Research Projects

Aortic aneurysms are life-threatening vascular conditions characterized by localized dilations of the arterial wall, often progressing silently until rupture. The proposed postdoctoral research aims to enhance the understanding and risk assessment of aneurysms by developing a digital twin—a computational replica of patient-specific aneurysmal conditions—through a combination of experimental and numerical hemodynamic analysis. The research is structured around creating compliant physical models of abdominal aortic aneurysms (AAA) and conducting Particle Image Velocimetry (PIV) to visualize and quantify flow dynamics under pulsatile conditions. The fabricated silicone-based phantoms will replicate physiological compliance and will be tested within a controlled mock circulatory loop. This experimental setup enables the acquisition of high-resolution flow fields critical to validating computational models. In parallel, 3D Computational Fluid Dynamics (CFD) simulations will be performed using ANSYS Fluent, employing realistic inlet waveforms and boundary conditions. These simulations will be benchmarked against the experimental PIV data, focusing on key hemodynamic indicators such as wall shear stress (WSS), oscillatory shear index (OSI), and vortical structures, all of which are strongly implicated in aneurysm progression and rupture. The integrated data from experiments and simulations will be used to train a neural network model, forming the core of the digital twin. This AI-driven framework will allow rapid prediction of hemodynamic patterns and rupture risks based on geometry and flow conditions, potentially guiding clinical decision-making and reducing the need for invasive diagnostics. The research is methodically planned over two years. The first year involves literature review, CAD modeling, model fabrication, preliminary simulations, and flow loop testing. The second year focuses on extensive simulations, parametric studies, validation, digital twin development, and dissemination of findings. The key outcomes of this research include: • A validated workflow integrating experimental and computational modeling of AAA, • Quantified hemodynamic markers associated with aneurysm growth and rupture risk, • A trained neural network model capable of simulating patient-specific hemodynamics, • And a functional digital twin prototype for non-invasive aneurysm assessment. This work has the potential to significantly impact biomedical device design, vascular diagnostics, and personalized medicine by providing clinicians with a reliable tool for pre-intervention planning and long-term patient monitoring.