calculated, which is quantified by weighting the grade change gradient value and the time length of the expected low level state. The longer the duration, the higher the relative weight of urgency, so the larger the index value, indicating that it needs to be paid attention to as soon as possible.

[0172] Then, according to the safety level at this moment and the calculated intervention urgency index, the screening of the maintenance measure knowledge base is started. By traversing the knowledge base, all candidate measures whose safety level trigger conditions are met by the current level are screened out, such as "crack pressure grouting", "local rust steel rust prevention treatment" and other measures, forming a preliminary matching measure set.

[0173] Each measure in the preliminary matching measure set is scored in detail. The technical and economic characteristic parameters of the measure and the intervention urgency index of the current time section are normalized respectively, and then combined by weighted operation. For example, the "technical effectiveness coefficient" is given a weight of 0.4, the "single implementation cost coefficient" is given a weight of 0.3 (the lower the cost, the higher the score), the "durability gain coefficient" is given a weight of 0.2, and the "intervention urgency index" itself is taken as a demand matching weight parameter, with a weight of 0.1 participating in the operation, and finally a comprehensive adaptation degree score reflecting the comprehensive cost performance and demand fit degree of the measure at this specific time is generated.

[0174] Finally, according to the comprehensive fitness scores of all time sections and corresponding all measures, a two-dimensional maintenance decision matrix is constructed with the time section as the row and the candidate measure as the column. By traversing the matrix and setting an acceptable comprehensive fitness score threshold, the recommended intervention time is output, that is, the time section of the first measure whose score exceeds the threshold. At the same time, the top 1-2 measures with the highest comprehensive fitness scores at this time are output as the recommended measure combination. For example, the output is "in the 29th year, recommend adopting the 'crack pressure grouting' measure".

[0175] In summary, the present application proposes a complete process and calculation method suitable for long-term performance evaluation of reinforced concrete structures in marine chloride salt environments, constructs a full-process evaluation chain from engineering information input, chloride ion diffusion and steel corrosion analysis, material performance time-varying degradation analysis, component time-varying resistance calculation to reliability index determination, and systematically reflects 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 suitable for A-D level safety levels of water transportation infrastructure such as high-pile wharfs is established, which can give the safety level and critical time of the component and structure at different service lives, thereby providing quantitative basis for durability design, structure state evaluation and maintenance and reinforcement decision, effectively serving the design and operation management of coastal port high-pile wharfs and other infrastructure, helping engineering and technical personnel accurately master the performance degradation state of the component in the service period, and scientifically and reasonably developing maintenance and reinforcement schemes, thereby reducing unnecessary maintenance investment and improving the durability and service life of the structure under the premise of ensuring the safety of the structure.

[0176] 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.

[0177] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed components can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0178] The units described as separate components above can or can not be physically separate, and the components shown as units can or can not be physical units; they can be located in one place or distributed on multiple network units; and part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0179] In addition, each functional unit in each embodiment of the present application 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 realized in the form of hardware or in the form of hardware plus software functional unit.

[0180] Those skilled in the art can understand that all or part of the steps of the above method embodiments can be completed by program instruction related hardware, and the aforementioned program can be stored in a computer readable storage medium, and the program executes the steps including the above method embodiments when executed; and the aforementioned storage medium includes mobile storage device, read-only memory (ROM), random access memory (RAM), magnetic disc or optical disc, and various storage program codes.

[0181] Alternatively, the integrated unit of the present application, if implemented in the form of a software function module and sold or used as an independent product, can also be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the embodiments of the present application. The aforementioned storage medium includes mobile storage devices, ROM, RAM, magnetic discs or optical discs, and various storage program codes.

[0182] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for evaluating the performance of a concrete structure in a marine environment, characterized in that, The method comprises the following steps: S1, engineering information and environmental condition input: obtaining basic information of the engineering to be analyzed and service environmental conditions; S2, determining analysis structure and section parameter: selecting structural members requiring performance evaluation according to engineering layout and stress characteristics, and determining calculation diagram, section geometric parameter, reinforcement arrangement and protective layer thickness of each member; S3, establishing random variable and probability model: establishing corresponding random variable and probability distribution model of uncertain parameters such as chloride ion diffusion coefficient, surface chloride ion concentration, critical chloride ion concentration, material strength and member size, as input of subsequent time-varying analysis and Monte Carlo simulation; S4, setting analysis period and time step: setting analysis period according to structure design service life, and discretizing analysis period into time steps to obtain performance evolution process of members at different time sections in the whole life cycle; S5, chloride ion diffusion and reinforcement corrosion analysis: performing chloride ion diffusion and reinforcement corrosion analysis in the set time range to obtain corrosion parameters; S6, time-varying degradation analysis of material performance: performing time-varying degradation analysis of material performance based on the corrosion parameters to obtain degraded material performance parameters; S7, calculating time-varying resistance of the member: substituting the degraded material performance parameters into a member bearing capacity calculation model to obtain resistance values of the structural member changing with time, realizing calculation of time-varying resistance of the member, and establishing a time-varying resistance calculation model; S8, establishing time-varying resistance probability model of the member: using random variables established in step S3 and the time-varying resistance calculation model obtained in step S7, and adopting Monte Carlo simulation probability analysis method to obtain resistance probability distribution of the member at each time section, and establishing a time-varying resistance probability model of the member; S9, evaluating long-term performance of the structure: comparing member resistance with corresponding load effect or target reliability index according to the time-varying resistance probability model of the member to evaluate safety level and performance of the structure at each time section in the analysis period, and obtaining structure performance evaluation results; In the set time range, the chloride ion diffusion and reinforcement corrosion analysis is performed to obtain corrosion parameters, specifically including: Using a reinforcement initial corrosion time prediction model, a reinforcement corrosion rate time-varying model, a reinforcement corrosion rate prediction model and a concrete cracking time prediction model to obtain reinforcement rusting time, corrosion rate, corrosion rate and protective layer cracking time results at each time section; In the set time range, the chloride ion diffusion and reinforcement corrosion analysis is performed to obtain corrosion parameters, specifically including: Using a reinforcement corrosion rate prediction model and a concrete cracking time prediction model to obtain degradation values of reinforcement and concrete material performance and reinforcement and concrete interface bonding performance at each time section.

2. The method for evaluating the performance of a concrete structure in a marine environment according to claim 1, characterized in that, In the S5, a chloride ion diffusion model is further established: ， In the formula, Ct(x, t) represents the chloride ion concentration at a distance x from the concrete surface at time t; t represents time; and x represents the depth from the concrete surface; C0 represents the chloride ion concentration at the concrete surface; erfc represents the complementary error function; β represents the environmental influence coefficient; α represents the chloride ion diffusion coefficient detection method correction coefficient; γ represents the concrete curing time correction coefficient; t0 represents the reference time for the chloride ion diffusion coefficient; D0 represents the chloride ion diffusion coefficient at the reference time; λ represents the aging factor.

3. The method for evaluating performance of a concrete structure in a marine environment according to claim 2, characterized in that: According to the determined chloride diffusion model, when the chloride ion concentration on the surface of the steel bar first reaches the critical concentration, it is considered that the steel bar begins to rust, that is, 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: ， ， wherein X1 is a corrosion time uncertainty parameter; C0 is the surface chloride concentration of concrete; C cr is the critical chloride concentration; D is the chloride diffusion coefficient at the actual time; is the thickness of the concrete cover; is the sensitivity coefficient of chloride concentration with water-cement ratio; is the reference value of the surface chloride concentration of concrete; is the water-cement ratio of concrete; The steel bar corrosion current density is acquired first i corr The steel bar corrosion rate, i.e. the corrosion development rate, is calculated by means of the current density i corr The steel bar corrosion rate is characterized by means of the current density i corr The time-varying model of the steel bar corrosion rate is represented as: ， ， In the formula, is the corrosion current density at the corrosion initiation time; is the water-cement ratio; t p denotes the time elapsed since the initiation of corrosion of the steel bar; denotes the concrete cover thickness.

4. The method for evaluating performance of a concrete structure in a marine environment according to claim 1, characterized in that: If the steel bar is uniformly corroded, the steel bar corrosion will cause the cross-sectional diameter and mechanical properties to gradually degrade over time. Assuming that the steel bar begins to corrode at time t0, the corrosion rate of the corroded steel bar at any time t is represented by the following formula: t corr t The corrosion rate of the corroded steel bar at any time t is represented by the following formula:​ ， ， wherein is the diameter of the steel bar remaining after corrosion; is the original diameter of the steel bar; is the corrosion rate of the steel bar; is the initial corrosion time of the steel bar; is the corrosion rate of the steel bar; The moment when the amount of steel bar corrosion reaches the critical corrosion amount is defined as the time when the initial cracking of the concrete protective layer occurs, and the concrete cracking time prediction model is represented as: ， In the formula, represents t the time of steel bar corrosion rate; represents the time of concrete cracking; is the initial corrosion time of steel bar; represents the critical corrosion depth of steel bar.

5. The method according to claim 1, characterized in that: The strength degradation model of the corroded steel bar is represented as: ， wherein is t the yield strength of the reinforcement at time t; is the initial yield strength of the reinforcement; is t the area loss due to corrosion of the reinforcement at time t; The ductility degradation model of the corroded steel bar is represented 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 initial yield strength of the steel bar; t is the ductility index of the steel bar at the moment The concrete strength degradation model is represented as: ， ， ， ， wherein is the confinement factor; is the peak compressive stress of plain concrete; is the peak compressive stress of confined concrete; is the finite lateral confinement of confined concrete; is the yield stress of the stirrup; is the lateral effective confinement factor, i.e. the ratio of the effective core concrete area to the total core concrete area; is the cross-sectional area of the stirrup after corrosion; is the spacing of the stirrup; d is the cross-sectional effective width, i.e. the cross-sectional width of the core concrete area; is the peak strain of confined concrete; The bond coefficient model of the reinforced concrete is represented as: ， ， In the formula, The bonding coefficients before and after the protective layer cracking, respectively; The steel reinforcement section loss rate; e is the base of natural logarithm.

6. The method according to claim 1, characterized in that: For the reinforced concrete slab and beam members, the bending action is adopted as the force form, the normal section bending capacity is used as the representation index of the member resistance, and the structural resistance is calculated according to the following formula: ， wherein, represents flexural capacity of the member; represents axial compressive strength of concrete; b represents width of the member cross-section; x represents compressive zone height; represents effective height of the member cross-section; represents yield strength of compressive zone reinforcement; represents compressive reinforcement cross-sectional area; represents distance from the point of action of the resultant force on the compressive reinforcement to the edge of the member cross-section; represents bond coefficient between the reinforcement and the concrete; represents tensile strength of the tensile zone reinforcement; represents tensile reinforcement cross-sectional area; In order to depict the time-varying nature of the probability distribution of the member resistance, the time-varying coefficient of the mean value and the time-varying coefficient of the standard deviation of the member resistance are defined, and the time-varying resistance calculation model is represented as: ， wherein is t the mean time-varying coefficient of the member resistance at year is t the standard deviation time-varying coefficient of the member resistance at year is t the mean member resistance at year is t the standard deviation of the member resistance at year is the mean initial member resistance; is the standard deviation of the initial member resistance.

7. The method for evaluating the performance of a concrete structure in a marine environment according to claim 1, wherein Utilizing a reliability index β to characterize the structural reliability, the computational formula can be expressed as: ， wherein 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.

8. A system for assessing the performance of a concrete structure in a marine environment, the system comprising: The concrete structure performance evaluation system comprises a memory and a processor, the memory stores a concrete structure performance evaluation method program, and when the concrete structure performance evaluation method program is executed by the processor, the steps of the concrete structure performance evaluation method according to claim 1 are realized.

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