Calibration of the CFD code based on testing of a standard AGARD-B model for determination of aerodynamic characteristics

Abstract

The goal of this work is to build a unique numerical method to obtain the basic aerodynamic characteristics of the aircraft and to enable a wide application of the method in the analysis of some aerodynamic characteristics of the aircraft, without use of empirical methods. The Computational fluid dynamics (CFD) simulation method was being calibrated based on test results of the standard AGARD-B (Advisory Group for Aerospace Research and Development) test model, which were obtained in the T-38 trisonic wind tunnel facility of the Military Technical Institute (VTI) in Belgrade, Serbia.The paper presents the CFD simulation through a description of the conditions of flow, geometry of the computer domain, grid density and mesh strategy, boundary conditions, initial strategy and turbulence model. The CFD simulation was carried out for flow cases with similarity parameters M = 0.6, M = 0.85 and M = 1.6 and Re = from 7.7(x10⁶) to 9.9(x10⁶) . The results of calculations were compared with the appropriate experimental ones and presented in the form of comparative diagrams for the drag, lift and pitching moment coefficients. The results of investigation presented in divergence diagrams show very good agreement between numerical and experimental ones. Simulated flows are illustrated by the distribution of pressure and velocity components on the surface of the tested model and the computational domain. This CFD simulation will be applied to other similar aerodynamic designs for a wide range angles of attack and Mach numbers and can be a strong point for the development of different aerodynamic designs.The ultimate aim of the work is to use the previous calibrated CFD simulation method as the basis for future determination of the aerodynamic characteristics of aircraft in non-stationary flight modes, caused by motion of the aircraft and/or by changing the free-velocity vector.

Keywords

Aerodynamic coefficients calibration model CFD code experimental aerodynamics fluid dynamics wind tunnel

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References

Rašuo

. Scaling between wind tunnels-results accuracy in two-dimensional testing. T Jpn Soc Aeronaut S 2012; 55: 109–115.

Rašuo B. On results’ accuracy at two-dimensional wind tunnel testing. In: 26th ICAS congress, Anchorage, Alaska, USA, 14–19 September 2008, paper no. ICAS2008-P2.12.

William

Trucano

. Verification and validation in computational fluid dynamics. Prog Aerosp Sci 2002; 38: 209–272.

Kostić

, et al. Hybrid approach in the initial aerodynamic, stability and performance calculations of a light airplane. Teh Vjesn 2013; 20: 605–614.

Ocokoljić

Rašuo

Kozić

. Supporting system interference on aerodynamic characteristics of an aircraft model in a low-speed wind tunnel. Aerosp Sci Technol 2017; 64: 133–146.

Yan

Mohammadian

Rennie

, et al. Numerical modeling of flow and local scour around pipeline in steady currents using moving mesh with masked elements. J Hydraul Eng 2020; 146: 06020005.

Zhou

Han

, et al. Aerodynamic configuration of the HCW based on the lifting body. J Aerosp Eng 2019; 32: 04019004.

Zhang

, et al. Unsteady experimental and numerical investigation of aerodynamic performance in ultra-high-lift LPT. Chin J Aeronaut 2020; 33: 1421–1432., pages

Paziresh A, Nikseresht AH and Moradi H. Wing-Body and vertical tail interference effects on downwash rate of the horizontal tail in subsonic flow. JOAE 2017; 30: 04017001.

10.

Vidanović

, et al. Validation of the CFD code used for determination of aerodynamic characteristics of non-standard AGARD-B calibration model. Therm Sci 2014; 18: 1223–1233.

11.

Menter

. Performance of popular turbulence models for attached and separated adverse pressure gradient flow. AIAA J 1992; 30: 2066–2072.

12.

Menter FR. Improved two-equation k-ω turbulence models for aerodynamic flows. NASA Technical Memorandum TM-103975, October 1992.

13.

Menter

. Two-equation eddy-viscosity turbulence model for engineering applications. AIAA J 1994; 32: 1598–1605.

14.

Menter

. Eddy-viscosity transport equations and their relation to the k-ε model. J Fluid Eng Trans ASME 1997; 119: 876–884.

15.

Zhong

. A modal approach for coupled fluid. Proc IMechE, Part G: J Aerospace Engineering 2017; 231: 72–81.

16.

Hadidoolabi

Ansarian

. Supersonic flow over a pitching delta wing using surface pressure measurements and numerical simulations. Chin J Aeronaut 2018; 31: 65–78.

17.

Damljanović

, et al. Testing of AGARD-B calibration model in the T-38 wind tunnel. Sci Tech Rev 2006; 56: 52–62.

18.

Damljanović

Rašuo

. Testing of calibration models in order to certify the overall reliability of the trisonic blowdown wind tunnel of VTI. FME Trans 2010; 38: 167–172.

19.

Damljanović

Isaković

Rašuo

, et al. The T-38 wind tunnel data quality assurance based on testing of a standard model. J Aircr 2013; 50: 1141–1149.

20.

Damljanović

Rašuo

Isaković

, et al. Hypervelocity ballistic reference models as experimental supersonic test cases. Aerosp Sci Technol 2016; 52: 189–197.

21.

AGARD. Specifications for AGARD Wind Tunnel Calibration Models. AGARD Memorandum AG-4/M3, AGARD, 1955.

22.

AGARD. Wind tunnel calibration models. AGARD Specification 2, AGARD, 1958.

23.

Hills R. A review of measurements on AGARD calibration models. AGARDograph 64, Aircraft Research Association Bedford, England, 1961.

24.

Djordje

Dijana

. Thermal effects influencing measurements in a supersonic blowdown wind tunnel. Therm Sci 2016; 20: 2101–2112.

25.

Anderson

. Computational fluid dynamics. 1st ed. New York: McGraw-Hill Inc., 1995.

26.

Lanfrit

. Best practice guidelines for handling automotive external aerodynamics with FLUENT. Germany: Fluent Deutschland GmbH, 2005.

27.

Kim E and Choudhury D. A near-wall treatment using wall functions sensitized to pressure gradient. ASME FED, Separated and Complex Flows 1995; 217: 273–280.

28.

Versteeg

Malalasekera

. An introduction to computational fluid dynamics: the finite volume method. London: Pearson Education Limited, 2007.

29.

Monk D, et al. Comparison of turbulence models effectiveness for a delta wing at low Reynolds numbers. In: 7th European conference for aeronautics and space sciences (EUCASS). Milan, Italy, 3–6 July 2017, paper no. EUCASS2017-653.

30.

Kim S, Choudhury D and Patel B. Computations of complex turbulent flows using the commercial code FLUENT. In: Salas MD, Hefner JN and Sakell L (eds) Modeling complex turbulent flows. ICASE/LaRC interdisciplinary series in science and engineering, vol. 7. Dordrecht: Springer, 1999, pp. 259–276.

31.

Garbaruk

Niculin

Strelets

, et al. Comparative study of different turbulence modeling approaches to prediction of transonic and supersonic flows past a reentry capsule with balance flaps. EUCASSProg Flight Phys 2013; 5: 3–22.

32.

Kostić

. Review of the Spalart-Allmaras turbulence model and its modifications to three-dimensional supersonic configurations. Sci Tech Rev 2015; 65: 43–49.

33.

Damljanovic D, Vukovic D, Ocokoljic G, et al. A study of wall-interference efects in wind-tunnel testing of a standard model at transonic speeds – experimental aerodynamics. In: The 30th ICAS congress, Daejeon, Korea, 25–30 September 2016.

34.

Rašuo B. The influence of Reynolds and Mach numbers on two-dimensional wind-tunnel testing: an experience. Aeronaut J 2011; 115: 249–254.

35.

Ocokoljić

Damljanović

Vuković

, et al. Contemporary frame of measurement and assessment of wind-tunnel flow quality in a low-speed facility. FME Trans 2018; 46: 429–442.

36.

Brett

Ooi

. Effect of sweep angle on the vortical flow over delta wings at an angle of attack of 10°. J Eng Sci Technol 2014; 9: 768–781.