Uncertainty design and optimization of a hybrid rocket motor with mixed random-interval uncertainties

Abstract

Uncertainties, which exist widely in the design of aerospace systems, have a great impact on system response and may lead to design failures. Both the probability and non-probability uncertainties exist in real engineering cases. Thus, it is imperative to incorporate the mixed uncertainties into the aerospace systems design and optimization. Present study proposed an efficient design optimization method considering the random and interval uncertainties to conduct the uncertainty analysis and optimize the design of a hybrid rocket motor with mixed uncertainties. A polynomial chaos expansion model was selected to deal with the random uncertainties, and an interval analysis method based on the first order Taylor expansion was adopted to calculate the response bounds of interval uncertainties. A simple structure was firstly used to verify the efficiency and accuracy of the proposed method. The random-interval analysis method was very efficient in searching the optimal results, showing considerable computational cost savings. Subsequently, a design model of hybrid rocket motor was introduced and verified by a long-time firing test. In the optimization of the upper-stage hybrid rocket motor, the comparison between uncertainty analysis and traditional methods showed that the design optimization considering the uncertainty in design variables was able to achieve more robust results. Compared with the deterministic scheme, the uncertainty scheme increased the total engine mass by nearly 18%, but the probabilities of all constraints considering parameter fluctuations remained above 0.9. Capable of solving complex problems with mixed uncertainties, this method shows its potential in aerospace engineering applications.