Experimental Fluid Dynamics Research Articles

A Review of Computational Fluid Dynamics Approaches Used to Investigate Lubrication of Rolling Element Bearings

Abstract Optimizing bearing performance is based on effective lubrication, especially in high-speed machinery, where minimizing churning and drag losses is of significant importance. Over the past few decades, extensive research has been conducted into the better understanding of different aspects of bearing lubrication. These investigations have employed a combination of experimental methods and advanced computational fluid dynamics (CFD) models. This article provides a comprehensive overview of critical aspects of bearing lubrication, with a specific emphasis on recent advances in CFD models. Lubricant flow and distribution patterns are discussed while examining their impact on drag and churning losses. An extensive discussion is provided on the meshing strategies and modeling approaches used to simulate various flow phenomena within bearings. In addition, relevant trends and impacts of cage design on bearing lubrication and fluid friction have been explored, along with a discussion of prevailing limitations that can be addressed in future bearing CFD models.

Predicting pressure fields from incomplete velocity fields based on deep convolutional neural network

Acquisition of an instantaneous pressure field in a flow field is essential for experimental fluid dynamics research because pressure is associated with various flow phenomena. Machine learning has performed well in various fluid mechanics studies in recent years due to its nonlinearity. In this paper, we use the machine learning method to predict the pressure fields from incomplete velocity fields while reconstructing the missing velocity information, as exemplified by the stationary circular cylinder flow and circular cylinder undergoing forced oscillating problems, in which the incompleteness of the velocity field is caused by the optical path occlusion in experiments. We propose a network model based on convolutional neural networks. The experimental results show that the error of machine learning methods is around 4%, and even if the resolution of the training set is reduced, it does not affect the prediction accuracy of the network. For statistical averaging of prediction results, the network has high accuracy in predicting first-order quantities, but its ability to predict second-order quantities is limited. We also explore the effects of the amount of noise on the performance of networks. When applying the model to the forced oscillating cylinder problem, we use transfer learning to train the network given the similarity of the two problems, and the training error yields faster convergence and more minor convergence results. In addition to this, we use flow field data with a single vibration frequency to construct a single dataset, and flow field data with multiple vibration frequencies to construct a mixed dataset, and study the effect of different datasets on the prediction accuracy, which shows that it is difficult for neural networks to achieve both accuracy and generalization.

Novel separate aeration self-circulating technology for continuous aerobic granular sludge process: Performance evaluation, hydrodynamic simulation and control strategy

The continuous aerobic granular sludge (AGS) process is promising for upgrading existing wastewater treatment facilities. However, this approach is still challenging because of its complicated structure and operation. To address this issue, a novel separate aeration self-circulating technology (abbreviated as Zier) was proposed, which is promising for cultivating AGS by its outstanding upflow velocity and circulation multiplier (more than 30 m/h and 200, respectively). This study elaborated on the Zier reactor's feasibility, optimization, and control strategy through computational fluid dynamics simulations, theoretical calculations, and experiments. An appropriate flow regime for efficient removal of pollutant and granulation of sludge was attained at a superficial gas velocity of 1.3 cm/s. Moreover, optimizing the aeration column diameter to half of the reaction column and increasing the height/diameter ratio to 20 dramatically boosted the nitrogen removal capacity over 1.6 kg N/m3/d. Utilizing a smaller circulation pipe diameter ensured granulation under a consistent flow regime. By judiciously regulating, multiple CSTRs and PFRs seamlessly integrated within the Zier reactor across a broad spectrum of particle sludge. The validity of these findings was further substantiated through experimental and theoretical validations. Drawing from these findings, a multi-scenario control strategy was proposed as Zier's map. With all the superiorities shown by the Zier reactor, this study could offer new insights into an efficient continuous AGS process.

A design method of turboexpander-compressors based on multi-objective optimization applied to reverse brayton cycle

This paper presents a new design method for turboexpander-compressors used in air refrigeration. As a key component of the reverse Brayton cycle, the efficiency of the turboexpander-compressor significantly has an impact on the overall cycle performance. The expander section is optimized for multi-objective efficiency at different flow rates using the Imperialist Competitive Algorithm to achieve high performance across all operating conditions. Regarding achieving high utilization efficiency for output power from efficient expanders, the compressor section adopts combined methods involving the jet-wake model and parameter equations. The proposed design is validated through public models, computational fluid dynamics simulations and experiments. Simulations and analysis are conducted on test cases representing comprehensive operational scenarios for both the compressor and the expander, confirming that conclusions drawn based on this method align well with underlying theoretical principles. At the design mass flow, the expander efficiency is 89%, and the compressor utilizes the output power of the expander with an efficiency of 90%. Near the design flow, the expander efficiency is more than 85%, and the compressor utilizes the output power of the expander with an efficiency exceeding 80%. This paper presents a method for turboexpander-compressors applicable to air refrigeration cycles, which achieves a reduction in design costs and an improvement in efficiency under varying loads.

High-temperature dolomite decomposition: An integrated experimental and computational fluid dynamics analysis for calcium looping and industrial applications

The thermal decomposition of dolomite was investigated as a potential low-cost and high-performance precursor to CaO in the calcium looping process, which shows great promise when integrated with carbon capture and storage and thermochemical energy storage technologies. Experimental thermogravimetric analysis (TGA) and computational fluid dynamics (CFD) modelling were used to study the isothermal calcination process of dolomite considering industrially relevant conditions, focusing on high temperatures (800–1200 °C), sample sizes (12–18 mm), different calcination atmospheres (air and CO2) and gas velocities (0.2–3 m·s−1). Based on experimental findings, optimal calcination conditions for industrial applications require a minimum temperature of 1000 °C to achieve complete conversion within 25 min and smaller particles for faster conversion rates. Calcination atmosphere is flexible as CO2 concentration shows minimal impact on conversion rates. Laminar flow gas velocity is not a limiting factor and its value should be considered based on other aspects (i.e., costs). Higher particle initial porosity is seen to increase reactivity and thermal efficiency. The CFD model was validated with experimental data, resulting in determination coefficients (R2) higher than 0.9 for all simulated cases. Model predictions revealed insights into particle level phenomena during calcination, such as increased rates at higher temperatures with proportional self-cooling effects, wake formation enhancing fluid mixing and the presence of a thermal boundary layer reducing heat transfer. The findings presented in this paper can be used in future work to determine reaction mechanisms and optimize kinetic parameters for decomposition, as well as further optimize other aspects of the process at industrially relevant operating conditions.

Effect of gas turbulence in quartz-enhanced photoacoustic spectroscopy: A comprehensive flow field analysis

Here we present a computational and experimental fluid dynamics study for the characterization of the flow field within the gas chamber of a Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) sensor, at different flow rates at the inlet of the chamber. The transition from laminar to turbulent regime is ruled both by the inlet flow conditions and dimension of the gas chamber. The study shows how the distribution of the flow field in the chamber can influence the QEPAS sensor sensitivity, at different operating pressures. When turbulences and eddies are generated within the gas chamber, the efficiency of photoacoustic generation is significantly altered.

Experimental and Computational Fluid Dynamics Analysis of Industrial Water Desalination with High Salinity by Adsorption Chlorine on Resin in a Packed Column

AbstractTo investigate chlorine adsorption from water onto resins, some batch adsorption tests were considered. The mechanisms and characteristic parameters of the adsorption process were analyzed using isotherm models which revealed the following order (based on the coefficient of determination): Flory–Huggins (0.99) > Fowler‐Guggenheim (0.98) >, and Langmuir (0.38).The experimental data were examined using two kinetic models, including first‐ and second‐order ones with R2 value of 0.88, 0.1 respectively. According to the adsorption isotherm study, the Flory–Huggins isotherm model better fit adsorption on the surface of resin, as compared to other models. Assessing the thermodynamic parameters found out that the adsorption of Cl onto resins became an exothermic and spontaneous process. The results were then obtained. Similarly, the results of the experiment were provided via the computational fluid dynamics evaluation. Moreover, the results obtained by computational fluid dynamics were compared with the experimental data, and their accuracy was proved. Subsequently, the effects of changing the design and operating parameters, including flow rate (3, 6, 10 L min−1) and bed height (10, 20, 40 cm) on the performance of this tower were studied. The results showed that by reducing the adsorbent, the adsorbed Cl increased and a longer bed was required for adsorption, which was not cost‐effective. The amount of adsorption decreased as the flow rate increased, indicating that there was little contact between the Cl and the adsorbent.

Dragonfly-Inspired Blades for high Aerodynamic Performance small Horizontal Axis Wind Turbine

Inspired from the fascinating realm of Dragonfly features, this study intricately investigates the aerodynamic performance of a distinctive 1 m diameter small-scale Horizontal Axis Wind Turbine characterized by a unique bio-inspired tandem-blades configuration. Based on experimental wind tunnel tests and computational fluid dynamics simulations, the turbine performance is explored at different Tip Speed Ratios (TSRs). Remarkably, the bio-inspired turbine exhibits exceptional traits, achieving a notable peak power coefficient of approximately 0.35 at a low TSR of 3. A detailed investigation includes thorough analyses of pressure contours, relative velocity distributions, and individual blade contributions, revealing unique dynamics within the tandem configuration. The fore blade notably prevails in extracting wind energy, showcasing superior performance. While the hind blade influence in enhancing the fore blade efficiency emerges, underscoring the role of blade interactions in this bio-inspired designs. This study contributes significantly to the comprehension of the new design dragonfly-inspired wind turbine aerodynamics.

Multi-Objective optimisation of oil demisters geometry for Ultra-Low charge ammonia chillers

Driven by global climate objectives, the pursuit for eco-friendly refrigeration solutions has catalysed impressive advancements in the sector. Ammonia, a historically utilized refrigerant, is now widely adopted in light industrial applications, largely due to the growth of Ultra-Low Charge package chillers. Opportunities, however, persist for refining system components to further diminish refrigerant charge, fostering safer and more efficient solutions. This paper focuses on optimizing the oil separator geometry of an experimentally tested Ultra-Low Charge ammonia chiller. The principal aim and novelty is to lower the specific refrigerant charge while enhancing the separation efficiency and the pressure drop performance. Assessing the separation efficiency involves an analytical model grounded in the “orbit-equilibrium” concept, while the pressure drop is evaluated with consideration of liquid particles presence. Utilizing the validated model, a Multi-Objective Optimization process driven by the eaMuPlusLambda algorithm produces geometries able to reduce the cut-size diameter by 1.4 % up to 15.4 %, pressure drop by 66.7 % up to 89.1 %, and internal volume by 51.3 % up to 68.9 %, compared to the baseline setup. This accomplishment stems from meaningful parameter adjustments, encompassing a 12.1 – 30.0 % decrease in the main diameter, 35.8 % reduction in the main height, 25.4 – 41.2 % contraction in the outlet diameter, 10.9 – 47.1 % augmentation in the inlet diameter, and the vortex finder elimination. Consequently, this translates to a 5% to 14% decrease in the chiller’s specific charge. This study intends an initial step in optimizing oil separators for Ultra-Low Charge ammonia chillers, presenting prospects for specific charge reduction and inciting further exploration through experimental testing or Computational Fluid Dynamics.

Thermosonication process of sour cherries: Microbial inactivation kinetics, experimental and computational fluid dynamics simulation

In this study, the inactivation of Listeria monocytogenes PTCC 1302 and Shigella sonnei PTCC 1974 of sour cherries by thermosonication (37 kHz, 300 W; 50and 60°C; 0–12 min) was evaluated. Several statistical models including polynomial, Weibull, and biphasic linear models were implemented to obtain the variation of microorganism population through time. The coupled non-linear Westervelt and heat transfer equations were solved to determine the acoustic pressure and thermal fields using computational fluid dynamics (CFD). According to the obtained results, average inactivation improvements of 15.47 and 17.13% were obtained when the temperature level was increased for both S. sonnei and L. monocytogenes, respectively. S. sonnei was more affected by the sonication procedure at the initial stages, while similar behavior was also found for L. monocytogenes but at the final stages. The maximum and minimum pressure level was obtained at ∼380 and −230 kPa, respectively. In the beginning, the hot spot was formed near the bottom of the simulated sour cherry, where the acoustic intensity was higher. Although, with the elapse of time, the temperature field became more uniform, and the hot spot moved toward the center of the sour cherry.

Planing Hull Hydrodynamic Performance Prediction Using LincoSim Virtual Towing Tank

This work shows the performance of LincoSim, a web-based virtual towing tank enabling automated and standardized calm water computational fluid dynamics (CFD) data sampling, extending previous published applications to the case of a high-speed hull. The calculations are performed for a 1:10 scale model of a 43 ft powerboat hull form in the Froude number range from 0.3 to 2.0. The counterpart physical model is the experimental fluid dynamics (EFD) campaign performed at the University of Naples Federico II, where the resistance, sinkage and trim data have been measured. The EFD/CFD data comparison is performed and shown with a discussion of the spotted differences. The average percentage differences between the EFD and CFD data for the whole speed range are 1.84, 6.87 and 6.94 for the resistance, dynamic trim, and sinkage, respectively. These results confirm the maturity of the standardized and automated CFD modeling for calm water hydrodynamic analysis included in LincoSim, even at very high Froude numbers. The wetted length of the keel and chine and the wetted surface are calculated from numerical data using the advanced post-processing. Finally, as a work in progress, we test a first comparison for the same hull of the EFD and CFD data, considering two seakeeping conditions for head waves at a given wavelength for two velocity conditions. Also, this kind of analysis confirms the tight correlation between the measured and computed outcomes. This synergic interplay of EFD and CFD can link the advantages of both methods to support hull design but also requires experiment planning and final data analysis to obtain physical parameters not easily measurable in laboratory, such as the wetted surface, wetted lengths, proper viscous contribution, and pressure distribution both in calm water and in waves.

Investigation of Ventilation Performance to Improve the Indoor Air Quality of Institutional Kitchens

Indoor Air Quality (IAQ) is a significant health determinant in the building environment. Ventilation plays a significant role in providing comfortable working conditions and securing contaminant removal from indoor spaces. The heat and effluents generated by cooking activity need to be exhausted from the kitchen space to control the IAQ and provide thermal comfort. The study investigates the ventilation performance concerning IAQ of five institutional kitchens in an educational campus. This study evaluates the influence of building parameters on ventilation performance and IAQ using experimental research and Computational Fluid Dynamics (CFD). The empirical part includes field measurement of indoor airflow and IAQ indicators (particulate matter, CO2, temperature, and RH). The Integrated Environmental Solutions Virtual Environment (IESVE) software performs the CFD analysis. The 'Local Mean Age of air' (LMA) is used as a parameter to analyze IAQ. The findings reveal that the LMA reduces with increased cross-ventilation at the operational level and the presence of local exhaust ventilation, such as chimneys. Moreover, a higher slenderness ratio, lower aspect ratio, and lower building volume reduce the age of air.

CFD simulation and experimental study of CO2 absorption in a rotating packed bed

The rotating packed bed (RPB), a process intensification equipment, has been widely studied and applied to chemical engineering processes such as gas absorption, nanomaterial preparation, and polymer devolatilization. In this study, we presented a typical RPB model to study the intensification mechanism of high gravity on gas-liquid mass transfer. Based on this, three-dimensional computational fluid dynamics (CFD) simulations and experiments of CO2 physical absorption were conducted to investigate the gas-liquid mass transfer characteristics in the RPB. The predicted and experimental values of CO2 saturation rates of the liquid phase showed good agreement, and the errors were within ± 15 % under various operating conditions. Moreover, detailed flow field and mass transfer information that are difficult to measure experimentally, such as the distribution of CO2 mass fraction in the liquid, liquid holdup, turbulent kinetic energy dissipation rate, and gas-liquid interfacial area, were analyzed by CFD simulation results. These results provide a solid foundation for the further development and application of RPB.

Facile preparation of superhydrophobic PVDF/MWCNTs distillation membranes: Synthesis, characteristics and separation performance

In recent years, membrane distillation (MD) has emerged as an effective solution to mitigate the high energy consumption associated with conventional fermentable sugar concentration processes. However, the inherent low mechanical strength of traditional organic membrane surfaces can result in issues related to membrane wetting during long-term MD experiments. In this work, superhydrophobic PVDF/MWCNTs (multi-walled carbon nanotubes) distillation membranes with high mechanical strength were prepared by a combination of templating and co-blending techniques. The process involved peeling the semi-gelation membrane from a sandpaper template, subsequently forming a high aspect ratio microstructure on the membrane surface via tearing and pulling. Additionally, the incorporation of MWCNTs further bolstered the mechanical strength of the membrane. At a peeling time of 90 s and a MWCNTs content of 0.08 wt%, the distillation membrane exhibited an impressive water contact angle of 153.2°, indicating it possess exceptional hydrophobicity while maintaining high mechanical strength. The separation performance of the prepared distillation membranes has been inspected by conducting both experimental analyses and computational fluid dynamics (CFD) modeling of the entire MD process. An appropriate elevation in both feed flow rate and temperature could effectively mitigate the problem of temperature and concentration polarization on the membrane surface. PVDF/MWCNTs distillation membrane demonstrated a modest reduction in permeate flux of about 11.69 % and a stable rejection rate exceeding 99.95 % throughout a 100-hour operational period, and it required only 15 h to concentration of aqueous glucose solution to 100 g/L, significantly enhancing the efficiency of the process. This study also employed a combination of experiments and simulations to optimizes the process conditions guiding the vacuum membrane distillation (VMD) process and could provide guidance for the future application of membrane distillation in the concentration of sugar solutions.

Dynamic temperature distribution characteristics of a large glasshouse with cooling system during the start-stop stage

Excessive heat accumulation leads to high temperature in the glasshouse, the high temperature directly affects the normal growth of crops. This research based on the cooling system as the cooling method of glasshouse, experimental and computational fluid dynamics technique were used to investigate the cooling effect in the start-stop stage. CFD was used to simulate and optimize the temperature dynamics during the start-stop phase of the glasshouse cooling system in the most common summer climates (rainy and sunny). A glasshouse test platform was built in Wuhan in order to conduct temperature experiments to verify the effectiveness of the simulation. The results show that starting the cooling system in summer can effectively reduce the temperature inside the glasshouse in a short time (when it is rainy, the temperature is reduced by 8.1 °C; when it is sunny, the temperature is reduced by 5 °C). During the start-stop stage, the temperature trend of the horizontal and vertical planes is the same. Until the system is running stably, the indoor temperature is maintained uniform and stable, with little fluctuation. In order to create the best growing environment for crops, the air velocity of the air supply outlet is increased to 6.0 m/s on sunny days, which is helpful to increase crop yield and reduce greenhouse gas emissions.

Investigation of experimental mice husbandry microenvironment and animal health in individual ventilated cage (IVC)

This work investigates the husbandry microenvironment and health status of experimental mice to help create a suitable husbandry microenvironment for experimental animals, with the aim of ensuring the quality and animal welfare of experimental mice through a suitable husbandry microenvironment. Experimental measurements and computational fluid dynamics (CFD) are used to analyze the husbandry microenvironment of experimental mice, and indicators for judging the health status and husbandry microenvironments of experimental mice are proposed. The results show that the correlation between the health state of mice and abdominal heat flux reaches 0.786 (p = 0.01), and there is a significant difference between the environmental evaluation indexes of healthy and sick mice. The relationship between the mice and the husbandry microenvironments could be characterized by the Cbs number, i.e.，Cbs number is defined as the biological surface convective heat transfer number of the microenvironment, and the value of Cbs number of the healthy mice could be referred to as about 0.3334. This is of guiding significance for the judgment of the health of experimental animals and the creation of a suitable husbandry microenvironment for experimental animals.

Analysis of Fluid Pressure Drop through a Globe Valve using Computational Fluid Dynamics and Statistical Techniques

Fluid mechanics plays a crucial role in everyday life, enabling the selection of accessories, materials, and various components essential for a system through which fluid flows. Pressure drop stands out as one of the most relevant factors in the design of fluid flow systems. However, analytical and experimental physical methods can increase these analyses' costs and time. Hence, in this study, statistical tools are employed to carry out specific experiments supported by numerical fluid simulation, aiming to comprehend the pressure drop behavior in a fluid as it passes through a globe valve. This valve, in turn, possesses distinct operating and manufacturing characteristics. The methods employed encompass a complete factorial system of response surface as support to construct the experimental design path through computational fluid dynamics. Among the key findings, it is demonstrated that, for systems with relatively low flow rates, the valve opening percentage does not exhibit a significant relationship with fluid pressure drop. Conversely, significant effects are observed for systems with relatively high flow rates regarding the valve opening percentage and pressure drop, reaching values of up to 73% pressure drop in this study. It can be inferred that the integration of statistical experimental design techniques and computational fluid dynamics constitutes a valuable resource for studying the pressure drop of a fluid passing through a system.

Experimental and theoretical fluid dynamics of spherical Savonius turbines operated in pipe flows

The performance of Savonius turbines driven by flow in a pipe is experimentally investigated. The turbine is manufactured to have a spherical outline based on the pipe cross section at a small clearance. The torque and power of the turbine are obtained from the time derivative of the rotational speed measured using a high-speed camera and an equation of rotational motion. We find that the idling tip-speed ratio of the turbine exceeds 5, which is much greater than that of a turbine operating in an open free stream. This proves the dominance of pulsatile flow through the gap between two hemispherical blades in torque generation. Widely varying the gap (i.e., the overlap ratio OR of the Savonius turbine) reveals that a turbine with OR = 30 % has the highest power coefficient. The output efficiency exceeds 50 % for a tip-speed ratio of approximately 3. These experimental results are supported by fluid dynamics theory and computational fluid dynamics simulation, which clarify the driving mechanism of the turbine in a pipeline.

Enhancing Heat Transfer Efficiency in Permanent Magnet Machines through Innovative Thermal Design of Stator Windings

This paper investigates innovative methods for enhancing heat transfer efficiency in high-power permanent magnet electrical machines. The objectives are to quantify the effects of increasing the air speed, increasing the turbulence intensity, and introducing the spacing between windings on cooling performance. The cooling of stator windings is studied through experimental wind tunnel testing and Computational Fluid Dynamics (CFD) modelling. The CFD model is validated against wind tunnel measurements to within 4 Kelvin (K). The results demonstrate that each enhancement method significantly improves the cooling capability. Increasing the air speed from 10 m/s to 40 m/s reduces the winding hotspot temperature by 34%. Introducing a high turbulence intensity of 40% leads to a 21% lower hotspot temperature compared to 0.5% turbulence intensity. Creating a 1.5 mm spacing between coils also substantially improves convection and conduction heat transfer. Overall, combining these optimised design parameters yields over a 40% reduction in hotspot temperature compared to the original design. This research provides practical guidance for maximising heat transfer efficiency in high-power permanent magnet machines, without increasing complexity. The findings will lead to higher machine efficiency, reliability, and longevity for aerospace and other applications.

Validation of a New Method for Continuous Flare Combustion Efficiency Monitoring

A new method is described for calculating flare combustion efficiency (CE) and destruction and removal efficiency (DRE) using a numerical parametric model. The method combines key variables that affect flare performance including the flare vent gas net heating value (NHV), flare design, flow rate, exit velocity, and inert gas composition, alongside the environmental influence of crosswind speed. Each effect is characterized using a parametric model derived from experimental testing data and computational fluid dynamics (CFD). The inclusion of CFD allows the model to be extended into the high-wind conditions that cannot be adequately controlled for in empirical testing yet represent some of the most challenging conditions in which to maintain good combustion. This new parametric model method (PMM) is coupled with ultrasonic flowmeters from which the molecular weight and net heating value of the flare gas can be derived using the vent gas speed of sound measurement. In doing so, this method provides a reliable continuous flare combustion efficiency measure that can be deployed at scale with minimum hardware updates. The system was verified using an extractive sampling method with tests conducted on three full-scale industrial flares including non-assisted, single-arm pressure-assisted, and multi-arm pressure-assisted flare designs. A total of seventy valid test points were carried out with varying flow rate and flare gas heating value, covering a CE range from 46–100%. The uncertainty of the method was assessed using both traditional error propagation and Monte Carlo methodology. The results from the new method agree with the extractive method to within 0.8% in the ≥98% DRE region where flares are expected to operate to limit the impacts of flaring as a source of methane as a greenhouse gas. Uncertainty analysis revealed that the larger DRE discrepancy for DRE ≤ 98% correlates to the measurement uncertainties for both methods.