| Summary: | At Université Libre de Bruxelles (ULB), research was performed on a 1 kN lab-scale Hybrid Rocket Motor (the ULB-HRM). It has a single-port solid paraffin fuel grain and uses liquid <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>N</mi><mn>2</mn></msub><mi>O</mi></mrow></semantics></math></inline-formula> as an oxidizer. The first Computational Fluid Dynamics (CFD) model of the motor was developed in 2020 and improved in 2021, using ANSYS Fluent software. It is a 2D axisymmetric, two-phase steady-state Reynolds-Averaged Navier–Stokes (RANS) model, which uses the average fuel and oxidizer mass flow rates as inputs. It includes oxidizer spray droplets and entrained fuel droplets, therefore adding many additional parameters compared to a single-phase model. It must be investigated how they affect the predicted operating conditions. In this article, a sensitivity analysis is performed to determine the model’s robustness. It is demonstrated that the CFD model performs well within the boundaries of its purpose, with average deviations between predicted and experimental values of about <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the chamber pressure and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the thrust. From the sensitivity analysis, multiple observations and conclusions are made. An important observation is that oxidizer related parameters have the highest potential impact, introducing deviations of the predicted operating chamber pressure of up to 18%, while this is only about <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>6</mn><mo>%</mo></mrow></semantics></math></inline-formula> for fuel-related parameters. In general, the baseline CFD model of the ULB-HRM seems quite insensitive and it does not suffer from an excessive or abnormal sensitivity to any of the major parameters. Furthermore, the predicted operating conditions seem to respond in a logical and coherent way to changing input parameters. The model therefore seems sufficiently reliable to be used for future qualitative and quantitative predictions of the performance of the ULB-HRM.
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