Accurate surrogate modeling method for performance of solid rocket motor under uncertainty
The uncertainty of thrust curve of solid rocket motor(SRM)need be accurately quantified to en-sure the reliability and improve the load capacity of solid rocket on multidisciplinary design optimization(MDO)in the scheme design phase.An accurate surrogate modeling method is proposed in this paper to solve the prob-lem of difficulty in accurately quantifying the uncertainty of thrust curves and the low efficiency of uncertainty analysis in the process of MDO considering uncertainty.First the proper orthogonal decomposition is used to real-ize the dimensional reduction of the engine thrust curve with uncertainty.Then a Kriging surrogate model is built to predict the first four statistical moments of base modal coefficients.Finally,an accurate probability distribution model of the base modal coefficients is established by the maximum entropy method.The precise distribution of the thrust curve is then calculated.The result of uncertainty trust model used on a star grain SRM shows that the predicted confidence level of thrust uncertainty distribution reaches 98%.And the time of single uncertainty anal-ysis is reduced by 99.92%compared with Monte Carlo method.
Solid rocket motorUncertainty modelingMaximum entropy methodProper orthogonal de-compositionSurrogate model
NETL
NSTL
万方数据
