Robust numerical tools are essential for enabling the use of hybrid rocket engines(HREs)in future space applications.In this context,Computational Fluid Dynamics(CFD)transient simulations can be employed to analyse an...Robust numerical tools are essential for enabling the use of hybrid rocket engines(HREs)in future space applications.In this context,Computational Fluid Dynamics(CFD)transient simulations can be employed to analyse and predict relevant fluid dynamics phenomena within the thrust chamber of small-scale HREs.This work applies such techniques to investigate two unexpected behaviours observed in a 10 N-class hydrogen peroxide-based hybrid thruster:an uneven regression rate during High-Density Polyethylene(HDPE)and Acrylonitrile Butadiene Styrene(ABS)fuel tests,and non-negligible axial consumption in the ABS test case.The present study seeks to identify their fluid-dynamic origins by analysing key aspects of the thruster’s internal ballistics.The impact of recirculation zones and mixing on regression rates is quantified,as is the effect of grain heating on performance.Although already known in the present scientific literature,these phenomena prove to become particularly relevant for small-scale engines.Furthermore,the study demonstrates how appropriate numerical tools can replicate experimental findings,helping to foresee and mitigate undesirable behaviours in the design phases of future HRE propulsion systems.CFD results match the final HDPE grain geometry,reproducing the uneven port diameters with a maximum error below 9%.For ABS,axial regression is accurately captured,confirming the model’s reliability.Furthermore,average regression rates differ by only 1.60%and 1.20%for HDPE and ABS,respectively,while mass consumption is reproduced within 1.70%for HDPE and 3.01%for ABS.Overall,the results of the work demonstrate the reliability of the numerical approach adopted.This enriches the analysis capabilities devoted to 10 N-class engines,provides an additional tool for simulating the internal ballistics of small-scale hybrid thrusters,and integrates the existing literature with new insights into their fluid dynamics.展开更多
文摘Robust numerical tools are essential for enabling the use of hybrid rocket engines(HREs)in future space applications.In this context,Computational Fluid Dynamics(CFD)transient simulations can be employed to analyse and predict relevant fluid dynamics phenomena within the thrust chamber of small-scale HREs.This work applies such techniques to investigate two unexpected behaviours observed in a 10 N-class hydrogen peroxide-based hybrid thruster:an uneven regression rate during High-Density Polyethylene(HDPE)and Acrylonitrile Butadiene Styrene(ABS)fuel tests,and non-negligible axial consumption in the ABS test case.The present study seeks to identify their fluid-dynamic origins by analysing key aspects of the thruster’s internal ballistics.The impact of recirculation zones and mixing on regression rates is quantified,as is the effect of grain heating on performance.Although already known in the present scientific literature,these phenomena prove to become particularly relevant for small-scale engines.Furthermore,the study demonstrates how appropriate numerical tools can replicate experimental findings,helping to foresee and mitigate undesirable behaviours in the design phases of future HRE propulsion systems.CFD results match the final HDPE grain geometry,reproducing the uneven port diameters with a maximum error below 9%.For ABS,axial regression is accurately captured,confirming the model’s reliability.Furthermore,average regression rates differ by only 1.60%and 1.20%for HDPE and ABS,respectively,while mass consumption is reproduced within 1.70%for HDPE and 3.01%for ABS.Overall,the results of the work demonstrate the reliability of the numerical approach adopted.This enriches the analysis capabilities devoted to 10 N-class engines,provides an additional tool for simulating the internal ballistics of small-scale hybrid thrusters,and integrates the existing literature with new insights into their fluid dynamics.
