Abstract:

 In order to evaluate the hypersonic vehicle separation reliability efficiently, the influence of the separation process uncertainties on the hypersonic vehicle separation reliability is studied and a new uncertainty-based reliability modeling and analysis method for the hypersonic vehicle separation is proposed. In this method, the kinetic model is constructed based on the hypersonic vehicle separation task requirements. The significant uncertainty parameters are identified through the sensitivity analysis method for the construction of the separation reliability model. To improve the efficiency of the separation reliability evaluation, an improved active Kriging (IAK) method is proposed in which the point that has a higher potential failure probability by a new sampling strategy is regarded as the next training point. It is shown that the influence of the uncertainties can be described exactly, and the accuracy and efficiency of the separation reliability analysis are improved, which can further support the detailed design of the vehicle separation.

Key words:  Vehicle separation, Uncertainty, Reliability analysis, Active learning Kriging, Reliability modeling