V s30 Prediction Models Based on Measured Shear-Wave Velocities in Tangshan, China

Yi Fang, Hao Li, Yu Li, Guoxing Chen (), Yuejun Lv and Yanju Peng
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Yi Fang: Institute of Geotechnical Engineering, Nanjing Tech University, Nanjing 211816, China
Hao Li: Institute of Geotechnical Engineering, Nanjing Tech University, Nanjing 211816, China
Yu Li: National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
Guoxing Chen: Institute of Geotechnical Engineering, Nanjing Tech University, Nanjing 211816, China
Yuejun Lv: National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
Yanju Peng: National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China

Sustainability, 2023, vol. 15, issue 4, 1-13

Abstract: V s30 (equivalent shear-wave velocity of soil layers within a depth of 30 m underground) is widely used in the field of seismic engineering; however, due to the limitation of funds, time, measuring devices, and other factors, the depth for testing shear-wave velocity in an engineering site rarely reaches 30 m underground. Therefore, it is necessary to predict Vs30 effectively. We analyzed the existing models using 343 boreholes with depths greater than 30 m in Tangshan, China. It shows that the topographic slope method is not suitable for predicting V s30 in Tangshan. The Boore (2011) model overestimates, while Boore (2004) underestimates V s30 in Tangshan, while Junju Xie’s (2016) model has ideal prediction results. We propose three new models in this paper, including the bottom constant velocity (BCV) model, linear model, and conditional independent model. We find that the BCV model has limited prediction ability, and the linear model is more suitable when z ≤ 18 m, while the conditional independent model shows good performance under conditions where z > 18 m. We propose that the model can be accurately and effectively applied in Tangshan and other regions with low shear-wave velocity.

Keywords: shear-wave velocity; Tangshan; topographic slope; prediction model; log-likelihood (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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