Mechanics, Modeling and Simulation of Aortic Dissection

Unknown Cauchy shear stress vs amount of shear curves for dissected human thoracic aortas under "in-plane" shear.

Unknown Schematic overview of the eXtended Finite Element Method: Crack is within elements and considered by enrichment functions at selected nodes.

In the Lead project a consortium of scientists from biomechanical-, civil-, electrical-, and mechanical engineering, computer science, mathematics, and physics from TU Graz has set itself the goal of unraveling the cause and the formation of the various stages of an aortic dissection (AD). Advanced computational tools and algorithms will be developed to assist clinicians with the diagnosis, treatment, and management of AD patients. In addition, related topics such as the optimization of implants, the better design for tissue engineering and of coatings and stent platforms for drug delivery will be investigated.

In particular, new multiscale constitutive models that include innovative parameters and failure criteria will be developed, which will allow the simulation of the rupture of aortic tissue and propagation of the false lumen. The development of thrombus in the false lumen will be modeled by using the theory of porous media, while the blood will be modeled as a non-Newtonian fluid. The 3D geometry of patient-specific morphologies will be reconstructed from medical images of carefully selected AD patients. Finally, computational fluid-structure interaction simulations will be performed in order to investigate the wall stresses, the hemodynamics, the false lumen propagation, and the thrombus formation and growth, etc. In addition, the 3D computational simulation results will be visualized by virtual reality techniques. We expect that this project will improve awareness of this life-threatening disease, and lead to its more effective treatment and control within the general public of Austria and beyond.

The Lead project will be carried out in the frame of the Graz Center of Computational Engineering (GCCE), which has been founded in 2016 as an interdisciplinary cooperation platform for basic research in the realm of computational science and engineering. The mission of GCCE is to improve computational techniques and its applicability by bringing together the expertise of leading scientists form different areas.

Funding: Graz University of Technology