Computational Fluid Dynamics Results Research Articles

Detecting Under-Resolved Flow Physics Using Supervised Machine Learning

The accuracy of flow simulations is a major concern in computational fluid dynamics (CFD) applications. A possible outcome of inaccuracy in CFD results is missing a major feature in the flowfield. Many methods have been proposed to reduce numerical errors and increase overall accuracy, but these are not always efficient or even feasible. In this study, the principal component analysis (PCA) has been performed on compressible flow simulations around an airfoil to map the high-dimensional CFD data to a lower-dimensional PCA subspace. A machine learning classifier based on the extracted principal components has been developed to detect the simulations that miss the separation bubble behind the airfoil. The evaluative measures indicate that the model is able to detect most of the simulations where the separation region is poorly resolved. Moreover, a single mode responsible for the missing flow separation was uncovered that could be the subject of future studies. The results demonstrate that a machine learning model based on the principal components of the dataset is a promising tool for detecting possible missing flow features in CFD.

Performance Optimization of Hybrid Draft Biomass Cookstove Using CFD

ABSTRACT The term “hybrid draft biomass cookstove” (HDBC) refers to a stove that employs both natural and forced drafts for its primary and secondary air supply. The HDBC optimization analysis is carried out in this work using computational fluid dynamics (CFD), considering the effect of forced draft secondary air mass flow rates to achieve the optimum (lower emissions and higher efficiency) HDBC performance. The analysis includes combustion and soot modeling to evaluate the thermal and emission performance of the stove. The CFD results are validated against the experimental data obtained from the water boiling test (WBT 4.2.3). The extremely low or high secondary air mass flow rate degrades the stove’s performance; hence, its optimization is essential. The optimal mass flow rate identified in this investigation was 0.017 kg/s, at which the thermal and emission performances of HDBC were evaluated. An eddy dissipation model is employed to simulate biomass combustion, considering the reaction kinetics of wood volatiles reacting with oxygen, and a one-step soot model is used to predict soot formation. The combustion model agreed well with the experimental data for efficiency and temperature, with an average deviance of 10% and 20%, respectively. However, it significantly overestimated CO emissions by 81% and achieved Tier 4 performance in simulation as opposed to Tier 0 in the experiment. The PM2.5 emissions were under predicted by the soot model, but both the CFD and the experiment results achieved Tier 4 performance as per the World Health Organization (WHO) standards. Hence, a one-step soot model was found to be effective in predicting soot formation.

The effects of non-Newtonian blood modeling and pulsatility on hemodynamics in the food and drug administration's benchmark nozzle model.

Computational fluid dynamics (CFD) is an important tool for predicting cardiovascular device performance. The FDA developed a benchmark nozzle model in which experimental and CFD data were compared, however, the studies were limited by steady flows and Newtonian models. Newtonian and non-Newtonian blood models will be compared under steady and pulsatile flows to evaluate their influence on hemodynamics in the FDA nozzle. CFD simulations were validated against the FDA data for steady flow with a Newtonian model. Further simulations were performed using Newtonian and non-Newtonian models under both steady and pulsatile flows. CFD results were within the experimental standard deviations at nearly all locations and Reynolds numbers. The model differences were most evident at Re =500, in the recirculation regions, and during diastole. The non-Newtonian model predicted blunter upstream velocity profiles, higher velocities in the throat, and differences in the recirculation flow patterns. The non-Newtonian model also predicted a greater pressure drop at Re =500 with minimal differences observed at higher Reynolds numbers. An improved modeling framework and validation procedure were used to further investigate hemodynamics in geometries relevant to cardiovascular devices and found that accounting for blood's non-Newtonian and pulsatile behavior can lead to large differences in predictions in hemodynamic parameters.

Determination of Flame Plume Characteristics utilising CFD and Experimental Approaches

The potential for plumes to affect the safety of aircraft operations is often predicted using MITRE EPA Models. For many projects, key input parameters to MITER EPA are not available and conservative assumptions or models such as OHIO model are used to characterize the combustion and approximate the key input parameters to EPA plume rise model. These assumptions and conservative models lead to inaccurate results of simulations. The current study provides a novel approach to use a combination of Computational Fluid Dynamics (CFD) tool and EPA Models to reliably predict the risk of turbulence and upset being encountered by a range of aircraft types that operate through a rising plume. The main objective of the current study is to develop a Computational Fluid Dynamics (CFD) combustion model and a procedure to determine an improved set of flare inputs for the Air Quality (AQ) and MITER EPA models. A CFD model has been developed to determine flame plume characteristics (Effective Height, Effective Diameter, Temperature and Velocity) from two flare stacks which are part of a trailer-mounted Mobile Purge Burner (MPB) system. A subsequent experimental test of a similar trailer-mounted MPB system has validated the CFD results. Plume temperatures within the combustion zone of the flares were very much in line with the temperatures predicted by the CFD Simulation study. Plume temperatures above the MPB System appear to drop very quickly, such that the plume temperature fell from just under 500°C at 5 m above ground level to around 15-16°C (and close to the ambient temperature) at 22 m above ground. Again, this is consistent with the CFD Study results. The CFD simulations in the current study accounted for the turbulent flow with chemical species mixing and reaction and utilised an advanced radiation model to solve participating radiation in the combusted zones. This study assesses all the parameters that have impact on the accuracy of the numerical model including computational domain, mesh distribution, numerical scheme and flame plume characteristics including ambient conditions (wind speed and temperature) and combustion under various air to fuel ratio scenarios.

CFD-FEA based model to predict leak-points in a 90-degree pipe elbow

The aim of this paper is to numerically investigate Vibration-Based Leak Detection (VBLD) method in pipeline systems based on Fluid–Structure Interaction (FSI) analysis to predict leakages. In previous investigations, laboratory tests were widely used to study the VBLD technique in small-diameter water loop system pipes. The current project uses Ansys Workbench to extend these findings by integrating Computational Fluid Dynamics (CFD) with Finite Element Analysis (FEA). The study outlines a numerical method for VBLD to identify leakages in a 90-degree pipe elbow by predicting variations in vibration signals, with applications in the oil and gas industry. Firstly, changes in fluid behaviour (centrifugal force, pressure drop, secondary flow, and frictional force) experienced in the internal pipe wall resulting from a probable leakage (modelled as an additional outlet) are determined using CFD. Subsequently, the CFD results are coupled with FEA to model structural responses of the pipe walls subjected to different forces. This in turn allows the variations in vibration signals to be measured. The numerical approach presented in this paper based on FSI and incorporating the VBLD method provides a practical and convenient early detection tool that can complement physical vibration monitoring equipment in the field.

BIO22: Effects of Leakage Flows around TAVI models on Thrombus Formation by Optical Visualization Method with Various Geometries in Vitro

Background: There is a possibility of leakage (PVL; Paravalvular leak) flow around TAVI (Transcatheter Aortic Valve Implantation) and a high risk of thrombus formation. To find out the mechanism of thrombus formation by this leakage flow is important issue. In our previous studies, effects of the high shear rate on the thrombus formation rate at wall on orifice flow were examined by observation of thrombus formation using laser sheet, and it was found that the thrombus formation rates increase with the high shear rates. In this study, observation of thrombus formation around TAVI models including leakage flows by laser sheet in vitro with various geometries. Method: Experimental objects are orifice pipe flow and the leakage models with (Fig.1) for observation of thrombus formation. Each leakage size h is 0mm, 0.5mm, 1mm respectively with 20 mm diameter with stenosis to simulate valve part. The target flow filed with fresh blood plasma of pigs is observed with high speed CCD camera by laser sheet. Once the thrombus formation starts, the scattering wave can be detected by this system. The movies for three kinds of geometries and two flow rates (3 and 5l/min). Results & Conclusions: As for visualization results, typical distribution of thrombus formation area at h= 0, 0.5, 1 mm is shown in Fig.2. Due to the increasing of leakage size, the thrombus formation area at the outer wall decreases. In case of leakage size h=0.5 and 1 mm, these areas correspond to wake size at the back side of the stenosis. Figure 3 shows the thrombus formation rate by evaluation of the thrombus area with changing the leakage size and geometries. It was found that the thrombus formation rate increases with the leakage size, and there are differences between the two geometries. These findings related thrombus formation area were also evaluated from the leakage flow rates in the CFD (Computational Fluid Dynamics) results. And it was also found that this formation rates increase with leakage flow rate obtained by CFD. In conclusion, there is a high possibility to generate thrombus formation with larger leakage flow for TAVI. In future, the effects of valve motion should be investigated.

Interaction Mechanism of Transonic Squealer Tip Cooling With the Effect of High-Speed Relative Casing Motion

Abstract The relative casing motion can significantly influence the turbine blade tip aerothermal performance. In this study, experimental investigation was conducted in a newly developed high-speed disk rotor rig which can mimic engine realistic high-speed casing relative motion while enabling full optical access to a transonic turbine blade tip surface. Spatially-resolved tip heat transfer data, including heat transfer coefficient and film cooling effectiveness, were obtained for a cooled transonic squealer tip by infrared transient thermal measurement. Combined with closely coupled Reynolds-averaged Navier–Stokes computational fluid dynamics (CFD) analysis, this paper reveals an interesting interaction mechanism between the cooling injections from the pressure side and the cavity floor with and without the effect of relative casing motion. Both experimental data and CFD results show a consistent trend in both heat transfer and cooling performance. With cavity cooling only, the cooling performance reduces with the effect of relative casing motion. However, with additional cooling injection from the pressure side, a significant improvement in the combined cooling performance with the relative casing motion can be observed. Such opposite trend highlights the importance of relative casing motion when ranking different tip cooling designs. With the consideration of relative casing motion, extra tip cooling benefit can be obtained by combining cooling injections from two different locations.

Pressurised combustion in hot and low-oxygen environments: Chemiluminescence imaging and modelling

Turbulent flames in a confined and pressurised jet-in-hot-coflow combustor, under a range of pressures and coflow conditions, are investigated in this study. The investigation involves both experimental and numerical analyses, with the central focus on extending the use of an atmospheric-pressure computational fluid dynamics (CFD) model to describe hot and low-oxygen combustion at elevated pressures. A series of CFD simulations are compared against experimental images, in terms of both flame structure and chemiluminescence behaviour. The imaging of OH* and CH* is performed experimentally for flames with Reynolds numbers of 10,000 and 15,000, issuing into coflows with O2 concentrations ranging from 3%–9%. The experimental results show a reduction in OH* and CH* intensity with increasing pressure under the various coflow conditions, while the CFD results display some key differences in the trends with pressure and O2. The computational analysis is complemented by a series of one-dimensional laminar flame simulations at a range of pressures and oxidant O2 concentrations. These simulations enable the changes in chemical kinetics with pressure and O2 concentration to be studied in greater detail, and several key differences in comparison with the CFD results are observed. Ultimately, the results highlight the importance of accurately predicting both the flow-field and finite-rate chemistry to reproduce the trends observed under hot and low-oxygen combustion conditions at elevated pressures.

Fluid dynamics simulations of pressure and flow control devices in polymer flooding selective use in enhanced oil recovery.

The flow rate in each sand of reservoirs on polymer flooding applications is regulated with flow regulator valves (FRV). Different valves are used depending on their permeability characteristics and reservoir pressure, among other reservoir parameters. However, synthetic polymer solutions generally used in oil recovery processes, like HPAM (Partially Hydrolyzed Polyacrylamide), present high viscosity losses as they flow through regulating valves. Mainly, these viscosity losses happen because commercial water valves designed for waterflooding are used to regulate polymer solutions. To minimize viscosity losses caused by the shear rate in valves, a new flow regulator helicoidal device for polymer flooding was designed and evaluated using computational fluid dynamics (CFD) and experimental tests in a laboratory and a testing bank. Following the energy dissipation principle, this helicoidal valve has a conical reduction and expansion toward the central spiral, creating a smooth flow area reduction. CFD results were compared to laboratory tests, obtaining less than a 15% error for six of the eight cases studied and less than 20% for two. The proposed helicoidal valve of 5 mm presented a reduction of 23 percentage points in the polymeric solution mechanical degradation compared to a commercial water valve. For a 6 mm valve, a reduction of 18 percentage points was achieved with a pressure drop of 500 psi and a polymer concentration of 300 ppm.

Advanced turbulence modeling improves thermal gradient prediction during compressed hydrogen tank filling

In order to use gaseous hydrogen for mobility of light and heavy duty vehicles, the standard J2601 from the Society of Automotive Engineers (SAE) recommends that the temperature in the tank must not exceed 85 °C for safety reasons. Prior experiments reported that a vertical thermal stratification can occur during the filling of horizontal tanks under specific conditions. Thermodynamic modeling of hydrogen tank filling can predict the average gas temperature but not the onset of stratification. In a previous study, the computational fluid dynamics (CFD) software OpenFOAM was used to carry out simulations of hydrogen filling for a type IV 37 L tank. The CFD results, by comparison with experimental results, were capable to predict the rise of the thermal stratification with however an underestimation of thermal gradient magnitudes. The maximal temperature predicted at the end of the filling was 15.05 °C bellow the experimental measurements. In this work, the k − ω SST turbulence model is replaced by the k − ω SST SAS turbulence model to limit the prediction of high levels of eddy-viscosity in stagnation areas which over-diffuses the temperature. By using the same mesh as in the above mentioned study, (651 482 cells in the fluid region and 449 126 cells in solid regions), the k − ω SST SAS turbulence model is found to be more appropriate for CFD simulation of tank filling as it predicts a thermal gradient magnitude in the gas in better agreement with experimental measurements than the k − ω SST turbulence model for a similar time of simulation. The maximal temperature predicted at the end of the filling is 2.17 °C bellow the experimental measurements.

A comparative study of mean-line models based on enthalpy loss and analysis of a cavity-structured radial turbine for solar hybrid microturbine applications

Lightweight components are essential for the future of the energy and aerospace fields. This paper presents an innovative radial turbine design that utilizes a cavity structure on the rotor for solar hybrid microturbines. The performance of the cavity-structured radial turbine is studied using mean-line models, computational fluid dynamics (CFD), and finite element analysis (FEA) simulations. The radial turbine is compared using air and supercritical carbon dioxide (sCO2) as the working fluid. The mean-line models based on enthalpy losses from recent literature are validated using commercial code Rital and CFD results. The impact of the isentropic velocity ratio (νs) and absolute flow angle at the rotor inlet (α1) on the optimum design for the rotor radial turbine is also demonstrated. A comparative loss enthalpy breakdown on the rotor is examined, such as incidence loss, passage loss, trailing edge loss, clearance loss, exit loss, and windage loss. The results show that the recent mean-line models based on enthalpy losses can accurately estimate the stage efficiency for both air and sCO2 turbines. By comparing the simulation results obtained from 3D-CFD and mean-line models, the efficiency prediction deviation is within an acceptable range of tolerance for both turbines when comparing the results obtained from 3D-CFD and mean-line models. The FE analysis reveals that the maximum stress decreased significantly for the air and sCO2 turbine after the rotor blade was added using the cavity structure inside. The maximum stress value on the rotor with the cavity structure design is still below the yield strength of the material limits. Furthermore, after the variations of the cavity structure design were added to the rotor blade of both turbines, the results were promising when the dangerous resonance at below 4EO (Engine Order) was minimized. The results of this study provide a promising direction for the development of high-efficiency and lightweight turbines in the energy and aerospace fields.

Experiments and Modeling of the Ceiling Effect with Drone-Scale Propellers

Aircraft designs involving aerodynamic interactions between rotors and other aerodynamic surfaces are becoming increasingly popular. Studying these interactions is key to developing good models for design and aspects of the system such as control. This paper seeks to understand the effect of obstructing the upstream of a propeller at varying distances, also called the ceiling effect, by examining in depth the canonical case of a theoretically infinite obstruction and its interaction with a propeller or actuator disk. Experimental studies of force and pressure are compared to results from computational fluid dynamics (CFD), and good agreement is shown. The CFD results are then compared against the Morillo flowfield model, and a correction is found to match the results. The data indicate that some propellers experienced a nearly twofold increase in thrust. However, a matching force on the surface develops, and the net force drops to nearly zero. The force interaction between the two nearly disappears once the separation exceeds half a propeller diameter. These results are independent of propeller size and pitch. The implemented theoretical model also has low computational cost, and it could be used to improve low-order models such as panel methods or provide a foundation for future rotor–body interaction modeling.

A numerical study on the added resistance and motion of a ship in bow quartering waves using a soft spring system

The prediction of resistance performance in oblique waves have been a key issue for the accurate estimation of added resistance of ships in the actual operating state. Therefore, in this paper, the added resistance of a large tanker in the bow quartering waves (180⁰, 150⁰, 120⁰) was studied by applying a computational fluid dynamics (CFD) solver based on the unsteady Reynolds-averaged Navier-Stokes equations. In addition, the forces and motion responses in bow quartering waves according to the captive test (heave, roll, and pitch free) and soft spring test (6 DOF) were investigated. To validate the CFD results, it was compared with the model test results showing good agreement. The maximum value of the added resistance was observed between 180⁰ and 150⁰, and it decreased sharply at 120⁰. The peak of the added resistance moved to a shorter wave region. The differences in added resistance, heave, and pitch motions in oblique wave according to the degree of freedom were insignificant. However, the discrepancy in roll motion occurred due to the forces and moments differences caused by the degree of freedom. The tendency of added resistance in the bow quartering waves and the forces and motion responses according to the degree of freedom were also investigated.

High time-resolution fenceline air quality sensing and dispersion modeling for environmental justice-centered source attribution

Since compliance air monitoring networks have limited spatial coverage, low-cost air quality sensors (LCAQS) are being used to facilitate exposure assessment for environmental justice communities and investigating the effects from nearby emitters. This study illustrates an application of LCAQS at the Spring Valley High School (SVHS), located at the southern fenceline of an asphalt plant in Las Vegas, Nevada, from March through August 2019 to assess the plant's contributions to schoolchildrens' PM2.5 and PM10 exposure. A computational fluid dynamics (CFD)-based dispersion modeling found that the plant's emissions affected SVHS only for wind directions ranging from 270° to 112.5°. Within the wind sector, the plant's contributions at a 5-min resolution were estimated by the incremental PM concentrations between downwind and upwind senor measurements made at SVHS and a northern fenceline site, respectively. The method was able to attribute 3.7% of the PM2.5 and 11.8% of the PM10 at SVHS to the asphalt plant over the measurement period and estimate the plant's daily contributions that were up to 28% and 50% for PM2.5 and PM10, respectively. The contributions depended on wind speed, time of day, and day of week (weekday vs. weekend), consistent with emission activities from aggregate handling in such a facility. By coupling LCAQS and CFD results, an average PM10 emission rate of 0.58 g s−1 and PM10/PM2.5 emission ratio of 11 were derived for a 10 miles per hour (4.5 m s−1) wind speed. The emission rate and ratio agree, within 20%, with estimates from the U.S. National Emission Inventory. This study design may be applicable for environmental justice-centered monitoring projects with resource constraints, providing information for stakeholders to take necessary actions to address air quality concerns.

Off-design performance evaluation of multistage axial gas turbines for a closed Brayton cycle of sodium-cooled fast reactor

In this study, the validity of reducing the number of gas turbine stages designed for a nitrogen Brayton cycle coupled to a sodium-cooled fast reactor was assessed. The turbine performance was evaluated through computational fluid dynamics (CFD) simulations under different off-design conditions controlled by a reduced flow rate and reduced rotational speed. Two different multistage gas turbines designed to extract almost the same specific work were selected: two- and three-stage turbines (mid-span stage loading coefficient: 1.23 and 1.0, respectively). Real gas properties were considered in the CFD simulation in accordance with the Peng–Robinson's equation of state. According to the CFD results, the off-design performance of the two-stage turbine is comparable to that of the three-stage turbine. Moreover, compared to the three-stage turbine, the two-stage turbine generates less entropy across the shock wave. The results indicate that under both design and off-design conditions, increasing the stage loading coefficient for a fewer number of turbine stages is effective in terms of performance and size. Furthermore, the Ellipse law can be used to assess off-design performance and increasing exponent of the expansion ratio term better predicts the off-design performance with a few stages (two or three).

A Study on Using Location-Information-Based Flow Field Reconstruction to Model the Characteristics of a Discharging Valve in a Hydrodynamic Retarder

In modeling the characteristics of a discharging valve in a hydrodynamic retarder, it is commonly required to determine the value of the flow area to calculate the force on the spool. However, the flow area often relies heavily on empirical or simulation data, which leads to increased uncertainty and computational cost, especially with the variation in the spool displacement. To overcome these shortcomings, Res-SE-U-Nets (networks that combine residual connections, squeeze-and-excitation blocks, and U-Net) are used to reconstruct the velocity field, and they have shown exceptional performance in image-to-image mapping tasks. The dataset of computational fluid dynamics (CFD) results for the velocity field is collected and verified using particle image velocimetry (PIV). The results show that Res-SE-U-Nets can capture the location information of the flow field using a training set of only 120 data points. By utilizing location information in velocity field reconstruction, the flow area can be directly obtained under different spool displacements and pressures to calculate the spool force. The valve characteristics calculated with this method show an error of less than 2% when compared with CFD results, which confirms the validity and effectiveness of this method. The proposed method, which utilizes location information extracted from flow field prediction results, is capable of calculating valve characteristics. This approach also demonstrates the feasibility of using Res-SE-U-Nets for flow field reconstruction.

Evaluation of infection probability of Covid-19 in different types of airliner cabins.

According to the World Health Organization (https://covid19.who.int/), more than 651 million people have been infected by COVID-19, and more than 6.6 million of them have died. COVID-19 has spread to almost every country in the world because of air travel. Cases of COVID-19 transmission from an index patient to fellow passengers in commercial airplanes have been widely reported. This investigation used computational fluid dynamics (CFD) to simulate airflow and COVID-19 virus (SARS-CoV-2) transport in a variety of airliner cabins. The cabins studied were economy-class with 2-2, 3-3, 2-3-2, and 3-3-3 seat configurations, respectively. The CFD results were validated by using experimental data from a seven-row cabin mockup with a 3-3 seat configuration. This study used the Wells-Riley model to estimate the probability of infection with SARS-CoV-2. The results show that CFD can predict airflow and virus transmission with acceptable accuracy. With an assumed flight time of 4h, the infection probability was almost the same among the different cabins, except that the 3-3-3 configuration had a lower risk because of its airflow pattern. Flying time was the most important parameter for causing the infection, while cabin type also played a role. Without mask wearing by the passengers and the index patient, the infection probability could be 8% for a 10-h, long-haul flight, such as a twin-aisle air cabin with 3-3-3 seat configuration.

Effect of pipe size on erosion measurements and predictions in liquid-dominated multiphase flows for the elbows

Solid particle erosion in pipelines and pipe fittings occurs when solids are produced in the oil and gas industries during transporting fluids. Erosion of elbows in series for liquid-dominated flows has gained recognition as many oil fields operate in deep-water subsea flow lines and also in conventional wells onshore. Although significant data is available for gas-dominated flows, the data for liquid-dominated flows are scarce and limited to 50.8 mm pipe elbows in dispersed bubble flow only. Thus, it is essential to determine erosion for different pipe sizes to investigate the pipe size effect and for different flow regimes. This work conducts experiments in vertical liquid-solid flows, and liquid-gas-solid churn flows to examine erosion using 340 μm sand particles in 50.8 mm and 76.2 mm standard SS316 elbows in series separated at a distance of three diameters between them. In addition, flow visualization and paint-removal experiments are conducted to predict the erosion patterns in the elbows. Furthermore, Computational Fluid Dynamics (CFD) simulations are performed to simulate the experimental conditions. Eulerian and VOF multiphase models with different turbulence models are used in CFD simulations to predict erosion on the elbows in series and compare with the experimental results. The CFD results, when modified to account for the lubrication effects of the liquid, can predict the experimentally observed erosion pattern and the magnitudes.

Airway Resistance and Respiratory Distress in Laryngeal Cancer: A Computational Fluid Dynamics Study.

Obstructive upper airway pathologies are a great clinical challenge for the airway surgeon. Protection against acute obstruction is critical, but avoidance of unnecessary tracheostomy must also be considered. Decision-making regarding airway, although supported by some objective findings, is largely guided by subjective experience and training. This investigation aims to study the relationship between clinical respiratory distress and objective measures of airway resistance in laryngeal cancer as determined by computational fluid dynamic (CFD) and morphometric analysis. Retrospective CT and clinical data were obtained for series of 20 cases, defined as newly diagnosed laryngeal cancer patients who required admission or urgent airway surgery, and 20 controls. Cases and controls were matched based on T-staging. Image segmentation and morphometric analysis were first performed. Computational models based on the lattice Boltzmann method were then created and used to quantify the continuous mass flow, rigid wall, and constant static pressure inlet boundary conditions. The analysis demonstrated a significant relationship between airway resistance and acute obstruction (OR 1.018, 95% CI 1.001-1.045). Morphometric analysis similarly demonstrated a significant relationship when relating measurements based on the minimum cross-section, but not on length of stenosis. Morphometric measurements also showed significance in predicting CFD results, and their relationship demonstrated that airway pressures increase exponentially below 2.5 mm. Tumor subsite did not show a significant difference, although the glottic subgroup tended to have higher resistances. Airway resistance analysis from CFD computation correlated with presence of acute distress requiring emergent management. Morphometric analysis showed a similar correlation, demonstrating a radiologic airway assessment technique on which future risk estimation could be performed. 4 (case-control study) Laryngoscope, 133:2734-2741, 2023.

Computational fluid dynamic analysis of graphene oxide/water nanofluid heat transfer over a double backward-facing microchannel

Background: Based on the literature, increasing the heat transfer of nanofluids in the backward microchannel owing to the micro scales and significant effects of the step has been introduced as an attractive issue.Methods: The effect of an inclined step combined with different types of obstacles on the heat transfer of graphene oxide nanofluid inside a double backward-facing step (BFS) microchannel is studied in this study. The numerical model according to the finite volume method (FVM) is utilized to discretize continuity, momentum, and energy equations via ANSYS Fluent 19.0 software. The simulation of double BFS microchannel by using computational fluid dynamics (CFD) is carried out to enhance the forced convection heat transfer of graphene oxide–water nanofluid. This work aims to illuminate the influences of the Reynolds numbers (1, 50, and 100), the nanoparticles volume fraction (0, 0.02, and 0.04), the triangular obstacle existence, and the obstacle location.Significant findings: Based on the CFD results, the maximum Nusselt number of 12.7% and heat transfer coefficient of 12.3% are observed compared to the pure water in the case of triangular obstacle at the top of the first step with nanoparticle volume fraction of 4% and Reynolds numbers of 50 and 1, respectively. Furthermore, heat transfer improves with high pressure drop and friction factor is widely affected by the triangular obstacles and their locations.