Improvement of and Parameter Identification for the Bimodal Time-Varying Modified Kanai-Tajimi Power Spectral Model
Joint Authors
Ren, Junru
Zhong, Ting
Liu, Guocui
Chen, Huiguo
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Based on the Kanai-Tajimi power spectrum filtering method proposed by Du Xiuli et al., a genetic algorithm and a quadratic optimization identification technique are employed to improve the bimodal time-varying modified Kanai-Tajimi power spectral model and the parameter identification method proposed by Vlachos et al.
Additionally, a method for modeling time-varying power spectrum parameters for ground motion is proposed.
The 8244 Orion and Chi-Chi earthquake accelerograms are selected as examples for time-varying power spectral model parameter identification and ground motion simulations to verify the feasibility and effectiveness of the improved bimodal time-varying modified Kanai-Tajimi power spectral model.
The results of this study provide important references for designing ground motion inputs for seismic analyses of major engineering structures.
American Psychological Association (APA)
Chen, Huiguo& Zhong, Ting& Liu, Guocui& Ren, Junru. 2017. Improvement of and Parameter Identification for the Bimodal Time-Varying Modified Kanai-Tajimi Power Spectral Model. Shock and Vibration،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1204997
Modern Language Association (MLA)
Chen, Huiguo…[et al.]. Improvement of and Parameter Identification for the Bimodal Time-Varying Modified Kanai-Tajimi Power Spectral Model. Shock and Vibration No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1204997
American Medical Association (AMA)
Chen, Huiguo& Zhong, Ting& Liu, Guocui& Ren, Junru. Improvement of and Parameter Identification for the Bimodal Time-Varying Modified Kanai-Tajimi Power Spectral Model. Shock and Vibration. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1204997
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204997