Search

This article reviews selected solar energy systems that utilize solar energy for heat generation and storage. Particular attention is given to research on individual components of these systems, aimed at improving their efficiency and performance. It focuses on an analysis of the literature concerning the design of thermal storage units, with an emphasis on the use of computational fluid dynamics (CFD) as a research tool. Conclusions from scientists' research regarding the impact of tank shape, thermal insulation, flow parameters, and the use of stratification partitions on heat storage efficiency have been presented. The literature review indicates that thermal storage units play a key role in the efficiency of solar systems, and thermal stratification within them can significantly improve their performance. The methodology was based on an analysis of journals, primarily from after 2008, focusing on articles related to the application of CFD methodology in the study of solar systems and heat storage. [ABSTRACT FROM AUTHOR]

This paper experimentally examines the influence of hybrid excitation on the performance of vibrational piezoelectric energy harvesting systems on a bluff body with a variable cross section along its generatrix. A combination of vibrational excitation from a shaker and airflow is considered the source from which energy is harvested. Varied excitation frequencies and airflow velocities across five different masses were considered, each defining the natural frequency of the system. The system's performance in hybrid excitation, enhancements in energy harvesting, and challenges with these was observed, helping to determine optimal operating conditions to function effectively in ambient environments. The tests identified the conditions and ranges within which maximized harvesting responses were observed. Next, computational fluid dynamic (CFD) simulations were carried out to understand the impact of circular and square cross sections controlling the nature of the airflow and representative of the wide range of cross sections that may be utilized for such purposes. The analyses helped contextualize the opportunities and limitations of the use of such cross sections and helped in understanding if a transition from one cross section to another can lead to an assimilation of the advantages observed in using each cross section independently. [ABSTRACT FROM AUTHOR]

A numerical study was performed to analyze the particle deposition of a cold spray process for the preparation of nickel electrocatalysts used in the Hydrogen Evolution Reaction (HER). The study focused on the creation of fin-shaped geometries with an optimal porosity on the electrode surface using a mask located between the nozzle exit and the substrate. Computational Fluid Dynamics (CFD) was performed on a three-dimensional high-pressure nozzle, with nickel powder used as the injection feedstock. The behavior of particles was effectively modeled through a two-way coupled Eulerian–Lagrangian approach. As per the parametric study, four masks of varying wire thicknesses and opening sizes were investigated. The masks were placed at 4 mm increments from the nozzle exit, with the substrate placed at standoff distances (SODs) of 10 mm and 20 mm. To capture the effects of the gas inlet operating conditions, two different nozzle inlet conditions were analyzed (2 MPa and 400 °C, 4 MPa and 800 °C). It was found that the nozzle inlet operating condition had the most significant impact, as it relates to the particle velocity and powder deposition. The high-pressure operating condition resulted in a deposition efficiency (DE) greater than 99.9% for all the test cases, with nearly all the impacted particles depositing on the substrate. For the medium-pressure operating condition, the DE increased linearly as the mask SOD was increased, due to the increase in the particle velocity upon impact. [ABSTRACT FROM AUTHOR]

This paper focuses on a typical pressure-controlled slide valve, utilizing momentum analysis and computational fluid dynamics to simulate and analyze the asymmetry of steady flow force curves under bidirectional throttling patterns. The entropy production theory is employed to reveal the causes of nonlinearity in the steady flow force of an inlet throttling slide valve. Based on flow field analysis, a flow force compensation scheme is proposed by adding a guiding shoulder and matching it with a suitably sized inner annular cavity. The study reveals that fluid momentum at the non-throttling valve port is the primary cause of the bidirectional throttling flow force difference, and under large-opening inlet throttling conditions, it may reverse the direction of the flow force. Vortex separation caused by turbulent pulsations is one of the intrinsic reasons for the nonlinearity of steady flow force. [ABSTRACT FROM AUTHOR]

The Crabster CR200 is an underwater walking robot inspired by crabs and lobsters, designed for precise seabed inspection and manipulation. It maintains stability and position on the seafloor, even in strong currents, by adjusting its posture through six legs, each with four degrees of freedom. The key advantage of the CR200 lies in its ability to resist drifting in strong currents by adapting its posture to maintain its position on the seafloor. However, information is still lacking on which specific posture generates the maximum downforce to ensure optimal stability in the presence of currents and the seabed. This study aims to determine the fluid forces acting on the CR200 in various postures using Computational Fluid Dynamics (CFD) and identify the posture that generates the maximum downforce. The posture is defined by two parameters: angle of attack and seafloor clearance, represented by the combination of the robot's pitch angle and distance to the seabed. By varying these parameters, we identified the posture that produces the greatest downforce. Through a series of analyses, we identified two main fluid dynamic principles affecting the downforce on a robot close to the seabed. First, an optimal pitch angle exists that generates the maximum downward lift on the robot's body. Secondly, there is an ideal distance from the seabed that produces maximum suction on the bottom surface, thereby creating a strong Venturi effect. Based on these principles, we determined the optimal robot posture to achieve maximum downforce in strong current conditions. The optimal underwater robot posture identified in this study could be applied to similar robots operating on the seafloor. Furthermore, the methodology adopted in this study for determining the optimal posture can serve as a reference for establishing operational postures for similar underwater robots. [ABSTRACT FROM AUTHOR]

The Joule heat generated by current flow between electrodes in a resistance furnace not only melts and heats the charge but also induces mixing of the molten material. Increased mixing promotes improved chemical and temperature uniformity within the bath. This paper presents a novel approach to effectively optimizing electrode geometry in resistance furnaces. The method relies on a surrogate criterion derived exclusively from an electromagnetic submodel, which governs the process hydrodynamics. This criterion is based on the location of the Joule heat generation center in the bath. Its idea is to lower this center as much as possible while keeping it close to the vertical bath axis. Owing to this, the best conditions for the development of natural convection were obtained. The developed methodology was demonstrated through an application to a two-electrode furnace. The results showed that the influence of forced MHD convection is negligible in this furnace (with a Lorentz force of only about 0.0015 N/kg). The validation of the optimized geometry, derived using solely the electromagnetic submodel, was carried out using a full process model, including time-consuming hydrodynamic calculations. The proposed optimization methodology enabled a 10-fold increase in the average mixing velocity (from 0.0008 to 0.0084 m/s). The main significance of the presented study is the introduction of a surrogate criterion that allows for a multiple reduction in the time of numerical optimization of the mixing intensity in electrode resistance furnaces in comparison to the standard solution based on the flow velocity criterion determined from the hydrodynamic model. [ABSTRACT FROM AUTHOR]

Historical building reuse is aimed at preservation, where buildings are recovered for new uses connected to cultural activities. This paper presents the analysis of the impact of thermo-fluid dynamics due to a 500 kW electrical power transformer installed inside a historical building. The analysis is performed using computational fluid dynamics simulations validated through measurement campaigns carried out during the summer period. High temperatures and wide humidity variations can damage building plasters and cause malfunctions in power equipment. To avoid these situations, two different installation layouts were studied. One consists of the power transformer directly installed in the environment and cooled by an inlet fan, and the other consists of the power transformer being insulated from the external environment by an enclosure connected to a forced ventilation system. The second layout showed better results both inside and outside the transformer enclosure. The maximum indoor condition was about 4.3 °C, with a −7.2% RH and an airflow rate of 1100 m3/h, and the maximum outdoor air condition was 3.3 °C, with a −1.39% RH and a flow rate of 2200 m3/h. However, the temperatures and humidity inside the building and outside the transformer enclosure were almost the same. [ABSTRACT FROM AUTHOR]

The considerable heat generated in electronic devices, resulting from their high-power consumption and dense component integration, underscores the importance of developing effective thermal interface materials. While composite materials are ideal for this application, the random distribution of filling materials leads to numerous interfaces, limiting improvements in thermal transfer capabilities. An effective method to improve the thermal conductivity of composites is the alignment of anisotropic fillers, such as hexagonal boron nitride (BN). In this study, the repeat blade coating method was employed to horizontally align BN within a polydimethylsiloxane (PDMS) matrix, followed by flipping and cutting to prepare BN/PDMS composites with vertically aligned BN (V-BP). The V-BP composite with 30 wt.% BN exhibited an enhanced out-of-plane thermal conductivity of up to 1.24 W/mK. Compared to the PDMS, the V-BP composite exhibited outstanding heat dissipation capacities. In addition, its low density and exceptional electrical insulation properties showcase its potential for being used in electronic devices. The impact of coating velocity on the performance of the composites was further studied through computational fluid dynamics simulation. The results showed that increasing the coating velocity enhanced the out-of-plane thermal conductivity of the V-BP composite by approximately 40% compared to those prepared at slower coating velocities. This study provides a promising approach for producing thermal interface materials on a large scale to effectively dissipate the accumulated heat in densely integrated electronic devices. [ABSTRACT FROM AUTHOR]

This study proposes a dual-fuel approach combining diesel and ammonia in a single-cylinder compression ignition engine to reduce harmful emissions from internal combustion. Diesel is directly injected into the combustion chamber, while ammonia is introduced through the intake manifold with intake air. In this study, injection timing and the percentage of ammonia energy fraction was varied. A computational fluid dynamics (CFD) model simulates the combustion and emission processes to assess the impact of varying diesel injection timings and ammonia energy contributions. Findings indicate that as ammonia content increases, the engine experiences reductions in peak in-cylinder pressure, temperature, heat release rate, as well as overall efficiency and power output. Emission results suggest that greater ammonia usage leads to a reduction in soot, carbon monoxide, carbon dioxide, and unburned hydrocarbons, though a slight increase in nitrogen oxides emissions is observed. This analysis supports ammonia's potential as a low-emission alternative fuel in future compression ignition engines. [ABSTRACT FROM AUTHOR]

This review investigates the role of windcatchers in modern architecture, exploring their optimization through the integration of traditional designs with contemporary technologies. Historically utilized in hot and arid climates for passive cooling, windcatchers offer energy-efficient solutions for improving indoor air quality (IAQ). This study examines the sustainability of traditional windcatcher designs and their relevance in preserving heritage structures. Using advanced tools like computational fluid dynamics (CFD) modeling, modern adaptations of windcatchers can be optimized for urban environments. This review also explores hybrid systems, combining windcatchers with solar chimneys, evaporative cooling, or heat pumps, to enhance performance in low-wind conditions by balancing natural and mechanical ventilation. Additionally, it addresses the role of artificial intelligence (AI) in heritage planning, facilitating the design and integration of windcatchers into contemporary architecture. The findings suggest that windcatchers, combined with modern design strategies and hybrid systems, continue to be viable and sustainable solutions for passive cooling, contributing to energy-efficient and climate-resilient buildings across different environmental and urban contexts. [ABSTRACT FROM AUTHOR]

Numerical analysis of a U-type solid oxide fuel cell stack was performed using computational fluid dynamics to investigate the effects of stack capacities and fuel/air utilization rates on the internal flow uniformity. The results indicated that increasing the fuel/air utilization rate improved the gas flow uniformity within the stack for the same stack capacity. The uniformity in the anode fluid domain was better than that in the cathode fluid domain. Furthermore, the flow uniformity within the stack was associated with the percentage of pressure drop in the core region of the stack. The larger the percentage of pressure drop in the core region, the more uniform the flow inside the stack. Additionally, under a fuel utilization rate of 75%, the computational results exhibited excessively high fuel utilization rates in the top cell of a 3 kWe stack, indicating a potential risk of fuel depletion during actual stack operation. [ABSTRACT FROM AUTHOR]

The work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine's power coefficient (CP): the number of blades (N), helix angle (γ), and aspect ratio (AR). Central composite design (CCD) was used for the design of experiments (DOE). For the CFD simulations, a three-dimensional computational domain was established in the Ansys Fluent software, version 2021R1 utilizing the k- ω SST turbulence model and the sliding mesh method to perform unsteady flow simulations. The objective function was to achieve the maximum CP, which was obtained using a high-correlation quadratic mathematical model. Under the optimum conditions, where N, γ , and AR were 5, 78°, and 0.6, respectively, a CP value of 0.3072 was achieved. The optimal turbine geometry was validated through experimental testing, and the CP curve versus tip speed ratio (TSR) was determined and compared with the numerical results, which showed a strong correlation between the two sets of data. [ABSTRACT FROM AUTHOR]

Machine learning tools represent a key methodology for the shape optimization of complex geometries in the turbomachinery field. One of the current challenges is to redesign High-Pressure Turbine (HPT) stages to couple them with innovative combustion technologies. In fact, recent developments in the gas turbine field have led to the introduction of pioneering solutions such as Rotating Detonation Combustors (RDCs) aimed at improving the overall efficiency of the thermodynamic cycle at low overall pressure ratios. In this study, a HPT vane equipped with diffusive endwalls is optimized to allow for ingesting a high-subsonic flow ( M a = 0.6 ) delivered by a RDC. The main purpose of this paper is to investigate the prediction ability of machine learning tools in case of multiple input parameters and different objective functions. Moreover, the model predictions are used to identify the optimal solutions in terms of vane efficiency and operating conditions. A new solution that combines optimal vane efficiency with target values for both the exit flow angle and the inlet Mach number is also presented. The impact of the newly designed geometrical features on the development of secondary flows is analyzed through numerical simulations. The optimized geometry achieved strong mitigation of the intensity of the secondary flows induced by the main flow separation from the diffusive endwalls. As a consequence, the overall vane aerodynamic efficiency increased with respect to the baseline design. [ABSTRACT FROM AUTHOR]

In order to reduce CO2 emissions in the brick manufacturing process, the effectiveness of the energy-intensive firing process needs to be improved. This can be achieved by enhancing the heat transfer in order to reduce firing times. As a result, current development of tunnel kilns is oriented toward fast firing as a long-term goal. However, a struggling building sector and complicated challenges, such as different requirements for product quality, have impeded developments in this direction. This creates potential for the further development of oven designs, such as improved airflow through the kiln. In this article, numerical flow simulations are used to investigate two different reconstruction measures and compare them to the initial setup. In the first measure, the kiln height is reduced, while in the second measure, the kiln cars are adjusted to alternate the height of the bricks so that every other pair of bricks is elevated, creating a staggered arrangement. Both measures are investigated to determine the effect on the heating rate compared to the initial configuration. A transient grid independence study is performed, ensuring numerical convergence and the setup is validated by experimental results from measurements on the initial kiln configuration. The simulations show that lowering the kiln height improves the heat transfer rate by 40 % , while the staggered arrangement of the bricks triples it. This leads to an average brick temperature after two hours which is around 130 °C higher compared to the initial kiln configuration. Therefore, the firing time can be significantly reduced. However, the average pressure loss coefficient rises by 70 % to 90 % , respectively, in the staggered configuration. [ABSTRACT FROM AUTHOR]

The geometric configuration, particularly the inner tube diameter, plays a significant role in the thermal performance of pulsating heat pipes (PHPs). Previous experimental research has demonstrated that single-loop triple-diameter PHPs (TD-PHPs) outperform single-loop single-diameter PHPs (SD-PHPs) and dual-diameter PHPs (DD-PHPs) in terms of thermal performance under moderate heating input powers ranging from 25 W to 75 W. However, a reduction in heat input from 75 W to 25 W leads to a diminished impact of TD-PHPs on the thermal performance. Therefore, to improve the overall performance of TD-PHPs, this study used two-dimensional transient computational fluid dynamics simulations to identify the optimal inner tube diameters for TD-PHPs at a low heat input by evaluating the thermal resistance of five TD-PHPs with various inner diameters. The findings reveal that the TD-PHP configuration exhibits minimum thermal resistance, with inner diameters of 4.5 mm for the upper arch (the condenser section), 4.0 mm for the wide branch, and 2.5 mm for the narrow branch, primarily due to its full circulation flow pattern. Furthermore, the overall heat transfer performance of the optimal TD-PHP was compared with that of an SD-PHP at low heat inputs (10 and 18 W), indicating that although the optimal TD-PHP shows lower thermal resistance, it does not significantly affect the start-up time. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the annual energy consumption that can be attributed to heating, ventilation, and air conditioning (HVAC) systems' mixing temperature error. To develop a mixing temperature prediction model for a single-duct variable air volume (VAV) system, the mixing temperature was measured using 15 temperature sensors installed in an HVAC mixing chamber as well as the existing air handling unit's (AHU) mixing temperature sensor. The mixing chamber was modeled using computational fluid dynamics (CFD), and a coefficient of variation of the root-mean-square error of 7.927% indicated that the model was reliable. Next, CFD simulation cases were formulated, and the temperature distribution of the mixing chamber was analyzed. This revealed that the amount of outdoor airflow input and the change in the temperature distribution of the mixing chamber were directly proportional to each other and that the mixing temperature measurements for the mixing chamber were not accurate. The mixing temperature prediction model was developed through multiple regression analysis and was successfully applied and verified. Compared with the measurements provided by existing mixing temperature sensors, the mixing temperature prediction model indicated an absolute error of 0.008–0.42 °C, confirming the model's prediction performance. [ABSTRACT FROM AUTHOR]

A vortex generator was installed inside an electric agglomeration device to apply aerodynamic agglomeration in the same space as electric agglomeration. Computational fluid dynamics simulation was utilized to assess the combined effects of electric and aerodynamic agglomeration, and this was subsequently validated through experiments. The discrete phase model was used to track particle trajectories. The results showed that both the aerodynamic agglomeration through the vortex generator and the electric agglomeration through the electric field were effective. When these two agglomerations existed individually in series, the total removal efficiency for submicron particles was 32.5%. However, when they coexisted in the same space, the efficiency increased to 50%. This increase is attributed to the increase in residence time when the vortex generator was added to a space with an electric field. This led to particles being exposed to the electric field for a longer duration, thus generating a synergistic effect. [ABSTRACT FROM AUTHOR]

This study demonstrates the significant advantages of integrating computational fluid dynamics (CFD) with artificial intelligence (AI)-based machine learning (ML) to optimize the pre-reforming process for reversible solid oxide cell (r-SOC) technologies. It places a distinct focus on the relationship between process variables, aiming to enhance the preparation of quality r-SOC-ready fuel, which is an indispensable element for successful operation. Evaluating the intricate thermochemistry of syngas-containing reforming processes involves employing an experimentally validated CFD model. The model serves as the foundation for gathering essential data, crucial for the development and training of AI-based machine learning models. The developed model forecasts and optimizes reforming processes across diverse fuel compositions, encompassing oxygen-containing syngas blends and controlled feedstock outlet process conditions. Impressively, the model's predictions align closely with CFD outcomes with an error margin as low as 0.34%, underscoring its accuracy and reliability. This research significantly contributes to a deeper understanding and the qualitative enhancement of preparing high-quality syngas for SOC under improved process conditions. Enabling the early availability of valuable information drives forward sustainable research and ensures the safe, consistent operation assessment of r-SOC. Additionally, this strategic approach substantially reduces the need for resource-intensive experiments. [ABSTRACT FROM AUTHOR]

The channel is a crucial component of the polymer electrolyte membrane fuel cell (PEMFC). Since the channel can change the reactant transfer capability, water removal capability, and distribution of the reactant, it affects the performance and durability of PEMFCs. This study investigated the effects of obstacles in the serpentine-type flow channel on the performance of PEMFCs by computational fluid dynamics (CFD). The height of the obstacles was varied to analyze the electrochemical performances of the fuel cells. In addition, the depth of the flow channel was varied to compare the performances of the PEMFCs. To better represent the real-world tendency, the agglomerate model and the Forchheimer inertial effect were used. The results showed that changes in the channel depth caused greater performance improvements compared to the installation of obstacles, due to the enhanced mass transfer and improved water removal. However, the results for the installation of obstacles showed the lower non-uniformity of the current density and a reduced pressure drop compared to the changes in the channel depth, offering advantages in terms of flooding, the fuel cell life, and the operating cost. [ABSTRACT FROM AUTHOR]

Propeller cavitation performance can be predicted based on model tests or simulations. However, the cavitation performance of an ice-blocked propeller near the free surface differs from that of a propeller in the cavitation tunnel. Therefore, research on the cavitation performance simulation of propellers near the free surface holds crucial scientific significance. In this study, a coupled model was established using Computational Fluid Dynamics (CFD) and the Volume of Fluid (VOF) coupling method. The CFD-VOF model weighted the overlapping grids and simulated the cavitation performance of an ice-blocked propeller using various immersion depths, cavitation numbers, and advance coefficients. The propeller inflow ahead of the propeller and the wake field behind it were controlled to accurately obtain the propeller cavitation performance. Moreover, a comparison was conducted between the cavitation tunnel test results and the numerical simulation results at various immersion depths. When the immersion depth was at a distance of 1D, the effect of the free surface on the propeller cavitation performance became significant. When the immersion depth was at a distance of 9D, the average errors between the numerical simulation and the model test data were within 10%. This study analyzed the cavitation performance of ice-blocked propellers near the free surface and provided valuable insights for the design of ice-class propellers. [ABSTRACT FROM AUTHOR]

Emptying processes are operations frequently required in hydraulic installations by water utilities. These processes can result in drops to sub-atmospheric pressure pulses, which may lead to pipeline collapse depending on soil characteristics and the stiffness of a pipe class. One-dimensional mathematical models and 3D computational fluid dynamics (CFD) simulations have been employed to analyse the behaviour of the air–water interface during these events. The numerical resolution of these models is challenging, as 1D models necessitate solving a system of algebraic differential equations. At the same time, 3D CFD simulations can take months to complete depending on the characteristics of the pipeline. This presents a mathematical approach for directly solving air–water interactions in emptying processes involving entrapped air, providing a predictive tool for water utilities. The proposed mathematical approach enables water utilities to predict emptying operations in water pipelines without needing 2D/3D CFD simulations or the resolution of a differential algebraic equations system (1D model). A practical application is demonstrated in a case study of a 350 m long pipe with an internal diameter of 350 mm, investigating the influence of air pocket size, friction factor, polytropic coefficient, pipe diameter, resistance coefficient, and pipe slope. The mathematical approach is validated using an experimental facility that is 7.36 m long, comparing it with 1D mathematical models and 3D CFD simulations. The results confirm that the derived mathematical expression effectively predicts emptying operations in single water installations. [ABSTRACT FROM AUTHOR]

Hydrogen is regarded as a promising energy source for the future due to its clean combustion products, remarkable efficiency and renewability. However, its characteristics of low-ignition energy, a wide flammable range from 4% to 75%, and a rapid flame speed may bring significant explosion risks. Typically, accidental release of hydrogen into confined enclosures can result in a flammable hydrogen–air mixture with concentration gradients, possibly leading to flame acceleration (FA) and deflagration-to-detonation transition (DDT). The current study focused on the evolutions of the FA and DDT of homogenous/inhomogeneous hydrogen–air mixtures, based on the open-source computational fluid dynamics (CFD) platform OpenFOAM and the modified Weller et al.'s combustion model, taking into account the Darrieus–Landau (DL) and Rayleigh–Taylor (RT) instabilities, the turbulence and the non-unity Lewis number. Numerical simulations were carried out for both homogeneous and inhomogeneous mixtures in an enclosed channel 5.4 m in length and 0.06 m in height. The predictions demonstrate good quantitative agreement with the experimental measurements in flame-tip position, speed and pressure profiles by Boeck et al. The characteristics of flame structure, wave evolution and vortex were also discussed. [ABSTRACT FROM AUTHOR]

This study experimentally investigated a water-cooled four-cylinder turbocharged diesel engine (DE) under different loads and fuel blend ratios. The integration of Computational Fluid Dynamics (CFD) simulations enables a deeper analysis of the combustion process. Through an in-depth analysis of the combustion process, the focus was placed on investigating the specific impacts of ethanol and n-butanol additives on diesel engine performance. Research shows that a fuel mixture consisting of 70% diesel, 10% biodiesel, and 20% ethanol reduced NOx emissions by 5.56% compared to pure diesel at 75% load. Furthermore, this study explores the combustion performance of diesel/biodiesel blended with butanol/ethanol. The findings indicate that n-butanol improves thermal efficiency, particularly at 100% load, with the D70B10E20 and D70B10BU20 blends demonstrating thermal efficiencies of 9.94%and 8.72% higher than that of diesel alone, respectively. All mixed fuels exhibited reduced hydrocarbon and CO emissions under different loads, with a notable reduction in hydrocarbon emissions of 34.4% to 46.1% at 75% load. [ABSTRACT FROM AUTHOR]

Refineries are industrial complexes of great economic importance which are located close to major cities. A pool fire accident that can occur from an oil leak combined with wind can result in disastrous consequences for such an industry. This study investigates the characteristics of an isolated n-heptane square pool fire of 36 m2 under the influence of a cross wind. The pool fire characteristics are numerically studied using open-source Computational Fluid Dynamics (CFD) software, such as FireFoam (v4.1) and Fire Dynamic Simulator (FDS) (version 6.9.0). The turbulent flow field and the fire characteristics were simulated with the LES Method. The crucial parameters of the pool fire, such as (a) the temperature and velocity fields, (b) the flame length and height, (c) the surface emissive power, and (d) the flame tilt angles, were computed. Comparisons against experimental data for both small and large-area pool fires from the literature were made successfully. The flame tilt angle is shown to correlate very well with the reciprocal of the Richardson number, which was approximated within a multiplication constant to the Froude number. Thus, both the reciprocal Richardson number and Froude number can be used for correlating the flame tilt angle. It is shown that both of these numbers are used to correlate the tilt angle of experimental pool fires with effective diameters from a fraction of a meter to approximately 16 m, and wind speeds up to 7 m/s. The goodness of a linear fit based on the sum of the residual squares is 0.91. [ABSTRACT FROM AUTHOR]

Mobile fans, as flexible and convenient new longitudinal ventilation and smoke extraction equipment for tunnels, demonstrate more significant effectiveness in an emergency response to tunnel fires compared to traditional smoke extraction methods. This study employs computational fluid dynamics simulation methods, selecting two fire scenarios to investigate the effects of fan inclined angles and fan airflow volumes on the longitudinal temperature distribution and smoke back-layering length in tunnels. The results indicate that when using mobile fans for longitudinal ventilation in tunnels, at a lower fan airflow volume, the temperature distribution along the longitudinal axis is nearly symmetrical. The fire source and the fan installed in the upstream are within a certain range, and it is more effective to use the horizontal angle for longitudinal ventilation. As the fan airflow volume increases, the back-layering length significantly decreases (210,000 m3/h < V < 270,000 m3/h). However, as the fan flow volume continues to increase (270,000 m3/h < V < 300,000 m3/h), the reduction in the back-layering length becomes less pronounced, the smoke spread distance of the latter is only 11% of that of the former. Therefore, selecting appropriate fan airflow volumes and fan inclined angles them can effectively enhance the performance of tunnel smoke extraction systems. Moreover, by comparing with traditional fans, we find that mobile fans provide an alternative effective strategy during firefighting by allowing adjustments in distance from the fire source and fan inclination angles, enhancing fire suppression effectiveness while reducing energy losses. The research findings can serve as a reference for tunnel fire prevention design. [ABSTRACT FROM AUTHOR]

The proper design and installation of systems that enable the efficient control and removal of smoke and hot gases in underground parking facilities are necessary for protecting the public and property in the event of a fire. This paper discusses how studies using Computational Fluid Dynamics (CFD) related to smoke venting have contributed to improving fire safety in underground parking facilities. As vehicle fire incidents continue to rise globally, particularly in regions with a high density of underground parking, the need for comprehensive measures to mitigate these incidents has become increasingly urgent. This paper examines the applicability of CFD as a tool to address the challenges of smoke control in underground car parks, including those caused by fires involving electric vehicles. CFD application under various fire scenarios and ventilation strategies allows for identifying more effective smoke removal solutions, improving the protection of occupants and property. However, despite the potential of CFD simulations to enhance fire safety and smoke exhaust efficiency in underground parking, it is important to recognize the limitations of these simulations, particularly in dealing with the complex challenges posed by electric vehicle fires. [ABSTRACT FROM AUTHOR]

Dolphin swimming has been a captivating subject, yet the dorsal fin's hydrodynamics remain underexplored. In this study, we conducted three-dimensional simulations of flow around a wall-mounted dolphin dorsal fin derived from a real dolphin scan. The NEK5000 (spectral element method) was employed with a second-order hex20 mesh to ensure high simulation accuracy and efficiency. A total of 13 cases were simulated, covering angles of attack (AoAs) ranging from 0 ° to 60 ° and Reynolds numbers (Re) between 691 and 2000. Our results show that both drag and lift increase significantly with the AoA. Almost no vortex was observed at AoA = 0 ° , whereas complex vortex structures emerged for AoA ≥ 30 ° , including half-horseshoe, hairpin, arch, and wake vortices. This study offers insights that can inform the design of next-generation underwater robots, heat exchangers, and submarine sails. [ABSTRACT FROM AUTHOR]

A novel tailless X-type flapping-wing micro air vehicle with two pairs of independent drive wings is designed and fabricated in this paper. Due to the complexity and unsteady of the flapping wing mechanism, the geometric and kinematic parameters of flapping wings significantly influence the aerodynamic characteristics of the bio-inspired flying robot. The wings of the vehicle are vector-controlled independently on both sides, enhancing the maneuverability and robustness of the system. Unique flight control strategy enables the aircraft to have multiple flight modes such as fast forward flight, sharp turn and hovering. The aerodynamics of the prototype is analyzed via the lattice Boltzmann method of computational fluid dynamics. The chordwise flexible deformation of the wing is implemented via designing a segmented rigid model. The clap-and-peel mechanism to improve the aerodynamic lift is revealed, and two air jets in one cycle are shown. Moreover, the dynamics experiment for the novel vehicle is implemented to investigate the kinematic parameters that affect the generation of thrust and maneuver moment via a 6-axis load cell. Optimized parameters of the flapping wing motion and structure are obtained to improve flight dynamics. Finally, the prototype realizes controllable take-off and flight from the ground. [ABSTRACT FROM AUTHOR]

An innovative approach is utilized in this paper to solve the fractional Fokker–Planck–Levy (FFPL) equation. A hybrid technique is designed by combining the finite difference method (FDM), Adams numerical technique, and physics-informed neural network (PINN) architecture, namely, the FDM-APINN, to solve the fractional Fokker–Planck–Levy (FFPL) equation numerically. Two scenarios of the FFPL equation are considered by varying the value of (i.e., 1 . 75 ,   1.85 ). Moreover, three cases of each scenario are numerically studied for different discretized domains with 100 ,   200 , and 500 points in x ∈ [ − 1 ,   1 ] and t ∈ [ 0 ,   1 ] . For the FFPL equation, solutions are obtained via the FDM-APINN technique via 1000 ,     2000 , and 5000 iterations. The errors, loss function graphs, and statistical tables are presented to validate our claim that the FDM-APINN is a better alternative intelligent technique for handling fractional-order partial differential equations with complex terms. The FDM-APINN can be extended by using nongradient-based bioinspired computing for higher-order fractional partial differential equations. [ABSTRACT FROM AUTHOR]

Intrauterine growth restriction (IUGR), the failure of the fetus to achieve his/her growth potential, is a common and complex problem in pregnancy. Clinically, IUGR is usually monitored using Doppler ultrasound of the umbilical artery (UA). The Doppler waveform is generally divided into three typical patterns in IUGR development, from normal blood flow (Normal), to the loss of end diastolic blood flow (LDBF), and even to the reversal of end diastolic blood flow (RDBF). Unfortunately, Doppler ultrasound hardly provides complete UA hemodynamics in detail, while the present in silico computational fluid dynamics (CFD) can provide this with the necessary ultrasound information. In this paper, CFD is employed to simulate the periodic UA blood flow for three typical states of IUGR, which shows comprehensive information on blood flow velocity, pressure, and wall shear stress (WSS). A new finding is the "hysteresis effect" between the UA blood flow velocity and pressure drop in which the former always changes after the latter by 0.1–0.2 times a cardiac cycle due to the unsteady flow. The degree of hysteresis is a promising indicator characterizing the evolution of IUGR. CFD successfully shows the hemodynamic details in different development situations of IUGR, and undoubtedly, its results would also help clinicians to further understand the relationship between the UA blood flow status and fetal growth restriction. [ABSTRACT FROM AUTHOR]

Silent Brain Infarction (SBI) is increasingly recognized in patients with cardiac conditions, particularly Atrial Fibrillation (AF) in elderly patients and those undergoing Transcatheter Aortic Valve Implantation (TAVI). While these infarcts often go unnoticed due to a lack of acute symptoms, they are associated with a threefold increase in stroke risk and are considered a precursor to ischemic stroke. Moreover, accumulating evidence suggests that SBI may contribute to the development of dementia, depression, and cognitive decline, particularly in the elderly population. The burden of SBI is substantial, with studies showing that up to 11 million Americans may experience a silent stroke annually. In AF patients, silent brain infarcts are common and can lead to progressive brain damage, even in those receiving anticoagulation therapy. The use of cerebral embolic protection devices (CEPDs) during TAVI has been explored to mitigate the risk of stroke; however, their efficacy remains under debate. Despite advancements in TAVI technology, cerebrovascular events, including silent brain lesions, continue to pose significant challenges, underscoring the need for improved preventive strategies and therapeutic approaches. We propose a device consisting of a strut structure placed at the base of the treated artery to model the potential risk of cerebral embolisms caused by atrial fibrillation, thromboembolism, or dislodged debris of varying potential TAVI patients. The study has been carried out in two stages. Both are based on computational fluid dynamics (CFD) coupled with the Lagrangian particle tracking method. The first stage of the work evaluates a variety of strut thicknesses and inter-strut spacings, contrasting with the device-free baseline geometry. The analysis is carried out by imposing flow rate waveforms characteristic of healthy and AF patients. Boundary conditions are calibrated to reproduce physiological flow rates and pressures in a patient's aortic arch. In the second stage, the optimal geometric design from the first stage was employed, with the addition of lateral struts to prevent the filtration of particles and electronegatively charged strut surfaces, studying the effect of electrical forces on the clots if they are considered charged. Flowrate boundary conditions were used to emulate both healthy and AF conditions. Results from numerical simulations coming from the first stage indicate that the device blocks particles of sizes larger than the inter-strut spacing. It was found that lateral strut space had the highest impact on efficacy. Based on the results of the second stage, deploying the electronegatively charged device in all three aortic arch arteries, the number of particles entering these arteries was reduced on average by 62.6 % and 51.2 %, for the healthy and diseased models respectively, matching or surpassing current oral anticoagulant efficacy. In conclusion, the device demonstrated a two-fold mechanism for filtering emboli: (1) while the smallest particles are deflected by electrostatic repulsion, avoiding micro embolisms, which could lead to cognitive impairment, the largest ones are mechanically filtered since they cannot fit in between the struts, effectively blocking the full range of particle sizes analyzed in this study. The device presented in this manuscript offers an anticoagulant-free method to prevent stroke and SBIs, imperative given the growing population of AF and elderly patients. [ABSTRACT FROM AUTHOR]

The editorial in the journal "Bioengineering (Basel)" discusses recent advances in fluid mechanics and acoustics in biomedical engineering. The research focuses on physiological processes in circulatory and respiratory systems, phonation, and their impact on human health. The article highlights the importance of computational tools and experimental diagnostics in developing new therapies and medical devices. Thirteen papers in the issue cover topics such as upper airway flow, cardiovascular flow, and blood rheology, showcasing the interdisciplinary nature of the field. [Extracted from the article]

The COVID-19 pandemic has highlighted the significant infection risks posed by aerosol-generating procedures (AGPs), such as intubation and cardiopulmonary resuscitation (CPR). Despite existing protective measures, high-risk environments like these require more effective safety solutions. In response, our research team has focused on developing a novel respiratory barrier enclosure designed to enhance the safety of healthcare workers and patients during AGPs. We developed a hood that covers the patient's respiratory area, incorporating a negative pressure system to contain aerosols. Using computational fluid dynamics (CFD) analysis, we optimized the hood's design and adjusted the negative pressure levels based on simulations of droplet dispersion. To test the design, Polyalphaolefin (PAO) particles were generated inside the hood, and leakage was measured every 10 s for 90 s. The open side of the hood was divided into nine sections for consistent leakage measurements, and a standardized structure was implemented to ensure accuracy. Our target was to maintain a leakage rate of less than 0.3%, in line with established filter-testing criteria. Through iterative improvements based on leakage rates and intubation efficiency, we achieved significant results. Despite reducing the hood's size, the redesigned enclosure showed a 36.2% reduction in leakage rates and an approximately 3204.6% increase in aerosol extraction efficiency in simulations. The modified hood, even in an open configuration, maintained a droplet leakage rate of less than 0.3%. These findings demonstrate the potential of a CFD-guided design in developing respiratory barriers that effectively reduce aerosol transmission risks during high-risk medical procedures. This approach not only improves the safety of both patients and healthcare providers but also provides a scalable solution for safer execution of AGPs in various healthcare settings. [ABSTRACT FROM AUTHOR]

This study aimed to examine the hemodynamic modifications in uncomplicated type B aortic dissection in relation to the location of re-entry tears using a computational fluid dynamics simulation. The geometry of uncomplicated type B aortic dissection was reconstructed using computed tomography images. Subsequently, 10 virtual models were artificially generated with re-entry tears at various locations. The simulation results indicated that most models with re-entry tears had lower pressure and wall shear stress than those without re-entry tears. The overall pressure distribution of the true lumen was greater than that of the models without re-entry tears when the re-entry tear was placed at the end of the false lumen. Furthermore, the recirculation phenomenon in the false lumen was reduced as the re-entry tear was relocated to the distal region of the aorta. To determine whether and how to perform fenestration surgery in patients with uncomplicated type B aortic dissection, these computational results can be used as supplemental indicators. However, further validation in a larger number of patients through additional investigation is necessary. [ABSTRACT FROM AUTHOR]

The sparse matrix–vector product (SpMV) is a fundamental computational kernel utilized in a diverse range of scientific and engineering applications. It is commonly used to solve linear and partial differential equations. The parallel computation of the SpMV product is a challenging task. Existing solutions often employ a fixed number of threads assignment to rows based on empirical formulas, leading to sub-optimal configurations and significant performance losses. Elegante, our proposed machine learning-powered tool, utilizes a data-driven approach to identify the optimal thread configuration for SpMV computations within a shared memory architecture. It accomplishes this by predicting the best thread configuration based on the unique sparsity pattern of each sparse matrix. Our approach involves training and testing using various base and ensemble machine learning algorithms such as decision tree, random forest, gradient boosting, logistic regression, and support vector machine. We rigorously experimented with a dataset of nearly 1000+ real-world matrices. These matrices originated from 46 distinct application domains, spanning fields like robotics, power networks, 2D/3D meshing, and computational fluid dynamics. Our proposed methodology achieved 62% of the highest achievable performance and is 7.33 times faster, demonstrating a significant disparity from the default OpenMP configuration policy and traditional practice methods of manually or randomly selecting the number of threads. This work is the first attempt where the structure of the matrix is used to predict the optimal thread configuration for the optimization of parallel SpMV computation in a shared memory environment. [ABSTRACT FROM AUTHOR]

Apart from headwind changes, crosswind changes may be hazardous to aircraft operation. This paper presents two cases of recently observed crosswind changes from the range height indicator scans of ground-based remote sensing meteorological equipment, namely an X-band microwave radar and a short-range LIDAR. Both instruments have a range resolution down to around 30 m, allowing the study of fine-scale details of the vertical profiles of cross-mountain airflow at the Hong Kong International Airport. Rapidly evolving winds have been observed by the equipment in tropical cyclone situations, revealing high levels of turbulence and vertically propagating waves. The eddy dissipation rate derived from radar spectrum width indicated severe turbulence, with values exceeding 0.5 m2/3 s−1. In order to study the feasibility of predicting such disturbed airflow, a mesoscale meteorological model and a computational fluid dynamics model with high spatial resolution are used in this paper. It is found that the mesoscale meteorological model alone is sufficient to capture some rapidly evolving airflow features, including the turbulence level, the waves, and the rapidly changing wind speeds. However, the presence of reverse flow could only be reproduced with the use of a building-resolving computational fluid dynamics model. This paper aims at providing a reference for airports to consider the feasibility of performing high-resolution numerical simulations of rapidly evolving airflow to alert the pilots in advance for airports in complex terrains and the setup of buildings. [ABSTRACT FROM AUTHOR]

Verifying the pattern of toxic gas dispersion simulations under mountainous conditions is vital for emergency response and rescue. In this study, a comparative analysis is conducted between CALPUFF (California Puff Model) and CFD (Computational Fluid Dynamics) gas dispersion modeling focusing on the range of Semi-Lethal Concentration (LC50) and Immediate Danger to Life and Health Concentration (IDLH). To identify general dispersion patterns, a hypothetical pipeline breakout accident in a mountainous area is simulated and thirteen groups of simulation conditions are set up for the experiments, including calm wind (velocity less than 0.5 m/s) and winds from the east (E), south (S), west (W), and north (N) at velocities of 1, 2, and 3 m/s with a 1 arc-second degree SRTM data as terrain data. Comparative experiments show the diffusion patterns of the two models are essentially consistent, and the overall dispersion range deviation between two methods is within 266 m. The evaluation of CALPUFF's adaptability for microscale mountainous environments indicates its potential use for high-sulfur gas fields and gas dispersion simulations in emergency scenarios. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has underscored the urgency of understanding virus transmission dynamics, particularly in indoor environments characterized by high occupancy and suboptimal ventilation systems. Airborne transmission, recognized by the World Health Organization (WHO), poses a significant risk, influenced by various factors, including contact duration, individual susceptibility, and environmental conditions. Respiratory particles play a pivotal role in viral spread, remaining suspended in the air for varying durations and distances. Experimental studies provide insights into particle dispersion characteristics, especially in indoor environments where ventilation systems may be inadequate. However, experimental challenges necessitate complementary numerical modeling approaches. Zero-dimensional models offer simplified estimations but lack spatial and temporal resolution, whereas Computational Fluid Dynamics, particularly with the Discrete Phase Model, overcomes these limitations by simulating airflow and particle dispersion comprehensively. This paper employs CFD-DPM to simulate airflow and particle dispersion in a coach bus, offering insights into virus transmission dynamics. This study evaluates the COVID-19 risk of infection for vulnerable individuals sharing space with an infected passenger and investigates the efficacy of personal ventilation in reducing infection risk. Indeed, the CFD simulations revealed the crucial role of ventilation systems in reducing COVID-19 transmission risk within coach buses: increasing clean airflow rate and implementing personal ventilation significantly decreased particle concentration. Overall, infection risk was negligible for scenarios involving only breathing but significant for prolonged exposure to a speaking infected individual. The findings contribute to understanding infection risk in public transportation, emphasizing the need for optimal ventilation strategies to ensure passenger safety and mitigate virus transmission. [ABSTRACT FROM AUTHOR]

Variable flow emitters are used in subsurface drip irrigation to address challenges in soil moisture transport. This study investigates the impact of flow channel structural parameters on the hydraulic performance and anticlogging ability of emitters using computational fluid dynamics (CFD) simulations and experimental tests. The results show that the realizable k–ε turbulence model can be used to simulate the flow field inside the variable flow emitter flow channel. The nRMSE between the measured (qm) and simulated (q) values of the flow rate is 11.23%, and the relative error between the measured (xm) and simulated (x) values of the flow index is 4.66%, which gives a high simulation accuracy. A polar analysis shows that the tooth angle (A) has the smallest effect on the effluent flow rate at 0.1 MPa (q0.1), x, and particle passage rate (η) of the variable flow emitter. Flow channel depth (D), tooth spacing (B), and tooth height (E) have a different order of precedence in the influence of the three indices, which are D > B > E > A, B > E > D > A and E > B > D > A, respectively. The value of η is positively correlated with the mean flow velocity (v) and the mean turbulent kinetic energy (k) in the flow channel, and η tends to increase and then decrease with the increase of x. The retention time of the particles in the flow channel is closely related to the magnitude of v and k. Three multivariate lin ear regression equations (R2 = 0.883–0.995) were constructed for q0.1, x, and η versus the flow channel structural parameters. The optimal design combination of channel structure parameters for different scenarios was determined using the scipy.optimize.minimize function in Python 3.8.0. The research results provide a reference for the optimal design of variable flow emitters. [ABSTRACT FROM AUTHOR]

Physics-informed neural networks (PINNs) have recently emerged as a promising alternative to traditional numerical methods for solving partial differential equations (PDEs) in fluid dynamics. By using PDE-derived loss functions and auto-differentiation, PINNs can recover solutions without requiring costly simulation data, spatial gridding, or time discretization. However, PINNs often exhibit slow or incomplete convergence, depending on the architecture, optimization algorithms, and complexity of the PDEs. To address these difficulties, a variety of novel and repurposed techniques have been introduced to improve convergence. Despite these efforts, their effectiveness is difficult to assess due to the wide range of problems and network architectures. As a novel test case for PINNs, we propose one-dimensional shallow water equations with closed boundaries, where the solutions exhibit repeated boundary wave reflections. After carefully constructing a reference solution, we evaluate the performance of PINNs across different architectures, optimizers, and special training techniques. Despite the simplicity of the problem for classical methods, PINNs only achieve accurate results after prohibitively long training times. While some techniques provide modest improvements in stability and accuracy, this problem remains an open challenge for PINNs, suggesting that it could serve as a valuable testbed for future research on PINN training techniques and optimization strategies. [ABSTRACT FROM AUTHOR]

The periodontal ligament (PDL) is crucial for maintaining the integrity and functionality of tooth-supporting structures. Mechanical forces applied to the tooth during orthodontic tooth movement generate pore pressure gradients, leading to interstitial fluid movement within the PDL. The generated fluid shear stress (FSS) stimulates the remodeling of PDL and alveolar bone. Herein, we present the construction of a parallel fluid-flow apparatus to determine the effect of FSS on PDL cells. The chamber was designed and optimized using computer-aided and computational fluid dynamics software. The chamber was formed by PDMS using a negative molding technique. hPDLCs from two donors were seeded on microscopic slides and exposed to FSS of 6 dyn/cm2 for 1 h. The effect of FSS on gene and protein expression was determined using RT-qPCR and Western blot. FSS upregulated genes responsible for mechanosensing (FOS), tissue formation (RUNX2, VEGFA), and inflammation (PTGS2/COX2, CXCL8/IL8, IL6) in both donors, with donor 2 showing higher gene upregulation. Protein expression of PTGS2/COX2 was higher in donor 2 but not in donor 1. RUNX2 protein was not expressed in either donor after FSS. In summary, FSS is crucial in regulating gene expression linked to PDL remodeling and inflammation, with donor variability potentially affecting outcomes. [ABSTRACT FROM AUTHOR]

This paper proposes a method based on Computational Fluid Dynamics (CFD) and the detection of Wind Energy Extraction Latency for a given wind turbine (WT) designed for ultra-short-term (UST) wind energy forecasting over complex terrain. The core of the suggested modeling approach is the Wind Spatial Extrapolation model (WiSpEx). Measured vertical wind profile data are used as the inlet for stationary CFD simulations to reconstruct the wind flow over a wind farm (WF). This wind field reconstruction helps operators obtain the wind speed and available wind energy at the hub height of the installed WTs, enabling the estimation of their energy production. WT power output is calculated by accounting for the average time it takes for the turbine to adjust its power output in response to changes in wind speed. The proposed method is evaluated with data from two WTs (E40-500, NM 750/48). The wind speed dataset used for this study contains ramp events and wind speeds that range in magnitude from 3 m/s to 18 m/s. The results show that the proposed method can achieve a Symmetric Mean Absolute Percentage Error (SMAPE) of 8.44% for E40-500 and 9.26% for NM 750/48, even with significant simplifications, while the SMAPE of the persistence model is above 15.03% for E40-500 and 16.12% for NM 750/48. Each forecast requires less than two minutes of computational time on a low-cost commercial platform. This performance is comparable to state-of-the-art methods and significantly faster than time-dependent simulations. Such simulations necessitate excessive computational resources, making them impractical for online forecasting. [ABSTRACT FROM AUTHOR]

An auxiliary structure can significantly improve the wind-trapping capacity of the Savonius wind turbine. In this study, a novel auxiliary structure called a wind energy gathering structure (WEGS) is proposed, and its five parameters, namely the lengths of the shrinkage and diffusion tubes, the length of the centerboard, the length of the throat, the length of the wind board, and the shrinkage and diffusion angles, are investigated using computational fluid dynamics (CFD) and Taguchi's method. Meanwhile, Taguchi's method and ANOVA reveal that among the studied parameters, the shrinkage and diffusion angles, the length of the centerboard, and the lengths of the shrinkage and diffusion tubes have a more significant influence on the performance of the WEGS. At a tip speed ratio (TSR) value of 1 and a wind speed of 7 m/s, the optimized combination of the WEGS parameters obtained by Taguchi's method improves the mean torque coefficient of the turbine by 42.1%. Moreover, at other TSRs (0.6–1.2), the turbine with the WEGS also outperforms an open turbine in terms of aerodynamic (increases of 20.1–53%) and lifetime performance. [ABSTRACT FROM AUTHOR]

Gas evolution and flow patterns inside an alkaline electrolyzer cell strongly affect efficiency, although such effects have not been explored in detail to date. The present study aims to critically analyze the dependence of cell performance on the multiphase flow phenomena, defining some key metrics for its assessment using CFD. Six performance indicators, involving gas accumulation, bubble coverage, and flow uniformity, are applied to a 3D CFD model of an alkaline cathodic cell, and possible optimizations of the cell geometry are evaluated. The results demonstrate the complexity of defining the optimal indicator, which strictly depends on the case study and on the analysis at hand. For the cell analyzed herein, the parameters linked to the electrode volume fraction were indicated as the most influential on the cell efficiency, allowing us to define the best geometry case during the optimization. Furthermore, a sensitivity analysis was conducted, which showed that higher mass flow rates are generally preferable as they are linked to higher bubble removal. Higher current densities, allowing enhanced gas production, are instead associated with slightly lower efficiencies and stronger nonuniformity of the electrolyte flow inside the cell. [ABSTRACT FROM AUTHOR]

The melting of scrap and hot briquetted iron (HBI) in an AC electric arc furnace (EAF) is simulated by an advanced 3D computational fluid dynamics (CFD) model that captures the arc heating, the scrap/HBI melting process, and the solid collapse mechanisms. The CFD model is used to simulate a scenario where charge layering and EAF power profiles are provided by a real EAF operation. CFD simulation of the EAF operation shows proper prediction of the charge melting when compared with standard industry practice. Namely, the CFD model predicts a 32.5%/67.5% ratio of solid/liquid steel at the beginning of refining, which approaches the 30%/70% ratio used in standard practice. Based on this prediction, the melting rate in the CFD results differs by 8.3% from actual EAF operation. The impact of charge layering on melting is also investigated. CFD results show that distributing charge material into a greater number of layers in the first bucket (10 layers as compared to 4) enhances the melting rate by 12%. However, including dense material at the bottom of the furnace deteriorates melting performance, reducing the impact of the number of layers of the charge. The CFD platform can be used to optimize the use of HBI/scrap in real EAF operations and to determine best recipe practices. [ABSTRACT FROM AUTHOR]

This study adapted the mean age of air, a time scale widely utilized in evaluating indoor ventilation, to assess the impact of building layouts on urban ventilation capacity. To distinguish it from its applications in enclosed indoor environments, the adapted index was termed the effective mean age of air ( τ ¯ E ). Based on an experimentally validated method, computational fluid dynamic (CFD) simulations were performed for parametric studies on four generic parameters that describe urban morphologies, including building height, building density, and variations in the heights or frontal areas of adjacent buildings. At the breathing level (z = 1.7 m), the results indicated three distinct distribution patterns of insufficiently ventilated areas: within recirculation zones behind buildings, in the downstream sections of the main road, or within recirculation zones near lateral facades. The spatial heterogeneity of ventilation capacity was emphasized through the statistical distributions of τ ¯ E . In most cases, convective transport dominates the purging process for the whole canopy zone, while turbulent transport prevails for the pedestrian zone. Additionally, comparisons with a reference case simulating an open area highlighted the dual effects of buildings on urban ventilation, notably through the enhanced dilution promoted by the helical flows between buildings. This study also serves as a preliminary CFD practice utilizing τ ¯ E with the homogenous emission method, and demonstrates its capability for assessing urban ventilation potential in urban planning. [ABSTRACT FROM AUTHOR]

The vortex tube, also known as the Ranque–Hilsch vortex tube, is a mechanical device that separates compressed gas into hot and cold streams. It offers a reliable and cost-effective solution to a wide range of cooling applications, as it operates without moving parts, electricity, or refrigerants. Research on vortex tubes has primarily focused on understanding the mechanisms of energy separation and optimizing cooling performance by altering geometric operational parameters. In this study, a Computation Fluid Dynamics (CFD) analysis was conducted to enhance the prediction of energy separation performance and improve the overall energy efficiency of the vortex tube. First, the geometry of the experimental device was modeled to closely match its actual shape, unlike the simplified geometries commonly used in previous CFD studies. Simulations were then carried out with variation in grid systems and turbulence models, and the results demonstrated improved agreement with experimental data compared to those reported in previous studies. Finally, simulations with a modified shape of the inlet nozzle shape were performed, revealing that the energy separation effect of the vortex tube could be enhanced by approximately 15% with an increased inlet expansion ratio ( ϵ ) while maintaining a constant nozzle length. [ABSTRACT FROM AUTHOR]

The production of raw-crushed wind-turbine blade (RCWTB) and its addition to conventionally designed self-compacting Concrete (SCC) enable us to provide a second life to wind-turbine blades. However, SCC containing RCWTB must show proper fresh behavior, an aspect evaluated in this paper both experimentally and through simulations based on computational fluid dynamics (CFD) for RCWTB additions up to 3.0% by volume. In experimental terms, RCWTB reduced the flowability and passing ability of SCC, and slowed SCC flow, although the performance of SCC with 1.5% RCWTB was adequate under free-flow conditions. In terms of modeling, RCWTB did not impact yield stress and increased plastic viscosity. CFD modeling under free flow, regardless of the presence or not of obstacles simulating concrete reinforcement, was successful, especially in the long term. Nevertheless, the modeling of the passing ability was not accurate; precision could be improved by simulating the effect of the individual GFRP fibers within the SCC flow. Finally, the mechanical properties of SCC were negatively impacted by RCWTB, the stitching effect of the GFRP fibers not being effective in an SCC with a conventional design. A specific SCC design when adding RCWTB is therefore needed to advance in the use of this waste in this concrete type. [ABSTRACT FROM AUTHOR]

In this article, we present a software tool developed in Python, named T-WorkFlow. It has been devised to meet some of the design needs of Tatuus Racing S.p.a., a leading company in the design and production of racing cars for the FIA Formula 3 Regional and Formula 4 categories. The software leverages the open-source tools OpenFOAM and FreeCAD to fully automate the fluid dynamics simulation process within car radiators. The goal of T-WorkFlow is to provide designers with precise and easily interpretable results that facilitate the identification of the geometry, ensuring optimal flow distribution in the radiator channels. T-WorkFlow requires the radiator's geometry files in .stp and .stl formats, along with additional user inputs provided through a graphical interface. For mesh generation, the software leverages the OpenFOAM tools blockMesh and snappyHexMesh. To ensure uniform mesh quality across different configurations, and thus, comparable numerical results, various pre-processing operations on the specific geometry files are needed. After generating the mesh, T-WorkFlow automatically defines a control surface for each radiator channel to monitor the volumetric flow rate distribution. This is achieved by combining the OpenFOAM command topoSet with specific geometric information directly obtained from the radiator's CAD through FreeCAD. During the simulation, the software provides various outputs that automate the main post-processing operations, enabling quick and easy identification of the configuration that ensures the desired performance. [ABSTRACT FROM AUTHOR]

Designing and improving collection systems for dust and toxic pollutants is crucial for improving the safety and indoor air quality of laboratory buildings. Push–pull ventilation systems with uniformly distributed parallel airflow have been proven to be of great help in this task. Designing exhaust hoods with parallel airflow distribution can effectively enhance the airflow uniformity of push–pull ventilation systems, especially when combining it with the implementation of rectifying orifice plates on the exhaust hoods. Therefore, this study combines a computational fluid dynamics (CFD) method and experimental approach to analyze the influence of key factors that lead to improvements in the airflow uniformity through the use of rectifying orifice plates, namely the aperture and porosity, as well as the number of rectifying orifice plates on the airflow uniformity of exhaust hoods. The study shows the following: (1) The aperture of the rectifying orifice plate considerably affects the airflow uniformity of the exhaust hood. Specifically, near the exhaust hood outlet, the airflow uniformity is negatively correlated with the aperture; conversely, near the exhaust hood inlet, the airflow uniformity is positively correlated with the aperture. (2) A rectifying orifice plate with a porosity of 35.43% can effectively improve the airflow uniformity of the exhaust hood. (3) Exhaust hoods with a double-layer rectifying orifice plate structure can improve airflow uniformity by approximately 40% compared to those with a single-layer structure. The above research results can guide the optimization of exhaust hood design to improve airflow uniformity, thereby effectively enhancing the capture efficiency of the push–pull ventilation system for dust and toxic pollutants and providing a safer environment for experimenters in laboratory buildings. [ABSTRACT FROM AUTHOR]