Simplified Prediction Method for PGA Amplification Factors Corrected by Site Conditions

CHEN Longwei; WU Xiaoyang; TANG Chuan

doi:10.3969/j.issn.0258-2724.20200508

Volume 57 Issue 1

Feb. 2022

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Journal of Southwest Jiaotong University > 2022 > 57(1): 173-181.

CHEN Longwei, WU Xiaoyang, TANG Chuan. Simplified Prediction Method for PGA Amplification Factors Corrected by Site Conditions[J]. Journal of Southwest Jiaotong University, 2022, 57(1): 173-181. doi: 10.3969/j.issn.0258-2724.20200508

Citation:

CHEN Longwei, WU Xiaoyang, TANG Chuan. Simplified Prediction Method for PGA Amplification Factors Corrected by Site Conditions[J]. Journal of Southwest Jiaotong University, 2022, 57(1): 173-181. doi: 10.3969/j.issn.0258-2724.20200508

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Simplified Prediction Method for PGA Amplification Factors Corrected by Site Conditions

doi: 10.3969/j.issn.0258-2724.20200508

CHEN Longwei^{1, 2
,},
WU Xiaoyang^{1, 2},
TANG Chuan^{1, 2}

1.
Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China
2.
Key Laboratory of Earthquake Engineering and Engineering Vibration, China Earthquake Administration, Harbin 150080, China

Received Date: 04 Aug 2020
Rev Recd Date: 25 Nov 2020

Available Online: 25 Dec 2020

Publish Date: 25 Dec 2020

Abstract

Abstract

Peak ground-motion acceleration (PGA) directly reflects ground shaking intensity with the advantages in conceptual clarity and engineering application. Prediction of PGA, along with site condition correction, needs to be handled in site-specific seismic design. In this work, 32 stations and the earthquake data recorded are collected from the KiK-net strong motion array, Japan, so as to propose a simplified method to predict PGA amplification factors (f_PGA) corrected by site condition. Linear and quadratic empirical formulae of the f_PGA possibility model parameters with respect to the combinations of site characteristic parameters are obtained via regression analysis. Using the f_PGA model, ground surface PGA values, corrected by site conditions, can be predicted under different exceedance probability levels. Data analysis indicates that f_PGA is variable but can be simulated by a log-normally distributed function, of which mean and standard deviation are less correlated with a single site characteristic parameter but have good correlation with the linear combinations of the site characteristic parameters. The reasonable agreement between the predictions and records testifies the feasibility of the proposed method.
- seismic data,
- PGA amplification factor,
- site correction,
- simplified method,
- KiK-net

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References(21)

References

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