Adjoint-based Shape Optimization for the Minimization of Flow-induced Hemolysis in Biomedical Applications

TL;DR

This paper develops an adjoint-based shape optimization method to reduce flow-induced hemolysis in biomedical devices, demonstrating up to 22% improvement in blood damage reduction through computational optimization.

Contribution

It introduces a continuous adjoint approach for shape optimization targeting hemolysis minimization in biomedical flows, validated against analytical and finite difference methods.

Findings

Validated the adjoint sensitivity approach with benchmark problems.

Achieved up to 22% reduction in hemolysis in optimized geometries.

Demonstrated robustness across different hemolysis parameters.

Abstract

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.