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Multi-disciplinary Conceptual Design Knowledge of Multi-stage Hybrid Rocket Using Data Mining Technique



Author(s)

Masahiro Kanazaki, Kazuhisa Chiba, Koki Kitagawa, Toru Shimada and Masashi Nakamiya

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DOI:10.17265/2159-5275/2015.01.001

This paper deals with the application of data mining techniques to the conceptual design knowledge for a LV (launch vehicle) with a HRE (hybrid rocket engine). This LV is a concept of the space transportation, which can deliver micro-satellite to the SSO (sun-synchronous orbit). To design the higher performance LV with HRE, the optimum size of each component, such as an oxidizer tank containing liquid oxidizer, a combustion chamber containing solid fuel, a pressurizing tank and a nozzle, should be acquired. The Kriging based ANOVA (analysis of variance) and SOM (self-organizing map) are employed as data mining techniques for knowledge discovery. In this study, the paraffin (FT-0070) is used as a propellant of HRE. Then, the relationship among LV performances and design variables are investigated through the analysis and the visualization. To calculate the engine performance, the regression rate is computed based on an empirical expression. The design knowledge is extracted for the design knowledge of the multi-stage LV with HRE by analysis using ANOVA and SOM. As a result, the useful design knowledge on the present design problem is obtained to design HRE for space transportation.

Hybrid rocket, data mining techniques, multidisciplinary design