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Computational Analysis of Shockwave–Boundary Layer Interaction at Hypersonic Speeds

Sravankumar Kota, P. V Subbaraju

Abstract


Successful plan of present-day supersonic and hypersonic vehicles requires a comprehension of the physical stream field structure of shockwave–boundary-layer interactions (SWBLIs) and productive reproduction techniques for their portrayal. The significant focal point of this paper is two-dimensional (2D) hypersonic SBLI as well as stream portrayal and physical properties around SWBLIs; be that as it may, even in ostensibly 2D/axis-symmetric streams, the mean stream measurements might be 3D.The objective of the present paper is to characterize the flow of double-wedge shock–shock interactions using CFD analysis. Conditions of types 4, 5, and 6 shock interactions are studied. The geometry used to generate the primary and secondary shocks is that of 2D, 3D double-wedge geometry including the heat transfer, because it is needed in hypersonics. Different types of SBLI can be studied and captured, i.e. incident-reflection shockwave, compression ramp, normal shock, an imposed pressure jump, oblique shock induced by forward facing step. The main objective is to capture the shockwave accurately by using different turbulence models, i.e. Reynolds-averaged Navier–Stokes equation, large eddy simulation, detached eddy simulation, direct numerical simulation, Spalart–Allmaras, k-epsilon, k-omega, etc. The results of double wedge can be compared with previous journal double-wedge shockwave integration flow characterization. We are using CFD tool (Gambit) to model and simulate(fluent) the domain with different turbulence models like k-epsilon, k-omega, RANS, LES, DES, etc., and comparing the results for better captured using Techplot360.


Keywords


hypersonic vehicles; Shock Wave Boundary Layer Interaction (SBLIs); hypersonic speed

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References


Sravan Kumar Kota, P.V Subbaraju. Computational Analysis of Shockwave–Boundary Layer Interaction at Hypersonic Speeds. International Journal of Computer Aided Manufacturing. 2019; 5(2): 1–25p.




DOI: https://doi.org/10.37628/jcam.v5i2.924

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