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Parametric estimation of dispersive viscoelastic layered media with application to structural health monitoring

机译:分散粘弹性层状介质的参数估计及其在结构健康监测中的应用

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We present a sequential Bayesian estimation method to estimate the material parameters that govern the one-dimensional propagation of shear waves through continuous, layered, viscoelastic solids. While the proposed estimation method is generic, namely, can be applied to waveform inversion problems that satisfy the above conditions, we here employ it for system identification of building structures. We approximate the linear-elastic response of building structures subjected to low-amplitude earthquake base excitations by a multilayer dispersive shear beam model with Kelvin-Voigt material subjected to vertically propagating shear waves. Utilizing the proposed sequential Bayesian estimation method, we sequentially update the probability distribution function of the unknown parameters to reduce the discrepancies between the estimated and measured frequency response functions. We next verify and validate the performance of the proposed estimation method and investigate the limitations of the presented structural system identification approach using two case studies. In the first case study, we use the simulated structural response of a three-dimensional 52-story building model subjected to bi-directional low-amplitude ground shakings. We estimate the frequency-dependent phase velocity and damping ratio, as well as the mass distribution along the building height. Then, we verify the structural damage detection and localization capabilities of the presented system identification approach by comparing the wave model parameters estimated from simulated response of undamaged and damaged structural models. In the second case study, we use data measured from a shake table experiment on a full-scale five-story reinforced concrete building specimen, where the estimated wave model parameters capture the progressive structural damage in the test specimen. The validation studies suggest that the sequential Bayesian estimation method based on viscoelastic dispersive wave propagation can be used for system and damage identification of building structures.
机译:我们提出了一种顺序贝叶斯估计方法,以估计控制通过连续,分层,粘弹性固体的剪切波的一维传播的材料参数。虽然所提出的估计方法是通用的,即可以应用于满足上述条件的波形反演问题,但在此我们将其用于建筑结构的系统识别。我们用开尔文-沃格特材料在垂直传播的剪切波作用下的多层色散剪切梁模型,对低振幅地震基础激励下的建筑结构的线弹性响应进行了近似。利用提出的顺序贝叶斯估计方法,我们顺序更新未知参数的概率分布函数,以减少估计和测量的频率响应函数之间的差异。接下来,我们通过两个案例研究来验证和验证所提出的估计方法的性能,并研究所提出的结构系统识别方法的局限性。在第一个案例研究中,我们使用经受双向低振幅地面振动的三维52层建筑模型的模拟结构响应。我们估计与频率有关的相速度和阻尼比,以及沿建筑物高度的质量分布。然后,我们通过比较从未损坏和损坏的结构模型的模拟响应估计的波浪模型参数,验证了所提出的系统识别方法的结构损伤检测和定位能力。在第二个案例研究中,我们使用从振动台实验中测得的全尺寸五层钢筋混凝土建筑标本的数据,其中估计的波浪模型参数捕获了测试标本中的渐进式结构破坏。验证研究表明,基于粘弹性弥散波传播的顺序贝叶斯估计方法可用于建筑结构的系统和损伤识别。

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