NOISEtte CFD&CAA Supercomputer Code for Research and Applications

Ilya V. Abalakin; Pavel A.  Bakhvalov; Vladimir G. Bobkov; Alexey P. Duben; Andrey V. Gorobets; Tatiana K. Kozubskaya; Pavel V. Rodionov; Natalia S.  Zhdanova

doi:10.14529/jsfi240206

Authors

Ilya V. Abalakin Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0002-4296-6802
Pavel A. Bakhvalov Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0003-3416-8277
Vladimir G. Bobkov Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0001-7020-1586
Alexey P. Duben Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0002-2280-4400
Andrey V. Gorobets Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0001-8308-2440
Tatiana K. Kozubskaya Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0002-9529-4093
Pavel V. Rodionov Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0001-7747-9708
Natalia S. Zhdanova Keldysh Institute of Applied Mathematics, RAS, Moscow, Russian Federation https://orcid.org/0000-0001-8712-2817

DOI:

https://doi.org/10.14529/jsfi240206

Keywords:

CFD code, computational fluid dynamics, aeroacoustics, turbulent flows, scale-resolving simulation, hybrid RANS-LES approach, mixed-element mesh, higher-accuracy method, CPU GPU, MPI OpenMP OpenCL

Abstract

The paper presents an overview of the CFD/CAA code NOISEtte. The code development began in the 2000s. At first it was a research code intended for elaboration of new methods and techniques in CFD and CAA. Nowadays NOISEtte is actively used as a means for solving numerically various applied problems in aviation industry, turbomachinery, helicopter manufacturing, and space rocket engineering. The code operates on mixed-element unstructured meshes, its numerical algorithm is built on higher-accuracy finite-volume methods using quasi-one-dimensional edge-based reconstruction of flow variables. It is well suited for simulating complex turbulent flows, and especially for high-fidelity scale-resolving simulation of non-stationary turbulent flows using novel RANS-LES methods. A remarkable feature of NOISEtte is its original parallel model, which allows computing with high efficiency on modern supercomputers with arbitrary architectures including CPU cores and GPU accelerators.

References

th AIAA CFD High Lift Prediction Workshop – Test Cases, https://hiliftpw.larc.nasa.gov/Workshop4/testcases.html

Abalakin, I., Bakhvalov, P., Kozubskaya, T.: Edge-based reconstruction schemes for unstructured tetrahedral meshes. International Journal for Numerical Methods in Fluids 81, 331–356 (2016). https://doi.org/10.1002/fld.4187

Abalakin, I., Kozubskaya, T., Vasilyev, O., Zhdanova, N.: Implementation of charcteristic based volume penalization method on unstructured meshes (01 2021). https://doi.org/10.23967/wccm-eccomas.2020.176

Abalakin, I.V., Anikin, V.A., Bakhvalov, P.A., et al.: Numerical investigation of the aerodynamic and acoustical properties of a shrouded rotor. Fluid Dyn. 51(3), 419–433 (Nov 2016). https://doi.org/10.1134/S0015462816030145

Abalakin, I.V., Bakhvalov, P.A., Bobkov, V.G., Gorobets, A.V.: Parallel algorithm for flow simulation in rotor–stator systems based on edge-based schemes. Math. Models Comput. Simul. 13, 172–180 (2021). https://doi.org/10.1134/S2070048221010026

Abalakin, I.V., Bobkov, V.G., Kozubskaya, T.K., et al.: Numerical simulation of flow around rigid rotor in forward flight. Fluid Dynamics 55(4), 534–544 (Jul 2020). https://doi.org/10.1134/s0015462820040011

Abalakin, I.V., Vasilyev, O.V., Zhdanova, N.S., Kozubskaya, T.K.: Characteristic based volume penalization method for numerical simulation of compressible flows on unstructured meshes. Comput. Math. and Math. Phys. 61(8), 1315–1329 (2021). https://doi.org/10.1134/S0965542521080029

Abalakin, I.V., Zhdanova, N.S., Kozubskaya, T.K.: Immersed boundary method for numerical simulation of inviscid compressible flow. Comput. Math. and Math. Phys. 58(9), 1411–1419 (2018). https://doi.org/10.1134/S0965542518090026

Aksenov, A., Dyadkin, A., Pokhilko, V.: Overcoming of barrier between CAD and CFD by modified finite volume method. In: ASME Pressure Vessels and Piping Division Conference Proc. vol. 377-1. ASME PVP, San Diego (1998)

Angot, P., Bruneau, C.H., Fabrie, P.: A penalization method to take into account obstacles in viscous flows. Numerische Mathematik 81, 497–520 (1999). https://doi.org/10.1007/s002110050401

Ansys inc.: ANSYS, https://www.ansys.com

Bakhvalov, P.A., Bobkov, V.G., Kozubskaya, T.K.: Technology to predict acoustic farfield disturbances in the case of calculations in a rotating reference frame. Math. Models and Comp. Simul. 9, 717–727 (2017). https://doi.org/https://doi.org/10.1134/S2070048217060035

Bakhvalov, P.A., Kozubskaya, T.K.: EBR-WENO scheme for solving gas dynamics problems with discontinuities on unstructured meshes. Computers and Fluids 157, 312–324 (2017). https://doi.org/10.1016/j.compfluid.2017.09.004

Bakhvalov, P.A., Kozubskaya, T.K., Rodionov, P.V.: EBR schemes with curvilinear reconstructions for hybrid meshes. Computers and Fluids 239 (2022). https://doi.org/10.1016/j.compfluid.2022.105352

Bakhvalov, P.A., Surnachev, M.D.: Method of averaged element splittings for diffusion terms discretization in vertex-centered framework. Journal of Computational Physics 450 (2022). https://doi.org/10.1016/j.jcp.2021.110819

Bakhvalov, P.A., Vershkov, V.A.: Edge-based schemes on moving hybrid meshes in the NOISEtte code. Keldysh Inst. Appl. Math. Preprint 127 (2018). https://doi.org/10.20948/prepr-2018-127

Bobkov, V.G., Vershkov, V.A., Kozubskaya, T.K., Tsvetkova, V.O.: Deformation technique of unstructured mesh deformation to find the aerodynamic characteristics of bodies at small displacements. Mathematical Models and Computer Simulations 13(6), 986–1001 (Nov 2021). https://doi.org/10.1134/s2070048221060028

Bobkov, V., Gorobets, A., Kozubskaya, T., Zhang, X., Zhong, S.: Supercomputer simulation of turbulent flow around isolated UAV rotor and associated acoustic fields. Communications in Computer and Information Science 1510, 256–269 (2021). https://doi.org/10.1007/978-3-030-92864-3_20

Brentner, K.S., Farassat, F.: Modeling aerodynamically generated sound of helicopter rotors. Progress in Aerospace Sciences 39(2), 83–120 (2003). https://doi.org/10.1016/S0376-0421(02)00068-4

Brown-Dymkoski, E., Kasimov, N., Vasilyev, O.V.: A characteristic based volume penalization method for general evolution problems applied to compressible viscous flows. J. Comp. Phys. 262, 344–357 (2014). https://doi.org/10.1063/1.4825260

Caradonna, F.X., Tung, C.Y.: Experimental and analytical studies of a model helicopter rotor in hover (1980), https://api.semanticscholar.org/CorpusID:106679612

Dankov, B.N., Duben, A.P., Kozubskaya, T.K.: Analysis of Self-Oscillation Processes in a Cavity with a Flow of OpenType on the Basis of the Data of Vortex-Resolving Calculations. Fluid Dynamics 58(4), 659–669 (Aug 2023). https://doi.org/10.1134/S0015462823600517

Deck, S., Renard, N.: Towards an enhanced protection of attached boundary layers in hybrid RANS/LES methods. Journal of Computational Physics 400, 108970 (Jan 2020). https://doi.org/10.1016/j.jcp.2019.108970

Denton, J.D.: An improved time-marching method for turbomachinery flow calculation. Journal of Engineering for Power 105(3), 514–521 (Jul 1983). https://doi.org/10.1115/1.3227444

Duben, A.P., Abalakin, I.V., Tsvetkova, V.O.: On boundary conditions on solid walls in viscous flow problems. Math. Models and Comput. Simul. 13(4), 591–603 (2021). https://doi.org/10.1134/S2070048221040128

Duben, A., Gorobets, A., Soukov, S., et al.: Supercomputer Simulations of Turbomachinery Problems with Higher Accuracy on Unstructured Meshes, pp. 356–367. Springer International Publishing (2022). https://doi.org/10.1007/978-3-031-22941-1_26

Duben, A., Kozubskaya, T., Bosnyakov, S.: Two Cases Calling for Scale-Resolving Simulation, pp. 77–87. Springer International Publishing (2022). https://doi.org/10.1007/978-3-031-12019-0_6

Duben, A.P., Kozubskaya, T.K.: Evaluation of Quasi-One-Dimensional Unstructured Method for Jet Noise Prediction. AIAA Journal 57(12), 5142–5155 (dec 2019). https://doi.org/10.2514/1.j058162

Duben, A.P., Ruano, J., Gorobets, A.V., et al.: Evaluation of enhanced gray area mitigation approaches based on jet aeroacoustics. AIAA Journal 61(2), 612–625 (Feb 2023). https://doi.org/10.2514/1.j062116

Evans, A., Lacy, D., Smith, I., Rivers, M.: Test Summary of the NASA High-Lift Common Research Model Half-Span at QinetiQ 5-Metre Pressurized Low-Speed Wind Tunnel. In: AIAA Paper 2020-2770. American Institute of Aeronautics and Astronautics Inc, AIAA (2020). https://doi.org/10.2514/6.2020-2770

Farassat, F.: Linear acoustic formulas for calculation of rotating blade noise. AIAA Journal 19(9), 1122–1130 (1981). https://doi.org/10.2514/3.60051

Ferris, R., Sacks, M., Cerizza, D., et al.: Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 1-Aerodynamic Simulations. AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 (2021). https://doi.org/10.2514/6.2021-2195

Ffowcs Williams, J., Hawkings, D.: Sound generated by turbulence and surfaces in unsteady motion. Philosophical Transactions of the Royal Society A. Mathematical, Physical and Engineering Sciences 264, 321–342 (1969). https://doi.org/10.1098/rsta.1969.0031

Filimonov, S.A., Gavrilov, A., Dekterev, A.A., Litvintsev, K.Y.: Mathematical modeling of the interaction of a thermal convective flow and a moving body. Computational Continuum Mechanics 16(1), 89–100 (Apr 2023). https://doi.org/10.7242/1999-6691/2023.16.1.7

FlowVision: FlowVision CFD package, https://flowvisioncfd.com

FSUE RFNC - VNIIEF: LOGOS CFD package, https://logos-support.ru

Gorobets, A.V., Duben, A.P., Kozubskaya, T.K., Rodionov, P.V.: Approaches to the numerical simulation of the acoustic field generated by a multi-element aircraft wing in high-lift configuration. Mathematical Models and Computer Simulations 15(1), 92–108 (feb 2023). https://doi.org/10.1134/S2070048223010088

Gorobets, A., Bakhvalov, P.: Heterogeneous CPU+GPU parallelization for high-accuracy scale-resolving simulations of compressible turbulent flows on hybrid supercomputers. Computer Physics Communications 271, 108231 (Dec 2022). https://doi.org/10.1016/j.cpc.2021.108231

Gorobets, A.V., Duben, A.P.: Technology for supercomputer simulation of turbulent flows in the good new days of exascale computing. Supercomputing Frontiers and Innovations 8(4), 4–10 (Dec 2021). https://doi.org/10.14529/jsfi210401

Gorobets, A.: An Approach to the Implementation of the Multigrid Method with Full Approximation for CFD Problems. Computational Mathematics and Mathematical Physics 63, 2150–2161 (2023). https://doi.org/10.1134/S0965542523110106

Gorobets, A., Magomedov, A., Soukov, S.: Heterogeneous parallel implementation of a multigrid method with full approximation in the NOISEtte code. Matematicheskoye modelirovaniye 36, in press (2024)

Guillard, H., Viozat, C.: On the behaviour of upwind schemes in the low Mach number limit. Computers and Fluids 28, 63–86 (1999). https://doi.org/10.1016/S0045-7930(98)00017-6

Guseva, E.K., Garbaruk, A.V., Strelets, M.K.: Assessment of Delayed DES and Improved Delayed DES Combined with a Shear-Layer-Adapted Subgrid Length-Scale in Separated Flows. Flow, Turbulence and Combustion 98, 481–502 (2017). https://doi.org/10.1007/s10494-016-9769-7

Guseva, E.K., Garbaruk, A.V., Strelets, M.K.: An automatic hybrid numerical scheme for global RANS-LES approaches. Journal of Physics: Conference Series 929, 012099 (nov 2017). https://doi.org/10.1088/1742-6596/929/1/012099

INM RAS: INMOST CFD package, http://inmost.ru

Khalighi, Y., Ham, F., Nichols, J., Lele, S., Moin, P.: Unstructured large eddy simulation for prediction of noise issued from turbulent jets in various configurations. In: AIAA Paper 2011-2886 (2011). https://doi.org/10.2514/6.2011-2886

Khorrami, M.R., Shea, P.R., Winski, C.S., et al.: Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 3-Aerodynamic Validation and Noise Source Identification. AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 (2021). https://doi.org/10.2514/6.2021-2197

Kolesnik, E., Smirnov, E., Smirnovsky, A.: RANS-based numerical simulation of shock wave/turbulent boundary layer interaction induced by a blunted fin normal to a flat plate. Computers & Fluids 247, 105622 (oct 2022). https://doi.org/10.1016/j.compfluid.2022.105622

Langtry, R.B., Menter, F.R.: Correlation-based transition modeling for unstructured parallelized computational fluid dynamics codes. AIAA Journal 47(12), 2894–2906 (dec 2009). https://doi.org/10.2514/1.42362

LeVeque, R.J.: Finite Volume Methods for Hyperbolic Problems. Cambridge Texts in Applied Mathematics, Cambridge University Press (2002). https://doi.org/10.1017/CBO9780511791253

Marakueva, O., Duben, A.: Accuracy of flow simulation in a low-pressure turbine using a laminar-turbulent transition model. St. Petersburg State Polytechnical University Journal: Physics and Mathematics (2023). https://doi.org/10.18721/JPM.161.141

Menter, F.R.: Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal 32(8), 1598–1605 (Aug 1994). https://doi.org/10.2514/3.12149

Menter, F.R., Matyushenko, A., Lechner, R., et al.: An algebraic LCTM model for laminar–turbulent transition prediction. Flow, Turbulence and Combustion 109(4), 841–869 (Jul 2022). https://doi.org/10.1007/s10494-022-00336-8

Menter, F.R., Smirnov, P.E., Liu, T., Avancha, R.: A one-equation local correlation-based transition model. Flow, Turbulence and Combustion 95(4), 583–619 (jul 2015). https://doi.org/10.1007/s10494-015-9622-4

MIPT: FlowModellium CFD package, https://flowmodellium.ru

Mockett, C., Fuchs, M., Garbaruk, A., et al.: Two non-zonal approaches to accelerate RANS to LES transition of free shear layers in DES. In: Progress in Hybrid RANS-LES Modelling, pp. 187–201. Springer International Publishing (2015). https://doi.org/10.1007/978-3-319-15141-0_15

Murayama, M., Yokokawa, Y., Ura, H., et al.: Experimental study of slat noise from 30P30N three-element high-lift airfoil in JAXA kevlar-wall low-speed wind tunnel. In: AIAA Paper 2018-3460. American Institute of Aeronautics and Astronautics Inc, AIAA (2018). https://doi.org/10.2514/6.2018-3460

Nicoud, F., Toda, H.B., Cabrit, O., Bose, S., Lee, J.: Using singular values to build a subgrid-scale model for large eddy simulations. Physics of Fluids 23(8), 085106 (aug 2011). https://doi.org/10.1063/1.3623274

Nkonga, B., Guillard, H.: Godunov type method on non-structured meshes for three-dimensional moving boundary problems. Computer Methods in Applied Mechanics and Engineering 113(1-2), 183–204 (1994). https://doi.org/10.1016/0045-7825(94)90218-6

Pascioni, K.A., Cattafesta, L.N.: Aeroacoustic measurements of leading-edge slat noise. AIAA Paper 2016-2960 (2016). https://doi.org/10.2514/6.2016-2960

Pascioni, K.A., Cattafesta, L.N., Choudhari, M.M.: An experimental investigation of the 30P30N multi-element high-lift airfoil. In: AIAA Paper 2014-3062. American Institute of Aeronautics and Astronautics Inc. (2014). https://doi.org/10.2514/6.2014-3062

Pont-Vlchez, A., Duben, A., Gorobets, A., et al.: New strategies for mitigating the gray area in delayed-detached eddy simulation models. AIAA Journal 59(9), 1–15 (Sep 2021). https://doi.org/10.2514/1.j059666

Ribeiro, A.F., Ferris, R., Khorrami, M.R.: Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 2-Airframe Noise Simulations. AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 (2021). https://doi.org/10.2514/6.2021-2196

Roe, P.L.: Approximate Riemann solvers, parameter vectors and difference schemes. Journal of Computational Physics 43(2), 357–372 (1981). https://doi.org/10.1016/0021-9991(81)90128-5

Saad, Y.: Iterative methods for sparse linear systems. Society for Industrial and Applied Mathematics, Philadelphia (2003)

Shershnev, A.A., Kudryavtsev, A.N., Kashkovsky, A.V., et al.: A numerical code for a wide range of compressible flows on hybrid computational architectures. Supercomputing Frontiers and Innovations 9(4), 85–99 (Dec 2022). https://doi.org/10.14529/jsfi220408

Shur, M., Strelets, M., Travin, A., et al.: Improved Embedded Approaches. Notes on Numerical Fluid Mechanics and Multidisciplinary Design 134, 65–69 (2017). https://doi.org/10.1007/978-3-319-52995-0_3

Shur, M.L., Spalart, P.R., Strelets, M.K., Travin, A.K.: Synthetic Turbulence Generators for RANS-LES Interfaces in Zonal Simulations of Aerodynamic and Aeroacoustic Problems. Flow, Turbulence and Combustion 93, 63–92 (2014). https://doi.org/10.1007/s10494-014-9534-8

Shur, M.L., Spalart, P.R., Strelets, M.K., Travin, A.K.: An enhanced version of DES with rapid transition from RANS to LES in separated flows. Flow, Turbulence and Combustion 95(4), 709–737 (2015). https://doi.org/10.1007/s10494-015-9618-0

Shur, M., Spalart, P., Strelets, M.: Noise prediction for increasingly complex jets. Part I, Methods and tests; Part II, Applications. International Journal of Aeroacoustics 4, 213–266 (2005). https://doi.org/10.1260/1475472054771376

Smagorinsky, J.: General circulation experiments with the primitive equations. Monthly Weather Review 91(3), 99–164 (1963). https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2

Spalart, P., Allmaras, S.: A one-equation turbulence model for aerodynamic flows. In: 30th Aerospace Sciences Meeting and Exhibit. American Institute of Aeronautics and Astronautics (Jan 1992). https://doi.org/10.2514/6.1992-439

Spalart, P., Shur, M.: Variants of the Ffowcs Williams–Hawkings equation and their coupling with simulations of hot jets. International Journal of Aeroacoustics 8, 477–492 (2009). https://doi.org/10.1260/147547209788549280

Stabnikov, A., Garbaruk, A.: An algebraic transition model for simulation of turbulent flows based on a detached eddy simulation approach. St. Petersburg Polytechnic University Journal - Physics and Mathematics 15(1) (2022). https://doi.org/10.18721/JPM.15102

T1: CADFlo CFD package, https://cadflo.com

Titarev, V.A., Faranosov, G.A., Chernyshev, S.A., Batrakov, A.S.: Numerical modeling of the influence of the relative positions of a propeller and pylon on turboprop aircraft noise. Acoustical Physics 64(6), 760–773 (Nov 2018). https://doi.org/10.1134/s1063771018060118

Toro, E.: Riemann Solvers and Numerical Methods for Fluid Dynamics: A Practical Introduction. Springer (2009). https://doi.org/10.1007/b79761

Trias, F.X., Folch, D., Gorobets, A., Oliva, A.: Building proper invariants for eddy-viscosity subgrid-scale models. Physics of Fluids 27(6), 065103 (jun 2015). https://doi.org/10.1063/1.4921817

Trias, F.X., Gorobets, A., Silvis, M.H., et al.: A new subgrid characteristic length for turbulence simulations on anisotropic grids. Physics of Fluids 29(11), 115109 (2017). https://doi.org/10.1063/1.5012546

Vasilyev, O.V., Zhdanova, N.S.: Characteristic-based volume penalization-imposed wall function method for turbulent boundary layer modeling. Computational Mathematics and Mathematical Physics 63(5), 821–836 (2023). https://doi.org/10.1134/S0965542523050160

Vasilyev, O.V., Zhdanova, N.S.: Generalization of the penalized wall function method for modeling of turbulent flows with adverse pressure gradient. Computational Mathematics and Mathematical Physics 63(12), 2384–2401 (2023). https://doi.org/10.1134/S0965542523120199

Voevodin, V., Antonov, A., Nikitenko, D., et al.: Supercomputer Lomonosov-2: Large scale, deep monitoring and fine analytics for the user community. Supercomput. Front. Innov. 6(2), 4–11 (2019). https://doi.org/10.14529/jsfi190201

Zhdanova, N.S., Abalakin, I.V., Vasilyev, O.V.: Generalized Brinkman volume penalization method for compressible flows around moving obstacles. Math. Models. and Comput. Simul. 14(5), 716–726 (2022). https://doi.org/10.1134/S2070048222050180

Zhdanova, N.S., Vasilyev, O.V.: Penalized wall function method for turbulent flow modeling. Supercomputing Frontiers and Innovations 9(4), 55–68 (Dec 2022). https://doi.org/10.14529/jsfi220406