This ANSYS Fluent tutorial shows you exactly how to simulate magnetic nanoparticles in arteries using simple computer models. Magnetic drug delivery is becoming super important for treating diseases like cancer and blood clots. By adding magnetic nanoparticles to medicines, doctors can guide drugs exactly where they’re needed in the body using magnets. This guide teaches you how to use ANSYS Fluent with a special combination of User-Defined Functions (UDF) and the Discrete Phase Model (DPM) to track nanoparticle movement through blood vessels. You’ll learn how magnetic forces affect particle trajectories in arterial flow and how to predict where the nanoparticles will go. This type of CFD simulation helps design better targeted drug delivery systems that put medicine exactly where it’s needed. The tutorial covers everything from setting up the blood flow model to adding magnetic field effects on the nanoparticles. Even though ANSYS Fluent’s standard tools have limitations for localized magnetic fields, our approach using UDF-DPM solves this problem completely. Whether you’re studying biomedical engineering or developing new nanomedicine treatments, this easy-to-follow guide makes complex magnetic nanoparticle simulations simple to understand and use in your work. We took the guidance from the reference paper:

• Reference [1]: Lunnoo, Thodsaphon, and Theerapong Puangmali. “Capture efficiency of biocompatible magnetic nanoparticles in arterial flow: A computer simulation for magnetic drug targeting.” Nanoscale research letters10 (2015): 1-11.

Figure 1: Forces acting on drug particles in the presence of a magnetic field

We built our artery model by using Plot Digitizer to get exact points from medical pictures of real arteries. This gave us the right shape with all the branches. After making the model, we created a mesh to split it into small pieces that the computer can solve. Since the normal MHD tool in ANSYS Fluent doesn’t work well for our needs, we wrote a special User-Defined Function (UDF) to add magnetic forces only in specific spots. Our simulation needed to track both the blood flow and the magnetic nanoparticles moving in it. For this, we used the Discrete Phase Model (DPM) in Fluent, which lets us follow thousands of tiny particles as they move with the blood. Our UDF needed three User-Defined Memory locations (UDM) to keep track of different things: one for the flow field, one for temperature effects, and one for the DPM particles. This way, we could see exactly where the magnetic nanoparticles go when pushed by both the blood flow and the magnetic field.

Post-processing

Figure 1 shows how the magnetic field is affecting the blood in our artery model. The bright red spot (about 0.00022) shows where the magnetic force pulls strongest in one direction, while the nearby blue area (-0.00021) shows force pulling in the opposite direction. This creates a kind of magnetic “trap” that catches nanoparticles as they flow past. We placed this magnetic field right at a branch point in the artery to see how it affects particle movement at these critical locations. The clear separation between red and blue areas proves our UDF is working properly to create a realistic magnetic field gradient.

Figure 2: Lorentz Force Distribution (User Memory 0)

The second image reveals something very important – it shows where the magnetic nanoparticles actually end up. The highest concentrations (shown in yellow and red, around 2.4e-06 kg/m³) appear exactly where the magnetic field is strongest. This proves our magnetic targeting is working! The particles are being pulled out of the normal blood flow path and concentrated in specific areas. Notice how some particles have also traveled into smaller branches after the main targeting area – this happens because once particles pass through the magnetic field, they return to following the blood flow. This kind of simulation helps doctors figure out exactly where to place magnets outside the body to deliver medicine to specific spots inside arteries. The final image shows very small secondary effects (notice the scale is only 2.3e-11) that happen when the magnetic field interacts with electrically conducting blood. These tiny swirls and patterns might seem unimportant, but they help mix the nanoparticles with the blood, which can improve how well medicines get delivered to artery walls. The highest values appear right in the branch where the main magnetic field is applied. This detailed information about secondary flows is something physical experiments can’t easily measure, showing why CFD simulation is so valuable for designing new magnetic drug delivery systems.

Figure 3: User Memory 2 for displaying Brownian and magnetic forces

Figure 4: Nanoparticle Concentration (DPM Concentration)