Structural Monitoring Arrays — Past, Present and Future

Çelebi, Mehmet

doi:10.1007/1-4020-3812-7_10

Cited by 9 publications

(10 citation statements)

References 30 publications

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“…As noted in previous studies of other structures (e.g. Çelebi, ; Çelebi et al ., 2013a), the response characteristics determined at low amplitude levels of shaking are generally significantly different from those expected at higher levels of shaking caused by earthquakes and strong winds. In particular, the response of this building during strong shaking is expected to be significantly altered by the special structural features described above.…”

Section: Introductionmentioning

confidence: 66%

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Ambient response of a unique performance‐based design tall building with dynamic response modification features

Çelebi

Huang

Shakal

et al. 2013

Structural Design Tall Build

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SUMMARYA 64-story, performance-based design building with reinforced concrete core shear walls and unique dynamic response modification features (tuned liquid sloshing dampers and buckling-restrained braces) has been instrumented with a monitoring array of 72 channels of accelerometers. The responses of the building to ambient motions from ground or wind were recorded and analyzed to identify modes and associated frequencies and damping. Not unexpectedly, the low-amplitude dynamic characteristics are considerably different than those computed from design analyses. Nonetheless, these computed values serve as a baseline against which to compare future strong shaking responses. Such studies help to improve our understanding of the effectiveness of the response modification features at various levels of shaking, to evaluate the predictive capabilities of the design analysis tools and to improve similar designs in the future.

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Section: Introductionmentioning

confidence: 66%

“…() as well as Çelebi et al (). General information on structural monitoring procedures and suggestions for deployments of accelerometers can be found in the work of COSMOS () and Çelebi ().…”

Section: Introductionmentioning

confidence: 99%

Ambient response of a unique performance‐based design tall building with dynamic response modification features

Çelebi

Huang

Shakal

et al. 2013

Structural Design Tall Build

Self Cite

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“…mth-order Markov source) is always smaller than that of a zero-memory information source, which makes decorrelation necessary for data compression. Mathematically, this can be expressed as H (X=X j1 ; X j2 ; : : : ; X jm ) 6 H (X ) (2) where H (X=X j1 ; X j2 ; : : : ; X jm ) is the information entropy of a correlated information source. Figure 1 shows a general procedure for seismic sensor data compression and reconstruction.…”

Section: Brief Overview Of Data Compression Theorymentioning

confidence: 99%

Efficient seismic response data storage and transmission using ARX model-based sensor data compression algorithm

Zhang

2006

Earthquake Engng Struct. Dyn.

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SUMMARYThis paper presents a linear predictor (LP)-based lossless sensor data compression algorithm for e cient transmission, storage and retrieval of seismic data. Auto-Regressive with eXogenous input (ARX) model is selected as the model structure of LP. Since earthquake ground motion is typically measured at the base of monitored structures, the ARX model parameters are calculated in a system identiÿcation framework using sensor network data and measured input signals. In this way, sensor data compression takes advantage of structural system information to maximize the sensor data compression performance. Numerical simulation results show that several factors including LP order, measurement noise, input and limited sensor number a ect the performance of the proposed lossless sensor data compression algorithm concerned. Generally, the lossless data compression algorithm is capable of reducing the size of raw sensor data while causing no information loss in the sensor data.

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“…Therefore, the strong-motion building array was designed to record abundant strong motions in a building during potential damaging earthquakes. Then the dynamic response of the buildings, which is strongly related to the damage of the buildings (Rojahn and Mork 1982;Çelebi et al 1993;Çelebi 2004;Hans et al 2005;Michel et al 2010), could be calculated by using these observed data.…”

Section: Strong-motion Building Arraymentioning

confidence: 99%