Distributed leading-edge （LE） roughness could have significant impact on the aerodynamicperformance of a low-Reynolds-number （low-Re） airfoil, which has not yet been fully understood.In the present study, experime...Distributed leading-edge （LE） roughness could have significant impact on the aerodynamicperformance of a low-Reynolds-number （low-Re） airfoil, which has not yet been fully understood.In the present study, experiments were conducted to study the effects of distributed hemisphericalroughness with different sizes and distribution patterns on the performance of a GA （W）-1 airfoil.Surface pressure and particle image velocimetry （PIV） measurements were performed undervarious incident angles and different Re numbers. Significant reduction in lift and increase in dragwere found for all cases with the LE roughness applied. Compared with the distribution pattern,the roughness height was found to be a more significant factor in determining the lift reductionand altering stall behaviors. It is also found while the larger roughness advances the aerodynamicstall, the smaller roughness tends to prevent deep stall at high incident angles. PIV results alsosuggest that staggered distribution pattern induces higher fluctuations in the wake flow than thealigned pattern does. Results imply that distributed LE roughness with large element sizes areparticularly detrimental to aerodynamic performances, while those with small element sizes couldpotentially serve as a passive control mechanism to alleviate deep stall conditions at high incidentangles.展开更多
Why the stall of an airfoil can be significantly delayed by its pitching-up motion？ Various attempts have been proposed to answer this question over the past half century, but none is satisfactory. In this letter we ...Why the stall of an airfoil can be significantly delayed by its pitching-up motion？ Various attempts have been proposed to answer this question over the past half century, but none is satisfactory. In this letter we prove that a chain of vorticity-dynamics processes at accelerating boundary is fully responsible for the causal mechanism underlying this peculiar phenomenon. The local flow behavior is explained by a simple potential-flow model.展开更多
文摘Distributed leading-edge （LE） roughness could have significant impact on the aerodynamicperformance of a low-Reynolds-number （low-Re） airfoil, which has not yet been fully understood.In the present study, experiments were conducted to study the effects of distributed hemisphericalroughness with different sizes and distribution patterns on the performance of a GA （W）-1 airfoil.Surface pressure and particle image velocimetry （PIV） measurements were performed undervarious incident angles and different Re numbers. Significant reduction in lift and increase in dragwere found for all cases with the LE roughness applied. Compared with the distribution pattern,the roughness height was found to be a more significant factor in determining the lift reductionand altering stall behaviors. It is also found while the larger roughness advances the aerodynamicstall, the smaller roughness tends to prevent deep stall at high incident angles. PIV results alsosuggest that staggered distribution pattern induces higher fluctuations in the wake flow than thealigned pattern does. Results imply that distributed LE roughness with large element sizes areparticularly detrimental to aerodynamic performances, while those with small element sizes couldpotentially serve as a passive control mechanism to alleviate deep stall conditions at high incidentangles.
基金supported by the National Natural Science Foundation of China(10921202,11221062,11521091,and 11472016)
文摘Why the stall of an airfoil can be significantly delayed by its pitching-up motion？ Various attempts have been proposed to answer this question over the past half century, but none is satisfactory. In this letter we prove that a chain of vorticity-dynamics processes at accelerating boundary is fully responsible for the causal mechanism underlying this peculiar phenomenon. The local flow behavior is explained by a simple potential-flow model.
