Skip to main content
SpringerLink
Log in

Computational Meshing for CFD Simulations

  • Chapter
  • First Online:
Clinical and Biomedical Engineering in the Human Nose

Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

Abstract

In CFD modelling, small cells or elements are created to fill this volume. They constitute a mesh where each cell represents a discrete space that represents the flow locally. Mathematical equations that represent the flow physics are then applied to each cell of the mesh. Generating a high quality mesh is extremely important to obtain reliable solutions and to guarantee numerical stability. This chapter begins with a basic introduction to a typical workflow and guidelines for generating high quality meshes, and concludes with some more advanced topics, i.e., how to generate meshes in parallel, a discussion on mesh quality, and examples on the application of lattice-Boltzmann methods to simulate flow without any turbulence modelling on highly-resolved meshes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    A large number of grid generation software and open source codes exist with a listing of some available software given in the appendix.

  2. 2.

    HERMIT is the predecessor of the currently installed HAZEL HEN system at HLRS Stuttgart.

  3. 3.

    JUQUEEN is the predecessor of the currently installed JUWELS system at JSC.

References

  1. K. Bass, P. Worth Longest, Recommendations for simulating microparticle deposition at conditions similar to the upper airways with two-equation turbulence models. J. Aerosol Sci. 119, 31–50 (2018)

    Google Scholar 

  2. R. Benzi, S. Succi, M. Vergassola, The lattice Boltzmann equation: theory and applications. Phys. Rep. 222(3), 145–197 (1992)

    Article  Google Scholar 

  3. P.L. Bhatnagar, E.P. Gross, M. Krook, A model for collision processes in gases. I. Small amplitude processes in charged and neutral one-component systems. Phys. Rev. 94(3), 511–525 (1954)

    Google Scholar 

  4. J. Bonet, J. Peraire, An alternating digital tree (ADT) algorithm for 3D geometric searching and intersection problems. Int. J. Numer. Methods Eng. 31(1), 1–17 (1991)

    Article  MATH  Google Scholar 

  5. M. Bouzidi, M. Firdaouss, P. Lallemand, Momentum transfer of a Boltzmann-lattice fluid with boundaries. Phys. Fluids 13(11), 3452–3459 (2001)

    Article  MATH  Google Scholar 

  6. C. Burstedde, L.C. Wilcox, O. Ghattas, p4est: scalable algorithms for parallel adaptive mesh refinement on forests of octrees. SIAM J. Sci. Comput. 33(3), 1103–1133 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  7. M.O. Cetin, V. Pauz, M. Meinke, W. Schröder, Computational analysis of nozzle geometry variations for subsonic turbulent jets. Comput. Fluids 136, 467–484 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  8. D. D’Humières, I. Ginzburg, M. Krafczyk, P. Lallemand, L.-S. Luo, Multiple-relaxation-time lattice Boltzmann models in three dimensions. Philos. Trans. Ser. A, Math., Phys., Eng. Sci. 360(1792), 437–451 (2002)

    Google Scholar 

  9. A. Dupuis, B. Chopard, Theory and applications of an alternative lattice Boltzmann grid refinement algorithm. Phys. Rev. E 67(6), 1–7 (2003)

    Article  Google Scholar 

  10. N. Filipovic, Chapter 8 - Computational modeling of dry-powder inhalers for pulmonary drug delivery (Academic Press, Cambridge, 2020)

    Google Scholar 

  11. M. Folk, E. Pourmal, Balancing performance and preservation lessons learned with HDF5, in Proceedings of the 2010 Roadmap for Digital Preservation Interoperability Framework Workshop on - US-DPIF ’10 (2010), pp. 1–8

    Google Scholar 

  12. D.O. Frank-Ito, M. Wofford, J.D. Schroeter, J.S. Kimbell, Influence of mesh density on airflow and particle deposition in sinonasal airway modeling. J. Aerosol. Med. Pulm. Drug Deliv. (2015)

    Google Scholar 

  13. M. Germano, U. Piomelli, P. Moin, W.H. Cabot, A dynamic subgridâscaleeddy viscosity model. Phys. Fluids A: Fluid Dyn. 3(7), 1760–1765 (1991)

    Article  MATH  Google Scholar 

  14. I. Ginzburg, D. D’Humières, Multireflection boundary conditions for lattice Boltzmann models. Phys. Rev. E 68(6), 066614 (2003)

    Article  MathSciNet  Google Scholar 

  15. H. Grotjans, F. Menter, Wall functions for industrial applications, in Computational Fluid Dynamics ’98, ECCOMAS (1998), ed. by K. Papailiou (Wiley, Hoboken, 1998), pp. 1112–1117

    Google Scholar 

  16. Z. Guo, B. Shi, C. Zheng, A coupled lattice BGK model for the Boussinesq equations. Int. J. Numer. Methods Fluids 39(4), 325–342 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  17. I. Hörschler, M. Meinke, W. Schröder, Numerical simulation of the flow field in a model of the nasal cavity. Comput. Fluids 32(1), 39–45 (2003)

    Article  MATH  Google Scholar 

  18. I. Hörschler, W. Schröder, M. Meinke, On the assumption of steadiness of nasal cavity flow. J. Biomech. 43(6), 1081–5 (2010)

    Article  Google Scholar 

  19. S. Hou, J. Sterling, S. Chen, G.D. Doolen, A lattice Boltzmann subgrid model for high Reynolds number flows. Pattern Form. Lattice Gas Autom. 6, 1–18 (1994)

    Google Scholar 

  20. K. Inthavong, A. Chetty, Y. Shang, J. Tu, Examining mesh independence for flow dynamics in the human nasal cavity. Comput. Biol. Med. 102, 40–50 (2018)

    Article  Google Scholar 

  21. T. Isaac, C. Burstedde, O. Ghattas, Low-cost parallel algorithms for 2:1 octree balance, in 2012 IEEE 26th International Parallel and Distributed Processing Symposium (IEEE, 2012), pp. 426–437

    Google Scholar 

  22. T. Ishida, S. Takahashi, K. Nakahashi, Efficient and robust cartesian mesh generation for building-cube method. J. Comput. Sci. Technol. 2(4), 435–446 (2008)

    Article  Google Scholar 

  23. Y. Kuwata, K. Suga, Anomaly of the lattice Boltzmann methods in three-dimensional cylindrical flows. J. Comput. Phys. 280, 563–569 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  24. P. Lallemand, L.-S. Luo, Theory of the lattice Boltzmann method: dispersion, dissipation, isotropy, Galilean invariance, and stability. Phys. Rev. E 61(6), 6546–6562 (2000)

    Article  MathSciNet  Google Scholar 

  25. B.E. Launder, D.B. Spalding, The numerical computation of turbulent flows. Comput. Methods Appl. Mech. Eng. 3(2), 269–289 (1974)

    Article  MATH  Google Scholar 

  26. J. Li, M. Zingale, W.-k. Liao, A. Choudhary, R. Ross, R. Thakur, W. Gropp, R. Latham, A. Siegel, B. Gallagher, Parallel netCDF: a high-performance scientific I/O interface, in Proceedings of the 2003 ACM/IEEE conference on Supercomputing - SC ’03 (ACM Press, New York, USA, 2003), p. 39

    Google Scholar 

  27. A. Lintermann, Efficient parallel geometry distribution for the simulation of complex flows, in Proceedings of the VII ECCOMAS Congress 2016 (Athens, 2016). Technical University of Athens (NTUA) Greece, pp. 1277–1293

    Google Scholar 

  28. A. Lintermann, G. Eitel-Amor, M. Meinke, W. Schröder, Lattice-Boltzmann solutions with local grid refinement for nasal cavity flows. New results in numerical and experimental fluid mechanics VIII (Springer, Berlin, 2013), pp. 583–590

    Google Scholar 

  29. A. Lintermann, M. Meinke, W. Schröder, Investigations of the inspiration and heating capability of the human nasal cavity based on a lattice-boltzmann method, in Proceedings of the ECCOMAS Thematic International Conference on Simulation and Modeling of Biological Flows (SIMBIO 2011) (Belgium, Brussels, 2011)

    Google Scholar 

  30. A. Lintermann, M. Meinke, W. Schröder, Fluid mechanics based classification of the respiratory efficiency of several nasal cavities. Comput. Biol. Med. 43(11), 1833–1852 (2013)

    Article  Google Scholar 

  31. A. Lintermann, M. Meinke, W. Schröder, Zonal flow solver (ZFS): a highly efficient multi-physics simulation framework. Int. J. Comput. Fluid Dyn., 1–28 (2020)

    Google Scholar 

  32. A. Lintermann, D. Pleiter, W. Schröder, Performance of ODROID-MC1 for scientific flow problems. Futur. Gener. Comput. Syst. 95, 149–162 (2019)

    Article  Google Scholar 

  33. A. Lintermann, S. Schlimpert, J. Grimmen, C. Günther, M. Meinke, W. Schröder, Massively parallel grid generation on HPC systems. Comput. Methods Appl. Mech. Eng. 277, 131–153 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  34. A. Lintermann, W. Schröder, A hierarchical numerical journey through the nasal cavity: from nose-like models to real anatomies. Flow, Turbul. Combust. (2017)

    Google Scholar 

  35. A. Lintermann, W. Schröder, Simulation of aerosol particle deposition in the upper human tracheobronchial tract. Eur. J. Mech.-B/Fluids 63, 73–89 (2017)

    Google Scholar 

  36. A. Loseille, V. Menier, F. Alauzet, Parallel generation of large-size adapted meshes. Procedia Eng. 124, 57–69 (2015)

    Article  Google Scholar 

  37. F. Menter, Zonal two equation k-\(\omega \) turbulence models for aerodynamic flows, in 24th AIAA Fluid Dynamics Conference (Orlando, FL, USA, 1993), pp. AIAA paper 93–2906

    Google Scholar 

  38. T. Nakashima, M. Tsubokura, M. Vázquez, H.C. Owen, Y. Doi, Coupled analysis of unsteady aerodynamics and vehicle motion of a heavy-duty truck in wind gusts. Comput. Fluids 80, 1–9 (2012)

    Google Scholar 

  39. H. Nishikawa, B. Diskin, Development and application of parallel agglomerated multigrid methods for complex geometries, in 20th AIAA Computational Fluid Dynamics Conference (Hawaii, Honolulu, 2011), pp. 27–30

    Google Scholar 

  40. M. Peric, Flow simulation using control volumes of arbitrary polyhedral shape. ERCOFTAC Bulletin, No. 62 (2004)

    Google Scholar 

  41. A. Pogorelov, M. Meinke, W. Schröder, large-eddy simulation of the unsteady full 3d rim seal flow in a one-stage axial-flow turbine. Flow, Turbul. Combust. (2018)

    Google Scholar 

  42. A. Pogorelov, L. Schneiders, M. Meinke, W. Schröder, An adaptive cartesian mesh based method to simulate turbulent flows of multiple rotating surfaces. Flow Turbul. Combust. 100(1), 19–38 (2018)

    Google Scholar 

  43. Y.H. Qian, D. D’Humières, P. Lallemand, Lattice BGK models for Navier-Stokes equation. Europhys. Lett. (EPL) 17(6), 479–484 (1992)

    Article  MATH  Google Scholar 

  44. L. Richardson, On the approximate arithmetical solution by finite differences of physical problems involving differential equations, with an application to the stresses in a masonry dam. Proc. R. Soc. London. Ser. A 83, 335–336 (1910)

    Google Scholar 

  45. P. Roache, Perspective: a method for uniform reporting of grid refinement studies. J. Fluids Eng. 116, 405–413 (1994)

    Article  Google Scholar 

  46. H. Sagan, Space-filling curves, 1st edn. (Universitext. Springer,New York, 1994)

    Google Scholar 

  47. B. Saint-Vernant, L. Wantzel, Mémoire et expérience sur l’écoulement déterminé par des différences de pressions considérables. Journal de l’École Polytechnique H 27, 85ff (1839)

    Google Scholar 

  48. L. Schneiders, J.H. Grimmen, M. Meinke, W. Schröder, An efficient numerical method for fully-resolved particle simulations on high-performance computers, in Proceedings in Applied Mathematics and Mechanics (Lecce, Italy, 2015), GAMM, Ed., Wiley-VCH

    Google Scholar 

  49. L. Schneiders, C. Günther, M. Meinke, W. Schröder, An efficient conservative cut-cell method for rigid bodies interacting with viscous compressible flows. J. Comput. Phys. 311, 62–86 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  50. L. Schneiders, M. Meinke, W. Schröder, Direct particleâfluid simulation ofKolmogorov-length-scale size particles in decaying isotropicturbulence. J. Fluid Mech. 819, 188–227 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  51. J. Smagorinsky, General circulation experiments with the primitive equations. Mon. Weather Rev. 91(3), 99–164 (1963)

    Google Scholar 

  52. J.F. Thompson, B.K. Soni, N.P. Weatherill, Handbook of grid generation (Taylor & Francis Inc., CRC Press, 1998)

    Book  MATH  Google Scholar 

  53. J.F. Thompson, Z. Warsi, C.W. Mastin, Numerical grid generation: foundations and applications (Elsevier Science Pub. Co., New York, 1985)

    MATH  Google Scholar 

  54. S. Vinchurkar, P.W. Longest, Evaluation of hexahedral, prismatic and hybrid mesh styles for simulating respiratory aerosol dynamics. Comput. Fluids 37, 317–331 (2008)

    Article  MATH  Google Scholar 

  55. M. Waldmann, A. Lintermann, Y.J. Choi, W. Schröder, Analysis of the effects of MARME treatment on respiratory flow using the lattice-Boltzmann method. New results in numerical and experimental fluid mechanics XII (2020), pp. 853–863

    Google Scholar 

  56. A.T. White, C.K. Chong, Rotational invariance in the three-dimensional lattice Boltzmann method is dependent on the choice of lattice. J. Comput. Phys. 230(16), 6367–6378 (2011)

    Article  MATH  Google Scholar 

  57. D. Yu, R. Mei, L.-S. Luo, W. Shyy, Viscous flow computations with the method of lattice Boltzmann equation. Prog. Aerosp. Sci. 39(5), 329–367 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Forschungszentrum Jülich GmbH, Jülich, Germany

    Andreas Lintermann

Authors
  1. Andreas Lintermann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andreas Lintermann .

Editor information

Editors and Affiliations

  1. Mechanical and Automotive Engineering, School of Engineering, RMIT University, Bundoora, VIC, Australia

    Kiao Inthavong

  2. Sydney Medical School, University of Sydney, Sydney, NSW, Australia

    Narinder Singh

  3. Mechanical and Automotive Engineering, School of Engineering, RMIT University, Bundoora, VIC, Australia

    Eugene Wong

  4. Mechanical and Automotive Engineering, School of Engineering, RMIT University, Bundoora, VIC, Australia

    Jiyuan Tu

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Lintermann, A. (2021). Computational Meshing for CFD Simulations. In: Inthavong, K., Singh, N., Wong, E., Tu, J. (eds) Clinical and Biomedical Engineering in the Human Nose. Biological and Medical Physics, Biomedical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-6716-2_6

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-6716-2_6

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-6715-5

  • Online ISBN: 978-981-15-6716-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation