A Versatile IBM-Based AMR Method for Studying Human Snoring

Wei Zhang, Yu Pan, Yuchen Gong, Haibo Dong, J. Xi
{"title":"A Versatile IBM-Based AMR Method for Studying Human Snoring","authors":"Wei Zhang, Yu Pan, Yuchen Gong, Haibo Dong, J. Xi","doi":"10.1115/fedsm2021-65790","DOIUrl":null,"url":null,"abstract":"\n In this work, a local adaptive mesh refinement (AMR) embedded incompressible flow solver is developed for biomedical flows. This AMR technique is based on the block-structured mesh and adapted from an in-house numerical solver for the Navier-Stokes equations with immersed-boundary method embedded, which is suitable for flows with complex and moving boundaries in biomedical applications. Flow behavior of the human upper airway under various head-neck postures is evaluated using the developed AMR technique, where the head-neck posture is hypothesized to change the cross-sectional area of the airway, therefore the airflow and aerodynamic behavior. The anatomically accurate three-dimensional human upper airway model is reconstructed from human magnetic resonance images (MRI) with measurements from the literature. Analyses were performed on vortex dynamics and pressure fluctuations in the pharyngeal airway. It was found that the vortex formation and aerodynamic pressure were affected by the airway bending. The sniffing position or the head-neck junction extension posture tend to facilitate the airflow through the upper human airway.","PeriodicalId":359619,"journal":{"name":"Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/fedsm2021-65790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

In this work, a local adaptive mesh refinement (AMR) embedded incompressible flow solver is developed for biomedical flows. This AMR technique is based on the block-structured mesh and adapted from an in-house numerical solver for the Navier-Stokes equations with immersed-boundary method embedded, which is suitable for flows with complex and moving boundaries in biomedical applications. Flow behavior of the human upper airway under various head-neck postures is evaluated using the developed AMR technique, where the head-neck posture is hypothesized to change the cross-sectional area of the airway, therefore the airflow and aerodynamic behavior. The anatomically accurate three-dimensional human upper airway model is reconstructed from human magnetic resonance images (MRI) with measurements from the literature. Analyses were performed on vortex dynamics and pressure fluctuations in the pharyngeal airway. It was found that the vortex formation and aerodynamic pressure were affected by the airway bending. The sniffing position or the head-neck junction extension posture tend to facilitate the airflow through the upper human airway.
基于ibm的多用途AMR方法研究人类打鼾
本文提出了一种基于局部自适应网格细化(AMR)的嵌入式不可压缩流求解器。该AMR技术以块结构网格为基础,采用内置的浸入边界法数值求解Navier-Stokes方程,适用于生物医学应用中具有复杂和移动边界的流动。采用开发的AMR技术评估了不同头颈姿势下人体上呼吸道的流动行为,其中头颈姿势假设会改变气道的横截面积,从而改变气流和空气动力学行为。解剖学上准确的三维人体上呼吸道模型是由人体磁共振图像(MRI)与测量从文献重建。分析了咽气道的涡流动力学和压力波动。研究发现,气道弯曲对涡的形成和气动压力都有影响。吸气体位或头颈交界处伸展体位有利于气流通过上呼吸道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信