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Adjoint-based shape optimization for the minimization of flow-induced hemolysis in biomedical applications
Citation Link: https://doi.org/10.15480/882.3659
Publikationstyp
Journal Article
Date Issued
2021-07-02
Sprache
English
Author(s)
Institut
TORE-DOI
TORE-URI
Volume
15
Issue
1
Start Page
1095
End Page
1095
Citation
Engineering applications of computational fluid mechanics 15 (1): 1095-1112 (2021)
Publisher DOI
Scopus ID
ArXiv ID
Publisher
CSE Dept., the H.K. PolyU
This paper reports on the derivation and implementation of a shape optimization procedure for the minimization of hemolysis induction in biomedical devices. Hemolysis is a blood damaging phenomenon that may occur in mechanical blood-processing applications where large velocity gradients are found. An increased level of damaged blood can lead to deterioration of the immune system and quality of life. It is, thus, important to minimize flow-induced hemolysis by improving the design of next-generation biomedical machinery. Emphasis is given to the formulation of a continuous adjoint complement to a power-law hemolysis prediction model dedicated to efficiently identifying the shape sensitivity to hemolysis. The computational approach is verified against the analytical solutions of a benchmark problem and computed sensitivity derivatives are validated by a finite differences study on a generic 2D stenosed geometry. The application included addresses a 3D ducted geometry which features typical characteristics of biomedical devices. An optimized shape, leading to a potential improvement in hemolysis induction up to 22%, is identified. It is shown, that the improvement persists for different, literature-reported hemolysis-evaluation parameters.
Subjects
Computational fluid dynamics(CFD)
adjoint-based shape optimization
biomedical design
hemolysis minimization
DDC Class
530: Physik
Funding Organisations
Freie und Hansestadt Hamburg
More Funding Information
The current work is a part of the research training group “Simulation-Based Design Optimization of Dynamic Systems Under Uncertainties” (SENSUS) funded by the state of Hamburg under the aegis of the Landesforschungsförderungs-Project LFF-GK11. Selected computations were performed with resources provided by the North-German Supercomputing Alliance (HLRN). This support is gratefully acknowledged by the authors.
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