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A one-dimensional model is introduced in this paper for problems of internal ballistics involving solid propellant combustion. First, the work presents the physical approach and equations adopted. Closure relationships accounting for the physical phenomena taking place during combustion (interfacial friction, interfacial heat transfer, combustion) are deeply discussed. Secondly, the numerical method proposed is presented. Finally, numerical results provided by this code (UXGun) are compared with results of experimental tests and with the outcome from a well-known zero-dimensional code. The model provides successful results in firing tests of artillery guns, predicting with good accuracy the maximum pressure in the chamber and muzzle velocity what highlights its capabilities as prediction/design tool for internal ballistics. [ABSTRACT FROM AUTHOR]

This work evaluates the capabilities of Large Eddy Simulation with perfectly stirred reactor (PSR) assumption and detailed chemistry to predict unsteady, premixed, hydrogen combustion sequences. The model was benchmarked with hydrogen-air experimental tests and with numerical data of flame acceleration in an obstructed channel. Results permit to identify major shortcomings that should be addressed with this approach and to assess the uncertainties linked to the use of different sub-models. Spatial resolution was found to be critical and limits the applications of this approach due to the increase of the computational costs with the flame surface. While the influence of the detailed kinetic chemical scheme used was low, the impact of the sub-grid turbulence model used was high. Results showed that simulations provided good agreement with the experimental data when a minimum spatial resolution of 1/8 of the laminar flame thickness was imposed. This threshold permits to simulate with good results the early stages of the combustion sequence (ignition and initial flame acceleration) but limits the model applications when the flame surface increases. In-situ Adaptive Tabulation (ISAT) was an effective strategy to overcome the limitations and partially reduce the computational cost when detailed chemistry models are used together with PSR-LES. [ABSTRACT FROM AUTHOR]