Model-form uncertainty quantification in RANS simulations of wakes and power losses in wind farms

Reynolds-averaged Navier-Stokes (RANS) is one of the most cost-efficient approaches to simulate wind-farm-atmosphere interactions. However, applicability RANS-based methods always limited by accuracy turbulence closure models, which introduce various uncertainties into models. In this study, we estimate model-form in RANS simulations wind farms. For purpose, compare different models a large-eddy simulation (LES). We find that realizable k −ϵ model representative for predicting mean velocity, intensity, and power losses within farm. then investigate uncertainty associated with perturbing Reynolds stress tensor. The focus placed on shape tensor represented its eigenvalues. results show perturbed successfully estimates region bounding LES quantities interest (QoIs). also discuss effect perturbation magnitude QoIs.