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Internal ballistic simulation(IBS)method of multi-burning-rate solid rocket motor(SRM)was developed based on 3-D burning regression method by parameterized feature CAD model(PFCADM)and lumped parameter,in consideration of time-dependent,erosive-burning-effect from internal ballistic numerical algorithm.By driving multi-parameter CAD model based on PFCADM,the approach is capable of conducting the geometric regression simulation of various grain combinations of complex configurations with different burning rates.Through suitably simplifying the internal ballistic numerical algorithm,the problems of coupling geometric regression simulation of sub-grains of different burning rates and high computational consumption of internal ballistic calculation were solved.One tri-burning-rate grain motor,which had been firing-tested,was used as the validation case of simulation.The results show that,with the 3-D grain regression model and sufficient accurate internal ballistic algorithm,the method realizes IBS of the case in low computationalconsumption prediction of its performance within the accuracy of 2% during 1hclock-time.The application of the method provides a practical approach to aid SRM design of multi-burning-rate grain.
Internal ballistic simulation (IBS) method of multi-burning-rate solid rocket motor (SRM) was developed based on 3-D burning regression method by parameterized feature CAD model (PFCADM) and lumped parameter, in consideration of time-dependent, erosive- burning-effect from internal ballistic numerical algorithm. By driving multi-parameter CAD model based on PFCADM, the approach is capable of conducting the geometric regression simulation of various grain combinations of complex configurations with different burning rates. Equivalent simplifying the internal ballistic numerical algorithm , the problems of coupling geometric regression simulation of sub-grains of different burning rates and high computational consumption of internal ballistic calculation were solved. One tri-burning-rate grain motor, which had been firing-tested, was used as the validation case of simulation.The results show that, with the 3-D grain regression model and sufficient accurate internal ballistic algorithm, the method rea lizes IBS of the case in low computationalconsumption prediction of its performance within the accuracy of 2% during 1hclock-time. the application of the method provides a practical approach to aid SRM design of multi-burning-rate grain.