CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity

Authors

  • Nur'Afifah Yousri Department of Electrical and Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
  • Nabilah Ibrahim Department of Electrical and Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
  • Nur Amani Hanis Roseman Department of Mechanical & Manufacturing Engineering, Faculty of University Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
  • Ishkrizat Taib Department of Mechanical & Manufacturing Engineering, Faculty of University Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
  • Shahnoor Shanta Computer and Information Sciences, Harrisburg University of Science and Technology, PA 17101, USA

DOI:

https://doi.org/10.37934/armne.17.1.5668

Keywords:

Aortic valve stenosis, computational fluid dynamics (CFD), Navier-Stokes equation, hemodynamic parameters

Abstract

Aortic valve disease plays a crucial role in the development of cardiovascular disease (CVD), leading to increased rates of mortality and morbidity. Two diseases, aortic valve regurgitation and aortic valve stenosis are known to occur in the aortic valve. However, aortic valve stenosis is gaining attention due to its severe impact on the patient. The malfunction of the aortic valve might be affected by blood flow, which leads to stenosis. This study aims to investigate the blood flow re-circulation on the aortic valve in different stenotic regions when the blood’s velocity reaches the pick flow of the time in the systole phases. Four different models of aortic valve stenotic are designed using computer-aided design (CAD) software. The computational fluid dynamics (CFD) approach governed by the Navier-Stokes equation is imposed to identify the characteristics of the blood backflow at the left ventricle. Several hemodynamic factors are considered, such as time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI) and relative residence time (RRT). The blood flow characteristic is expected to be chaotic, especially at the highest percentages of aortic valve stenosis, presenting the worst condition to the heart. This finding supports healthcare providers in foreseeing the deterioration of the patient’s condition and opting for aorta valve surgery replacement.

Author Biographies

Nur'Afifah Yousri, Department of Electrical and Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia

afifahyousri97@gmail.com

Nabilah Ibrahim, Department of Electrical and Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia

nabilah@uthm.edu.my

Nur Amani Hanis Roseman, Department of Mechanical & Manufacturing Engineering, Faculty of University Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia

hanisrose95@gmail.com

Ishkrizat Taib, Department of Mechanical & Manufacturing Engineering, Faculty of University Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia

iszat@uthm.edu.my

Shahnoor Shanta, Computer and Information Sciences, Harrisburg University of Science and Technology, PA 17101, USA

sshanta@harrisburgu.edu

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Published

2024-03-30

How to Cite

Nur’Afifah Yousri, Nabilah Ibrahim, Nur Amani Hanis Roseman, Ishkrizat Taib, and Shahnoor Shanta. 2024. “CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity”. Journal of Advanced Research in Micro and Nano Engineering 17 (1):56-68. https://doi.org/10.37934/armne.17.1.5668.
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