基于信息更新的RC受弯构件抗力衰减概率模型
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摘要
我国现有公路桥梁65.81万余座,其中混凝土桥梁占90%以上,因环境和车辆荷载等因素导致的钢筋锈蚀病害突出,进而引起钢筋混凝土(RC)桥梁抗力衰减,严重影响其服役安全。对既有桥梁进行抗力评估存在很大的不确定性,若完全通过试验和统计回归的方法概括出结构生命周期的发展规律实为不易。因此,如何充分挖掘和利用RC桥梁的检测信息,得到更为合理的抗力评估结果,是值得深入研究的课题。
针对上述问题,本文结合国家自然科学基金项目“模糊及随机信息条件下既有RC桥梁时变可靠性研究(50908023)”和“既有RC桥梁构件抗剪性能退化模型及可靠性研究(50878031)”,对氯离子引起的钢筋锈蚀进而导致的RC桥梁性能退化、抗力衰减等展开研究,主要做了以下的工作:
(1)建立了RC桥梁中钢筋锈蚀率的先验概率模型。根据Fick第二扩散定律,结合Monte Carlo数值模拟的方法,分析了锈蚀初始时间、开裂时间和开裂至规定宽度时间的概率特征,并对各参数的敏感性进行探讨;研究了钢筋局部锈蚀深度的分布规律,对比了保护层厚度、混凝土强度对其的影响。
(2)建立了钢筋锈蚀率的后验概率模型。采用信息更新的Bayes原理和方法,通过引入不同时段的实桥检测信息,对锈蚀率先验模型进行了动态更新,并得到了锈蚀率的概率密度函数,结果显示更新后的模型较接近于实际,更加真实可靠,可为由于锈蚀导致的结构耐久性评估提供科学依据。
(3)基于钢筋力学性能试验与粘结试件的拔出试验,研究了锈蚀对钢筋强度的影响,提出了钢筋与混凝土间协同工作系数的表达式。对从实桥和快速腐蚀构件中得到的452根钢筋进行力学性能试验,讨论了钢筋锈蚀对其破坏形式的影响,得到了钢筋锈蚀率与屈服强度的关系。通过快速锈蚀内贴片变形钢筋混凝土试件的拔出试验,给出了钢筋与混凝土协同工作系数的表达式。
(4)构建了更新后RC桥梁构件的抗力衰减动态概率模型。考虑锈蚀钢筋截面积减小、钢筋强度降低和粘结性能退化,以实桥受弯构件为例,建立了信息更新后的抗力衰减概率模型。针对无实测信息的桥梁或构件,分析了信息不确定性对抗力的影响。研究表明:通过Bayes方法得到更新后的模型能较好地综合先验信息与RC构件的具体信息,进而减小了主观不确定性,由此得到结构的评估和预测结果更接近真实情况。
There are about 658100 highway bridges of China, which concrete bridge account for above 90%. Corrosion due to the environment and vehicle loads has become a serious problem in these concrete bridges, which is a key factor to affect the resistance attenuation and service security. It is difficult to gain the law of life-cycle based on experiment and statistical regression method because great uncertainty lie in evaluation of existing bridge. Therefore, it is an important task to evaluate the performance of degraded for RC bridge by fully using inspection data.
Aim at the above problems, the performance and resistance attenuation of RC bridge due to corrosion in chloride ions environment are studied. This work is supported by National Natural Science Fund of China under the Project NO.50908023“Research on Time-variant Reliability of Existing RC Bridge under Fuzzy and Random Information”and NO.50878031“The Degradation Model and Reliability of Shear of Existing RC Bridge”. The main research works include as follows:
(1) The prior probability model of corrosion rate is established. On the basis of Fick diffusion law, the distribution form and the probability density function (PDF) of corrosion initiation time, propagation time and the sensitivity of input parameters are analyzed. Monte Carlo simulation method is also applied. The effect of concrete cover and concrete strength on the probability distribution of the corrosion depth are analyzed.
(2) The posterior probability model of corrosion rate is established based on information updating. The inspection data of bridge are incorporated and the prior probability model of corrosion rate is updated using bayes method, in addition, the probability density function is obtained. The results show that the updated model is more reliable and closer to the actual situation. This will provide scientific basis for durability assessment of RC bridge.
(3) The tensile test on 452 corroded reinforcements from the electrochemical accelerated corrosion members and the field bridge members are conducted. The effect of corrosion rate on failure model are also discussed. The relation between steel corrosion rate and yield strength is established. The pullout tests on the bonding specimens with the deformed reinforcing bar installed by the interior strain gauge are conducted, and the associate expression of bond between steel and concrete is introduced.
(4) The dynamic probability model of resistance attenuation of flexural member for RC bridge is established. In this model, the reduction of steel cross-sectional, and the decrease of corroded steel strength, and the degradation of bond properties between corroded steel and concrete are considered. For structural members with no inspection data, the effect of uncertainty information on resistance is also studied. The results show that the Bayes Model can efficiently combine the prior information and the specific information of RC bridge so that can reduce knowledge-based epistemic uncertainties, thus making resistance analysis more accurate.
针对上述问题,本文结合国家自然科学基金项目“模糊及随机信息条件下既有RC桥梁时变可靠性研究(50908023)”和“既有RC桥梁构件抗剪性能退化模型及可靠性研究(50878031)”,对氯离子引起的钢筋锈蚀进而导致的RC桥梁性能退化、抗力衰减等展开研究,主要做了以下的工作:
(1)建立了RC桥梁中钢筋锈蚀率的先验概率模型。根据Fick第二扩散定律,结合Monte Carlo数值模拟的方法,分析了锈蚀初始时间、开裂时间和开裂至规定宽度时间的概率特征,并对各参数的敏感性进行探讨;研究了钢筋局部锈蚀深度的分布规律,对比了保护层厚度、混凝土强度对其的影响。
(2)建立了钢筋锈蚀率的后验概率模型。采用信息更新的Bayes原理和方法,通过引入不同时段的实桥检测信息,对锈蚀率先验模型进行了动态更新,并得到了锈蚀率的概率密度函数,结果显示更新后的模型较接近于实际,更加真实可靠,可为由于锈蚀导致的结构耐久性评估提供科学依据。
(3)基于钢筋力学性能试验与粘结试件的拔出试验,研究了锈蚀对钢筋强度的影响,提出了钢筋与混凝土间协同工作系数的表达式。对从实桥和快速腐蚀构件中得到的452根钢筋进行力学性能试验,讨论了钢筋锈蚀对其破坏形式的影响,得到了钢筋锈蚀率与屈服强度的关系。通过快速锈蚀内贴片变形钢筋混凝土试件的拔出试验,给出了钢筋与混凝土协同工作系数的表达式。
(4)构建了更新后RC桥梁构件的抗力衰减动态概率模型。考虑锈蚀钢筋截面积减小、钢筋强度降低和粘结性能退化,以实桥受弯构件为例,建立了信息更新后的抗力衰减概率模型。针对无实测信息的桥梁或构件,分析了信息不确定性对抗力的影响。研究表明:通过Bayes方法得到更新后的模型能较好地综合先验信息与RC构件的具体信息,进而减小了主观不确定性,由此得到结构的评估和预测结果更接近真实情况。
There are about 658100 highway bridges of China, which concrete bridge account for above 90%. Corrosion due to the environment and vehicle loads has become a serious problem in these concrete bridges, which is a key factor to affect the resistance attenuation and service security. It is difficult to gain the law of life-cycle based on experiment and statistical regression method because great uncertainty lie in evaluation of existing bridge. Therefore, it is an important task to evaluate the performance of degraded for RC bridge by fully using inspection data.
Aim at the above problems, the performance and resistance attenuation of RC bridge due to corrosion in chloride ions environment are studied. This work is supported by National Natural Science Fund of China under the Project NO.50908023“Research on Time-variant Reliability of Existing RC Bridge under Fuzzy and Random Information”and NO.50878031“The Degradation Model and Reliability of Shear of Existing RC Bridge”. The main research works include as follows:
(1) The prior probability model of corrosion rate is established. On the basis of Fick diffusion law, the distribution form and the probability density function (PDF) of corrosion initiation time, propagation time and the sensitivity of input parameters are analyzed. Monte Carlo simulation method is also applied. The effect of concrete cover and concrete strength on the probability distribution of the corrosion depth are analyzed.
(2) The posterior probability model of corrosion rate is established based on information updating. The inspection data of bridge are incorporated and the prior probability model of corrosion rate is updated using bayes method, in addition, the probability density function is obtained. The results show that the updated model is more reliable and closer to the actual situation. This will provide scientific basis for durability assessment of RC bridge.
(3) The tensile test on 452 corroded reinforcements from the electrochemical accelerated corrosion members and the field bridge members are conducted. The effect of corrosion rate on failure model are also discussed. The relation between steel corrosion rate and yield strength is established. The pullout tests on the bonding specimens with the deformed reinforcing bar installed by the interior strain gauge are conducted, and the associate expression of bond between steel and concrete is introduced.
(4) The dynamic probability model of resistance attenuation of flexural member for RC bridge is established. In this model, the reduction of steel cross-sectional, and the decrease of corroded steel strength, and the degradation of bond properties between corroded steel and concrete are considered. For structural members with no inspection data, the effect of uncertainty information on resistance is also studied. The results show that the Bayes Model can efficiently combine the prior information and the specific information of RC bridge so that can reduce knowledge-based epistemic uncertainties, thus making resistance analysis more accurate.
引文
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