Research Article
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Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM

Year 2022, Volume 26, Issue 6, 1131 - 1141, 31.12.2022
https://doi.org/10.16984/saufenbilder.1173983

Abstract

In this study, a patient-specific carotid artery model was analyzed with an open source program foam-extend. The research includes the effect of arterial wall deformation by fluid-structure analysis. Pulsatile velocity cycle is trained for 144 patients with different hemodynamic parameters, by machine learning algorithm using blood flow velocity measured from 337 points of the carotid artery. Data used for training is obtained from an open source in the literature. Here, the machine learning algorithm was created by the help of an open source code Phyton. Then, using trained values of machine learning, and the known systole and diastole blood pressures for a specific chosen patient, the patient-specific pulsatile velocity cycle was estimated. The estimated pulsatile velocity cycle was then fitted to Fourier series. This pulsatile velocity cycle is used as the input boundary condition for the model analyzed in foam-extend. The outlet boundary condition, pulsatile pressure cycle is found by 4-Element Windkessel algorithm. Wall shear stresses and time averaged wall shear stresses were obtained for both the rigid and fluid structure interaction models, and variation of displacement throughout the pulsatile cycle was found for the FSI model. Wall shear stresses, velocity, and displacements were obtained high at peak systole, consistent with pulsatile cycles. Like the wall shear stresses, the time averaged wall shear stresses for the FSI model were also found lower than the rigid model. The wall shear stresses showed an increase towards the exit of internal and external carotid artery.

References

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Year 2022, Volume 26, Issue 6, 1131 - 1141, 31.12.2022
https://doi.org/10.16984/saufenbilder.1173983

Abstract

References

  • [1] P. Çeltikçi, Ö. Eraslan, M. A. Atıcı, I. Conkbayır, O. Ergun, H. Durmaz, E. Çeltikçi, “Application of machine learning algorithms for predicting internal carotid stenosis and comparing their value to duplex Doppler ultrasonography criteria,” Pamukkale Medical Journal, vol. 15, no. 2, pp. 213-222, 2022.
  • [2] S. Savaş, N. Topaloğlu, Ö. Kazcı, P. N. Koşar, “Comparison of deep learning models in carotid artery Intima-Media thickness ultrasound images: CAIMTUSNet,” Bilişim Teknolojileri Dergisi, vol. 15, no. 1, pp. 1-11, 2022.
  • [3] K. Perklot, M. Resch, H. Florian, “Pulsatile Non-Newtonian flow characteristics in a three-dimensional human carotid bifurcation model,” Journal of Biomechanical Engineering, Transactions of the ASME, vol. 113, pp. 464-475, 1991.
  • [4] F. Yubo, J. Wentao, Z. Yuanwen, L Jinchuan, C. Junkai, D. Xiaoyan, “Numerical Simulation of Pulsatile Non-Newtonian Flow in the Carotid Artery Bifurcation,” Acta Mechanica Sinica, vol. 25, no. 249, pp. 249-255, 2009.
  • [5] J. Moradicheghamahi, J. Sadeghiseraji, M. Jahangiri, “Numerical solution of the pulsatile, Non-Newtonian and turbulent flow in a patient specific elastic carotid artery,” International Journal of Mechanical Sciences, vol. 150, pp. 393-403, 2019.
  • [6] N. Kumar, S. M. Abdul Khader, R. B. Pai, P. Kyriacou, S. Khan, K. Prakashini, R. Srikanth, “Effect of Newtonian and Non-Newtonian flow in subject specific carotid artery,” Journal of Engineering Science and Technology, vol. 14, no. 4, pp.2746-2763, 2020.
  • [7] D. N. Ku, “Blood flow in arteries,” Annual Review of Fluid Mechanics, vol. 29, pp. 399-434, 1997.
  • [8] B. K. Bharadvaj, R. F. Mabon, D. P. Giddens, “Steady flow in a model of the human carotid bifurcation part I- flow visualization,” Journal of Biomechanics, vol. 15, pp. 349-362, 1982.
  • [9] D. Lopes, H. Puga, J. C. Teixeira, S. F. Teixeria, “Influence of arterial mechanical properties on carotid blood flow: comparison of CFD and FSI studies,” International Journal of Mechanical Sciences, vol. 160, pp. 209-218, 2019.
  • [10] D. Lopes, H. Puga, J. C. Teixeira, S. F. Teixeria, “Fluid-Structure interaction study of carotid blood flow: Comparison between viscosity models,” European Journal of Mechanics/ B Fluids, vol. 83, pp. 226-234, 2020.
  • [11] K. K. L. Wong, P. Thavornpattanapong, S. C. P. Cheung, J. Y. Tu, “Biomechanical investigation of pulsatile flow in a three-dimensional atherosclerotic carotid bifurcation model,” Journal of Mechanics in Medicine and Biology, vol. 13, pp.1-21, 2013.
  • [12] S. Tada, M. Tarbell, “A Computational study flow in a compliant carotid bifurcation-stress phase angle correlation with shear stress,” Annals of Biomedical Engineering, vol. 33, no. 9, pp.1202-1212, 2005.
  • [13] N. Kumar, S. M. Abdul Khader, R. Pai, S. H. Khan, P. A. Kyriacou, “Fluid structure interaction study of stenosed carotid artery considering the effects of blood pressure,” International Journal of Engineering Science, vol. 154, pp.1-14, 2020.
  • [14] S. H. Lee, S. Kang, N. Hur., S. Jeong, “A Fluid-Structure interaction analysis on hemodynamics in carotid artery based on patient specific clinical data,” Journal of Mechanical Science and Technology, vol. 26, pp. 3821-3831, 2012.
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  • [20] [20] C. Cortes, V. Vapnik, "Support-vector networks," Machine Learning, vol. 20, pp. 273-297, 1995.

Details

Primary Language English
Subjects Engineering, Mechanical
Journal Section Research Articles
Authors

Murad KUCUR> (Primary Author)
İSTANBUL ÜNİVERSİTESİ-CERRAHPAŞA, MÜHENDİSLİK FAKÜLTESİ, MAKİNE MÜHENDİSLİĞİ BÖLÜMÜ
0000-0002-0356-0359
Türkiye


Banu KÖRBAHTİ This is me
İSTANBUL ÜNİVERSİTESİ-CERRAHPAŞA, MÜHENDİSLİK FAKÜLTESİ, MAKİNE MÜHENDİSLİĞİ BÖLÜMÜ
0000-0002-2579-5255
Türkiye

Publication Date December 31, 2022
Submission Date September 12, 2022
Acceptance Date October 8, 2022
Published in Issue Year 2022, Volume 26, Issue 6

Cite

Bibtex @research article { saufenbilder1173983, journal = {Sakarya University Journal of Science}, eissn = {2147-835X}, address = {}, publisher = {Sakarya University}, year = {2022}, volume = {26}, number = {6}, pages = {1131 - 1141}, doi = {10.16984/saufenbilder.1173983}, title = {Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM}, key = {cite}, author = {Kucur, Murad and Körbahti, Banu} }
APA Kucur, M. & Körbahti, B. (2022). Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM . Sakarya University Journal of Science , 26 (6) , 1131-1141 . DOI: 10.16984/saufenbilder.1173983
MLA Kucur, M. , Körbahti, B. "Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM" . Sakarya University Journal of Science 26 (2022 ): 1131-1141 <https://dergipark.org.tr/en/pub/saufenbilder/issue/74051/1173983>
Chicago Kucur, M. , Körbahti, B. "Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM". Sakarya University Journal of Science 26 (2022 ): 1131-1141
RIS TY - JOUR T1 - Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM AU - MuradKucur, BanuKörbahti Y1 - 2022 PY - 2022 N1 - doi: 10.16984/saufenbilder.1173983 DO - 10.16984/saufenbilder.1173983 T2 - Sakarya University Journal of Science JF - Journal JO - JOR SP - 1131 EP - 1141 VL - 26 IS - 6 SN - -2147-835X M3 - doi: 10.16984/saufenbilder.1173983 UR - https://doi.org/10.16984/saufenbilder.1173983 Y2 - 2022 ER -
EndNote %0 Sakarya University Journal of Science Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM %A Murad Kucur , Banu Körbahti %T Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM %D 2022 %J Sakarya University Journal of Science %P -2147-835X %V 26 %N 6 %R doi: 10.16984/saufenbilder.1173983 %U 10.16984/saufenbilder.1173983
ISNAD Kucur, Murad , Körbahti, Banu . "Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM". Sakarya University Journal of Science 26 / 6 (December 2022): 1131-1141 . https://doi.org/10.16984/saufenbilder.1173983
AMA Kucur M. , Körbahti B. Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM. SAUJS. 2022; 26(6): 1131-1141.
Vancouver Kucur M. , Körbahti B. Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM. Sakarya University Journal of Science. 2022; 26(6): 1131-1141.
IEEE M. Kucur and B. Körbahti , "Fluid-Structure Interaction Analysis of Carotid Artery Blood Flow with Machine Learning Algorithm and OpenFOAM", Sakarya University Journal of Science, vol. 26, no. 6, pp. 1131-1141, Dec. 2022, doi:10.16984/saufenbilder.1173983

Sakarya University Journal of Science (SAUJS)