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Reducing the impact of geometric errors in flow computations using velocity measurements

Numerical blood flow simulations are typically set up from anatomical medical images and calibrated using velocity measurements. However, the accuracy of the computational geometry itself is limited by the resolution of the anatomical image. We first show that applying standard no‐slip boundary cond...

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Detalles Bibliográficos
Autores principales: Nolte, David, Bertoglio, Cristóbal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6619346/
https://www.ncbi.nlm.nih.gov/pubmed/30932361
http://dx.doi.org/10.1002/cnm.3203
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author Nolte, David
Bertoglio, Cristóbal
author_facet Nolte, David
Bertoglio, Cristóbal
author_sort Nolte, David
collection PubMed
description Numerical blood flow simulations are typically set up from anatomical medical images and calibrated using velocity measurements. However, the accuracy of the computational geometry itself is limited by the resolution of the anatomical image. We first show that applying standard no‐slip boundary conditions on inaccurately extracted boundaries can cause large errors in the results, in particular the pressure gradient. In this work, we therefore propose to augment the flow model calibration by slip/transpiration boundary conditions, whose parameters are then estimated using velocity measurements. Numerical experiments show that this methodology can considerably improve the accuracy of the estimated pressure gradients and 3D velocity fields when the vessel geometry is uncertain.
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spelling pubmed-66193462019-07-22 Reducing the impact of geometric errors in flow computations using velocity measurements Nolte, David Bertoglio, Cristóbal Int J Numer Method Biomed Eng Advances in Cardiovascular Modeling and Simulation (Acms) Numerical blood flow simulations are typically set up from anatomical medical images and calibrated using velocity measurements. However, the accuracy of the computational geometry itself is limited by the resolution of the anatomical image. We first show that applying standard no‐slip boundary conditions on inaccurately extracted boundaries can cause large errors in the results, in particular the pressure gradient. In this work, we therefore propose to augment the flow model calibration by slip/transpiration boundary conditions, whose parameters are then estimated using velocity measurements. Numerical experiments show that this methodology can considerably improve the accuracy of the estimated pressure gradients and 3D velocity fields when the vessel geometry is uncertain. John Wiley and Sons Inc. 2019-04-16 2019-06 /pmc/articles/PMC6619346/ /pubmed/30932361 http://dx.doi.org/10.1002/cnm.3203 Text en © 2019 The Authors International Journal for Numerical Methods in Biomedical Engineering Published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Advances in Cardiovascular Modeling and Simulation (Acms)
Nolte, David
Bertoglio, Cristóbal
Reducing the impact of geometric errors in flow computations using velocity measurements
title Reducing the impact of geometric errors in flow computations using velocity measurements
title_full Reducing the impact of geometric errors in flow computations using velocity measurements
title_fullStr Reducing the impact of geometric errors in flow computations using velocity measurements
title_full_unstemmed Reducing the impact of geometric errors in flow computations using velocity measurements
title_short Reducing the impact of geometric errors in flow computations using velocity measurements
title_sort reducing the impact of geometric errors in flow computations using velocity measurements
topic Advances in Cardiovascular Modeling and Simulation (Acms)
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6619346/
https://www.ncbi.nlm.nih.gov/pubmed/30932361
http://dx.doi.org/10.1002/cnm.3203
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