The addition of aluminum (Al) to the fuel is an effective way to increase the regression rate of hybrid rocket motors (HRMs). Due to its high regression rate, the impact of the regression of combustion surface on the performance of HRMs cannot be ignored. Therefore, it is significant to establish a dynamic numerical simulation model to predict the performance of HRMs. In this study, the dynamic simulation model was established based on dynamic mesh technology and was verified by a firing test. The results show that the simulation results agree well with the experimental results, and the errors of the average thrust and combustion chamber pressure are 3.4% and 1.4%, respectively. The dynamic simulation shows that with the regression of the combustion surface, the vortex of the pre-combustion chamber is divided into two vortices. The vortex near the front of the grain will increase the regression rate downstream. The results show that the addition of Al can obviously improve the regression rate of HRMs. The fuel containing 58% Al can improve the regression rate by 88.8% compared with the fuel with pure hydroxyl-terminated polybutadiene (HTPB). Moreover, due to the higher combustion temperature and the scouring of metal particles, the ablation rate of the nozzle with carbon ceramic materials reaches 0.16 mm/s. This investigation provides a valuable reference for HRMs design and simulation.

Hybrid rocket motors have great development potential due to their outstanding thrust adjustment flexibility and long-term operation ability. However, nozzle erosion during the motor operation can cause an increase in the throat area of the nozzle, which leads to a decrease in combustion chamber pressure and nozzle efficiency. Therefore, a performance prediction model for hybrid rocket motors considering nozzle erosion has become a key technology that must be addressed when developing hybrid rocket motors. This study uses dynamic grid technology to simulate the regression of the combustion surface and nozzle erosion, which fits well with experimental values. The behavior of high-energy particles in the combustion chamber is simulated through a discrete phase model. Notably, distinctive behavior is observed in Al and Mg droplets, with Al droplets exhibiting incomplete vaporization in the combustion chamber while Mg droplets completely vaporize. A ground firing test using the Φ336 mm hybrid rocket motor lasting 200 s is conducted. The results show that the dynamic numerical simulation, accounting for nozzle erosion, substantially enhances performance prediction accuracy. The average deviation in motor thrust remains below 1.8%, and the combustion chamber pressure deviation stays under 2.6%, confirming the precision of the model. Ultimately, both simulation and experimental outcomes indicate a gradual decrease in specific impulse and characteristic velocity over the long-term operation, attributed to the gradual deviation of the oxygen-fuel ratio. This research provides valuable insights for guiding hybrid rocket motor design and optimizing design parameters to improve overall performance. This model can achieve long-duration and high-precision performance predictions for hybrid rocket motors.

This study investigated reconstruction techniques for building the instantaneous fuel regression rate of the hybrid rocket motor (HRM). Specifically, an experiment in a laboratory 500 N-class hybrid rocket motor with single-port wagon wheel fuel grain, operated with hydrogen peroxide (HP) and hydroxyl-terminated polybutadiene (HTPB) based fuel (including Al), was carried out. A piece of post-processing software was developed to reconstruct the instantaneous regression rate and other performance parameters of the HRM during the firing test. The results produced by the reconstruction techniques are in good agreement with experimental data obtained by traditional methods, with a maximum error of less than 5.75%. Moreover, compared with the traditional endpoint method, the reconstruction method had a significant advantage, which could ascertain the sensitivity of the regression rate to changes in the oxidizer mass flux and fit the formula of regression rate in a single firing test. Additionally, digital image processing techniques were employed to determine the axial distribution of the fuel regression rate after the test using computed tomography (CT) scanning. This served to verify the accuracy of the instantaneous reconstruction calculation. The error in the average regression rate between CT scanning and the reconstruction calculation was 1.91%, proving that the CT scanning and pixel statistic method of the calculating regression rate was practical for characterizing the axial distribution of the average regression rate during the firing test. In summary, the main objective of this study was to reconstruct the transient parameters of hybrid rocket motor with single-port wagon wheel fuel grain using reconstruction techniques, and to fit the formula of the regression rate through a single-firing test. Furthermore, this paper proposes a modified reconstruction method that is essential for investigating fuel regression rate during the firing test of HRMs.