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Computational fluid dynamics simulation of Reynolds stress frequencies in the FDA nozzle

Year 2024, Volume: 13 Issue: 3, 969 - 974, 15.07.2024
https://doi.org/10.28948/ngumuh.1465806

Abstract

It is known that examining turbulence effects on medical devices has an important effect in design and optimization of blood-contacting devices. CFD has been commonly used on prosthetic heart valves, stents, and Ventricular Assist Devices (VADs) in both the design process and also on hemodynamics of the flow characteristics. In this study, flows in the FDA nozzle were modeled to examine Reynolds stresses in the whole domain. The flow behavior was determined by applying the Reynolds-Averaged Navier-Stokes model of turbulence (k-ω SST) to simulate five distinctive experimental cases in the nozzle taken from the literature. The Reynolds stress frequencies are determined for the five different experimental conditions. Results showed that the highest velocity case (corresponding throat Reynolds number of 6500) has much higher Reynolds stresses with a high number of frequencies. However, the lowest velocity case has very small Reynolds numbers in a very high frequency. When different parts of the nozzle were examined, the Reynolds stress values showed more fluctuations for the higher velocities and more regular profiles for the lower velocity cases.

References

  • V. Laxmi, Medical devices: technologies and global markets. BCC Res., 2018.
  • G. W. Burgreen, J. F. Antaki, Z. J. Wu, and A. J. Holmes, Computational fluid dynamics as a development tool for rotary blood pumps. Artif. Organs, vol. 25, no. 5, pp. 336–340, 2001. doi: 10.10 46/j.1525-1594.2001.025005336.x.
  • K. H. Fraser, T. Zhang, M. E. Taskin, B. P. Griffith, and Z. J. Wu, A quantitative comparison of mechanical blood damage parameters in Rotary Ventricular Assist Devices: shear stress, exposure time, and hemolysis index. J. Biomech. Eng., vol. 134, no. 8, p. 81002, 2012. DOI:10.1115/1.4007092
  • V. Izraelev et al., A passively suspended Tesla pump left ventricular assist device. ASAIO J., vol. 55, no. 6, pp. 556–561, 2009. doi: 10.1097/MAT.0b013e3181ba e73e
  • Y. S. Morsi, W. Yang, P. J. Witt, A. M. Ahmed, and M. Umezu, Numerical analysis of the flow characteristics of the rotary blood pump. J. Artif. Organs, vol. 4, no. 1, pp. 54–60, 2001, doi: 10.1007/BF01235837.
  • V.-T. Nguyen et al., Experimentally Validated Hemodynamics Simulations of Mechanical Heart Valves in Three Dimensions. Cardiovasc. Eng. Technol., vol. 3, no. 1, pp. 88–100, 2012, doi: 10.1007/s13239-011-0077-z.
  • J. Wu, B. E. Paden, H. S. Borovetz, and J. F. Antaki, Computational fluid dynamics analysis of blade tip clearances on hemodynamic performance and blood damage in a centrifugal ventricular assist device. Artif. Organs, vol. 34, no. 5, pp. 402–411, 2010. doi: 10.11 11/j.1525-1594.2009.00875.x
  • C. C. Long, A. L. Marsden, and Y. Bazilevs, Shape optimization of pulsatile ventricular assist devices using FSI to minimize thrombotic risk. Comput. Mech., vol. 54, no. 4, pp. 921–932, 2014, doi: 10.1007/s00466-013-0967-z.
  • G. A. Giridharan et al., Performance evaluation of a pediatric viscous impeller pump for Fontan cavopulmonary assist. J. Thorac. Cardiovasc. Surg., vol. 145, no. 1, pp. 249–257, Jan. 2013, doi: 10.1016/j.jtcvs.2012.01.082.
  • C. Karmonik, J. Bismuth, M. G. Davies, D. J. Shah, H. K. Younes, and A. B. Lumsden, A computational fluid dynamics study pre- and post-stent graft placement in an acute type B aortic dissection. Vasc. Endovascular Surg., vol. 45, no. 2, pp. 157–164, Feb. 2011, doi: 10.1177/1538574410389342.
  • Y. He, N. Duraiswamy, A. O. Frank, and J. E. J. Moore, Blood flow in stented arteries: a parametric comparison of strut design patterns in three dimensions. J. Biomech. Eng., vol. 127, no. 4, pp. 637–647, Aug. 2005, doi: 10.1115/1.1934122.
  • S. Seshadhri, G. Janiga, O. Beuing, M. Skalej, and D. Thévenin, Impact of Stents and Flow Diverters on Hemodynamics in Idealized Aneurysm Models. J. Biomech. Eng., vol. 133, p. 71005, 2011, doi: 10.1115/1.4004410.
  • Z. Cheng et al., Assessment of Hemodynamic Conditions in the Aorta Following Root Replacement with Composite Valve-Conduit Graft. Ann. Biomed. Eng., vol. 44, no. 5, pp. 1392–1404, May 2016, doi: 10.1007/s10439-015-1453-x.
  • I. Borazjani, L. Ge, and F. Sotiropoulos, High-resolution fluid-structure interaction simulations of flow through a bi-leaflet mechanical heart valve in an anatomic aorta. Ann. Biomed. Eng., vol. 38, no. 2, pp. 326–344, Feb. 2010, doi: 10.1007/s10439-009-9807-x.
  • E. Sirois and W. Sun, Computational Evaluation of Platelet Activation Induced by a Bioprosthetic Heart Valve. Artif. Organs, vol. 35, no. 2, pp. 157–165, Feb. 2011, doi: https://doi.org/10.1111/j.1525-1594.2010.0 1048.x.
  • S. Pirola et al., Computational study of aortic hemodynamics for patients with an abnormal aortic valve: The importance of secondary flow at the ascending aorta inlet. APL Bioeng., vol. 2, no. 2, p. 26101, Jun. 2018, doi: 10.1063/1.5011960.
  • N. Franck, C. Chnafa, J. Sigüenza, V. Zmijanovic, and S. Mendez, Large-Eddy Simulation of Turbulence in Cardiovascular Flows. in Lecture Notes in Applied and Computational Mechanics, 2017, pp. 147–167. doi: 10. 1007/978-3-319-59548-1_9.
  • J. Lantz, T. Ebbers, J. Engvall, and M. Karlsson, Numerical and experimental assessment of turbulent kinetic energy in an aortic coarctation. J. Biomech., vol. 46, no. 11, pp. 1851–1858, 2013, doi: https://doi.org /10.1016/j.jbiomech.2013.04.028.
  • M. Andersson, J. Lantz, T. Ebbers, and M. Karlsson, Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation: Impact of Virtual Interventions. Cardiovasc. Eng. Technol., vol. 6, no. 3, pp. 281–293, Sep. 2015, doi: 10.1007/s13239-015-0218-x.
  • A. M. Sallam and N. H. C. Hwang, Human red blood cell hemolysis in a turbulent shear flow: contribution of Reynolds shear stresses. Biorheology, vol. 21, no. 6, pp. 783–797, 1984. doi: 10.3233/bir-1984-21605
  • M. Grigioni, C. Daniele, G. D’Avenio, and V. Barbaro, A discussion on the threshold limit for hemolysis related to Reynolds shear stress. J. Biomech., vol. 32, no. 10, pp. 1107–1112, 1999. doi: 10.1016/s0021-92 90(99)00063-9.
  • M. V Kameneva, G. W. Burgreen, K. Kono, B. Repko, J. F. Antaki, and M. Umezu, Effects of Turbulent Stresses upon Mechanical Hemolysis: Experimental and Computational Analysis. ASAIO J., vol. 50, no. 5, pp. 418–423, 2004.
  • S. J. Hund, J. F. Antaki, and M. Massoudi, On the Representation of Turbulent Stresses for Computing Blood Damage. Int. J. Eng. Sci., vol. 48, no. 11, pp. 1325–1331, 2010. doi: 10.1016/j.ijengsci.2010.09.003
  • J. Taylor et al., Analysis of Transitional and Turbulent Flow Through the FDA Benchmark Nozzle Model Using Laser Doppler Velocimetry. Cardiovasc. Eng. Technol., vol. 7, Jun. 2016, doi: 10.1007/s13239-016-0270-1.
  • M. Ozturk, E. A. O’Rear, and D. V. Papavassiliou, Hemolysis Related to Turbulent Eddy Size Distributions Using Comparisons of Experiments to Computations. Artif. Organs, vol. 39, no. 12, pp. E227–E239, 2015, doi: 10.1111/aor.12572.
  • P. Hariharan et al., Multilaboratory particle image velocimetry analysis of the FDA benchmark nozzle model to support validation of computational fluid dynamics simulations. J. Biomech. Eng., vol. 133, no. 4, p. 41002, Apr. 2011, doi: 10.1115/1.4003440.
  • N. Fehn, W. A. Wall, and M. Kronbichler, Modern discontinuous Galerkin methods for the simulation of transitional and turbulent flows in biomedical engineering: A comprehensive LES study of the FDA benchmark nozzle model. Int. j. numer. method. biomed. eng., vol. 35, no. 12, p. e3228, Dec. 2019, doi: https://doi.org/10.1002/cnm.3228.
  • N. Sánchez Abad, R. Vinuesa, P. Schlatter, M. Andersson, and M. Karlsson, Simulation strategies for the Food and Drug Administration nozzle using Nek5000. AIP Adv., vol. 10, no. 2, p. 25033, Feb. 2020, doi: 10.1063/1.5142703.
  • E. L. Manchester and X. Y. Xu, The effect of turbulence on transitional flow in the FDA’s benchmark nozzle model using large-eddy simulation. Int. j. numer. method. biomed. eng., vol. 36, no. 10, p. e3389, Oct. 2020, doi: https://doi.org/10.1002/cnm.33 89.
  • P. Drešar and J. Duhovnik, A Hybrid RANS-LES Computational Fluid Dynamics Simulation of an FDA Medical device benchmark. Mechanics, vol. 25, pp. 291–298, Aug. 2019, doi: 10.5755/j01.mech.25.4.2010 5.
  • R. A. Malinauskas et al., FDA Benchmark Medical Device Flow Models for CFD Validation. ASAIO J., vol. 63, no. 2, pp. 150–160, 2017, doi: 10.1097/MAT. 0000000000000499.
  • S. F. C. Stewart et al., Assessment of CFD Performance in Simulations of an Idealized Medical Device: Results of FDA’s First Computational Interlaboratory Study. Cardiovasc. Eng. Technol., vol. 3, no. 2, pp. 139–160, 2012, doi: 10.1007/s13239-012-0087-5.

FDA nozulundaki Reynolds gerilme frekanslarının hesaplamalı akışkanlar dinamiği simülasyonu

Year 2024, Volume: 13 Issue: 3, 969 - 974, 15.07.2024
https://doi.org/10.28948/ngumuh.1465806

Abstract

Tıbbi cihazlar üzerindeki türbülans etkilerinin incelenmesinin, kanla temas eden cihazların tasarımında ve optimizasyonunda önemli bir etkiye sahip olduğu bilinmektedir. Hesaplamalı Akışkanlar Mekaniği (HAD), protez kalp kapakçıkları, stentler ve Ventriküler Destek Cihazları (VAD) üzerinde hem tasarım sürecinde hem de akış karakteristiklerinin hemodinamiği üzerinde yaygın olarak kullanılmaktadır. Bu çalışmada, The U.S. Food and Administration (FDA) nozulundaki akışlar modellenerek tüm etki alanındaki Reynolds gerilmeleri incelenmiştir. Akış davranışı, literatürden alınan nozüldeki beş farklı deneysel vakayı simüle etmek için Reynolds Ortalamalı Navier-Stokes türbülans modeli (k-ω SST) uygulanarak belirlenmiştir. Beş farklı deneysel durum için Reynolds gerilme frekansları belirlenmiştir. Sonuçlar, en yüksek hız durumunun (6500, boğaz Reynolds sayısına karşılık gelir) yüksek frekans sayısı ile çok daha yüksek Reynols gerilmelerine sahip olduğunu göstermiştir. Bununla birlikte, en düşük hız durumu çok yüksek frekanslarda çok küçük Reynolds sayılarına sahiptir. Nozulun farklı kısımları incelendiğinde, Reynolds gerilme değerleri yüksek hızlar için daha fazla dalgalanma gösterirken, düşük hız durumları için daha düzenli profiller göstermektedir.

References

  • V. Laxmi, Medical devices: technologies and global markets. BCC Res., 2018.
  • G. W. Burgreen, J. F. Antaki, Z. J. Wu, and A. J. Holmes, Computational fluid dynamics as a development tool for rotary blood pumps. Artif. Organs, vol. 25, no. 5, pp. 336–340, 2001. doi: 10.10 46/j.1525-1594.2001.025005336.x.
  • K. H. Fraser, T. Zhang, M. E. Taskin, B. P. Griffith, and Z. J. Wu, A quantitative comparison of mechanical blood damage parameters in Rotary Ventricular Assist Devices: shear stress, exposure time, and hemolysis index. J. Biomech. Eng., vol. 134, no. 8, p. 81002, 2012. DOI:10.1115/1.4007092
  • V. Izraelev et al., A passively suspended Tesla pump left ventricular assist device. ASAIO J., vol. 55, no. 6, pp. 556–561, 2009. doi: 10.1097/MAT.0b013e3181ba e73e
  • Y. S. Morsi, W. Yang, P. J. Witt, A. M. Ahmed, and M. Umezu, Numerical analysis of the flow characteristics of the rotary blood pump. J. Artif. Organs, vol. 4, no. 1, pp. 54–60, 2001, doi: 10.1007/BF01235837.
  • V.-T. Nguyen et al., Experimentally Validated Hemodynamics Simulations of Mechanical Heart Valves in Three Dimensions. Cardiovasc. Eng. Technol., vol. 3, no. 1, pp. 88–100, 2012, doi: 10.1007/s13239-011-0077-z.
  • J. Wu, B. E. Paden, H. S. Borovetz, and J. F. Antaki, Computational fluid dynamics analysis of blade tip clearances on hemodynamic performance and blood damage in a centrifugal ventricular assist device. Artif. Organs, vol. 34, no. 5, pp. 402–411, 2010. doi: 10.11 11/j.1525-1594.2009.00875.x
  • C. C. Long, A. L. Marsden, and Y. Bazilevs, Shape optimization of pulsatile ventricular assist devices using FSI to minimize thrombotic risk. Comput. Mech., vol. 54, no. 4, pp. 921–932, 2014, doi: 10.1007/s00466-013-0967-z.
  • G. A. Giridharan et al., Performance evaluation of a pediatric viscous impeller pump for Fontan cavopulmonary assist. J. Thorac. Cardiovasc. Surg., vol. 145, no. 1, pp. 249–257, Jan. 2013, doi: 10.1016/j.jtcvs.2012.01.082.
  • C. Karmonik, J. Bismuth, M. G. Davies, D. J. Shah, H. K. Younes, and A. B. Lumsden, A computational fluid dynamics study pre- and post-stent graft placement in an acute type B aortic dissection. Vasc. Endovascular Surg., vol. 45, no. 2, pp. 157–164, Feb. 2011, doi: 10.1177/1538574410389342.
  • Y. He, N. Duraiswamy, A. O. Frank, and J. E. J. Moore, Blood flow in stented arteries: a parametric comparison of strut design patterns in three dimensions. J. Biomech. Eng., vol. 127, no. 4, pp. 637–647, Aug. 2005, doi: 10.1115/1.1934122.
  • S. Seshadhri, G. Janiga, O. Beuing, M. Skalej, and D. Thévenin, Impact of Stents and Flow Diverters on Hemodynamics in Idealized Aneurysm Models. J. Biomech. Eng., vol. 133, p. 71005, 2011, doi: 10.1115/1.4004410.
  • Z. Cheng et al., Assessment of Hemodynamic Conditions in the Aorta Following Root Replacement with Composite Valve-Conduit Graft. Ann. Biomed. Eng., vol. 44, no. 5, pp. 1392–1404, May 2016, doi: 10.1007/s10439-015-1453-x.
  • I. Borazjani, L. Ge, and F. Sotiropoulos, High-resolution fluid-structure interaction simulations of flow through a bi-leaflet mechanical heart valve in an anatomic aorta. Ann. Biomed. Eng., vol. 38, no. 2, pp. 326–344, Feb. 2010, doi: 10.1007/s10439-009-9807-x.
  • E. Sirois and W. Sun, Computational Evaluation of Platelet Activation Induced by a Bioprosthetic Heart Valve. Artif. Organs, vol. 35, no. 2, pp. 157–165, Feb. 2011, doi: https://doi.org/10.1111/j.1525-1594.2010.0 1048.x.
  • S. Pirola et al., Computational study of aortic hemodynamics for patients with an abnormal aortic valve: The importance of secondary flow at the ascending aorta inlet. APL Bioeng., vol. 2, no. 2, p. 26101, Jun. 2018, doi: 10.1063/1.5011960.
  • N. Franck, C. Chnafa, J. Sigüenza, V. Zmijanovic, and S. Mendez, Large-Eddy Simulation of Turbulence in Cardiovascular Flows. in Lecture Notes in Applied and Computational Mechanics, 2017, pp. 147–167. doi: 10. 1007/978-3-319-59548-1_9.
  • J. Lantz, T. Ebbers, J. Engvall, and M. Karlsson, Numerical and experimental assessment of turbulent kinetic energy in an aortic coarctation. J. Biomech., vol. 46, no. 11, pp. 1851–1858, 2013, doi: https://doi.org /10.1016/j.jbiomech.2013.04.028.
  • M. Andersson, J. Lantz, T. Ebbers, and M. Karlsson, Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation: Impact of Virtual Interventions. Cardiovasc. Eng. Technol., vol. 6, no. 3, pp. 281–293, Sep. 2015, doi: 10.1007/s13239-015-0218-x.
  • A. M. Sallam and N. H. C. Hwang, Human red blood cell hemolysis in a turbulent shear flow: contribution of Reynolds shear stresses. Biorheology, vol. 21, no. 6, pp. 783–797, 1984. doi: 10.3233/bir-1984-21605
  • M. Grigioni, C. Daniele, G. D’Avenio, and V. Barbaro, A discussion on the threshold limit for hemolysis related to Reynolds shear stress. J. Biomech., vol. 32, no. 10, pp. 1107–1112, 1999. doi: 10.1016/s0021-92 90(99)00063-9.
  • M. V Kameneva, G. W. Burgreen, K. Kono, B. Repko, J. F. Antaki, and M. Umezu, Effects of Turbulent Stresses upon Mechanical Hemolysis: Experimental and Computational Analysis. ASAIO J., vol. 50, no. 5, pp. 418–423, 2004.
  • S. J. Hund, J. F. Antaki, and M. Massoudi, On the Representation of Turbulent Stresses for Computing Blood Damage. Int. J. Eng. Sci., vol. 48, no. 11, pp. 1325–1331, 2010. doi: 10.1016/j.ijengsci.2010.09.003
  • J. Taylor et al., Analysis of Transitional and Turbulent Flow Through the FDA Benchmark Nozzle Model Using Laser Doppler Velocimetry. Cardiovasc. Eng. Technol., vol. 7, Jun. 2016, doi: 10.1007/s13239-016-0270-1.
  • M. Ozturk, E. A. O’Rear, and D. V. Papavassiliou, Hemolysis Related to Turbulent Eddy Size Distributions Using Comparisons of Experiments to Computations. Artif. Organs, vol. 39, no. 12, pp. E227–E239, 2015, doi: 10.1111/aor.12572.
  • P. Hariharan et al., Multilaboratory particle image velocimetry analysis of the FDA benchmark nozzle model to support validation of computational fluid dynamics simulations. J. Biomech. Eng., vol. 133, no. 4, p. 41002, Apr. 2011, doi: 10.1115/1.4003440.
  • N. Fehn, W. A. Wall, and M. Kronbichler, Modern discontinuous Galerkin methods for the simulation of transitional and turbulent flows in biomedical engineering: A comprehensive LES study of the FDA benchmark nozzle model. Int. j. numer. method. biomed. eng., vol. 35, no. 12, p. e3228, Dec. 2019, doi: https://doi.org/10.1002/cnm.3228.
  • N. Sánchez Abad, R. Vinuesa, P. Schlatter, M. Andersson, and M. Karlsson, Simulation strategies for the Food and Drug Administration nozzle using Nek5000. AIP Adv., vol. 10, no. 2, p. 25033, Feb. 2020, doi: 10.1063/1.5142703.
  • E. L. Manchester and X. Y. Xu, The effect of turbulence on transitional flow in the FDA’s benchmark nozzle model using large-eddy simulation. Int. j. numer. method. biomed. eng., vol. 36, no. 10, p. e3389, Oct. 2020, doi: https://doi.org/10.1002/cnm.33 89.
  • P. Drešar and J. Duhovnik, A Hybrid RANS-LES Computational Fluid Dynamics Simulation of an FDA Medical device benchmark. Mechanics, vol. 25, pp. 291–298, Aug. 2019, doi: 10.5755/j01.mech.25.4.2010 5.
  • R. A. Malinauskas et al., FDA Benchmark Medical Device Flow Models for CFD Validation. ASAIO J., vol. 63, no. 2, pp. 150–160, 2017, doi: 10.1097/MAT. 0000000000000499.
  • S. F. C. Stewart et al., Assessment of CFD Performance in Simulations of an Idealized Medical Device: Results of FDA’s First Computational Interlaboratory Study. Cardiovasc. Eng. Technol., vol. 3, no. 2, pp. 139–160, 2012, doi: 10.1007/s13239-012-0087-5.
There are 32 citations in total.

Details

Primary Language English
Subjects Chemical Engineering (Other)
Journal Section Research Articles
Authors

Mesude Avcı 0000-0001-8211-7779

Early Pub Date July 5, 2024
Publication Date July 15, 2024
Submission Date April 5, 2024
Acceptance Date May 31, 2024
Published in Issue Year 2024 Volume: 13 Issue: 3

Cite

APA Avcı, M. (2024). Computational fluid dynamics simulation of Reynolds stress frequencies in the FDA nozzle. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 13(3), 969-974. https://doi.org/10.28948/ngumuh.1465806
AMA Avcı M. Computational fluid dynamics simulation of Reynolds stress frequencies in the FDA nozzle. NOHU J. Eng. Sci. July 2024;13(3):969-974. doi:10.28948/ngumuh.1465806
Chicago Avcı, Mesude. “Computational Fluid Dynamics Simulation of Reynolds Stress Frequencies in the FDA Nozzle”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13, no. 3 (July 2024): 969-74. https://doi.org/10.28948/ngumuh.1465806.
EndNote Avcı M (July 1, 2024) Computational fluid dynamics simulation of Reynolds stress frequencies in the FDA nozzle. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13 3 969–974.
IEEE M. Avcı, “Computational fluid dynamics simulation of Reynolds stress frequencies in the FDA nozzle”, NOHU J. Eng. Sci., vol. 13, no. 3, pp. 969–974, 2024, doi: 10.28948/ngumuh.1465806.
ISNAD Avcı, Mesude. “Computational Fluid Dynamics Simulation of Reynolds Stress Frequencies in the FDA Nozzle”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13/3 (July 2024), 969-974. https://doi.org/10.28948/ngumuh.1465806.
JAMA Avcı M. Computational fluid dynamics simulation of Reynolds stress frequencies in the FDA nozzle. NOHU J. Eng. Sci. 2024;13:969–974.
MLA Avcı, Mesude. “Computational Fluid Dynamics Simulation of Reynolds Stress Frequencies in the FDA Nozzle”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, vol. 13, no. 3, 2024, pp. 969-74, doi:10.28948/ngumuh.1465806.
Vancouver Avcı M. Computational fluid dynamics simulation of Reynolds stress frequencies in the FDA nozzle. NOHU J. Eng. Sci. 2024;13(3):969-74.

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