Active control of skin-friction and wall-heat-flux in hypersonic turbulent boundary layers via wall mass transport

Active control of hypersonic turbulent boundary layers (HTBLs) at Mach 5.9 via wall mass transport, including uniform blowing, opposition control and their combination, is studied using direct numerical simulation. For uniform blowing, scalings of drag reduction rate (DR) and wall-heat-flux reduction rate (HR) are discovered by defining a novel friction-blowing velocity

, which collapses the results across the hypersonic and low-speed flows, enabling rapid engineering estimation. Skin-friction and wall-heat-flux decompositions reveal that the enhanced mean wall-normal convection plays the primary role in skin-friction and wall-heat-flux reduction. However, the Reynolds stress is enhanced due to the promotion of ejection and sweep events, which is detrimental to control performance. Then, opposition control is successfully extended to HTBLs to reduce skin-friction and wall-heat-flux while suppressing Reynolds stress. It is discovered that DR and HR remain similar within the detection location

y Subscript d Superscript asterisk Baseline less than or slanted equals 15 y d ∗ ⩽ 15 $y^*_d\leqslant 15$

, but differ significantly beyond this region. The empirical functions for DR and HR based on

v Subscript w comma italic rms Superscript plus v w , rms + $ v_{w,\textit{rms}}^+$

are proposed for near-wall

y Subscript d Superscript asterisk y d ∗ $y^*_d$

, while the mechanism for the difference at

y Subscript d Superscript asterisk Baseline equals 20 y d ∗ = 20 $y^*_d=20$

is revealed by analysing the new temperature coherent structures. Finally, by combining uniform blowing and opposition control, a novel composite control technique for HTBLs is proposed to synergistically reduce skin-friction and wall-heat-flux, which achieves effectively controlling the mean wall-normal convection while suppressing Reynolds stress, thereby acquiring better control performance. Moreover, it is revealed that DR and HR could be decomposed into the contributions from the mean-convection and fluctuation-modulation, which are estimable via empirical functions using

v Subscript w comma 0 Superscript plus v w , 0 + $v_{w,0}^+$

and

v Subscript w comma italic rms Superscript plus v w , rms + $ v_{w,\textit{rms}}^+$

.