Sonification of Flow Instabilities in CFD Aneurysm Models
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Abstract
Recent investigations using image-based computational flow dynamics (CFD) have revealed turbulent-like blood flow instabilities (hemodynamics) within intracranial cerebral aneurysms and surrounding vasculature, which may contribute to aneurysm initiation, growth, and rupture. We describe a method derived from spectral decomposition of flow for inspecting and characterizing these “turbulent-like” hemodynamic structures in intracranial aneurysms by sonification of CFD generated data. Motivated by auscultation techniques, the current research seeks to address the limitations of conventional CFD animations by allowing the user to listen to complex flow patterns that are often difficult to discern visually. In the process, the proposed method of sonification is successfully applied to a series of datasets resulting from highfidelity numerical simulations of intracranial aneurysms. The resulting framework is shown to be highly efficient in performing parametric sonification in real time.