Affect of Quantity, Resolution, & Scaling of Turbulence Boxes on Aeroelastic Simulation Convergence скачать в хорошем качестве

Affect of Quantity, Resolution, & Scaling of Turbulence Boxes on Aeroelastic Simulation Convergence

IEA Wind Task 44 presents this talk by speaker Dr. Jamie Lieu of MIT. Join us for an in-depth exploration into the world of aeroelastic wind turbine simulations! In this talk, Jamie delves into the crucial role these simulations play in the design process, specifically focusing on their use in estimating structural fatigue loading. Abstract: Aeroelastic wind turbine simulations are extensively used in the turbine design process to estimate structural fatigue loading. While it is assumed that more stochastic realisations (seeds) and higher resolution simulations will converge to the 'true' result faster, a detailed study has not been published to support how many seeds and what resolution is required to achieve an arbitrary level of convergence. In this study, we perform a comprehensive study on the convergence of turbine fatigue statistics as a function of turbulence grid resolution, number of seeds, and the type of turbulence scaling. The study is performed using the HAWC2 aeroelastic code in conjunction with Mann turbulence fields of varying resolution. Key findings are that over 21 seeds are required to ensure a standard error of the mean of less than 5% for fatigues statistics, and a turbulence resolution of at least 2048×64×64 (in the longitudinal, lateral and vertical, respectively) is required to ensure statistical convergence of a 10 minute simulation on one turbine. The presented study provides a valuable insight into the uncertainties involved in turbine fatigue load calculations, and the conclusions can be extended to wind farm level simulations. This is particularly important when attempting to quantify the effect of wind farm control strategies on fatigue loads.