Interactive Visual Design Optimization and Analysis for Solid Rocket Motor
- Paper number
IAC-06-D1.3.04
- Author
Dr. Ou Haiying, National University of Defense Technology, China
- Year
2006
- Abstract
The traditional design optimization process for Solid Rocket Motor (SRM) is a black box to designers. Also, it is not easy for designers to an build optimization model, to choose proper optimization algorithms and to analyze the design result. This paper presents the Interactive Visual Design Optimization and Analysis (IVDOA) method to incorporate designers’ knowledge and experience into the design, and there is no need to build an optimization model and to write optimization code. In other words, IVDOA allows the designer to design, not to compute. The procedure starts with taking design variables as controls (combo boxes, radio buttons and sliders, etc.) in a command panel. Design variables involve continuous variables (design pressure and expansion ratio, etc.), discrete variables (shell material and grain type, etc.) and integral variables (fin numbers of finocyl grain, etc.). Designers can change these variables value interactively through the controls. The procedure then invokes the analysis code such as the code for mass computing and internal ballistic computing when designers change the variables value. Following that design performance parameters are changed in real time and are displayed in a viewing panel. The parameters involve pressure-time history, thrust-time history and general performance parameters such as motor mass, impulse and loading fraction. Designers can choose preferable schemes according to these parameters. Taking system design optimization of a high pressure SRM as an example, IVDOA gives a means of visualizing the effect design variables have on the performance; IVDOA provides many feasible design schemes from which designers can choose preferable ones; IVDOA can also analyze the parameter sensitivity of the design result easily. The result shows that good designs are provided by IVDOA in less than five minutes, yet more than four hours are needed if optimized by Genetic Algorithms. It demonstrates that IVDOA is simple, intuitive and efficient.
- Abstract document