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Empirical relationships between Arias Intensity and peak ground acceleration for western China.
- Source :
- Frontiers in Earth Science; 2024, p1-15, 15p
- Publication Year :
- 2024
-
Abstract
- There is little available attenuation relationship for Arias Intensity (AI) in China. Empirical relationships between AI and peak ground acceleration (PGA) provide another option for predicting AI. We establish empirical relationships for AI and PGA for western China, utilizing 3,169 horizontal and 979 vertical strong motion records with PGA >0.01 g from 274 earthquakes (M[sub S] 4.0-8.0), originating in eight provinces in southwest (Yunnan, Sichuan) and northwest China (Gansu, Shaanxi, Ningxia, Qinghai, Inner Mongolia, and Xinjiang). The influences of M[sub S] epicenter distance, and site conditions indicators V[sub S30], generic site classes (i.e., rock and soil) are explored. The results show that the logarithm of AI increases linearly with the increase of the logarithm of PGA and M[sub S], and decreases with the logarithm of V[sub S30]. However, the influence of site conditions on AI-PAG relationships can't be recognized by the simple generic rock and soil site classes. The epicenter distance has little effect on the AI-PAG relationships. Empirical relationships are developed to estimate horizontal or vertical AI as a function of PGA (basic model), PGA and M[sub S] (model 2) for southwest, northwest, and western China, using all the records. Empirical relationships for AI as a function of PGA, M[sub S], and V[sub S30] (model 1) are established using the 2,248 horizontal (70.9% of the total) and 670 vertical (68.4% of the total) records with V[sub S30] between 148 and 841m/s. The notable disparity between model 1 of the southwest and northwest regions is chiefly attributed to local site conditions, indicating that the AI-PGA correlation is region-dependent. These findings enable one way of estimating AI for western China and will contribute to a better understanding of AI attenuation. [ABSTRACT FROM AUTHOR]
- Subjects :
- VERTICAL motion
EMPIRICAL research
ARTIFICIAL intelligence
LOGARITHMS
EARTHQUAKES
Subjects
Details
- Language :
- English
- ISSN :
- 22966463
- Database :
- Complementary Index
- Journal :
- Frontiers in Earth Science
- Publication Type :
- Academic Journal
- Accession number :
- 178758374
- Full Text :
- https://doi.org/10.3389/feart.2024.1434194