Xinlei Huang

In extremely cold environments, inhaling frigid, dry air can pose significant health risks, potentially leading to airway inflammation and respiratory injury. While previous studies have examined thermal exchange within lung airways under hot-air inhalation, the majority have focused on localized regions rather than the entire respiratory tract. This study expands the scope of inquiry by simulating airflow and heat transfer throughout a more complete computed tomography (CT)-based respiratory tract, from the nasal cavity to the larynx and trachea and extending down to the 13th generation of the bronchial tree, under two cold-air inhalation scenarios at −5 °C and −20 °C. Using computational fluid dynamics, this study integrates Large Eddy Simulation with the Smagorinsky–Lilly subgrid-scale model to capture the complex interaction of turbulent flow and thermal transport in the human respiratory system. By analyzing temperature distributions, heat flux, heat-transfer coefficients, Nusselt numbers, and mass flux across the airways, the research shows how varying degrees of cold inhalation influence respiratory thermodynamics and associated biomechanical responses. As such, this study establishes a rigorous scientific foundation for the development of more sophisticated and predictive respiratory-tract models in sub-zero environments in future work.

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.

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.