Project overview:
Physics based digital twins for optimal asset management
Awardee:
Tufts University
Start Date:
Q1, 2021
Technical Challenge Area:
O&M and Safety
Completion Date:
Q1, 2023
Synopsis:
Tufts University is developing an algorithm that integrates a physics-based model of offshore wind turbines with live measurement data from turbines. The software allows offshore wind asset managers to remotely access actionable turbine health data, providing them with predictive maintenance and failure prediction capabilities.
Target Outcomes:
1
Develop optimal, low-cost measurement regimes for offshore wind turbines (OWT) that enable advanced physics-based digital twin technologies
2
These advanced digital twins shall enable load prediction, virtual sensing, and damage prognosis for the U.S. offshore environment.
Project Principal Investigator
Professor of the Practice, Civil and Environmental Engineering