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

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 at...

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Main Authors: Yousri, Nur’Afifah, Ibrahim, Nabilah, Roseman, Nur Amani Hanis, Taib, Ishkrizat, Shanta, Shahnoor
Format: Article
Language:English
Published: semarak ilmu 2024
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Online Access:http://eprints.uthm.edu.my/11017/1/J17522_0dcc956d91d001781af24ac44d69f181.pdf
http://eprints.uthm.edu.my/11017/
https://doi.org/10.37934/armne.17.1.5668
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spelling my.uthm.eprints.110172024-06-04T02:42:20Z http://eprints.uthm.edu.my/11017/ CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity Yousri, Nur’Afifah Ibrahim, Nabilah Roseman, Nur Amani Hanis Taib, Ishkrizat Shanta, Shahnoor TA Engineering (General). Civil engineering (General) 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. semarak ilmu 2024 Article PeerReviewed text en http://eprints.uthm.edu.my/11017/1/J17522_0dcc956d91d001781af24ac44d69f181.pdf Yousri, Nur’Afifah and Ibrahim, Nabilah and Roseman, Nur Amani Hanis and Taib, Ishkrizat and Shanta, Shahnoor (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). pp. 56-468. ISSN 2756-8210 https://doi.org/10.37934/armne.17.1.5668
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Yousri, Nur’Afifah
Ibrahim, Nabilah
Roseman, Nur Amani Hanis
Taib, Ishkrizat
Shanta, Shahnoor
CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity
description 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.
format Article
author Yousri, Nur’Afifah
Ibrahim, Nabilah
Roseman, Nur Amani Hanis
Taib, Ishkrizat
Shanta, Shahnoor
author_facet Yousri, Nur’Afifah
Ibrahim, Nabilah
Roseman, Nur Amani Hanis
Taib, Ishkrizat
Shanta, Shahnoor
author_sort Yousri, Nur’Afifah
title CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity
title_short CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity
title_full CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity
title_fullStr CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity
title_full_unstemmed CFD Based on The Visualisation of Aortic Valve Mechanism in Aortic Valve Stenosis for Risk Prediction at The Peak Velocity
title_sort cfd based on the visualisation of aortic valve mechanism in aortic valve stenosis for risk prediction at the peak velocity
publisher semarak ilmu
publishDate 2024
url http://eprints.uthm.edu.my/11017/1/J17522_0dcc956d91d001781af24ac44d69f181.pdf
http://eprints.uthm.edu.my/11017/
https://doi.org/10.37934/armne.17.1.5668
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score 13.212058