Computational Fluid Dynamics Techniques Research Articles

Helicopter flight dynamics with simulated rainfall

Sustaining flight operation that encounters with rainfall might be a challenge to a pilot due to lacking of understanding flight dynamics in the rain conditions. This paper, combined with a computational fluid dynamics (CFD) technique, develops a nonlinear flight dynamics model in the rain conditions that can be capable of exploring UH-60A single-rotor helicopter flight dynamics in the rain conditions, including trim, stability, and controllability. Firstly, in order to obtain a data-driven basis relating to multiple working conditions of the blades, a CFD-based method of simulation of the blade airfoil in the conditions of the angles of attack ranging from −26° to 26° and under a thunderstorm heavy rain scenario when the rate of rainfall is 1500 mm/h is developed. Then, these data are incorporated into a nonlinear flight dynamics model in the form of coefficient increments. Numerical simulations are conducted in the range of the flight velocities from 0 knots to 160 knots. The quantitative results indicate that rainfall degrades the blade airfoil aerodynamic performance and increases the rotor torque and required power, affecting the helicopter trim, stability, and controllability. More importantly, helicopter that flies in a small or moderate flight velocity and that encounters rainfall might be a relative serious case, which should be paid attention to.

A technique for efficient computation of steady yaw manoeuvres using CFD

Hydrodynamic loads acting on a ship can nowadays be reliably obtained from Computational Fluid Dynamics (CFD) techniques. In particular for the determination of the hydrodynamic coefficients of a mathematical manoeuvring model, the forces and moments on a ship sailing at a drift angle or with a yaw rate can be computed efficiently with CFD. While computations with a drift angle are relatively straightforward, computations involving a yaw rate present a challenge. This challenge consists in how to deal with the grid, the setup and the ship encountering its own wake when rotating. A solution based on a single grid setup with consistent boundary conditions and utilising a body force wake damping zone to remedy this challenge is proposed in this paper, leading to an effective, fast, and accurate method to compute hydrodynamic loads of a ship in steady yaw manoeuvres.

Computational fluid dynamics and machine learning as tools for optimization of micromixers geometry

Microfluidic devices have become a new trend in different fields and have attracted attention due to their compact size and capability to deal with a small amount of fluid. Micromixing is an efficient way to mix miscible fluids at this microfluidic level. This work explores a new approach for optimization in microfluidics, using CFD (Computational Fluid Dynamics) and ML (Machine Learning) techniques. The objective of this combination is to enable global optimization with lower computational costs. A Y-type micromixer inspires the initial geometry with cylindrical grooves on the surface of the main channel and obstructions inside it. Simulations for circular obstructions were carried out using the OpenFOAM software to observe the influence of these obstacles. The effects of obstruction diameter and its offset on the percentage of mixing, pressure drop and energy cost were investigated. Numerical experiments were analyzed using machine learning. A neural network was used to train the dataset composed of obstruction diameter and its offset as inputs and percentage of mixing and pressure drop as outputs. The genetic algorithm was used to find the geometry that offers the maximum value of the percentage of mixing and the minimum pressure drop value. The optimal value obtained for the obstruction diameter was 131 mm and for its offset 10 mm, which corresponds to obstructions of medium size close to the channel wall. It is worth mentioning that each simulation takes around 4h, and the total time to guarantee the global optimization would be about 25.000 days. With this methodology, the dataset production, training and optimization takes 40 days. This procedure is a tremendous advantage for microfluidic optimization.

Droplet velocity and thermal state from hot gas atomization of steel melt: Impact on the quality of the spray-formed tubular deposit

The velocity and thermal behavior (temperature, enthalpy, solid fraction) of atomized droplets in a metal spray play the most important role in the spray forming process. These properties mainly determine the materials yield and the final product quality (e.g., porosity, microstructure) of the as-sprayed materials. Changing the gas temperature in the atomization process directly influences these droplet properties in the spray. To understand the droplet behavior in the spray at various atomization gas temperatures (i.e., room temperature RT 293 K, 573 K, 873 K), numerical simulations using computational fluid dynamics (CFD) techniques have been performed and validated by experiments. A series of atomization runs (powder production and spray-forming with AISI 52100 steel) has been conducted at different atomization gas temperatures and pressures with a close-coupled atomizer (CCA). The in-situ temperature detection of the deposit surface (pyrometer) and in the substrate (thermocouples) has been performed to observe the effect of particle properties on the deposit. The result shows that hot gas atomization provides smaller droplets with faster velocity in the spray, affecting the droplet impact and deformation time in the deposition zone. A higher solid fraction of the smaller droplets by hot gas atomization also reduces the deposit surface temperature. Increasing the substrate diameter further decreases the deposit surface temperature without compromising the deposit quality (i.e., porosity) and also refines the grain size. Pre-heating of the substrate up to 573 K results in lower porosity in the vicinity of the substrate.

Rooftop Greenhouse: (2) Analysis of Thermal Energy Loads of a Building-Integrated Rooftop Greenhouse (BiRTG) for Urban Agriculture

Building-integrated rooftop greenhouses (BiRTGs) are innovative vertical farms consisting of a greenhouse on the roof of a building. BiRTGs can provide environmental benefits by recycling energy, carbon dioxide, and water between the greenhouse and the building. Moreover, BiRTGs can reduce cooling and heating loads by reducing the exposure of the building surface to heat gains/losses through the roof. However, the benefits of BiRTGs have not yet been completely elucidated from an energy perspective. This study aimed to analyse the energy-saving efficiency of BiRTGs using building energy simulations (BES) and computational fluid dynamics (CFD) techniques. BES is a calculation method for analysing the heating and cooling loads of buildings; however, it was difficult to consider time-dependent changes in the ventilation characteristics in the BES model. CFD can be used to calculate more detailed ventilation characteristics of an experimental facility. Thus, CFD and the BES were combined to obtain more accurate BES-based data. The BES-computed annual energy load for a single-span greenhouse in which tomatoes were grown was 490,128 MJ, whereas the annual energy load for growing tomatoes in a BiRTG resulted in a 5.2% reduction, on average (464,673 MJ). The energy-saving effects were positive from October to April because the BiRTG helped transmit heat energy transmitted from the building to the greenhouse. Regarding the total energy load in the BiRTG after alternating the air temperature management (ATM), the heating energy load was reduced in the winter. ATM was expected to apply from November to March, with average energy savings of 11.8%.

Morphological and Physiological Characteristics of Ruptured Plaques in Native Arteries and Neoatherosclerotic Segments: An OCT-Based and Computational Fluid Dynamics Study.

BackgroundIntravascular imaging has been used to assess the morphology of lesions causing an acute coronary syndrome (ACS) in native vessels (NV) and identify differences between plaques that ruptured (PR) and caused an event and those that ruptured without clinical manifestations. However, there is no data about the morphological and physiological characteristics of neoatherosclerotic plaques that ruptured (PR-NA) which constitute a common cause of stent failure.MethodsWe retrospectively analyzed data from patients admitted with an acute myocardial infarction that had optical coherence tomography (OCT) imaging of the culprit vessel before balloon pre-dilation. OCT pullbacks showing PR were segmented at every 0.4 mm. The extent of the formed cavity, lipid and calcific tissue, thrombus, and macrophages were measured, and the fibrous cap thickness (FCT) and the incidence of micro-channels and cholesterol crystals were reported. These data were used to reconstruct a representative model of the native and neoatherosclerotic lesion geometry that was processed with computational fluid dynamics (CFD) techniques to estimate the distribution of the endothelial shear stress and plaque structural stress.ResultEighty patients were included in the present analysis: 56 had PR in NV (PR-NV group) and 24 in NA segments (PR-NA group). The PR-NV group had a larger minimum lumen area (2.93 ± 2.03 vs. 2.00 ± 1.26 mm2, p = 0.015) but similar lesion length and area stenosis compared to PR-NA group. The mean FCT (186 ± 65 vs. 232 ± 80 μm, p = 0.009) and the lipid index was smaller (16.7 ± 13.8 vs. 25.9 ± 14.1, p = 0.008) while the of calcific index (8.3 ± 9.5 vs. 2.2 ± 1.6%, p = 0.002) and the incidence of micro-channels (41.4 vs. 12.5%, p = 0.013) was higher in the PR-NV group. Conversely, there was no difference in the incidence of cholesterol crystals, thrombus burden or the location of the rupture site between groups. CFD analysis revealed higher maximum endothelial shear stress (19.1 vs. 11.0 Pa) and lower maximum plaque structural stress (38.8 vs. 95.1 kPa) in the PR-NA compared to the PR-NV model.ConclusionWe reported significant morphological and physiological differences between culprit ruptured plaques in native and stented segments. Further research is needed to better understand the causes of these differences and the mechanisms regulating neoatherosclerotic lesion destabilization.

Blood flow and diameter effect in the navigation process of magnetic nanocarriers inside the carotid artery

Background and objective: Serious side effects are occurred during the cancer therapy. Magnetic driving of nanoparticles is a novel method for the elimination of these effects by supplying with anticancer drug or increase the temperature of the infected area. For this reason, a numerical model for optimal guidance of nanoparticles, through the gradient magnetic field, inside the human artery system is presented in this study. Methods: The present method couples Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) techniques. In addition, the optimum magnetic intensity each time is evaluated by using the covariance matrix adaptation evolution strategy (CMA-ES). Under five feature blood flow velocities in cardiac cycle, the developed method evaluate and select the optimum gradient magnetic field in order to eliminate the deviation of the guided nanoparticles from a pre-described trajectory. Results: Results of the simulations indicate both the influence of the blood flow and the volume of nanocarriers in the magnetic driving process in real conditions. Specifically, the blood flow and the volume of particles are inversely proportional parameters in the magnetic navigation process. As the blood flow is decreased, the deviation of nanoparticles compared to the desired path is minimized. On the contrary, the decrease of the volume of nanocarriers increase the distance of particles from the described trajectory. However, greater magnetic gradient values are needed as the blood flow is increased. Furthermore, the imposed gradient magnetic values are strongly connected with the position of the nanoparticles and the blood blow velocity. Conclusions: Based on the results of the present study, the most important parameter in the navigation process is the magnetic volume of particles. Under real conditions, the effect of the blood flow is insignificant compared to the volume of particles in the navigation process. In addition, great differences in the optimized magnetic sequence are presented both among the different blood flows and the volume of particles.

Three-Dimensional Simulation of the Temperature Distribution in a Commercial Broiler House.

Simple SummarySuitable environmental conditions in broiler houses are essential for animal welfare and successful broiler production. Animals’ effective adaptations to environmental challenges are crucial to their development and production. Computational fluid dynamics (CFD) tools can be seen as an alternative to evaluating indoor environmental conditions. The primary aim of this paper was to evaluate the environment inside a commercial broiler house provided with a heating system. The proposed CFD model presented a good simulation of the experimental data. This analysis indicated the existence of failures in the heating system in some areas of the broiler house during the experimental periods, and it may cause discomfort for the broilers and consequently affect the chicks’ productive and economic losses. Thus, these obtained results can be used to drive decision-making processes to create satisfactory environmental conditions for the development of chicks.The aim of this paper was to analyze, using computational fluid dynamics (CFD), a heating system in a commercial broiler house. Data were collected in a broiler house located in the western mesoregion of Minas Gerais, Brazil. The data were collected at 10 a.m. on the seventh day of chicks’ life in 16 points inside the house. A tetrahedral mesh was adopted for the simulation, and testing of the mesh yielded a geometry of 485,691 nodes. The proposed model was developed in a permanent state condition to simulate the temperature air inside the broiler house, and all other input variables were considered constant. The applied CFD technique resulted in satisfactory fitting of the air temperature variable along the broiler facility as a function of the input data. The results indicated that the model predicted the environmental conditions inside the broiler house very accurately. The mean error of the CFD model was 1.49%, indicating that the model is effective and therefore that it can be used in other applications. The results showed that the heating system provided favorable thermoneutral conditions for chicks in the biggest part of the broiler house. However, there were some areas with air temperature above and below the thermoneutral zone

CFD investigation of air-oil two-phase flow in oil jet nozzle

In aero-engines applications, nozzle geometric parameters have major effects on the lubricating oil to accurately reach target gears or bearings. To investigate the deviation phenomenon of oil jet flow in the lubrication system, the computational fluid dynamics (CFD) technique integrating with the volume of fluid (VOF) method and SST k- ω turbulence model is adopted to deeply understand the flow characteristics of the nozzle. By leveraging this method, the relationship between nozzle geometry, inlet pressure, jet velocity, and jet deviation are firstly analyzed. The results reveal that a higher average velocity and smaller jet deviation can be determined via adjusting the nozzle geometry. Furthermore, a specific test rig, composed of an oil supply system, target system and data collection system, is set up for oil injection test; experimental outlet velocity and mass flow rate of oil passing through the hole on the target plate are monitored and recorded. The experimental findings compare well with numerical results obtained by the CFD method.

Targeted drug delivery to the inferior meatus cavity of the nasal airway using a nasal spray device with angled tip

Background and Objective: Nowadays, by advancement in computational tools, Computational Fluid and Particle Dynamics (CFPD) technique can be used more than ever. The main aim of this study is using a nasal spray device with angled tip to deliver drug particles to the inferior meatus cavity for treatment purposes. In the present study, the drug delivery to the lower regions of the nasal cavity will be improved that has been considered less in the literature.Methods: For this purpose, a spray with an angled tip was used, and the deposition of sprayed particles was compared with a spray with a straight tip. Based on the objectives presented above, a realistic model of the nasal route, including facial geometry, and paranasal sinuses obtained from a series of Computed tomography (CT) scan images, as well as the geometry of a nasal spray with two types of tip were developed.Results: It is observed that by using the spray with the straight tip, particles were mainly deposited in the middle and superior regions of the nasal cavity and no particles entered the inferior meatus airway. The results proved that the spray with the angled tip improved the regional deposition percentage in the inferior meatus cavity up to 2.4% of the total sprayed particles and 1 mg drug mass delivered to this region. The majority of these particles had a diameter between 15–55 µm and that could be considered by spray designers to produce more compatible sprays with the targeted region. Also, most particles were deposited near the inferior meatus cavity and so there is a strong chance to be absorbed and delivered to this region.Conclusion: The deposition pattern and particle size contour due to the spray with the angled tip can give sight to the designers and producers of nasal sprays to build more efficient types for better targeted drug delivery purposes. With this spray type, deposited particles were observed in the inferior meatus that never happened with the straight type. Also, the angled tip of the nasal spray shows the benefit of the ease of use for the user.

Effect of Aerodynamics on Film Blowing Process

Abstract A Computational Fluid Dynamics (CFD) technique using a renormalization group (RNG) k –ε model and Fluent software was employed to analyze numerically the effects of aerodynamics on the air ring cooling system of a film blowing process. An in-line scanning camera system developed in our lab was used to study experimentally the detailed dynamics of bubble instabilities. An operation window for the heat transfer coefficient and the maximum air velocity function was established. The simulation results showed that it is adequate mainly at low BUR (Blow-Up-Ratio) outside of the air ring. The relationship between thermal inertia and cooling air aerodynamics for different bubble geometries was also explored. Different bubble shapes, for the same BUR, produced significant differences in the airflow pattern and heat transfer coefficient. The combination of experimental measurements and numerical simulations indicated that various cooling rates result in important variations in the dynamics of bubble instabilities for different BUR bubbles. It was observed that increasing the cooling rate can destabilize the lower BUR bubbles, but stabilize the higher ones due to the production of different bubble shapes. Finally, it is shown that the bubble instabilities depend on the static pressure distribution along the bubble surface, and that minimizing the pressure gradient can stabilize the bubbles.

Predicting non-uniform indoor air quality distribution by using pulsating air supply and SVM model

Mixing ventilation is the most common air distribution strategy, and often the same diffusers provide space cooling and heating. Although aiming to achieve uniform air distributions, there are still non-uniformities at specific indoor locations. This study innovatively predicts the non-uniform indoor air quality (IAQ) distribution with mixing ventilation, directly from air temperature and air velocity. Both heating and cooling cases are conducted with computational fluid dynamics (CFD) techniques, validated by the experimental measurements in a multi-occupant office configuration. The comparison shows that the support vector machine (SVM) model outperforms the back-propagation neural network (BPNN) and genetic algorithm back-propagation neural network (GABPNN) models, with a medium computation time. The innovative method is demonstrated that the pulsating air supply is useful in generating effective inputs, i.e., the dynamic variations of air temperature and velocity during pulsating air supply (ΔT and Δv), for the air age prediction under the corresponding steady state (τsteady). ΔT and Δv can be fast obtained by monitoring the air velocity and temperature for 10–20 min. With a random selection, the data size should be larger than 180 to reach the mean absolute percentage error (MAPE) threshold value of 5%. However, it can also be reduced to 60 when the data points have a similar steady air temperature. The prediction accuracy under heating is slightly higher than that under cooling, as achieving good mixing under heating is more difficult. We aim to provide guidelines on effective and measurable inputs and valid data-driven models for non-uniform IAQ prediction.

Computational Fluid Dynamic (CFD) Analysis of NACA Airfoil for Wind Turbine Blade Design

The paper presents a conceptual study of performance enhancing devices of an airfoil using computational Fluid Dynamics (CFD) technique. Two simple passive devices were selected and examined for increase in lift and decrease in drag. The target of the study was to evaluate and select the best airfoil suitable for wind turbine blade in a typical Nigeria Environment. The selected airfoils includes; NACA 0012, NACA 2412 and NACA 4412 while the selected angle of attack are; 0°, 4°, 8° and 12. The various airfoils geometry was created using Autodesk inventor and imported into ANSYS design modeler while meshing of the airfoil fluid geometry was done with the aid of ANSYS Meshing. To implement the ANSYS design modeller, the spalart-Allmaras turbulence model was selected and strain/vorticity based sub-option subsequently selected. The CAD Model was prepared in CATIA VS R19 while Pre-processing and simulation was done in ANSYS ICEM CFD 16.0 and ANSYS FLUENT 16.0 respectively. Result of the study shows that NACA 4412 at 4° angle of attack gave the maximum lift to drag ratio and hence, was considered for use in the design of wind turbine blade. The results justify the optimum position for enhancing airfoil performance at a specified angle of attack Keywords : Airfoil, Wind turbine blade, Angle of attack, Coefficient of lift, Coefficient of drag and CFD analysis DOI: 10.7176/IEL/12-2-03 Publication date: May 31 st 2022

A Computational Fluid Dynamic Investigation of a Data Centre Employing Rear Door Heat Exchangers

As the global demand for data services expands, cooling in data centres continues to evolve towards more efficient and cost-effective systems. Incorporating active rear door heat exchangers has become a popular and reliable method that increases the capability of data centres to operate at higher power densities. This study conducts a thermal analysis of a data centre employing active rear door heat exchangers with the use of computational fluid dynamic (CFD) techniques. The data centre under investigation contains seventy-seven cooled racks with three additional uncooled racks operating in the centre of the hall. The main purpose of this study is to understand how the uncooled racks affect the temperature distribution in the data centre. This study presents a modelling technique which uses temperature and velocity field measurements to facilitate the modelling of rear door heat exchangers. Computer server modelling server was carried out at varying inlet temperature and load. Server simulation results have been utilized with field measurements to create four data centre scenarios. Scenarios were created to show how inlet temperature and load affect the temperature distribution in the data centre. Data centre scenarios have been used to validate and compare with field measurements performed. It was found that heat dissipation in the server was directly related to the server’s velocity profile. From the data centre scenarios created it was found that when higher loaded racks are isolated amongst lower loaded racks the distribution of heat is less significant than if the higher loaded racks were situated in clusters of three or more. It was also found that higher loaded racks could be positioned strategically to diminish the effect of the untreated air produced by the uncooled racks in the data centre. The findings from this paper help to understand the thermal behaviour in data centres and suggests areas to consider when reviewing pre-existing data centre designs.

Employing computational fluid dynamics technique for analyzing the PACK-1300XY with methanol and isopropanol mixture

In this study, an innovative wire gauze structured packing, namely PACK-1300XY with a specific surface area of 1300 m2/m3 has been characterized by performing computational fluid dynamics (CFD) approach. Indeed, different features of this packing (height equivalent to a theoretical plate, wet/dry pressure drop, and mass transfer efficiency) were analyzed by analyzing the flow regime using the three-dimensional CFD approach with the Eulerian–Eulerian multiphase scenario. The results showed the mean relative deviation of 16% (for wet pressure drop), 14% (for dry pressure drop), and 17% (for mass transfer efficiency) between the CFD predictions and experimental measurements. These excellent levels of consistency between the numerical findings and experimental observations approve the usefulness of the CFD-based approach for reliable simulation of separation processes.

Computational characterization of the behavior of a saliva droplet in a social environment

The conduct of respiratory droplets is the basis of the study to reduce the spread of a virus in society. The pandemic suffered in early 2020 due to COVID-19 shows the lack of research on the evaporation and fate of droplets exhaled in the environment. The current study, attempts to provide solution through computational fluid dynamics techniques based on a multiphase state with the help of Eulerian–Lagrangian techniques to the activity of respiratory droplets. A numerical study has shown how the behavior of droplets of pure water exhaled in the environment after a sneeze or cough have a dynamic equal to the experimental curve of Wells. The droplets of saliva have been introduced as a saline solution. Considering the mass transferred and the turbulence created, the results has showed that the ambient temperature and relative humidity are parameters that significantly affect the evaporation process, and therefore to the fate. Evaporation time tends to be of a higher value when the temperature affecting the environment is lower. With constant parameters of particle diameter and ambient temperature, an increase in relative humidity increases the evaporation time. A larger particle diameter is consequently transported at a greater distance, since the opposite force it affects is the weight. Finally, a neural network-based model is presented to predict particle evaporation time.

Numerical investigation of combustion and flame characteristics for a model solid oxide fuel cell performance improvement

This paper applies computational fluid dynamics techniques to investigate the flame characteristics in the afterburner of a model solid oxide fuel cell system. The main objective of this research is to analyze the flame characteristics to serve as a reference for performance improvement of the model solid oxide fuel cell. The generated swirl burner was modelled under conventional and colorless distributed combustion conditions. It is because recommended for obtaining a more uniform temperature distributions over the entire of the combustor, resulting in far enough temperature levels for the best performance of the fuel cell. In order to achieve distributed regime during methane combustion, oxygen concentration in the oxidizer was reduced through entrainment of the diluent mixture (90% N2 and 10% CO2). The parameters affecting the performance of a model solid oxide fuel cell were also numerically investigated. The temperature zones obtained from combustion were used to initiate and sustain the solid oxide fuel cell. Cell performance values for different temperatures were analyzed and interpreted. The maximum power value was obtained under distributed regime. While the maximum power points of the cells were gathered in the high performance region at 15% O2, lower power values were obtained at 21% O2 content.

The Reduced-Order Model for Droplet Drift of Aerial Spraying under Random Lateral Wind

The droplet drift during aerial spraying process of oilseed rape, which is induced by complex flow field including random lateral wind, is difficult to predict and suppress. In this study, the high-fidelity computational fluid dynamics (CFD) technique is employed to simulate the two-phase flow of droplets in the rotor flow field, and the influence of main operation parameters on spraying effect is investigated numerically. Furthermore, the mechanism of droplet deposition in various operation conditions is discussed according to the analysis of unsteady flow field characteristics. However, the simulation via CFD technique is time-consuming, and it is not suitable for multidisciplinary work and optimization design. To address such issue, a filter white Gaussian noise signal is used to mimic the random lateral wind, and the droplet drift distance is obtained numerically. Based on the input and output dataset of CFD, the recursive algorithm including nonlinear autoregressive exogenous model and surrogate-based recurrence framework and the deep learning method for time-series prediction called long short-term memory neural network are used to build the efficient reduced-order model, respectively. Numerical simulations show that the droplet drift distance can be predicted by measurable lateral wind speed via the reduced-order model approach, which agreed well with the results obtained via the CFD method. In addition, the reduced-order model could decrease computation cost by 6 orders of magnitude with an acceptable accuracy, which indicates that the proposed method could be used for the design of off-line closed-loop controller of a variable spraying system.

In vitro measurement of hepatic flow distribution in Fontan vascular conduits: Towards rapid validation techniques

Fontan operation is the last stage of single-ventricle surgical reconstructions that connects superior and inferior vena cava (SVC, IVC) to the pulmonary arteries. The key design objectives in total cavopulmonary connections (TCPC) are to achieve low power loss (PL) and balanced hepatic flow distribution (HFD). Computational fluid dynamics (CFD) played a pivotal role in pre-surgical design of single-ventricle patients. However, the clinical application of current CFD techniques is limited due to their complexity, high computational time and untested accuracy for HFD prediction. This study provides a performance assessment of computationally low-cost steady Reynolds-Averaged Navier-Stokes (RANS) k-ɛ turbulent models for simulation of Fontan hemodynamics. The performance is evaluated based on prediction accuracy for three clinically important Fontan hemodynamic indices: HFD, PL and total pulmonary flow split (TPFS). For this purpose, a low-cost experimental technique is developed for rapid quantification of Fontan performance indices. Experiments and simulations are performed for both an idealized and a complex 3D reconstructed patient-specific TCPC. Time-averaged flow data from phase contrast MRI was used as the boundary conditions for the patient-specific model. For the idealized model, different SVC/IVC flow ratios corresponding to different cardiac outputs and Reynolds’ numbers were examined. This study revealed that steady RANS k-ɛ models are able to estimate the Fontan hemodynamic indices with acceptable accuracy within minutes. Among these, standard k-ɛ two-layer was found to deliver the best agreement with the in vitro data with an average error percentage of 1.7, 2.0 and, 3.9 for HFD, TPFS and, PL, respectively for all cases.

CFD modeling of the flow behavior around a PDC drill bit: effects of nano-enhanced drilling fluids on cutting transport and cooling efficiency

ABSTRACT In the present study, hydraulic and thermal performances of nano-enhanced drilling muds have been studied across the complex geometry of a rotating polycrystalline diamond compact (PDC) drill bit using computational fluid dynamics techniques. Toward this goal, a robust converging procedure is applied to generate an advanced tetrahedral/prism grid structure using special techniques. We also utilize a combination of the realizable k-ԑ turbulence model with enhanced wall treatment and Eulerian-Lagrangian discrete phase model (DPM) to investigate the flow field and particles tracking across the bit. The results reveal that the rheological properties enhancement obtained by adding even a small quantity of nano-fluids leads to a remarkable increase in the cutting transport efficiency. According to our results, CuO and ZnO nano-enhanced muds show up to 127% and a 68% rise over the cutting transport ratio of the base fluid at the bit rotational speed of 30 rpm. Besides, the predicted temperature on tip of the bit cutters indicates that increasing the thermal conductivity of nano-enhanced muds can lead to effective cooling only in conjunction with improving rheological characteristics. CuO NWBMs show up to a 16.7% reduction in the temperature of the front surface of bit cutters over the base fluid.