Research Information System
1st International Congress on Artificial Intelligence and Data Science, İzmir, Turkey, 26 - 28 November 2021, pp.330-336
Rockets are widely used in aerospace and defense with their speed and improved mechanical
properties. The skills and mechanical properties of rockets can be developed depending on
the design methods, production process and structural features. Lots of design parameters
in the rocket modeling process has an impact on the structural features In this study, the
effects of fourteen different major design variables on the output parameters in rocket
modeling process were investigated. This study was carried out in two stages, simulation
and design-optimization. In the first part, scenarios were determined by using the Design of
Experiment (DoE) approach to collect data and these scenarios were realized through the
OpenRocket simulator. MacroRecorder app was used to speed up to process applied tries on
the OpenRocket and the outputs such as maximum velocity, apogee were recorded. In the
second part, different mathematical models were created to define the phenomena by using
the multiple nonlinear regression analysis with combining neuro-regression method. The
coefficient of determination (R2
), adjusted coefficient of determination (R2
adjusted) also
R
2
training and R2
testing values were calculated for each model, to see how well the models define
the phenomena. As a design-oriented solution, the values of the process parameters that
provide the maximum speed values are optimized based on stochastic optimization
algorithms (Differential Evolution Algorithm, DE). The results show that modeling and
optimization are important in achieving higher efficiency in the rocket modeling process.