Sep-24-2026 - INFORMS RAS International Webinar #35: Tianyu Han: Rail Recovery after Earthquakes
Railway Applications Section Informs
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Sep-24-2026 - INFORMS RAS International Webinar #35: Tianyu Han: Rail Recovery after Earthquakes
9 просмотров · 4 дн. назад
Railway Applications Section Informs
154 подписчика
9 просмотров · 4 дн. назад
Abstract:
Earthquakes can disrupt critical rail links, reduce regional mobility, and place pressure on substitute roads and transit services. Restoring service requires not only repairing physical damage but also coordinating inspections, operating restrictions, replacement buses, personnel, staging, and public information. This webinar will explore these connected challenges through BART's Berkeley Hills Tunnel in the San Francisco Bay Area, a single critical rail link that intersects the Hayward Fault. The webinar will show how tunnel damage is translated into operating and restoration scenarios, how disruptions affect cross-hills mobility, and why strategies such as bus bridges depend on institutional resources and coordination. The findings and analyses are built upon detailed tunnel analysis developed by UCLA engineers, multimodal transportation modeling at UC Berkeley, and interviews with BART, Caltrans, and regional agencies. The webinar will address actionable insights for scenario planning, interagency preparedness, and implementable recovery strategies
Bio:
Tianyu Han is a PhD candidate under the supervision of Prof. Kenichi Soga at the Department of Civil and Environmental Engineering at the University of California, Berkeley. His research focuses on the risk, resilience, and recovery of urban infrastructure systems exposed to natural hazards, including transportation networks and buried water and gas pipelines. Through his work with the NHERI SimCenter and collaborations with government agencies and engineering consulting firms, he has contributed to a range of infrastructure resilience projects. His work combines engineering analysis, probabilistic risk assessment, infrastructure and network modeling, and decision support to improve preparedness and recovery planning.