This thesis aim to provide SSC, Swedish Space Corporation, with a foundation for understanding the key ideas behind water injection during rocket lift-off, including problems to be avoided when simulating the phenomena. This investigation focus on finding approaches suitable for obtaining a rough estimate of the reduction in noise generation, when too expensive equipment required is absent. The main idea was to compare different methods at the end as an alternative suitable way of verifying, since validation data was not available. The setup of the simulations consisted of two cases, one with water injection and the second case was without, and they were simulated the OpenFOAM software while the mesh was constructed using the GMSH software. A 1D analytical prediction model was computed using Matlab to estimate the noise generated. The result of the simulation showed an error of approximately 300-400 m/s within the rocket engine when compared to the Rocket Propulsion Analysis (RPA) software result. The maximum sound pressure level without water injection (SPL) from the analytical prediction model, ended up at approximately 172dB as well as 164dB depending on where it was "recorded". The maximum SPL with water injection was approximately 7dB lower in both recorded locations which was achieved by using optimal initial values. The biggest error observed by researches using this prediction model is approximately +2 dB above the real value. However, the error from this specific setup could not be estimated. The challenges and approximations encountered throughout this investigation is thoroughly discussed within the thesis and despite the absence of accurate results this investigation provides a thorough insight into water injection during rocket lift-off, with the potential of achieving better results using a more advanced solver in OpenFOAM.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-87278 |
Date | January 2021 |
Creators | Linus, Sångberg |
Publisher | Luleå tekniska universitet, Rymdteknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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