Liam
N Rochet

Fabrication of Patient-Specific Compliant Aorta model for In Vitro Flow Experiments STEM

Abstract profile. Full document pending author claim.

Authors:

Liam N Rochet

Date Created:

Not specified

Course Title:
Professor:

Not specified

About Paper:

The ability to accurately simulate the behavior of blood flow within human organs is essential for advancing cardiovascular research. Despite the availability of computational modeling options, physical models are the most accurate in terms of replicating and simulating real operations. This project is focused on fabricating a realistic model of the aorta using a mold-silicone casting method for use in in vitro flow experiments. The model replicates the complex geometry and physical properties of the aorta, enabling future validation through particle tracking velocimetry and 4D Flow MRI. We aim to show that this method offers a practical representation of the aortic structure that can support accurate flow measurements, something that many other aorta models lacked in prior research. The first step involves a manipulation process on the Solidworks and Meshmixer software packages, ensuring the proper wall thickness and other characteristic features of the aorta. From this computational blueprint, the inner core and outer molds are fabricated using 3D printing. Once generated, the molds and core are connected, and silicone is cast in the space between. The silicone is then cured to form the final model, and the molds and core are dissolved using acetone. Once this fabrication process is complete, the model is inspected to analyze the dimensional accuracy, overall uniformity, and other physical characteristics. We expect that the resulting aorta model will exhibit physiologically relevant functional properties. Ultimately, our process and production of the model could offer a practical solution for medical training and future vascular model applications. Keywords: Aorta Model; Silicone Casting; Flow Visualization; Particle Tracking Velocimetry; 4D Flow MRI

Source:

Purdue University / 2025

Topics:

No topics listed

Co-authors:

Liam N Rochet

0