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Direct numerical simulation (DNS) of transition over a hypersonic lifting body model HyTRV developed by China Aerodynamics Research and Development Center is performed. The free-stream parameters are: the free-stream Mach number is 6, the unit Reynolds number is 10000/mm, the free-stream temperature is 79 K, the angle of attack is 0, and the wall temperature is 300 K. Weak random blowing-and-suction perturbations in the leading range are used to trigger the transition. A high order finite-difference code OpenCFD developed by the authors is used for the simulation, and grid convergence test shows that the transition locations are grid-convergence. DNS results show that transition occurs in central area of the lower surface and the concaved region of the upper surface, and the transition regions are also the streamline convergence regions. The transition mechanisms in different regions are investigated by using the spectrum and POD analysis. [ABSTRACT FROM AUTHOR]

Uncertainty-based design optimization (UBDO) is becoming increasingly important with great attention to critical system reliability and robustness. However, most traditional UBDO methods only consider low-order response moments and a limited number of aleatory uncertainties, which desiderates to be resolved. In this study, an efficient UBDO approach based on cumulative distribution matching is presented to address all response moments under mixed aleatory and epistemic uncertainties. The mathematical formulation of cumulative distribution function (CDF) matching is systematically derived including the distance metric definition and numerical computation process. Uncertainty analysis within the CDF matching optimization loop is also investigated, including the identification of active subspaces and the propagation of constructed surrogate model in reduced dimensions. Extended active subspaces are furthered discussed for mixed uncertainty analysis to obtain the bounds of CDF efficiently, instead of the time-consuming full-dimensional simulation. The proposed approach is illustrated by three typical optimization examples, i.e., response function matching, standard NASA test problem, and satellite system design in aerospace engineering. The UBDO results based on the CDF matching are discussed and compared with the probability density function matching, which exhibits higher efficiency and better convergence in tackling constrained optimization design problems subject to mixed uncertainties. [ABSTRACT FROM AUTHOR]