利用各种振动监测数据更新剪力墙高层建筑的模型:准确性和稳健性

Jiazeng Shan, Changhao Zhuang, Xi Chao, C. Loong
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引用次数: 0

摘要

加速度测量通常用于土木工程结构的模型更新,尤其是在地震监测情况下。但目前还不清楚仅靠加速度是否就能生成准确、稳健的有限元(FE)模型。本研究探讨了这一概念,并分析了使用其他振动监测数据更新剪力墙高层建筑模型的可能性。本研究比较了通过加速度、屋顶位移、墙体旋转、层间漂移比以及这些测量数据的线性组合进行优化的有限元模型的准确性和稳健性。一项数值案例研究使用 Timoshenko 梁对地震激励下 42 层基准建筑的横向振动进行了建模分析。结果表明,受测建筑的加速度响应主要由其较高的振动模式控制。根据地面运动的特点,仅使用加速度可能会生成偏向高阶模态的有限元模型,而无法有效捕捉低阶模态。例如,更新后的 FE 模型的第一模态频率可能比真实值低 12.0%,重建的位移和旋转响应也明显不准确。采用多源监测数据进行模型更新,例如屋顶位移和加速度测量组合,可将位移的归一化均方根误差降低 70% 以上。本研究还量化了 FE 模型在不同测量噪声水平和 50 对地震记录下的稳健性。最后,通过对一栋 7 层剪力墙建筑的实验,验证了多源数据对 FE 模型更新的影响。分析表明,通过加速度和顶部位移的组合确定的 FE 模型比仅通过加速度确定的模型更准确、更稳健。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model updating of a shear‐wall tall building using various vibration monitoring data: Accuracy and robustness
Acceleration measurements are often used for model updating of civil engineering structures, especially in the case of seismic monitoring. It is yet unclear if accelerations alone would generate an accurate and robust finite‐element (FE) model. This study examines this notion and analyzes the possibility of using other vibration monitoring data for model updating of shear‐wall tall buildings. This study compares the accuracy and robustness of the FE models being optimized via accelerations, roof displacement, wall rotations, interstory drift ratios, and the linear combination of these measurements. A numerical case study is analyzed using Timoshenko beams for modeling the lateral vibration of a benchmark 42‐story building under seismic excitations. Results show that the acceleration response of the examined building is mostly governed by its higher vibration modes. Depending on the characteristics of ground motions, using accelerations alone may generate an FE model biased towards higher‐order modes without effectively capturing the lower‐order modes. For instance, the first modal frequency of the updated FE model could be 12.0% lower than the true value, and the reconstructed displacement and rotation responses are noticeably inaccurate. Employing multi‐source monitoring data for model updating, for example, the combinations of roof displacement and acceleration measurements, could reduce the normalized root‐mean‐square errors in displacements by more than 70%. This study also quantifies the robustness of the FE model under various measurement noise levels and 50 pairs of earthquake records. Finally, the effects of multi‐source data on FE model updating are validated via experiments on a 7‐story shear wall building. Analysis reveals that a more accurate and robust FE model can be determined via a combination of accelerations and top displacement than via acceleration alone.
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