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Probabilistic Digital Twins for System Monitoring and Decision-Making

Distinguished Research Seminar Series

20230502Prof Sankaran MahadevanEvent banner
  • Date

    02 May 2023

  • Organiser

    Department of Industrial and Systems Engineering, PolyU; Research Institute for Advanced Manufacturing (RIAM)

  • Time

    10:00 - 11:30

  • Venue



Prof. Sankaran Mahadevan

20230502Prof Sankaran MahadevanPoster


The digital twin paradigm integrates information obtained from sensor data, system physics models, as well as the operational and inspection/maintenance/repair history of a physical system or process of interest. As more and more data become available, the resulting updated model becomes increasingly accurate in predicting the future behavior of the system or process, and can potentially be used to support several objectives, such as safety, quality, mission planning, operational maneuvers, process control and risk management. This seminar will present recent advances in using Bayesian computational methods that advance the digital twin technology to support all these objectives, based on several types of computation: current state diagnosis, model updating, future state prognosis, and decision-making. All these computations are affected by uncertainty regarding system properties, operational parameters, usage, and environment, as well as uncertainties in data and prediction models. Thus, uncertainty quantification becomes an important need in system diagnosis and prognosis, considering both aleatory and epistemic uncertainty sources. The Bayesian methodology is able to address this need in a comprehensive manner and aggregate the uncertainty from multiple sources. A wide range of use cases such as additive manufacturing, aviation system safety, and power grid operations will be presented.

Keynote Speaker

Prof. Sankaran Mahadevan

Prof. Sankaran Mahadevan

John R. Murray Sr. Professor of Engineering
Department of Civil and Environmental Engineering
Vanderbilt University, United States


Professor Sankaran Mahadevan (Vanderbilt University, Nashville, TN, USA) has thirty-five years of research and teaching experience in uncertainty quantification, risk and reliability analysis, machine learning, system health diagnosis and prognosis, and optimization under uncertainty. He has applied these methods to a variety of structures, materials, and systems in civil, mechanical, and aerospace engineering, and to manufacturing processes and network systems. His research has been extensively funded by NSF, NASA, DOE, DOD, FAA, NIST, as well as GM, Chrysler, GE, Union Pacific, and Mitsubishi, and he has co-authored two textbooks and 350 peer-reviewed journal papers. During the past decade, he has been at the forefront of academic research on digital twin methodologies for air and marine transportation vehicles, buildings, additive manufacturing, and power grid networks. Professor Mahadevan is currently President of the ASCE Engineering Mechanics Institute, Managing Editor of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, and a winner of the Senior Distinguished Research Award from the International Association of Structural Safety and Reliability. He is a Fellow of the American Institute of Aeronautics and Astronautics (AIAA), Engineering Mechanics Institute (ASCE), and the Prognostics & Health Management Society.

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