Purdue Center for Intelligent Infrastructure Hosts Presentation from Professor Danny Smyl
Purdue Center for Intelligent Infrastructure Hosts Presentation from Professor Danny Smyl
| Event Date: | October 14, 2021 |
|---|---|
| Priority: | No |
| College Calendar: | Show |
The Center for Intelligent Infrastructures (CII) is pleased to invite you to join us for a presentation by Professor Danny Smyl on applications of inverse problems to infrastructure nondestructive evaluation (NDE) and structural health monitoring (SHM). Professor Smyl hails from the Sunflower State and earned a BS and MS in Civil Engineering from the University of Kansas. Following, he was commissioned in the US Marine Corps where he served as an Engineer Officer. After retiring from active-duty service, Professor Smyl completed PhD studies at North Carolina State University, investigating NDE characterization of cement-based materials. During this time,
Professor Smyl traveled to Finland as a Fulbright Scholar researching inverse problems and AI in the Department of Applied Physics at the University of Eastern Finland. Thereafter, he worked as a research associate in the Mechanical Engineering Department at Aalto University, investigating optical methods for NDE. Presently, Professor Smyl is a Lecturer in Structural Engineering at the University of Sheffield in the UK and is transitioning to faculty at the University of South Alabama. When away from the computer, Danny enjoys spending time with his fiancé, fishing, and listening to physics podcasts.
Presentation Title: Some recent advances in inverse problems applied to NDE and SHM
Abstract: The field of inverse problems, the mathematics of estimating and understanding causalities from effects (data), has taken massive strides in the past 20 years. Since the advent of high performance, probabilistic, and learned computation, inversion-based applications in nondestructive evaluation (NDE) and structural health monitoring (SHM) have become increasingly pervasive. In this seminar, we highlight some key contemporary advances in inverse problems applied to NDE and SHM. In this effort, we evidence recent developments in learned (direct) inversion, multi-state reconstruction, sensor optimization, highly dynamical spatial loading prediction, and finite element model error prediction/compensation.
Date, Time, and Location: October 14th at 2:00 PM in ARMS 2008.
Virtual Option: https://purdue.webex.com/purdue/j.php?MTID=m3b6d2f58859c5cbf90215869a146b046
