Figure 3 - uploaded by Junshi Wang
Content may be subject to copyright.
Typical triangular mesh (in red) and computational grid (in blue) employed in the current simulations for the airway-uvula system model.
Source publication
The fluid dynamics of air flow in the pharynx is critical to the vibration of the uvula and to the generation of the snoring sound. In this work, a combined experimental and computational approach was conducted to study the aerodynamics of the flow field in the human airway. An anatomically accurate pharynx model associated with different uvula kin...
Similar publications
Snoring and obstructive sleep apnea (OSA) are often associated with uvula vibrations and pharynx constrictions. However, successful treatment of snoring or accurate diagnosis of OSA has been proven challenging. This study aimed to identify acoustic indexes that were sensitive to underlying airway structural or kinematic variations. Six physiologica...
Snoring and obstructive sleep apnea (OSA) are often associated with uvula vibrations and pharynx constrictions. However, successful treatment of snoring or accurate diagnosis of OSA has been proven challenging. This study aimed to identify acoustic indexes that were sensitive to underlying airway structural or kinematic variations. Six physiologica...
Citations
... Direct numerical simulations (DNS) were implemented to resolve the inspiratory flows with high-frequency uvula oscillations. The immersed boundary method (IBM) was used to control the uvula kinematics based on a Cartesian-grid finite-difference approach (Figure 1d) [49], which has undergone extensive testing in simulations of flapping propulsion for insects [50,51], birds [52,53], fish [54,55], and breathing [56]. In summary, the airway surface with tetrahedral meshes was immersed in a structured hexahedral grid ...
... Direct numerical simulations (DNS) were implemented to resolve the inspiratory flows with high-frequency uvula oscillations. The immersed boundary method (IBM) was used to control the uvula kinematics based on a Cartesian-grid finite-difference approach ( Figure 1d) [49], which has undergone extensive testing in simulations of flapping propulsion for insects [50,51], birds [52,53], fish [54,55], and breathing [56]. In summary, the airway surface with tetrahedral meshes was immersed in a structured hexahedral grid (Figure 1c), with the boundary conditions specified on the immersed surfaces via the ghost-cell approach [57]. ...
This study presents a data-driven approach to identifying anomaly-sensitive parameters through a multiscale, multifaceted analysis of simulated respiratory flows. The anomalies under consideration include a pharyngeal model with three levels of constriction (M1, M2, M3) and a flapping uvula with two types of kinematics (K1, K2). Direct numerical simulations (DNS) were implemented to solve the wake flows induced by a flapping uvula; instantaneous vortex images, as well as pressures and velocities at seven probes, were recorded for twelve cycles. Principal component analysis (PCA), wavelet-based multifractal spectrum and scalogram, and Poincaré mapping were implemented to identify anomaly-sensitive parameters. The PCA results demonstrated a reasonable periodicity of instantaneous vortex images in the leading vector space and revealed distinct patterns between models with varying uvula kinematics (K1, K2). At higher PCA ranks, the periodicity gradually decays, eventually transitioning to a random pattern. The multifractal spectra and scalograms of pressures in the pharynx (P6, P7) show high sensitivity to uvula kinematics, with the pitching mode (K2) having a wider spectrum and a left-skewed peak than the heaving mode (K1). Conversely, the Poincaré maps of velocities and pressures in the pharynx (Vel6, Vel7, P6, P7) exhibit high sensitivity to pharyngeal constriction levels (M1–M3), but not to uvula kinematics. The parameter sensitivity to anomaly also differs with the probe site; thus, synergizing measurements from multiple probes with properly extracted anomaly-sensitive parameters holds the potential to localize the source of snoring and estimate the collapsibility of the pharynx.
... The advantage of this method is that the numerical simulations with complex moving boundaries can be carried out on stationary non-body conformal Cartesian grids and this avoids the cost of the generation of a body-fitted grid at each time step. This approach has been successfully applied to biological flow problems [18][19][20][21], as well as bio-inspired flying [22][23][24] and swimming [25,26]. A detailed description of the sharp-interface method and validation of this solver can be found in Ref. [27,28]. ...
In this paper, a numerical approach combined with experiments is employed to characterize the airflow through the vocal cord. Rabbits are used to perform in vivo magnetic resonance imaging (MRI) experiments and the MRI scan data are directly imposed for the three-dimensional (3D) reconstruction of a 3D high-fidelity model. The vibration modes are observed via the in vivo high-speed videoendoscopy (HSVM) technique, and the time-dependent glottal height is evaluated dynamically for the validation of the 3D reconstruction model. 72 sets of rabbit in vivo high-speed recordings are evaluated to achieve the most common vibration mode. The reconstruction is mainly based on MRI data and the HSVM records are supporting and validate the 3D model. A sharp-interface immersed-boundary-method (IBM)-based compressible flow solver is employed to compute the airflow. The primary purpose of the computational effort is to characterize the influence of the vocal folds that applied to the airflow and the airflow-induced phonation. The vocal fold kinematics and the vibration modes are quantified and the vortex structures are analyzed under the influence of vocal folds. The results have shown significant effects of the vocal fold height on the vortex structure, vorticity and velocity. The reconstructed 3D model from this work helps to bring insight into further understanding of the rabbit phonation mechanism. The results provide potential improvement for diagnosis of human vocal fold dysfunction and phonation disorder.
... The capability of RANS solver in solving unsteady, internal flow problem has been validated by the previous study [8] on human nasal airflow and has been demonstrated by complex biomedical problems [9][10][11][12][13][14][15][16][17][18]. The RANS results of flow speed, turbulence intensity, and pressure were in good agreement with the results from an immersed-boundary-method-based direct numerical simulation solver [19] which has been successfully applied to flow analysis in human snoring [20][21][22]. ...
Pulse-synchronous tinnitus (PST) has been linked to multiple anatomical variants of the venous outflow tract, including transverse sinus (TS) stenosis and sigmoid sinus (SS) dehiscence. It is unknown if the size of diameter in the TS part at the symptomatic side will result in PST. In this study, a combined experimental and computational approach is adopted to study the blood flow during PST. A parametric study is performed on the diameter size of one PST patient at the symptomatic side. A Reynold-averaged-Navier-Stokes (RANS) flow solver is employed in ANSYS Fluent to simulate the symptomatic side at different TS diameter sizes. Results have shown distinct differences in the flow characteristics (including pressure, turbulent kinetic energy (TKE), velocity and shear stress) between the symptomatic side at different TS diameter sizes. The result provides evidence to the hypothesis that anatomic differences can be an important element in affecting blood flow in the venous outflow tract. Resulted findings reveal the strong connection between the flow characteristics of a dehiscent SS and resultant PST. The findings help to understand the flow physics of PST and provide insightful guidance for surgical interventions.
... Significant pressure difference at corresponding regions were found. As expected, the upper wall (red box) in constricted pharynx had higher pressure than in the normal one, while the lower part (blue box) had lower pressure, being consistent with probe pressure results in the previous study (Wang et al., 2018). The upper wall had the lowest pressure at t/T = 0.25 when the uvula was rightmost (closest to the back wall) and the highest pressure at t/T = 0.75 when leftmost, showing the direct influence of uvula motions on the wall pressure distribution. ...
... Similar mean forces were found in the RoI between the heaving and the pitching uvula (Fig. 9c), showing insensitivity of the mean wall forces to the uvula flapping mode. However, the standard deviations of the heaving uvula were larger than the pitching one (Fig. 9f), showing more force fluctuations, reaffirming the finding from probe pressures in the previous study (Wang et al., 2018). ...
... The flow solver employs a second-order central difference scheme for spatial discretization and a fractional step method for time stepping, which can provide a second-order accuracy in both space and time. This approach has been successfully applied to the flapping propulsion of insects [21][22][23], bird [24,25], fish [26][27][28][29][30], as well as human airway [31,32], and various canonical problems [6,[33][34][35][36]. A detailed description of the sharp-interface method and validation of this solver can be found in Ref. [37][38][39]. ...
