Flow Computational Fluid Research Articles

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.

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.

Realization of Bio-Coal Injection into the Blast Furnace

The steel industry accounts, according to the International Energy Agency, for ~6.7% of global CO2 emissions, and the major portion of its contribution is from steelmaking via the blast furnace (BF) route. In the short term, a significant reduction in fossil CO2 emissions can be achieved through the introduction of bio-coal into the BF as part of cold bonded briquettes, by injection, or as part of coke. The use of bio-coal-containing residue briquettes was previously demonstrated in industrial trials in Sweden, whereas bio-coal injection was only tested on a pilot scale or in one-tuyere tests. Therefore, industrial trials replacing part of the pulverized coal (PC) were conducted. It was concluded that the grinding, conveying, and injection of up to 10% of charcoal (CC) with PC can be safely achieved without negative impacts on PC injection plant or BF operational conditions and without losses of CC with the dust. From a process point of view, higher addition is possible, but it must be verified that grinding and conveying is feasible. Through an experimentally validated computational fluid flow model, it was shown that a high moisture content and the presence of oversized particles delay devolatilization and ignition, lowering the combustion efficiency. By using CC with similar heating value to PC, compositional variations in the injected blend are not critical.

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.

GPU-powered CFD-DEM framework for modelling large-scale gas–solid reacting flows (GPU- rCFD-DEM) and an industry application

The coupling of CFD (computational fluid dynamics) and DEM (discrete element method) is extensively used for simulating gas–solid reacting flows in various industrial processes, while its high computational cost limits its industry applications, especially large-scale systems with a large number of particles and complex geometries. This paper reports a robust highly efficient GPU (graphics processing unit) − powered CFD-DEM coupling approach that is, for the first time, capable of simulating large-scale gas–solid reacting flow systems with complex geometries (GPU- rCFD-DEM). The fluid flow calculations are performed using CPU parallelization, while the particle flow simulations leverage GPU parallelization, and the coupling calculations between CFD and DEM are fully implemented on GPU. The model includes advanced coupling strategies to enhance numerical stability, especially when handling complex geometries with unstructured CFD meshes. The developed model is validated through experimental measurements and its computational performance is evaluated by comparison with previous GPU-based simulations. It shows good agreement with the experiments and superior performance compared to the traditional coupling method. The model is then applied to simulate raceway dynamics and coke combustion in an industrial-scale blast furnace, showcasing its effectiveness in handling complex geometries and a huge number of particles in gas–solid reacting flows. This work provides an efficient and robust solution for numerically simulating industrial applications of gas–solid reacting flow systems.

Optimization of a radial-axial turbine at the stage of center line of fluid flow calculation

Optimization of a radial-axial turbine at the stage of center line of fluid flow calculation

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.

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.

Topological "Shape" in Micellar Dynamics.

For micelles, "shape" is prominent in rheological computations of fluid flow, but this "shape" is often expressed too informally to be useful for rigorous analyses. We formalize topological "shape equivalence" of micelles, both globally and locally, to enable visualization of computational fluid dynamics. Although topological methods in visualization provide significant insights into fluid flows, this opportunity has been limited by the known difficulties in creating representative geometry. We present an agile geometric algorithm to represent the micellar shape for input into fluid flow visualizations. We show that worm-like and cylindrical micelles have formally equivalent shapes, but that visualization accentuates unexplored differences. This global-local paradigm is extensible beyond micelles.

Synergy between heterogeneous catalysis and homogeneous radical reactions for pharmaceutical waste destruction: Perspective

Enormous quantities of pharmaceuticals are consumed by humans leading to a growing and continuous release of harmful components into the environment. Existing conventional water treatment plants are designed mainly for eliminating biodegradable organics and nutrients and cannot degrade pharmaceuticals and personal care products efficiently enough due to their chemical stability. Advanced oxidation processes using radicals generated from ozone can be efficiently combined with heterogeneous catalysis for treatment of wastewater containing pharmaceuticals and personal care products. From the technology viewpoint, elimination of pharmaceuticals from water by heterogeneously catalyzed ozonation should done in a continuous fixed bed reactor. The structured catalysts can be prepared by additive manufacturing using 3D-direct printing of supports/catalysts allowing a high degree of freedom in both the composition and design of the final catalytic material for a fixed bed heterogeneous-homogeneous reaction. Structured materials can exhibit non-periodic structure, such as for example semi-ordered structures, inspired by nature. For periodic and semi-periodic structures, heat and mass transfer should be investigated using computational fluid dynamics and flow imaging methods, guiding further design of novel architectures and subsequently allowing in combination with the materials development efficient control of activity and selectivity. The innovative catalytic reactor engineering should include experimental and numerical investigation of the stage wise injection of the oxidation agent, variation of the reactor cross-section size, changing the distance between the catalyst beds and introduction of the recycle loops.

Into the boundary layer behavior of segmented grinding wheels and its illustration on Ti6Al4V

Segmented grinding wheels, with active abrasive regions and passive slots, have been reported as a promising choice for controlling the grinding force via an intermittent cutting scheme. With an appropriate selection of feed and other operating variables, segmented grinding could mark its merits of improved thermal performance and grinding efficiency, typically in difficult-to-machine aerospace materials. However, the formation of a boundary layer around a rotating grinding wheel is always a barrier to effective cutting fluid delivery in the grinding zone. This article attempts to investigate the boundary layer characteristics of segmented grinding wheels, typically with a comparison of 8-segmented and 32-segmented grinding wheels with a non-porous electroplated structure and its comparison with traditional porous grinding wheel configuration. The regression model proposed in this article can predict boundary layer thickness and tangential air velocity in the grinding zone during the rotation of the wheel. A closer look at flow aspects has been covered using computational fluid flow modeling/simulation, followed by experimental assessments through particle image velocimetry and shadowgraphs. The influence of segmentation and its configuration (typically the number of segments) have been illustrated through a case study of wet grinding on Ti6Al4V.

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.

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.

Computational Fluid Dynamics Calculations of Moderator Heat and Fluid Flow of Small Modular Heavy Water Reactor

Abstract The heavy water reactor concept Teplator is a pressure channel type reactor with independent systems for the primary coolant and the moderator. The present study analyses the low-pressure moderator cooling system of Teplator during full-power operation. The moderator is heated from neutron thermalization, gamma rays absorption, fission product decay, and decay of activation products. Additionally, heat transfer from the coolant channels has to be taken in the analyses of the moderator cooling system. Preliminary thermal-hydraulic analyses of the cooling system are supplemented by computational fluid dynamics (CFD) simulations of heat and fluid flow in the moderator's vessel, emphasizing flow-type regimes. Results from CFD simulations showed that the buoyancy-dominated flow (case MF-22) resulted in a higher thermal stratification and high moderator temperature close to the upper plate of the moderator vessel. The inertia-dominated flow regime MF-90 resulted in good mixing of the moderator and a low thermal stratification in the vessel. Finally, the midmass flow rate regime MF-45 was identified as a transitional region from a buoyancy-dominated to a mix-type regime.

Development of a piston-actuated 3D bio-printer with performance prediction system for the reliable printing of tubular structures

3D bio-printing is a promising approach for creating tubular structures within the human body by precisely controlling the distribution of cells. While several 3D bio-printers have been developed for printing tubular structures, achieving reliable and repeatable construction of effective human tubular structures remains a challenge. This paper presents a piston-actuated 3D bio-tubular structures printer that uses a rotary rod-support printing method and a printing performance prediction system. The printing performance prediction system is based on a two-phase flow computational fluid dynamics model that simulates the tubular structure forming process and provides optimal printing setup parameters, such as extrusion nozzle movement speed, nozzle height, and rod rotating speed. Experimental testing has validated the performance prediction system, which achieved a fair prediction accuracy with an average error of around 10%. The proposed bio-printer and prediction system have the potential to improve the efficiency and effectiveness of tubular structure printing for various biomedical applications.

A Computationally Efficient Method for the Thermo-Structural Analysis of a Turbocharger Turbine Wheel Under Engine Transient Operation

Abstract The accurate evaluation of thermally-induced stresses is of particular importance for life-cycle analysis of modern turbochargers. Conjugated heat transfer (CHT), steady-state calculations represent the state-of-the-art, whose temperature distribution is usually imported into a structural solver as a thermal load for carrying out thermo-structural analyses. In the case of transient analyses, however, issues arise. Indeed, due to the different timescales of convective and conductive heat-transfer mechanisms, unsteady CHT simulations are burdened by high computational costs. Moreover, in the specific case of turbocharged engines, the timescales of engine load transients and turbocharger response may differ by a factor of up to 105. The present study proposes an approach for carrying out transient thermo-structural analyses of the solid domain only, characterized by a physical time in the order of 101 s, without the need for unsteady fluid flow calculations, which would imply the use of a solver time-step in the order of 10−5 s. In the proposed methodology, the effects of the fluid flow in the heat-transfer process are modeled by imposing adequate boundary conditions to wet surfaces of the solid domain with minimum computational effort. Indeed, by performing two steady-state CHT calculations and one steady-state computational fluid dynamics (CFD) calculation, time-dependent boundary conditions can be derived in terms of convective heat transfer coefficient and near-wall fluid temperature. The case study used for model development is a high-performance turbocharger turbine for automotive applications, responding to engine load transients of tenths of seconds. Initially, steady-state CFD and CHT models of the turbine stage are validated against experimental data. Then, transient analyses on the turbine wheel are carried out, and their results are imported as thermal loads into an unsteady structural solver, allowing for accurate transient thermo-structural analyses at sustainable computational cost.

Benchmark computations of dynamic poroelasticity

AbstractWe present benchmark computations of dynamic poroelasticity modeling fluid flow in deformable porous media by a coupled hyperbolic–parabolic system of partial differential equations. A challenging benchmark setting and goal quantities of physical interest for this problem are proposed. Computations performed by space–time finite element approximations with continuous and discontinuous discretizations of the time variable are summarized. By this work, we intend to stimulate comparative studies by other research groups for the evaluation of dynamic poroelasticity solver regarding the accuracy of discretization techniques, the efficiency and robustness of iterative methods for the linear systems, and the arrangement of the model equations in terms of their variables (two‐field or multifield formulations).

Predicting gas diffusion layer flow information in proton exchange membrane fuel cells from cross-sectional data using deep learning methods

Obtaining transient flow field information of gas diffusion layers (GDLs) is a crucial issue for improving the performance of proton exchange membrane fuel cells (PEMFCs). While physically-based methods, such as effective medium theory and solving partial differential equations, can be utilized to calculate fluid flow in GDL, the computational cost associated with such methods remains substantial. In this study, a 3D multiphase flow dataset of GDLs is obtained using fluid of volume (VOF) calculation, and the 3D data is sliced. The resulting cross-sectional data are used to establish a convolutional neural network (CNN) model based on two-dimensional (2D) data for predicting fluid flow in GDLs. The reliability of predicting the saturation information of 3D GDLs using 2D cross-sectional data is verified and discussed. Subsequently, a comparison is made between the accuracy and computational cost of predicting the saturation of 3D GDLs using 2D and 3D CNN models. The results indicate that using 25 cross-sectional images provide accurate predictions of GDL saturation in 3D. When using cross-sectional images as inputs, 100 × 100 images are found to be more representative than 50 × 50 images, resulting in an average increase of 1.86% and 13.36% in R2 and RMSE, respectively. While the 3D CNN model outperforms the 2D CNN model in predicting GDL saturation in 3D by only 0.62% in terms of R2 score, its computational cost is two orders of magnitude higher. These findings suggest that 2D GDL cross-sectional images can also be used for predicting 3D GDL flow information and effectively reducing computational costs. The findings of this study provide a profound insight into the GDL flow phenomena and contribute to the development of more efficient and accurate fuel cell models.

Mechanism Analysis of Vascular Calcification Based on Fluid Dynamics.

Vascular calcification is the abnormal deposition of calcium phosphate complexes in blood vessels, which is regarded as the pathological basis of multiple cardiovascular diseases. The flowing blood exerts a frictional force called shear stress on the vascular wall. Blood vessels have different hydrodynamic properties due to discrepancies in geometric and mechanical properties. The disturbance of the blood flow in the bending area and the branch point of the arterial tree produces a shear stress lower than the physiological magnitude of the laminar shear stress, which can induce the occurrence of vascular calcification. Endothelial cells sense the fluid dynamics of blood and transmit electrical and chemical signals to the full-thickness of blood vessels. Through crosstalk with endothelial cells, smooth muscle cells trigger osteogenic transformation, involved in mediating vascular intima and media calcification. In addition, based on the detection of fluid dynamics parameters, emerging imaging technologies such as 4D Flow MRI and computational fluid dynamics have greatly improved the early diagnosis ability of cardiovascular diseases, showing extremely high clinical application prospects.