Computation and analysis for airflow characteristics of physical quantities caused by nasal obstruction

  • Yue-Lin Hsieh
  • Yi-Chern HsiehEmail author
  • Zhao Han
  • Hui-Fang Lin
Technical Paper


Nasal obstruction is a common disease found in humans and one of the most popular research topics. This article proposes an adaptive computing algorithm to construct the mesh structure for simulating the unsteady turbulent airflow in the nasal cavity of patients with nasal airway obstruction (NAO) with the help of MIMICS 16.0 × 64 and COMSOL 5.4. The computing results provide a lucid explanation for the aerodynamic impairment of the nasal passages and efficiently locate the three-dimensional region of the obstruction. Details of the time-dependent flow properties in different nasal cavities indicate that the pressure gradient along the streamline provides the NAO region. Several physical properties were discussed during one respiratory cycle. The merits of the adaptive computing technique showed that the time consumption and precision of the solutions were both satisfactory. The implementation of computer-aided diagnosis can be expected with more efforts in the near future.


Compliance with ethical standards

Conflict of interest

All authors declare that there is no potential conflict of interest, including any financial, personal or other relationships with other persons or organizations that may inappropriately influence this work.


  1. Ardeshirpour F, McCarn KE, McKinney AM, Odland RM, Yueh B, Hilger PA (2016) Computed tomography scan does not correlate with patient experience of nasal obstruction. Laryngoscope 126:820–825CrossRefGoogle Scholar
  2. Bochev PB (1997) Analysis of least-squares finite element methods for the Navier–Stokes equations. SIAM J Numer Anal 34:1817–1844MathSciNetCrossRefzbMATHGoogle Scholar
  3. Bochev PB, Gunzburger MD (1993) Accuracy of least-squares methods for the Navier–Stokes equations. Comput Fluids 22:549–563MathSciNetCrossRefzbMATHGoogle Scholar
  4. Cai Z, Manteuffel TA, McCormick SF (1997) First-order system least squares for second-order partial differential equations: part II. SIAM J Numer Anal 34:425–454MathSciNetCrossRefzbMATHGoogle Scholar
  5. Chen XB, Lee HP, Chong VF, Wang DY (2009) Assessment of septal deviation effects on nasal air flow: a computational fluid dynamics model. Laryngoscope 119:1730–1736CrossRefGoogle Scholar
  6. Chung SK, Kim SK (2008) Digital particle image velocimetry studies of nasal airflow. Respir Physiol Neurobiol 163:111–120CrossRefGoogle Scholar
  7. Dahl R, Mygind N (1998) Anatomy, physiology and function of the nasal cavities in health and disease. Adv Drug Deliv Rev 29:3–12CrossRefGoogle Scholar
  8. Derin S, Sahan M, Deveer M, Erdogan S, Tetiker H, Koseoglu S (2016) The causes of persistent and recurrent nasal obstruction after primary septoplasty. J Craniofac Surg 27:828–830CrossRefGoogle Scholar
  9. Doorly DJ, Taylor DJ, Schroter RC (2008) Mechanics of airflow in the human nasal airways. Respir Physiol Neurobiol 163:100–110CrossRefGoogle Scholar
  10. Eccles R (2000) Nasal airflow in health and disease. Acta Otolaryngol 120:580–595CrossRefGoogle Scholar
  11. Elad D, Liebenthal R, Wening BL, Einav S (1993) Analysis of air flow patterns in the human nose. Med Biol Eng Comput 31:585–592CrossRefGoogle Scholar
  12. Elad D, Wolf M, Keck T (2008) Air-conditioning in the human nasal cavity. Respir Physiol Neurobiol 163:121–127CrossRefGoogle Scholar
  13. Empey DW (1980) Assessment of the nasal passages. Br J Clin Pharmacol 9:317–319CrossRefGoogle Scholar
  14. Fraser L, Kelly G (2009) An evidence-based approach to the management of the adult with nasal obstruction. Clin Otolaryngol 34:151–155CrossRefGoogle Scholar
  15. Garcia GJ, Bailie N, Martins DA, Kimbell JS (2007) Atrophic rhinitis: a CFD study of air conditioning in the nasal cavity. J Appl Physiol 103:1082–1092CrossRefGoogle Scholar
  16. Garcia GJ, Rhee JS, Senior BA, Kimbell JS (2010) Septal deviation and nasal resistance: an investigation using virtual surgery and computational fluid dynamics. Am J Rhinol Allergy 24:e46–e53CrossRefGoogle Scholar
  17. Gerhart PM, Gross RJ, Hochstein JI (1992) Fundamentals of fluid mechanics, 2nd edn. Addison Wesley, Reading, pp 170–182Google Scholar
  18. Girardin M, Bilgen E, Arbour P (1983) Experimental study of velocity fields in a human nasal fossa by laser anemometry. Ann Otol Rhinol Laryngol 92:231–236CrossRefGoogle Scholar
  19. Gupta JK, Lin CH, Chen Q (2010) Characterizing exhaled airflow from breathing and talking. Indoor Air 20:31–39CrossRefGoogle Scholar
  20. Hariri BM, Rhee JS, Garcia GJ (2015) Identifying patients who may benefit from inferior turbinate reduction using computer simulations. Laryngoscope 125:2635–2641CrossRefGoogle Scholar
  21. Hilberg O (2002) Objective measurement of nasal airway dimensions using acoustic rhinometry: methodological and clinical aspects. Allergy 57:5–39CrossRefGoogle Scholar
  22. Hörschler I, Meinke M, Schröder W (2003) Numerical simulation of the flow field in a model of the nasal cavity. Comput Fluids 32:39–45CrossRefzbMATHGoogle Scholar
  23. Houtmeyers E, Gosselink R, Gayan-Ramirez G, Decramer M (1999) Regulation of mucociliary clearance in health and disease. Eur Respir J 13:1177–1188CrossRefGoogle Scholar
  24. Jian HZ, Lim KM, Thong KT, Wang DY, Lee HP (2014) Assessment of airflow ventilation in human nasal cavity and maxillary sinus before and after targeted sinonasal surgery: a numerical case study. Respir Physiol Neurobiol 194:29–36CrossRefGoogle Scholar
  25. Jiang BN (1992) A least-squares finite element method for incompressible Navier–Stokes problems. Int J Numer Methods Fluids 14:843–859CrossRefzbMATHGoogle Scholar
  26. Jo G, Chung SK, Na Y (2015) Numerical study of the effect of the nasal cycle on unilateral nasal resistance. Respir Physiol Neurobiol 219:58–68CrossRefGoogle Scholar
  27. Keyhani K, Scherer PW, Mozell MM (1995) Numerical simulation of airflow in the human nasal cavity. J Biomech Eng 117:429–441CrossRefGoogle Scholar
  28. Keyhani K, Scherer PW, Mozell MM (1997) A numerical model of nasal odorant transport for the analysis of human olfaction. J Theor Biol 186:279–301CrossRefGoogle Scholar
  29. Kim SK, Na Y, Kim JI, Chung SK (2013) Patient specific CFD models of nasal airflow: overview of methods and challenges. J Biomech 46:299–306CrossRefGoogle Scholar
  30. Kim SK, Heo GE, Seo A, Na Y, Chung SK (2014) Correlation between nasal airflow characteristics and clinical relevance of nasal septal deviation to nasal airway obstruction. Respir Physiol Neurobiol 192:95–101CrossRefGoogle Scholar
  31. Kimbell JS, Garcia GJ, Frank DO, Cannon DE, Pawar SS, Rhee JS (2012) Computed nasal resistance compared with patient-reported symptoms in surgically treated nasal airway passages: a preliminary report. Am J Rhinol Allergy 26:e94–e98CrossRefGoogle Scholar
  32. Larrabee YC, Kacker A (2014) Which inferior turbinate reduction technique best decreases nasal obstruction? Laryngoscope 124:814–815CrossRefGoogle Scholar
  33. Lee JH, Na Y, Kim SK, Chung SK (2010) Unsteady flow characteristics through a human nasal airway. Respir Physiol Neurobiol 172:136–146CrossRefGoogle Scholar
  34. Li L, Han D, Zhang L, Li Y, Zang H, Wang T, Liu Y (2012) Aerodynamic investigation of the correlation between nasal septal deviation and chronic rhinosinusitis. Laryngoscope 122:1915–1919CrossRefGoogle Scholar
  35. Liu JL (2000) Exact a posteriori error analysis of the least squares finite element method. Appl Math Comput 116:297–305MathSciNetzbMATHGoogle Scholar
  36. Liu JL, Lin IJ, Shih MZ, Chen RC, Hsieh MC (1996) Object-oriented programming of adaptive finite element and finite volume methods. Appl Numer Math 21:439–467CrossRefzbMATHGoogle Scholar
  37. Liu T, Han D, Wang J, Tan J, Zang H, Wang T, Li Y, Cui S (2011) Effects of septal deviation on the airflow characteristics: using computational fluid dynamics models. Acta Otolaryngol 132:290–298CrossRefGoogle Scholar
  38. Mihaescu M, Murugappan S, Kalra M, Khosla S, Gutmark E (2008) Large Eddy simulation and Reynolds-averaged Navier–Stokes modeling of flow in a realistic pharyngeal airway model: an investigation of obstructive sleep apnea. J Biomech 41:2279–2288CrossRefGoogle Scholar
  39. Moore M, Eccles R (2011) Objective evidence for the efficacy of surgical management of the deviated septum as a treatment for chronic nasal obstruction: a systematic review. Clin Otolaryngol 36:106–113CrossRefGoogle Scholar
  40. Mylavarapu G, Murugappan S, Mihaescu M, Kalra M, Khosla S, Gutmark E (2009) Validation of computational fluid dynamics methodology used for human upper airway flow simulations. J Biomech 42:1553–1559CrossRefGoogle Scholar
  41. Proctor DF (1977) The upper airways. I. Nasal physiology and defense of the lungs. Am Rev Respir Dis 115:97–129Google Scholar
  42. Proetz AW (2008) Air currents in the upper respiratory tract and their clinical importance. Ann Otol Rhinol Laryngol 60:439–467CrossRefGoogle Scholar
  43. Rhee JS (2009) Measuring outcomes in nasal surgery: realities and possibilities. Arch Facial Plast Surg 11:416–419CrossRefGoogle Scholar
  44. Swift DL, Proctor DF (1977) Access of air to the respiratory tract. In: Brain JD, Proctor DF, Reid LM (eds) Respiratory defense mechanisms. Marcel Dekker, New York, pp 63–91Google Scholar
  45. Wang Y, Elghobashi S (2014) On locating the obstruction in the upper airway via numerical simulation. Respir Physiol Neurobiol 193:1–10CrossRefGoogle Scholar
  46. Wen J, Inthavong K, Tu J, Wang S (2008) Numerical simulations for detailed airflow dynamics in a human nasal cavity. Respir Physiol Neurobiol 161:125–135CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Otology and Skull Base Surgery, Eye Ear Nose and Throat HospitalFudan UniversityShanghaiChina
  2. 2.Department of Power Mechanical EngineeringNational Formosa UniveristyYunlinTaiwan (Republic of China)
  3. 3.Key Laboratory of Hearing ScienceMinistry of HealthShanghaiChina

Personalised recommendations