Bulletin of the American Physical Society
72nd Annual Meeting of the APS Division of Fluid Dynamics
Volume 64, Number 13
Saturday–Tuesday, November 23–26, 2019; Seattle, Washington
Session A29: Biological Fluid Dynamics : Respiratory Flows I |
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Chair: Jean-François Louf, Princeton University Room: 611 |
Saturday, November 23, 2019 3:00PM - 3:13PM |
A29.00001: Modeling of Indoor Airborne Disease Transmission via Human Expiratory Activities Sima Asadi, Anthony Wexler, Nicole Bouvier, William Ristenpart Infectious disease transmission between humans by expelled respiratory aerosol particles persists as an important public health issue. Coughing, sneezing, speaking, and breathing are all known to cause micron-scale infectious particles to be emitted into the air, but it remains unclear which expiratory activities contribute most heavily to airborne disease transmission. Here, we use a transient eddy diffusion model with an isotropic turbulent diffusivity to predict the spread of pathogens in an indoor environment. We implement this model to assess the probability of transmission to a nearby susceptible individual when a single infector (a point source) releases pathogen-laden aerosol particles into the air while breathing, speaking, coughing, or sneezing. We also investigate how the presence of``speech superemitters,'' individuals who release an order of magnitude more aerosol particles than others, affect the probability of transmission. Our results suggest that in some circumstances speaking can lead to higher probabilities of transmission than coughing and sneezing. [Preview Abstract] |
Saturday, November 23, 2019 3:13PM - 3:26PM |
A29.00002: Scaled experiments for improving diagnosis of pathological lower airway obstruction Chang Liu, Kenneth Kiger, Daniel Hariprasad, Anders Wallqvist, Jaques Reifman Many lung diseases are characterized by obstructed airflow, particularly, in the lower airway. To explore the detectability of wake structures in the trachea due to regionalized lower-airway obstructions, a transparent patient-specific lung model, resolved down to the 5th daughter branches and scaled up to 1.8 times the human size, was constructed. 5 independently controlled piston pumps are used to prescribe the flowrate to the different lung lobes, simulating constant exhalation processes with both healthy and diseased/obstructed lobar flow fractions. Quantification of the complex 3D flow in the lower trachea is achieved by conducting stereo PIV measurements in both the coronal and transverse planes at different elevations. The Reynolds number is maintained at the lowest end of the physiology range (around 584, based upon the bulk flowrate and the tracheal diameter). Notable differences in the tracheal velocity profiles among different flow conditions were discovered and quantified by utilizing the method of proper orthogonal decomposition. The wake structures due to deficit flow in each single lobe are presented and their formations are discussed. These results will be used to discuss a potential means to identify a pathological flow condition using non-intrusive diagnostics. [Preview Abstract] |
Saturday, November 23, 2019 3:26PM - 3:39PM |
A29.00003: Experimental Evaluation of Dust Mask Performance Sejin Choi, Ryeol Park, Namkeon Hur, Wonjung Kim The fine dust in contaminated air can accumulate in the respiratory organs in the human body and cause various diseases. Various types of masks for filtering fine dust are commercially available. Given the trade-off between the filtering performance and wearing comfort, the physical understanding of respiratory mechanics through a mask is important in assessing the performance of the masks in mask design. We suggest an experimental setup to evaluate the filtering performance and wearing comfort of dust masks. By constructing a respiration simulator, we measure dust particles that are filtered by a mask and quantify the respiratory resistance in terms of the power required for respiration. We analyze the effects of additional elements such as fans and valves attached to the mask to assist respiration. [Preview Abstract] |
Saturday, November 23, 2019 3:39PM - 3:52PM |
A29.00004: Computational analysis of airflow dynamics for predicting collapsible sites in the upper airways: Advanced machine learning Susie Ryu, Seung Ho Yeom, Young Woo Kim, Joon Sang Lee, Hyung Ju Cho, Yoon Jeong Choi, Hwi Dong Jung Recently, the number of patients who undergo orthodontic treatment of sleep apnea is increasing. Existing diagnostic methods, the polysomnography (PSG), however, have not been able to provide quantitative criteria and the non-scientific judgment method. Moreover, it is uncomfortable method to patent. In order to solve these problems, people try to use computational fluid dynamics (CFD) using upper airway geometry from the computed tomography (CT) data. The patients who have sleep apnea have considerable pressure drop is occurred due to a narrow airway. This feature is the main indicator of that used to determine the patient has OSAS or not. This study makes CFD models of upper airway for increasing the quantity of airway model data and simulate it to get aerodynamic features. Because of the requiring of heavy computational time cost, this study uses a machine learning algorithm. We use multivariate gaussian process machine learning for predicting aerodynamic features of unknown patents. This method can eliminate the high time consuming of CFD computation time. Also, we use Support vector machine learning algorithm to classify between normal and moderate OSAS patient. This algorithm classification showed about 80\% classification accuracy that can be useful decision to clinician. [Preview Abstract] |
Saturday, November 23, 2019 3:52PM - 4:05PM |
A29.00005: Elasto-capillary network dynamics of inhalation Felix Kratz, Jean-Francois Louf, Anvitha Sudhakar, Nathanael Ji, Sujit Datta The seemingly simple process of inhalation relies on the complex interplay between muscular contraction in the thorax, elasto-capillary interactions in the individual airway branches, connectivity between different branches, and overall air flow into the lungs. Sophisticated pulmonary fluid dynamics models have been developed to elaborate the competition between capillarity, which tends to keep flexible branches closed, and elasticity, which favors opening, for single airway branches. However, a quantitative model combining the physiological opening process of flexible airway branches with the biomechanics and interconnected geometry of the lungs is still missing. To address this issue, we develop a statistical model of the lungs as a symmetrically-branched network of liquid-lined flexible cylinders coupled to a viscoelastic thoracic cavity. Each branch opens at a rate and a pressure that is determined by input biomechanical parameters, enabling us to test the influence of changes in the mechanical properties of lung tissues and secretions on inhalation dynamics. By summing the dynamics of all the individual branches, we quantify the evolution of overall lung pressure and volume during inhalation, and find good agreement with typical breathing curves obtained in the literature. [Preview Abstract] |
Saturday, November 23, 2019 4:05PM - 4:18PM |
A29.00006: Effect of Cartilaginous Rings in a Model of Human Trachea with Stenosis Humberto Bocanegra Evans, José Montoya Segnini, Ali Doosttalab, Joehassin Cordero, Luciano Castillo The human trachea is structurally supported by a series of cartilaginous rings, which introduce corrugations along the wall surface. Nevertheless, the airway walls are generally considered smooth for respiratory fluid dynamics research purposes. Previous results by Bocanegra Evans and Castillo (J. Biomech., 49, 1601, 2016) demonstrate that these rings have a significant impact on the flow separation found in the tracheobronchial bifurcation. Here, we study the effect that such rings have in a trachea model with stenosis. We present an experimental comparison of smooth and `ringed' models with a grade II (70{\%} blockage) stenotic contraction. Particle image velocimetry measurements are carried out in a refractive index-matching facility simulating resting breathing state conditions (ReD $=$ 3,350). Our results show that cartilaginous rings induce velocity fluctuations in the downstream flow, which enhances the near-wall momentum flux and reduces flow separation after the stenosis. The maximum upstream velocity of the recirculation is reduced by 38{\%} in the model with rings, resulting in a weaker recirculation zone. These results highlight the importance of the cartilaginous rings---and other small features---in respiratory flows. [Preview Abstract] |
Saturday, November 23, 2019 4:18PM - 4:31PM |
A29.00007: Analysis of Inlet Velocity Profile Effects on Airflow Simulations in Patient-Specific Healthy Trachea Bipin Tiwari, Tarun Kore, Zhenglun Alan Wei, Sandeep Bodduluri, Surya P. Bhatt, Vrishank Raghav Expiratory Central Airway Collapse (ECAC), defined by greater than 50{\%} collapse of the trachea during expiration, is a disorder associated with Chronic Obstructive Pulmonary Disease. Pathophysiology of ECAC is multifactorial and the biofluid mechanics of airflow in the trachea could be an important factor resulting in the progression of the disease. Using computational methodology, a comprehensive investigation of the biofluid mechanics in the healthy and diseased patient-specific trachea can be conducted. One of the key considerations for setting up computations is choosing correct boundary conditions (BC). Most common BCs used by previous studies are a) flat, b) parabolic, c) Womersley, d) parabolic with an extension, and e) real, patient-specific profile. This is the first step in that direction to explore the effects of different inlet BCs for patient-specific trachea flow simulations. We test for steady and tidal flow combined with the five aforementioned inlet velocity profile conditions. Metrics such as wall shear stress and time-averaged wall shear stress were used to quantify the differences among different inlet velocity profile condition. This will lay a solid foundation towards obtaining accurate computational results in modeling ECAC. [Preview Abstract] |
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