Mathematical Modeling of Wind Tunnels for Low Reynolds Number Unsteady Aerodynamic Testing

Rennie, Mark R.; Catron, Brian; Williams, David R.; Feroz, Muhammad Zubair

doi:10.2514/6.2017-1532

Cited by 8 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The velocity field v in the wind tunnel is governed by the three-dimensional, Navier-Stokes equations. The true boundary conditions at every solid surface are no slip and no flow through, and the conditions at the inlets and outlets depend on the entire wind-tunnel system, including the flow resistance of each wind tunnel component and the fan operating conditions [10]. Furthermore, most wind tunnels rely on a flow straightener (such as a honeycomb screen) to reduce the turbulence intensity at the inlet of the test section, but the turbulence can usually not be removed entirely.…”

Section: Methodsmentioning

confidence: 99%

“…While experimental facilities can usually create both discrete and continuous gusts, they are often limited to one type of velocity disturbance, based on the gust generator or wind tunnel type in use. Common setups include actuated airfoils positioned upstream of the test subject for discrete and continuous vorticity-induced gusts in a wind or water tunnel [2][3][4][5][6], a towed airfoil in a water tank with a jet for discrete transverse gusts [7,8], and wind tunnels equipped with controllable louvers upstream or downstream of the test subject for discrete and continuous stream-wise flow variations [9][10][11]. More recently, gust generators have been installed that create transverse gusts that are irrotational, unlike the aforementioned jet setup.…”

Section: > 1 Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Wind tunnel effects on gust-interaction simulations

Beckers

Eldredge

2023

Theor. Comput. Fluid Dyn.

View full text Add to dashboard Cite

Large-amplitude flow disturbances such as gusts can drastically change the aerodynamic loads on machines. Developing active flow control strategies to mitigate these gusts is challenging because the flow response depends non-linearly on the gust parameters. Wind-tunnel experiments and computational models can explore this parameter space but suffer from individual limitations such as a sensor's limited field of view or modeling uncertainties. However, combining both tools through data assimilation can alleviate some issues and generate richer data sets. For accurate results, it is important that the computational model can realistically predict the flow in the wind tunnel. For this purpose, we present a computational model (a digital twin) for a low-speed aerodynamics wind tunnel with irrotational gust generation using suction at the top of the test section. The model couples a viscous flow solution without wind-tunnel walls with a potential flow to correct the normal velocity at the walls and model the suction. We demonstrate the simulation of gust responses using three examples and compare different airfoils and approximations to show their effects. In the last example, we illustrate how to apply this model for data assimilation with experiments by inferring the time-varying gust strength from synthetic velocity measurements.

show abstract

Section: Methodsmentioning

confidence: 99%