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An application of finite element model updating for damage assessment of a two-story reinforced concrete building and comparison with lidar

机译:有限元模型更新在两层钢筋混凝土建筑损伤评估中的应用及与激光雷达的比较

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This article investigates the performance of finite element model updating to identify the induced damage in a two-story reinforced concrete masonry-infilled building using vibration data as well as lidar (light detection and ranging) scans. The building, located in El Centro, California, was severely damaged due to the 2010 El Mayor-Cucapah (Baja California, Mexico) Earthquake, and it was planned to be demolished following a number of ambient and forced vibration tests. The forced vibration tests were performed using an eccentric mass shaker. During the testing sequence, damage was induced to the building by removing four exterior walls. The modal parameters of the structure are estimated using the ambient vibration and forced vibration measurements at the reference state and damaged state. Lidar data are also used to detect surface defects and quantify the temporal changes of surface defects caused by the wall removal and forced vibration tests. Based on site inspections, geometry measurements, and material test data, two initial finite element models are built, namely the un-tuned initial model and the tuned initial model. The tuned initial model implements stiffness reduction factors to account for the observed damage in the building at its reference state while the un-tuned model does not. Two sets of reference models are calibrated to represent the structure at the reference state using the un-tuned and tuned initial models. The reference models are then updated to fit the measured data at the damaged state of the building with damage being estimated as the loss of stiffness in updating substructures. The estimated damage is compared to the nominal value of induced damage and surface defects detected by lidar scans. The analysis of the results indicates that the un-tuned and tuned initial models provide similar updated models and damage identification results which are in good agreement with the nominal values of damage and lidar detection results.
机译:本文研究了使用振动数据以及激光雷达(光检测和测距)扫描进行的有限元模型更新性能,以识别两层钢筋混凝土砌筑的建筑物中的诱发损伤。该建筑物位于加利福尼亚州埃尔森特罗,由于2010年El Mayor-Cucapah(墨西哥下加利福尼亚州)地震而受到严重破坏,并且计划在进行多次环境和强制振动测试后拆除。使用偏心质量振动器进行强制振动测试。在测试过程中,通过移除四个外墙对建筑物造成了损坏。使用参考状态和损坏状态下的环境振动和强制振动测量来估算结构的模态参数。激光雷达数据还用于检测表面缺陷并量化由壁去除和强制振动测试引起的表面缺陷的时间变化。基于现场检查,几何测量和材料测试数据,建立了两个初始有限元模型,即未调整的初始模型和已调整的初始模型。调整后的初始模型实现了刚度降低因子,以解决在参考状态下建筑物中观察到的损坏,而未调整的模型则没有。使用未调整和调整的初始模型,校准两组参考模型以表示参考状态下的结构。然后更新参考模型以适合建筑物受损状态下的测量数据,并将损坏估计为更新子结构时刚度的损失。将估计的损坏与通过激光雷达扫描检测到的感应损坏和表面缺陷的标称值进行比较。结果分析表明,未调整和已调整的初始模型提供了相似的更新模型和损伤​​识别结果,与损伤和激光雷达检测结果的标称值非常吻合。

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