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Continuously increasing offshore wind turbine scales require rotor designs that maximize power and performance. Downwind rotors offer advantages in lower mass due to reduced potential for tower strike, and is especially true at large scales, e.g., for a 25 MW turbine. In this study, three 25 MW downwind rotors, each with different prescribed lift coefficient distributions were designed (chord, geometry, and twist) and compared to maximize power production at unprecedented scales and Reynolds numbers, including a new approach to optimize rotor tilt and coning based on aeroelastic effects. To achieve this objective the design process was focused on achieving high power coefficients, while maximizing swept area and minimizing blade mass. Maximizing swept area was achieved by prescribing pre-cone and shaft tilt angles to ensure the aeroelastic orientation when the blades point upwards was nearly vertical at nearly rated conditions. Maximizing the power coefficient was achieved by prescribing axial induction factor and lift coefficient distributions which were then used as inputs for an inverse rotor design tool. The resulting rotors were then simulated to compare performance and subsequently optimized for minimum rotor mass. To achieve these goals, a high Reynolds number design space was developed using computational predictions as well as new empirical correlations for flatback airfoil drag and maximum lift. Within this design space, three rotors of small, medium and large chords were considered for clean airfoil conditions (effects of premature transition were also considered but did not significantly modify the design space). The results indicated that the medium chord design provided the best performance, producing the highest power in Region 2 from simulations while resulting in the lowest rotor mass, both of which support minimum LCOE. The methodology developed herein can be used for the design of other extreme-scale (upwind and downwind) turbines. 

Acute and chronic hydration status is important for athlete safety and performance and is frequently measured by sports scientists and performance staff in team environments via urinalysis. However, the time required for urine collection, staff testing, and reporting often delays immediate reporting and personalized nutrition insight in situations of acute hydration management before training or competition. Furthermore, the burdensome urine collection and testing process often renders chronic hydration monitoring sporadic or non-existent in real-world settings. An automated urinalysis device (InFlow) was developed to measure specific gravity, an index of hydration status, in real-time during urination. The device was strongly correlated to optical refractometry with a mean absolute error of 0.0029 (±0.0021). Our results show this device provides a novel and useful approach for real-time hydration status via urinalysis for male athletes in team environments with high testing frequency demands.