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2 - An Overview of Scale-Resolving Simulation Models for Practical Flows

from Part I - Paradigms and Tools

Published online by Cambridge University Press:  31 January 2025

By
Filipe S. Pereira
Edited by
Fernando F. Grinstein ,
Filipe S. Pereira  and
Massimo Germano
Fernando F. Grinstein
Affiliation:
Los Alamos National Laboratory
Filipe S. Pereira
Affiliation:
Los Alamos National Laboratory
Massimo Germano
Affiliation:
Duke University, North Carolina
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Summary

Scale-resolving simulation (SRS) methods of practical interest are coarse-graining formulations widely used in science and engineering. These methods aim to efficiently predict complex flows by only resolving the phenomena not amenable to modeling, unleashing the concept of accuracy on demand. This chapter provides an overview of the SRS methods best suited for engineering applications: hybrid and bridging models. It starts by reviewing basic turbulence modeling concepts. Following on from that is an overview of hybrid and bridging models, discussing their main advantages and limitations. The challenges to the predictive application of these models are enumerated, as well as possible strategies to solve or mitigate them. Several examples are provided to illustrate the potential of these classes of SRS methods. Overall, the chapter intends to help new and experienced SRS modelers and users obtain predictive turbulence computations.

Type
Chapter
Information
Coarse Graining Turbulence
Modeling and Data-Driven Approaches and their Applications
 , pp. 48 - 90
Publisher: Cambridge University Press
Print publication year: 2025

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References

Abdol-Hamid, K. S., and Girimaji, S. S. 2004. A Two-Stage Procedure toward the Efficient Implementation of PANS and Other Hybrid Turbulence Models. Technical Report TM-2004-213260. National Aeronautics and Space Administration (NASA), Langley Research Center, Hampton, United States of America.Google Scholar
Achenbach, E. 1971. Influence of Surface Roughness on the Cross-Flow around a Circular Cylinder. Journal of Fluid Mechanics, 46(2), 321–335.CrossRefGoogle Scholar
AIAA CFD Drag Prediction Workshop. 2022. https://aiaa-dpw.larc.nasa.gov.Google Scholar
AIAA CFD High Lift Prediction Workshop. 2023. https://hiliftpw.larc.nasa.gov.Google Scholar
ASME. 2009. Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer – ASME V&V 20–2009. ASME.Google Scholar
ASME VVUQ Symposium. 2023. American Society of Mechanical Engineers.Google Scholar
Basara, B., Pavlovic, Z., and Girimaji, S. 2018. A New Approach for the Calculation of the Cut-Off Resolution Parameter in Bridging Methods for Turbulent Flow Simulation. International Journal of Heat and Fluid Flow, 74, 76–88.CrossRefGoogle Scholar
Batten, P., Goldberg, U., and Chakravarthy, S. 2000. Sub-grid Turbulence Modeling for Unsteady Flow with Acoustic Resonance. In: Proceedings of the 38th American Institute of Aeronautics and Astronautics Aerospace Sciences Meeting & Exhibit.CrossRefGoogle Scholar
Batten, P., Goldberg, U., and Chakravarthy, S. 2002. LNS – An Approach towards Embedded LES. In: Proceedings of the 40th American Institute of Aeronautics and Astronautics Aerospace Sciences Meeting & Exhibit.CrossRefGoogle Scholar
Billson, M., Eriksson, L.-E., Davidson, L., and Jordan, P. 2004. Modeling of Synthetic Anisotropic Turbulence and Its Sound Emission. In: Proceedings of the 10th American Institute of Aeronautics and Astronautics (AIAA) and Council of European Aerospace Societies (CEAS) Aeroacoustics Conference.CrossRefGoogle Scholar
Boffeta, G., and Mazzino, A. 2017. Incompressible Rayleigh–Taylor Turbulence. Annual Review of Fluid Mechanics, 49, 119–143.Google Scholar
Boris, J. P., Grinstein, F. F., Oran, E. S., and Kolbe, R. L. 1992. New Insights into Large Eddy Simulation. Fluid Dynamics Research, 10(4–6), 199–228.CrossRefGoogle Scholar
Bose, S. T., and Park, G. I. 2018. Wall-Modeled Large-Eddy Simulation for Complex Turbulent Flows. Annual Review of Fluid Mechanics, 50(1), 535–561.CrossRefGoogle ScholarPubMed
Boussinesq, J. 1877. Essai sur la Théorie des Eaux Courantes. Mémoires Présentés par Divers Savants à L’Académie des Sciences, 23(1).Google Scholar
Brachet, M. E., Meiron, D. I., Orzag, S. A., Nickel, B. G., Morf, R. H., and Frisch, U. 1983. Small Scale Structure of the Taylor–Green Vortex. Journal of Fluid Mechanics, 130, 411–452.CrossRefGoogle Scholar
Brouwer, J., Tukker, J., and van Rijsbergen, M. 2013 (17–18 September). Uncertainty Analysis of Finite Length Measurement Signals. In: Proceedings of the 3rd International Conference on Advanced Model Measurement Technology for EU Maritime Industry.Google Scholar
Caruelle, B. 2000. Simulations D’Écoulements Instationnaires Turbulents en Aérodynamique: Application à la Prédiction du Phénomène de Tremblement. Ph.D. thesis, Institut National Polytechnique Toulose, Toulouse, France.Google Scholar
Chaouat, B. 2017. The State of the Art of Hybrid RANS/LES Modeling for the Simulation of Turbulent Flows. Flow, Turbulence, and Combustion, 99, 279–327.CrossRefGoogle ScholarPubMed
Chaouat, B., and Schiestel, R. 2005. A New Partially Integrated Transport Model for Subgrid-Scale Stresses and Dissipation Rate for Turbulent Developing Flows. Physics of Fluids, 17(6).Google Scholar
Crow, S. C. 1970. Stability Theory for a Pair of Trailing Vortices. AIAA Journal, 8(12), 2172–2179.CrossRefGoogle Scholar
Dahlström, S., and Davidson, L. 2003. Hybrid RANS/LES Employing Interfaces Condition with Turbulent Structure. Pages 689–696 of: Proceedings of the 4th International Symposium on Turbulence, Heat and Mass Transfer.Google Scholar
D’Alessandro, V., Giammichele, L., Lops, C., and Ricci, R. 2020. Towards DES/DDES Computation of the Flow Field and Heat Transfer Adopting Elliptic Relaxation and Local Correlation Based Transition Approaches. Journal of Physics: Conference Series, 1599, 012042.Google Scholar
Davidson, L., and Friess, C. 2019. A New Formulation of fk for the PANS model. Journal of Turbulence, 20(5), 322–336.CrossRefGoogle Scholar
Davidson, P. A. 2006. Turbulence: An Introduction for Scientists and Engineers. Oxford University Press.Google Scholar
Deck, S. 2002. Simulation Numérique de Charges Latéras Instationnaires sur des Configurations de Lanceur. Ph.D. thesis, Université D’Orléans, Orléans, France.Google Scholar
Dol, H. S., Kok, J. C., and Oskam, B. 2002. Turbulence Modelling for Leading-Edge Vortex Flows. In: Proceedings of the 40th American Institute of Aeronautics and Astronautics (AIAA) Aerospace Sciences Meeting and Exhibit.CrossRefGoogle Scholar
Donzis, D. A., Yeung, P. K., and Sreenivasan, K. R. 2008. Dissipation and Enstrophy in Isotropic Turbulence: Resolution Effects and Scaling in Direct Numerical Simulations. Physics of Fluids, 20(4), 045108.CrossRefGoogle Scholar
Drikakis, D., Fureby, C., Grinstein, F. F., and Youngs, D. 2007. Simulation of Transition and Turbulence Decay in the Taylor–Green Vortex. Journal of Turbulence, 8(20).CrossRefGoogle Scholar
Eisfeld, B. 2004. Implementation of Reynolds Stress Models into the DLR-FLOWer Code. Technical report IB 124-2004/31. Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Braunschweig, Germany.Google Scholar
Eisfeld, B., and Brodersen, O. 2005. Advanced Turbulence Modelling and Stress Analysis for the DLR-F6 Configuration. In: Proceedings of the 23rd American Institute of Aeronautics and Astronautics (AIAA) Applied Aerodynamics Conference.CrossRefGoogle Scholar
Eisfeld, B., Rumsey, C., and Togiti, V. 2016. Verification and Validation of a Second-Moment-Closure Model. American Institute of Aeronautics and Astronautics (AIAA) Journal, 54(5), 1524–1542.Google Scholar
Elmiligui, A., Abdol-Hamid, K. S., Massey, S. J., and Pao, S. P. 2004. Numerical Study of Flow Past a Circular Cylinder Using RANS, Hybrid RANS/LES and PANS Formulations. In: Proceedings of the 22nd American Institute of Aeronautics and Astronautics (AIAA) Applied Aerodynamics Conference and Exhibit.CrossRefGoogle Scholar
Fage, A., and Warsap, J. H. 1930. The Effects of Turbulence and Surface Roughness on the Drag of a Circular Cylinder. Reports and Memoranda 1283. Aeronautical Research Committee, London, United Kingdom.Google Scholar
Fasel, H. F., Seidel, J., and Wernz, S. 2002. A Methodology for Simulations of Complex Turbulent Flows. Journal of Fluids Engineering, 124(4), 993–942.CrossRefGoogle Scholar
Ferrante, A., and Elghobashi, S. E. 2004. A Robust Method for Generating Inflow Conditions for Direct Simulations of Spatially-Developing Turbulent Boundary Layers. Journal of Computational Physics, 198(1), 372–387.CrossRefGoogle Scholar
Fröhlich, J., and von Terzi, D. 2008. Hybrid LES/RANS Methods for the Simulation of Turbulent Flows. Progress in Aerospace Sciences, 44(5), 349–377.CrossRefGoogle Scholar
Georgiadis, N. J., Rizzetta, D. P., and Fureby, C. 2009. Large-Eddy Simulation: Current Capabilities, Recommended Practices, and Future Research. Technical Report TM-2009-215616. National Aeronautics and Space Administration (NASA), Glenn Research Center, Cleveland, United States of America.Google Scholar
Gerich, D., and Eckelmann, H. 1982. Influence of End Plates and Free Ends on the Shedding Frequency of Circular Cylinders. Journal of Fluid Mechanics, 122, 109–121.CrossRefGoogle Scholar
Germano, M. 1992. The Filtering Approach. Journal of Fluid Mechanics, 238, 325–36.CrossRefGoogle Scholar
Germano, M. 1999. From RANS to DNS: Towards a Bridging Model. In: Direct and Large-Eddy Simulation III, Voke, P. R., Sandham, N. D., and Kleiser, L. (eds). ERCOFTAC series, vol. 7. Springer.Google Scholar
Ghosal, S., and Moin, P. 1995. The Basic Equations for the Large Eddy Simulation of Turbulent Flows in Complex Geometries. Journal of Computational Physics, 118(1), 24–37.CrossRefGoogle Scholar
Girimaji, S., Haase, W., Peng, S.-H., and Schwamborn, D. (eds). 2015. Progress in Hybrid RANS-LES Modelling. Papers Contributed to the 5th Symposium on Hybrid RANS-LES Methods, 19–21 March 2014, College Station, A&M University, Texas, United States of America. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol. 130. Switzerland: Springer.Google Scholar
Girimaji, S. S. 2005. Partially-Averaged Navier–Stokes Model for Turbulence: A Reynolds-Averaged Navier–Stokes to Direct Numerical Simulation Bridging Method. Journal of Applied Mechanics, 73(3), 413–421.Google Scholar
Girimaji, S. S., and Abdol-Hamid, K. S. 2005 (10–13 January). Partially-Averaged Navier Stokes Model for Turbulence: Implementation and Validation. In: Proceedings of the 43rd American Institute of Aeronautics and Astronautics (AIAA) Aerospace Sciences Meeting and Exhibit.CrossRefGoogle Scholar
Girimaji, S. S., and Wallin, S. 2013. Closure Modeling in Bridging Regions of Variable-Resolution (VR) Turbulence Computations. Journal of Turbulence, 14(1), 72–98.CrossRefGoogle Scholar
Girimaji, S. S., Jeong, E., and Srinivasan, R. 2006. Partially Averaged Navier–Stokes Method for Turbulence: Fixed Point Analysis and Comparison with Unsteady Partially Averaged Navier–Stokes. ASME Journal of Applied Mechanics, 73(3), 422–429.Google Scholar
Goc, K., Lehmkuhl, O., Park, G., Bose, S., and Moin, P. 2021. Large Eddy Simulation of Aircraft at Affordable Cost: A Milestone in Computational Fluid Dynamics. Flow, 1, E14.CrossRefGoogle Scholar
Grinstein, F. F., Margolin, L. G., and Rider, W. J. 2010. Implicit Large Eddy Simulation: Computing Turbulent Flow Dynamics. 2nd ed. Cambridge University Press.Google Scholar
Grinstein, F. F., Saenz, J. A., Rauenzahn, R. M., Germano, M., and Israel, D. M. 2020. Dynamic Bridging Modeling for Coarse Grained Simulations of Shock Driven Turbulent Mixing. Physics of Fluids, 199, 104430.Google Scholar
Gritskevich, M. S., Garbaruk, A. V., Schütze, J., and Menter, F. R. 2012. Development of DDES and IDDES Formulations for the k – ω Shear Stress Transport Model. Flow, Turbulence and Combustion, 88(3), 431–449.CrossRefGoogle Scholar
Güven, O., Farrel, C., and Patel, V. C. 1980. Surface-Roughness Effects on the Mean Flow Past Circular Cylinders. Journal of Fluid Mechanics, 98(4), 673–701.CrossRefGoogle Scholar
Haase, W., Braza, M., and Revell, A. (eds). 2009. DESider – An European Effort on Hybrid RANS-LES Modelling. Results of the European-Union Funded Project, 2004–2007. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol. 103. Springer-Verlag.Google Scholar
Haller, G. 2005. An Objective Definition of a Vortex. Journal of Fluid Mechanics, 525, 1–26.CrossRefGoogle Scholar
Hamba, F. 2011. Analysis of Filtered Navier–Stokes Equation for Hybrid RANS/LES Simulation. Physics of Fluids, 23(015108).CrossRefGoogle Scholar
Hanjalić, K. 2005. Will RANS Survive LES? A View of Perspectives. Journal of Fluids Engineering, 127(5), 831–839.CrossRefGoogle Scholar
Hanjalić, K., and Launder, B. 2011. Modelling Turbulence in Engineering and the Environment. Second-Moment Routes to Closure. 1st ed. Cambridge University Press.CrossRefGoogle Scholar
Heinz, S. 2020. A Review of Hybrid RANS-LES Methods for Turbulent Flows: Concepts and Applications. Progress in Aerospace Sciences, 114, 100597.CrossRefGoogle Scholar
Hussain, A. K. M. F., and Reynolds, W. C. 1970. The Mechanics of an Organized Wave in Turbulent Shear Flow. Journal of Fluid Mechanics, 41(2), 241–258.CrossRefGoogle Scholar
Jasak, H. 1996. Error Analysis and Estimation in the Finite Volume Method with Applications to Fluid Flows. Ph.D. thesis, Imperial College of Science, Technology and Medicine, London, United Kingdom.Google Scholar
Jeong, J., and Hussain, F. 1995. On the Identification of a Vortex. Journal of Fluid Mechanics, 285, 69–94.CrossRefGoogle Scholar
Juretic, F. 2004. Error Analysis in Finite Volume CFD. Ph.D. thesis, Imperial College of Science, Technology and Medicine, London, United Kingdom.Google Scholar
Keating, A., Piomelli, U., Balaras, E., and Kaltenbach, H.-J. 2004. A Priori and A Posteriori Tests of Inflow Conditions for Large-Eddy Simulation. Physics of Fluids, 16(12), 4696–4712.CrossRefGoogle Scholar
Kida, S., and Takaoka, M. 1994. Vortex Reconnection. Annual Review of Fluid Mechanics, 26, 169–177.CrossRefGoogle Scholar
Kim, Y., Castro, I. P., and Xie, Z.-T. 2013. Divergence-Free Turbulence Inflow Conditions for Large-Eddy Simulations with Incompressible Flow Solvers. Computers & Fluids, 84, 56–68.CrossRefGoogle Scholar
Kok, J. C. 2017. A Stochastic Backscatter Model for Grey-Area Mitigation in Detached Eddy Simulations. Flow, Turbulence and Combustion, 99(1), 119–150.Google Scholar
Kok, J. C., Dol, H. S., Oskam, B., and van der Ven, H. 2004. Extra-Large Eddy Simulation of Massively Separated Flows. In: Proceedings of the 42nd American Institute of Aeronautics and Astronautics (AIAA) Aerospace Sciences Meeting and Exhibit.CrossRefGoogle Scholar
Koopmann, G. H. 1967. The Vortex Wakes of Vibrating Cylinders at Low Reynolds Numbers. Journal of Fluid Mechanics, 28(3), 501–512.CrossRefGoogle Scholar
Lakshmipathy, S., and Girimaji, S. S. 2006. Partially-Averaged Navier–Stokes Method for Turbulent Flows: k – ω Model Implementation. In: Proceedings of the 44th American Institute of Aeronautics and Astronautics (AIAA) Aerospace Sciences Meeting and Exhibit.CrossRefGoogle Scholar
Laporte, F., and Leweke, T. 2002. Elliptic Instability of Counter-Rotating Vortices: Experiment and Direct Numerical Simulation. American Institute of Aeronautics and Astronautics (AIAA) Journal, 40(12), 2483–2494.Google Scholar
Lawson, T. V., Anthony, K. C., Cockrell, D. J., Davenport, A. G., Flint, A. R., Freeston, D. H., Harris, R. I., Lyons, R. A., Mayne, J. R., Melling, R. J., Mowatt, G. A., Pedersen, J. R. C., Richards, D. J. W., Scruton, C., and Whitbread, R. E. 1986. Mean Forces, Pressures and Flow Field Velocities for Circular Cylindrical Structures: Single Cylinder with Two-Dimensional Flow. Technical Report ESDU 80025. Engineering Sciences Data Unit (ESDU), London, UK.Google Scholar
Leweke, T., and Williamson, C. 1998. Cooperative Elliptic Instability of a Vortex Pair. Journal of Fluid Mechanics, 360, 85–119.CrossRefGoogle Scholar
Leweke, T., Le, Dizés, S., and Williamson, C. H. K. 2016. Dynamics and Instabilities of Vortex Pairs. Annual Review of Fluid Mechanics, 48(1), 507–541.CrossRefGoogle Scholar
Livescu, D., Wei, T., and Brady, P. T. 2021. Rayleigh–Taylor Instability with Gravity Reversal. Physica D, 417, 132832.CrossRefGoogle Scholar
Lund, T. S., Wu, X., and Squires, K. D. 1998. Generation of Turbulent Inflow Data for Spatially-Developing Boundary Layer Simulations. Journal of Computational Physics, 140(2), 233–258.CrossRefGoogle Scholar
Mansoor, M. M., Dalton, S. M., Martinez, A. A., Desjardins, T., Charonko, J. J., and Prestridge, K. P. 2020. The Effect of Initial Conditions on Mixing Transition of the Richtmyer–Meshkov Instability. Journal of Fluid Mechanics, 904, A3.CrossRefGoogle Scholar
Menter, F., Hüppe, A., Matyushenko, A., and Kolmogorov, D. 2021. An Overview of Hybrid RANS–LES Models Developed for Industrial CFD. Applied Sciences, 11, 2459.CrossRefGoogle Scholar
Menter, F. R. 2016. Stress-Blended Eddy Simulation (SBES) – A New Paradigm in Hybrid RANS-LES Modeling. In: Proceedings of the 6th Hybrid RANS-LES Methods (HRLM) Symposium.Google Scholar
Menter, F. R., and Egorov, Y. 2010. The Scale-Adaptive Simulation Method for Unsteady Turbulent Flow Predictions. Part 1: Theory and Model Description. Flow, Turbulence and Combustion, 85(1), 113–138.CrossRefGoogle Scholar
Menter, F. R., and Kuntz, M. 2004. Adaptation of Eddy–Viscosity Turbulence Models to Unsteady Separated Flow Behind Vehicles. In: Symposium on the Aerodynamics of Heavy Vehicles: Trucks, Buses and Trains, McCallen, R., Browand, F., and Ross, J. (eds). Lecture Notes in Applied and Computational Mechanics, vol. 19. Springer.Google Scholar
Menter, F. R., Kuntz, M., and Bender, R. 2003a. A Scale-Adaptive Simulation Model for Turbulent Flow Predictions. In: Proceedings of the 41st American Institute of Aeronautics and Astronautics (AIAA) Aerospace Science Meeting and Exhibit.CrossRefGoogle Scholar
Menter, F. R., Kuntz, M., and Langtry, R. 2003b. Ten Years of Industrial Experience with the SST Turbulence Model. Pages 625–632 of: Proceedings of the 4th Turbulence, Heat and Mass Transfer.Google Scholar
Menter, F. R., Schütze, J., and Kurbatskii, K. A. 2011 (27–30 June). Scale-Resolving Simulation Techniques in Industrial CFD. In: Proceedings of the 6th American Institute of Aeronautics and Astronautics (AIAA) Theoretical Fluid Mechanics Conference.CrossRefGoogle Scholar
Mocket, C., Haase, W., and Schwamborn, D. (eds). 2018. Go4Hybrid: Grey Area Mitigation for Hybrid RANS-LES Methods. Results of the 7th Framework Research Project Go4Hybrid, Funded by the European Union, 2013–2015. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol. 134. Springer-Verlag.Google Scholar
Nelson, N. J., and Grinstein, F. F. 2015. Effects of Initial Condition Spectral Content on Shock-Driven Turbulent Mixing. Physical Review E, 92, 013014.CrossRefGoogle ScholarPubMed
Norberg, C. 1994. An Experimental Investigation of the Flow around a Circular Cylinder: Influence of Aspect Ratio. Journal of Fluid Mechanics, 258, 287–316.CrossRefGoogle Scholar
Norberg, C. 2002 (17–20 December). Pressure Distributions around a Circular Cylinder in Cross-Flow. In: Proceedings of the Symposium on Bluff Body Wakes and Vortex-Induced Vibrations – BBVIV-3.Google Scholar
Norberg, C. 2003. Fluctuating Lift on a Circular Cylinder: Review and New Measurements. Journal of Fluids and Structures, 17(1), 57–96.CrossRefGoogle Scholar
Norberg, C., and Sundén, B. 1987. Turbulence and Reynolds Number Effects on the Flow and Fluid Forces on a Single Cylinder in Cross Flow. Journal of Fluids and Structures, 1(3), 337–357.CrossRefGoogle Scholar
Oberkampf, W. L., and Roy, C. J. 2010. Verification and Validation in Scientific Computing. 1st ed. Cambridge University Press.CrossRefGoogle Scholar
Parnaudeau, P., Carlier, J., Heitz, D., and Lamballais, E. 2008. Experimental and Numerical Studies of the Flow over a Circular Cylinder at Reynolds Number 3900. Physics of Fluids, 20(085101,).CrossRefGoogle Scholar
Pereira, F. S. 2012 (October). Verification of ReFRESCO with the Method of Manufactured Solutions. M.Phil. thesis, Instituto Superior Técnico, Lisbon, Portugal.Google Scholar
Pereira, F. S., Vaz, G., and Eça, L. 2014 (28–30 September). On the Use of Hybrid Turbulence Models. In: 17th Numerical Towing Tank Symposium (NuTTS 2014).Google Scholar
Pereira, F. S., Vaz, G., and Eça, L. 2015 (15–18 September). An Assessment of Scale-Resolving Simulation Models for the Flow around a Circular Cylinder. In: Proceedings of the Eighth International Symposium On Turbulence Heat and Mass Transfer.CrossRefGoogle Scholar
Pereira, F. S., Vaz, G., Eça, L., and Girimaji, S. S. 2018a. Simulation of the Flow around a Circular Cylinder at Re= 3900 with Partially-Averaged Navier–Stokes Equations. International Journal of Heat and Fluid Flow, 69, 234–246.CrossRefGoogle Scholar
Pereira, F. S., Vaz, G., and Eça, L. 2019a. Evaluation of RANS and SRS Methods for Simulation of the Flow around a Circular Cylinder in the Sub-Critical Regime. Ocean Engineering, 186(106067).CrossRefGoogle Scholar
Pereira, F. S., Eça, L., and Vaz, G. 2019b. Investigating the Effect of the Closure in Partially-Averaged Navier–Stokes Equations. Journal of Fluids Engineering, 141(121402).CrossRefGoogle Scholar
Pereira, F. S., Grinstein, F. F., Israel, D. M., Rauenzahn, R., and Girimaji, S. S. 2021a. Modeling and Simulation of Transitional Rayleigh–Taylor Flow with Partially-Averaged Navier–Stokes Equations. Physics of Fluids, 33, 115118.CrossRefGoogle Scholar
Pereira, F. S., Grinstein, F. F., Israel, D. M., Rauenzahn, R., and Girimaji, S. S. 2021b. Modeling and Simulation of Transitional Taylor–Green Vortex Flow with Partially Averaged Navier–Stokes Equations. Physical Review Fluids, 6, 054611.Google Scholar
Pereira, F. S., Grinstein, F. F., Israel, D. M., Rauenzahn, R., and Girimaji, S. S. 2021c. Partially Averaged Navier–Stokes Equations Closure Modeling for Variable-Density Turbulent Flow. Physical Review Fluids, 6, 084602.Google Scholar
Pereira, F. S., Eça, L., Vaz, G., and Girimaji, S. S. 2021d. Toward Predictive RANS and SRS Computations of Turbulent External Flows of Practical Interest. Archives of Computational Methods in Engineering, 28, 3953–4029.CrossRefGoogle Scholar
Pereira, F. S., Grinstein, F. F., Israel, D. M., and Eça, L. 2022. Verification and Validation: The Path to Predictive Scale-Resolving Simulations of Turbulence. ASME Journal of Verification, Validation, and Uncertainty Quantification, 7(2), 021003.Google Scholar
Pereira, F. S., Eça, L., Vaz, G., and Girimaji, S. S. 2018b. Challenges in Scale-Resolving Simulations of Turbulent Wake Flows with Coherent Structures. Journal of Computational Physics, 363, 98–115.CrossRefGoogle Scholar
Pereira, F. S., Eça, L., Vaz, G., and Girimaji, S. S. 2019c. On the Simulation of the Flow around a Circular Cylinder at Re = 140,000. International Journal of Heat and Fluid Flow, 76, 40–56.CrossRefGoogle Scholar
Pereira, F. S., Barthel, A., Bachman, S., Maltrud, M., Asay-Davis, A., Roberts, A., and van Roekel, L. 2024. Influence of Regionally Mesh Refinement and Enhanced Physics on Ocean Simulations Fidelity. Journal of Advances in Modeling Earth Systems, (In elaboration).Google Scholar
Piomelli, U., and Balaras, E. 2002. Wall-Layer Models for Large-Eddy Simulations. Annual Review of Fluid Mechanics, 34(1), 349–374.CrossRefGoogle Scholar
Piomelli, U., Balaras, E., Pasinato, H., Squires, K. D., and Spalart, P. R. 2003. The Inner-Outer Layer Interface in Large-Eddy Simulations with Wall-Layer Models. International Journal of Heat and Fluid Flow, 24(4), 538–550.CrossRefGoogle Scholar
Piquet, J. 1999. Turbulent Flows – Models and Physics. 2nd ed. Berlin, Germany: Springer-Verlag.CrossRefGoogle Scholar
Pope, S. B. 1999. Modeling Complex Turbulent Flows. Pages 53–67 of: A Perspective on Turbulence Modeling. ICASE LaRC Interdisciplinary Series in Science and Engineering, vol. 7. Springer.Google Scholar
Pope, S. B. 2000. Turbulent Flows. Cambridge University Press.Google Scholar
Prasad, A., and Williamson, C. H. K. 1997a. The Instability of the Shear Layer Separating from a Bluff Body. Journal of Fluid Mechanics, 333, 375–402.CrossRefGoogle Scholar
Prasad, A., and Williamson, C. H. K. 1997b. Three-Dimensional Effects in Turbulent Bluff-Body Wakes. Journal of Fluid Mechanics, 343, 235–265.CrossRefGoogle Scholar
Rajagopalan, S., and Antonia, R. A. 2005. Flow around a Circular Cylinder – Structure of the Near Wake Shear Layer. Experiments in Fluids, 38(4), 393–402.CrossRefGoogle Scholar
Rayleigh, L. 1882. Investigation of the Character of the Equilibrium of an Incompressible Heavy Fluid of Variable Density. Proceedings of the London Mathematical Society, 14, 170–177.Google Scholar
Roache, P. J. 1998. Verification and Validation in Computational Science and Engineering. 1st ed. Hermosa Publishers.Google Scholar
Rotta, J. C. 1972. Turbulente Stromungen. Teubner Verlag.CrossRefGoogle Scholar
Sadeh, W. Z., and Saharon, D. B. 1982 (November). Turbulence Effect on Crossflow around a Circular Cylinder at Subcritical Reynolds Numbers. NASA Contractor Report 3622. National Aeronautics and Space Administration (NASA), Lewis Research Center, Cleveland, USA.Google Scholar
Saenz, J. A., Aslangil, D., and Livescu, D. 2021. Filtering, Averaging, and Scale Dependency in Homogeneous Variable Density Turbulence. Physics of Fluids, 33, 025115.CrossRefGoogle Scholar
Sagaut, P., Deck, S., and Terracol, M. 2006. Multiscale and Multiresolution Approaches in Turbulence. Imperial College Press.CrossRefGoogle Scholar
Schiestel, R. 1987. Multiple-Time-Scale Modeling of Turbulent Flows in One-Point Closures. Physics of Fluids, 30(3), 722–731.Google Scholar
Schiestel, R. 2008. Modeling and Simulation of Turbulent Flows. 1st ed. ISTE/Wiley.CrossRefGoogle Scholar
Schiestel, R., and Chaouat, B. 2022. Turbulence Modeling and Simulation Advances in CFD during the Past 50 Years. Comptes Rendus: Mécanique, 1–29.Google Scholar
Schiestel, R., and Dejoan, A. 2005. Towards a New Partially Integrated Transport Model for Coarse Grid and Unsteady Turbulent Flow Simulations. Theoretical and Computational Fluid Dynamics, 18(6), 443–468.CrossRefGoogle Scholar
Sharp, D. H. 1987. An Overview of Rayleigh–Taylor Instability. Physica D: Nonlinear Phenomena, 12(1–3), 3–18.Google Scholar
Shur, M. L., Spalart, P. R., Strelets, M. Kh., and Travin, A. K. 2008. A Hybrid RANS-LES Approach with Delayed-DES and Wall-Modelled LES Capabilities. International Journal of Heat and Fluid Flow, 29(6), 1638–1649.CrossRefGoogle Scholar
Silva, T. S., Zecchetto, M., and da Silva, C. B. 2018. The Scaling of the Turbulent/Non-Turbulent Interface at High Reynolds Numbers. Journal of Fluid Mechanics, 843, 156–179.CrossRefGoogle Scholar
Slotnick, J. P., Khodadoust, A., Alonso, J., Darmofal, D., Lurie, W. Gropp E., and Mavriplis, D. J. 2014. CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences. Techreport NASA/CR–2014-218178. National Aeronautics and Space Administration (NASA), Langley Research Center, Hampton, Virginia, USA.Google Scholar
Smagorinsky, J. 1963. General Circulation Experiments with the Primitive Equation I: The Basic Experiment. Monthly Weather Review, 91, 99–164.2.3.CO;2>CrossRefGoogle Scholar
Smirnov, A., Shi, S., and Celik, I. 2001. Random Flow Generation Technique for Large Eddy Simulations and Particle Dynamics Modeling. Journal of Fluids Engineering, 123(2), 359–371.CrossRefGoogle Scholar
Son, J. S., and Hanratty, T. J. 1969. Velocity Gradients at the Wall for Flow around a Cylinder at Reynolds Numbers from 5 × 103 to 105. Journal of Fluid Mechanics, 35(2), 353–368.CrossRefGoogle Scholar
Spalart, P. R. 2000. Strategies for Turbulence Modelling and Simulations. International Journal of Heat and Fluid Flow, 21(3), 252–263.CrossRefGoogle Scholar
Spalart, P. R. 2001. Young-Person’s Guide to Detached-Eddy Simulation Grids. Technical Report CR-2001-211032. National Aeronautics and Space Administration (NASA), Langley Research Center, Hampton, USA.Google Scholar
Spalart, P. R., and Venkatakrishnan, V. 2016. On the Role and Challenges of CFD in the Aerospace Industry. The Aeronautical Journal, 120(1223), 209–232.CrossRefGoogle Scholar
Spalart, P. R., Jou, W.-H., Strelets, M., and Allmaras, S. R. 1997. Comments on the Feasibility of LES for Wings, and on a Hybrid RANS/LES Approach. In: Proceedings of the 1st Air Force Office of Scientific Research (AFOSR) International Conference on DNS/LES.Google Scholar
Spalart, P. R., Deck, S., Shur, M. L., Squires, K. D., Strelets, M. Kh., and Travin, A. 2006. A New Version of Detached-Eddy Simulation, Resistant to Ambiguous Grid Densities. Theoretical and Computational Fluid Dynamics, 20, 181–195.CrossRefGoogle Scholar
Speziale, C. G. 1997. Computing Non-Equilibrium Turbulent Flows with Time-Dependent RANS and VLES. In: 15th International Conference on Numerical Methods in Fluid Dynamics, Kutler, P., and Chattot, J. Flores, J. J. (eds). Lecture Notes in Physics, vol. 490. Springer.Google Scholar
Speziale, C. G. 1998. Turbulence Modeling for Time-Dependent RANS and VLES: A Review. AIAA Journal, 36(2), 173–184.CrossRefGoogle Scholar
Szepessy, S., and Bearman, P. W. 1992. Aspect Ratio and End Plate Effects on Vortex Shedding from a Circular Cylinder. Journal of Fluid Mechanics, 234, 191–217.CrossRefGoogle Scholar
Tabor, G. R., and Baba-Ahmadi, M. H. 2010. Inlet Conditions for Large Eddy Simulation: A Review. Computers & Fluids, 39(4), 553–567.CrossRefGoogle Scholar
Taylor, G. 1950. The Instability of Liquid Surfaces When Accelerated in a Direction Perpendicular to Their Planes. Proceeding of the Royal Society A, 201(1065), 192–196.Google Scholar
Taylor, G. I., and Green, A. E. 1937. Mechanism of the Production of Small Eddies from Large Ones. Proceedings of the Royal Society A, 158.Google Scholar
Tennekes, H., and Lumley, J. 1999. First Course of Turbulence. 7th ed. MIT Press.Google Scholar
Thornber, B., Drikakis, D., Youngs, D. L., and Williams, R. J. R. 2010. The Influence of Initial Conditions on Turbulent Mixing due to Richtmyer–Meshkov Instability. Journal of Fluid Mechanics, 654, 99–139.CrossRefGoogle Scholar
Thorpe, S. A. 2007. An Introduction to Ocean Turbulence. Cambridge University Press.CrossRefGoogle Scholar
Tokumaru, P. T., and Dimotakis, P. E. 1991. Rotary Oscillation Control of a Cylinder Wake. Journal of Fluid Mechanics, 224, 77–90.CrossRefGoogle Scholar
Trucano, T. G., Pilch, M., and Oberkampf, W. L. 2002 (March). General Concepts for Experimental Validation of ASCI Code Applications. Technical Report SAND2002-0341. Sandia National Laboratories, Albuquerque, USA.Google Scholar
Valente, P. C., da Silva, C. B., and Pinho, P. T. 2014. The Effect of Viscoelasticity on the Turbulent Kinetic Energy Cascade. Journal of Fluid Mechanics, 760, 39–62.CrossRefGoogle Scholar
Virk, D., Hussain, F., and Kerr, R. M. 1995. Compressible Vortex Reconnection. Journal of Fluid Mechanics, 304, 47–86.CrossRefGoogle Scholar
West, G. S., and Apelt, C. J. 1982. The Effects of Tunnel Blockage and Aspect Ratio on the Mean Flow Past a Circular Cylinder with Reynolds Numbers between 104 and 105. Journal of Fluid Mechanics, 114, 361–377.CrossRefGoogle Scholar
Wilcox, D. C. 1988. Reassessment of the Scale-Determining Equation for Advanced Turbulence Models. American Institute of Aeronautics and Astronautics Journal, 26(11), 1299–1310.CrossRefGoogle Scholar
Wilcox, D. C. 2006. Turbulence Modeling for CFD. 3rd ed. La Cañada, USA: DCW Industries.Google Scholar
Williamson, C. H. K. 1996. Vortex Dynamics in the Cylinder Wake. Annual Review of Fluid Mechanics, 28, 477–539.Google Scholar
Yao, J., and Hussain, F. 2020. Separation Scaling for Viscous Vortex Reconnection. Journal of Fluid Mechanics Rapids, 900(R4).Google Scholar
Zdravkovich, M. M. 1997. Flow Around Circular Cylinders. Volume 1: Fundamentals. First ed. Oxford Science Publications.Google Scholar
Zhou, Y. 2017a. Rayleigh–Taylor and Richtmyer–Meshkov Instability Induced Flow, Turbulence, and Mixing. I. Physics Reports, 720–722, 1–136.Google Scholar
Zhou, Y. 2017b. Rayleigh–Taylor and Richtmyer–Meshkov Instability Induced Flow, Turbulence, and Mixing. II. Physics Reports, 723–725, 1–160.Google Scholar

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