A comprehensive fluid–solid coupling dynamic simulation for spatiotemporal distribution of regression rate in hybrid rocket motors

Abstract

The spatiotemporal distribution characteristics of the regression rate are crucial aspects of the research on Hybrid Rocket Motor (HRM). This study presents a pioneering effort in achieving a comprehensive numerical simulation of fluid dynamics and heat transfer in both the fluid and solid regions throughout the entire operation of an HRM. To accomplish this, a dynamic grid technique that incorporates fluid–solid coupling is utilized. To validate the precision of the numerical simulations, a firing test is conducted, with embedded thermocouple probes being used to measure the inner temperature of the fuel grain. The temperature variations in the solid fuel obtained from both experiment and simulations show good agreement. The maximum combustion temperature and average thrust obtained from the simulations are found to deviate from the experimental results by only 3.3% and 2.4%, respectively. Thus, it can be demonstrated that transient numerical simulations accurately capture the fluid–solid coupling characteristics and transient regression rate. The dynamic simulation results of inner flow field and solid region throughout the entire working stage reveal that the presence of vortices enhances the blending of combustion gases and improves the regression rate at both the front and rear ends of the fuel grain. In addition, oscillations of the regression rate obtained in the simulation can also be well corresponded with the corrugated surface observed in the experiment. Furthermore, the zero-dimension regression rate formula and the formula describing the axial location dependence of the regression rate are fitted from the simulation results, with the corresponding coefficients of determination (R2) of 0.9765 and 0.9298, respectively. This research serves as a reference for predicting the performance of HRM with gas oxygen and polyethylene, and presents a credible way for investigating the spatiotemporal distribution of the regression rate.