Turbulence Manipulation to Increase Effective Reynolds Numbers in Vehicle Aerodynamics

AIAA Journal ◽  
1989 ◽  
Vol 27 (6) ◽  
pp. 763-769 ◽  
Author(s):  
J. Wiedemann ◽  
B. Ewald
2019 ◽  
Vol 29 (9) ◽  
pp. 3169-3191
Author(s):  
Zhen Chen ◽  
Zhengqi Gu ◽  
Zhonggang Wang

Purpose This paper aims to propose a precise turbulence model for vehicle aerodynamics, especially for vehicle window buffeting noise. Design/methodology/approach Aiming at the fact that commonly used turbulence models cannot precisely predict laminar-turbulent transition, a transition-code-based improvement is introduced. This improvement includes the introduction of total stress limitation (TSL) and separation-sensitive model. They are integrated into low Reynolds number (LRN) k-ε model to concern transport properties of total stress and precisely capture boundary layer separations. As a result, the ability of LRN k-ε model to predict the transition is improved. Combined with the constructing scheme of constrained large-eddy simulation (CLES) model, a modified LRN CLES model is achieved. Several typical flows and relevant experimental results are introduced to validate this model. Finally, the modified LRN CLES model is used to acquire detailed flow structures and noise signature of a simplified vehicle window. Then, experimental validations are conducted. Findings Current results indicate that the modified LRN CLES model is capable of achieving acceptable accuracy in prediction of various types of transition at various Reynolds numbers. And, the ability of this model to simulate the vehicle window buffeting noise is greater than commonly used models. Originality/value Based on the TSL idea and separation-sensitive model, a modified LRN CLES model concerning the laminar-turbulent transition for the vehicle window buffeting noise is first proposed.


2020 ◽  
Vol 21 (6) ◽  
pp. 621
Author(s):  
Veerapathiran Thangaraj Gopinathan ◽  
John Bruce Ralphin Rose ◽  
Mohanram Surya

Aerodynamic efficiency of an airplane wing can be improved either by increasing its lift generation tendency or by reducing the drag. Recently, Bio-inspired designs have been received greater attention for the geometric modifications of airplane wings. One of the bio-inspired designs contains sinusoidal Humpback Whale (HW) tubercles, i.e., protuberances exist at the wing leading edge (LE). The tubercles have excellent flow control characteristics at low Reynolds numbers. The present work describes about the effect of tubercles on swept back wing performance at various Angle of Attack (AoA). NACA 0015 and NACA 4415 airfoils are used for swept back wing design with sweep angle about 30°. The modified wings (HUMP 0015 A, HUMP 0015 B, HUMP 4415 A, HUMP 4415 B) are designed with two amplitude to wavelength ratios (η) of 0.1 & 0.24 for the performance analysis. It is a novel effort to analyze the tubercle vortices along the span that induce additional flow energy especially, behind the tubercles peak and trough region. Subsequently, Co-efficient of Lift (CL), Co-efficient of Drag (CD) and boundary layer pressure gradients also predicted for modified and baseline (smooth LE) models in the pre & post-stall regimes. It was observed that the tubercles increase the performance of swept back wings by the enhanced CL/CD ratio in the pre-stall AoA region. Interestingly, the flow separation region behind the centerline of tubercles and formation of Laminar Separation Bubbles (LSB) were asymmetric because of the sweep.


2010 ◽  
Vol 1 (1-2) ◽  
pp. 15-20 ◽  
Author(s):  
B. Bolló

Abstract The two-dimensional flow around a stationary heated circular cylinder at low Reynolds numbers of 50 < Re < 210 is investigated numerically using the FLUENT commercial software package. The dimensionless vortex shedding frequency (St) reduces with increasing temperature at a given Reynolds number. The effective temperature concept was used and St-Re data were successfully transformed to the St-Reeff curve. Comparisons include root-mean-square values of the lift coefficient and Nusselt number. The results agree well with available data in the literature.


2012 ◽  
Vol 43 (5) ◽  
pp. 589-613
Author(s):  
Vyacheslav Antonovich Bashkin ◽  
Ivan Vladimirovich Egorov ◽  
Ivan Valeryevich Ezhov ◽  
Sergey Vladimirovich Utyuzhnikov

AIAA Journal ◽  
1999 ◽  
Vol 37 ◽  
pp. 1062-1071 ◽  
Author(s):  
A. Seifert ◽  
L. G. Pack

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