Geers, AJ, Larrabide, I, Morales, HG et al. (1 more author) (2014) Approximating hemodynamics of cerebral aneurysms with steady flow simulations. Journal of Biomechanics, 47 (1). pp. 178-185. ISSN 0021-9290
Abstract
Computational fluid dynamics (CFD) simulations can be employed to gain a better understanding of hemodynamics in cerebral aneurysms and improve diagnosis and treatment. However, introduction of CFD techniques into clinical practice would require faster simulation times. The aim of this study was to evaluate the use of computationally inexpensive steady flow simulations to approximate the aneurysm's wall shear stress (WSS) field. Two experiments were conducted. Experiment 1 compared for two cases the time-averaged (TA), peak systole (PS) and end diastole (ED) WSS field between steady and pulsatile flow simulations. The flow rate waveform imposed at the inlet was varied to account for variations in heart rate, pulsatility index, and TA flow rate. Consistently across all flow rate waveforms, steady flow simulations accurately approximated the TA, but not the PS and ED, WSS field. Following up on experiment 1, experiment 2 tested the result for the TA WSS field in a larger population of 20 cases covering a wide range of aneurysm volumes and shapes. Steady flow simulations approximated the space-averaged WSS with a mean error of 4.3%. WSS fields were locally compared by calculating the absolute error per node of the surface mesh. The coefficient of variation of the root-mean-square error over these nodes was on average 7.1%. In conclusion, steady flow simulations can accurately approximate the TA WSS field of an aneurysm. The fast computation time of 6 min per simulation (on 64 processors) could help facilitate the introduction of CFD into clinical practice.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Cerebral aneurysm; Hemodynamics; Computational fluid dynamics; Steady; Pulsatile |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 31 Jan 2019 15:07 |
Last Modified: | 31 Jan 2019 15:07 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jbiomech.2013.09.033 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141881 |