Concrete beam reliability index calculation method, device and equipment considering uneven corrosion of reinforcing steel bars, storage medium and program product

Abstract

The invention relates to the technical field of computer-aided building design, discloses a concrete beam reliability index calculation method and device considering uneven corrosion of a reinforcing steel bar, electronic equipment, a readable storage medium and a program product, and is used for solving the problem that an existing reliability index calculation method cannot consider nonuniformity of the corrosion of the reinforcing steel bar in the longitudinal direction of the reinforcing steel bar. And the calculation result cannot reflect the real situation. The method comprises the following steps: obtaining design parameters of a concrete beam and a probability distribution function of a corrosion non-uniform coefficient of a reinforcing steel bar; dispersing the concrete beam into a plurality of sampling units, and sampling the corrosion non-uniform coefficient based on a probability distribution function to obtain a sampling coefficient; based on the sampling coefficient and the design parameters of the concrete beam, constructing a bearing performance function of each sampling unit, calculating a function value and judging the simulation failure condition of the concrete beam in the current cycle; and calculating the failure probability of the concrete beam in all cyclic sampling, and calculating the reliable index of the concrete beam according to the failure probability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer-aided architectural design, and in particular to a concrete beam reliability index calculation method considering uneven corrosion of steel bars, a device, an electronic device, a computer storage medium, and a computer program product. BACKGROUND

[0002] Steel bar corrosion is a key factor leading to the performance degradation of concrete structures. Generally, the corrosion of steel bars in concrete is random and uneven. These uneven corrosion often appears in the form of local pitting. Local corrosion pits can cause the local reduction of the cross-sectional area of the steel bar, leading to stress concentration. This stress concentration not only weakens the strength of the steel bar, but also reduces its deformation capacity, having a significant negative impact on the mechanical properties of the steel bar. Since the corroded steel bar often fails at the minimum cross-section, it is crucial to understand the distribution of the minimum cross-section of the corroded steel bar in engineering, for example, the bearing capacity of the concrete structure based on the minimum cross-sectional area of the corroded steel bar determines the actual reliability of the structure.

[0003] Currently, when evaluating the mechanical properties of corroded concrete structures, the reliability index can only be calculated by assuming uniform corrosion of steel bars. The spatial variability of the cross-sectional area distribution of the corroded steel bar is usually ignored, and the unevenness of the steel bar corrosion along the longitudinal direction of the steel bar is not considered, thereby overestimating the reliability of the corroded concrete structure, leading to insufficient calculation of the reliability of the reinforced concrete beam, and making it difficult to approach the real situation. Therefore, considering the characteristics of the uneven corrosion of steel bars along the longitudinal direction in concrete and the change of the failure type of the steel bar with the development of corrosion, there is an urgent need for a concrete beam reliability index calculation method that can consider the uneven corrosion of steel bars, so as to calculate more accurate and realistic concrete beam reliability index values, and to provide a more scientific method for the reliability evaluation of reinforced concrete beams. SUMMARY

[0004] The present application aims to solve the technical problem that the existing reliability index calculation method cannot consider the unevenness of the corrosion of steel bars along the longitudinal direction of the steel bar, resulting in calculation results that cannot reflect the real situation.

[0005] The first aspect of the present application provides a method for calculating a reliability index of a concrete beam considering uneven corrosion of steel bars, comprising: obtaining design parameters of the concrete beam and a probability distribution function of uneven corrosion coefficients of the steel bars; calling a Monte Carlo algorithm for multiple loop sampling, in each loop sampling, discretizing the concrete beam into multiple sampling units, and sampling the uneven corrosion coefficients based on the probability distribution function to obtain sampling coefficients corresponding to each sampling unit; based on the sampling coefficients and the design parameters of the concrete beam, constructing a bearing function function of each sampling unit, and calculating a function value based on the bearing function function of each sampling unit and judging the simulation failure of the concrete beam in the current loop; calculating the failure probability of the concrete beam in all loop samplings, and calculating the reliability index of the concrete beam according to the failure probability.

[0006] Optionally, in the first implementation manner of the first aspect of the present application, after the concrete beam is discretized into multiple sampling units, the method further comprises: obtaining the load type and the sampling statistical characteristics of each sampling unit, and determining the load effect parameter of each sampling unit. The bearing function function of each sampling unit is constructed based on the sampling coefficients and the design parameters of the concrete beam, comprising: judging the failure type of each sampling unit based on the sampling coefficients and the design parameters of the concrete beam; calculating the tensile bearing capacity of the steel bars of each sampling unit based on the failure type, and calculating the unit bending bearing capacity according to the tensile bearing capacity of the steel bars; and constructing the bearing function function based on the unit bending bearing capacity of each sampling unit and the load effect parameter.

[0007] Optionally, in the second implementation manner of the first aspect of the present application, the sampling coefficients comprise sampling coefficients corresponding to each steel bar in each sampling unit; after the design parameters of the concrete beam are obtained, the method further comprises: calculating critical parameters of the steel bar unit according to the design parameters of the concrete beam; and the failure type of each sampling unit is judged based on the sampling coefficients and the design parameters of the concrete beam, comprising: if the sampling coefficients of all steel bar units contained in the current sampling unit are less than the critical parameters, the sampling unit is in ductile failure; if the sampling coefficient of any one steel bar unit contained in the current sampling unit is greater than or equal to the critical parameters, the sampling unit is in brittle failure.

[0008] Optionally, in the third implementation manner of the first aspect of the present application, comprising: when the failure type is ductile failure, the calculation formula of the tensile bearing capacity of the steel bars of each sampling unit is: When the failure type is brittle failure, the calculation formula of the tensile bearing capacity of the steel bars of each sampling unit is: wherein, represents the tensile load bearing capacity of a sampling unit; n represents the number of tensile reinforcement in each sampling unit; i represents the i root reinforcement, i= (1, 2, 3, …, n ); represents the tensile load bearing capacity of the i root reinforcement in a sampling unit; is the yield strength of the i root reinforcement based on the minimum corrosion cross-sectional area; is the minimum cross-sectional area of the i root reinforcement.

[0009] Optionally, in the fourth implementation form of the first aspect of the present application, the expression of the load bearing function is: wherein, represents the load bearing function, represents the unit flexural load bearing capacity of each sampling unit; represents the load effect parameter of each sampling unit; j（ 1, 2, 3 ,…,m） ; m represents the number of sampling units; the load bearing function of each of the sampling units is used to determine the simulated failure of the concrete beam in the current cycle, including: when the load bearing function values of all the sampling units in the current cycle sampling are greater than or equal to 0, the concrete beam in the current cycle is safe; when the load bearing function value of any one of the sampling units in the current cycle sampling is less than 0, the concrete beam in the current cycle is failed.

[0010] Optionally, in the fifth implementation form of the first aspect of the present application, the calculation of the failure probability of the concrete beam in the whole cycle sampling, and the calculation of the reliability index of the concrete beam according to the failure probability include: obtaining the cycle sampling number, and counting the failure number of the concrete beam in the whole cycle sampling process; calculating the failure probability based on the failure number and the cycle sampling number; and calculating the reliability index of the concrete beam according to the failure probability and a preset probability cumulative distribution function.

[0011] The second aspect of the present application provides a device for calculating a reliability index of a concrete beam considering uneven corrosion of steel bars, comprising: a data acquisition module configured to acquire design parameters of the concrete beam and a probability distribution function of uneven corrosion coefficients of the steel bars; a sampling simulation module configured to call a Monte Carlo algorithm to perform multiple loop sampling, in each loop sampling, discretize the concrete beam into multiple sampling units, sample the uneven corrosion coefficients based on the probability distribution function to obtain sampling coefficients corresponding to each sampling unit, and based on the sampling coefficients and the design parameters of the concrete beam, construct a load-carrying function of each sampling unit, and calculate a function value based on the load-carrying function of each sampling unit and judge a simulation failure condition of the concrete beam in the loop; and an index calculation module configured to calculate a failure probability of the concrete beam in all loop samplings, and calculate a reliability index of the concrete beam according to the failure probability.

[0012] The third aspect of the present application provides a device for calculating a reliability index of a concrete beam considering uneven corrosion of steel bars, comprising: a memory and at least one processor, the memory storing instructions; the at least one processor calling the instructions in the memory to make the device for calculating a reliability index of a concrete beam considering uneven corrosion of steel bars perform the steps of the method for calculating a reliability index of a concrete beam considering uneven corrosion of steel bars described above.

[0013] The fourth aspect of the present application provides a computer-readable storage medium, the computer-readable storage medium storing instructions, when the instructions are run on a computer, making the computer perform the steps of the method described above.

[0014] The fifth aspect of the present application provides a computer program product, comprising computer programs / instructions, when the computer programs / instructions are executed by a processor, realizing the steps of the method for calculating a reliability index of a concrete beam considering uneven corrosion of steel bars described above.

[0015] The technical scheme provided by the present application comprises the following steps: obtaining the design parameters of a concrete beam and a probability distribution function of a non-uniform corrosion coefficient of steel bars; calling a Monte Carlo algorithm to perform multiple loop sampling, in each loop sampling, discretizing the concrete beam into multiple sampling units, sampling the non-uniform corrosion coefficient based on the probability distribution function to obtain a sampling coefficient corresponding to each sampling unit; based on the sampling coefficient and the design parameters of the concrete beam, constructing a bearing function function of each sampling unit, and calculating a function value based on the bearing function function of each sampling unit and judging the simulation failure of the concrete beam in the loop; calculating the failure probability of the concrete beam in all loop samplings, and calculating a reliability index of the concrete beam according to the failure probability. The reliability index calculation method can consider the non-uniform corrosion of the steel bars contained in the concrete beam, and can calculate more accurate and real concrete beam reliability index values. The device, electronic equipment, computer readable storage medium and computer program product provided by the present application also solve the corresponding technical problems. BRIEF DESCRIPTION OF DRAWINGS

[0016] The drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute improper limitations on the present application. In the drawings: Figure 1 A flowchart of a first embodiment of the concrete beam reliability index calculation method considering the non-uniform corrosion of steel bars in the embodiments of the present application; Figure 2 A flowchart of a second embodiment of the concrete beam reliability index calculation method considering the non-uniform corrosion of steel bars in the embodiments of the present application; Figure 3 A structural diagram of a concrete beam in the concrete beam reliability index calculation method considering the non-uniform corrosion of steel bars in the embodiments of the present application; Figure 4 A diagram showing the influence of corrosion rate on reliability index in the embodiments of the present application; Figure 5 A diagram showing the influence of steel bar diameter on reliability index in the embodiments of the present application; Figure 6 A diagram showing the influence of different failure modes on reliability index under one corrosion rate in the embodiments of the present application; Figure 7 A diagram showing the influence of different failure modes on reliability index under another corrosion rate in the embodiments of the present application; Figure 8 A diagram showing the relationship between corrosion rate and reliability index in the embodiments of the present application; Figure 9A diagram of a relationship between the diameter of the steel bar and the reliability index in an embodiment of the present application Figure 10 A diagram of an embodiment of a device for calculating the reliability index of a concrete beam considering uneven corrosion of the steel bar in an embodiment of the present application Figure 11 A diagram of an embodiment of a device for calculating the reliability index of a concrete beam considering uneven corrosion of the steel bar in an embodiment of the present application Figure 12 A diagram of the principle of a computer-readable medium in an embodiment of the present application. DETAILED DESCRIPTION

[0017] Exemplary embodiments of the present application will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, can be embodied in various forms, and should not be construed as being limited to only the embodiments set forth herein. Rather, the exemplary embodiments are provided as a full and enabling disclosure of the application, and are presented to provide an enabling concept of the application to those skilled in the art. Like reference numerals refer to like elements throughout the several views of the drawings, and thus repeated description is omitted.

[0018] Features, structures, characteristics or other details described in relation to one particular embodiment are not excluded from being combinable with one or more other embodiments, as long as such combinations are within the scope of the technical concept of the present application.

[0019] In the description of the specific embodiments, features, structures, characteristics or other details described in relation to the present application are to enable those skilled in the art to fully understand the embodiments. However, it is not excluded that one or more of the features, structures, characteristics or other details can not be practiced by those skilled in the art without the specific feature, structure, characteristic or other detail.

[0020] The flowcharts shown in the drawings are only exemplary illustrations, and do not necessarily include all contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be further divided, and some operations / steps can be combined or partially combined, so that the actual execution order can be changed according to the actual situation.

[0021] The block diagrams shown in the drawings are only functional entities, and do not necessarily correspond to physically independent entities. That is, the functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0022] The term "and / or" or "and / or" includes all combinations of one or more of the associated listed items.

[0023] Please refer toFigure 1 The first embodiment of the method for calculating the reliability index of a concrete beam considering uneven corrosion of steel bars in the embodiments of the present application comprises the following steps: S101, obtaining the design parameters of the concrete beam and the probability distribution function of the uneven corrosion coefficient of the steel bars; It can be understood that the execution subject of the present application can be a concrete beam reliability index calculation device considering uneven corrosion of steel bars, and can also be a terminal or a server, which is not limited here. The server is taken as an example for illustration in the embodiments of the present application.

[0024] After receiving the request for calculating the reliability index of the concrete beam, the server first obtains the relevant data required for calculating the reliability index. The relevant data includes the design parameters of the concrete beam. Based on the design parameters of the concrete beam, the relevant information of the type of steel bars contained therein can be further obtained. Since the corrosion condition of the steel bars is related to the type of the steel bars, the probability distribution function of the uneven corrosion coefficient of the steel bars is determined based on the type of the steel bars in the present embodiment. The uneven corrosion coefficient in the present application represents the unevenness parameter of the longitudinal distribution of the corrosion of the steel bars, which can be obtained by experimental data fitting and is used to describe the ratio of the minimum cross-sectional area to the average cross-sectional area.

[0025] Specifically, the probability distribution of the uneven corrosion coefficient can be obtained by combining the experimental and data fitting methods based on the existing research results, the relationship between the uneven corrosion coefficient and the average cross-sectional corrosion rate and the model of the uneven corrosion coefficient of the steel bars are established, and the distribution of the uneven corrosion coefficient of the steel bars is obtained.

[0026] S102, calling the Monte Carlo algorithm for multiple loop sampling, and in each loop sampling, discretizing the concrete beam into multiple sampling units and sampling the uneven corrosion coefficient based on the probability distribution function to obtain the sampling coefficient corresponding to each sampling unit; The Monte Carlo algorithm is also called statistical simulation method or statistical experiment method. In the present embodiment, the idea of the Monte Carlo algorithm is mainly used for loop sampling, and the reliability index of the concrete beam is further calculated according to the calculation results obtained after loop sampling.

[0027] Before performing specific sampling in the present embodiment, the related parameters of the Monte Carlo algorithm are first determined, including the number of loop samplings and the number of sampling units; wherein the number of sampling units refers to the number of sampling units into which the concrete beam is discretized in each loop sampling process.

[0028] For each loop sampling, the probability distribution function obtained in the foregoing step is used to sample each steel bar in each sampling unit after discretization to obtain the sampling coefficient corresponding to each steel bar.

[0029] S103, based on the sampling coefficient and the design parameter of the concrete beam, a bearing function function of each sampling unit is constructed, and a function value is calculated based on the bearing function function of each sampling unit and a simulation failure condition of the concrete beam in the current cycle is judged; For each sampling unit in each sampling cycle, after obtaining the sampling coefficient corresponding to the steel bar in each sampling unit, the minimum cross-sectional area of the steel bar under various corrosion conditions can be further calculated based on the uneven corrosion coefficient obtained by sampling. The minimum cross-sectional area of each steel bar in each sampling unit is further used to calculate the tensile bearing capacity and the bending bearing capacity corresponding to the current sampling unit, and the function value of the bearing function function is calculated based on the tensile bearing capacity, the bending bearing capacity of each sampling unit and the load effect value of each unit. The bearing function function in the embodiment is a function for evaluating the safety state of the concrete beam, which is represented as the difference between the unit bending bearing capacity and the load effect.

[0030] Based on the calculated function value of the bearing function function, the simulation failure condition of the concrete beam in the current cycle can be determined, and the simulation failure condition of each sampling cycle is recorded and counted.

[0031] S104, the failure probability of the concrete beam in the whole cycle sampling is calculated, and the reliability index of the concrete beam is calculated according to the failure probability.

[0032] Based on the failure probability of the concrete beam in the whole cycle sampling, the reliability index of the concrete beam is calculated according to the failure probability.

[0033] In a preferred embodiment, the influence of the diameter of the steel bar, the failure type and the corrosion rate on the reliability of the corroded concrete beam can be considered in software such as MATLAB, the simulation calculation is carried out, and the calculation method of the reliability index is proposed based on the simulation calculation result, so as to further speed up the calculation; at the same time, with the help of the software simulation process, the number of sampling cycles can be further increased, so that the reliability index of the concrete beam calculated is closer to the actual situation and the reliability is improved.

[0034] The beneficial effects of the embodiment of the present application are that the uneven corrosion of the steel bar can be considered when calculating the reliability index of the concrete beam, and the calculated concrete beam reliability index value is more accurate and close to the actual situation.

[0035] Please refer to Figures 2-9 The second embodiment of the concrete beam reliability index calculation method considering the uneven corrosion of the steel bar in the embodiment of the present application comprises: S201, obtaining the design parameter of the concrete beam and the probability distribution function of the uneven corrosion coefficient of the steel bar; Before performing the specific reliable index calculation, first, the design parameters of the concrete beam are obtained by querying the design data of the concrete beam, the use environment conditions, the detection data or the specification standards, and the design parameters specifically include: (1) Geometric parameters of the concrete beam: including the diameter d of the steel bar used in the concrete beam, the number n of the steel bars, the width b of the concrete beam, the height h of the concrete beam, the length l and the like information; (2) Material parameters: including the compressive strength of the concrete , the yield strength of the steel bar , the type of the steel bar (or the model of the steel bar, such as HPB300 or HRB400); (3) Load parameters: including the dead load G and the live load Q; (4) Environmental and corrosion parameters: including the corrosion rate , the average sectional corrosion rate , the maximum sectional corrosion rate .

[0036] Among them, the environmental and corrosion parameters in the (4) can be obtained by experiment, detection specification or simulation to establish a regression model, for example, the corrosion rate can be obtained by an electrochemical detection method or an empirical model based on environmental conditions, and the average sectional corrosion rate can be measured by steel bar sampling or calculated based on a corrosion prediction model; specific ways are not described here.

[0037] In a specific embodiment, the probability distribution function of the corrosion unevenness coefficient of the steel bar also needs to be obtained, wherein the actual data are obtained by experiment, and a regression model is established to obtain the theoretical value expression of the corrosion unevenness coefficient R as follows: Among them, is the average value of the corrosion sectional area of the steel bar, with the unit of square millimeter (mm 2 ); is the minimum sectional area of the corroded steel bar, with the unit of square millimeter (mm 2 ); represents the sectional area of the non-corroded steel bar, with the unit of square millimeter (mm 2 ); is the average sectional corrosion rate; is the maximum sectional corrosion rate; the regression parameters a, b and c are respectively regression parameters obtained by regression analysis on the relationship between the maximum sectional corrosion rate and the average sectional corrosion rate; for example, in a specific embodiment, the regression parameters a, b and c are obtained by nonlinear regression analysis on the corrosion experimental data of HPB300 and HRB400 steel bars, and are suitable for steel bars with a diameter d of 8-14 mm.

[0038] Different steel types have certain influence on the regression parameters. In a specific example, refer to Table 1 for specific values of the regression parameters: Table 1: Regression parameter values of different steels where d is the diameter of the steel.

[0039] Since the corrosion unevenness coefficient R obeys the extreme value type I distribution, the distribution parameters are related to the diameter of the steel, the corrosion rate and the average corrosion rate Therefore, the probability distribution function of the corrosion unevenness coefficient R is as follows: where μ is the expectation of R; and σ is the standard deviation of R.

[0040] Specifically, first, the distribution parameters of the unevenness coefficient R, including the expectation μ and the standard deviation σ of R, are obtained through experiments and regression analysis; after obtaining the corrosion rate , the average sectional corrosion rate , the expectation μ and the standard deviation σ of the unevenness coefficient R, in a specific implementation, refer to Table 2 for specific values of the distribution parameters of the unevenness coefficient R in a specific case: Table 2: Distribution parameters of the unevenness coefficient R S202, calling the Monte Carlo algorithm for multiple loop sampling, in each loop sampling, the concrete beam is discretized into multiple sampling units; Before performing the specific sampling operation, the Monte Carlo parameters are obtained in this embodiment, including the sampling number N and the unit discretization number m. Please refer to Figure 3 , which is a schematic diagram of a concrete beam with a length of l, a height of h, and a side width of b. As can be seen from the Figure 3 left side of the concrete beam side view, during the loop sampling, the concrete beam can be discretized into multiple samples with a fixed length of m represents the number of unit discretization; each unit is represented by j (j = 1, 2, 3, …, m); as can be seen from the Figure 3 right side of the concrete beam side view, a concrete beam contains n steels, and each steel is represented by i (i = 1, 2, 3, …, n).

[0041] S203, sampling the corrosion unevenness coefficient based on the probability distribution function to obtain the sampling coefficient corresponding to each sampling unit; Considering the non-uniformity of steel bar corrosion, the non-uniformity coefficient R is randomly sampled based on the probability distribution function, and for each steel bar i in each sampling unit j, a non-uniformity coefficient value is randomly sampled from the distribution of the non-uniformity coefficient R as the sampling coefficient of each unit, denoted as ; The minimum cross-sectional area of each steel bar is calculated : wherein, is the average corrosion cross-sectional area, d is the diameter of the steel bar, is the corrosion rate; the constant 0.0232 is obtained based on regression analysis of steel bar corrosion experimental data, and represents a correction coefficient of the corrosion rate on the diameter of the steel bar.

[0042] In a preferred embodiment, after the concrete beam is discretized into a plurality of sampling units, the load type and the sampling statistical characteristics of each sampling unit are obtained, and the load effect parameter of each sampling unit is determined. Specifically, the load effect of each sampling unit is obtained using an algorithm . Specifically, for each Monte Carlo sampling, the load value is randomly sampled from the distribution of the dead load G and the live load Q, and based on the design information of the concrete beam, the bending moment distribution of the current concrete beam is calculated, and based on the bending moment distribution, the load effect (e.g., the bending moment value at the center of each unit j) of each sampling unit j is calculated.

[0043] In a specific embodiment, the reliability index can be calculated for a designed reinforced concrete simply supported beam. Taking a specific example, the cross-sectional size of the reinforced concrete simply supported beam is 200mm x 500mm, the length is 6m, 6 steel bars of the same diameter are arranged in the tensile zone, the concrete cover thickness is 25mm, and the design reference period is 50 years. For longitudinal spatial variability analysis, it is crucial to select an appropriate unit length. Assuming that the steel reinforced concrete beam is well anchored at both ends, as long as the unit length is not less than twice the diameter of the steel bar, the stress concentration phenomenon caused by non-uniform corrosion can be ignored, and each unit of the steel bar can reach its yield strength. Specifically, a 50mm unit cutoff length can be selected for spatial analysis of the corroded beam.

[0044] Assuming a corroded beam is subjected to a uniformly distributed dead load G and a live load Q, the dead and live loads on the corroded beam are calculated based on the "Code for Design of Concrete Structures" (GB50010-2010). The partial factors in my country's standards for building structure reliability design are mainly based on specific actions and structural resistance probability characteristics from the 1980s. The statistical information of random variables can be described by the mean coefficient, coefficient of variation, and probability distribution. This invention does not consider the influence of time on the reliability of the corroded beam; therefore, the temporal characteristics of the load are mainly reflected in the values ​​of its distribution parameters, as shown in Table 3. For example, the coefficient of variation of the dead load is small, reflecting its invariance, while the coefficient of variation of the live load is large, meeting the conditions of practical engineering.

[0045] Table 3 Loads, Geometric Dimensions and Material Parameters S204. Determine the failure type of each sampling unit based on the sampling factor and the design parameters of the concrete beam; Considering the variability of the corrosion rate of the reinforcing steel section along the longitudinal direction (spatial domain), the corroded concrete beam is discretized into m equal elements along the longitudinal direction. The tensile bearing capacity of the corroded reinforcing steel in each element is... It is related to the type of damage it causes.

[0046] Therefore, after obtaining each sampling coefficient, the sampling coefficients of all sampling units in a single sampling are... Critical parameters of the reinforcing bars respectively In comparison; based on sampling coefficient and critical parameters The magnitude relationship is used to determine the damage type of each sampling unit. The critical parameter described in this embodiment... It is a threshold used to distinguish between ductile and brittle failure of steel bars. It is related to the diameter of the steel bar and can be obtained through experimental statistical analysis.

[0047] Specifically, the critical parameter can be determined by obtaining data from experiments and performing statistical analysis. This is related to the diameter of the reinforcing steel. In a specific example, considering that the failure type of the reinforcing steel changes with the development of corrosion (i.e., from ductile to brittle), the method for assessing the flexural capacity of corroded beams needs to be adjusted accordingly. Based on existing research and time-delay data, the critical non-uniformity coefficient of failure type for corroded reinforcing steel with diameters of 10mm and 14mm in this embodiment is... We take 1.31 and 1.30 respectively to correspond to the threshold for the transition of corroded steel bars from ductile to brittle.

[0048] Specifically, for a sampling unit, if the sampling factor of all reinforcement units in that unit is... All are less than the critical parameter If the failure type of the sampling unit is ductile failure (i.e. all the steels in the unit are in ductile failure), the steel tensile bearing capacity of the sampling unit is expressed as: If the sampling coefficient of any steel in the sampling unit is greater than or equal to the critical parameter , the current failure type is brittle failure.

[0049] S205, the steel tensile bearing capacity of each sampling unit is calculated based on the failure type, and the unit bending bearing capacity is calculated according to the steel tensile bearing capacity; For a sampling unit, if the failure type of the sampling unit is ductile failure (i.e. all the steels in the unit are in ductile failure), the steel tensile bearing capacity of the sampling unit is expressed as: Wherein, represents the overall steel tensile bearing capacity of the sampling unit; n is the number of tensile steels; is the minimum cross-sectional area of the i-th steel, in square millimeters (mm2); is the yield strength of the i-th steel based on the minimum corrosion cross-sectional area, in Newton per square millimeter (N / mm2).

[0050] In a preferred embodiment, since remains basically unchanged with the development of corrosion, when the failure type is ductile failure, the steel tensile bearing capacity of the sampling unit can be simplified as: Wherein, is the yield strength of the uncorroded steel, in Newton per square millimeter (N / mm 2 ).

[0051] For a sampling unit, if the failure type of the sampling unit is brittle failure (i.e. at least one steel in the unit is in brittle failure), the steel tensile bearing capacity of the sampling unit is expressed as: Wherein, .

[0052] Similarly, in a preferred embodiment, since remains basically unchanged with the development of corrosion, when the failure type is brittle failure, the steel tensile bearing capacity of the sampling unit can be simplified as: Wherein, is the yield strength of the uncorroded steel, in Newton per square millimeter (N / mm 2 ), Next, the flexural capacity of the steel bar is calculated according to the tensile capacity calculation unit. The calculation does not consider the influence of the degradation of the bonding performance between the steel bar and the concrete, and the flexural capacity of the corroded beam is calculated based on the minimum cross-sectional area of the corroded steel bar , the expression is: wherein, is the tensile capacity of the corroded steel bar calculated in the previous step, and the unit is Newton (N); is the compressive strength of the concrete, and the unit is megapascal (MPa); b is the width of the beam, and the unit is millimeter (mm); h is the height of the concrete beam, and the unit is millimeter (mm).

[0053] The tensile capacity of the steel bar of each sampling unit is substituted into the above expression to obtain the flexural capacity of each sampling unit , wherein the flexural capacity of each unit can be represented by .

[0054] S206, based on the unit flexural capacity of each sampling unit and the load effect parameter, a load function is constructed; based on the flexural capacity of the sampling unit and the load effect of each sampling unit obtained in the foregoing step S203, a target corroded beam function is constructed, and the expression is: wherein, X= represents the combination of q influencing factors of the corroded beam, is the load effect of the j unit.

[0055] If and only if the values of m (j=1, 2, …, m) are all greater than or equal to 0, it is considered that the corroded beam is safe and reliable in the “simulation test” obtained this time, and the failure number is recorded as =0; If any one of the m (j=1, 2, …, m) is less than 0, it is considered that the corroded beam fails in this “simulation test”, and the failure number is recorded as =1.

[0056] S207, the failure number of the concrete beam judged as failure in the whole cyclic sampling process is counted, the failure probability is calculated based on the failure number and the cyclic sampling number, and the reliability index of the concrete beam is calculated according to the failure probability and the preset probability cumulative distribution function.

[0057] Based on the repeated N times of sampling experiments, N judgment results can be obtained, and the reliability index of the corroded concrete beam is calculated based on the obtained results, and the specific expression is: wherein, () is the probability cumulative distribution function of the standard normal function, is the failure probability, and its expression is: wherein, N is the sampling number, and n' = {1, 2,..., N}.

[0058] In a preferred embodiment, the failure probability calculation accuracy depends on the sampling number N, and since the failure probability obtained based on the Monte Carlo method is only an estimated value , and its variance calculation expression is: When a 95% confidence level is selected, the sampling error calculation expression of the Monte Carlo method is: wherein, is the upper 0.05 quantile of the standard normal distribution.

[0059] Expressed by the relative error, the expression is: Considering that is a smaller value, so: Taking ε = 0.2, we have: According to the above formula, it can be seen that the accuracy of the failure probability depends on the size of the sampling number. In a specific embodiment, the reliability index β of the ductile failure and the brittle failure is taken as 3.2 and 3.7 respectively, and the corresponding is 6.871 × 10 -4 and 1.08 × 10 -4 , respectively, and the corresponding sampling number is calculated to be N≥1.46 × 105 and N≥9.28 × 105, respectively. Therefore, in order to ensure the accuracy of the scheme in this embodiment, in a preferred embodiment, the sampling number is taken as 100,000 times.

[0060] In a specific embodiment, the calculation model established in this embodiment can be simulated and calculated by software such as MATLAB when considering the influence of the steel bar diameter, the failure type and the corrosion rate on the reliability index of the corroded concrete beam. In order to ensure the accuracy and universality of the calculation method of the present application, multiple working conditions are simulated, and the specific calculation working conditions used are shown in Table 4: Table 4 Calculation working conditions Based on the calculation scheme described in the embodiment, a specific example of the failure probability of each average corrosion rate under different working conditions is shown in Table 5: Table 5 Failure probability of each average corrosion rate Based on the average corrosion rate, the reliability index of each average corrosion rate under different working conditions is calculated, as shown in Table 6: Table 6 Reliability index of each average corrosion rate In Table 6, inf represents infinity, and the corresponding failure probability is 0.

[0061] In a specific embodiment, based on the technical scheme in the embodiment, the reliability index under different conditions can be calculated and a chart can be generated for visualization, so as to compare the reliability index of the concrete beam under different corrosion conditions under different conditions. Please refer to Figures 4-9 , these figures respectively show the specific calculation results and variation of the reliability index of the concrete beam under different corrosion rates, different diameters of reinforcing steel bars and different failure modes; wherein, Figure 4 is a schematic diagram of the influence of corrosion rate on reliability index, Figure 5 is a schematic diagram of the influence of reinforcing steel bar diameter on reliability index, Figure 6 and Figure 7 are respectively a schematic diagram of the influence of different corrosion rates on reliability index under different failure modes, Figure 8 is a schematic diagram of the relationship between corrosion rate and reliability index, Figure 9 is a schematic diagram of the relationship between reinforcing steel bar diameter and reliability index.

[0062] In the embodiment of the application, the limit state equation of the corroded concrete beam is established based on theoretical analysis, and the Monte Carlo method is used to numerically calculate the reliability index of the corroded concrete beam. Based on this, the beneficial effects of the embodiment of the application are: the characteristics of the longitudinal uneven corrosion of the reinforcing steel bars in the concrete are innovatively considered, the influence of the reinforcing steel bar failure type, the corrosion rate and the reinforcing steel bar diameter on the reliability index of the concrete beam is studied, and a calculation method of the reliability index considering the unevenness of the longitudinal corrosion of the reinforcing steel bars is proposed, so that the calculation result is more realistic and reliable, and can better reflect the actual situation, and a more scientific method for reliability evaluation of existing corroded concrete beams is provided.

[0063] The calculation method of the reliability index of the concrete beam considering the uneven corrosion of the reinforcing steel bars in the embodiment of the application is described above, and the calculation device of the reliability index of the concrete beam considering the uneven corrosion of the reinforcing steel bars in the embodiment of the application is described below, please refer to Figure 10 , one embodiment of the calculation device of the reliability index of the concrete beam considering the uneven corrosion of the reinforcing steel bars in the embodiment of the application comprises: The data acquisition module 1001 is configured to acquire design parameters of the concrete beam and a probability distribution function of an uneven corrosion coefficient of the steel bars. The sampling simulation module 1002 is configured to call a Monte Carlo algorithm to perform multiple loop samplings, sample the uneven corrosion coefficient based on the probability distribution function in each loop sampling, and obtain a sampling coefficient corresponding to each sampling unit. The index calculation module 1003 is configured to calculate a failure probability of the concrete beam in all loop samplings, and calculate a reliability index of the concrete beam according to the failure probability.

[0064] The technical effect of the embodiment of the present application is that the device can consider the uneven corrosion of the steel bars when calculating the reliability index of the concrete beam, and the calculated reliability index of the concrete beam is more accurate and closer to the actual situation.

[0065] In another embodiment of the present application, the acquisition module 1001 is further configured to acquire a load type and sampling statistical characteristics of each sampling unit, and determine a load effect parameter of each sampling unit. The sampling simulation module 1002 is further configured to determine a failure type of each sampling unit based on the sampling coefficient and the design parameters of the concrete beam, calculate a steel bar tensile bearing capacity of each sampling unit based on the failure type, calculate a unit bending bearing capacity according to the steel bar tensile bearing capacity, and construct a bearing function function based on the unit bending bearing capacity of each sampling unit and the load effect parameter.

[0066] In another embodiment of the present application, the sampling coefficient includes a sampling coefficient corresponding to each steel bar in each sampling unit. The acquisition module 1001 is further configured to calculate a critical parameter of the steel bar unit according to the design parameters of the concrete beam. The determination of the failure type of each sampling unit based on the sampling coefficient and the design parameters of the concrete beam includes that if the sampling coefficients of all steel bar units included in the current sampling unit are less than the critical parameter, the sampling unit is in ductile failure, and if the sampling coefficient of any one steel bar unit included in the current sampling unit is greater than or equal to the critical parameter, the sampling unit is in brittle failure.

[0067] In another embodiment of the present application, when the failure type is ductile failure, the calculation formula of the steel bar tensile bearing capacity of each sampling unit is: When the failure type is brittle failure, the formula for calculating the tensile load bearing capacity of the reinforcement of each sampling unit is: wherein, represents the tensile load bearing capacity of a sampling unit; n represents the number of tensile reinforcement in each sampling unit; i represents the i th reinforcement, i= (1, 2, 3, …, n ); represents the tensile load bearing capacity of the i th reinforcement in a sampling unit; is the yield strength of the i th reinforcement based on the minimum corrosion cross-sectional area; is the minimum cross-sectional area of the i th reinforcement.

[0068] In another embodiment of the present application, the expression of the load bearing function is: wherein, represents the load bearing function, represents the unit flexural load bearing capacity of each sampling unit; represents the load effect parameter of each sampling unit; j (1, 2, 3, …, m ); m represents the number of sampling units; The judgment of the simulated failure of the concrete beam in the current cycle based on the load bearing function of each sampling unit includes: when the load bearing function values of all the sampling units in the one-cycle sampling are greater than or equal to 0, the concrete beam in the current cycle is safe; when the load bearing function value of any one of the sampling units in the one-cycle sampling is less than 0, the concrete beam in the current cycle is failed.

[0069] In another embodiment of the present application, the calculation of the failure probability of the concrete beam in the whole-cycle sampling, and the calculation of the reliability index of the concrete beam according to the failure probability includes: obtaining the number of cycle samplings, and counting the failure number of times of the concrete beam judged as failed in the whole-cycle sampling process, calculating the failure probability based on the failure number of times and the number of cycle samplings; calculating the reliability index of the concrete beam according to the failure probability and the preset probability cumulative distribution function.

[0070] In another embodiment of this application, the specific method by which the concrete beam reliability index calculation device considering uneven corrosion of reinforcing bars implements the concrete beam reliability index calculation method considering uneven corrosion of reinforcing bars can be referred to the content of the foregoing method embodiment, and will not be repeated here.

[0071] The technical effect of this invention is that, based on the above-mentioned device, when calculating the reliability index of concrete beams, the uneven corrosion of steel bars can be taken into account, and the calculated reliability index value of concrete beams is more accurate and closer to the real situation.

[0072] The corresponding description of the reliability index calculation system for concrete beams that considers uneven corrosion of reinforcing bars provided in this invention can be found in the above embodiments, and will not be repeated here.

[0073] Based on the same inventive concept, this specification also provides an electronic device for calculating the reliability index of concrete beams considering uneven corrosion of reinforcing bars. The electronic device for calculating the reliability index of concrete beams considering uneven corrosion of reinforcing bars in this embodiment of the invention will be described in detail below from the perspective of hardware processing.

[0074] Figure 11 This is a schematic diagram of an electronic device provided as an embodiment of this specification. Refer to the following... Figure 11 To describe the electronic device 1100 according to this embodiment of the invention. Figure 11 The electronic device 1100 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0075] like Figure 11 As shown, the electronic device 1100 is presented in the form of a general-purpose computing device. The components of the electronic device 1100 may include, but are not limited to: at least one processing unit 1110, at least one storage unit 1120, a bus 1130 connecting different system components (including storage unit 1120 and processing unit 1110), a display unit 1140, etc.

[0076] The storage unit stores program code that can be executed by the processing unit 1110, causing the processing unit 1110 to perform the steps described in the processing method section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 1110 can perform, for example... Figure 1 The steps are shown.

[0077] The storage unit 1120 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 11201 and / or a cache storage unit 11202, and may further include a read-only memory unit (ROM) 11203.

[0078] The storage unit 1120 may also include a program / utility 11204 having a set (at least one) program module 11205, such program module 11205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0079] Bus 1130 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0080] Electronic device 1100 can also communicate with one or more external devices 1000 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 1100, and / or with any device that enables electronic device 1100 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 1150. Furthermore, electronic device 1100 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 1160. Network adapter 1160 can communicate with other modules of electronic device 1100 via bus 1130. It should be understood that, although... Figure 11 As not shown, other hardware and / or software modules can be used in conjunction with electronic device 1100, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0081] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described in this invention can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, or network device, etc.) to execute the method described above according to this invention. When the computer program is executed by a data processing device, it enables the computer-readable medium to implement the method described above, i.e.: as... Figure 1 or Figure 2 The method shown.

[0082] Figure 12A schematic diagram of a computer readable medium according to an embodiment of the present disclosure.

[0083] Implementation Figure 1 Or Figure 2 The computer program of the method shown can be stored on one or more computer readable media. The computer readable media can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0084] The computer readable storage medium can include a data signal carried in the baseband or propagated as a carrier wave in a propagated data signal, in which the readable program code is carried. Such a propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The readable storage medium can also be any readable medium that can send, propagate or transfer the program for use by or in connection with an instruction execution system, apparatus or device. The program code contained on the readable storage medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical, RF, or the like, or any suitable combination of the above.

[0085] In addition, the present disclosure also provides a computer program product, comprising computer programs / instructions, which, when executed by a processor, implement the reliability index calculation method of a concrete beam considering uneven corrosion of steel bars as described in any of the above embodiments.

[0086] The program code may be implemented in any of various ways, including procedure-based (e.g., C), object-oriented (e.g., Java), and / or design-based (e.g., Veloprint) ways. The program code can execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device (e.g., through the Internet using an Internet Service Provider).

[0087] In light of the above, the present application can be implemented in hardware, or software on one or more processors, or a combination of both. Those skilled in the art will appreciate that the various embodiments can be implemented in their entirety, or any part, in one or more general purpose data processing devices, special purpose data processing devices, or any other device. The present application can also be implemented as a program of instructions for implementing any part of the above-described methods on a data processing device or apparatus (e.g., a computer program and a computer program product). Such a program of instructions can be stored on a computer readable medium, or can be in the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

[0088] The above-described embodiments are merely intended to further describe the purpose, technical solutions and beneficial effects of the present application, and should be understood that the present application is not inherently related to any specific computer, virtual device or electronic device, and various general-purpose devices can also implement the present application. The above-described embodiments are merely specific embodiments of the present application, and are not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

[0089] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments.

[0090] If the technical scheme of the application involves personal information, the product applying the technical scheme of the application has clearly informed the personal information processing rules before processing the personal information and has obtained the personal independent consent. If the technical scheme of the application involves sensitive personal information, the product applying the technical scheme of the application has obtained the personal independent consent before processing the sensitive personal information and at the same time meets the requirement of "explicit consent".

[0091] The above only describes the embodiments of the application and is not used to limit the application. The application can have various changes and variations for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the application shall be included in the scope of claims of the application.

Claims

1. A method for calculating a reliability index of a concrete beam considering uneven corrosion of reinforcing steel, characterized by, The method comprises the following steps: obtaining design parameters of a concrete beam and a probability distribution function of uneven corrosion coefficients of steel bars; calling a Monte Carlo algorithm to perform multiple loop samplings, in each loop sampling, discretizing the concrete beam into multiple sampling units, sampling the uneven corrosion coefficients based on the probability distribution function to obtain sampling coefficients corresponding to the sampling units; based on the sampling coefficients and the design parameters of the concrete beam, constructing a bearing function function of each sampling unit, and calculating function values of the bearing function function of each sampling unit and judging a simulation failure condition of the concrete beam in the loop sampling based on the bearing function function of each sampling unit; calculating a failure probability of the concrete beam in all loop samplings, and calculating a reliability index of the concrete beam according to the failure probability.

2. The method of claim 1, wherein the method is characterized by, After the concrete beam is discretized into multiple sampling units, the method further comprises the following steps: obtaining a load type and a sampling statistical characteristic of each sampling unit to determine a load effect parameter of each sampling unit; the step of constructing the bearing function function of each sampling unit based on the sampling coefficients and the design parameters of the concrete beam comprises the following steps: judging a failure type of each sampling unit based on the sampling coefficients and the design parameters of the concrete beam; calculating a tensile bearing capacity of the steel bars of each sampling unit based on the failure type, and calculating a unit bending bearing capacity according to the tensile bearing capacity of the steel bars; constructing the bearing function function based on the unit bending bearing capacity of each sampling unit and the load effect parameter.

3. The method of claim 2, wherein the method is characterized by: The sampling coefficients comprise sampling coefficients corresponding to each steel bar in each sampling unit; after the design parameters of the concrete beam are obtained, the method further comprises the following step: calculating a critical parameter of a steel bar unit according to the design parameters of the concrete beam; the step of judging the failure type of each sampling unit based on the sampling coefficients and the design parameters of the concrete beam comprises the following steps: if the sampling coefficients of all steel bar units contained in a current sampling unit are all less than the critical parameter, the sampling unit is in ductile failure; if the sampling coefficient of any one steel bar unit contained in the current sampling unit is greater than or equal to the critical parameter, the sampling unit is in brittle failure.

4. The method of claim 3, wherein the method is characterized by, The method comprises the following steps: when the failure type is ductile failure, the calculation formula of the tensile bearing capacity of the steel bars of each sampling unit is: when the failure type is brittle failure, the calculation formula of the tensile bearing capacity of the steel bars of each sampling unit is: in, This represents the tensile bearing capacity of the steel reinforcement in a sampling unit. n Indicates the number of tensile reinforcement bars in each sampling unit; i Indicates the first i One steel bar, i= (1,2,3,…, n ); Represents the first sampling unit in a sampling unit. i The tensile bearing capacity of the reinforcing bar; For the first i The yield strength of the reinforcing bar is based on the minimum corrosion cross-sectional area; For the first i Minimum cross-sectional area of ​​a steel bar.

5. The method of calculating a reliability index of a concrete beam considering uneven corrosion of a steel bar according to any one of claims 2 to 4, characterized in that, the expression of the bearing function function is: wherein, represents a bearing capacity function, represents a unit bending resistance bearing capacity of each sampling unit; represents a load effect parameter of each sampling unit; j (1, 2, 3, …, m ); m represents the number of sampling units; the step of judging the simulation failure condition of the concrete beam in the loop sampling based on the bearing function function of each sampling unit comprises the following steps: when the function values of the bearing function functions of all sampling units in one loop sampling are all greater than or equal to 0, the concrete beam is safe in this loop sampling; when the function value of the bearing function function of any one sampling unit in one loop sampling is less than 0, the concrete beam is in failure in this loop sampling.

6. The method of claim 5, wherein the method is characterized by: The step of calculating the failure probability of the concrete beam in all loop samplings and calculating the reliability index of the concrete beam according to the failure probability comprises the following steps: obtaining a loop sampling number, and counting a failure number of times that the concrete beam is judged to be in failure in all loop sampling processes, calculating a failure probability based on the failure number and the loop sampling number; The reliability index of the concrete beam is calculated according to the failure probability and a preset probability cumulative distribution function.

7. A device for calculating a reliability index of a concrete beam considering uneven corrosion of a reinforcing bar, characterized by, The device for calculating the reliability index of the concrete beam considering uneven corrosion of the steel bars comprises: a data acquisition module configured to acquire design parameters of the concrete beam and a probability distribution function of uneven corrosion coefficients of the steel bars; a sampling simulation module configured to call a Monte Carlo algorithm to perform multiple loop samplings, sample the uneven corrosion coefficients based on the probability distribution function to obtain sampling coefficients corresponding to each sampling unit in each loop sampling by discretizing the concrete beam into multiple sampling units, and calculate function values based on the bearing capacity function of each sampling unit and determine the simulation failure of the concrete beam in the loop sampling; an index calculation module configured to calculate the failure probability of the concrete beam in all loop samplings and calculate the reliability index of the concrete beam according to the failure probability.

8. A device for calculating a reliability index of a concrete beam considering uneven corrosion of a steel bar, characterized by, The device for calculating the reliability index of the concrete beam considering uneven corrosion of the steel bars comprises a memory and at least one processor, and the memory stores instructions. The at least one processor calls the instructions in the memory to enable the device for calculating the reliability index of the concrete beam considering uneven corrosion of the steel bars to perform the steps of the method for calculating the reliability index of the concrete beam considering uneven corrosion of the steel bars according to any one of claims 1-6.

9. A computer-readable storage medium having stored thereon computer programs / instructions, characterized in that, The program / instructions enable the processor to perform the steps of the method for calculating the reliability index of the concrete beam considering uneven corrosion of the steel bars according to any one of claims 1-6 when executed.

10. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instructions enable the processor to perform the steps of the method for calculating the reliability index of the concrete beam considering uneven corrosion of the steel bars according to any one of claims 1-6 when executed.

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