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Computational Fluid Dynamics in Cardiovascular Disease

Computational fluid dynamics (CFD) is a mechanical engineering field for analyzing fluid flow, heat transfer, and associated phenomena, using computer-based simulation. CFD is a widely adopted methodology for solving complex problems in many modern engineering fields. The merit of CFD is developing...

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Autor principal: Lee, Byoung-Kwon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Cardiology 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3173660/
https://www.ncbi.nlm.nih.gov/pubmed/21949524
http://dx.doi.org/10.4070/kcj.2011.41.8.423
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author Lee, Byoung-Kwon
author_facet Lee, Byoung-Kwon
author_sort Lee, Byoung-Kwon
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description Computational fluid dynamics (CFD) is a mechanical engineering field for analyzing fluid flow, heat transfer, and associated phenomena, using computer-based simulation. CFD is a widely adopted methodology for solving complex problems in many modern engineering fields. The merit of CFD is developing new and improved devices and system designs, and optimization is conducted on existing equipment through computational simulations, resulting in enhanced efficiency and lower operating costs. However, in the biomedical field, CFD is still emerging. The main reason why CFD in the biomedical field has lagged behind is the tremendous complexity of human body fluid behavior. Recently, CFD biomedical research is more accessible, because high performance hardware and software are easily available with advances in computer science. All CFD processes contain three main components to provide useful information, such as pre-processing, solving mathematical equations, and post-processing. Initial accurate geometric modeling and boundary conditions are essential to achieve adequate results. Medical imaging, such as ultrasound imaging, computed tomography, and magnetic resonance imaging can be used for modeling, and Doppler ultrasound, pressure wire, and non-invasive pressure measurements are used for flow velocity and pressure as a boundary condition. Many simulations and clinical results have been used to study congenital heart disease, heart failure, ventricle function, aortic disease, and carotid and intra-cranial cerebrovascular diseases. With decreasing hardware costs and rapid computing times, researchers and medical scientists may increasingly use this reliable CFD tool to deliver accurate results. A realistic, multidisciplinary approach is essential to accomplish these tasks. Indefinite collaborations between mechanical engineers and clinical and medical scientists are essential. CFD may be an important methodology to understand the pathophysiology of the development and progression of disease and for establishing and creating treatment modalities in the cardiovascular field.
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spelling pubmed-31736602011-09-23 Computational Fluid Dynamics in Cardiovascular Disease Lee, Byoung-Kwon Korean Circ J Review Computational fluid dynamics (CFD) is a mechanical engineering field for analyzing fluid flow, heat transfer, and associated phenomena, using computer-based simulation. CFD is a widely adopted methodology for solving complex problems in many modern engineering fields. The merit of CFD is developing new and improved devices and system designs, and optimization is conducted on existing equipment through computational simulations, resulting in enhanced efficiency and lower operating costs. However, in the biomedical field, CFD is still emerging. The main reason why CFD in the biomedical field has lagged behind is the tremendous complexity of human body fluid behavior. Recently, CFD biomedical research is more accessible, because high performance hardware and software are easily available with advances in computer science. All CFD processes contain three main components to provide useful information, such as pre-processing, solving mathematical equations, and post-processing. Initial accurate geometric modeling and boundary conditions are essential to achieve adequate results. Medical imaging, such as ultrasound imaging, computed tomography, and magnetic resonance imaging can be used for modeling, and Doppler ultrasound, pressure wire, and non-invasive pressure measurements are used for flow velocity and pressure as a boundary condition. Many simulations and clinical results have been used to study congenital heart disease, heart failure, ventricle function, aortic disease, and carotid and intra-cranial cerebrovascular diseases. With decreasing hardware costs and rapid computing times, researchers and medical scientists may increasingly use this reliable CFD tool to deliver accurate results. A realistic, multidisciplinary approach is essential to accomplish these tasks. Indefinite collaborations between mechanical engineers and clinical and medical scientists are essential. CFD may be an important methodology to understand the pathophysiology of the development and progression of disease and for establishing and creating treatment modalities in the cardiovascular field. The Korean Society of Cardiology 2011-08 2011-08-31 /pmc/articles/PMC3173660/ /pubmed/21949524 http://dx.doi.org/10.4070/kcj.2011.41.8.423 Text en Copyright © 2011 The Korean Society of Cardiology http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Lee, Byoung-Kwon
Computational Fluid Dynamics in Cardiovascular Disease
title Computational Fluid Dynamics in Cardiovascular Disease
title_full Computational Fluid Dynamics in Cardiovascular Disease
title_fullStr Computational Fluid Dynamics in Cardiovascular Disease
title_full_unstemmed Computational Fluid Dynamics in Cardiovascular Disease
title_short Computational Fluid Dynamics in Cardiovascular Disease
title_sort computational fluid dynamics in cardiovascular disease
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3173660/
https://www.ncbi.nlm.nih.gov/pubmed/21949524
http://dx.doi.org/10.4070/kcj.2011.41.8.423
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