CFD Analysis of C-D Nozzle Compared with Theoretical & Experimental Data
Journal Title: INCAS BULLETIN - Year 2018, Vol 10, Issue 2
Abstract
In modern Computational Fluid Dynamic (CFD) Analysis of Convergent-Divergent (C-D) Nozzles, current research has shown that, it is common practice to use either experimental or analytical results to predict the accuracy of the CFD models by comparison of the results. It is also commonly agreed, amongst the literature reviewed, that the CFD modelling software packages available do not accurately model turbulence for applications such as transonic C-D nozzles. This study aims to develop a theoretical approach for calculation of flow properties along the axis of the C-D nozzle based on the fundamental gas dynamic equations. The theoretical analyses is validated by experimental data. Then, the CFD model is used to simulate the experimental cases which are compared with the data from both theoretical analysis and experimental measurements. Then, the validated CFD model can be used for more complex analyses, representing more elaborate flow phenomena such as internal shockwaves and boundary layers. The geometry used in the analytical study and CFD simulations constructed to model the experimental rig. The [1, 2] analytical study is undertaken using isentropic and adiabatic relationships and the output of the analytical study, the 'shockwave location tool', is created. The results from the analytical study are then used to optimise the redesign an experimental rig to for more favorable placement of pressure taps and gain a much better representation of the shockwaves occurring in the divergent section of the nozzle. The results from the CFD model can then be directly compared other results in order to gauge the accuracy of each method of analysis. The validated model can then be used in order to create several, novel nozzle designs which may offer better performance and ease of manufacture and may present feasible improvements to existing high-speed flow applications.
Authors and Affiliations
(Andrew) Stewart KEIR, Rob IVES, Faik HAMAD
Keywords
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- EP ID EP296937
- DOI 10.13111/2066-8201.2018.10.2.6
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