Project overview:

Physics based digital twins for optimal asset management

Awardee:

Tufts University

Started:

Q1, 2021

Technical Challenge Area:

O&M and Safety

Completed:

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.

NOWRDC Project Manager

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Senior Program Manager

Project Principle Investigator

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Professor of the Practice, Civil and Environmental Engineering

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