We report several examples of applying the obtained scaling results to improve turbulent CFD predictions (She et al, JFM 2018) as well as drag reductions (Yao, Chen & Hussain, JFM 2019) of wall flows. First, an algebraic model for compressible turbulent boundary layers (CTBL) is developed – predicting mean profiles of velocity, temperature and density – valid from incompressible to hypersonic flow regimes (Mach number Ma from 0 to 6). The accuracy of our new model is notably superior to popular current models such as Baldwin-Lomax and Spalart-Allmaras models, due to an improved eddy viscosity function compared to competing models. Second, we introduce the modification of the popular k- equation, which achieves better predictions of both mean velocity profile and the turbulence intensity ( ) of pipe flows (Chen et al PRE 2016, JoT 2016). These results suggest the path for developing advanced CFD models by incorporating the multi-layer structures. Finally, we present a new method for skin friction reduction in wall flows. We show that the lack of drag reduction at high Re ( = 550) observed by Canton et al. (PRF 2016) is remedied by the proper choice of the large-scale control flow, i.e. a pair of near-wall spanwise opposed wall-jet forcing (SOJF), whose height follows our predicted scaling of Reynolds shear stress peak. The flow control definitely suppresses the wall shear stress at a series of Reynolds numbers, namely, 18%, 14%, and 10% drag reductions at = 180, 395, and 550, respectively.