报告承办单位：土木工程学院

报告内容：Cyclone resilience assessment of large-scale civil infrastructure systems  

报告人姓名：Hao Zhang

报告人所在单位： University of Sydney

报告人职称/职务及学术头衔：副教授

报告时间：4月17日（周三）15:00

报告地点：工科二号楼B302

报告人简介：Dr. Hao Zhang is an Associate Professor in the School of Civil Engineering at the University of Sydney. He obtained his BE and ME degrees from Tsinghua University, and PhD from Georgia Institute of Technology. His primary research interests lie in structural reliability theory, probability-based structural design, natural hazards, risk assessment and resilience of infrastructures. Dr Zhang has been consistently included in the Stanford’s list of World Top 2% Scientists, both for single year and career-long impact. He is on the Board of Directors Committee of CERRA (International Civil Engineering Risk and Reliability Association). He is on the editorial boards of several international journals, including Structural Safety, Reliability Engineering and System Safety. His research findings in the system reliability-based steel design have been incorporated into Australian Standards, including AS4600 Cold-formed Steel Structures and the draft revision of AS4100 Steel Structures.

报告摘要：Resilience analysis of spatially distributed infrastructure systems (e.g. an electric power system) under a scenario tropical cyclone must consider the spatial correlation of cyclone wind speeds to estimate their impact on the built environment. Previous studies have seldom considered the impact of this spatial correlation on damage assessments of distributed civil infrastructure. In this study, a stochastic cyclone wind field model is developed to capture the uncertainty of cyclone wind speeds and their spatial correlation. A series of recorded wind speed fields of historical cyclone events are examined. The bias between the recorded wind speeds and computed wind speeds based on a widely used cyclonic wind field model is obtained. The statistics of the wind field bias are estimated using geostatistical tools. The effect of wind speed uncertainty and spatial correlation on performance assessment of distributed infrastructure systems is illustrated using an electric power system, investigating its damage ratio, outage ratio and outage cost.