This study investigates the accuracy of different numerical schemes of OpenFOAM software to simulate compressible turbulent jets. Both pressure-based schemes utilizing the implicit PIMPLE algorithm and density-based schemes relying on AUSM scheme and explicit Runge-Kutta time integration are considered. The results of the numerical tests are compared and validated against data from NASA ARN nozzle geometry. The choice of parameter setting of the schemes is discussed in depth and possible optimization strategies are proposed to increase accuracy of RANS simulations of turbulent jets.
References
[1]
Moreau, S. (2022) The Third Golden Age of Aeroacoustics. Physics of Fluids, 34, Article ID: 031301. https://doi.org/10.1063/5.0084060
[2]
Paoli, R. and Shariff, K. (2015) Contrail Modeling and Simulation. Annual Review of Fluid Mechanics, 48, 393-427. https://doi.org/10.1146/annurev-fluid-010814-013619
[3]
Brés, G., P. Jordan, V. Januet, M. Le Rallic, A. Cavalieri, A. Towne, Lele, S., Colonius, T. and Schmidt, O. (2018) Importance of the Nozzle-Exit Boundary-Layer State in Subsonic Turbulent Jets. Journal of Fluid Mechanics, 581, 83-124. https://doi.org/10.1017/jfm.2018.476
[4]
Ball, C., Fellouah, H. and Pollard, A. (2012) The Flow Field in Turbulent Round Free Jets. Progress in Aerospace Sciences, 50, 1-26. https://doi.org/10.1016/j.paerosci.2011.10.002
[5]
Boguslawski, A., Tyliszczak, A., Wawrzak, A. and Wawrzak, K. (2017) Numerical Simulation of Free Jets. International Journal of Numerical Methods for Heat & Fluid Flow, 27, 1056-1063. https://doi.org/10.1108/HFF-03-2016-0103
[6]
Spalart, P. and Allmaras, S. (1992) A One-Equation Turbulence Model for Aero-Dynamic Flows. 30th Aerospace Sciences Meeting and Exhibit, Reno, 6-9 January 1992, 439. https://doi.org/10.2514/6.1992-439
[7]
Jones, W. and Launder, B.E. (1972) The Prediction of Laminarization with a Two-Equation Model of Turbulence. International Journal of Heat and Mass Transfer, 15, 301-314. https://doi.org/10.1016/0017-9310(72)90076-2
Cebeci, T. (2013) Analysis of Turbulent Flows with Computer Programs. Butterworth-Heinemann, Oxford.
[10]
Kenzakowski, D. (2004) Turbulence Modeling Improvements for Jet Noise Prediction Using PIV Datasets. 10th AIAA/CEAS Aeroacoustics Conference, Manchester, 10-12 May 2004, 2978. https://doi.org/10.2514/6.2004-2978
[11]
Koch, L., Bridges, J. and Khavaran, A. (2002) Flow Field Comparisons from Three Navier-Stokes Solvers for an Axisymmetric Separate Flow Jet. 40th AIAA Aerospace Sciences Meeting & Exhibit, Reno, 14-17 January 2002, 672. https://doi.org/10.2514/6.2002-672
[12]
Miltner, M., Jordan, C. and Harasek, M. (2015) CFD Simulation of Straight and Slightly Swirling Turbulent Free Jets Using Different RANS-Turbulence Models. Applied Thermal Engineering, 89, 1117-1126. https://doi.org/10.1016/j.applthermaleng.2015.05.048
[13]
Kaushik, M., Kumar, R. and Humrutha, G. (2015) Review of Computational Fluid Dynamics Studies on Jets. American Journal of Fluid Dynamics, 5, 1-11.
[14]
Georgiadis, N.J., Yoder, D.A. and Engblom, W.A. (2006) Evaluation of Modified Two-Equation Turbulence Models for Jet Flow Predictions. AIAA Journal, 44, 3107-3114. https://doi.org/10.2514/1.22650
[15]
Mishra, A.A. and Iaccarino, G. (2017) Uncertainty Estimation for Reynolds-Averaged Navier-Stokes Predictions of High-Speed Aircraft Nozzle Jets. AIAA Journal, 55, 3999-4004. https://doi.org/10.2514/1.J056059
[16]
Georgiadis, N.J., Rumsey, C.L., Yoder, D.A. and Zaman, K.B. (2006) Turbulence Modeling Effects on Calculation of Lobed Nozzle Flow Fields. Journal of Propulsion and Power, 22, 567-575. https://www.openfoam.com https://doi.org/10.2514/1.17160
[17]
Weller, H.G. and Tabor, G. (1998) A Tensorial Approach to Computational Continuum Mechanics Using Object-Oriented Techniques. Computers in Physics, 12, 620-631. https://doi.org/10.1063/1.168744
[18]
Kannan, B. (2015) Computation of an Axisymmetric Jet Using OpenFOAM. Procedia Engineering, 127, 1292-1299. https://doi.org/10.1016/j.proeng.2015.11.486
[19]
Zang, B., Vevek, U., Lim, H., Wei, X. and New, T. (2018) An Assessment of OpenFOAM Solver on RANS Simulations of Round Supersonic Free Jets. Journal of Computational Science, 28, 18-31. https://doi.org/10.1016/j.jocs.2018.07.002
[20]
Lee, Y.C., Yao, W. and Fn, X. (2017) A Low-Dissipation Scheme Based on OpenFOAM Designed for Large Eddy Simulation in Compressible Flow. 21st AIAA International Space Planes and Hypersonics Technologies Conference, Xiamen, 6-9 March 2017, 2017-2444. https://doi.org/10.2514/6.2017-2444
[21]
Li, S. and Paoli, R. (2020) Scalability of OpenFOAM Density-Based Solver with Runge-Kutta Temporal Discretization Scheme. Scientific Programming, 2020, Article ID: 9083620. https://doi.org/10.1155/2020/9083620
[22]
Modesti, D. and Pirozzoli, S. (2017) A Low-Dissipative Solver for Turbulent Compressible Flows on Unstructured Meshes, with OpenFOAM Implementation. Computers & Fluids, 152, 14-23. https://doi.org/10.1016/j.compfluid.2017.04.012
[23]
Bridges, J. and Wernet, M.P. (2011) The NASA Subsonic Jet Particle Image Velocimetry (PIV) Dataset.
[24]
Liou, M.-S. and Steffn Jr., C.J. (1993) A New Flux Splitting Scheme. Journal of Computational Physics, 107, 23-39. https://doi.org/10.1006/jcph.1993.1122