Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Dario De Marinis"'
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 8 (2022)
The development of turbulence after transcatheter aortic valve (TAV) implantation may have detrimental effects on the long-term performance and durability of the valves. The characterization of turbulent flow generated after TAV implantation can prov
Externí odkaz:
https://doaj.org/article/f84f6b899db24b5caf65409e764e86ad
Autor:
Dario De Marinis, Dominik Obrist
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 8 (2021)
We propose a data assimilation methodology that can be used to enhance the spatial and temporal resolution of voxel-based data as it may be obtained from biomedical imaging modalities. It can be used to improve the assessment of turbulent blood flow
Externí odkaz:
https://doaj.org/article/7502ec0bb44848babce8fd56ab2cd7cd
Publikováno v:
International Journal of Numerical Methods for Heat & Fluid Flow, 2016, Vol. 26, Issue 3/4, pp. 1272-1288.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/HFF-11-2015-0473
Autor:
Dominik Obrist, Dario De Marinis
Publikováno v:
De Marinis, Dario; Obrist, Dominik (2021). Data Assimilation by Stochastic Ensemble Kalman Filtering to Enhance Turbulent Cardiovascular Flow Data From Under-Resolved Observations. Frontiers in cardiovascular medicine, 8, p. 742110. Frontiers 10.3389/fcvm.2021.742110
Frontiers in Cardiovascular Medicine
Frontiers in Cardiovascular Medicine, Vol 8 (2021)
Frontiers in Cardiovascular Medicine
Frontiers in Cardiovascular Medicine, Vol 8 (2021)
We propose a data assimilation methodology that can be used to enhance the spatial and temporal resolution of voxel-based data as it may be obtained from biomedical imaging modalities. It can be used to improve the assessment of turbulent blood flow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b3f578cf5590157af4f51c5ceabfc50
https://boris.unibe.ch/164023/1/De_Marinis__Obrist__Data_Assimilation_by_Stochastic_Ensemble_Kalman_Filtering__Front_Cardiovasc_Med__2021.pdf
https://boris.unibe.ch/164023/1/De_Marinis__Obrist__Data_Assimilation_by_Stochastic_Ensemble_Kalman_Filtering__Front_Cardiovasc_Med__2021.pdf
Autor:
Dominik Obrist, Barna Errol Mario Becsek, Maria Giuseppina Chiara Nestola, Hadi Zolfaghari, Patrick Zulian, Rolf Krause, Dario De Marinis
We present a novel framework inspired by the Immersed Boundary Method for predicting the fluid-structure interaction of complex structures immersed in laminar, transitional and turbulent flows. The key elements of the proposed fluid-structure interac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::355b1058390fcdf1b3e62a142d3dc426
http://hdl.handle.net/11589/241302
http://hdl.handle.net/11589/241302
Publikováno v:
Journal of Fluid Mechanics
Journal of Fluid Mechanics, Cambridge University Press (CUP), 2013, 724, pp.425-449. ⟨10.1017/jfm.2013.161⟩
Journal of Fluid Mechanics, 2013, 724, pp.425-449. ⟨10.1017/jfm.2013.161⟩
Journal of Fluid Mechanics, Cambridge University Press (CUP), 2013, 724, pp.425-449. ⟨10.1017/jfm.2013.161⟩
Journal of Fluid Mechanics, 2013, 724, pp.425-449. ⟨10.1017/jfm.2013.161⟩
This paper presents an extension of existing works dealing with the dynamics of a passive scalar in freely decaying isotropic turbulence, by accounting for a production mechanism of the passive scalar itself. The physically relevant case of the tempe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::244a7276a4fd70991242dc9f184051c8
https://hal.archives-ouvertes.fr/hal-01298933
https://hal.archives-ouvertes.fr/hal-01298933