Computational Fluid Dynamics Simulation of Airflow Alteration in the Trachea Before and After Vascular Ring Surgery

2013 ◽  
Author(s):  
Tzu-Ching Shih ◽  
Tzyy-Leng Horng ◽  
Fong-Lin Chen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Vascular Ring ◽  
Dynamics Simulation ◽  
Positive Pressure ◽  
Local Pressure ◽  
Pressure Drops ◽  
Vascular Rings ◽  
Before And After ◽  
Key Factor

Vascular rings, congenital intracardic anomalies of the aortic arch and the vessels emerging from the heart, completely encircle the trachea and esophagus [1]. The vascular ring results in narrowing and obstruction of the trachea and the esophagus. Due to the existence of a complete or partial vascular ring compressing either the trachea or esophagus, symptoms of a vascular ring in children include cough, stridor, chronic cough, dysphagia, persistent wheeze, and noisy breathing [2]. Some studies reported that the vascular ring surgery provides an excellent chance to improve the patient respiration conditions, especially for relief of symptoms [1–3]. Al-Bassam et al. reported that the thoracoscopic division of vascular rings in infants and children is a safe and effective surgery rather than an open thoracotomy[4]. Even after the treatment of a surgical division of the vascular ring, however, the fixed obstruction is relieved but the patient continues to have dynamic collapse because the compressed trachea segment is always malacic. Airway resistance to flow in the airway, thus, is a key factor for not only clinical diagnosis severity assessment but also therapeutic decision in tracheal stenosis. Furthermore, Malvè et al. (2011) utilized the finite element-based commercial software code (ADINA R&D Inc.) to model the fluid structure interaction of a human trachea under different ventilation conditions [5]. They also found that the positive pressure in the trachea does not result in the airway collapse during the time period of mechanical breathing. Therefore, the purpose of this study is to use the computational fluid dynamics (CFD) technique to calculate the local pressure drops in the tracheal segment for different inspiratory and expiratory flow rates due to preoperative and preoperative vascular ring surgery.

scholarly journals Computational Fluid Dynamics Simulation of Gas–Solid Hydrodynamics in a Bubbling Fluidized-Bed Reactor: Effects of Air Distributor, Viscous and Drag Models

Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 524 ◽  
Author(s):  
Khezri ◽  
Ghani ◽  
Masoudi Soltani ◽  
Biak ◽  
RobiahYunus ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Pressure Drop ◽  
Turbulence Models ◽  
Solid Particles ◽  
Dynamics Simulation ◽  
Actual Process ◽  
Momentum Exchange ◽  
Pressure Drops ◽  
Drag Models

In this work, we employed a computational fluid dynamics (CFD)-based model with a Eulerian multiphase approach to simulate the fluidization hydrodynamics in biomass gasification processes. Air was used as the gasifying/fluidizing agent and entered the gasifier at the bottom which subsequently fluidized the solid particles inside the reactor column. The momentum exchange related to the gas-phase was simulated by considering various viscous models (i.e., laminar and turbulence models of the re-normalisation group (RNG), k-ε and k-ω). The pressure drop gradient obtained by employing each viscous model was plotted for different superficial velocities and compared with the experimental data for validation. The turbulent model of RNG k-Ɛ was found to best represent the actual process. We also studied the effect of air distributor plates with different pore diameters (2, 3 and 5 mm) on the momentum of the fluidizing fluid. The plate with 3-mm pores showed larger turbulent viscosities above the surface. The effects of drag models (Syamlal–O’Brien, Gidaspow and energy minimum multi-scale method (EMMS) on the bed’s pressure drop as well as on the volume fractions of the solid particles were investigated. The Syamlal–O’Brien model was found to forecast bed pressure drops most consistently, with the pressure drops recorded throughout the experimental process. The formation of bubbles and their motion along the gasifier height in the presence of the turbulent flow was seen to follow a different pattern from with the laminar flow.

Computational Fluid Dynamics Analysis of Pressure Drop Alteration in the Trachea Before and After Vascular Ring Surgery

2013 ◽  
Author(s):  
Tzu-Ching Shih ◽  
Tzyy-Leng Horng ◽  
Fong-Lin Chen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Pressure Drop ◽  
Tracheal Stenosis ◽  
Flow Resistance ◽  
Vascular Ring ◽  
Pressure Change ◽  
Computational Fluid Dynamics Analysis ◽  
Before And After ◽  
Air Flow Velocity

The purpose of this study is to apply the computational fluid dynamics (CFD) technique to evaluate the tracheal airway pressure change before and after the vascular ring surgery (VRS) based on patient computed tomography (CT) images. Computer simulation results also show that after a surgical treatment the pressure drop in the tracheal airway was significantly decreased, especially for low inspiratory and expiratory velocities. In other words, the flow resistance in the tracheal airway becomes decreased after the VRS when the airway is expanded. The airway flow resistance of tracheal stenosis caused by CVR can be augmented by increased air flow velocity. Numerical results show that the pressure drop in the tracheal airway was 0.1099 Pa for the inlet inspiratory velocity of 10 cm/s before the VRS. After the VRS, the pressure drop was reduced and became 0.0598 Pa. In the meantime, the improvement gain was 45.58%. In word words, the pressure drop was reduced after the vascular ring surgery. Therefore, the CFD approach can be a useful method for quantifying the change of airway resistance and evaluating the effectiveness of relief of tracheal stenosis by the VRS.

scholarly journals Enhancement of cerebrovascular 4D flow MRI velocity fields using machine learning and computational fluid dynamics simulation data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
David R. Rutkowski ◽  
Alejandro Roldán-Alzate ◽  
Kevin M. Johnson
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Velocity Fields ◽  
Dynamics Simulation ◽  
Patient Specific ◽  
4D Flow Mri ◽  
4D Flow ◽  
Flow Phase ◽  
Flow Mri ◽  
Trained Network

AbstractBlood flow metrics obtained with four-dimensional (4D) flow phase contrast (PC) magnetic resonance imaging (MRI) can be of great value in clinical and experimental cerebrovascular analysis. However, limitations in both quantitative and qualitative analyses can result from errors inherent to PC MRI. One method that excels in creating low-error, physics-based, velocity fields is computational fluid dynamics (CFD). Augmentation of cerebral 4D flow MRI data with CFD-informed neural networks may provide a method to produce highly accurate physiological flow fields. In this preliminary study, the potential utility of such a method was demonstrated by using high resolution patient-specific CFD data to train a convolutional neural network, and then using the trained network to enhance MRI-derived velocity fields in cerebral blood vessel data sets. Through testing on simulated images, phantom data, and cerebrovascular 4D flow data from 20 patients, the trained network successfully de-noised flow images, decreased velocity error, and enhanced near-vessel-wall velocity quantification and visualization. Such image enhancement can improve experimental and clinical qualitative and quantitative cerebrovascular PC MRI analysis.

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