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Computational fluid dynamics modelling of store separation using grid method
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Date
2017
Author
Demir, Görkem
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In this study, two different wind tunnel techniques, captive trajectory and the grid surveying method, were implemented to computational fluid dynamics (CFD) and used to calculate the trajectory of a store. The main purpose of this thesis is to demonsrate that grid method is an alternative method to those already used as it provides flexibility to store separation problems and can be used during the design process. EGLIN test geometry was used to validate the analyses results because it provided existing wind tunnel results. Simulations were performed using a well-known flow solver called ANSYS Fluent. The trajectory of the store was estimated using the captive trajectory approach and the results compared with experimental data. Secondly, a six degrees of freedom (6DOF) code was developed using MATLAB Simulink to calculate the trajectory using the grid method. The required CFD analyses corresponding to different attitudes of the store were performed to generate an aerodynamic grid database and the trajectory was computed. The results were compared with both captive trajectory and wind tunnel results to investigate the reliability of grid method results. Then, two different simulations were also performed to demonsrate the advantage of the grid method in terms of time. The simulation times were compared between both methods and the required time for the grid method was observed considerably lower. Therefore, grid method is an alternative solution techniques for store separation problems.
Subject Keywords
Wind tunnel models.
,
Trajectories (Mechanics).
,
Computational fluid dynamics.
,
Computational grids (Computer systems)
URI
http://etd.lib.metu.edu.tr/upload/12620899/index.pdf
https://hdl.handle.net/11511/26398
Collections
Graduate School of Natural and Applied Sciences, Thesis
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G. Demir, “Computational fluid dynamics modelling of store separation using grid method,” M.S. - Master of Science, Middle East Technical University, 2017.