Uncertainty analysis and probabilistic design optimization of hybrid rocket motors for manned lunar landing

Abstract

To obtain a conceptual design for a hybrid rocket motor (HRM) to be used as the Ascent Propulsion System in the Apollo lunar module, the deterministic design optimization (DDO) method is applied to the HRM design. Based on the results of an uncertainty analysis of HRMs, an uncertainty-based design optimization (UDO) method is also adopted to improve the design reliability. The HRM design process, which is a multidisciplinary system, is analyzed, and a mathematical model for the system design is established to compute the motor performance from the input parameters, including the input variables and model parameters. The input parameter uncertainties are quantified, and a sensitivity analysis of the model parameter uncertainties is conducted to identify the most important model parameter uncertainties for HRMs. The DDO and probabilistic UDO methods are applied to conceptual designs for an HRM to be used as a substitute for the liquid rocket motor (LRM) of the Ascent Propulsion System. The conceptual design results show that HRMs have several advantages as an alternative to the LRM of the Ascent Propulsion System, including nontoxic propellant combination, small motor volume, and comparable functions, such as restarting and throating. Comparisons of the DDO and UDO results indicate that the UDO method achieves more robust and reliable optimal designs than the DDO method. The probabilistic UDO method can be used to develop better conceptual designs for HRMs. hybrid rocket motor, deterministic design optimization, uncertainty-based design optimization, sensitivity analysis, manned lunar landing Citation: Zhu H, Tian H, Cai G B, et al. Uncertainty analysis and probabilistic design optimization of hybrid rocket motors for manned lunar landing. Sci

Transient probabilistic design of flexible multibody system using a dynamic fuzzy neural network method with distributed collaborative strategy

“…Such a probabilistic approach can describe the dynamic responses of flexible multibody system with acceptable accuracy. 10,11 The transient probabilistic analysis has been commonly applied in many fields. 12–14…”

“…Such a probabilistic approach can describe the dynamic responses of flexible multibody system with acceptable accuracy. 10,11 The transient probabilistic analysis has been commonly applied in many fields. [12][13][14] Classical transient probabilistic analysis methods include Monte Carlo (MC) method, [15][16][17] and extremum response surface method (ERSM).…”