Conference Agenda

Intracranial aneurysms are strongly influenced by local hemodynamics, motivat-ing the combined use of computational fluid dynamics (CFD) and experimental validation techniques such as particle image velocimetry (PIV). However, PIV velocity measurements in aneurysm models are often affected by a wide dynamic range and reduced accuracy close to the boundaries, limiting direct comparison with numerical predictions. In this paper, a new post-processing methodology is proposed to enhance the reliability of PIV-derived velocity fields and enable con-sistent validation of CFD results in idealized single-vessel aneurysm geometry. A rigid transparent PDMS phantom of a giant saccular aneurysm was realized using a lost core casting technique and tested in a steady-flow loop with refractive-index-matched working fluid. PIV acquisitions were performed using multiple inter-frame time intervals to capture both high-velocity regions in the parent ves-sel and low-velocity recirculation inside the sac. A novel iterative filtering strate-gy based on skewness reduction and percentile trimming was developed to re-move outliers, followed by a spatial stitching algorithm that com-bines multiple time interval acquisition datasets into a single composite velocity magnitude map. The resulting experimental velocity fields showed improved consistency across the full velocity range and enabled meaningful comparison with RANS CFD simulations, supporting the proposed framework as a robust benchmark method-ology for aneurysm hemodynamic validation.