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Publisher DOI: 10.1080/19942060.2021.1943532
arXiv ID: 2101.10715v1
Title: Adjoint-based shape optimization for the minimization of flow-induced hemolysis in biomedical applications
Language: English
Authors: Bletsos, Georgios 
Kühl, Niklas  
Rung, Thomas  
Keywords: Computational fluid dynamics(CFD); adjoint-based shape optimization; biomedical design; hemolysis minimization
Issue Date: 2-Jul-2021
Publisher: CSE Dept., the H.K. PolyU
Source: Engineering applications of computational fluid mechanics 15 (1): 1095-1112 (2021)
Abstract (english): 
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.
DOI: 10.15480/882.3659
ISSN: 1997-003X
Journal: Engineering applications of computational fluid mechanics 
Institute: Fluiddynamik und Schiffstheorie M-8 
Document Type: Article
Project: Simulationsbasierte Entwurfsoptimierung dynamischer Systeme unter Unsicherheiten 
Publikationsfonds 2021 
Funded by: 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.
License: CC BY 4.0 (Attribution) CC BY 4.0 (Attribution)
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