Speaker: Pingbo Tang ，Associate Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University

Time: 13:00-14:00 Oct. 28th, 2019

Venue: Tongji Building Block A Room 306

Speaker’s Bio:

Pingbo Tang, Ph.D., P.E., is an associate professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University. He founded and is directing Spatiotemporal Workflows and Resilient Management Laboratory (SWARM Lab). He obtained his bachelor’s degree of Civil Engineering in 2002, and his master’s degree of Bridge Engineering in 2005, both from Tongji University, China. He obtained is Ph.D. degree from the group of Advanced Infrastructure Systems (AIS) at Carnegie Mellon University in 2009. Tang’s research explores the remote sensing, human systems engineering, data analytics, and information modeling technology to support spatiotemporal analyses needed for predictive management of constructed facilities, workspaces and civil infrastructure systems. His on-going studies have been examining sensing and modeling methods for comprehending the Human-Cyber-Physical-Systems (H-CPS) in accelerated construction and infrastructure operations (e.g., airport operations, nuclear plant outage control). He has published more than 100 peer-reviewed articles in these areas. Tang holds memberships or leadership positions of multiple professional organizations, including serving as the Chair of the Data Sensing and Analysis committee of the American Society of Civil Engineers (ASCE). He is on the editorial board of ASCE Journal of Computing in Civil Engineering, as well as a reviewer of multiple top journals and conferences related to Computing in Civil Engineering. He won best paper/poster awards on top conferences, the 2013 Recent Alumnus Achievement Award of the Civil and Environmental Engineering Department at Carnegie Mellon University, and the National Science Foundation CAREER Award in 2015.

Abstract:

The operation and maintenance of aging civil infrastructures (e.g., bridges, airports, power plants, and water facilities) in built environments pose various systems security challenges that interweave natural, technical, and human decision and operational processes. While information and communication technologies enable engineers, stakeholders, and the public to collaborate on civil infrastructure operation and maintenance, the interactions between people and technology form dynamic human-technology systems that can link people into teams.  However, these interactions sometimes introduce redundancies, confusions, delays, and errors. For example, when thousands of workers and managers are simultaneously working on a shutdown of an old nuclear power plant for refueling and maintenance, minor cognitive and communication errors in exchanging task status and sensory pressure data can cause failures in operating connected water and electronic systems. Such failures can result in expensive delays and accidents. In particular, one day of delay in a refueling project of a nuclear power plant can cost 1.5 million dollars for purchasing external electricity during the outage. Similar challenges occur when people are collaborating on technology uses for the monitoring and control of changing civil infrastructure systems, such as in gate management of water distribution systems, air traffic control, and accelerated bridge construction in busy cities.

This presentation introduces a dynamic human-technology reliability analysis framework that captures, diagnoses, and predicts risks of human-technology interaction and collaboration processes in civil infrastructure operation and maintenance. This framework integrates reliable human behavior tracking and analysis technologies, automated sensory data collection and analysis techniques, stochastic models for data-driven human-in-the-loop simulations, and spatiotemporal knowledge-based reasoning for automatic vulnerability checking of human-technology systems. The presenter will use case studies to illustrate how this dynamic human-technology reliability analysis framework enables risk assessment of the operation and maintenance processes of civil infrastructure systems. These cases include the dry-up planning and operation in of a canal system in Arizona, air traffic analyses and control of two main airports, and outage control of a nuclear power plant.