Magnetic Field Effect on Arterial Flow CFD Simulation – ANSYS Fluent Tutorial
Magnetic Field Effect on Arterial Flow CFD Simulation – ANSYS Fluent Tutorial
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Ever wonder how magnetic fields affect blood flow in your arteries? This ANSYS Fluent tutorial shows you how to simulate magnetic field effects on arterial flow using simple CFD techniques. Blood flow behaves in special ways when exposed to magnetic fields, which matters for medical devices and treatments. Using ANSYS Fluent with a custom User-Defined Function (UDF), you can model these magnetohydrodynamic effects even though the built-in MHD module has some problems. This guide walks through setting up a complete blood flow simulation with a locally applied magnetic field to see how the Lorentz force changes the flow patterns in arterial geometry. Magnetic field simulation helps doctors and engineers design better MRI-compatible devices, understand blood flow disruption during imaging, and develop new magnetic treatments for cardiovascular disease. Whether you’re studying hemodynamics or designing medical equipment, this step-by-step arterial flow CFD tutorial makes complex magnetohydrodynamic blood flow modeling easy to understand. Learn how blood velocity profiles change under magnetic influence and why these effects matter for cardiovascular health. In our stydt path, the following reference paper has been our guide:
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 letters 10 (2015): 1-11.
Figure 1: Locally magnetic field applied around the artery
Simulation process
We made our artery model by finding points from real artery pictures using Plot Digitizer software. This gave us the exact shape of a real artery with branches. After building the model, we made a mesh (grid) to break it into small pieces for the computer to solve. We ran into a problem – the built-in MHD module in ANSYS Fluent doesn’t work well for locally applied magnetic fields like we needed. So, we wrote a special User-Defined Function (UDF) that adds extra forces to the equations that control fluid flow. This trick lets us see how a magnetic field affects blood flow in just one part of the artery. We also turned on the heat transfer option to see how temperatures change. Our UDF puts the magnetic force only in one spot instead of everywhere, which is more like real medical situations.
Post-processing
Figure 2 shows where the magnetic field is pushing on the blood. The bright orange-red spot in the middle shows where the magnetic force is strongest (around 0.00019). Right near it is a blue area showing where the force pushes in the opposite direction (-0.00022). This proves our UDF is working correctly – the magnetic field only affects blood in one small area, not the whole artery. This local effect is important because in real medical treatments, doctors often need to target just one trouble spot in an artery. The temperature picture shows how blood heats up when affected by the magnetic field. Normal blood temperature starts at 300K (blue), but rises up to 309K (red) in areas where the magnetic field slows down the flow. Look at how the temperature is highest near the walls – this happens because the magnetic force creates friction there. The velocity picture confirms this pattern, showing blood moving fastest (red, 0.039 m/s) in the center of the main artery and slowing down (blue, 0-0.004 m/s) in the smaller branches. Notice how the velocity pattern changes right where the magnetic field is applied. This proves that magnetic fields can significantly change blood flow patterns – slowing it down in some places and speeding it up in others. This kind of information helps doctors understand how MRI machines might affect blood flow in patients with heart problems.
Figure 2: Lorentz Force Distribution (User Memory 0)
Figure 3: Temperature and Velocity Distribution
We pride ourselves on presenting unique products at CFDLAND. We stand out for our scientific rigor and validity. Our products are not based on guesswork or theoretical assumptions like many others. Instead, most of our products are validated using experimental or numerical data from valued scientific journals. Even if direct validation isn’t possible, we build our models and assumptions on the latest research, typically using reference articles to approximate reality.
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