Prediction of horizontal tail buffeting loads based on URANS and DES approaches

At high angles-of-attack, modern high-agility aircraft experience large areas of flow separation and the generation of vortical structures. The interaction of the resulting unsteady flow fields with the tail structure can result in severe vibrations commonly known as tail buffeting. Buffeting phenomena can be predicted using a partitioned coupling between computational fluid dynamics (CFD) and computational structural dynamics (CSD). However, the results strongly depend on the prediction characteristics of the CFD methods regarding the unsteady flow field. As an example, the capabilities of Unsteady Reynolds-Averaged Navier-Stokes (URANS) and Detached-Eddy Simulation (DES) methods for prediction of unsteady flow phenomena differ significantly which has been investigated in the literature. However, little attention has been paid on how these characteristics of the CFD methods affect the actual buffeting loads on a configuration. In the paper the detailed prediction characteristics of different URANS and DES methods are investigated regarding 1) the unsteady flow phenomena involved in tail buffeting and 2) the structural loads on the horizontal tail with a one-way coupling. A configuration with double-delta wing and horizontal tail plane (HTP) is investigated which is sized to highlight buffeting effects in wind-tunnel tests. Simulation conditions are Ma8 = 0.2, a = 25° and Re/1m = 4.66 × 106. The results of the presented research provide a detailed understanding of which CFD methods can be employed for an adequate prediction of tail buffeting in partitioned couplings. © Universal Technology Corporation, 2018.     «

At high angles-of-attack, modern high-agility aircraft experience large areas of flow separation and the generation of vortical structures. The interaction of the resulting unsteady flow fields with the tail structure can result in severe vibrations commonly known as tail buffeting. Buffeting phenomena can be predicted using a partitioned coupling between computational fluid dynamics (CFD) and computational structural dynamics (CSD). However, the results strongly depend on the prediction charact...     »