A design optimization approach of a solid propellant rocket motor is considered. A genetic algorithm (GA) optimization method has been used. The optimized solid rocket motor (SRM) is intended to use as a booster of a flight vehicle, and delivering a specific payload following a predefined prescribed trajectory. Sensitivity analysis of the optimized solution has been conducted using Monte Carlo method to evaluate the effect of uncertainties in design parameters. The results show that the proposed optimization approach was able to find the convergence of the optimal solution with highly acceptable value for conceptual design phase.

A steel channel with the size of 30×2×1.2 m was made to simulate the full surface fire of 50000 m3methanol tank in coal-to-olefins industry. Some fire characteristic parameters of methanol were investigated, including flame spread rate, flame height, temperature distribution and radiation heat flux distribution. It is found that the flame spread rate of methanol is 1.98 m/s and the flame height could reach to 3.2 m. The temperature of methanol flame is first up and then down with the increase of height, while the highest temperature is 768oC. It is also found that the radiation heat flux of methanol flame is in the changes between 4.4 kW/m2and 12.2 kW/m2. The feature of methanol fire is different from the normal oil fire, which is worth for us to pay more attention.

This paper describes the optimization approach of a three stage solid propellant launch vehicle configuration from existing solid rocket motors (SRM). The optimal launch vehicle (LV) is capable of delivering a small satellite of 100 kg to a circular low earth orbit of 400, 500 and 600 km altitude. The overall LV configuration and the trajectory profile were optimized simultaneously, thus the existing SRM parameters for first, second and three stages, vertical flight time, launch maneuver variable, maximum angle of attack, coasting time between first and second stage and the second coasting time between second and third stages were optimized. A genetic algorithm global optimization method has been implemented to perform the analysis, the algorithm consider mixed integer continuous variables. The results show that the proposed optimization approach was able to find the optimal solution for all three variants with very acceptable values, and the approach proved to be reliable for conceptual design level.

The multiphase numerical optimization study has been carried out for a 2-stage boost vehicle and small size X-33 type lifting-body reentry vehicle with heat rate and dynamic pressure constraint. The problem has been modeled as a nonlinear, multiphase optimal control problem with the objective to compute the optimum burn-out conditions as well as the best control deflections that would maximize the cross range performance of the boost-glide vehicle under study. The study has been performed using hp-adaptive Pseudospectral method. Comparative performance of the lifting-body vehicle with conventional ballistic missile trajectory has also been carried out. It has been found that for vehicle under study, and near maximum down range, the optimum burn-out angle is 13.6 degree which results in a cross-range of more than 100 km.

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