主讲人：Qingwen Zhou Assistant Professor

邀请人：李辉 教授、张献英 特聘研究员

时间：2024年6月21日（周五）上午10:00-11:30

地点：通达馆103会议室

主讲人简介：

Dr. Qingwen Zhou is an Assistant Professor at Wayne State University, starting January 1, 2024. She earned her Ph.D. degree from the University of Illinois Urbana-Champaign in December 2023, where she also earned a master's degree in 2019. She received her bachelor's degree from Tongji University in 2016. Dr. Zhou's research focuses on infrastructure sustainability and resilience, with particular interests in life-cycle assessment (LCA), life-cycle cost analysis (LCCA), social LCA, interactions between emerging vehicles and pavement, infrastructure health monitoring, infrastructure sensing, and the application of machine learning/deep learning techniques, including physics-informed machine learning. She has participated in several research projects funded by the Federal Highway Administration, Federal Aviation Administration, Illinois Department of Transportation, Center for Connected and Autonomous Transportation, University Transportation Centers, and the Center for Highway Pavement Preservation. Dr. Zhou is also a member of the American Society of Civil Engineers and the Academy of Pavement Science and Engineering.

主讲内容简介：

In the global effort to combat climate change, sustainability assessment in transportation engineering has become a critical concern. As a key sector in transportation, conducting sustainability assessments on pavements can provide governments and agencies with reliable knowledge and approaches to improve transportation sustainability. The presenter will share experiences on conducting pavement sustainability assessments in the U.S., including the use of life cycle assessments (LCA) and environmental product declarations (EPD) as standard methods for selecting sustainable pavement materials and designs. Current practices of implementing pavement sustainability assessment in China will also be reviewed in the presentation. Additionally, promoting new and innovative materials, design procedures, and specifications will help accelerate the adoption of sustainable pavement practices. The presenter will also present an example of applying physics-informed machine learning in advanced pavement design to improve pavement sustainability.

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