Campos Marin, A., Grossi, T., Bianchi, E. et al. (2 more authors) (2016) 1.2D µ-Particle Image Velocimetry and Computational Fluid Dynamics Study Within a 3D Porous Scaffold. Annals of Biomedical Engineering. ISSN 0090-6964
Abstract
Transport properties of 3D scaffolds under fluid flow are critical for tissue development. Computational fluid dynamics (CFD) models can resolve 3D flows and nutrient concentrations in bioreactors at the scaffold-pore scale with high resolution. However, CFD models can be formulated based on assumptions and simplifications. μ-Particle image velocimetry (PIV) measurements should be performed to improve the reliability and predictive power of such models. Nevertheless, measuring fluid flow velocities within 3D scaffolds is challenging. The aim of this study was to develop a μPIV approach to allow the extraction of velocity fields from a 3D additive manufacturing scaffold using a conventional 2D μPIV system. The μ-computed tomography scaffold geometry was included in a CFD model where perfusion conditions were simulated. Good agreement was found between velocity profiles from measurements and computational results. Maximum velocities were found at the centre of the pore using both techniques with a difference of 12% which was expected according to the accuracy of the μPIV system. However, significant differences in terms of velocity magnitude were found near scaffold substrate due to scaffold brightness which affected the μPIV measurements. As a result, the limitations of the μPIV system only permits a partial validation of the CFD model. Nevertheless, the combination of both techniques allowed a detailed description of velocity maps within a 3D scaffold which is crucial to determine the optimal cell and nutrient transport properties.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Springer Verlag. This is an author produced version of a paper subsequently published in Annals of Biomedical Engineering. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Computational model; Imaging; Mass transport properties; Microfluidics; Tissue engineering scaffolds |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN RESEARCH COUNCIL MECHANOBIO - 258321 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Dec 2016 16:46 |
Last Modified: | 12 Dec 2017 01:38 |
Published Version: | http://doi.org/10.1007/s10439-016-1772-6 |
Status: | Published |
Publisher: | Springer Verlag |
Refereed: | Yes |
Identification Number: | 10.1007/s10439-016-1772-6 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109538 |