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Using plasma as an energy source in thermal spraying allows the processing of feedstock materials with high melting temperatures. In plasma spraying, hydrogen or nitrogen is commonly injected into the argon plasma, which increases the specific enthalpy and thermal conductivity. The objective of this study is to improve the understanding of this process through numerical simulation and to investigate the impact on the plasma properties. A comprehensive modelling approach for the electrodes in the three‐cathode plasma generator is built upon the previous work of the authors. The plasma is described as an electromagnetically reactive fluid in local thermodynamic equilibrium using temperature‐dependent thermodynamic and transport properties. The increase of flow temperature and velocity as well as the temperature distribution at the electrodes can be successfully simulated. The simulation model could accelerate parameter development for new coating systems in the future. This study completes the simulation model for multi‐arc plasma spraying using binary gas mixtures. [ABSTRACT FROM AUTHOR]

This article proposes the development of a novel polymer composites using non‐conventional materials, specifically constructional wastes such as red brick dust, in different weight percentages (0 wt.‐%, 10 wt.‐%, 20 wt.‐%, and 30 wt.‐%) and their erosion wear characteristics has been studied. Solid particle erosion test equipment is employed to evaluate the erosion wear characteristics of the composites. According to the study, adding red brick dust to epoxy resin enhances its erosion resistance. The influence of input parameters has also been evaluated using Taguchi approach. The results of this experiment show that the most important variables influencing the composites′ wear rate are impact velocity and filler content. The factor combinations A2B4C4D2E3 exhibit the lowest erosion wear. Moreover, a commercial finite element method tool called ANSYS 2019 R2 is utilized to estimate the wear rate of epoxy/red brick dust composites. After that, the experimental and predicted wear rates of the composites are compared, and it is discovered that the two sets of data accord better. Scanning electron microscopy is utilized to examine the eroded composite samples, and the potential wear causes are explored. [ABSTRACT FROM AUTHOR]

Key points Atrial fibrillation (AF) is the most common heart arrhythmia, linked to a five‐fold increase in stroke risk. The left atrial appendage (LAA), prone to blood stasis, is a common thrombus formation site in AF patients. The LAA can be classified into four morphologies: broccoli, cactus, chicken wing and windsock. Stroke risk prediction in AF typically relies on demographic characteristics and comorbidities, often overlooking blood flow dynamics. We developed patient‐specific non‐Newtonian models of blood flow, dependent on fibrinogen and haematocrit, to predict changes in LAA viscosity, aiming to predict stroke in AF patients. We conducted 480 computational fluid dynamics (CFD) simulations using the non‐Newtonian model across the four LAA morphologies for four virtual patient cohorts: AF + Covid‐19, AF + pathological fibrinogen, AF + normal fibrinogen, and healthy controls. Gaussian process emulators (GPEs) were trained on this in silico cohort to predict average LAA viscosity at near‐zero computational cost. GPEs demonstrated high accuracy in AF cohorts but lower accuracy when the chicken wing GPE was applied to other morphologies. Global sensitivity analysis showed fibrinogen significantly influenced blood viscosity in all AF cohorts. The chicken wing morphology exhibited the highest viscosity, while the AF + Covid‐19 cohort had the highest viscosity. Our non‐Newtonian model in CFD simulations confirmed fibrinogen's substantial impact on blood viscosity at low shear rates in the LAA, suggesting that combining blood values and geometric parameters of the LAA into GPE training could enhance stroke risk stratification accuracy. Fibrinogen has a significant effect on blood viscosity in the left atrial appendage (LAA) at low shear rates. Gaussian process emulators (GPEs) can predict the viscosity of blood in the LAA at near‐zero computational cost. Out of all LAA morphologies, the chicken wing morphology exhibited the highest average blood viscosity. High average blood viscosity in the LAA of atrial fibrilation + Covid‐19 patients was observed due to high fibrinogen levels in this cohort. Combining blood values and geometric parameters of the LAA into GPE training could enhance stroke risk stratification accuracy. [ABSTRACT FROM AUTHOR]

Stroke is a leading cause of death and disability worldwide. Atrial myopathy, including fibrosis, is associated with an increased risk of ischaemic stroke, but the mechanisms underlying this association are poorly understood. Fibrosis modifies myocardial structure, impairing electrical propagation and tissue biomechanics, and creating stagnant flow regions where clots could form. Fibrosis can be mapped non‐invasively using late gadolinium enhancement magnetic resonance imaging (LGE‐MRI). However, fibrosis maps are not currently incorporated into stroke risk calculations or computational electro‐mechano‐fluidic models. We present multiphysics simulations of left atrial (LA) myocardial motion and haemodynamics using patient‐specific anatomies and fibrotic maps from LGE‐MRI. We modify tissue stiffness and active tension generation in fibrotic regions and investigate how these changes affect LA flow for different fibrotic burdens. We find that fibrotic regions and, to a lesser extent, non‐fibrotic regions experience reduced myocardial strain, resulting in decreased LA emptying fraction consistent with clinical observations. Both fibrotic tissue stiffening and hypocontractility independently reduce LA function, but, together, these two alterations cause more pronounced effects than either one alone. Fibrosis significantly alters flow patterns throughout the atrial chamber, and particularly, the filling and emptying jets of the left atrial appendage (LAA). The effects of fibrosis in LA flow are largely captured by the concomitant changes in LA emptying fraction except inside the LAA, where a multifactorial behaviour is observed. This work illustrates how high‐fidelity, multiphysics models can be used to study thrombogenesis mechanisms in patient‐specific anatomies, shedding light onto the links between atrial fibrosis and ischaemic stroke. Key points: Left atrial (LA) fibrosis is associated with arrhythmogenesis and increased risk of ischaemic stroke; its extent and pattern can be quantified on a patient‐specific basis using late gadolinium enhancement magnetic resonance imaging.Current stroke risk prediction tools have limited personalization, and their accuracy could be improved by incorporating patient‐specific information such as fibrotic maps and haemodynamic patterns.We present the first electro‐mechano‐fluidic multiphysics computational simulations of LA flow, including fibrosis and anatomies from medical imaging.Mechanical changes in fibrotic tissue impair global LA motion, decreasing LA and left atrial appendage (LAA) emptying fractions, especially in subjects with higher fibrosis burdens.Fibrotic‐mediated LA motion impairment alters LA and LAA flow near the endocardium and the whole cavity, ultimately leading to more stagnant blood regions in the LAA. [ABSTRACT FROM AUTHOR]

Chemical vapor deposition of carbon precursors on Cu‐based substrates at temperatures exceeding 1000 °C is currently a typical route for the scalable synthesis of large‐area high‐quality single‐layer graphene (SLG) films. Using molecules with higher activities than CH4 may afford lower growth temperatures that might yield fold‐ and wrinkle‐free graphene. The kinetics of growth of graphene using hydrocarbons other than CH4 are of interest to the scientific and industrial communities. We measured the growth rates of graphene islands on Cu(111) foils by using C2H2, C2H4, C2H6 and CH4, respectively (each mixed with H2). From such kinetics data we obtain the activation enthalpy (ΔH≠) of graphene growth as shown in parentheses (C2H2 (0.93±0.09 eV); C2H4 (2.05±0.19 eV); C2H6 (2.50±0.11 eV); CH4 (4.59±0.26 eV)); C2Hy (y=2, 4, 6) show similar growth behavior but CH4 is different. Computational fluid dynamics and density functional theory simulations suggest that C2Hy differs from CH4 due to different values of adsorption energy and the lifetime of relevant carbon precursors on the Cu(111) surface. Combining experimental and simulation results, we find that the rate determining step (RDS) is the dissociation of the first C−H bond of CH4 molecules in the gas phase, while the RDS using C2Hy is the first dehydrogenation of adsorbed C2Hy that happens with assistance of H atoms adsorbed on the Cu(111) surface. By using C2H2 as the carbon precursor, high‐quality single‐crystal adlayer‐free SLG films are achieved on Cu(111) foils at 900 °C. [ABSTRACT FROM AUTHOR]

A tap‐to‐tap operation conducted in a 150 t AC electric arc furnace (EAF) by NLMK Indiana is used to validate a computational fluid dynamics (CFD)‐EAF solver. Model validation is conducted by comparing the electrodes position and melting rates obtained by CFD model against those reported in actual operation. Comparison demonstrates close alignment between simulation and actual process. Namely, electrode position is predicted with less than 5% error. Electrode bore‐in after the first bucket charge is predicted to within 3% of industrial data, whereas bore‐in prediction after the second bucket charge deteriorates due to arc instabilities driven by cave‐ins, not currently included in the CFD solver. At the beginning of the refining stage, the predicted ratio of solid to molten steel mass is 6% higher than that expected by industry. Validated tap‐to‐tap results are further analyzed to determine main features of the melting process. Specifically, in the results, reduction of molten steel temperature after each scrap charge and a temperature rise after electrode bore‐in are shown. Molten steel temperature further increases during the refining/melting stage due to reduction of arc heating losses. In the thermal analysis, it is shown that heating losses increase with pit size, reaching 25% right before charging of second bucket and 20% at the beginning of refining. [ABSTRACT FROM AUTHOR]

Unmanned underwater vehicles (UUVs) are currently one of the practical instruments to complete some human unreachable tasks such as deep‐sea exploration, hazardous chemical‐contaminated underwater areas, and very tight or narrow underwater channels. A remotely operated vehicle (ROV), one of the UUV categories, plays an important role in several missions and has been an active field of engineering research since its introduction. In this work, the new observation class ROV (OCROV) hull designs are introduced to provide more understanding of drag prediction, improve power management, and prolong the endurance. To represent the restricted underwater channel, the fluid domain duplicated the size of the underground water trunk main in Northern Bangkok with a diameter of 1000 mm is focused. The OCROV hull designs are based on a streamlined torpedo‐like shape OCROV. Computational fluid dynamics (CFD) code with Reynolds‐averaged Navier–Stokes (RANS) equations is used to calculate total resistance (RT), frictional resistance (RF), and pressure resistance (RP). The results for restricted areas are also compared against free stream (unbounded) conditions to introduce the blockage and its effects. [ABSTRACT FROM AUTHOR]

This study introduces an innovative real‐time surgical planning platform optimized for the treatment of arterial aneurysms using intrasaccular flow disruption (IFD) devices. This platform incorporates a cutting‐edge fast virtual deployment (FVD) algorithm alongside a discrete element method (DEM) for computational fluid dynamics (CFD) analyses. It facilitates the efficient virtual deployment of IFD devices, minimizing computational overhead while allowing for comprehensive postoperative hemodynamic efficacy assessment. The FVD algorithm employs an adaptive wall adherence and curvature control system, validated through both idealized and patient‐specific model simulations. Post‐treatment hemodynamic shifts are quantified by discretizing device wire filaments into discrete particles, which are then integrated with blood flow simulations for enhanced realism. The FVD algorithm efficiently executes virtual deployment of IFD devices within seconds, producing DEM‐CFD computational models that align closely with bench testing, traditional Finite Element Method (FEM) analyses, and angiographic data. DEM‐CFD outcomes link occlusion effectiveness to post‐implantation hemodynamic characteristics, influenced by the aneurysm's unique anatomical features and clinical intervention strategies. The proposed platform demonstrates substantial improvement in balancing computational efficiency with analytical precision. It provides a viable and innovative framework for real‐time surgical planning, presenting significant implications for clinical application in arterial aneurysm management. [ABSTRACT FROM AUTHOR]

This study presents an investigation of an innovative microfluidic flow separator using both numerical and experimental approaches to calibrate contrast‐enhanced ultrasound scanners. Numerical simulations were conducted using Lagrangian particles tracking and passive scalar transport methodologies using the OpenFOAM software. The experimental validation confirmed the accuracy of the numerical simulations, particularly at an imposed total pressure of 0.7P0, showing an excellent agreement in particle distributions. The study emphasizes the computational efficiency and modeling of passive scalar transport, providing valuable understanding into the behavior of scalar quantities in microfluidic systems. An optimized diffusion coefficient value of 10−7m2s−1 was identified, showing its critical role in achieving accurate simulation results and optimizing the performance of microfluidic flow separators for contrast‐enhanced ultrasound scanner calibration. [ABSTRACT FROM AUTHOR]

Endovascular coil embolization is the primary therapeutic modality for intracranial aneurysms. Substantial reports have been found regarding the coil packing density and inflow jet. However, the hemodynamic effect of increasing the rate of tamponade in the inflow jet area within the aneurysm remains unclear. In this study, individualized geometries of six intracranial aneurysms were recruited: all six aneurysms were located in the internal carotid artery. Two groups were created by changing the position and orientation of the microcatheter for the release of the third segment of the filling coil. The finite element method was used to simulate coil deployment. Computational fluid dynamics was used to characterize hemodynamics in post‐deployment aneurysms. The parameters evaluated included velocity reduction, wall shear stress (WSS), low WSS (LWSS), relative residence time (RRT), flow kinetic energy in the neck region of the aneurysms, and residual flow volume (RFV) in the aneurysms. At the peak time (t = 0.17 s), the targeted deployment group has similar proportion of LWSS area to conventional deployment groups: targeted 78.13% ± 34.59% versus normal 74.20% ± 36.94% (mean ± SD, p = 0.583). The targeted deployment group has a higher RRT area (targeted 16.84% ± 5.58% vs. normal 6.42% ± 5.67% [mean ± SD, p = 0.009]), smaller flow kinetic energy (targeted 9.43 ± 4.33 vs. normal 16.23 ± 5.92 [mean ± SD, p = 0.047]), and a larger RFV in the aneurysms (targeted 35.97 ± 24.35 mm3 vs. normal 25.80 ± 18.94 mm3 [mean ± SD, p = 0.44]). Inflow jets play an important role in the treatment of aneurysms, and deploying filling coils in accordance with inflow jets may result in a better hemodynamic environment. [ABSTRACT FROM AUTHOR]

Hydrogen is often envisioned as a green fuel and energy carrier. However, a greenhouse gas‐free production method is still needed for this purpose. A promising method is the pyrolysis of methane. In this study, we present the three‐dimensional simulation of methane pyrolysis in a microwave plasma torch operated in an argon–methane mixture. Due to the high gas temperatures, the chemistry is dominated by reactions between neutral particles. Therefore, the plasma is treated only as a heat source using space‐resolved gas temperature measurements as input. The end‐of‐pipe results of the simulation are compared to measured values, showing good agreement for methane conversion. [ABSTRACT FROM AUTHOR]

Background: A patient's subjective response to topical nasal decongestant is often used to screen for turbinate reduction surgery suitability. However, this anecdotal strategy has not been objectively and quantitatively evaluated. Methods: Prospective, longitudinal, and single‐blinded cohort study employing computational fluid dynamic modeling based on computed tomography scans at baseline, 30 min postoxymetazoline, and 2 months postsurgery on 11 patients with chronic turbinate hypertrophy. Results: Nasal obstruction symptom evaluation (NOSE) and visual analogue scale (VAS) obstruction scores significantly improved from baseline to postoxymetazoline and again to postsurgery (NOSE: 71.82 ± 14.19 to 42.27 ± 25.26 to 22.27 ± 21.04; VAS: 6.09 ± 2.41 to 4.14 ± 2.20 to 2.08 ± 1.56; each interaction p < 0.05), with significant correlation between the latter two states (r∼0.37–0.69, p < 0.05). Oxymetazoline had a broader anatomical impact throughout inferior and middle turbinates than surgery (many p < 0.05); however, the improvement in regional airflow is similar (most p > 0.05) and predominantly surrounding the inferior turbinate. Strong postoxymetazoline to postsurgery correlations were observed in decreased nasal resistance (r = 0.79, p < 0.05), increased regional airflow rates (r = ‐0.47 to −0.55, p < 0.05) and regional air/mucosa shear force and heat flux (r = 0.43 to 0.58, p < 0.05); however, only increasing peak heat flux significantly correlated to symptom score improvement (NOSE: r = 0.48, p < 0.05). Conclusion: We present the first objective evidence that the "topical decongestant test" can help predict turbinate reduction surgery outcomes. The predictive effect is driven by similar improvementin regional airflow that leading to improved air/mucosa stimulations (peak heat flux) rather than through reduced nasal resistance. [ABSTRACT FROM AUTHOR]

The microstructure characteristics and the properties of rolled steels are significantly affected by the heat transfer and boiling phenomena occurring during the jet impingement cooling on run‐out tables (ROT). In this study, experiments are conducted using a full industrial‐scale ROT facility with rectangular plates made of low‐carbon stainless steel (type 316L). The plate is heated up to a temperature ranging from 500 to 900 °C, then rapidly impinged using a single circular water jet, and the temperature drop is captured using an infrared thermal camera (FLIR A615 25°–50 Hz type). The dissipated heat flux, estimated experimentally using a 2D inverse heat conduction analysis, ranges from 6.1 to 3.4 MW m−2 across different zones along the plate surface. The impact of different initial plate temperature on the boiling behavior is studied by developing a 2D‐computational fluid dynamics (CFD) model, and the results are closely aligned with the experimental findings. The results reveal that when estimating the heat flux from CFD simulations, the best accuracy is obtained when considering fluid temperature at a point close to the plate surface (about 1 μm above the surface). Furthermore, the maximum extracted heat flux (MHF) is significantly influenced by the initial temperature of the plate. Increasing the initial plate temperature from 500 to 900 °C led to an increase of 82% in the MHF in stagnation zone, and 137% increase in the parallel‐flow region. The CFD model presented in this study and the full calculation of the boiling curves numerically will pave the road for investigating various practical parameters in jet impingement cooling. [ABSTRACT FROM AUTHOR]

This study presents a novel protective membrane, (0.8MnCuSnOx‐NaCl)@M, designed for high‐efficiency filtration of dust particles and carbon monoxide (CO) gas offers superior moisture resistance, air permeability, and catalytic functionality in high‐humidity underground settings. The membrane, incorporating tin oxide‐doped CuMnOx into polyvinylidene fluoride (PVDF) fibers with sodium chloride (NaCl), achieves 99.99% air filtration efficiency, 323.68 mm s−1 air permeability, and 92.5% CO catalytic filtration efficiency. Concurrently, the membrane exhibited exceptional hydrophobicity, characterized by a substantial water contact angle of 116.7°, negligible water staining, and a high hydrostatic pressure rating of 2035 Pa, suitable for humid environments. Furthermore, the water absorption profile of the membrane featured a diminished hydroxyl vibrational band, accompanied by a sustained CO conversion efficiency, attesting to its resistance to moisture‐induced deterioration. Computational fluid dynamics (CFD) simulations further clarify the membrane's filtration mechanism, indicating its potential for selective CO and particle filtration. This study provides a reliable idea for the development of moisture‐resistant fiber membranes with high efficiency for filtration of dust and CO. and underscores the synergy of experimental and theoretical approaches. [ABSTRACT FROM AUTHOR]

A stagnation‐flow reactor was employed to investigate the decomposition of ammonia over a Ni/Al2O3 catalyst across a range of system pressures and ammonia mole fractions. The results indicate that the system pressure has a negligible impact on the light‐off behavior and the concentration profiles of NH₃. A comparison of 1D modelling with 3D computational fluid dynamics (CFD) computations justifies the use of the simpler flow model. Good agreement between experiments and the 1D simulation is achieved for two different kinetic models from literature in the mainly diffusion‐controlled regime. For lower temperatures, at which the process is kinetically controlled, the two mechanisms exhibit significant differences. The stagnation‐flow reactor concept is shown to be a promising tool for understanding, developing, and validating the reaction kinetics of heterogeneous catalytic processes. [ABSTRACT FROM AUTHOR]

Single‐particle reactors in lab‐scale are a promising technology to gain an in‐depth understanding of the intricate reaction and transport processes that occur in catalyst particles under operando conditions. It is not described whether the effect of the bounding walls in such narrow flow channels influence the processes at the particle. Therefore, this work applies three‐dimensional (3D) computational fluid dynamics (CFD) simulations to analyze the drag coefficient CD alongside the local and average particle Nusselt number Nup as characteristic local and integral quantities in the range of particle Reynolds numbers 10 ≤ Rep ≤ 103. An equation is derived to correct for the wall effects on CD and Nup and assist the experimenter in the interpretation of measured results. [ABSTRACT FROM AUTHOR]

Mixing in biogas fermenters is complex due to the non‐Newtonian rheology of biogenic substrates, which exhibit both pseudoplasticity and elasticity. It is yet unclear how these non‐Newtonian properties affect propeller flows and the mixing behavior in fermenters. Therefore, propeller flows in Newtonian as well as shear‐thinning inelastic and elastic fluids are compared numerically and validated against particle image velocity (PIV) data. Elastic normal stresses lead to an increase of pumping rates in the laminar regime and a suppression of the formation of a propeller jet in the transitional regime. Thus, flow rates are severely overestimated by the inelastic, shear‐thinning model in this regime. The results indicate that elasticity is critical for an accurate modeling of flows of biogenic substrates. [ABSTRACT FROM AUTHOR]

System‐scale computational fluid dynamics (CFD) simulations in chemical and process engineering remain limited owing to the complexity of integrating the results obtained at different scales. The present study addresses this issue by correlating the flow behaviors calculated by CFD in porous media at the micro‐scale and the macro‐scale using deep neural network (DNN) technology. The DNN model is trained using a dataset constructed from the results obtained for a large number of particle‐scale CFD simulations that are coupled to macroscopic governing equations. Comparisons with experimental results obtained with a packed bed show that the proposed CFD‐DNN method provides predictions of pressure drop with an accuracy that is 28% greater than that of a method based on the Ergun equation. [ABSTRACT FROM AUTHOR]

This study investigates, for the first time ever, the suffusion on gap‐graded granular soils under torsional shear conditions from a microscopic perspective. A numerical model of the hollow cylinder torsional shear test (HCTST) using the discrete element method (DEM) is first developed, where an algorithm for simulating the real inner and outer rubber membranes of the hollow cylinder apparatus (HCA) is introduced. After the validation, the computational fluid dynamics (CFD) approach is introduced for the coupling between the particle and fluid phases. Then, a series of the coupled CFD‐DEM suffusion simulations considering the rotation of the major principal stress axis (α) and intermediate principal stress ratio (b) are conducted. It is found that more fine particles are eroded in cases having smaller α and b, and the clogging phenomenon in the middle zones becomes more significant as both α and b increase. From the microscopic perspective, the specimens whose contact anisotropy principal direction is close to the fluid direction will lose more fines, and the anisotropy magnitude also plays an important role. In addition, the differences in structure and vertical connectivity of the pores in HCTST samples under various complex loading conditions cause fine particles to have different migration paths, further resulting in different fines mass loss. [ABSTRACT FROM AUTHOR]

This article explores the utilization of a synthetic jet as an approach to cool microelectronic devices, addressing their thermal management needs. The study includes both experimental measurements and numerical simulations to gain a comprehensive understanding of the heat transfer characteristics and fluid flow patterns generated by the synthetic jet actuator. The average Nusselt number (Nu) of the synthetic jet impinging flow with the dimensionless separation distances of the orifice to the heated surface (H/D) is investigated at different Reynolds numbers. A dynamic mesh scheme is employed in performing the simulations of the fluid domain to showcase the diaphragm's vibration and its deformation over time. The velocity profiles exhibit that the synthetic jet flow prompts the formation of two countervortices during every vibrating cycle of the diaphragm. The experimental results align closely with the predicted outcomes, indicating that the synthetic jet significantly enhances heat transfer by 3.1 times relative to the natural convection in the case of (H/D = 8.4) across different Reynolds numbers while maintaining low power consumption, a compact size, and a noise‐free operation. [ABSTRACT FROM AUTHOR]

This study optimizes the main parameters of the cold‐side heat exchanger (CHE) longitudinal fin, including fin quantity (Nf), fin thickness (Tf), and fin height (Hf), to enhance the performance of motorcycle exhaust thermoelectric generator units (TGUs) utilizing the computational fluid dynamics approach. The investigation shows that these parameters significantly affect the dissipation area of the CHE heat and the outside air velocity distribution in fin gaps, resulting in the fluctuation of TGU output power. The output power increases with respect to Hf; nevertheless, it first increases as Nf and Tf increase but decreases dramatically when Nf or Tf becomes too large. Besides, Hf significantly affects output power, and its impact is almost independent of Tf and Nf, and vice versa; meanwhile, Tf and Nf have a strong relation. This study proposes two Hf of 40 and 60 mm along with the optimal Tf of 1 mm and Nf of 29, providing significantly high output power, low weight, and compact size for TGU. This work contributes insight into the effect of CHE parameters on the TGU performance, and it is a crucial case study for selecting suitable heat sink parameters for TGU, considering practical requirements and conditions. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive numerical analysis of a full‐scale horizontal‐axis floating offshore wind turbine (FOWT) rotor subjected to harmonic surging motions under both laminar and turbulent inflow conditions. Utilizing high‐fidelity computational fluid dynamics (CFD) simulations, namely, large eddy simulation (LES) with actuator line model (ALM), this research investigates the rotor performance, wake characteristics, and wake structures of a surging FOWT in detail. The study delves into the influence of varying inflow turbulence intensities, surging settings, and their interplay on the aerodynamic performance and the wake aerodynamics of a FOWT rotor. The results show that, through employing the phase‐averaging technique, surge‐induced periodic coherent structures (SIPeCS) can be identified in the wake of all the surging cases studied, irrespective of the inflow conditions and the surging settings. Additionally, the findings show that the faster wake recovery observed in the surging cases is not caused by enhancing the instability‐induced turbulence level, a previously accepted hypothesis. Instead, the results indicate that it is due to the enhanced advection process resulting from the induction fields of SIPeCS that causes the wake to recover faster. The analysis of rotor performance shows that the time‐averaged rotor performances are affected by the intricate aerodynamics arising from the surging motions. With certain surging settings, the time‐averaged thrust and the time‐averaged power of a surging rotor are found to be simultaneously lower and higher compared with those of a fixed rotor. Furthermore, the study underscores the importance of considering both the magnitude of surging and the rate of surging simultaneously to fully characterize the hysteresis load on a surging rotor. [ABSTRACT FROM AUTHOR]

In the framework of process safety studies, consequence assessment of accidental scenarios is a crucial step affecting the eventual risk profile associated with the facilities under analysis. Conventional models used for consequence assessment are based on integral models, and may not be adequate to cope with the dynamic evolution of accidental scenarios and their three‐dimensional features. On the other hand, consequence assessment models based on computational fluid dynamics (CFD) approaches are promising to cope with complex scenarios and environments, but setting the simulation introduces relevant uncertainties associated with both the input data, assumptions, and with the modelling of physical effects involved. In the present study, uncertainty quantification (UQ) techniques are applied to support advanced safety studies based on CFD simulations of hazardous gas dispersion. Firstly, the accidental scenarios are characterized by defining release scenarios and conditions and quantifying source terms using integral models. At the same time, input meteorological data are gathered. This enables the development of high‐fidelity CFD simulations of gas dispersion based on different input sets and eventually the implementation of UQ techniques. The generalized polynomial chaos (gPC) expansion is employed to obtain hazardous gas concentration based on the variation of wind direction and speed. The present method is applied for the analysis of a real plant featuring a complex layout. The results show the advantages of the present approach by quantifying the influence of meteorological conditions and providing indications for supporting the development of protection systems and emergency measures. [ABSTRACT FROM AUTHOR]

Shale reservoirs are highly complex and are difficult to study using conventional reservoir simulation tools. This study introduces a novel methodology for estimating production from complex shale gas reservoirs by coupling decline curve analysis (DCA) with computational fluid dynamics (CFD) simulations. The proposed method uses exponential DCA to analyze production data from a dual porosity–permeability shale gas transport model. These complexities include fracture characteristics, geomechanical properties, nanopore confinement effects, and multiple flow mechanisms contributing to the total production performance. The shale gas transport model is validated through historical production data from Marcellus shale. The new methodology also tests fracture characteristics. It shows that increased porosity and permeability will increase the recoverable reserves but will have varying effects on the decline rate. The paper demonstrates the advantages of the proposed methodology over conventional reservoir simulation tools. It provides insights into the factors affecting shale gas production performance through the inclusion of the complexities of an unconventional shale gas reservoir. The paper provides a proof of concept on the particular reservoir of which the field data is provided—Barnett and Marcellus Shale. [ABSTRACT FROM AUTHOR]

Utilizing computational fluid dynamics (CFD) for analytical purposes, this study developed a fundamental model employing the multiple reference frame (MRF) method, facilitated by the CFX simulation platform. The investigation conducted numerical simulations of the flow field within the rotor‐stator assembly of a high shear mixer, guided by the Navier–Stokes equations and the standard k‐ε turbulence model. To quantify the homogenization efficacy of the high shear mixer under scenarios with and without energy consumption considerations, the study introduced two distinct parameters: the mixing index (γ) and the energy ratio mixing index (λ). The impact of structural parameters such as the number of rotor‐stator teeth, radial clearance, and tooth apex‐base axial clearance on the local flow characteristics—velocity, pressure, turbulent kinetic energy, shear rate distribution, net power consumption, and the specified indices—was meticulously analyzed. This analysis aimed to identify the optimal structural configurations for the mixer, considering energy efficiency and mixing effectiveness, and to determine the relative influence of these structural variations on the mixing index (γ) and the energy ratio mixing index (λ). [ABSTRACT FROM AUTHOR]

The study utilized computational fluid dynamics (CFD) simulations employing the volume of fluid (VOF) model to analyze silicone oil–air flows in a vertical pipe with a diameter of 67 mm. Various structured meshes ensured grid independence, and the k‐ε realizable model addressed turbulence. The analysis characterized bubbly to annular flows, involving the evaluation of flow patterns, radial void fractions, void fraction time series, probability density functions (PDFs), power spectral densities (PSDs), and mean void fractions. Results indicated a transition from bubbly to annular flow with increasing gas velocities and notable changes in radial void fraction profiles. Void fraction exhibited significant variations with distinct flow patterns at constant liquid velocity. PDFs identified flow regimes, and PSDs revealed frequency patterns. CFD results were validated against experiments, demonstrating good agreement. The validated CFD model was utilized to investigate radial gas velocities and pressure drops, revealing a shift from uniform velocity distributions to irregular patterns and a decrease in total pressure drop with an increase in gas superficial velocity. The model was also applied to a water‐air system to explore two‐phase flow behaviour. The impact of superficial gas velocity on flow patterns and radial void fractions was studied through numerical analysis and compared with the silicone oil‐air system. Results showed that at extreme gas velocities (0.06 and 5.53 m/s), silicone oil exhibited bubbly and annular flows, while water displayed cap bubbly and churn flows. The significant variation in radial void fraction at these velocities emphasized the impact of fluid properties. [ABSTRACT FROM AUTHOR]

The integrated photovoltaic‐thermoelectric cooling systems (PV‐TECS) can be used to enhance the performance and life expectancy of commercial PV power plants for sustainable power generation. The objective of the study is to assess the efficacy of PV‐TECS to address these concerns. In this study, computational fluid dynamics/finite element method analysis and experimental investigation of photovoltaic micro‐modules (PVMM‐2) with a thermoelectric cooling system and a reference system without it (PVMM‐1), is carried out under real outdoor conditions. The logged data and infrared thermal imaging analysis results show that thermoelectric cooling is very effective in maintaining a consistent PV back temperature difference of 18.24°C between PVMM‐2 and the reference system, even reaching subzero temperature when the reference module operates close to 60°C. The simulated results are found to be in close agreement with the experimental results (R2 values of 0.83 and 0.94) which allows accurate prediction of system performance under actual solar loading conditions. Further analysis shows that PV‐TECS can be effectively used in photovoltaic power plants for efficiency enhancement with a gain in the range of 1%–22% for a monocrystalline PV module depending on location and type of integration. The study is of interest for further research to develop industrial applications. [ABSTRACT FROM AUTHOR]

Electrocatalytic nitrite reduction (e‐NO2−RR) offers an attractive strategy for industrial green ammonia synthesis. The understanding of electrochemical kinetics is the core to guarantee the efficient operation of e‐NO2−RR system. However, the application of the widely used Butler–Volmer equation should be restricted to the constraint of non‐mass transfer effects. In this work, an electrochemical macrokinetics equation for mass transfer restriction region was developed based on the traditional macrokinetics thought, which combined the Practical Butler–Volmer equation and Nernst‐Plank equation. The model validation was carried out by the combination of multiphysics‐field simulation, computational fluid dynamics simulation and experiments, and the results show that the average relative error between experiments and simulations is less than 2%. The results in this article contribute to an in‐depth understanding of the kinetics behavior for e‐NO2−RR and achieve the extension of electrochemical kinetics equation from non‐mass transfer restriction region to mass transfer restriction region. [ABSTRACT FROM AUTHOR]

It is frequent that gas leakage accidents occur at chemical enterprises located in slope terrain. Meet the requirement of urgently studying the gas leakage and diffusion law in slope terrain. In this study, we utilize computational fluid dynamics (CFD) to simulate the scenarios of propane leakage and diffusion under four distinct slope conditions, which are 0°, 10°, 15°, and 20°. The gas diffusion law under different slopes is investigated, and the influence of wind speed and wind direction on the diffusion process is also further analyzed. The study indicates that when the slope exceeds 15°, the change in slope exerts a pronounced influence on the dispersion of propane leakage. Compared with diffusion on flat ground, there is a distinct propane aggregation area at the bottom of the slope terrain. Also, the steeper the slope, the more noticeable the aggregation phenomenon. The increase of wind speed makes propane gas lifted, and the gas aggregation at the bottom of the slope decreases. In particular, at a wind speed of 3.3 m/s, the aggregation of propane at the bottom of the first 15° and 20° slopes is more pronounced. Under the upwind condition, the propane gas is entrained at the slope surface, increasing the propane concentration in the area around the tank, which in turn increases the safety risk. The findings of this study have significant implications for the rational layout of chemical enterprises, gas leakage monitoring, and emergency evacuation planning for leakage accidents. They can also help enhance chemical enterprises' safety prevention abilities and the efficiency of their emergency response. [ABSTRACT FROM AUTHOR]

Aero‐structural shape design and optimization of bridge decks rely on accurately estimating their self‐excited aeroelastic forces within the design domain. The inherent nonlinear features of bluff body aerodynamics and the high cost of wind tunnel tests and computational fluid dynamics (CFD) simulations make their emulation as a function of deck shape and reduced velocity challenging. State‐of‐the‐art methods address deck shape tailoring by interpolating discrete values of integrated flutter derivatives (FDs) in the frequency domain. Nevertheless, more sophisticated strategies can improve surrogate accuracy and potentially reduce the required number of samples. We propose a time domain emulation strategy harnessing temporal fusion transformers (TFTs) to predict the self‐excited forces time series before their integration into FDs. Emulating aeroelastic forces in the time domain permits the inclusion of time‐series amplitudes, frequencies, phases, and other properties in the training process, enabling a more solid learning strategy that is independent of the self‐excited forces modeling order and the inherent loss of information during the identification of FDs. TFTs' long‐ and short‐term context awareness, combined with their interpretability and enhanced ability to deal with static and time‐dependent covariates, make them an ideal choice for predicting unseen aeroelastic forces time series. The proposed TFT‐based metamodel offers a powerful technique for drastically improving the accuracy and versatility of wind‐resistant design optimization frameworks. [ABSTRACT FROM AUTHOR]

This paper focuses on the optimization of a winged UAV airframe utilizing a preliminary configuration and the combination of the Taguchi experimental design method and the evolutionary genetic optimization algorithm, along with computational fluid dynamics. Simulations were carried out based on the Reynolds‐averaged Navier–Stokes (RANS) equations and SST k‐ω turbulence model and the large eddy simulation (LES) for a speed of 50 m/s and a Reynolds number of 1.6 million. Optimization was conducted for six variables in a single stage, with 25 tests performed. The tested case is a winged UAV with a Lambda‐shaped airframe design named SACCON, featuring wings with a tilt angle of 53°. The objective function in this study is the ratio of lift to drag specified. A genetic algorithm is used in conjunction with an initial configuration to create a new aircraft. Ultimately, the newly designed airframe demonstrates a 14% improvement in aerodynamic efficiency compared to the default state, and the lift‐to‐drag ratio increases by 55%, successfully concluding the optimization process. [ABSTRACT FROM AUTHOR]

ABSTRACT Flow‐accelerated corrosion (FAC) is a complex phenomenon that poses a significant threat to the integrity of piping and fittings in power plants, affecting infrastructure protection and power production reliability. The presence of corrosive substances in the fluid and elevated flow velocity and temperature leads to increased material loss in piping and equipment. Understanding the intricate relationship among the contributing factors such as flow dynamics, environmental factors, and corrosion reactions is essential for developing effective prediction and mitigation strategies. This review discusses the recent advancements in the numerical modeling of FAC using computational fluid dynamics (CFD). The numerical models presented show abilities to predict FAC profiles across multiple power plant components, and a review was conducted on the evaluation of these predictions with experimental measurements. Notably, increased turbulence in the flow significantly contributed to prediction errors, emphasizing the need for advanced turbulence models in numerical simulations of FAC. Addressing these challenges is crucial for maintaining sustainable infrastructure and reducing industrial risks through enhanced predictive maintenance strategies. [ABSTRACT FROM AUTHOR]

Fish can use hydrodynamic stimuli, decoded by lateral line systems, to explore the surroundings. Eyeless species of the genus Sinocyclocheilus have evolved conspicuous horns on their heads, whereas the specific function of which is still unknown. Meanwhile, the eyeless cavefish exhibits more sophisticated lateral line systems and enhanced behavioral capabilities (for instance rheotaxis), compared with their eyed counterparts. Here, the influence of head horn on the hydrodynamic perception capability is investigated through computational fluid dynamics, particle image velocimetry, and a bioinspired cavefish model integrated with an artificial lateral line system. The results show strong evidence that the head horn structure can enhance the hydrodynamic perception, from aspects of multiple hydrodynamic sensory indicators. It is uncovered as that the head horn renders eyeless cavefish with stronger hydrodynamic stimuli, induced by double‐stagnation points near the head, which are perceived by the strengthened lateral line systems. Furthermore, the eyeless cavefish model has ≈17% higher obstacle recognition accuracy and lower cost (time and sensor number) than eyed cavefish model is conceptually demonstrated, by incorporating with machine learning. This study provides novel insights into form‐function relationships in eyeless cavefish, in addition paves the way for optimizing sensor arrangement in fish robots and underwater vehicles. [ABSTRACT FROM AUTHOR]

ABSTRACT The Taylor–Green vortex represents an exact solution of the Navier–Stokes equations in R2$\mathbb {R}^2$. In this work, an approximation of this solution in two spatial dimensions is proposed for weakly compressible flows. These flows are characterized by small compressibility (or, equivalently, by a small Mach number) and are often employed in computational fluid dynamics to approximate the behaviour of incompressible Newtonian fluids. In this framework, the proposed solution is expected to be a useful benchmark for numerical solvers that implement the weakly compressibility approximation. To this end, some numerical examples are reported in the final section of this work. [ABSTRACT FROM AUTHOR]

Porous organic cages (POCs) are a class of emerging porous materials with high porosity and selectivity for gas adsorption and separation. As a representative of first‐generation POCs, the cage molecule CC3, has huge potential for separating noble gases and volatile organic compounds (VOCs). 3D printing CC3 using direct ink writing (DIW) offers significant advantages to build complex structures. Through rational design, formulations that are both printable and functional are achieved. Optimised formulations have the elasto‐visco‐plastic behavior required while retaining the functional properties of the cages. The characterization of printed parts evidence that the CC3 structure and adsorption capacity are well preserved. BET surface areas vary with CC3 concentration and can reach up to ≈249 m2 g−1 for 70 wt% CC3. However, high CC3 content leads to a decrease in shrinkage, higher porosity, and low compressive strength ≈0.7 MPa. Computational fluid dynamics (CFD) is used to investigate the gas flow behavior through grid‐type structures with tailored geometric parameters. The results reveal that changing the offset distance and porosity manipulates the flow path, velocity distribution, and pressure drop. This work provides a pathway to design and fabricate structures with multi‐scale porosity that can be widely used for other functional materials and applications. [ABSTRACT FROM AUTHOR]

This research studied the performance of a spindle‐controlled steam ejector using models such as ideal gas and wet steam under various operating conditions based on computational fluid dynamics (CFD). A wet steam model incorporating nonequilibrium condensation was employed to simulate the complex flow phenomena within the ejector. The structure of the flow, entrainment ratio (Er), and shock wave characteristics of the steam ejector were examined in two different models. Results indicate that the spindle position has a substantial impact on steam ejector performance. For the ideal gas and wet steam models, the optimal spindle position (SP‐5) at a .1 MPa motive pressure achieves the highest entrainment ratios (Er) of 1.01 and 1.042, respectively. However, an ejector with a fixed geometry achieves Er values of only .517 and .549 for the ideal gas and wet steam models, under identical working conditions. This represents a substantial improvement of 89.8% over the fixed‐geometry ejector. The wet steam model consistently predicts 2%–4% higher Er values compared with the ideal gas model across all spindle positions. The study also reveals that increasing the motive pressure from .1 to .3 MPa reduces Er by up to 45.8% at the optimal spindle position, with the shock train length extending to 35% of the mixing chamber at .3 MPa. These findings offer insights for improving the design and optimization of variable‐geometry steam ejectors, potentially increasing efficiency in industrial applications. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) is a powerful tool to provide information on detailed turbulent flow in unit processes. For that reason, this study intends to reveal the flow structures in the horizontal pipe and biomass combustor. The simulation was aided by ANSYS Fluent employing standard k‐ ε model. The results show that a greater Reynolds number generates more turbulence. The pressure drop inside the pipe is also found steeper for small pipe diameters following Fanning's correlation. The fully developed flow for the laminar regime is found in locations where the ratio of entrance length to pipe diameter complies with Hagen–Poiseuille's rule. The sucking phenomenon in jet flow is also similar to the working principle of ejector. For the biomass combustor, the average combustion temperature is 356–696°C, and the maximum flame temperature is 1587–1697°C. Subsequently, air initially flows through the burner area and then moves to the outlet when enters the combustor chamber. Not so for particle flow, the particle experiences sedimentation in the burner area and then falls as it enters the combustor chamber. This study also convinces that secondary air supply can produce more circulating effects in the combustor. [ABSTRACT FROM AUTHOR]

Thermal runaway of polymerization reactions causes serious accidents. To study the emergency inhibition process of thermal runaway, a styrene thermal polymerization reaction model is established by using computational fluid dynamics (CFD) combined with a thermodynamic model. The DIV critical criterion is used to determine the critical point of the runaway reaction. The inhibitory effect of injection diameter, injection rate, and injection angle of inhibitor (ethylbenzene) on the styrene polymerization reaction is studied comprehensively. The injection mixing trajectory of the inhibitor is visualized by using the Lagrangian particle tracking method. The injection parameters are optimized to suppress thermal runaway by the response surface method. The result shows that a combination of injection parameters with 2 mm injection port diameter, 5 m/s injection rate, and 90° injection angle can improve the suppression effect of thermal runaway for the established model in this paper. This work provides a theoretical basis for preventing thermal runaway for polymerization reactions. [ABSTRACT FROM AUTHOR]

The efficacy of vaccine storage is significantly impacted by temperature fluctuations within the cooler, often exacerbated by using phase change materials in existing cooler designs for remote areas. These materials can undergo uneven melting and phase separation, leading to temperature instability and vaccine potency loss. In response to this challenge, the present study introduces a novel design of a portable, locally‐made solar‐powered cooler optimized for longer storage periods. The cooler's performance in terms of temperature distribution, airflow dynamics, and the coefficient of performance (COP) is meticulously examined through computational fluid dynamics (CFD) simulations. The simulated results were validated using experimental data from the open literature, ensuring accuracy and reliability. The findings indicate that the developed cooler achieves significant improvements over traditional models. For instance, the current model reaches a temperature of +12°C in just 84 min, compared to 208 min, as reported in the literature results. Moreover, the current model reaches a temperature of −12°C in 195 min and it has energy efficient with a COP of 4.5. Statistical analysis further confirms the reliability of the simulation results, with root mean square and mean absolute percentage errors of 6.587 and 24.2%, respectively. Additionally, a comparative study of five insulative materials highlights polyurethane (Po) as the top performer, with a heat transfer performance of 14.3%, followed by feather fiber (Fe) (18.7%), fly ash (Fl) (19.8%), fiberglass (Fi) (21.9%), and coconut fiber (Co) (25.9%). Notably, net present value (NPV) of $689.336 and $448.01 was obtained for economic analysis of the current model over the existing model, showing the feasibility of the study. Hence, the cooler's effectiveness in storing vaccines in isolated regions exceeds that of conventional models, providing a hopeful solution to tackle vital challenges in vaccine distribution and preservation. [ABSTRACT FROM AUTHOR]

Background and Objective: The updated World Health Organization (WHO) air quality guideline recommends an annual mean concentration of fine particulate matter (PM2.5) not exceeding 5 or 15 μg/m3 in the short‐term (24 h) for no more than 3–4 days annually. However, more than 90% of the global population is currently exposed to daily concentrations surpassing these limits, especially during extreme weather conditions and due to transboundary dust transport influenced by climate change. Herein, the effect of respirable

The article presents a semi‐automatic approach to generating structured hexahedral meshes of patient‐specific aortas ailed by aortic dissection. The condition manifests itself as a formation of two blood flow channels in the aorta, as a result of a tear in the inner layers of the aortic wall. Subsequently, the morphology of the aorta is greatly impacted, making the task of domain discretization highly challenging. The meshing algorithm presented herein is automatic for the individual lumina, whereas the tears require user interaction. Starting from an input (triangle) surface mesh, we construct an implicit surface representation as well as a topological skeleton, which provides a basis for the generation of a block‐structure. Thereafter, the mesh generation is performed via transfinite maps. The meshes are structured and fully hexahedral, exhibit good quality and reliably match the original surface. As they are generated with computational fluid dynamics in mind, a fluid flow simulation is performed to verify their usefulness. Moreover, since the approach is based on valid block‐structures, the meshes can be made very coarse (around 1000 elements for an entire aortic dissection domain), and thus promote using solvers based on the geometric multigrid method, which is typically reliant on the presence of a hierarchy of coarser meshes. [ABSTRACT FROM AUTHOR]

Experimental blood flow measurement techniques are invaluable for a better understanding of cardiovascular disease formation, progression, and treatment. One of the emerging methods is time‐resolved three‐dimensional phase‐contrast magnetic resonance imaging (4D flow MRI), which enables noninvasive time‐dependent velocity measurements within large vessels. However, several limitations hinder the usability of 4D flow MRI and other experimental methods for quantitative hemodynamics analysis. These mainly include measurement noise, corrupt or missing data, low spatiotemporal resolution, and other artifacts. Traditional filtering is routinely applied for denoising experimental blood flow data without any detailed discussion on why it is preferred over other methods. In this study, filtering is compared to different singular value decomposition (SVD)‐based machine learning and autoencoder‐type deep learning methods for denoising and filling in missing data (imputation). An artificially corrupted and voxelized computational fluid dynamics (CFD) simulation as well as in vitro 4D flow MRI data are used to test the methods. SVD‐based algorithms achieve excellent results for the idealized case but severely struggle when applied to in vitro data. The autoencoders are shown to be versatile and applicable to all investigated cases. For denoising, the in vitro 4D flow MRI data, the denoising autoencoder (DAE), and the Noise2Noise (N2N) autoencoder produced better reconstructions than filtering both qualitatively and quantitatively. Deep learning methods such as N2N can result in noise‐free velocity fields even though they did not use clean data during training. This work presents one of the first comprehensive assessments and comparisons of various classical and modern machine‐learning methods for enhancing corrupt cardiovascular flow data in diseased arteries for both synthetic and experimental test cases. [ABSTRACT FROM AUTHOR]

Background: Intraoperative 2D quantitative angiography (QA) for intracranial aneurysms (IAs) has accuracy challenges due to the variability of hand injections. Despite the success of singular value decomposition (SVD) algorithms in reducing biases in computed tomography perfusion (CTP), their application in 2D QA has not been extensively explored. This study seeks to bridge this gap by investigating the potential of SVD‐based deconvolution methods in 2D QA, particularly in addressing the variability of injection durations. Purpose: Building on the identified limitations in QA, the study aims to adapt SVD‐based deconvolution techniques from CTP to QA for IAs. This adaptation seeks to capitalize on the high temporal resolution of QA, despite its two‐dimensional nature, to enhance the consistency and accuracy of hemodynamic parameter assessment. The goal is to develop a method that can reliably assess hemodynamic conditions in IAs, independent of injection variables, for improved neurovascular diagnostics. Materials and methods: The study included three internal carotid aneurysm (ICA) cases. Virtual angiograms were generated using computational fluid dynamics (CFD) for three physiologically relevant inlet velocities to simulate contrast media injection durations. Time‐density curves (TDCs) were produced for both the inlet and aneurysm dome. Various SVD variants, including standard SVD (sSVD) with and without classical Tikhonov regularization, block‐circulant SVD (bSVD), and oscillation index SVD (oSVD), were applied to virtual angiograms. The method was applied on virtual angiograms to recover the aneurysmal dome impulse response function (IRF) and extract flow related parameters such as Peak Height PHIRF, Area Under the Curve AUCIRF, and Mean transit time MTT. Next, correlations between QA parameters, injection duration, and inlet velocity were assessed for unconvolved and deconvolved data for all SVD methods. Additionally, we performed an in vitro study, to complement our in silico investigation. We generated a 2D DSA using a flow circuit design for a patient‐specific internal carotid artery phantom. The DSA showcases factors like x‐ray artifacts, noise, and patient motion. We evaluated QA parameters for the in vitro phantoms using different SVD variants and established correlations between QA parameters, injection duration, and velocity for unconvolved and deconvolved data. Results: The different SVD algorithm variants showed strong correlations between flow and deconvolution‐adjusted QA parameters. Furthermore, we found that SVD can effectively reduce QA parameter variability across various injection durations, enhancing the potential of QA analysis parameters in neurovascular disease diagnosis and treatment. Conclusion: Implementing SVD‐based deconvolution techniques in QA analysis can enhance the precision and reliability of neurovascular diagnostics by effectively reducing the impact of injection duration on hemodynamic parameters. [ABSTRACT FROM AUTHOR]

Flow efficiency in a two‐strand continuous casting tundish is studied by analyzing the residential time distribution (RTD) curves in a small‐scale tundish water model using a conductive NaCl solution tracer. The velocity fields in the tundish water model are measured by particle image velocimetry, which is used to validate the results of the mathematical model in the article. It is found that the tracer concentration has a significant impact on the predicted dead volume fraction in the RTD analysis. Validated mathematical modeling of the computational fluid dynamics (CFD) technology is performed to explore the root cause of the defective results in the RTD analysis. It is found that the flow inside the tundish is sensitive to density variations caused by the injected tracer. A denser tracer will stay lower in the tundish by gravity and flow out of the tundish more quickly. A proper tracer concentration in the water model experiments is discussed to visualize the dead volume and improve tundish furniture design efficiently for future work, a new method using CFD modeling is proposed in this article, which can directly demonstrate the dead volume's location. [ABSTRACT FROM AUTHOR]

This review article reports the critical issue of reoxidation in clean steel production during secondary refining and continuous casting processes. Reoxidation presents substantial challenges to process stability and final product quality. Various sources of reoxidation, including exposure to oxidizing gases, reducible oxides in slag and refractories, and the presence of ferroalloys are explored. Fundamental reactions and their consequences, such as changes in steel composition, inclusion composition/morphology, and the formation of reaction products at the interface between liquid steel and refractory materials, are reviewed. High oxygen partial pressure on the refractory side is identified as a significant factor, particularly in tundish and continuous casting processes. To address reoxidation effectively, the review discusses modeling approaches like computational fluid dynamics and thermodynamic/kinetic modeling. In the industrial context, reoxidation in the tundish is mainly attributed to open‐eye formation in the tundish flux and reducible oxides like SiO2 in an insulating cover powder, for example, rice hust ash. Maintaining precise tundish flux control is crucial for steel cleanliness. In conclusion, this review highlights the multifaceted nature of reoxidation challenges in clean steel production. A comprehensive understanding of reoxidation mechanisms and the implementation of effective strategies are essential for achieving cleaner steel production. [ABSTRACT FROM AUTHOR]

Conventional fluids used in fission‐based water‐cooled nuclear reactors have lower heat transfer coefficients (HTCs) and thermal conductivity, which has led researchers to explore high‐performance fluids that can enhance heat transfer in routine operation and prevent core meltdown in the case of accidents. It is important to investigate a wide range of fluids that can help designers improve thermal hydraulic characteristics, such as HTC, critical heat flux, and minimum departure from nucleate boiling ratio (MDNBR). In this study, the effectiveness of nanofluids in enhancing heat transfer parameters, including thermal conductivity and heat capacity, was investigated. Four different nanofluids (Al2O3–H2O, ZrO2–H2O, Ag–H2O, and Si–H2O) with pure water as the primary coolant in an HPR‐1000 nuclear reactor were compared using computational methods. Due to computational limitations, only the flow channel among four fuel rods with the highest power density in the core was simulated using Eulerian computational fluid dynamics. The results of this study show that silver water (Ag–H2O) nanofluid outperformed other nanofluids and pure water. It had a higher average HTC and MDNBR, with a 67.15 % and 45.23 % improvement, respectively, compared to pure water. The fuel rod wall temperature was also reduced by 28.5 K with Ag–H2O compared to water. Comparison of current simulated results with literature data shows a good agreement. [ABSTRACT FROM AUTHOR]

A pressure correction method is proposed considering the influence of a dual factor. The applicability of a pressure correction method coupled with a drag model is discussed along with the accuracy of the simulation results obtained by such a pressure correction method. It is found that the present pressure correction method combined with the DBS (dual bubble size) drag model can accurately reflect the changing trend of gas holdup distribution with pressure. It is also established that results from this model applied to a bubble column match well with the experimental data. Finally, when compared with other pressure correction models, the proposed model shows better robustness in three‐dimensional simulations and can predict radial gas holdup distributions with better accuracy. [ABSTRACT FROM AUTHOR]

This paper explores the effects of egg orientation and yolk position during thermal processing using computational fluid dynamics simulation and experimentation. A carboxymethyl cellulose suspension was used to simulate the egg white, and a two‐dimensional model incorporated an air cell near the larger end. The simulation included four cases: two focused on vertical orientation with the yolk at the rear shell and the geometric center, and two on horizontal orientation with similar yolk positions. Repositioning the yolk in a horizontal orientation near the eggshell resulted in significant temperature variations. The findings show that a horizontal egg position, especially with the yolk near the eggshell, led to a significant 8%–16% reduction in heating times. This configuration also improved pasteurization efficiency, assessed by the F value, by about 13.8%. The study also revealed distinct flow patterns influenced by buoyancy forces, significantly related to temperature distribution inside the egg. [ABSTRACT FROM AUTHOR]

Laboratory scale conventional single‐use bioreactor was used to investigate the effect of different stirrer speeds on the Arthrospira platensis (Spirulina platensis) culture. Experiments were handled in two steps. First step was the selection of the stirring speeds, which was simulated via using CFD, and the second was the long term cultivation with the selected speed. During 10 days of batches as the first step, under identical culture conditions, stirrer speed of 230 rpm gave higher results, compared to 130 and 70 rpm, with respect to dry biomass weight, absorbance value (AB) and chlorophyll‐a concentration. Volumetric productivity during the growth phase of the cultures were calculated as 0.39 ± 0.03, 0.28 ± 0.01, and 0.19 ± 0.02 g L−1 d−1, from the fast to the slower speeds. According to the results a 17 day batch was handled with 230 rpm in order to monitor the effects on the culture. The culture reached a volumetric productivity of 0.33 ± 0.04 g L−1 d−1. Statistical analysis showed the significance of the parameters related with the stirring speed. [ABSTRACT FROM AUTHOR]

Sand dunes are the primary factor influencing wind‐sand disasters. To explore the evolution law of wind‐blown sand dunes surrounding high vertical‐type sand fences along desert railways, numerical simulation analyses based on computational fluid dynamics coupled with a discreet element method of the wind‐sand flow field and sand particles trajectories around sand fences were conducted. The focus of this study was the Yandun section of the Lanzhou‐Xinjiang Railway in Xinjiang, China (42.38°N, 93.95°E). By combining ERA5 wind data with field measurements and monitoring, a three‐dimensional coupling model was established. According to the results of L9 (33) orthogonal tests, the sensitivity of the three factors to the evolution of sand dunes can be ordered as wind speed > porosity > height, indicating that wind speed is closely related to sand dune evolution (p < 0.05). The results of single‐factor tests indicate that the structure of wind‐sand flow fields, sand accumulation patterns, and sand particle movement trajectories vary significantly under different wind speeds. The sand accumulation rates on the windward slope of the sand dune are 29.67%, 25.91%, and 20.04%, while on the leeward slope, these rates are 40.33%, 34.09%, and 29.96%, respectively. The obtained information on the evolution law of sand dunes surrounding high vertical‐type sand fences provides a scientific basis for wind‐sand prevention measures along railways in desert regions. [ABSTRACT FROM AUTHOR]