DOE OSTI · 3531185
Computational capacity in hydrodynamic real-time hybrid simulation applied to simulate the dynamic response of floating offshore wind turbines
Abstract
Real-time hybrid simulation (RTHS) mitigates similitude distortions in model-scale tests of floating offshore wind turbines (FOWTs) by coupling physical experiments with numerical models in real time. The coupling requires faster-than-real-time numerical computations to satisfy temporal similitude with the physical experiment, presenting a bottleneck for using more complex numerical models in RTHS. This paper presents a hydrodynamic-RTHS (hydro-RTHS) framework for FOWTs that simulates the hydrodynamics physically and the aerodynamics numerically with sensor feedback from the physical testing. The framework adapts the three-loop hardware architecture to leverage greater computational resources and mitigate strict temporal requirements, enabling more computationally demanding numerical analyses in hydro-RTHS. The three-loop hardware architecture integrates multiple machines, each dedicated to either numerical analysis or RTHS controls, with a rate-transition algorithm to synchronize the tasks executed across the different machine processors. Virtual and physical tests verified and validated the hydro-RTHS framework, respectively. The ”virtual” tests, which approximates the physical domain numerically, verified the RTHS framework with respect to a numerical full-scale complete FOWT model simulated in the open-source software, OpenFAST. The virtual tests were able to maintain comparable control signals while enabling greater computational resources for the numerical calculations. Real-world physical tests demonstrated that the hydro-RTHS framework computes aerodynamic forces similar to the complete OpenFAST model, validating the hydro-RTHS framework using the three-loop hardware architecture. Findings show that the hydro-RTHS framework with the three-loop hardware architecture is computationally efficient, with reserve capacity to simulate more complex problems due to the customized software, hardware, and rate-transition algorithm.
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Seki, Akiri [Stanford University, CA (United States)] (ORCID:0000000277367375), Devin, Michael [Oregon State University, Corvallis, OR (United States)] (ORCID:0000000244633905), Ni, Yun [Stanford University, CA (United States)], Gadasi, Jonah [NAVFAC EXWC Oceans, Port Hueneme, CA (United States)] (ORCID:0000000318523881), Bosma, Bret [Oregon State University, Corvallis, OR (United States)], Robertson, Bryson [Oregon State University, Corvallis, OR (United States)], Brekken, Ted [Oregon State University, Corvallis, OR (United States)], DuPont, Bryony [Oregon State University, Corvallis, OR (United States)], Schellenberg, Andreas [Maffei Structural Engineering, San Francisco, CA (United States)] (ORCID:0009000006300969), Lomonaco, Pedro [Oregon State University, Corvallis, OR (United States)] (ORCID:0000000167215688), Simpson, Barbara [Stanford University, CA (United States)]. 2026-12-01. Computational capacity in hydrodynamic real-time hybrid simulation applied to simulate the dynamic response of floating offshore wind turbines. https://doi.org/10.1016/j.weer.2026.100037
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