Regional Ground Motion Prediction Equation Developed for the Korean Peninsula Using Recorded and Simulated Ground Motions

Jee, Hyun Woo; Han, Sang Whan

doi:10.1080/13632469.2021.1871682

Cited by 9 publications

(1 citation statement)

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“…Cumulating ground motion records over time with an increased number of seismic stations, some GMMs have been developed empirically (Emolo et al, 2015), but still, the largest M W is low to be considered for the seismic design practice. A hybrid approach, combining empirical data set and ground motion from stochastic simulation, was another way for the GMM development (Jee and Han, 2021).…”

Section: Introductionmentioning

confidence: 99%

Linearly combined ground motion model using quadratic programming for low- to mid-size seismicity region: South Korea

Jang

Ahn²,

Kim³

et al. 2023

Front. Earth Sci.

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This study suggests a linearly combined ground motion model (GMM) optimized for the within-rock conditions of South Korea. Ground motions recorded by accelerometers positioned in within-rock layers are used as target intensity measures (IMs), and five local GMMs and four global GMMs are used as candidates for combination. Optimization, which seeks to find a weight vector minimizing the uncertainty of the combined model, is performed using the quadratic programming (QP) technique, which provides very fast and solid results for the linear combination problem. This study illustrates how to use the QP technique for the linear combination problems. Also, we suggest optimized weight vectors for GMM combinations for two conditions: 1) the IM prediction of a scenario event without observations and 2) the IM prediction of a past event with observations. Among the local and global GMMs considered, JB03, Eea15, JH21, and BSSA14 are selected as the best four GMMs for the first condition, and Jea02, JB03, JH21, and CB14 are selected as the best four GMMs for the second condition. The combined model reduces the standard deviation of residuals in natural logarithms by 10% and 8% for the first and second conditions, respectively, compared to the best individual GMM at each period. Among the GMMs considered, the prediction by Eea15 is only applicable for magnitudes less than 5. Hence, for large magnitude (Mw > 5) prediction, CB14 is recommended instead of Eea15 for the best four models for the first condition.

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Section: Introductionmentioning

confidence: 99%

Linearly combined ground motion model using quadratic programming for low- to mid-size seismicity region: South Korea

Jang

Ahn²,

Kim³

et al. 2023

Front. Earth Sci.

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Correction factors for GMMs considering site and topographic effects in South Korea

Park

Lee

Kim

2021

Bull Earthquake Eng

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Simulation of ground motions in the Korean peninsula using a stochastic model with generalized inversion technique

Jee,

Han

2024

Bull Earthquake Eng

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In low to moderate seismic regions such as the Korean peninsula, it is di cult to perform seismic hazard analyses to construct hazard maps and curves because only a limited number of strong ground motion records is available. In this study, to solve such obstacles, ground motions were simulated using a model with a GIT-based spectral decomposition algorithm. The algorithm was adopted to determine the constituent parameters (source effect, path effect, site effect) of the Fourier amplitude spectrum (FAS) while considering Korea's seismological characteristics. The accuracy of the GIT-based spectral decomposition algorithm for FAS and the ground motion simulation (GMS) model with the calculated FAS values was veri ed.

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Regional Ground Motion Prediction Equation Developed for the Korean Peninsula Using Recorded and Simulated Ground Motions

Cited by 9 publications

References 50 publications

Linearly combined ground motion model using quadratic programming for low- to mid-size seismicity region: South Korea

Linearly combined ground motion model using quadratic programming for low- to mid-size seismicity region: South Korea

Correction factors for GMMs considering site and topographic effects in South Korea

Simulation of ground motions in the Korean peninsula using a stochastic model with generalized inversion technique

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