WO2024041233A1 - 桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法 - Google Patents

桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法 Download PDF

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WO2024041233A1
WO2024041233A1 PCT/CN2023/105667 CN2023105667W WO2024041233A1 WO 2024041233 A1 WO2024041233 A1 WO 2024041233A1 CN 2023105667 W CN2023105667 W CN 2023105667W WO 2024041233 A1 WO2024041233 A1 WO 2024041233A1
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reliability
factor
damage
life
bridge
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French (fr)
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郭彤
刘中祥
汪诗园
刘杰
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东南大学
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/10—Numerical modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces

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  • the invention belongs to the field of multi-factor disaster analysis and life assessment of bridges, and relates to a method for evaluating fatigue damage and life of bridge structures due to multi-factor coupling effects.
  • the service environment of bridge structures is complex and has many influencing factors, including fatigue effects such as vehicle load, wind, and temperature, as well as corrosion and wear. Under complex load-environment effects, damage to long-span bridges is often caused by numerous factors/actions and their coupling effects. The frequency and intensity of each factor/action are highly random, have different distributions, and have different time phases and frequencies. The fatigue damage mechanism of structures under the action of multiple factors is unclear and complex, which leads to structural damage and life assessment. difficulty. However, with the increase of service life, bridge structure coupling fatigue damage accidents have become more and more prominent, seriously affecting the operation and maintenance safety of bridges.
  • Patent No. 201510225325.4 discloses a crack propagation prediction method for structural parts based on multi-factor fusion correction
  • Patent No. 201510247506.7 discloses a prediction of the remaining life of structural parts based on multi-factor fusion correction.
  • Method Patent No. 201710001052.4 discloses a method for evaluating the residual strength of structural parts based on multi-factor fusion correction, which takes into account the impact of fatigue life, stress concentration, stress distribution, manufacturing process, surface strength, etc. on the damage status of structural parts. factors, but the effects of these factors are all considered through the effects of coefficients on stress, and the effects of each factor cannot be distinguished and all Indian effects need to be converted into effects on stress; Patent No.
  • Patent No. 201811067793.3 discloses a corrosion-fatigue-based remaining life assessment method and system for sling wires, which is A testing method and system that only considers the effects of two factors, corrosion and fatigue, and the coupling effect is considered in general testing.
  • the present invention provides A comprehensive, accurate, and efficient assessment method for coupling fatigue damage and life due to multi-factor effects on vulnerable parts of a bridge structure. It can be used to analyze fatigue damage conditions and predict remaining life of bridge structures in operating environments, providing guidance for bridge maintenance decisions, reinforcement implementation, and Optimized design provides support.
  • the present invention provides a method for evaluating fatigue damage and life under the multi-factor coupling effect of a bridge structure, which includes the following steps:
  • the damage index and time-varying reliability calculation formula of structural performance under the single factor/action of fatigue, corrosion, and wear respectively calculate the degradation rate of structural performance reliability under the effects of fatigue, corrosion, and wear in the current calculation step; the one with the largest reliability degradation rate is the dominant factor of the current calculation step, and the reliability reduction amount of the current calculation step is calculated from the reliability reduction rate of the dominant factor, that is, the reliability reduction rate is competitively determined under the action of each factor.
  • the reliability of the current calculation step is determined by the reliability reduction of the previous calculation step. Remove the decrease in reliability of the current calculation step, where the reliability of the first calculation step is the initial reliability;
  • ⁇ lnx and ⁇ lnx represent the mean and standard deviation of lnx respectively, which are calculated and determined by ⁇ x and ⁇ x , where x represents ⁇ , A, N(t), N 0 and Seq of the above formula; ⁇ is the Miner critical
  • the damage accumulation index can be described by the lognormal distribution function, with the mean value ⁇ ⁇ being 1.0 and the coefficient of variation ⁇ ⁇ being 0.3;
  • A is the fatigue detail index, which is determined by the detail type of vulnerable parts according to the specification;
  • N 0 is the number of cycles ;
  • S eq is the equivalent stress amplitude, calculated by the following formula;
  • N (t) is equal to 365 ⁇ ADT ⁇ N 0 ⁇ t, ADT is the average daily traffic volume, and t is the time in years.
  • m is the index, which can generally be taken as 3; N is the number of cycles required to cause fatigue failure under the equivalent stress amplitude S eq ; n i is the actual number of cycles of the stress amplitude S i .
  • ⁇ ac and ⁇ ac are the mean and standard deviation of the critical index of corrosion damage; a(t) is the corrosion damage index, which is calculated and determined by the following formula; ⁇ a(t) and ⁇ (t) are the mean and standard deviation of the corrosion damage index. standard deviation.
  • ⁇ and ⁇ are the parameters of the corrosion damage index calculation formula, indicating the uniform corrosion rate and trend, which are related to the metal type and corrosion environment conditions.
  • ⁇ Vc and ⁇ Vc are the mean and standard of the critical indicators of wear damage;
  • V(t) is the corrosion damage index, calculated by the following formula;
  • ⁇ V(t) and ⁇ V(t) are the mean and standard of the corrosion damage index. Difference.
  • k is the wear depth development rate formula parameter
  • H is the hardness
  • F is the lateral force.
  • the dominant factor of each calculation step in step three is the one with the largest decrease rate.
  • ⁇ i is the reliability decrease of the current calculation step
  • ⁇ t is the time increment, in years
  • ⁇ (t) i and ⁇ (t) i-1 are the reliability of the current calculation step and the previous calculation step.
  • a computer-readable storage medium on which a computer program is stored.
  • the program is executed by a processor, the multi-factor coupling effect fatigue damage and life assessment method of a bridge structure of the present invention is implemented. A step of.
  • the invention is used to accurately evaluate the fatigue damage and remaining life of the bridge structure under the multi-factor coupling effect under the in-service load environment. Provide a basis for damage analysis and detection, maintenance and reinforcement decisions of bridge structures.
  • the present invention has the following advantages:
  • the present invention uses the reliability decline rate as the dominant factor in index determination and its transformation, which avoids the problem of different differentiated damage representation quantities caused by different factors, achieves unified consideration of damage determination caused by different factors, and has strong adaptability.
  • Figure 1 is a numerical reproduction flow chart for vehicle, wind, temperature, corrosion, and wear monitoring of complex service environment effects
  • Figure 2 shows the finite element model of the bridge structure and examples of vulnerable parts
  • Figure 3 shows the equivalent stress amplitude
  • Figure 4 shows the number of cycles
  • Figure 5 is a diagram of the reliability decline rate of fatigue, wear, and corrosion damage
  • Figure 6 is a flow chart of the assessment method for fatigue damage and life due to multi-factor coupling effects on bridge structures
  • Figure 7 shows the reliability decline rate competition, time-varying reliability and life evaluation diagram of various factors.
  • the vulnerable parts are bolted channel steel nodes as an example.
  • a method for evaluating fatigue damage and life due to multi-factor coupling effects on bridge structures includes the following steps:
  • the probability distribution model of vehicle role representation parameters includes axle weight probability distribution function, wheelbase probability distribution function, vehicle lane distribution ratio, etc., and is established by analyzing vehicle monitoring data such as mobile weighing systems and monitoring videos.
  • the wind action characterization parameters include hourly average wind speed, wind direction angle distribution ratio, etc., which are statistically established from measured wind load data.
  • Temperature effect characterization parameters The data includes daily average temperature, temperature gradient, etc., and is statistically established by monitoring temperature data.
  • the parameters characterizing the wear effect include the wear depth development rate formula parameter k, hardness H, and lateral force F, which are statistically established from the wear test measurement data; k obeys a normal distribution, with a mean value of 7 ⁇ 10 -4 and a coefficient of variation of 0.1.
  • three-dimensional geometric model, etc. establish a finite element model of the entire bridge including vulnerable parts, as shown in Figure 2.
  • the main beam is simulated by Qiao element
  • the main tower is simulated by 6-degree-of-freedom beam element
  • the cable is simulated by 3-degree-of-freedom rod element that is only subjected to tension but not compression.
  • Material properties are assigned to the corresponding elements as specified.
  • the vulnerable parts are bolted channel steel nodes as an example. They are locally refined according to their local structural geometric dimensions or a refined local finite element model is established using sub-model technology.
  • ⁇ lnx and ⁇ lnx respectively represent the mean and standard deviation of lnx, which are calculated and determined by ⁇ x and ⁇ x , where x represents ⁇ , A, N(t), N 0 and Seq of the above formula; ⁇ is the Miner critical
  • the damage accumulation index can be described by the lognormal distribution function.
  • ⁇ ⁇ is 1.0 and the coefficient of variation ⁇ ⁇ is 0.3;
  • A is the fatigue detail index, which is determined by the type of details of vulnerable parts according to the specification;
  • N 0 is the number of cycles ;
  • S eq is the equivalent stress amplitude;
  • N(t) is equal to 365 ⁇ ADT ⁇ N 0 ⁇ t,
  • ADT is the average daily traffic flow, t is the time in years, and m is the index, which can generally be taken as 3.
  • ⁇ ac and ⁇ ac are the mean and standard deviation of the critical index of corrosion damage; a(t) is the corrosion damage index, which is calculated and determined by the following formula; ⁇ a(t) and ⁇ (t) are the mean and standard deviation of the corrosion damage index. standard deviation.
  • t 0 is the initial time
  • d is the corrosion direction size of the vulnerable part.
  • ⁇ Vc and ⁇ Vc are the mean and standard of the critical indicators of wear damage;
  • V(t) is the corrosion damage index, calculated by the following formula;
  • ⁇ V(t) and ⁇ V(t) are the mean and standard of the corrosion damage index. Difference.
  • the one with the largest reliability decline rate is the dominant factor in the i-th step.
  • the reliability decline amount ⁇ i in the i-th step is calculated from the reliability decline rate of the dominant factor in the i-th step. That is, the reliability decline rate is determined by competition under the action of each factor.
  • ⁇ i is the reliability decrease of the current calculation step
  • ⁇ t is the time increment, in years
  • ⁇ (t) i and ⁇ (t) i-1 are the reliability of the current calculation step and the previous calculation step.

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  • Geometry (AREA)
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  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
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Abstract

本发明公开了一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，包括如下步骤：S1、复杂服役环境作用数值复现；S2、桥梁结构性能数值分析；S3、易损部位耦合疲劳损伤计算；S4、桥梁结构剩余寿命预测。本发明可以准确评估在役桥梁多因素耦合作用疲劳损伤状况以及剩余寿命，定量分析易损部位疲劳损伤中各因素/作用效应及其耦合效应，为桥梁的运维管理、加固修复以及优化设计提供数据支撑和决策参考。

Description

桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法 技术领域
本发明属于桥梁多因素灾害分析及寿命评估领域，涉及一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法。
背景技术
桥梁结构服役环境复杂，其影响因素众多，包括车辆荷载、风、温度等疲劳作用以及腐蚀作用和磨损作用。复杂荷载-环境作用下，大跨桥梁的损伤往往是众多因素/作用及其耦合效应导致的。各因素/作用的频率、强度存在着高度的随机性、不同的分布以及差异性的时间相位及频率，多因素作用下结构的疲劳损伤存机理不明、机制复杂，从而带来结构损伤和寿命评估困难。然而，随着服役年限的增加，桥梁结构耦合疲劳损伤事故愈发突出，严重影响桥梁的运维安全。以往研究主要考虑疲劳、腐蚀或磨损等单因素作用下桥梁性能分析与寿命评估，而多因素效应以笼统的系数或多个单因素作用重复叠加考虑，导致结果合理性和可靠性问题。为有效支撑桥梁运维决策，需要建立能全面考虑复杂在役环境多因素作用且准确评估桥梁结构性能的方法，研究多因素作用耦合疲劳损伤灾变机制，分析结构失效中各因素的影响规律。针对上述问题，本发明建立一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法。
目前，考虑多因素作用的结构评估方法包括：专利号201510225325.4公开了一种基于多因素融合修正的结构件裂纹扩展预测方法，专利号201510247506.7公开了一种基于多因素融合修正的结构件剩余寿命预测方法，专利号201710001052.4公开了一种基于多因素融合修正的结构件剩余强度评估方法，均是考虑了疲劳寿命、应力集中、应力分布情况、制造工艺、表面强度等能够对结构件损伤状态造成影响的因素，但这些因素的作用均是通过系数等对应力的影响考虑的，未能分辨各因素的作用且所有印度的影响均需转化到对应力的影响；专利号202111427626.7公开了一种基于多因素综合影响的结构安全性分析方法，通过设定荷载放大系数、材性折减系数、截面损伤系数、支座变化系数调整有限元模型以分析性分析多个因素较不利折减因素组合的影响，不涉及多因素竞争关系的耦合疲劳模型且不涉及概率可靠度及其主导因素下降速率积分技术；专利号201811067793.3公开了一种基于腐蚀-疲劳的拉吊索钢丝剩余寿命评估方法及系统，是一种测试方法及系统，仅考虑了腐蚀和疲劳的两个因素作用且耦合作用是笼统测试考虑的。
发明内容
为了实现复杂荷载-环境作用下桥梁结构耦合疲劳损伤和寿命的评估，本发明提供了 一种全面、准确、高效的桥梁结构易损部位多因素作用耦合疲劳损伤和寿命的评估方法，可用于分析运营环境下桥梁结构疲劳损伤状况和预测剩余寿命，为桥梁的维护决策、加固实施和优化设计提供支撑。
本发明的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，包括以下步骤：
S1、根据桥梁服役环境结构监测数据，建立车辆、风、温度、腐蚀、磨损等因素/作用表征参数的概率分布模型，按各因素/作用联合发生频率和持时的比例确定样本量并进行抽样生成各因素/作用表征参数样本；
S2、根据桥梁设计图纸、三维几何模型等，建立包含易损部位的整桥有限元模型；将所述步骤一中各因素/作用表征参数样本按联合发生频率和持时的比例以及作用区域组合形成样本系列；依次输入有限元模型进行桥梁结构性能数值分析，获得桥梁易损部位应力时程；采用雨流计数方法从应力时程计算获得等效应力幅和循环次数分布；
S3、根据疲劳、腐蚀、磨损单因素/作用下损伤指标和结构性能时变可靠度计算公式，分别计算当前计算步疲劳、腐蚀、磨损作用结构性能可靠度下降速率；以可靠度下降速率最大者为当前计算步的主导因素，由主导因素可靠度下降速率计算得到当前计算步可靠度下降量，即各因素作用下可靠度下降速率竞争确定，当前计算步可靠度采用上一计算步可靠度减去当前计算步可靠度下降量，其中第一计算步可靠度为初始可靠度；
S4、依次计算直至前计算步可靠度不小于临界可靠度，即可得到耦合疲劳寿命；否则计算步增加，返回S3。
进一步的，本发明方法中，S3中疲劳作用结构性能可靠度βF计算公式如下：
其中，μlnx和σlnx分别表示lnx的均值和标准差，由μx和σx计算确定，其中x代表上式的Δ、A、N(t)、N0和Seq；Δ是Miner临界破坏累积指标，可采用对数正态分布函数来描述，其均值μΔ为1.0，变异系数σΔ为0.3；A是疲劳细节指标，由易损部位细节类型根据规范确定；N0是循环次数；Seq是等效应力幅，由下式计算；N(t)等于365×ADT×N0×t，ADT是日均车流量，t是以年为单位的时间。
其中，m为指数，一般可取为3；N为等效应力幅Seq下发生疲劳破坏所需的循环次数；ni为应力幅Si的实际循环次数。
进一步的，本发明方法中，S3中腐蚀作用结构性能可靠度βC计算公式如下：
其中，μac和σac是腐蚀损伤临界指标的均值和标准差；a(t)是腐蚀损伤指标，由下式计算确定；μa(t)和σ(t)是腐蚀损伤指标的均值和标准差。
其中，α和β为腐蚀损伤指标计算公式参数，表示均匀腐蚀率和趋势，与金属类型和腐蚀环境条件有关，对于钢材腐蚀呈对数增长，钢材腐蚀呈对数增长，其β＝0.5；α服从对数正态分布，其平均值和偏差系数分别为7.91×10-6m/年和0.135；t0为初始时间；d为易损部位腐蚀方向尺寸。
进一步的，本发明方法中，所述步骤三中磨损作用结构性能可靠度βW计算公式如下：
其中，μVc和σVc是磨损损伤临界指标的均值和标准；V(t)是腐蚀损伤指标，由下式计算；μV(t)和σV(t)是腐蚀损伤指标的均值和标准差。
其中，k为磨损深度发展速率公式参数；H为硬度；F为侧向力。
进一步的，本发明方法中，所述步骤三中各计算步主导因素为下降速率最大者，当前计算步可靠度下降量和可靠度由下列公式计算。

β(t)＝β(t)i-1-Δβi        (4)
其中，Δβi是当前计算步可靠度下降量；Δt是时间增量，以年为单位；β(t)i和β(t)i-1是当前计算步和上一计算步可靠度。
根据本发明的另一方面，提供了一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现本发明的桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法中的步骤。
本发明用于准确评估在役荷载环境下桥结构多因素耦合作用疲劳损伤和剩余寿命， 为桥梁结构的损伤分析和检测、养护及加固决策提供依据。
本发明与现有技术相比，具有以下优点：
1、现有技术关注单因素作用，对多因素共同作用考虑不足，评估结果准确性有待提升；本申请的“一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法”考虑了多因素耦合作用，较为全面合理地考虑了复杂在役环境因素影响，评估结果合理可靠。
2、现有技术考虑多因素效应时往往笼统的系数或多个单因素作用重复叠加考虑，无法定量分析各因素的影响，存在重复计算问题，方法合理性有待提升；本申请的“一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法”采用以各计算步主导因素可靠度下降速率计算可靠度下降量、计算步间累计得到可靠度的多因素竞争关系的耦合疲劳损伤模型，实现了各因素的定量分析及其耦合效应的合理计算，计算精度。
3、本发明采用可靠度下降速率为指标判定主导因素及其转变，避免了不同因素作用损伤表征量不同差别化难题，实现了不同因素作用损伤判定的统一考虑，适应性强。
附图说明
图1为复杂服役环境作用监测的车辆、风、温度、腐蚀、磨损数值复现流程图；
图2为桥梁结构有限元模型及易损部位示例图；
图3为等效应力幅；
图4为循环次数；
图5为疲劳、磨损、腐蚀损伤可靠度下降速率图；
图6为桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法流程图；
图7为各因素作用可靠度下降速率竞争、时变可靠度及寿命评估图。
具体实施方式
下面结合实施例和说明书附图对本发明作进一步的说明，易损性部位以栓接槽钢节点为例。
如图1-7所示，一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，包括以下步骤：
S1、根据桥梁服役环境结构监测数据，建立车辆、风、温度、腐蚀、磨损等因素/作用表征参数的概率分布模型，按各因素/作用联合发生频率和持时的比例确定样本量并进行抽样生成各因素/作用表征参数样本，如图1所示。
车辆作用表征参数的概率分布模型包括轴重概率分布函数、轴距概率分布函数、车型车道分布比例等，由移动称重系统、监测视频等车辆监测数据分析建立。风作用表征参数包括时均风速、风向角分布比例等，由实测风荷载数据统计建立。温度作用表征参 数包括日平均温度、温度梯度等，由监测温度数据统计建立。腐蚀作用表征参数包括为腐蚀损伤指标计算公式参数α和β，由腐蚀试验测量数据统计建立；α服从对数正态分布，其平均值和偏差系数分别为7.91×10-6m/年和0.135，β＝0.5。磨损作用表征参数包括磨损深度发展速率公式参数k、硬度H，侧向力F，由磨损试验测量数据统计建立；k服从正态分布，均值为7×10-4，变异系数为0.1。
S2、据桥梁设计图纸、三维几何模型等，建立包含易损部位的整桥有限元模型，如图2所示。主梁采用乔单元模拟，主塔采用6自由度梁单元模拟，缆索采用只受拉不受压的3自由度杆单元模拟。材料属性按规定分配给相应的单元。易损性部位以栓接槽钢节点为例，根据其局部构造几何尺寸对其进行局部细化或采用子模型技术建立精细化的局部有限元模型。
将所述步骤一中各因素/作用表征参数样本按联合发生频率和持时的比例以及作用区域组合形成样本系列；依次输入有限元模型进行桥梁结构性能数值分析，获得桥梁易损部位应力时程；采用雨流计数方法从应力时程计算获得等效应力幅和循环次数分布，采用回归分析拟合得到等效应力幅和循环次数概率分布函数，如图3和4所示。
S3、计算第i步疲劳作用结构性能可靠度下降速率，如图5所示，其疲劳损伤下结构性能时变可靠度计算公式如下：
其中，μlnx和σlnx分别表示lnx的均值和标准差，由μx和σx计算确定，其中x代表上式的Δ、A、N(t)、N0和Seq；Δ是Miner临界破坏累积指标，可采用对数正态分布函数来描述，其均值μΔ为1.0，变异系数σΔ为0.3；A是疲劳细节指标，由易损部位细节类型根据规范确定；N0是循环次数；Seq是等效应力幅；N(t)等于365×ADT×N0×t，ADT是日均车流量，t是以年为单位的时间，m为指数，一般可取为3。
计算第i步腐蚀作用结构性能可靠度下降速率，如图5所示，其腐蚀损伤下结构性能时变可靠度计算公式如下：
其中，μac和σac是腐蚀损伤临界指标的均值和标准差；a(t)是腐蚀损伤指标，由下式计算确定；μa(t)和σ(t)是腐蚀损伤指标的均值和标准差。
其中，t0为初始时间；d为易损部位腐蚀方向尺寸。
计算第i步磨损作用结构性能可靠度下降速率，如图5所示，其磨损损伤下结构性能时变可靠度计算公式如下：
其中，μVc和σVc是磨损损伤临界指标的均值和标准；V(t)是腐蚀损伤指标，由下式计算；μV(t)和σV(t)是腐蚀损伤指标的均值和标准差。
以可靠度下降速率最大者为第i步主导因素，由第i步主导因素可靠度下降速率计算得到第i步可靠度下降量Δβi，即各因素作用下可靠度下降速率竞争确定，第i步可靠度βi采用第i-1步可靠度βi-1减去第i步可靠度下降量Δβi，其中第1步可靠度为初始可靠度β0＝12.0。具体计算公式如下：

β(t)＝β(t)i-1-Δβi        (4)
其中，Δβi是当前计算步可靠度下降量；Δt是时间增量，以年为单位；β(t)i和β(t)i-1是当前计算步和上一计算步可靠度。
S4、依次计算直至前计算步可靠度不小于临界可靠度βth，即可得到耦合疲劳寿命；否则计算步增加，返回S3。临界可靠度βth可设置0，表示完全损坏，需维修更换。
上述桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法的流程如图6所示。根据上述流程计算疲劳、腐蚀、磨损作用结构性能时变可靠度以及耦合疲劳损伤剩余寿命如图7所示。由该图可知，服役过程中主导因素会发生改变，结构性能可靠度随着时间而不断地下降，栓接槽钢节点多因素耦合作用疲劳损伤剩余寿命约为24.8年。
上述实施例仅是本发明的优选实施方式，应当指出：对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和等同替换，这些对本发明权利要求进行改进和等同替换后的技术方案，均落入本发明的保护范围。

Claims (10)

  1. 一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，该方法包括以下步骤：
    S1、复杂服役环境作用数值复现；
    S2、桥梁结构性能数值分析；
    S3、易损部位耦合疲劳损伤计算；
    S4、桥梁结构剩余寿命预测。
  2. 根据权利要求1所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，S1的具体步骤为：根据桥梁服役环境结构监测数据，建立因素/作用表征参数的概率分布模型，按各因素/作用联合发生频率和持时的比例确定样本量并进行抽样生成各因素/作用表征参数样本。
  3. 根据权利要求1所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，S2的具体步骤为：建立包含易损部位的整桥有限元模型；将S1中各因素/作用表征参数样本按联合发生频率和持时的比例以及作用区域组合形成样本系列；依次输入有限元模型进行桥梁结构性能数值分析，获得桥梁易损部位应力时程；采用雨流计数方法从应力时程计算获得等效应力幅和循环次数分布。
  4. 根据权利要求1所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，S3的具体步骤为：根据疲劳、腐蚀、磨损单因素/作用下损伤指标和结构性能时变可靠度计算公式，分别计算当前计算步疲劳、腐蚀、磨损作用结构性能可靠度下降速率；以可靠度下降速率最大者为当前计算步的主导因素，由主导因素可靠度下降速率计算得到当前计算步可靠度下降量，即各因素作用下可靠度下降速率竞争确定，当前计算步可靠度采用上一计算步可靠度减去当前计算步可靠度下降量，其中第一计算步可靠度为初始可靠度。
  5. 根据权利要求4所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，S3中疲劳作用结构性能可靠度βF计算公式如下：
    其中，μlnx和σlnx分别表示lnx的均值和标准差，其中x代表上式的Δ、A、N(t)、N0和Seq；Δ是Miner临界破坏累积指标；A是疲劳细节指标；N0是循环次数；Seq是等效应力幅；N(t)等于365×ADT×N0×t，ADT是日均车流量，t是以年为单位的时间。
  6. 根据权利要求5所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法， 其特征在于，S3中腐蚀作用结构性能可靠度βC计算公式如下：
    其中，μac和σac是腐蚀损伤临界指标的均值和标准差；a(t)是腐蚀损伤指标；μa(t)和σ(t)是腐蚀损伤指标的均值和标准差。
  7. 根据权利要求6所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，S3中磨损作用结构性能可靠度βW计算公式如下：
    其中，μVc和σVc是磨损损伤临界指标的均值和标准；V(t)是腐蚀损伤指标；μV(t)和σV(t)是腐蚀损伤指标的均值和标准差。
  8. 据权利要求7所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，S3中各计算步主导因素为下降速率最大者，当前计算步可靠度下降量和可靠度由下列公式计算：

    β(t)i＝β(t)i-1-Δβi       (4)
    其中，Δβi是当前计算步可靠度下降量；Δt是时间增量，以年为单位；β(t)i和β(t)i-1是当前计算步和上一计算步可靠度。
  9. 根据权利要求1所述的一种桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法，其特征在于，S4的具体步骤为：依次计算直至前计算步可靠度不小于临界可靠度，即可得到耦合疲劳寿命；否则计算步增加，返回S3。
  10. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于：该程序被处理器执行时实现如权利要求1～9中任一项所述的桥梁结构多因素耦合作用疲劳损伤与寿命的评估方法中的步骤。
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