Pilot Study: Learning Fluid-Structure Interaction via Machine Learning
PI: Barbara Simpson (OSU), barbara.simpson@oregonstate.edu, ORCID: 0000-0002-3661-9548
Co PIs: Michael Scott (OSU)
AMOUNT & MATCH: $40,000 from PacTrans; $40,000 Match
PERFORMANCE PERIOD: 8/16/2019 – 8/15/2021
STATUS: Completed
CATEGORIES: Natural Disasters, Bridges
DESCRIPTION: This proposal addresses the content area, improving mobility of people and goods, particularly ensuring reliable mobility across bridges after tsunami loading. This work also aligns with ongoing interest in tsunami loading on bridges and machine learning applications by the Oregon Department of Transportation and the Pacific Earthquake Engineering Research (PEER) Center.
Although implemented herein for the analysis of bridges, the resulting machine learning framework would be applicable to other computationally-expensive simulations and a larger set of data-driven transportation problems, such as evacuation models, active traffic control, analyzing sensor data, etc.
Implementing faster models that maintain the efficacy of the original data would result in prompt feedback for analysis and design, increased feasibility for parametric applications, and better fragility functions based on CFD/FSI rather than equivalent static analysis.
DELIVERABLE | DUE DATE | DATE RECEIVED |
Research Project Progress Report #1 | 4/10/2020 | 4/3/2020 |
Research Project Progress Report #2 | 10/10/2020 | 10/12/2020 |
Research Project Progress Report #3 | 4/10/2021 | 4/16/2021 |
Research Project Progress Report #4 | 10/10/2021 | 10/12/2021 |
No Cost Extension Request | 6/15/2021 | 6/3/2021 |
Draft Report | 6/15/2022 | 8/16/2022 |
Final Project Report | 8/15/2022 | 11/9/2022 |