Computational Fluid Dynamics Flow Research Articles

Developing a Flow-Resistance Module for Elucidating Cell Mechanotransduction on Multiple Shear Stresses.

Fluid shear stress plays a pivotal role in regulating cellular behaviors, maintaining tissue homeostasis, and driving disease progression. Cells in various tissues are specifically adapted to physiological levels of shear stress and exhibit sensitivity to variations in its magnitude, highlighting the requirement for a comprehensive understanding of cellular responses to both physiologically and pathologically relevant levels of shear stress. In this study, we developed an independent upstream flow-resistance module with high fluidic resistances comprising three microchannels. The validity of the flow-resistance module was confirmed via computational fluid dynamics (CFD) simulations and flow calibration experiments, resulting in the generation of steady wall shear stresses ranging from 0.06 to 11.57 dyn/cm2 within the interconnected cell culture chips. Gene expression profiles, cytoskeletal remodeling, and morphological changes, as well as Yes-associated protein (YAP) nuclear translocation, were investigated in response to various shear stresses to authenticate the reliability of our experimental platform, indicating an increasing trend as the shear stress increases, reaching its maximum at various shear stresses. Our findings suggest that this flow-resistance module can be readily employed for precise characterization of cellular responses under various shear stresses.

Improvement of bubble distribution characteristics through multi-objective optimization of flow characteristics of a swirling flow type microbubble generator with fixed blades

Swirling flow type microbubble generators with fixed blades (hereafter referred to as "bubblers") can be easily downsized and upsized and can be easily integrated into existing facilities. For this reason, bubblers have been used for mercury targets; however, there is a need to improve the bubble distribution characteristics. The objective of this study is to establish a technique to rapidly improve bubble distribution characteristics through multi-objective optimization of the flow characteristics of this bubbler using single-phase flow computational fluid dynamics (CFD) analysis. Therefore, design variables for the bubbler blades were defined by applying turbomachinery design methods, and four flow characteristics were subjected to multi-objective optimization using single-phase flow CFD analysis and the response surface methods. While the resulting optimized bubbler increased the pressure loss coefficient by 0.9 %, it improved the wall shear stress by 3.4 %, the swirl number by 10.0 %, and the pressure reduction coefficient by 14.3 % compared to the original bubbler. Furthermore, experiments showed that the optimized bubbler produced smaller bubbles than the original bubbler, demonstrating that the multi-objective optimization design method can significantly improve the bubble distribution characteristics while maintaining the same pressure loss coefficient.

Development and Validation of a Flow-Dependent Endothelialized 3D Model of Intracranial Atherosclerotic Disease.

Intracranial atherosclerotic disease (ICAD) is a major cause of stroke globally, with mechanisms presumed to be shared with atherosclerosis in other vascular regions. Due to the scarcity of relevant animal models, testing biological hypotheses specific to ICAD is challenging. We developed a workflow to create patient-specific models of the middle cerebral artery (MCA) from neuroimaging studies, such as CT angiography. These models, which can be endothelialized with human endothelial cells and subjected to flow forces, provide a reproducible ICAD model. Using imaging from the SAMMPRIS clinical trial, we validated this novel model. Computational fluid dynamics flow velocities correlated strongly with particle-derived flow, regardless of stenosis degree. Post-stenotic flow disruption varied with stenosis severity. Single-cell RNA-seq identified flow-dependent endothelial gene expression and specific endothelial subclusters in diseased MCA segments, including upregulated genes linked to atherosclerosis. Confocal microscopy revealed flow-dependent changes in endothelial cell proliferation and morphology in vessel segments related to stenosis. This platform, rooted in the specific anatomy of cerebral circulation, enables detailed modeling of ICAD lesions and pathways. Given the high stroke risk associated with ICAD and the lack of effective treatments, these experimental models are crucial for developing new ICAD-related stroke therapies.

Chemical Bath Deposition of NiFe Alloy Anode for Efficient Alkaline Water Electrolyzer Integration.

Green hydrogen production from water splitting is a feasible way for intermittent renewable energy storage and utilization, where the exploration and scale-up preparation of high-performance anodic oxygen evolution electrocatalysts are critical prerequisites for its industrial-level applications. Herein, a chemical bath deposition of FeNi3 intermetallic alloys onto Ni mesh support is performed, which delivers a current density of 0.62 Acm-2 at 1.72 V versus reversible hydrogen electrode for alkaline water oxidation in 1 m KOH and an excellent electrolysis stability at 0.2 A cm-2 for over 300 h. Moreover, via 3D computational fluid dynamics simulation and flow field optimization, a homogeneous deposition of ≈5400 cm2 NiFe anode is demonstrated within 4 min using the developed flow bath reactor. Once integrating the as-prepared NiFe anodes into alkaline electrolyzer stack, the voltage variation between each unit cell is below 40 mV at a total operation current of 71 A, or ca. current density of 0.2 A cm-2, confirming the uniformity of this batch synthesis protocol and its great potential for industrial alkaline water electrolysis.

Toward production zonal flow allocation using novel completion tracer dosing line and diffuser: Prototype laboratory flow loop experiments and computational fluid dynamics studies

Complex completion schemes with inflow control valves (ICVs) in multi-lateral wells are now the industry standard for modern fields. Understanding the production contributions from different production zones/laterals is of great importance in optimizing the zonal flow rates to prolong the field lifetimes, reduce water cuts and the associated costs, and achieve production targets. Furthermore, the improved operational efficiency can reduce the producers’ energy usages and carbon footprints for a more sustainable operation. For the past decade, inflow tracer technology based on embedding tracers in degradable polymer matrices, which are then placed in downhole completion zones at initial installation, has been used in understanding production zonal flow contributions in field demonstrations as well as in commercial projects. However, the current technology based on degradable polymers has the following limitations: (1) there are limited lifetimes for the degradable polymer matrices that will lose their functionality past their expiration dates, and (2) the tracers are released from the polymer matrices at a constant rate; so in order to create a transient for tracer flowback measurements the wells need to be shut-in for a period of time which will interfere with normal production and possibly, with the long-term productivity of the well. Here, we introduce an alternative approach for deploying inflow tracers that has no such limitations mentioned above. Specifically, we propose the installation of passive chemical tracer dosing lines connected to diffuser chambers at the annular regions downhole during completion. Pulses of tracers can be injected into the different production zones and monitored for their flowback characteristics on-demand. The passive tracer dosing lines and diffusers only require minimum upfront investments and have no limitations of lifetime compared to the degradable polymer matrices. Furthermore, the injection of tracer pulses into the annulus near production zones creates appropriate transient responses for their flowback measurements, which do not require well shut-in and will not affect normal production.Laboratory flow loop experiments and computational fluid dynamics (CFD) studies were performed to demonstrate the proposed methodology and to understand the underlying physics. Half-scale and quarter-scale flow loops made of transparent polyvinyl chloride (PVC) pipes that resemble annular regions near the ICVs were constructed with tracer dosing lines and diffusers attached within. Colored dyes were injected into the flow loops to visualize their flush out and flowback behaviors. In CFD studies, a two-step approach was used with first solving for the turbulent fluid flow profiles, and then solving for the tracer convection diffusion behaviors in the turbulent fields. The CFD model parameters were carefully matched with flow loop experiments to predict the possible real field responses. With appropriate diffuser design, we can achieve desirable zonal flow-rate-dependent tracer flowback responses with reasonable sampling times and injected tracer quantities.

Four-dimensional Flow MRI-based Computational Fluid Dynamics Simulation for Noninvasive Portosystemic Pressure Gradient Assessment in Patients with Cirrhosis and Transjugular Intrahepatic Portosystemic Shunt.

Background Transjugular intrahepatic portosystemic shunt (TIPS) dysfunction in patients with liver cirrhosis and recurrent symptoms of portal hypertension is primarily assessed with US and confirmed with invasive catheter venography, which can be used to measure the portosystemic pressure gradient (PSPG) to identify TIPS-refractory portal hypertension. To avoid the risks and costs of invasive catheter venography, noninvasive PSPG evaluation strategies are needed. Purpose To demonstrate the feasibility of the combination of four-dimensional (4D) flow MRI with computational fluid dynamics (CFD) for noninvasive PSPG assessment in participants with cirrhosis and TIPS. Materials and Methods Abdominal 4D flow MRI was performed prospectively in participants with cirrhosis and TIPS between January 2019 and September 2020. Flow rates were measured within the TIPS and inferior vena cava (IVC). The portal vein (PV), TIPS, right hepatic vein, and IVC were segmented on MRI scans to create a CFD mesh. The PV and infrahepatic IVC were defined as inflows for 4D flow MRI-derived flow rates. The suprahepatic IVC was defined as the outflow. CFD simulations were used to noninvasively estimate PSPG as the difference between the simulated pressures in the PV and suprahepatic IVC. Invasive venographic measurements of the PSPG served as the reference standard, and Pearson correlation analysis was conducted to evaluate the relationship between noninvasive estimates and invasive measurements. Results In all 20 participants with cirrhosis (mean age, 58 years ± 9 [SD]; 11 men), 4D flow MRI-based CFD simulations enabled visualization of flow velocities and pressure distributions within the segmented vasculature and TIPS. Noninvasive estimates and invasive measures of PSPG were strongly correlated (r = 0.77; P < .001). The 4D flow MRI-based CFD simulations correctly classified the presence or absence of a post-TIPS PSPG greater than 12 mm Hg in 16 of 20 participants (80%). Conclusion The combination of 4D flow MRI and CFD was feasible for noninvasive PSPG assessment in participants with cirrhosis, portal hypertension, and TIPS. © RSNA, 2024 See also the editorial by Motosugi and Watanabe in this issue.

Navigating Hemodynamic Insights: A Promising Future with Four-dimensional Flow MRI and Computational Fluid Dynamics in Transjugular Intrahepatic Portosystemic Shunt Management.

Navigating Hemodynamic Insights: A Promising Future with Four-dimensional Flow MRI and Computational Fluid Dynamics in Transjugular Intrahepatic Portosystemic Shunt Management.

Estimating velocity distribution and flood discharge at river bridges using entropy theory – insights from computational fluid dynamics flow fields

Abstract. Estimating the flow velocity and discharge in rivers is of particular interest for monitoring, modeling, and research purposes. Instruments for measuring water level and surface velocity are generally mounted on bridge decks, and this poses a challenge because the bridge structure, with piers and abutments, can perturb the flow field. The current research aims to investigate the applicability of entropy theory to estimate the velocity distribution and the discharge in the vicinity of river bridges. For this purpose, a computational fluid dynamics (CFD) model is used to obtain three-dimensional flow fields along a stretch of the Paglia River (central Italy), where a historical multi-arch bridge strongly affects flood flows. The input data for the entropy model include the cross-sectional bathymetry and the surface velocity provided by the numerical simulations. A total of 12 samples, including three different flow conditions at four cross-sections, one upstream and three downstream of the bridge, are considered. It is found that the entropy model can be reliably applied upstream of the bridge, also when forced with a single (i.e., the maximum) value of the surface velocity, with errors on total discharge below 13 % in the considered case. By contrast, downstream of the bridge, the wakes generated by the bridge piers strongly affect the velocity distribution, both in the spanwise and in the vertical directions and for very long distances. Here, notwithstanding the complex and multimodal spanwise distribution of flow velocity, the entropy model estimates the discharge with error lower than 8 % if forced with the river-wide distribution of the surface velocity. The present study has important implications for the optimal positioning of sensors and suggests the potential of using CFD modeling and entropy theory jointly to foster greater knowledge of river systems.

A New Development of Cross-Correlation-Based Flow Estimation Validated and Optimized by CFD Simulation

The accurate measurement of mass flow rates is important in nuclear power plants. Flow meters have been invented and widely applied in several industries; however, the operating environment in advanced nuclear power plants is especially harsh due to high temperatures, high radiation, and potentially corrosive conditions. Traditional flow meters are largely limited to deployment at the outlet of pumps, on pipes, or in limited geometries. Cross-correlation function (CCF) flow estimation, on the other hand, can estimate the flow velocity indirectly without any specific instruments for flow measurement and in any geometry of the flow region. CCF flow estimation relies on redundant instruments, typically temperature sensors, in series in the direction of flow. One challenge for CCF flow estimation is that the accuracy of the flow measurement is mainly determined by inherent, common local process variation across the sensors, which may be small compared to the uncorrelated measurement noise. To differentiate the process variations from the uncorrelated noise, this research implements periodic fluid injection at a different temperature than the bulk fluid before the temperature sensors to amplify process variation. The feasibility and accuracy of this method are investigated through flow loop experiments and Computational Fluid Dynamics (CFD) simulations. This paper focuses on a CFD simulation model to verify the previous experimental results and optimize CCF flow estimation with different configurations. The optimization study is carried out to perform a grid search on the optimal location of the sensor pair under different flow rates. The CFD results show that the optimal sensor spacing depends on the flow rate being measured and provides guidance for sensor location implementation under various anticipated flow rates.

Image2Flow: A proof-of-concept hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data.

Computational fluid dynamics (CFD) can be used for non-invasive evaluation of hemodynamics. However, its routine use is limited by labor-intensive manual segmentation, CFD mesh creation, and time-consuming simulation. This study aims to train a deep learning model to both generate patient-specific volume-meshes of the pulmonary artery from 3D cardiac MRI data and directly estimate CFD flow fields. This proof-of-concept study used 135 3D cardiac MRIs from both a public and private dataset. The pulmonary arteries in the MRIs were manually segmented and converted into volume-meshes. CFD simulations were performed on ground truth meshes and interpolated onto point-point correspondent meshes to create the ground truth dataset. The dataset was split 110/10/15 for training, validation, and testing. Image2Flow, a hybrid image and graph convolutional neural network, was trained to transform a pulmonary artery template to patient-specific anatomy and CFD values, taking a specific inlet velocity as an additional input. Image2Flow was evaluated in terms of segmentation, and the accuracy of predicted CFD was assessed using node-wise comparisons. In addition, the ability of Image2Flow to respond to increasing inlet velocities was also evaluated. Image2Flow achieved excellent segmentation accuracy with a median Dice score of 0.91 (IQR: 0.86-0.92). The median node-wise normalized absolute error for pressure and velocity magnitude was 11.75% (IQR: 9.60-15.30%) and 9.90% (IQR: 8.47-11.90), respectively. Image2Flow also showed an expected response to increased inlet velocities with increasing pressure and velocity values. This proof-of-concept study has shown that it is possible to simultaneously perform patient-specific volume-mesh based segmentation and pressure and flow field estimation using Image2Flow. Image2Flow completes segmentation and CFD in ~330ms, which is ~5000 times faster than manual methods, making it more feasible in a clinical environment.

Experimental and numerical study of the added resistance and seakeeping performance of a new unmanned survey catamaran

Experimental and numerical methods were employed to investigate the added resistance and seakeeping performance of an innovative unmanned catamaran for offshore surveying. Model experiments validated numerical results from viscous flow computational fluid dynamics (CFD) modeling using the unsteady Reynolds-averaged Navier–Stokes (URANS) equations and the potential flow method. URANS modeling precisely predicted the catamaran's performance in regular waves, and the potential flow method offered effective short-term predictions in irregular waves. Simulations were performed at three velocities (4, 6, and 8 knots). The results highlight the fundamental relationships between added resistance and motion responses with changing wave conditions. The extreme motion responses generated by typical actual sea conditions are summarized. The added resistance and motion responses are greatest when the wavelength is slightly longer than the length of the catamaran and the encounter frequency, fe, is ∼1.2. The optimal velocity of the catamaran is 6 knots. The seakeeping performance of the catamaran was assessed using existing indicators for manned vessels. Compared with manned vessels, unmanned survey vessels are more tolerant of first-order motion response but require stricter limitations on second-order accelerations in each degree of freedom.

Response of sediment microbial communities to the flow effect of the triangular artificial reef: A simulation-based experimental study

Artificial reefs (ARs), as an important tool for habitat restoration, play significant impacts on benthic microbial ecosystems. This study utilized 16S rRNA gene sequencing technology and computational fluid dynamics (CFD) flow simulation to investigate the effects of flow field distribution around ARs on microbial community structure. The results revealed distinct regional distribution patterns of microbial communities affected by different hydrodynamic conditions. Flow velocity and flow regime of water in sediment-water interface shaped the microbial community structure. The diversity and richness in R–HF were significantly decreased compared to other five regions (p < 0.05). At the phyla and OUT levels, most abundant taxa (1>%) showed an enrichment trend in R–HB. However, more than half of differentially abundant taxa were enriched in R–HB, which was significantly correlated with organic matter (OM). Bugbase phenotypic predictions indicated a low abundance of the anaerobic phenotype in R–HF and a high abundance of the biofilm-forming phenotype in R–HB.

Dynamic wetting performance and resin-flow behavior of two-level selective laser-etched metal surface in resin transfer moulding process of fiber-metal laminates

ABSTRACT In selective laser etching for the interfacial strengthening of Fiber Metal Laminates (FMLs), the wettability of customized structured features significantly affects their overall mechanical properties. For two-level features, their complicated geometry makes the evaluation of wettability difficult, which introduces challenges to feature design. In this study, a sandwich FMLs comprising an AA2024-O metal skin and a plain-woven carbon-fiber fabric core is investigated. Three types of two-level feature interfaces are designed and introduced into the FMLs structure. To understand the effect of two-level features on the resin flow and dynamic wetting progress in resin transfer molding, two-phase flow Computational Fluid Dynamics numerical models coupled with porous media and level-set numerical methods are built. The feasibility of the numerical simulation in the qualitative analysis was verified by comparing the results with those of the testing porosity values from X-ray scanning. In addition, the mechanisms of pore formation and transportation are revealed. These results indicate that the deeper groove structure in the etched features plays an important role in discharging residual air and determining the transformation of pores to reduce porosity. The permeability orientations of the porous media and surface structure both have significant impacts on the flow behavior and formation of pores.

A hybrid atomistic-continuum framework for multiscale simulations of boiling

Boiling is a multiscale physics process where the nucleation of vapour bubbles occurs due to molecular-scale interactions between the fluid and a heated wall, but it also depends on the larger-scale hydrodynamics and thermal boundary layers determined by the outer system boundary conditions. Modelling boiling from the nanometre up to the millimetre scales at which bubble departure occurs is not possible via state-of-the-art simulation methods: Molecular Dynamics (MD) simulations can capture nucleation from first principles but are limited to nanometre scales due to their computational cost, whereas computational fluid dynamics (CFD) simulations based on the continuum Navier-Stokes equations cannot capture nucleation. Here, we present a novel multiscale simulation method which merges MD and CFD descriptions into a single modelling framework, where MD resolves the near-wall region where molecular interactions are important, and a CFD solver resolves the bulk flow. We model the progressive heating of a Lennard-Jones fluid via contact with a solid wall until a vapour bubble nucleates in the MD region of the domain and grows by entering in the CFD domain. Our results show that an incompressible CFD flow model based on the Volume Of Fluid method with interphase mass transfer calculated via the Hertz-Knudsen-Schrage equation is sufficient to obtain seamless coupling of phase fraction, velocity and temperature fields, with the hybrid MD-CFD framework yielding bubble dynamics closely matching those of MD alone.

Recent Advancements in Fluid Dynamics: Drag Reduction, Lift Generation, Computational Fluid Dynamics, Turbulence Modelling, and Multiphase Flow

Recent Advancements in Fluid Dynamics: Drag Reduction, Lift Generation, Computational Fluid Dynamics, Turbulence Modelling, and Multiphase Flow

Continuous ultrasonic ozone coupling technology-assisted control of ceramic membrane fouling coupled enhanced multiphase mixing to treat dye wastewater and CFD flow field simulation

In this study, ozone catalysts (hydrogenation-modified red mud, HM-RM) successfully prepared by hydrogenation-modification of industrial hazardous solid waste red mud (RM) as a raw material in accordance with the viewpoint of treating waste with waste and using waste. Meanwhile, as for the common phenomenon of membrane fouling, uneven distribution of multiphase solid catalysts and ozone in liquids, the addition of ultrasound can not only disperse materials, but also play a role in online cleaning of ceramic membranes and catalysts. The optimum treatment conditions for Rhodamine B (RhB) solution with volume of 2 L and concentration of 40 mg/L were catalyst concentration of 0.4 mg/L, reaction temperature of 45 °C, ultrasonic time of 1 h, ultrasonic intensity of 600 W, removal rate of RhB was up to 90 %. In addition, the computational fluid dynamics (CFD) simulation method was used to investigate the fluid flow between the two gas-liquid phases and the effect of the negative pressure of the membrane pump on the fluid by the analysis of flow, pressure and ozone flux of the ceramic membrane(CM) reaction apparatus. The CFD simulation results showed that at the inlet gas-liquid flow rate of 3 m/s and the negative pressure of 20,000 Pa, the maximum flow rates of CM-1 were 3 m/s, 0.752 m/s for CM-2, and 0.228 m/s for CM-3, respectively. Vortices, which are beneficial to solid-liquid mixing and gas-liquid mass transfer, formed between the suction port CM-1 of CM-1 and the inlets of CM-2 and CM-3. This discovery is consistent with relevant experimental research results. Significantly higher concentrations of both •OH and dissolved ozone were observed in the US/HM-RM/O3 system compared to other systems, indicating the significant improvement in ozone utilization rate through the application of ultrasound. The superiority of the US/HM-RM/O3 device was demonstrated. The real dye effluent was tested under optimum operating conditions and the results showed that COD and TOC were reduced by 81.34 % and 60.23 % respectively after 180 min of treatment. The above research can provide technical support for the treatment of dye wastewater using Ultrasound-enhanced ozone oxidation ceramic membranes.

Noninvasive Advanced Cardiovascular Magnetic Resonance-Derived Fontan Hemodynamics Are Associated With Reduced Kidney Function But Not Albuminuria.

Kidney disease is the most important predictor of death in patients with a Fontan circulation, yet its clinical and hemodynamic correlates have not been well established. A total of 53 ambulatory patients with a Fontan circulation (median age, 16.2 years, 52.8% male patients) underwent advanced cardiovascular magnetic resonance assessment, including 4-dimensional flow imaging and computational fluid dynamics. Estimated glomerular filtration rate (eGFR) <90 mL/min per 1.73 m2 was observed in 20.8% and albumin-to-creatinine ratio >3 mg/mmol in 39.6%. The average eGFR decline rate was -1.83 mL/min per 1.73 m2 per year (95% CI, -2.67 to -0.99; P<0.001). Lower eGFR was associated with older age, larger body surface area at examination, longer time since Fontan procedure, and lower systemic ventricular ejection fraction. Higher albumin-to-creatinine ratio was associated with absence of fenestration at the Fontan operation, and older age and lower systemic ventricular ejection fraction at the assessment. Lower cross-sectional area of the Fontan conduit indexed to flow (r=0.32, P=0.038), higher inferior vena cava-conduit velocity mismatch factor (r=-0.35, P=0.022), higher kinetic energy indexed to flow in the total cavopulmonary connection (r=-0.59, P=0.005), and higher total cavopulmonary connection resistance (r=-0.42, P=0.005 at rest; r=-0.43, P=0.004 during exercise) were all associated with lower eGFR but not with albuminuria. Kidney dysfunction and albuminuria are common among clinically well adolescents and young adults with a Fontan circulation. Advanced cardiovascular magnetic resonance-derived metrics indicative of declining Fontan hemodynamics are associated with eGFR and might serve as targets to improve kidney health. Albuminuria might be driven by other factors that need further investigation.

Investigating the Characteristics of Pulverized Coal Combustion Using Ansys Fluent: A CFD Study of a 300 kW Swirl Burner

Although the global focus is shifting towards clean energy to replace coal, an immediate technological transition is not yet feasible due to the widespread prevalence of the existing coal combustion technology. The main objective of the present work is to investigate the characteristics of pulverized coal combustion by using Ansys Fluent. This study describes the fluid flow and combustion reactions in the 2D axisymmetric computational fluid dynamics (CFD) model for the 300 kW cylindrical swirl pulverized coal burner. The study was conducted to analyze the combustion process including the volatilization and char combustion models, while varying the ratio of air inlet velocity, and examining the effect of swirl number on pulverized coal combustion. The numerical modeling results for burner′s operating conditions are validated with the steady‐state temperature measurement in the burner. The significant outcome of the associated parameters found that the flame in the burner formed a spiral before converging into the flame line in the main combustion chamber. As a result, increasing the primary airflow rate led to a decrease in the axial temperature in the preliminary combustion chamber and decreasing the primary airflow showed the highest temperature in all three cases. While the secondary airflow increases, the swirling flow will be induced inside the chamber, which affects the highest temperature profile in the preliminary combustion chamber. Changing the tertiary airflow rate did not significantly affect the combustion. However, increasing the tertiary airflow rate improved the completeness of combustion. The swirl numbers also influenced the phenomena of combustion, the volatile released, and combustion reactions which could occur more rapidly with a higher swirl number due to a higher concentration of vortex region. Similarly, the highest swirl numbers resulted in the lowest excess O2 at the exit and the least amount of CO formation.

Comparing the Utility of Coupled Aero-Hydrodynamic Analysis Using a CFD Solver versus a Potential Flow Solver for Floating Offshore Wind Turbines

There has been a great effort towards development of renewable energy systems to combat global warming with significant interest towards research and development of floating offshore wind turbines (FOWTs). With commercial projects such as Hywind Scotland, Hywind Tampen and others, there is a shift of industry attention from bottom-fixed offshore turbines to FOWTs. In this work, we focus on comparing industry standard Potential Flow (PF) methods versus Computational Fluid Dynamics (CFD) solvers for a scaled version of the IEA 15 MW turbine and associated FOWT system. The results from the two solvers are compared/validated using experimental thrust values for the fixed turbine. The motions and the thrust for the FOWT system are then compared for the two solvers along with hydrodynamic properties of the floater hull. The wake features downstream of the turbine are analyzed for the fixed and floating turbine using the CFD solver. The wake from the CFD solver is also compared with a simplified PF model. Finally, a simplified cost-benefit analysis is presented for the two solvers to compare the usefulness and utility of a CFD solver as compared to presently used industry-standard PF methods.

Performance evaluation on full-scale proton exchange membrane fuel cell: Mutual validation of one-dimensional, three-dimensional and experimental investigations

The coupling of multiple physical processes such as gas multi-component transport, gas–liquid multiphase flow, and electrochemical reactions within the proton exchange membrane fuel cell (PEMFC) makes its hydrothermal management exceptionally complicated. Therefore, the complex heat and mass transfer processes in the full-scale PEMFC are investigated in single cell with single channel serpentine flow field (FF). Firstly, the reliability of the proposed three-dimensional (3D) computational fluid dynamics (CFD) numerical model is verified by using the experimental test results of a single cell. Among them, the trend of simulation and experiment performance curves is consistent, and the minimum error of current density is 0.665%. Secondly, the ionomer model of cathode catalyst layer (CCL) is considered in CFD simulation, which is closer to the actual working condition of fuel cell (FC). The resistance of ionomer film and liquid water film mainly affects the diffusion rate of oxygen in CCL, resulting in a decrease in both current density values and power density values. Subsequently, the electrochemical reaction platform of one-dimensional (1D) FC is constructed, and the performance curves of multi-scale FCs are analyzed. The results demonstrate that the error of stack level is the largest, followed by single cell and single channel is the smallest. Finally, the 1D numerical model and the 3D PEMFC multiphase flow CFD model are utilized to investigate the cell voltage losses in the bionic spider flow field, the variable path flow field, and the serpentine flow field, respectively, under different operating conditions.