Estimation of strong motion distribution in the 1995 Kobe earthquake based on building damage data

Yamaguchi, Naoya; Yamazaki, Fumio

doi:10.1002/eqe.33

Cited by 47 publications

(26 citation statements)

References 18 publications

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“…In the 1995 Kobe earthquake (M w 6.9), about 49 000 buildings were collapsed (G5 in EMS-98 scale) or severely damaged (G4) out of 560 000 buildings in the affected urban area (Building Research Institute, 1996). The recorded strong motion distribution in the Kobe earthquake was at a similar level to that of the Kumamoto earthquake (Yamaguchi and Yamazaki, 2001). However, in 1995, the number of strong motion accelerometers was much lower, about only 10 in the hard-hit zone.…”

Section: Discussionmentioning

confidence: 54%

“…For instance, Whitman et al (1973) provided earthquake damage probability matrices using data collected after the 1971 San Fernando, California earthquake. Yamazaki and Murao (2000) proposed vulnerability functions for Japanese buildings based on building inventory and damage data and the spatial distribution of strong motion (Yamaguchi and Yamazaki, 2001) during the 1995 Kobe earthquake in Japan.…”

Section: Introductionmentioning

confidence: 99%

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Detection of collapsed buildings from lidar data due to the 2016 Kumamoto earthquake in Japan

Moya¹,

Yamazaki

Wen

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. The 2016 Kumamoto earthquake sequence was triggered by an M w 6.2 event at 21:26 on 14 April. Approximately 28 h later, at 01:25 on 16 April, an M w 7.0 event (the mainshock) followed. The epicenters of both events were located near the residential area of Mashiki and affected the region nearby. Due to very strong seismic ground motion, the earthquake produced extensive damage to buildings and infrastructure. In this paper, collapsed buildings were detected using a pair of digital surface models (DSMs), taken before and after the 16 April mainshock by airborne light detection and ranging (lidar) flights. Different methods were evaluated to identify collapsed buildings from the DSMs. The change in average elevation within a building footprint was found to be the most important factor. Finally, the distribution of collapsed buildings in the study area was presented, and the result was consistent with that of a building damage survey performed after the earthquake.

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Section: Discussionmentioning

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Detection of collapsed buildings from lidar data due to the 2016 Kumamoto earthquake in Japan

Moya¹,

Yamazaki

Wen

et al. 2018

Nat. Hazards Earth Syst. Sci.

Self Cite

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“…For comparison, a complete numerical analysis using the same FEM model used for the pushover analysis is also performed. The faultnormal component of the 1995 JMA Kobe ground motion is adopted for these analyses [24]. A 28% difference in the displacement response of the first story can be observed in Figure 5(a) between the initial-stiffness scheme and the overall analysis, while the difference is rather limited, 3%, comparing the secant stiffness with the overall analysis.…”

Section: Numerical Analyses By P2p Frameworkmentioning

confidence: 99%

“…A time interval of 0.01 s is adopted. The fault-normal ground motion recorded at the JR Takatori station during the 1995 Hyogoken-Nanbu earthquake [24] is used. The ground motion is enlarged by 1.5 times to ensure severe damage to the column base and eventual collapse.…”

Section: Distributed Testmentioning

confidence: 99%

Collapse simulation of a four‐story steel moment frame by a distributed online hybrid test

Wang

McCormick

Yoshitake

et al. 2008

Earthq Engng Struct Dyn

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SUMMARYThe collapse of a one-bay, four-story steel moment frame is simulated in this study by the proposed peer-to-peer (P2P) Internet online hybrid test system. The typical beam hinging mechanism, which is ensured by a strong-column, weak-beam design, is reproduced. The plastic hinges at the column bases are taken as the experimental portions, while the superstructure is analyzed numerically by a general-purpose finite element program. The implicit plastic rotations of the two column bases are treated as boundary displacements. In order to account for the complex behavior of the column bases, the P2P system is modified to use the secant stiffness during iterations, and the physical specimens are designed such that the plastic hinge behavior can be obtained. For this study, the three substructures are distributed to different locations. A large ground motion is repeatedly imposed until the column bases lose their capacity to sustain the gravity load. As a result, significant deterioration is observed at both column bases. The proposed P2P system is thus demonstrated to be able to accommodate multiple-tested substructures involving unstable behavior. The results suggest that the P2P Internet online hybrid test system provides a reliable means of studying structures up to collapse.

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“…They are expressed in different mathematical forms and can be based on observation data from one or more earthquakes. Even if sample sizes vary from 20 (Sarabandi et al 2004) up to hundreds of thousands of data (e.g., Yamaguchi and Yamazaki 2001), a suitable sample size can be considered 200 or above (Rossetto et al 2013).…”

Section: Empirical Fragility Relationshipsmentioning

confidence: 99%

RC infilled building performance against the evidence of the 2016 EEFIT Central Italy post-earthquake reconnaissance mission: empirical fragilities and comparison with the FAST method

Luca

Woods

Galasso

et al. 2017

Bull Earthquake Eng

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Damage data on low-to-mid-rise Reinforced Concrete (RC) buildings, collected during the UK Earthquake Engineering Field Investigation Team post-earthquake reconnaissance mission on the August 24 Central Italy earthquake, are employed to derive empirical fragility relationships. Given the small dataset, the new data distributions are used for the Bayesian update of fragility functions derived for the L'Aquila earthquake (same seismic region and similar construction typologies). Other properties such as number of storeys, age of construction and shape in plan of the buildings are also analyzed. This information is employed to assess the ability of the FAST method to predict damage states in non-regular infilled RC buildings for the municipalities of Amatrice, Accumoli, Arquata del Tronto and Norcia, all severely affected by the 2016 Central Italy sequence. FAST is a spectral-based method to derive capacity curves and peak ground acceleration damage state thresholds for buildings. It is a dedicated methodology for regular RC frame buildings with masonry infills, first calibrated on damage data from the 2009 L'Aquila earthquake and applied to the 2011 Lorca (Spain), the 2012 Emilia (Italy) events for damage backanalyses. The new data from the August 2016 Central Italy earthquake provide a test-bed for FAST further employments in case of less homogenous building samples. The application of FAST presented here accounts for different shake-maps produced by both the United States Geological Survey and the Italian National Institute of Geophysics and Volcanology which are significantly different and representative of different refinements of the demand scenario. For the area of Amatrice, where the two shake-maps provide similar estimates and the buildings considered match reasonably well the typology for which FAST is calibrated, the comparison between damage level observed and as provided by

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Estimation of strong motion distribution in the 1995 Kobe earthquake based on building damage data

Cited by 47 publications

References 18 publications

Detection of collapsed buildings from lidar data due to the 2016 Kumamoto earthquake in Japan

Detection of collapsed buildings from lidar data due to the 2016 Kumamoto earthquake in Japan

Collapse simulation of a four‐story steel moment frame by a distributed online hybrid test

RC infilled building performance against the evidence of the 2016 EEFIT Central Italy post-earthquake reconnaissance mission: empirical fragilities and comparison with the FAST method

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