A spectrum-based earthquake record truncation method for nonlinear dynamic analysis of arch dams. Issue 132 (May 2020)

• Record Type: Journal Article
• Authors: Jin, Ai-Yun; Pan, Jian-Wen; Wang, Jin-Ting; Du, Xiu-Li
• Is Part Of: Soil dynamics and earthquake engineering. Issue 132(2020)
• Publication Date: 2020-05
• Subjects: Arch dam -- Dynamic analysis -- Damage -- Earthquake record truncation -- Acceleration response spectrum; Soil dynamics -- Periodicals; Earthquake engineering -- Periodicals; Sols -- Dynamique -- Périodiques; Génie parasismique -- Périodiques; 624.176205
• DOI: 10.1016/j.soildyn.2020.106104
• Languages: English
• ISSNs: 0267-7261

Abstract

Abstract: Due to the complexity of the model and the long duration of earthquake records, the nonlinear dynamic analysis of arch dams consumes a lot of calculation time. In this paper, an earthquake record truncation method based on the acceleration response spectrum (ARS) is proposed to save the calculation time of nonlinear dynamic analysis of arch dams. The nonlinear dynamic responses of the 210m-high Dagangshan dam of China are performed as a numerical example. Firstly, the statistical relationship between the Arias intensity (AI) and ARS is investigated using a large number of actual ground motion records. Secondly, the spectrum-based earthquake record truncation method is proposed. Finally, the accuracy of the proposed method is verified using the actual earthquake records, and the efficiency of the proposed method is compared with the AI-based method. Analysis results show that the proposed method, considering the structural characteristics of the arch dam, can save more calculation time than the AI-based method, while ensuring a sufficiently accurate calculation result. Highlights: The statistical relationship between ARS and AI is investigated using a large number of actual earthquake records. It is found that the AI-based earthquake record truncating method may be conservative for arch dams. A spectrum-based method is proposed, which considers the structural characteristics of the arch dam. The proposed method is proved to be accurate and it has advantages in reducing calculation time over the AI-based method.