Structural Health Monitoring intern
About Principle Power
Principle Power is a leading global technology and services provider for the floating offshore wind energy market. The WindFloat®, the company’s globally and proven floating platform technology, enables offshore wind turbines to be sited in any water depth or seabed condition, unlocking offshore wind potential worldwide and allowing projects to harvest the best wind resources. Principle Power acts as a trusted partner to developers, independent power producers, utilities, and EPCs, supporting its customers throughout the entire lifecycle of their projects. With 105 MW of cumulative capacity in operation or under advanced development and a multi-GW commercial pipeline globally, Principle Power is the market leader in floating offshore wind technology.
PPI recently completed a R&D project – DigiFloat – that aimed at developing a prototype Digital Twin of an asset of the WindFloat Atlantic© floating wind farm offshore Viana do Castello, Portugal. The internship focuses on further developing the Structural Health Monitoring (SHM) capabilities of such tools.
The internship will be articulated around three main blocks:
- Conversion matrix approach for floating wind semi-submersible foundation
- Data analytics of strain gauge data from WindFloat Atlantic© floating wind farm
- Operational structural health monitoring
The first block deals with the so-called conversion matrix approach and its numerical application to the WindFloat© platform. The base of the conversion matrix approach in this context is to use a reduced number of measurements made on a structure, and combine them to get the desired output quantities that cannot be directly measured. In this case, the measurements are obtained from Strain Gauges (SG) placed on the structure, and the desired outputs are internal loads and/or hot spot stresses used for fatigue calculations. The approach has been developed and tested on a variety of marine systems (containerships and FPSO).
The successful candidate will further validate the approach for a semi-submersible floating wind platform, basing her/his work on existing FE numerical models (ANSYS) and PPI’s fatigue tools.
The second part of the internship will be to work on SG data that is currently acquired on an asset of the WindFloat Atlantic© farm. The SG data stream to the online timeseries database is operational and has been validated. The work will consist in further calibrating the SG data for usage in fatigue calculations, implying Python code development (building on existing in-house libraries), data analytics of SG and related platform motions and environmental measurements and making the link between measurement and FE numerical models (ANSYS).
Last, the successful candidate will work on implementing an operational tool based on previous work to compute live fatigue damage of the WindFloat Atlantic© floating wind farm.
Bigot, F., Derbanne, Q., & Baudin, E. (2013). A review of strains to internal loads conversion methods in full scale measurements. Proceedings of the PRADS2013, 20(25), 259-266.
Sireta, F. X., & Storhaug, G. (2022, April). A modal approach for holistic hull structure monitoring from strain gauges measurements and structural analysis. In Offshore Technology Conference (p. D011S011R009). OTC.
Required qualifications and competencies
- Master of Science, or equivalent degree in marine engineering, naval architecture, mechanical engineering, or equivalent.
- Knowledge in Naval architecture, mechanical/structural engineering, coding (Python).