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Assessing temporal requirements for SHM campaigns

机译:评估SHM活动的时间要求

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In the context of limited funds, continuous long-term monitoring may turn out not to be cost-effective to assess structural assets and estimate their service life. Motivated by this, the authors discuss how much data in terms of strain, pavement temperatures and traffic intensities are required to provide estimates of fatigue lives of an orthotropic steel deck. This is done by quantifying the uncertainty reduction due to increasing monitoring training data sets being available. First, several options for monitoring campaigns are defined in terms of the number, the time and the duration of the different monitoring phases associated with each monitoring option. The monitoring outcomes corresponding to each of the different monitoring options are then used to regress the statistical models for fatigue loading prediction based on daily averaged pavement temperatures and daily aggregated heavy-traffic counts. Fatigue reliability profiles are then calculated following a probabilistic methodology to estimate the remaining fatigue life for each location monitored. Finally, the error in determining the fatigue life of a structure detail is calculated for different monitoring options to determine the optimum duration for short-term monitoring campaigns. The proposed approach is illustrated by considering the field data from the Great Belt Bridge (Denmark).
机译:在资金有限的情况下,进行连续的长期监测可能会导致评估结构资产和估计其使用寿命不合算。受此启发,作者讨论了需要多少应变,路面温度和交通强度方面的数据来估算正交异性钢甲板的疲劳寿命。通过量化由于增加的可用监控培训数据集而导致的不确定性降低,可以完成此操作。首先,根据与每个监视选项相关的不同监视阶段的数量,时间和持续时间,定义了几个监视活动的选项。然后,将与每个不同监控选项相对应的监控结果用于基于每日平均路面温度和每日汇总的重载交通次数回归用于疲劳负荷预测的统计模型。然后,按照概率方法来计算疲劳可靠性曲线,以估计每个监测位置的剩余疲劳寿命。最后,针对不同的监视选项计算确定结构细节疲劳寿命的误差,以确定短期监视活动的最佳持续时间。通过考虑大皮带桥(丹麦)的现场数据来说明所建议的方法。

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