BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Nico Dirkes (RWTH Aachen) DTSTART:20260622T110000Z DTEND:20260622T123000Z DTSTAMP:20260705T165130Z UID:NSCM/217 DESCRIPTION:Title: C omputational Prediction of Red Blood Cell Damage: Mathematical Modeling an d Uncertainty Quantification\nby Nico Dirkes (RWTH Aachen) as part of Nečas Seminar on Continuum Mechanics\n\nLecture held in Room K6\, Facult y of Mathematics and Physics\, Charles University\, Sokolovská 83 Prague 8..\n\nAbstract\nComputational simulations have become an important tool for the design of mechanical circulatory support devices as well as surgic al planning ahead of implantation. While computational fluid dynamics can accurately predict flow fields\, the prediction of hemolysis (red blood ce ll damage) remains challenging. Absolute predictions of hemolysis indices often deviate by multiple orders of magnitude from experimental measuremen ts. This discrepancy can be attributed to two issues. First\, most existin g models for hemolysis employ a simple power law relationship between shea r stress\, exposure time\, and hemolysis index\, with model parameters fit ted to experimental data. Second\, experimental data often exhibits large variability between donors and between studies\, leading to significant un certainty in the fitted model parameters. This is due to individual differ ences in red blood cell properties and high sensitivity to experimental co nditions. Consequently\, the predictive capabilities of these models are l imited\, especially when applied to flow conditions that differ from those used in experiments.\n\nWe propose a two-sided approach to enhance the pr edictive capabilities of hemolysis models. First\, we introduce a more phy siological model that incorporates two important effects of the red blood cell membrane: viscoelastic deformation and pore formation. We highlight t he differences between the Lagrangian and Eulerian model formulations. The Eulerian formulation enables a stabilized finite element discretization\, which we apply to various benchmark cases. Second\, we show how uncertain ty quantification techniques can be employed to account for the variabilit y in experimental data when fitting model parameters. This facilitates the integration of new experimental data as it becomes available\, thereby en abling patient-specific predictions of hemolysis. Overall\, this two-sided approach allows for more accurate and uncertainty-aware predictions of he molysis to support the development process of future generations of biomed ical devices.\n\nNote that we meet in the lecture hall K6.\n LOCATION:https://researchseminars.org/talk/NSCM/217/ END:VEVENT END:VCALENDAR