Hostname: page-component-848d4c4894-nr4z6 Total loading time: 0 Render date: 2024-05-04T10:25:48.200Z Has data issue: false hasContentIssue false
  • English
  • Français

High-fidelity aerodynamic modeling of an aircraft using OpenFoam – application on the CRJ700

Published online by Cambridge University Press:  07 October 2021

M. Segui ,
F.R. Abel ,
R.M. Botez Open the ORCID record for R.M. Botez [Opens in a new window]  and
A. Ceruti
M. Segui
Affiliation:
Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity LARCASE, École de Technologie Supérieure, Montreal, Quebec, Canada
F.R. Abel
Affiliation:
School of Engineering and Architecture, University of Bologna, Bologna, Italy
R.M. Botez*
Affiliation:
Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity LARCASE, École de Technologie Supérieure, Montreal, Quebec, Canada
A. Ceruti
Affiliation:
Department of Industrial Engineering, University of Bologna, Bologna, Italy
*
Email: ruxandra@gpa.etsmtl.ca
Get access Rights & Permissions [Opens in a new window]

Abstract

This study is focused on the development of longitudinal aerodynamic models for steady flight conditions. While several commercial solvers are available for this type of work, we seek to evaluate the accuracy of an open source software. This study aims to verify and demonstrate the accuracy of the OpenFoam solver when it is used on basic computers (32–64GB of RAM and eight cores). A new methodology was developed to show how an aerodynamic model of an aircraft could be designed using OpenFoam software. The mesh and the simulations were designed only using OpenFoam utilities, such as blockMesh, snappyHexMesh, simpleFoam and rhoSimpleFoam. For the methodology illustration, the process was applied to the Bombardier CRJ700 aircraft and simulations were performed for its flight envelope, up to M0.79. Forces and moments obtained with the OpenFoam model were compared with an accurate flight data source (level D flight simulator). Excellent results in data agreement were obtained with a maximum absolute error of 0.0026 for the drag coefficient, thus validating a high-fidelity aerodynamic model for the Bombardier CRJ-700 aircraft.

Keywords

AerodynamicsOpenFoam softwareCRJ-700 aircraftCompressible flowIncompressible flow
Type
Research Article
Information
The Aeronautical Journal , Volume 126 , Issue 1298 , April 2022 , pp. 585 - 606
Check for updates
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Filippone, A., Zhang, M. and Bojdo, N. Validation of an integrated simulation model for aircraft noise and engine emissions, Aerospace Sci. Technol., 2019, 89, pp 370–381. https://doi.org/10.1016/j.ast.2019.04.008.CrossRefGoogle Scholar
Filippone, A. Theoretical framework for the simulation of transport aircraft flight, J. Aircraft, 2010, 47, (5), pp 1679–1696. https://doi.org/10.2514/1.C000252.CrossRefGoogle Scholar
Bacchini, A. and Cestino, E. Key aspects of electric vertical take-off and landing conceptual design, Proc. Inst. Mech. Eng. Part G J. Aerospace Eng., 2020, 234, (3), pp 774–787. https://doi.org/10.1177/0954410019884174.CrossRefGoogle Scholar
Cestino, E., Frulla, G., Spina, M., Catelani, D. and Linari, M. Numerical simulation and experimental validation of slender wings flutter behaviour, Proc. Inst. Mech. Eng. Part G J. Aerospace Eng., 2019, 233, (16), pp 5913–5928. https://doi.org/10.1177/0954410019879820.CrossRefGoogle Scholar
Bacchini, A., Cestino, E., Van Magill, B. and Verstraete, D. Impact of lift propeller drag on the performance of EVTOL Lift+cruise aircraft, Aerospace Sci. Technol., 2021, 109, p 106429. https://doi.org/10.1016/j.ast.2020.106429.CrossRefGoogle Scholar
Filippone, A., Parkes, B., Bojdo, N. and Kelly, T. Prediction of aircraft engine emissions using ADS-B flight data, Aeronaut. J., 2021, pp 1–25. https://doi.org/10.1017/aer.2021.2.Google Scholar
Liem, R.P., Mader, C.A. and Martins, J.R.R.A. Surrogate models and mixtures of experts in aerodynamic performance prediction for aircraft mission analysis, Aerospace Sci. Technol., 2015, 43, pp 126–151. https://doi.org/10.1016/j.ast.2015.02.019.CrossRefGoogle Scholar
Sugar Gabor, O., Koreanschi, A. and Botez, R. A new non-linear vortex lattice method: applications to wing aerodynamic optimizations, Chin. J. Aeronaut., 2016, 29. https://doi.org/10.1016/j.cja.2016.08.001.CrossRefGoogle Scholar
Segui, M., Mantilla, M. and Botez, R.M. Design and validation of an aerodynamic model of the Cessna citation X horizontal stabilizer using both OpenVSP and digital Datcom.” Int. J. Mech. Ind. Aerospace Sci., 2018, 11, (1). https://doi.org/10.5281/zenodo.1315951.Google Scholar
Segui, M., Ghazi, G., Botez, R.M. and Thompson, E. Design, development and validation of a Cessna citation X aerodynamic model using OpenVSP software, AIAA Aviation Forum, No. No: AIAA 2018-3256, Atlanta, Georgia, USA, 2018.CrossRefGoogle Scholar
Segui, M., Kuitche, M. and Botez, R.M. Longitudinal aerodynamic coefficients of hydra technologies UAS-S4 from geometrical data. Presented at the AIAA Scitech Forum, Grapevine, Texas, 2017.CrossRefGoogle Scholar
Segui, M. and Botez, R.M. Aerodynamic coefficients prediction from minimum computation combinations using OpenVSP software, Int. J. Mech. Ind. Eng., 2018, 12, (1), pp 9–16. https://doi.org/10.5281/zenodo.1315609.Google Scholar
Liauzun, C. Assessment of CFD techniques for wind turbine aeroelasticity, Presented at the ASME 2006 Pressure Vessels and Piping/ICPVT-11 Conference, Vancouver, BC, Canada, 2006.CrossRefGoogle Scholar
Huvelin, F., Dequand, S., Lepage, A. and Liauzun, C. On the validation and use of high-fidelity numerical simulations for gust response analysis, AerospaceLab J., 2018, 14, 16 p. https://doi.org/10.12762/2018.AL14-06.Google Scholar
Zou, Y., Zhao, X. and Chen, Q. Comparison of STAR-CCM+ and ANSYS fluent for simulating indoor airflows, Build. Simul., 2018, 11, (1), pp 165–174. https://doi.org/10.1007/s12273-017-0378-8.CrossRefGoogle Scholar
He, P., Mader, C.A., Martins, J.R.R.A. and Maki, K.J. An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM, Comput. Fluids, 2018, 168, pp 285–303. https://doi.org/10.1016/j.compfluid.2018.04.012.CrossRefGoogle Scholar
Mangano, M. and Martins, J.R.R.A. Multipoint aerodynamic shape optimization for subsonic and supersonic regimes, J. Aircraft, 2021, 58, (3), pp 650–662. https://doi.org/10.2514/1.C036216.CrossRefGoogle Scholar
Secco, N.R., Kenway, G.K.W., He, P., Mader, C. and Martins, J.R.R.A. “Efficient mesh generation and deformation for aerodynamic shape optimization, AIAA J., 59, (4), 2021, pp 1151–1168. https://doi.org/10.2514/1.J059491.CrossRefGoogle Scholar
Comparing CFD Software - Part 2: Open Source CFD Software Packages . Resolved Analytics CFD Consulting and Simulation Strategy. https://www.resolvedanalytics.com/theflux/comparing-cfd-software-part-2-open-source-cfd-software-packages. Accessed April 27, 2020.Google Scholar
Le, N.T.P., Greenshields, Ch.J. and Reese, J.M. Evaluation of nonequilibrium boundary conditions for hypersonic rarefied gas flows, Presented at the Progress in Flight Physics, Versailles, France, 2012.CrossRefGoogle Scholar
Sorribes-Palmer, F., Sanz Andres, A., Figueroa, A., Donisi, L., Franchini, S. and Ogueta, M. Aerodynamic design of a wind turbine diffuser with OpenFoam, Presented at the 7th European and African Conference on Wind Engineering, Liège, Belgium, 2017.Google Scholar
Ashton, N. and Skaperdas, V. Verification and validation of OpenFOAM for high-lift aircraft flows, J. Aircraft, 2019, 56, (4), pp 1641–1657. https://doi.org/10.2514/1.C034918.CrossRefGoogle Scholar
Li, S. and Paoli, R. Modeling of ice accretion over aircraft wings using a compressible OpenFOAM solver, Int. J. Aerospace Eng., 2019, 2019, pp 1–11. https://doi.org/10.1155/2019/4864927.Google Scholar
Hou, Y., Angland, D. and Scotto, A. The ability of a weakly compressible solver to predict landing gear noise with flow-acoustic interactions, Presented at the 23rd AIAA/CEAS Aeroacoustics Conference, Denver, Colorado, 2017.CrossRefGoogle Scholar
Behrens, A., Grund, T., Ebert, C., Luckner, R. and Weiss, J. Investigation of the aerodynamic interaction between two wings in a parallel flight with close lateral proximity, CEAS Aeronaut. J., 2020, 11, (2), pp 553–563. https://doi.org/10.1007/s13272-019-00435-9.CrossRefGoogle Scholar
Ashton, N., Unterlechner, P. and Blacha, T. Assessing the sensitivity of hybrid RANS-LES simulations to mesh resolution, numerical schemes and turbulence modelling within an industrial CFD process, Presented at the WCX World Congress Experience, 2018.CrossRefGoogle Scholar
Ghazi, G., Bosne, M., Sammartano, Q. and Botez, R.M. Cessna citation X stall characteristics identification from flight data using neural networks, Presented at the AIAA Scitech Forum, Grapevine, Texas, USA, 2017.CrossRefGoogle Scholar
Ghazi, G., Botez, R.M. and Messi Achigui, J. Cessna citation X engine model identification from flight tests, SAE Int. J. Aerospace, 2015, 8. https://doi.org/10.4271/2015-01-2390.CrossRefGoogle Scholar
Botez, R.M., Bardela, P.-A. and Bournisien, T. Cessna citation X simulation turbofan modelling: identification and identified model validation using simulated flight tests, Aeronaut. J., 2019, 123, pp 1–31. https://doi.org/10.1017/aer.2018.166.CrossRefGoogle Scholar
Botez, R. Morphing wing, UAV and Aircraft Multidisciplinary Studies at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity LARCASE, AerospaceLab J., 14, 2018, September 2018; ISSN: 21076596. https://doi.org/10.12762/2018.AL14-02.Google Scholar
Bardela, P.-A., Botez, R.M., Bournisien, T. and Rusovici, R. Identification and validation of the Cessna citation X Turbofan modelling with flight tests, Presented at the AIAA Scitech Forum, Kissimmee, Florida, USA, 2018.CrossRefGoogle Scholar
Koreanschi, A., Sugar Gabor, O. and Botez, R.M. Numerical and experimental validation of a morphed wing geometry using price-païdoussis wind tunnel testing, Aeronaut. J., 2016, 120. https://doi.org/10.1017/aer.2016.30.CrossRefGoogle Scholar
Kuitche, M., Botez, R., Guillemin, A. and Communier, D. Aerodynamic modelling of unmanned aerial system through nonlinear vortex lattice method, computational fluid dynamics and experimental validation - application to the UAS-S45 Bàlaam: part 1, INCAS Bull., 2020, 12, pp 91–103. https://doi.org/10.13111/2066-8201.2020.12.1.9.CrossRefGoogle Scholar
Airplane Simulator Qualification. Publication AC 120-40B. Federal Aviation Administration (FAA), U.S Department of Transportation, 1991.Google Scholar
Stańkowski, T.P., MacManus, D.G., Sheaf, C.T. and Christie, R. Aerodynamics of aero-engine installation, Proc. Inst. Mech. Eng. Part G J. Aerospace Eng., 2016, 230, (14), pp 2673–2692. https://doi.org/10.1177/0954410016630332.CrossRefGoogle Scholar
Lee, E.E. and Pendergraft, O.C. Installation Effects of Long-Duct Pylon-Mounted Nacells on a Twin-Jet Transport Model with Swept Supercritical Wing. Publication 2457. National Aeronautics and Space Administration (NASA), Langley Memorial Laboratory, 1985, Hampton, Virginia, USA.Google Scholar
Raymer, D.P. Aircraft Design: A Conceptual Approach, American Institute of Aeronautics and Astronautics, 2012, Reston, VA.CrossRefGoogle Scholar
Cfdsupport. CFDsupport OpenFoam for windows. https://www.cfdsupport.com/openfoam-for-windows.html.Google Scholar
Wilcox, D.C. Turbulence Modeling for CFD, DCW Industries, Inc., 2006.Google Scholar
Anderson, J.D. Fundamentals of Aerodynamics, McGraw Hill Education, 2017, New York, NY.Google Scholar
Caretto, L.S., Gosman, A.D., Patankar, S.V. and Spalding, D.B. Two Calculation Procedures for Steady, Three-Dimensional Flows with Recirculation. Publication 197315. National Aeronautics and Space Administration (NASA), p 26.Google Scholar
Moukalled, F., Mangani, L. and Darwish, M. The Finite Volume Method in Computational Fluid Dynamics: An Advanced Introduction with OpenFOAM and Matlab, Springer, 2016, Cham, Heidelberg, New York, Dordrecht, London.CrossRefGoogle Scholar
Menter, F.R. Two-equation Eddy-viscosity turbulence models for engineering applications, AIAA J., 1994, 32, (8), pp 1598–1605. https://doi.org/10.2514/3.12149.CrossRefGoogle Scholar
Rumsey, C. NASA Langley Research Center - Turbulence Modeling Resource. https://turbmodels.larc.nasa.gov/index.html.Google Scholar
Spalart, P.R. and Rumsey, C.L. Effective inflow conditions for turbulence models in aerodynamic calculations, AIAA J., 2007, 45, (10), pp 2544–2553. https://doi.org/10.2514/1.29373.CrossRefGoogle Scholar
Grisval, J.-P. and Liauzun, C. Application of the finite element method to aeroelasticity, Revue Européenne des Éléments Finis, 1999, 8, (5–6), pp 553–579. https://doi.org/10.1080/12506559.1999.10511397.CrossRefGoogle Scholar
Launder, B.E. and Spalding, D.B. The numerical computation of turbulent flows, Comput. Methods Appl. Mech. Eng., 1974, 3, (2), pp 269–289. https://doi.org/10.1016/0045-7825(74)90029-2.CrossRefGoogle Scholar
Fangqing, L. A Thorought Description of How Wall Function are Implemented in OpenFOAM, Chalmers University of Technology, 2016.Google Scholar
OpenCFD ltd (ESI Group). OpenFoam The Open Source CFD Toolbox. OpenCFD ltd (ESI Group), 2019.Google Scholar
Finite Volume Method: A Crash Introduction. Wold Dynamics - Multiphyisics Simulations, Optimization & Data analytics. http://www.wolfdynamics.com/wiki/fvm_crash_intro.pdf.Google Scholar
Menter, F.R., Kuntz, M. and Langtry, R. Ten years of industrial experience with the SST turbulence model, Turbul. Heat Mass Transfer, 2003, 4, pp 625–632.Google Scholar
White, F.M. Viscous Fluid Flow, McGraw-Hill Higher Education, 2006, New York, NY.Google Scholar
Chevalier, C. and Pellegrini, F. PT-scotch: a tool for efficient parallel graph ordering, Paral. Comput., 2008, 34, (6–8), pp 318–331. https://doi.org/10.1016/j.parco.2007.12.001.CrossRefGoogle Scholar
Friedlander, S. and Serre, D. (Eds), Handbook of Mathematical Fluid Dynamics, Elsevier, 2007, Amsterdam.Google Scholar