This paper investigates the interior ballistic propelling charge design using the optimization methods to select the optimum charge design and to improve the interior ballistic performance. The propelling charge consists of a mixture propellant of seven-perforated granular propellant and one-hole tubular propellant. The genetic algorithms and some other evolutionary algorithms have complex evolution operators such as crossover, mutation, encoding, and decoding. These evolution operators have a bad performance represented in convergence speed and accuracy of the solution. Hence, the particle swarm optimization technique is developed. It is carried out in conjunction with interior ballistic lumped-parameter model with the mixture propellant. This technique is applied to both single-objective and multiobjective problems. In the single-objective problem, the optimization results are compared with genetic algorithm and the experimental results. The particle swarm optimization introduces a better performance of solution quality and convergence speed. In the multiobjective problem, the feasible region provides a set of available choices to the charge's designer. Hence, a linear analysis method is adopted to give an appropriate set of the weight coefficients for the objective functions. The results of particle swarm optimization improved the interior ballistic performance and provided a modern direction for interior ballistic propelling charge design of guided projectile.

The two-phase flow mathematical model for the solid granular propellant and its products of combustion inside large caliber naval gun guided projectile system (NGGPS) during interior ballistic cycle is presented. The model includes the governing equations of mass, momentum and energy for both phases as well as the constitutive laws. The discharged combustion products from the igniter vent-holes into the chamber are acquired by incorporation in the model the two-phase flow model of the bayonet igniter. The system of equations of the two-phase flow model is solved using the second order accurate Maccromacks technique. A one dimensional model introduced by G.A. Sod (shock tube) is utilized to test the ability of Maccromacks algorithm in solving the initial boundary value problem (IBVP) for the system of equations with shock wave behavior. The numerical method is verified by using an exact solution of a test problem. The moving control volume conservation method (MCVC) is used to handle the moving boundary as well as a self-adapting method was used to expand the computational domain in order to follow the movement of the projectile down the gun bore. The numerical results are validated with experimental data. The interior ballistics performance of a 130 mm naval guided projectile gun system is closely predicted using the presented two-phase flow model and the numerical code.

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