| Seismic attenuation relationship with homogeneous and heterogeneous prediction-error variance models |
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| 作者姓名： | He-Qing Mu Rong-Rong Xu and Ka-Veng Yuen |
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| 基金项目： | Research Committee of University of Macau under Research Grant No.MYRG081(Y1-L2)-FST13-YKV;the Science and Technology Development Fund of the Macau SAR government under Grant No.012/2013/A1 |
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| 摘 要： | Peak ground acceleration(PGA) estimation is an important task in earthquake engineering practice.One of the most well-known models is the Boore-Joyner-Fumal formula,which estimates the PGA using the moment magnitude,the site-to-fault distance and the site foundation properties.In the present study,the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an effi ciency-robustness balanced formula is proposed.For this purpose,a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship.In this approach,each model class(a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data.The one with the highest plausibility is robust since it possesses the optimal balance between the data fi tting capability and the sensitivity to noise.A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis.The optimal predictive formula is proposed based on this database.It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore,Joyner and Fumal(1993).
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| 关 键 词： | Bayesian inference Boore-Joyner-Fumal formula heterogeneity variance input-dependent variance model class selection peak ground acceleration seismic attenuation |
Seismic safety of high concrete dams |
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| He-Qing Mu,Rong-Rong Xu and Ka-Veng Yuen.Seismic attenuation relationship with homogeneous and heterogeneous prediction-error variance models[J].Earthquake Engineering and Engineering Vibration,2014,13(1):1-11. |
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| Authors: | Houqun Chen |
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| Institution: | 1. Faculty of Science and Technology, University of Macau, Macao, China
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| Abstract: | Peak ground acceleration (PGA) estimation is an important task in earthquake engineering practice. One of the most well-known models is the Boore-Joyner-Fumal formula, which estimates the PGA using the moment magnitude, the site-to-fault distance and the site foundation properties. In the present study, the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an efficiency-robustness balanced formula is proposed. For this purpose, a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship. In this approach, each model class (a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data. The one with the highest plausibility is robust since it possesses the optimal balance between the data fitting capability and the sensitivity to noise. A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis. The optimal predictive formula is proposed based on this database. It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore, Joyner and Fumal (1993). |
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| Keywords: | Bayesian inference Boore-Joyner-Fumal formula heterogeneity variance input-dependent variance model class selection peak ground acceleration seismic attenuation |
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