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Wind energy plays a crucial role in meeting the electricity demands of the U.S.; however, high maintenance costs highlight the need for accurate predictions of unsteady loading caused by turbine layout and off-design wind conditions. Existing design tools often neglect fluid-structure interactions that drive costly fatigue loads, prompting the research community to leverage high-performance computing (HPC) solvers to study these effects. Unfortunately, such tools remain too complex and costly for industrial applications, particularly due to challenges in grid generation and setup. To address this, CDI is developing a Cartesian-based hybrid solver that integrates an incompressible vorticity-based far-field formulation with a compressible primitive variable solver in the near field. The framework is built on the AMReX library, enabling block-structured mesh refinement for efficient computation. This talk will explore both the computational and mathematical aspects of coupling these two solvers, highlighting advancements in predictive modeling for wind turbine aerodynamics.
