Mathematical models that simulate the internal ballistics of solid propellant rocket motors are widely used in lieu of the expensive, hazardous, time‐consuming static firing experiments. Since they rely on the input of various measured data, these models are vulnerable to uncertainties that may deteriorate their prediction accuracy. Improving the accuracy of internal ballistics prediction can be achieved by coupling the mathematical models with optimization algorithm. This paper discusses the issues of uncertainties and their impact on prediction accuracy of developed mathematical models. The model handles two types of dual thrust rocket motors, where the impact of uncertainties is more pronounced since they include more geometric and ballistic parameters. The model is developed based on the fundamental principles of internal ballistics and is coupled with a commercial genetic algorithm optimization tool. Two static firing tests are conducted to assess the proposed optimized prediction model. It is found that prediction optimization via tuning the uncertain parameters has led to significantly improving the prediction accuracy. More importantly, the tuned uncertain parameters give better understanding and clearer insight of the phenomena taking place inside dual thrust solid propellant rocket motors.

Despite that many sophisticated prediction tools are made to explicate the phenomena of internal ballistic for dual thrust rocket motor due to geometry change, none of them discussed uncertainties due to geometric, ballistic and regression simultaneously. Mathematical models are developed on the basic governing theories to estimate the pressure time history for two tubular grains with two different diameters along the grain. A Computer module was made to facilitate this study with consideration to uncertainties as they have a noticed effect on the results. The need for an optimization tool was necessary to reduce the error between theoretical and experimental results, genetic algorithm (MATLAB toolbox) was used as optimization tool. A set of static firing test are made for validation and to determine the operating characteristics of the motors experimentally. It was apparent in this study that some of these uncertainties are applicable in large scale motors only and the others are applicable for both small, and large scale motors.