Background: Abdominal aortic aneurysms (AAAs) present a formidable public health concern due to their propensity for localized, anomalous expansion of the abdominal aorta. These insidious dilations, often in their early stages, mask the life-threatening potential for rupture, which carries a grave prognosis. Understanding the hemodynamic intricacies governing AAAs is paramount for predicting aneurysmal growth and the imminent risk of rupture. Objective: Our extensive investigation delves into this complex hemodynamic environment intrinsic to AAAs, utilizing comprehensive numerical analyses of the physiological pulsatile blood flow and realistic boundary conditions to explore the multifaceted dynamics influencing aneurysm rupture risk. Our study introduces novel elements by integrating these parameters into the overall context of aneurysm pathophysiology, thus advancing our understanding of the intricate mechanics governing their evolution and rupture. Methods: Conservation of mass and momentum equations are used to model the blood flow in an AAAs, and these equations are solved using a finite volume-based ANSYS Fluent solver. Resistance pressure outlets following a three-element Windkessel model were imposed at each outlet to accurately model the blood flow and the AAAs’ shear stress. Results: Our results uncover elevated blood flow velocities within an aneurysm, suggesting an augmented risk of future rupture due to increased stress in the aneurysm wall. During the systole phase, high wall shear stress (WSS) was observed, typically associated with a lower risk of rupture, while a low oscillatory shear index (OSI) was noted, correlating with a decreased risk of aneurysm expansion. Conversely, during the diastole phase, low WSS and a high OSI were identified, potentially weakening the aneurysm wall, thereby promoting expansion and rupture. Conclusion: Our study underscores the indispensable role of computational fluid dynamic (CFD) techniques in the diagnostic, therapeutic, and monitoring realms of AAAs. This body of research significantly advances our understanding of aneurysm pathophysiology, thus offering pivotal insights into the intricate mechanics underpinning their progression and rupture, informing clinical interventions and enhancing patient care.

Utilizing a computed tomography (CT)‐based realistic nasal‐to‐lung respiratory tract model allows for a comprehensive investigation of the transport and deposition of nasal sprayed aerosols. This study has three main objectives: first, to determine the optimal mesh that achieves the quickest convergence for computational fluid‐particle dynamics (CFPD) simulations of a nasal‐to‐lung nasal respiratory tract by assessing the performance of different element types, sizes, and prism boundary layers; second, to design and validate a numerical method to compare grid data with different mesh structures and densities for simulation result validation; and finally, to observe and analyze fluid‐particle dynamics in the respiratory tract to aid in the development of nasal sprayed medications. This study involves reverse‐engineering a realistic and anatomically accurate respiratory tract model from CT scans. Results reveal that the optimal numerical approach for minimum calculation time is the polyhedral hybrid mesh with four boundary prism layers and the SIMPLE pressure‐velocity coupling scheme. Furthermore, observations of particle dynamics reveal that the vocal cords' location contains a concentration site of deposited small aerosols due to the turbulent airflow in the region. The optimal diameters of nasal sprayed aerosols to target each region are concluded in the end.

Continuous high-frequency oscillation (CHFO) is used clinically as an adjunct for airway clearance and lung expansion, yet its pressure and shear distribution within human conducting airways remains poorly quantified. To better understand these flow mechanics, we created a patient-specific, CT-derived airway model (nasal and oral cavity to the 13th lung generation) and performed transient RANS simulations with k-ω SST turbulence closure on a 7.75 million cell hybrid mesh. A slow-breathing waveform was combined with 3 Hz oscillatory pressure input representative of a MetaNeb® system, and two therapeutic settings were compared: A standard CHFO mode and a high-pressure CHFO mode. We analyzed instantaneous and phase-averaged velocity, static pressure, wall shear stress, area-averaged pressure, time-averaged pressure and wall-normal force. The results show that anatomy fixes "hot spots" of mechanical loading: A persistent laryngeal jet generates local static-pressure minima and elevated shear, while the broader nasal-pharyngeal cavities carry the highest global wall-normal forces. In addition, distal generations experience tightly phase-locked pressures with modest proximal-to-distal gradients within the modeled conducting airways, indicating limited axial attenuation of oscillatory forcing over the resolved G0-G13 airway segment. Switching to high-pressure CHFO uniformly elevates mean and RMS airway pressures, increases wall-normal forces by ∼15-30% and extends exposure to values greater than 25 cmH₂O, yet pre65serves the spatial hierarchy of pressure and shear. These findings describe how CHFO-representative forcing reshapes pressure, shear, and wall-normal loading within the resolved rigid-wall conducting-airway model, from more phasic loading under standard CHFO to more tonic loading under high-pressure CHFO, while preserving an anatomy-defined spatial hierarchy within the model.