Work

Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight

Year: 2015

Type: article

Abstract: In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM) powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity analysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization (DDO) and uncertainty-based design optimization (UDO) are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation (KMCS) and Kriging-based Taylor series approximation (KTSA), are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.

Source: Chinese Journal of Aeronautics

DOI: 10.1016/j.cja.2015.04.015

Authors: Hao Zhu, Hui Tian, Guobiao Cai, Weimin Bao

Institutions: Beihang University, China Aerospace Science and Technology Corporation

Language: English

Topic: Probabilistic and Robust Engineering Design

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,000

Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation