Dylan Armfield is a PhD researcher in I-Form based at UCD, focussing on product and process numerical modelling. Dylan completed his bachelors, honours, and master’s degrees in mechanical engineering at the University of Pretoria. His master’s thesis was on computational modelling of the laser-shock peening surface treatment for advanced alloys, including the implementation of physics-based material models to capture the high strain-rate shock waves occurring during the surface treatment process. Dylan is pursuing his PhD in the biomedical engineering field, incorporating both fluid dynamics and solid mechanics to develop better understanding and longevity of aortic valve systems.
Research Interests (Lay Summary)
Dylan started his PhD with I-Form in 2021 and is investigating the fatigue behaviour of aortic valve systems. He will be developing a modelling methodology that will capture the fluid dynamics which drive the movement of the aortic valve as a result of the pulses from the heart. The fluid behaviour will be coupled to a structural model of the valve system, allowing for fatigue analysis of the stent and valve under accurately represented physiological conditions. Representing the valve system flexure through a holistic, multi-physics model could potentially reduce the amount of physical testing for each design iteration, while providing new insights and design improvements for manufacturing. The focus of his work will be on the fluid-structure interactions affecting the cyclic loading on these systems.
The aim of this work is to develop modelling approaches to analyse the fatigue behaviour of aortic valve systems under in-vivo and in-vitro (pulse duplicator) loading conditions. Currently, confident fatigue evaluation is performed on the porcine pericardial valve and NiTi stent through extensive physical testing of the system. The current modelling approach may not fully capture the flow and structural deformation intricacies that are representative of physiological conditions.
The development of a simulation approach that would more realistically capture the physiological loading through coupled fluid-structure interaction which will allow the fatigue life of the device to be considered virtually during the design phase. This has the potential to reduce the amount of physical testing required and hence accelerate the design process. In addition, the added insight provided by the new models will contribute to the development of improved devices, both with respect to structural integrity and optimal flow design.