NAFEMS International Journal of CFD Case Studies

Volume 12, February 2020

ISSN 1462-236X
ISBN 978-1-910643-94-5

CFD analysis of a check valve from SAFRAN Helicopter Engines using a Lattice-Boltzmann solution

Abiza¹, David Holman¹, David Taieb², Marine Robin^2
1Dassault Systemes, Madrid, Spain, ²SAFRAN Helicopter Engines, Buchelay, France

https://doi.org/10.59972/b7bd6y72

Keywords: CFD, LBM, computational fluid dynamics, lattice boltzmann method, helicopter engines, check valve

Abstract

Unsteady Computational Fluid Dynamics (CFD) solvers with accurate turbulence modelling are increasingly required to solve real industrial problematics where most applications include complex moving parts, highly turbulent flows and transient phenomena. Most of these industrial requirements are out of reach for the traditional CFD solutions based on steady state or unsteady Reynolds-Averaged Navier-Stokes (RANS) turbulence approaches and with limited capabilities to deal with moving parts and Fluid-Structure Interaction (FSI).

XFlow is the innovative CFD software developed by Next Limit Dynamics to deal with this increasing demand on new industrial applications. XFlow features a particle-based discretization approach that uses a state-of-the-art Lattice-Boltzmann Method (LBM) to discretize the continuous Boltzmann equation, a time evolution equation for statistical probability distribution functions that describe accurately the behavior of a fluid. This proprietary particle-based kinetic solver implements at collision operator a Large Eddy Simulation (LES) turbulence model fully coupled with a generalized law of the wall (WMLES) in order to solve the transient turbulent effects usually observed on industrial applications.

The aim of the work presented in this paper is to demonstrate the capability of the XFlow approach to predict costly instability issues of the Check Valves (CV) integrated inside the fuel circuit in helicopter engines. The results of XFlow will be compared to the experimental measurements provided by SAFRAN Helicopter Engines on one of their CV designs during real working conditions.

The CV dynamics will be modelled in XFlow as a rigid body with one degree of freedom along the axis aligned with the flow direction. A spring effort is modelled with a pre-load force and a stiffness. With these two parameters, XFlow computes dynamically the valve position according to the dynamic movement equation based on the hydraulic and spring forces applied on. As preliminary step, different fixed flow-rate boundary conditions will be applied at the inlet of the CV in order to validate the global valve characteristics with the incompressible solver. The CV oscillations are studied considering acoustics with an additional bulk viscosity term inside the flow equations. An increasing inlet volumetric flow law is applied to compute the dynamic response of the valve and to predict the frequency and the flow-rate range at which instabilities appear. This simulation shows a good agreement; the experimental instability range is well predicted as the eigen frequency.

References

[1] Asinari, P., 2008, Entropic multiple-relaxation-time lattice Boltzmann models, Tech. rep., Politecnico di Torino, Torino, Italy, 2008.

[2] Asinari, P., Ohwada, T., Chiavazzo, E., and Di Rienzo, A. F., 2012, Link-wise artificial compressibility method, Journal of Computational Physics, Vol. 231, No. 15, pp. 51095143. https://doi.org/10.1016/j.jcp.2012.04.027.

[3] Chen, S. and Doolen, G., 1998, Lattice Boltzmann method for fluid flows, Annual review of fluid mechanics, Vol. 30, No. 1, pp. 329-364. https://doi.org/10.1146/annurev.fluid.30.1.329.

[4] Ducros, F., Nicoud, F., & Poinsot, T., 1998, Wall-adapting local eddy-viscosity models for simulations in complex geometries, Proceedings of 6th ICFD Conference on Numerical Methods for Fluid Dynamics, pp. 293-299.

[5] Frisch, U., Hasslacher, B., and Pomeau, Y., 1986, Lattice-gas automata for the NavierStokes equation, Physical review letters, Vol. 56, No. 14, pp. 15051508.

[6] Geier, M., Greiner, A., and Korvink, J., 2009, A factorized central moment lattice Boltzmann method, The European Physical Journal Special Topics, Vol. 171, No. 1, pp. 55-61. https://doi.org/10.1103/PhysRevLett.56.1505

[7] Higuera, F.J., & Jimenez, J., 1989, Boltzmann approach to lattice gas simulations, Europhysics Letters, vol. 9, pp. 663-668. https://doi.org/10.1209/0295-5075/9/7/009.

[8] Brionnaud, R., Trapani, G., Modena, M. C., & Holman, D. M., 2016, Direct Noise Computation with a Lattice-Boltzmann Method and Application to Industrial Test Cases, 22nd AIAA/CEAS Aeroacoustics Conference (p. 2969). https://doi.org/10.2514/6.2016-2969

[9] D'Humieres, D., 2002, Multiple-relaxation-time lattice Boltzmann models in three dimensions, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, Vol. 360, No. 1792, 2002, pp. 437451. https://doi.org/10.1098/rsta.2001.0955

[10] McNamara, G. R. and Zanetti, G., Nov. 1988, Use of the Boltzmann equation to simulate lattice-gas automata, Physical Review Letters, Vol. 61, pp. 23322335. https://doi.org/10.1103/PhysRevLett.61.2332.

[11] Premnath, K., & Banerjee, S., 2011, On the Three-Dimensional Central Moment Lattice Boltzmann Method, Journal of Statistical Physics, 2011, pp. 148. https://doi.org/10.48550/arXiv.1202.6081.

[12] Qian, Y.H., d’Humieres, D., & Lallemand, P., 1992, Lattice BGK models for NavierStokes equation. EPL (Europhysics Letters), 17:479. https://doi.org/10.1209/0295-5075/17/6/00

[13] Ran, Z., & Xu, Y., 2008, Entropy and weak solutions in the thermal model for the compressible Euler equations, axXiv: 0810.3477. https://doi.org/10.48550/arXiv.0810.3477.

[14] Sbragaglia, M., Benzi, R., Biferale, L., Succi, S., Sugiyama, K., and Toschi, F., 2007, Generalized lattice Boltzmann method with multirange pseudopotential, Physical Review E, Vol. 75, No. 2, pp. 026702. https://doi.org/10.1103/PhysRevE.75.026702.

[15] Shan, X., & Chen, H., 2007, A general multiple-relaxation-time Boltzmann models in three dimensions, International Journal of Modern Physics C, Vol. 18, No. 4, 2007, pp. 635-643.

[16] Shih, T., Povinelli, L., Liu, N., Potapczuk, M., & Lumley, J., 1999, A generalized wall function, NASA Technical Report.

[17] Xu, A.-G., Zhang, G.-C., Gan, Y.-B., Chen, F., and Yu, X.-J., 2012, Lattice Boltzmann modeling and simulation of compressible flows, Frontiers of Physics, Vol. 7, No. 5, pp. 582-600. https://doi.org/10.1007/s11467-012-0269-5

Cite this paper

Daniel Hung, Anthony Mosquera, Fluid-Structure Interaction of a Rigid Wing for Minesto Deep Green, a Tidal Energy Device, NAFEMS International Journal of CFD Case Studies, Volume 12, 2020, Pages 35-48, https://doi.org/10.59972/ef8rt5x2