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We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics, and will give delegates an opportunity to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please join us at the conference and take advantage of this opportunity to learn and engage with your peers in the academic community. We look forward to seeing you there!
PO019: POSTER AWARD WINNER - Multi-Fidelity Digital Twin to Bridge the Gap Between Rapid and Accurate Twinning of Floating Wind Turbines Incorporating Wave Prediction Capabilities
Yuksel Rudy Alkarem, Research Assistant, University of Maine
Abstract
To ensure the optimal operation of floating wind turbines (FWT), their digital twin must possess high fidelity to represent the physical system while guaranteeing fast computation. In the domain of wave forecasting for FWT, near-future wave predictions can fluctuate rapidly, making the precise computation of the system's response vital for both system monitoring and condition-driven control. While physics-based modeling is crucial for accurately capturing the system's linear and nonlinear dynamics, computational efficiency becomes imperative for real-time, data-driven wind/wave predictive schemes. This research presents a multi-fidelity twinning approach, OpenFAST-informed State Space (OFiSS), that melds the accuracy of a medium-fidelity, physics-based model with the computational speed of a low-fidelity, linearized model. Preliminary results showcase OFiSS's significant accuracy boost, particularly in the pitch degree of freedom by 50%-60% compared to low-fidelity model while operating 300 times faster than the mid-fidelity model, rendering it as an ideal choice for digital applications in FWT systems. This novel method requires only a one-time measurement of the system's physical states for calibration, making the virtual model both efficient and reliable. This design reduces the system's reliance on continuous sensor-based monitoring. However, if substantial changes in the system are anticipated, such as due to vegetation growth, mooring fatigue, or hull mass loss, periodic recalibrations might be necessary. These can coincide with routine unit inspections. By adhering to this approach, the digital twin is consistently synchronized with the FWT's real-world behavior, reducing the need for complex sensors on the hull and consequently lowering costs.