Gaussian process surrogate modeling for efficient controller tuning and fatigue load prediction of the helix wake-mixing method

Short summary

A new framework uses Gaussian process regression and limited large-eddy simulations to optimize wake-mixing control for wind farms, achieving a 7.5% power gain with specific parameters, and predicts associated fatigue loads.

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