Paper Title
EXPLORING UNCERTAINTY IN MICRO WIND TURBINE AIRFOIL DESIGN AND PERFORMANCE THROUGH POLYNOMIAL CHAOS

Abstract
Micro wind turbines are gaining popularity in urban environments as a decentralized, renewable energy source, offering benefits like compactness, lower reliance on the grid, and cost efficiency. These turbines present a promising solution for improving energy independence and minimizing environmental impact. However, they face unique challenges due to their operation at low Reynolds numbers, where laminar-to-turbulent transitions and viscous forces play a critical role in determining aerodynamic performance. This study addresses the inherent uncertainties in the operational conditions of micro wind turbines, such as fluctuating wind speeds, varying angles of attack, and turbulence levels, all of which can significantly impact performance. To tackle these challenges, we propose a robust airfoil design methodology that incorporates uncertainty quantification into the optimization process. Using the NACA 0012, NACA 0018, and NACA 006 airfoils as case studies, the Non-Intrusive Polynomial Chaos (NIPC) method, combined with a Kriging metamodel, was employed to optimize airfoil geometry under uncertain conditions. Results highlight that even small uncertainties can result in significant reductions in average aerodynamic efficiency at low Reynolds numbers. However, the proposed optimization approach demonstrates notable improvements in aerodynamic performance by smoothing the pressure gradient on the suction side, thereby reducing flow separation and enhancing overall turbine efficiency. Key performance indicators such as pressure coefficient distribution and skin friction are analyzed, with particular attention to the formation of laminar separation bubbles and laminar-to-turbulent transition phenomena, further elucidating the impact of the optimized design on turbine performance.