An Integrated Wind Risk Warning Model for Urban Rail Transport in Shanghai, China
by
Zhihui Han 1,2,3, Jianguo Tan 2,4,5,*, C. S. B. Grimmond 6
, Bingxin Ma 1, Tongxiao Yang 1 and Chunhui Weng 7
Zhihui Han 1,2,3, Jianguo Tan 2,4,5,*, C. S. B. Grimmond 6, Bingxin Ma 1, Tongxiao Yang 1 and Chunhui Weng 7
1
Shanghai Ecological Forecasting and Remote Sensing Center, Shanghai Meteorological Service, Shanghai 200030, China
2
Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Service, Shanghai 200030, China
3
State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200030, China
4
Shanghai Climate Center, Shanghai Meteorological Service, Shanghai 20003, China
5
Key Laboratory of Cities’ Mitigation and Adaptation to Climate Change in Shanghai, CMA, Shanghai 200030, China
6
Department of Meteorology, University of Reading, Reading RG6 6BB, UK
7
Shanghai Metro Operation Management Center, Shanghai 200030, China
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(1), 53; https://doi.org/10.3390/atmos11010053
Received: 7 November 2019 / Revised: 20 December 2019 / Accepted: 27 December 2019 / Published: 1 January 2020
(This article belongs to the Special Issue Climate Events and Extreme Weather )
The integrated wind risk warning model for rail transport presented has four elements: Background wind data, a wind field model, a vulnerability model, and a risk model. Background wind data uses observations in this study. Using the wind field model with effective surface roughness lengths, the background wind data are interpolated to a 30-m resolution grid. In the vulnerability model, the aerodynamic characteristics of railway vehicles are analyzed with CFD (Computational Fluid Dynamics) modelling. In the risk model, the maximum value of three aerodynamic forces is used as the criteria to evaluate rail safety and to quantify the risk level under extremely windy weather. The full model is tested for the Shanghai Metro Line 16 using wind conditions during Typhoon Chan-hom. The proposed approach enables quick quantification of real-time safety risk levels during typhoon landfall, providing sophisticated warning information for rail vehicle operation safety.
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MDPI and ACS Style
Han, Z.; Tan, J.; Grimmond, C.S.B.; Ma, B.; Yang, T.; Weng, C. An Integrated Wind Risk Warning Model for Urban Rail Transport in Shanghai, China. Atmosphere 2020, 11, 53.
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