Numerical Simulation of Rotating Detonation Engines

Kurzfassung

Rotating Detonation Engines (RDEs) are a type of pressure-gain combustion system based on detonation waves traveling around a cylindrical combustion chamber igniting the fresh gases. Compared to classical combustors, detonative combustion offers an increment in thermodynamic efficiency of the engine due to rapid heat release and lower entropy rise. The development of this technology could bring more compact and efficient combustors with applications to energy generation, aviation, and rocket propulsion. The objective of the present work is to develop a robust set up to simulate an RDE employing the DLR TAU code to obtain physical solutions to investigate the flow field within the engine and its performance. The impact of different modeling decisions and their influence on the flow physics shall be addressed. First, a set of 1D shock tube simulations have been conducted to evaluate the best solver parameters to capture detonation dynamics. Later, results of 2D simulations based on a test case from literature were performed and the modeling decisions were re-evaluated for this more realistic case. Lastly, two different 3D simulations have been performed and compared with the respective experimental results. The results showed that a resolution of 200 µm was enough in 2D simulations to capture the main flow features. Moreover, the chosen chemical reaction mechanism was from O Conaire, and the upwind flux that performed the best was the AUSMDV solver. Moreover, the time step employed was of the order of 10e-8 seconds. Different inlet boundary conditions were studied, finding the Dirichlet type more suitable to uncouple injection and detonation dynamics. In addition, different ignition strategies were evaluated, proving that the strategies were successful and achieved a stable mode of operation. This work presents a robust set up to perform 2D and 3D RDE simulations employing the DLR TAU code. It also provides many insights into the impact of different modeling decisions on the flow field and evolution of the engine performance.