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Uncertainty Quantification of Store-Separation Simulation Due to Ejector Modeling using a Monte Carlo Approach with Kriging Model
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作者 shuling tian Rongjie Li +2 位作者 Jiawei Fu Zihan Jiao Jiangtao Chen 《Advances in Applied Mathematics and Mechanics》 SCIE 2022年第3期622-651,共30页
Precise calculation of the trajectory of store separation is critical in assess-ing whether the store can be released safely.Store ejection is the initial stage of the releasing process and any uncertainty introduced ... Precise calculation of the trajectory of store separation is critical in assess-ing whether the store can be released safely.Store ejection is the initial stage of the releasing process and any uncertainty introduced at this stage will propagate through the whole trajectory.In this work,the impact of the uncertainties in ejector modeling on the simulation of a generic store separation is investigated by using a Monte-Carlo-based approach.To reduce the extremely large computation cost resulted from the direct use CFD in Monte Carlo simulation,the CFD solutions are represented by a time-dependent Kriging model,which is constructed at each time step by using the samples from the URANS simulations.The stochastic outputs,including the distri-bution of probability density function,expected value and 95%confidence interval of store separation trajectory,are obtained by the Monte Carlo simulations.The sensitiv-ity analysis is also carried out by using the Monte-Carlo-based method to determine the most significant variables in ejector modeling,which affect the output uncertainty.Our results show that ejector modeling is one of the main uncertainty sources of store separation simulation and the approximation in ejector modeling can cause a signifi-cant deviation,especially in the angular displacement. 展开更多
关键词 Uncertainty quantification Monte Carlo simulation Kriging surrogate model store separation
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