Bubble tracking in arterial line filters is a vital process for keeping patients safe during heart surgery. During a procedure called cardiopulmonary bypass, a machine takes over for the heart and lungs. Sometimes, tiny air bubbles can get into the blood, which is very dangerous. These arterial line filters are special safety nets designed to catch these microbubbles. A good Arterial Line Filters CFD study helps engineers design better filters. Using special tools like the Discrete Phase Model (DPM), a Bubble Tracking CFD simulation lets us watch how these bubbles move through the filter’s porous media without any risk. This helps medical companies create safer devices that protect patients from harm. Our CFD study follows the methods described in the research paper, “Bubble Tracking Through Computational Fluid Dynamics in Arterial Line Filters for Cardiopulmonary Bypass” [1].

• Reference [1]: Fiore, Gianfranco B., et al. “Bubble tracking through computational fluid dynamics in arterial line filters for cardiopulmonary bypass.” ASAIO Journal5 (2009): 438-444.

Figure 1: Schematic of the arterial line filter model used for this CFD for Medical Devices simulation [1].

Simulation Process: Fluent Setup, DPM and Porous Zone Configuration

To begin our Arterial Line Filters CFD analysis, we first created a 3D model of the filter using Design Modeler. Then, using Fluent Meshing, we made a high-quality grid with 1,570,612 tetrahedral cells to accurately capture the blood flow. A very important step was modeling the main filter screen. In ANSYS Fluent, we defined this screen as a porous medium, which acts like a barrier that blood can flow through but that helps trap bubbles. To model the bubbles themselves, we activated the Discrete Phase Model (DPM). This let us inject bubbles of many different sizes, from 10 to 1,000 micrometers, using the Rosin-Rammler distribution method, which is a realistic way to represent the range of bubbles found in medical situations.

Post-processing: CFD Analysis, Visualizing Bubble Capture and Flow Dynamics

The particle tracking results give a clear, professional visual of the filter at work. The colored lines show the paths of many different bubbles as they travel through the filter. This professional visual confirms that the filter design is very effective. We can see that larger bubbles tend to move in straighter lines, while smaller bubbles get caught in the swirling blood flow inside the main chamber. The most important observation is how the porous screen in the middle successfully traps most of the bubbles, preventing them from reaching the outlet pipe. This tracking information is critical for proving that the filter can protect patients from dangerous air emboli.

Figure 2: DPM results from the Bubble Tracking Fluent analysis, showing bubble trajectories and capture by the porous filter.

The velocity contour explains why the filter is so good at catching bubbles. The blood flows very fast in the narrow entrance pipe, up to 2.2 m/s. But once it enters the large filter chamber, the blood slows down a lot. This professional visual shows large blue areas of slow-moving fluid, which is part of the filter’s smart design. This slowing gives the bubbles more time to be pushed into the filter screen by the swirling flow patterns. By combining fast and slow flow zones, the filter creates the perfect conditions to separate bubbles from the blood. The most important achievement of this simulation is the successful use of the DPM and porous media models to show exactly how the filter’s flow dynamics and physical screen work together to capture dangerous microbubbles, providing a validated tool to design safer medical devices and improve patient outcomes during heart surgery.

Figure 3: Velocity streamlines from the Arterial Line Filters CFD analysis, showing the flow patterns that improve bubble capture.