Browsing by Author "Liao, W."

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A cost-benefit analysis of sensor quality and spatial density for rapid regional post-event seismic damage assessment: Application to Istanbul
(Elsevier, 2022-12) Cheng, Q.; Liao, W.; Fei, Y.; Tian, Y.; Lu, X.; Zhang, W.; Ghahari, F.; Kurtuluş, Aslı; Taciroglu, E.; Civil Engineering; KURTULUŞ, Asli
A quantitative evaluation of the influence of sensor quality and spatial density on the results of rapid regional seismic damage evaluations of buildings can provide an important reference for the deployment of a strong-motion network. However, the influence of sensor quality and spatial density on seismic damage assessment is still unclear. Therefore, a cost-benefit analysis framework of sensor quality and spatial density for rapid regional post-event seismic damage assessment is proposed. In this framework, a simulation method for sensor-recorded ground motions and an interpolation-based ground motion field refinement method are used to consider the influence of the quality and density of the sensor network. The accuracies of seismic damage assessments with different sensor layout schemes were compared using the time-history analysis-based regional seismic damage assessment method, through which the influence of sensor quality and spatial density on the seismic damage assessment can be quantitatively evaluated. Finally, the Zeytinburnu district of Istanbul was selected as an example for illustrating the proposed framework. The main conclusions are as follows: (1) the spatial density of the sensors used is more significant for improving the accuracy of a seismic damage assessment than the quality of the sensors used; (2) the influence of population density can be considered using the proposed framework; and (3) the proposed framework can quantitatively consider the influence of sensor quality and spatial density on the rapid regional seismic damage assessment of buildings, which provides an important reference for the deployment of a strong-motion network for a given budget.
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Influence of accelerometer type on uncertainties in recorded ground motions and seismic damage assessment
(Springer, 2022-07) Liao, W.; Fei, Y.; Ghahari, F.; Zhang, W.; Chen, P. Y.; Kurtuluş, Aslı; Yen, C. H.; Cheng, Q.; Lu, X.; Taciroglu, E.; Civil Engineering; KURTULUŞ, Asli
Strong motion data recorded by strong-motion networks are essential for preventing and mitigating earthquake disasters, such as earthquake early warning and earthquake emergency responses, and the type of accelerometer can significantly influence the quality of recorded ground motions (GMs) and the subsequent usage. Different types of accelerometers vary significantly in both the price and the quality of collected data, because cheap accelerometers generate non-negligible self-noise and reduce the quality of the collected GMs. However, the effects of the accelerometer type and spatial density on the accuracy of GM-based seismic damage assessment are still unknown. The present study attempts to quantify these effects comprehensively at a regional scale. First, a method to simulate recorded data from different quality sensors is devised, using characteristics of existing low-, medium-, and high-quality accelerometers. These simulations use input data from either the Pacific Earthquake Engineering GM database or from a high-fidelity fault rupture and regional wave propagation simulation. Subsequently, the simulated sensor data are used to assess the seismic damage to typical buildings at a city scale. The results indicate that low-quality sensors found in most smartphones are currently insufficient for assessing seismic damage. Medium-quality accelerometers (MEMS-based instruments), on the other hand, can provide feasible solutions for cost-effective city-scale deployment and may offer deployment options that are superior to sensor networks with high-quality accelerometers.
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Influence of sensor density on seismic damage assessment: A case study for istanbul
(Seismological Society of America, 2022-08) Cheng, Q.; Fei, Y.; Lu, X.; Liao, W.; Zhang, W.; Chen, P. Y.; Kurtuluş, Aslı; Ghahari, F.; Vela, V.; Taciroglu, E.; Civil Engineering; KURTULUŞ, Asli
The strong ground motions (GMs) recorded by strong motion networks are significant to increase the accuracy of seismic damage assessment. However, the influence of sensor density on seismic damage assessment remains unclarified. Therefore, a workflow is proposed in this study to quantitatively analyze the influence of sensor density on seismic damage assessment. The scenario-based earthquake simulation method is first used to provide the time history of GM at each location as the ground truth of the analysis. Subsequently, a GM prediction method, namely the interpolation method, is adopted to predict GMs at locations without sensors using measuring data from the limited sensors. Finally, the building scale and region scale seismic damage under different sensor densities are compared to quantitatively analyze the influence of sensor density on seismic damage assessment. A detailed case study for Zeytinburnu District, Istanbul, Turkey, is performed to demonstrate the proposed methods. The findings of this study can provide an important reference for seismic damage assessment and the deployment of strong motion networks.