Fluids

17 pages, 5030 KB

Open AccessEditor’s ChoiceArticle

Mitigating Airborne Infection Transmission in the Common Area of Inpatient Wards—A Case Study

by Xiangdong Li, Kevin Kevin, Wai Kit Lam, Andrew Ooi, Cameron Zachreson, Nicholas Geard, Loukas Tsigaras, Samantha Bates, Forbes McGain, Lidia Morawska, Marion Kainer and Jason Monty

Fluids 2025, 10(10), 267; https://doi.org/10.3390/fluids10100267 - 14 Oct 2025

Viewed by 1438

Abstract

In a hospital ward, transmission of airborne pathogens can occur in any area where people breathe the same air. These areas include patient rooms and specialised treatment rooms, as well as corridors and common areas. Numerous studies have been conducted to investigate the [...] Read more.

In a hospital ward, transmission of airborne pathogens can occur in any area where people breathe the same air. These areas include patient rooms and specialised treatment rooms, as well as corridors and common areas. Numerous studies have been conducted to investigate the risk of airborne transmission within hospital rooms where patient care activities take place; however, studies assessing the risk of exposure to airborne pathogens in common areas such as nurse stations and corridors, in which healthcare workers spend up to 63% of their time, are very rare. In this study, we addressed this gap by simulating aerosol transport in the common area of a real inpatient ward encompassing different types of patient rooms and equipped with a mixing ventilation system. The risk of airborne transmission of COVID-19 in the ward was evaluated using a spatially resolved risk model, coupled with the clinical and pathological data on SARS-CoV-2 infection. The results showed that the central-return ventilation system causes directional air flows in the corridors, which enhanced long-distance aerosol transport and were conducive to infection transmission between different rooms. An improved ventilation system was proposed that aimed to reduce air mixing and minimise directional air flows. The improvement involved only rearrangement of air supply and exhaust vents, but led to significant reductions in both particle residence time and travelling distance within the ward, contributing to a nearly two-fold increase and 60% decrease in the areas of low-risk and high-risk zones, respectively, resulting in a 34% reduction in the overall infection probability in the studied area. This study demonstrated the potential of preventing hospital-acquired infection (HAI) via engineering controls and provided recommendations for future studies to assess novel ventilation configurations to reduce transmission risk. Full article

(This article belongs to the Special Issue CFD Applications in Environmental Engineering)

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29 pages, 4433 KB

Open AccessEditor’s ChoiceArticle

Influence of Boundary Conditions and Heating Modes on the Onset of Columnar Convection in Rotating Spherical Shells

by William Seeley, Francesca Coke, Radostin D. Simitev and Robert J. Teed

Fluids 2025, 10(9), 237; https://doi.org/10.3390/fluids10090237 - 5 Sep 2025

Viewed by 976

Abstract

We investigate the linear onset of thermal convection in rotating spherical shells with a focus on the influence of mechanical boundary conditions and thermal driving modes. Using a spectral method, we determine critical Rayleigh numbers, azimuthal wavenumbers, and oscillation frequencies over a wide [...] Read more.

We investigate the linear onset of thermal convection in rotating spherical shells with a focus on the influence of mechanical boundary conditions and thermal driving modes. Using a spectral method, we determine critical Rayleigh numbers, azimuthal wavenumbers, and oscillation frequencies over a wide range of Prandtl numbers and shell aspect ratios at moderate Ekman numbers. We show that the preferred boundary condition for convective onset depends systematically on both aspect ratio and Prandtl number: for sufficiently thick shells or for large Pr, the Ekman boundary layer at the outer boundary becomes destabilising, so that no-slip boundaries yield a lower

{Ra}_{c}

than stress-free boundaries. Comparing differential and internal heating, we find that internal heating generally raises

{Ra}_{c}

, shifts the onset to larger wavenumbers and frequencies, and relocates the critical column away from the tangent cylinder. Mixed boundary conditions with no-slip on the inner boundary behave similarly to purely stress-free boundaries, confirming the dominant influence of the outer surface. These results demonstrate that boundary conditions and heating mechanisms play a central role in controlling the onset of convection and should be carefully considered in models of planetary and stellar interiors. Full article

(This article belongs to the Collection Challenges and Advances in Heat and Mass Transfer)

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15 pages, 3838 KB

Open AccessEditor’s ChoiceArticle

Cavitation–Velocity Correlation in Cavitating Flows Around a Clark-Y Hydrofoil Using a Data-Driven U-Net

by Yadong Han, Bingfu Han, Ming Liu and Lei Tan

Fluids 2025, 10(8), 213; https://doi.org/10.3390/fluids10080213 - 13 Aug 2025

Viewed by 853

Abstract

Cavitating flows are of great interest in the fields of hydraulic machineries, which can significantly affect mechanical performance and safety. Despite various efforts being dedicated to figuring out the interaction between flow and cavitation fields, their correlation has not been clearly addressed. To [...] Read more.

Cavitating flows are of great interest in the fields of hydraulic machineries, which can significantly affect mechanical performance and safety. Despite various efforts being dedicated to figuring out the interaction between flow and cavitation fields, their correlation has not been clearly addressed. To this end, in this study, a convolutional neural network, U-Net, was adopted to build a model that can predict the vapor volume fraction from velocity fields. Large eddy simulations of cavitating flows around a Clark-Y hydrofoil were conducted, and the simulated snapshots with velocity and vapor volume fraction were adopted as a dataset for training the network. The predicted vapor volume fraction shows good agreement with the referred simulation results, with a L₁ deviation lower than 2 × 10⁻⁴, considering all the snapshots. The comparable L₁ deviation between the training and validation datasets suggests the existence of a strong correlation between velocity and cavitation fields. The cavitation–velocity interaction derived from using U-Net suggests that the location with zero velocity indicates the interior part of attached and cloud cavitations, and the local vortical velocity fields usually suggest the existence of cavitation shedding. Full article

(This article belongs to the Special Issue Multiphase Flow and Fluid Machinery)

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28 pages, 10432 KB

Open AccessEditor’s ChoiceReview

Rapid CFD Prediction Based on Machine Learning Surrogate Model in Built Environment: A Review

by Rui Mao, Yuer Lan, Linfeng Liang, Tao Yu, Minhao Mu, Wenjun Leng and Zhengwei Long

Fluids 2025, 10(8), 193; https://doi.org/10.3390/fluids10080193 - 28 Jul 2025

Cited by 13 | Viewed by 11728

Abstract

Computational Fluid Dynamics (CFD) is regarded as an important tool for analyzing the flow field, thermal environment, and air quality around the built environment. However, for built environment applications, the high computational cost of CFD hinders large-scale scenario simulation and efficient design optimization. [...] Read more.

Computational Fluid Dynamics (CFD) is regarded as an important tool for analyzing the flow field, thermal environment, and air quality around the built environment. However, for built environment applications, the high computational cost of CFD hinders large-scale scenario simulation and efficient design optimization. In the field of built environment research, surrogate modeling has become a key technology to connect the needs of high-fidelity CFD simulation and rapid prediction, whereas the low-dimensional nature of traditional surrogate models is unable to match the physical complexity and prediction needs of built flow fields. Therefore, combining machine learning (ML) with CFD to predict flow fields in built environments offers a promising way to increase simulation speed while maintaining reasonable accuracy. This review briefly reviews traditional surrogate models and focuses on ML-based surrogate models, especially the specific application of neural network architectures in rapidly predicting flow fields in the built environment. The review indicates that ML accelerates the three core aspects of CFD, namely mesh preprocessing, numerical solving, and post-processing visualization, in order to achieve efficient coupled CFD simulation. Although ML surrogate models still face challenges such as data availability, multi-physics field coupling, and generalization capability, the emergence of physical information-driven data enhancement techniques effectively alleviates the above problems. Meanwhile, the integration of traditional methods with ML can further enhance the comprehensive performance of surrogate models. Notably, the online ministry of trained ML models using transfer learning strategies deserves further research. These advances will provide an important basis for advancing efficient and accurate operational solutions in sustainable building design and operation. Full article

(This article belongs to the Special Issue Feature Reviews for Fluids 2025–2026)

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23 pages, 12509 KB

Open AccessEditor’s ChoiceArticle

Tuned Generalised k-ω (GEKO) Turbulence Model Parameters for Predicting Transitional Flow Through Stenosis Geometries of Various Degrees

by Jake Emmerling, Sara Vahaji, David A. V. Morton, Svetlana Stevanovic, David F. Fletcher and Kiao Inthavong

Fluids 2025, 10(7), 168; https://doi.org/10.3390/fluids10070168 - 28 Jun 2025

Viewed by 1969

Abstract

Stenosis geometries are constrictions of a biological tube that can be found in many forms in the human body. Capturing the flow field in such geometries is important. For this purpose, simulations were performed using the generalised k-

ω

(GEKO) turbulence model [...] Read more.

Stenosis geometries are constrictions of a biological tube that can be found in many forms in the human body. Capturing the flow field in such geometries is important. For this purpose, simulations were performed using the generalised k-

ω

(GEKO) turbulence model to study flow through stenosis geometries with throat constrictions of 75, 50 and 25% area reduction. Laminar flow conditions of Re = 2000 and 1000 were applied and the results were compared with experimental data. The effect of four GEKO parameters (

C_{S E P}

,

C_{N W}

,

C_{J E T}

and

C_{M I X}

) on flow in the post-stenotic region was investigated by simulating a wide range of parameter values. Results showed that the

C_{M I X}

parameter, combined with a modified GEKO blending function, had the greatest effect on axial velocity, velocity fluctuations and the location of the jet breakdown region. A

C_{M I X}

value of 0.4 closely matched the experimental results for a 75% area reduction stenosis at

R e = 2000

and showed significant improvements over existing Reynolds-averaged Navier–Stokes models. The GEKO model was also able to closely match the axial velocity results predicted by previously published large-eddy simulation models under the same flow conditions. Furthermore, the GEKO model was applied to a realistic oral-to-tracheal airway model for a Reynolds number of 2000 and produced results consistent with the idealised stenotic tube. Full article

(This article belongs to the Section Mathematical and Computational Fluid Mechanics)

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19 pages, 3128 KB

Open AccessEditor’s ChoiceArticle

Slow Translation and Rotation of a Composite Sphere Parallel to One or Two Planar Walls

by Yu F. Chou and Huan J. Keh

Fluids 2025, 10(6), 154; https://doi.org/10.3390/fluids10060154 - 12 Jun 2025

Cited by 2 | Viewed by 1291

Abstract

A semi-analytical investigation is conducted to examine the coupled translational and rotational motions of a composite spherical particle (consisting of an impermeable hard core surrounded by a permeable porous shell) immersed in a viscous fluid parallel to one or two planar boundaries under [...] Read more.

A semi-analytical investigation is conducted to examine the coupled translational and rotational motions of a composite spherical particle (consisting of an impermeable hard core surrounded by a permeable porous shell) immersed in a viscous fluid parallel to one or two planar boundaries under the steady condition of a low Reynolds number. The fluid flow is described using the Stokes equations outside the porous shell and the Brinkman equation within it. A general solution is formulated by employing fundamental solutions in both spherical and Cartesian coordinate systems. The boundary conditions on the planar walls are implemented using the Fourier transform method, while those on the inner and outer boundaries of the porous shell are applied via a collocation technique. Numerical calculations yield hydrodynamic force and torque results with good convergence across a broad range of physical parameters. For validation, the results corresponding to an impermeable hard sphere parallel to one or two planar walls are shown to be in close agreement with established solutions from the literature. The hydrodynamic drag force and torque experienced by the composite particle increase steadily with larger values of the ratio of the particle radius to the porous shell’s permeation length, the ratio of the core radius to the total particle radius, and the separations between the particle and the walls. It has been observed that the influence of the walls on translational motion is significantly stronger than that on rotational motion. When comparing motions parallel versus normal to the walls, the planar boundaries impose weaker hydrodynamic forces but stronger torques during parallel motions. The coupling between the translation and rotation of the composite sphere parallel to the walls exhibits complex behavior that does not vary monotonically with changes in system parameters. Full article

(This article belongs to the Section Flow of Multi-Phase Fluids and Granular Materials)

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19 pages, 3372 KB

Open AccessEditor’s ChoiceReview

A Comprehensive Review of Biomass Gasification Characteristics in Fluidized Bed Reactors: Progress, Challenges, and Future Directions

by Lu Wang, Tuo Zhou, Bo Hou, Hairui Yang, Nan Hu and Man Zhang

Fluids 2025, 10(6), 147; https://doi.org/10.3390/fluids10060147 - 1 Jun 2025

Cited by 16 | Viewed by 9102

Abstract

Biomass fluidized bed gasification technology has attracted significant attention due to its high efficiency and clean energy conversion capabilities. However, its industrial application has been limited by insufficient technological maturity. This paper systematically reviews the research progress on biomass fluidized bed gasification characteristics; [...] Read more.

Biomass fluidized bed gasification technology has attracted significant attention due to its high efficiency and clean energy conversion capabilities. However, its industrial application has been limited by insufficient technological maturity. This paper systematically reviews the research progress on biomass fluidized bed gasification characteristics; compares the applicability of bubbling fluidized beds (BFBs), circulating fluidized beds (CFBs), and dual fluidized beds (DFBs); and highlights the comprehensive advantages of CFBs in large-scale production and tar control. The gas–solid flow characteristics within CFB reactors are highly complex, with factors such as fluidization velocity, gas–solid mixing homogeneity, gas residence time, and particle size distribution directly affecting syngas composition. However, experimental studies have predominantly focused on small-scale setups, failing to characterize the impact of flow dynamics on gasification reactions. Therefore, numerical simulation has become essential for in-depth exploration. Additionally, this study analyzes the influence of different gasification agents (air, oxygen-enriched, oxygen–steam, etc.) on syngas quality. The results demonstrate that oxygen–steam gasification eliminates nitrogen dilution, optimizes reaction kinetics, and significantly enhances syngas quality and hydrogen yield, providing favorable conditions for downstream processes such as green methanol synthesis. Based on the current research landscape, this paper employs numerical simulation to investigate oxygen–steam CFB gasification at a pilot scale (500 kg/h biomass throughput). The results reveal that under conditions of O₂/H₂O = 0.25 and 800 °C, the syngas H₂ volume fraction reaches 43.7%, with a carbon conversion rate exceeding 90%. These findings provide theoretical support for the industrial application of oxygen–steam CFB gasification technology. Full article

(This article belongs to the Special Issue Feature Reviews for Fluids 2025–2026)

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22 pages, 2043 KB

Open AccessEditor’s ChoiceArticle

Spectral Analysis of Confined Cylinder Wakes

by Wilson Lu, Leon Chan and Andrew Ooi

Fluids 2025, 10(4), 84; https://doi.org/10.3390/fluids10040084 - 25 Mar 2025

Cited by 5 | Viewed by 1574

Abstract

Bluff body flows, while commonly assumed to be isolated, are often subject to confinement effects due to interactions with nearby objects. In this study, a simple approximation of such a flow configuration is considered, where a cylinder is placed symmetrically within an infinite [...] Read more.

Bluff body flows, while commonly assumed to be isolated, are often subject to confinement effects due to interactions with nearby objects. In this study, a simple approximation of such a flow configuration is considered, where a cylinder is placed symmetrically within an infinite channel. The presence of walls implies the wake is physically confined and introduces interactions between the wake and the boundary layer along the wall. To isolate the effect of confinement, simulations are conducted with slip channel walls, removing the boundary layers. Comparisons of flow statistics between simulations of slip and no-slip channel walls show minor differences at a low blockage ratio,

β

(defined as the ratio of cylinder diameter to channel height), while for larger blockage ratios, the differences are significant. Spectral analysis is also performed on the wake and shear layers. At the lowest blockage,

β = 0.3

, little modification is made to the wake, and we find that Kármán vortices are one-way coupled to the boundary layers along the walls. For

β = 0.5

, wall–wake interactions are determined to significantly contribute to wake dynamics, thus to two-way coupling Kármán vortices and the wall boundary layers. Finally, for

β = 0.7

, the absence of Kármán shedding couples Kelvin–Helmoltz vortices in the shear layer, separating off the cylinder to the wall boundary layer. Full article

(This article belongs to the Special Issue Aerodynamics and Aeroacoustics of Vehicles, 4th Edition)

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24 pages, 3605 KB

Open AccessEditor’s ChoiceReview

Solution Combustion Synthesis for Various Applications: A Review of the Mixed-Fuel Approach

by Samantha Padayatchee, Halliru Ibrahim, Holger B. Friedrich, Ezra J. Olivier and Pinkie Ntola

Fluids 2025, 10(4), 82; https://doi.org/10.3390/fluids10040082 - 25 Mar 2025

Cited by 11 | Viewed by 4250

Abstract

As solution combustion synthesis (SCS) becomes a universal route to metal oxide nanomaterials, it also paves the way for mixed-fuel combustion synthesis as an advanced approach to the synthesis of materials of desirable properties for diverse applications. Major significance is attached to the [...] Read more.

As solution combustion synthesis (SCS) becomes a universal route to metal oxide nanomaterials, it also paves the way for mixed-fuel combustion synthesis as an advanced approach to the synthesis of materials of desirable properties for diverse applications. Major significance is attached to the rates of decomposition and combustion temperatures of the fuel as determinant factors of the morphology and physicochemical properties of the materials obtained. This has promoted the use of mixed-fuel systems characterized by lower decomposition temperatures of organic fuels and higher rates of combustion. The review work presented herein provides a comprehensive analysis of the applications of mixed-fuel SCS in ceramics, fuel cells, nanocomposite materials, and the recycling of lithium battery materials while taking into consideration the effects of the mixed-fuel system on the physicochemical and morphological properties of those materials, as compared to their analogues prepared via single-fuel SCS. Full article

(This article belongs to the Special Issue Turbulence and Combustion)

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17 pages, 5109 KB

Open AccessEditor’s ChoiceArticle

Numerical Mixing Index: Definition and Application on Concrete Mixer

by Cristian Ferrari, Nicolò Beccati and Luca Magri

Fluids 2025, 10(3), 72; https://doi.org/10.3390/fluids10030072 - 20 Mar 2025

Cited by 3 | Viewed by 2787

Abstract

In this work, a statistical method is applied to a multiphase CFD simulation of concrete mixing performed in a truck mixer. The numerical model is based on an Eulerian–Eulerian approach in a transient regime. The aggregate materials are simulated as dispersed solid particles [...] Read more.

In this work, a statistical method is applied to a multiphase CFD simulation of concrete mixing performed in a truck mixer. The numerical model is based on an Eulerian–Eulerian approach in a transient regime. The aggregate materials are simulated as dispersed solid particles of various diameters, while the cement paste is simulated as a non-Newtonian continuous fluid. The first ten drum revolutions are analyzed from the condition of the completely segregated materials. The cell mixing index, defined by a statistical method in terms of mean, variance, and density probability function, is applied to the analysis of the simulation results. The statistical variables are implemented using the fluid dynamics code in the post-processing result analyses. The method predicts the distribution efficiency of the materials within a truck mixer as a function of its internal geometry, rotation speed, and mixture composition. As the number of revolutions increases, the distribution qualitatively improves, as shown by the motion fields, velocities, and vortices of the various materials, quantified through the calculation of the mixing index. The illustrated method can be used to predictively calculate the distribution effectiveness of new truck mixer designs before prototyping them and can be applied to other types of mixers. Furthermore, this study can be applied to liquid–solid mixing processes analyzed via the Eulerian multiphase numerical approach. Full article

(This article belongs to the Special Issue Industrial CFD and Fluid Modelling in Engineering, 2nd Edition)

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17 pages, 13494 KB

Open AccessEditor’s ChoiceArticle

Linear Stability Analysis on Flow-Induced Vibration of an Elastically Mounted Rotating Cylinder

by Jianfeng Lu, Zhiyu Zhang and Xing Zhang

Fluids 2025, 10(3), 56; https://doi.org/10.3390/fluids10030056 - 21 Feb 2025

Cited by 1 | Viewed by 1098

Abstract

In this paper, we present a linear stability analysis on flow-induced vibration of an elastically mounted cylinder subjected to forced rotation. Four series of cases, with different combinations of degrees of freedoms in oscillation and Reynolds number are investigated. For each series of [...] Read more.

In this paper, we present a linear stability analysis on flow-induced vibration of an elastically mounted cylinder subjected to forced rotation. Four series of cases, with different combinations of degrees of freedoms in oscillation and Reynolds number are investigated. For each series of cases, a wide range of reduced velocity at various rotation rates are considered. The variations of growth and frequency with reduced velocity for the leading modes are presented. Some phenomena observed in previous numerical studies are interpreted by using the results of linear stability analysis. The supressing of vortex shedding at moderate rotation rate is explained by the absence of unstable fluid mode. The amplitude enhancement in high range of rotaton rate is explained by the emergence of unstable elastic mode. The stability properties of the leading modes provide some new insight into the influences of forced rotation on flow-induced vibration. The results of the current study have important implications in the design of offshore structures and energy-havesting devices. Full article

(This article belongs to the Section Mathematical and Computational Fluid Mechanics)

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24 pages, 5992 KB

Open AccessEditor’s ChoiceReview

The Impact of Polydimethylsiloxane (PDMS) in Engineering: Recent Advances and Applications

by Rui A. Lima

Fluids 2025, 10(2), 41; https://doi.org/10.3390/fluids10020041 - 9 Feb 2025

Cited by 32 | Viewed by 10131

Abstract

Since the introduction of polydimethylsiloxane (PDMS) microfluidic devices at the beginning of the 21st century, this elastomeric polymer has gained significant attention in the engineering community due to its biocompatibility, exceptional mechanical and optical properties, thermal stability, and versatility. PDMS has been widely [...] Read more.

Since the introduction of polydimethylsiloxane (PDMS) microfluidic devices at the beginning of the 21st century, this elastomeric polymer has gained significant attention in the engineering community due to its biocompatibility, exceptional mechanical and optical properties, thermal stability, and versatility. PDMS has been widely used for in vitro experiments ranging from the macro- to nanoscale, enabling advances in blood flow studies, biomodels improvement, and numerical validations. PDMS devices, including microfluidic systems, have been employed to investigate different kinds of fluids and flow phenomena such as in vitro blood flow, blood analogues, the deformation of individual cells and the cell free layer (CFL). The most recent applications of PDMS involve complex hemodynamic studies such as flow in aneurysms and in organ-on-a-chip (OoC) platforms. Furthermore, the distinctive properties of PDMS, including optical transparency, thermal stability, and versality have inspired innovative applications beyond biomedical applications, such as the development of transparent, virus-protective face masks, including those for SARS-CoV-2 and serpentine heat exchangers to enhance heat transfer and energy efficiency in different kinds of thermal systems. This review provides a comprehensive overview of the current research performed with PDMS and outlines some future directions, in particular applications of PDMS in engineering, including biomicrofluidics, in vitro biomodels, heat transfer, and face masks. Additionally, challenges related to PDMS hydrophobicity, molecule absorption, and long-term stability are discussed alongside the solutions proposed in the most recent research studies. Full article

(This article belongs to the Special Issue Physics and Applications of Microfluidics)

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Graphical abstract

74 pages, 7040 KB

Open AccessEditor’s ChoiceArticle

The Lattice Boltzmann Method with Deformable Boundary for Colonic Flow Due to Segmental Circular Contractions

by Irina Ginzburg

Fluids 2025, 10(2), 22; https://doi.org/10.3390/fluids10020022 - 21 Jan 2025

Cited by 3 | Viewed by 1881

Abstract

We extend the 3D Lattice Boltzmann method with a deformable boundary (LBM-DB) for the computations of the full-volume colonic flow of the Newtonian fluid driven by the peristaltic segmented circular contractions which obey the three-step “intestinal law”: (i) deflation, (ii) inflation, and (iii) [...] Read more.

We extend the 3D Lattice Boltzmann method with a deformable boundary (LBM-DB) for the computations of the full-volume colonic flow of the Newtonian fluid driven by the peristaltic segmented circular contractions which obey the three-step “intestinal law”: (i) deflation, (ii) inflation, and (iii) elastic relaxation. The key point is that the LBM-DB accurately prescribes a curved deforming surface on the regular computational grid through precise and compact Dirichlet velocity schemes, without the need to recover for an adaptive boundary mesh or surface remesh, and without constraint of fluid volume conservation. The population “refill” of “fresh” fluid nodes, including sharp corners, is reformulated with the improved reconstruction algorithms by combining bulk and advanced boundary LBM steps with a local sub-iterative collision update. The efficient parallel LBM-DB simulations in silico then extend the physical experiments performed in vitro on the Dynamic Colon Model (DCM, 2020) to highly occlusive contractile waves. The motility scenarios are modeled both in a cylindrical tube and in a new geometry of “parabolic” transverse shape, which mimics the dynamics of realistic triangular lumen aperture. We examine the role of cross-sectional shape, motility pattern, occlusion scenario, peristaltic wave speed, elasticity effect, kinematic viscosity, inlet/outlet conditions and numerical compressibility on the temporal localization of pressure and velocity oscillations, and especially the ratio of retrograde vs antegrade velocity amplitudes, in relation to the major contractile events. The developed numerical approach could contribute to a better understanding of the intestinal physiology and pathology due to a possibility of its straightforward extension to the non-Newtonian chyme rheology and anatomical geometry. Full article

(This article belongs to the Special Issue Lattice Boltzmann Methods: Fundamentals and Applications)

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24 pages, 6157 KB

Open AccessEditor’s ChoiceArticle

Machine Learning Model for Gas–Liquid Interface Reconstruction in CFD Numerical Simulations

by Tamon Nakano, Michele Alessandro Bucci, Jean-Marc Gratien and Thibault Faney

Fluids 2025, 10(1), 20; https://doi.org/10.3390/fluids10010020 - 20 Jan 2025

Cited by 5 | Viewed by 2154

Abstract

The volume of fluid (VoF) method is widely used in multiphase flow simulations to track and locate the interface between two immiscible fluids. The relative volume fraction in each cell is used to recover the interface properties (i.e., normal, location, and curvature). Accurate [...] Read more.

The volume of fluid (VoF) method is widely used in multiphase flow simulations to track and locate the interface between two immiscible fluids. The relative volume fraction in each cell is used to recover the interface properties (i.e., normal, location, and curvature). Accurate computation of the local interface curvature is essential for evaluation of the surface tension force at the interface. However, this interface reconstruction step is a major bottleneck of the VoF method due to its high computational cost and low accuracy on unstructured grids. Recent attempts to apply data-driven approaches to this problem have outperformed conventional methods in many test cases. However, these machine learning-based methods are restricted to computations on structured grids. In this work, we propose a machine learning-enhanced VoF method based on graph neural networks (GNNs) to accelerate interface reconstruction on general unstructured meshes. We first develop a methodology for generating a synthetic dataset based on paraboloid surfaces discretized on unstructured meshes to obtain a dataset akin to the configurations encountered in industrial settings. We then train an optimized GNN architecture on this dataset. Our approach is validated using analytical solutions and comparisons with conventional methods in the OpenFOAM framework on a canonical test. We present promising results for the efficiency of GNN-based approaches for interface reconstruction in multiphase flow simulations in the industrial context. Full article

(This article belongs to the Special Issue Advances in Multiphase Flow Simulation with Machine Learning)

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36 pages, 1641 KB

Open AccessEditor’s ChoiceReview

The Reynolds Number: A Journey from Its Origin to Modern Applications

by Manuel Saldana, Sandra Gallegos, Edelmira Gálvez, Jonathan Castillo, Eleazar Salinas-Rodríguez, Eduardo Cerecedo-Sáenz, Juan Hernández-Ávila, Alessandro Navarra and Norman Toro

Fluids 2024, 9(12), 299; https://doi.org/10.3390/fluids9120299 - 16 Dec 2024

Cited by 22 | Viewed by 24466

Abstract

The Reynolds number (Re), introduced in the late 19th century, has become a fundamental parameter in a lot of scientific fields—the main one being fluid mechanics—as it allows for the determination of flow characteristics by distinguishing between laminar and turbulent regimes, or some [...] Read more.

The Reynolds number (Re), introduced in the late 19th century, has become a fundamental parameter in a lot of scientific fields—the main one being fluid mechanics—as it allows for the determination of flow characteristics by distinguishing between laminar and turbulent regimes, or some intermediate stage. Reynolds’ 1895 paper, which decomposed velocity into average and fluctuating components, laid the foundation for modern turbulence modeling. Since then, the concept has been applied to various fields, including external flows—the science that studies friction—as well as wear, lubrication, and heat transfer. Literature research in recent times has explored new interpretations of Re, and despite its apparent simplicity, the precise prediction of Reynolds numbers remains a computational challenge, especially under conditions such as the study of multiphase flows, non-Newtonian fluids, highly turbulent flow conditions, flows on very small scales or nanofluids, flows with complex geometries, transient or non-stationary flows, and flows of fluids with variable properties. Reynolds’ work, which encompasses both scientific and engineering contributions, continues to influence research and applications in fluid dynamics. Full article

(This article belongs to the Special Issue Recent Advances in Fluid Mechanics: Feature Papers, 2024)

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35 pages, 2694 KB

Open AccessEditor’s ChoiceReview

Synthetic Jet Actuators for Active Flow Control: A Review

by Howard H. Ho, Ali Shirinzad, Ebenezer E. Essel and Pierre E. Sullivan

Fluids 2024, 9(12), 290; https://doi.org/10.3390/fluids9120290 - 6 Dec 2024

Cited by 8 | Viewed by 7334

Abstract

A synthetic jet actuator (SJA) is a fluidic device often consisting of a vibrating diaphragm that alters the volume of a cavity to produce a synthesized jet through an orifice. The cyclic ingestion and expulsion of the working fluid leads to a zero-net [...] Read more.

A synthetic jet actuator (SJA) is a fluidic device often consisting of a vibrating diaphragm that alters the volume of a cavity to produce a synthesized jet through an orifice. The cyclic ingestion and expulsion of the working fluid leads to a zero-net mass-flux and the transfer of linear momentum to the working fluid over an actuation cycle, leaving a train of vortex structures propagating away from the orifice. SJAs are a promising technology for flow control applications due to their unique features, such as no external fluid supply or ducting requirements, short response time, low weight, and compactness. Hence, they have been the focus of many research studies over the past few decades. Despite these advantages, implementing an effective control scheme using SJAs is quite challenging due to the large parameter space involving several geometrical and operational variables. This article aims to explain the working mechanism of SJAs and provide a comprehensive review of the effects of SJA design parameters in quiescent conditions and cross-flow. Full article

(This article belongs to the Special Issue Flow Control Techniques: Advances in Flow System Analysis, Modeling and Applications)

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27 pages, 2703 KB

Open AccessEditor’s ChoiceReview

Indoor Air Quality Control for Airborne Diseases: A Review on Portable UV Air Purifiers

by Shriram Sankurantripati and Florent Duchaine

Fluids 2024, 9(12), 281; https://doi.org/10.3390/fluids9120281 - 26 Nov 2024

Cited by 8 | Viewed by 9484

Abstract

The spread of airborne diseases such as COVID-19 underscores the need for effective indoor air quality control. This review focuses on ventilation strategies and portable air purifiers as key mitigation solutions. Ventilation systems, including natural and mechanical approaches, can reduce pathogen concentrations by [...] Read more.

The spread of airborne diseases such as COVID-19 underscores the need for effective indoor air quality control. This review focuses on ventilation strategies and portable air purifiers as key mitigation solutions. Ventilation systems, including natural and mechanical approaches, can reduce pathogen concentrations by improving airflow. However, combining ventilation with portable air purifiers, particularly those using HEPA filters, ESP filters, and UV-C radiation, can enhance Indoor air quality. While HEPA and ESP filters focus on trapping airborne particles, UV-C radiation can inactivate pathogens by disrupting their RNA. A review of UV air purifiers reveals a lack of studies on their efficacy and effectiveness in real-world settings. A thorough investigation into the performance of this mitigation solution is necessary, focusing on varying key factors, such as purifier placement, airflow dynamics, and UV dosage, to ensure optimal effectiveness. High-fidelity computational methods are essential in accurately assessing these factors, as informed by the physics of airborne transmission. Such advanced computations are necessary to determine the viability of portable UV air purifiers in mitigating airborne transmission in enclosed environments such as hospitals and public spaces. Integrating advanced air purification technologies with proper ventilation can improve safety in indoor environments and prevent future disease-related outbreaks. Full article

(This article belongs to the Special Issue Recent Advances in Fluid Mechanics: Feature Papers, 2024)

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22 pages, 11690 KB

Open AccessEditor’s ChoiceReview

The Potential of Machine Learning Methods for Separated Turbulent Flow Simulations: Classical Versus Dynamic Methods

by Stefan Heinz

Fluids 2024, 9(12), 278; https://doi.org/10.3390/fluids9120278 - 25 Nov 2024

Cited by 12 | Viewed by 2653

Abstract

Feasible and reliable predictions of separated turbulent flows are a requirement to successfully address the majority of aerospace and wind energy problems. Existing computational approaches such as large eddy simulation (LES) or Reynolds-averaged Navier–Stokes (RANS) methods have suffered for decades from well-known computational [...] Read more.

Feasible and reliable predictions of separated turbulent flows are a requirement to successfully address the majority of aerospace and wind energy problems. Existing computational approaches such as large eddy simulation (LES) or Reynolds-averaged Navier–Stokes (RANS) methods have suffered for decades from well-known computational cost and reliability issues in this regard. One very popular approach to dealing with these questions is the use of machine learning (ML) methods to enable improved RANS predictions. An alternative is the use of minimal error simulation methods (continuous eddy simulation (CES), which may be seen as a dynamic ML method) in the framework of partially or fully resolving simulation methods. Characteristic features of the two approaches are presented here by considering a variety of complex separated flow simulations. The conclusion is that minimal error CES methods perform clearly better than ML-RANS methods. Most importantly and in contrast to ML-RANS methods, CES is demonstrated to be well applicable to cases not involved in the model development. The reason for such superior CES performance is identified here: it is the ability of CES to properly account for causal relationships induced by the structure of separated turbulent flows. Full article

(This article belongs to the Special Issue Machine Learning and Artificial Intelligence in Fluid Mechanics)

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19 pages, 7421 KB

Open AccessEditor’s ChoiceArticle

Multi-Objective Numerical Analysis of Horizontal Rectilinear Earth–Air Heat Exchangers with Elliptical Cross Section Using Constructal Design and TOPSIS

by Ivanilton Reinato de Andrade, Elizaldo Domingues dos Santos, Houlei Zhang, Luiz Alberto Oliveira Rocha, Andre Luis Razera and Liércio André Isoldi

Fluids 2024, 9(11), 257; https://doi.org/10.3390/fluids9110257 - 31 Oct 2024

Cited by 9 | Viewed by 1740

Abstract

This study presents a numerical evaluation of a Horizontal Rectilinear Earth–air Heat Exchanger (EAHE), considering the climatic and soil conditions of Viamão, Brazil, a subtropical region. The Constructal Design method, combined with the Exhaustive Search, was utilized to define the system constraints, degree [...] Read more.

This study presents a numerical evaluation of a Horizontal Rectilinear Earth–air Heat Exchanger (EAHE), considering the climatic and soil conditions of Viamão, Brazil, a subtropical region. The Constructal Design method, combined with the Exhaustive Search, was utilized to define the system constraints, degree of freedom, and performance indicators. The degree of freedom was characterized by the aspect ratio between the vertical and horizontal lengths of the elliptical cross-section duct (H/L). The performance indicators for the EAHE configurations were assessed based on thermal potential (TP) and pressure drop (PD). The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied for multi-objective evaluation, and a methodology for EAHE is proposed. The problem was solved using FLUENT software (version 2024 R2), which employs the Finite Volume Method to solve the conservation equations for mass, momentum, and energy. The (H/L)_T_,o = 6.0 configuration showed a 16.4% increase in thermal performance for heating and 15.9% for cooling compared to the conventional circular duct. Conversely, the (H/L)_F_,o = 1.0 configuration reduced pressure loss by 65.33%. The integration of Constructal Design with TOPSIS facilitated the identification of optimized geometries that achieve a balance between performance indicators and those that specifically prioritize thermal or fluid dynamic aspects, being this approach an original scientific contribution of the present work. Full article

(This article belongs to the Collection Challenges and Advances in Heat and Mass Transfer)

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36 pages, 37451 KB

Open AccessEditor’s ChoiceReview

Non-Spherical Cavitation Bubbles: A Review

by Boxin Jia and Hitoshi Soyama

Fluids 2024, 9(11), 249; https://doi.org/10.3390/fluids9110249 - 25 Oct 2024

Cited by 9 | Viewed by 4122

Abstract

Cavitation is a phase-change phenomenon from the liquid to the gas phase due to an increased flow velocity. As it causes severe erosion and noise, it is harmful to hydraulic machinery such as pumps, valves, and screw propellers. However, it can be utilized [...] Read more.

Cavitation is a phase-change phenomenon from the liquid to the gas phase due to an increased flow velocity. As it causes severe erosion and noise, it is harmful to hydraulic machinery such as pumps, valves, and screw propellers. However, it can be utilized for water treatment, in chemical reactors, and as a mechanical surface treatment, as radicals and impacts at the point of cavitation bubble collapse can be utilized. Mechanical surface treatment using cavitation impacts is called “cavitation peening”. Cavitation peening causes less pollution because it uses water to treat the mechanical surface. In addition, cavitation peening improves on traditional methods in terms of fatigue strength and the working life of parts in the automobile, aerospace, and medical fields. As cavitation bubbles are utilized in cavitation peening, the study of cavitation bubbles has significant value in improving this new technique. To achieve this, many numerical analyses combined with field experiments have been carried out to measure the stress caused by bubble collapse and rebound, especially when collapse occurs near a solid boundary. Understanding the mechanics of bubble collapse can help to avoid unnecessary surface damage, enabling more accurate surface preparation, and improving the stability of cavitation peening. The present study introduces three cavitation bubble types: single, cloud, and vortex cavitation bubbles. In addition, the critical parameters, governing equations, and high-speed camera images of these three cavitation bubble types are introduced to support a broader understanding of the collapse mechanism and characteristics of cavitation bubbles. Then, the results of the numerical and experimental analyses of non-spherical cavitation bubbles are summarized. Full article

(This article belongs to the Special Issue Cavitation and Bubble Dynamics)

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26 pages, 881 KB

Open AccessEditor’s ChoiceArticle

Lattice Boltzmann Model for Rarefied Gaseous Mixture Flows in Three-Dimensional Porous Media Including Knudsen Diffusion

by Michel Ho, Jean-Michel Tucny, Sami Ammar, Sébastien Leclaire, Marcelo Reggio and Jean-Yves Trépanier

Fluids 2024, 9(10), 237; https://doi.org/10.3390/fluids9100237 - 9 Oct 2024

Cited by 5 | Viewed by 5136

Abstract

Numerical modeling of gas flows in rarefied regimes is crucial in understanding fluid behavior in microscale applications. Rarefied regimes are characterized by a decrease in molecular collisions, and they lead to unusual phenomena such as gas phase separation, which is not acknowledged in [...] Read more.

Numerical modeling of gas flows in rarefied regimes is crucial in understanding fluid behavior in microscale applications. Rarefied regimes are characterized by a decrease in molecular collisions, and they lead to unusual phenomena such as gas phase separation, which is not acknowledged in hydrodynamic equations. In this work, numerical investigation of miscible gaseous mixtures in the rarefied regime is performed using a modified lattice Boltzmann model. Slip boundary conditions are adapted to arbitrary geometries. A ray-tracing algorithm-based wall function is implemented to model the non-equilibrium effects in the transition flow regime. The molecular free flow defined by the Knudsen diffusion coefficient is integrated through an effective and asymmetrical binary diffusion coefficient. The numerical model is validated with mass flow measurements through microchannels of different cross-section shapes from the near-continuum to the transition regimes, and gas phase separation is studied within a staggered arrangement of spheres. The influence of porosity and mixture composition on the gas separation effect are analyzed. Numerical results highlight the increase in the degree of gas phase separation with the rarefaction rate and the molecular mass ratio. The various simulations also indicate that geometrical features in porous media have a greater impact on gaseous mixtures’ effective permeability at highly rarefied regimes. Finally, a permeability enhancement factor based on the lightest species of the gaseous mixture is derived. Full article

(This article belongs to the Special Issue Rarefied Gas Flows: From Micro-Nano Scale to Hypersonic Regime)

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23 pages, 1627 KB

Open AccessEditor’s ChoiceArticle

Data Assimilation and Parameter Identification for Water Waves Using the Nonlinear Schrödinger Equation and Physics-Informed Neural Networks

by Svenja Ehlers, Niklas A. Wagner, Annamaria Scherzl, Marco Klein, Norbert Hoffmann and Merten Stender

Fluids 2024, 9(10), 231; https://doi.org/10.3390/fluids9100231 - 1 Oct 2024

Cited by 6 | Viewed by 2965

Abstract

The measurement of deep water gravity wave elevations using in situ devices, such as wave gauges, typically yields spatially sparse data due to the deployment of a limited number of costly devices. This sparsity complicates the reconstruction of the spatio-temporal extent of surface [...] Read more.

The measurement of deep water gravity wave elevations using in situ devices, such as wave gauges, typically yields spatially sparse data due to the deployment of a limited number of costly devices. This sparsity complicates the reconstruction of the spatio-temporal extent of surface elevation and presents an ill-posed data assimilation problem, which is challenging to solve with conventional numerical techniques. To address this issue, we propose the application of a physics-informed neural network (PINN) to reconstruct physically consistent wave fields between two elevation time series measured at distinct locations within a numerical wave tank. Our method ensures this physical consistency by integrating residuals of the hydrodynamic nonlinear Schrödinger equation (NLSE) into the PINN’s loss function. We first showcase a data assimilation task by employing constant NLSE coefficients predetermined from spectral wave properties. However, due to the relatively short duration of these measurements and their possible deviation from the narrow-band assumptions inherent in the NLSE, using constant coefficients occasionally leads to poor reconstructions. To enhance this reconstruction quality, we introduce the base variables of frequency and wavenumber, from which the NLSE coefficients are determined, as additional neural network parameters that are fine tuned during PINN training. Overall, the results demonstrate the potential for real-world applications of the PINN method and represent a step toward improving the initialization of deterministic wave prediction methods. Full article

(This article belongs to the Special Issue Machine Learning and Artificial Intelligence in Fluid Mechanics)

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31 pages, 15837 KB

Open AccessEditor’s ChoiceReview

Numerical Simulations of Scalar Transport on Rough Surfaces

by Zvi Hantsis and Ugo Piomelli

Fluids 2024, 9(7), 159; https://doi.org/10.3390/fluids9070159 - 11 Jul 2024

Cited by 6 | Viewed by 2618

Abstract

Numerical simulations provide unfettered access to details of the flow where experimental measurements are difficult to obtain. This paper summarises the progress achieved in the study of passive scalars in flows over rough surfaces thanks to recent numerical simulations. Townsend’s similarity applies to [...] Read more.

Numerical simulations provide unfettered access to details of the flow where experimental measurements are difficult to obtain. This paper summarises the progress achieved in the study of passive scalars in flows over rough surfaces thanks to recent numerical simulations. Townsend’s similarity applies to various scalar statistics, implying the differences due to roughness are limited to the roughness sublayer (RSL). The scalar field exhibits a diffusive sublayer that increasingly conforms to the roughness surface as

k_{s}^{+}

or

P r

increase. The scalar wall flux is enhanced on the windward slopes of the roughness, where the analogy between momentum and scalar holds well; the momentum and scalar fields, however, have very different behaviours downwind of the roughness elements, due to recirculation, which reduces the scalar wall flux. Roughness causes breakdown of the Reynolds analogy: any increase in

S t

is accompanied by a larger increase in

c_{f}

. A flattening trend for the scalar roughness function,

Δ Θ^{+}

, is observed as

k_{s}^{+}

increases, suggesting the possibility of a scalar fully rough regime, different from the velocity one. The form-induced (FI) production of scalar fluctuations becomes dominant inside the RSL and is significantly different from the FI production of turbulent kinetic energy, resulting in notable differences between the scalar and velocity fluctuations. Several key questions remain open, in particular regarding the existence of a fully rough scalar regime and its characteristics. With the increase in

R e

and

P r

, various quantities such as scalar roughness function, the dispersive fluxes, FI wall flux, etc., appear to trend towards saturation. However, the limited range of

R e

and

P r

achieved by numerical simulations only allows us to speculate regarding such asymptotic behaviour. Beyond extending the range of

R e

and

P r

, systematic coverage of different roughness types and topologies is needed, as the scalar appears to remain sensitive to the geometrical details. Full article

(This article belongs to the Special Issue Recent Advances in Fluid Mechanics: Feature Papers, 2024)

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16 pages, 3777 KB

Open AccessEditor’s ChoiceArticle

Analytical Solution for Transient Electroosmotic and Pressure-Driven Flows in Microtubes

by Yu Feng, Hang Yi and Ruguan Liu

Fluids 2024, 9(6), 140; https://doi.org/10.3390/fluids9060140 - 11 Jun 2024

Cited by 4 | Viewed by 4976

Abstract

This study focuses on deriving and presenting an infinite series as the analytical solution for transient electroosmotic and pressure-driven flows in microtubes. Such a mathematical presentation of fluid dynamics under simultaneous electric field and pressure gradients leverages governing equations derived from the generalized [...] Read more.

This study focuses on deriving and presenting an infinite series as the analytical solution for transient electroosmotic and pressure-driven flows in microtubes. Such a mathematical presentation of fluid dynamics under simultaneous electric field and pressure gradients leverages governing equations derived from the generalized continuity and momentum equations simplified for laminar and axisymmetric flow. Velocity profile developments, apparent slip-induced flow rates, and shear stress distributions were analyzed by varying values of the ratio of microtube radius to Debye length and the electroosmotic slip velocity. Additionally, the “retarded time” in terms of hydraulic diameter, kinematic viscosity, and slip-induced flow rate was derived. A simpler polynomial series approximation for steady electroosmotic flow is also proposed for engineering convenience. The analytical solutions obtained in this study not only enhance the fundamental understanding of the electroosmotic flow characteristics within microtubes, emphasizing the interplay between electroosmotic and pressure-driven mechanisms, but also serve as a benchmark for validating computational fluid dynamics models for electroosmotic flow simulations in more complex flow domains. Moreover, the analytical approach aids in the parametric analysis, providing deeper insights into the impact of physical parameters on electroosmotic and pressure-driven flow behavior, which is critical for optimizing device performance in practical applications. These findings also offer insightful implications for diagnostic and therapeutic strategies in healthcare, particularly enhancing the capabilities of lab-on-a-chip technologies and paving the way for future research in the development and optimization of microfluidic systems. Full article

(This article belongs to the Special Issue Physics and Applications of Microfluidics)

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30 pages, 6032 KB

Open AccessEditor’s ChoiceSystematic Review

Hydraulic Flushing of Sediment in Reservoirs: Best Practices of Numerical Modeling

by Yong G. Lai, Jianchun Huang and Blair P. Greimann

Fluids 2024, 9(2), 38; https://doi.org/10.3390/fluids9020038 - 1 Feb 2024

Cited by 11 | Viewed by 10751

Abstract

This article provides a comprehensive review and best practices for numerically simulating hydraulic flushing for reservoir sediment management. Three sediment flushing types are discussed: drawdown flushing, pressure flushing, and turbidity current venting. The need for reservoir sediment management and the current practices are [...] Read more.

This article provides a comprehensive review and best practices for numerically simulating hydraulic flushing for reservoir sediment management. Three sediment flushing types are discussed: drawdown flushing, pressure flushing, and turbidity current venting. The need for reservoir sediment management and the current practices are reviewed. Different hydraulic drawdown types are described in terms of the basic physical processes involved as well as the empirical/analytical assessment tools that may be used. The primary focus has been on the numerical modeling of various hydraulic flushing options. Three model categories are reviewed: one-dimensional (1D), two-dimensional (2D) depth-averaged or layer-averaged, and three-dimensional (3D) computational fluid dynamics (CFD) models. General guidelines are provided on how to select a proper model given the characteristics of the reservoir and the flushing method, as well as specific guidelines for modeling. Case studies are also presented to illustrate the guidelines. Full article

(This article belongs to the Special Issue Environmental Hydraulics, Turbulence and Sediment Transport, 2nd edition)

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48 pages, 6734 KB

Open AccessEditor’s ChoiceReview

Fluid Flow in Helically Coiled Pipes

by Leonardo Di G. Sigalotti, Carlos E. Alvarado-Rodríguez and Otto Rendón

Fluids 2023, 8(12), 308; https://doi.org/10.3390/fluids8120308 - 27 Nov 2023

Cited by 13 | Viewed by 15388

Abstract

Helically coiled pipes are widely used in many industrial and engineering applications because of their compactness, larger heat transfer area per unit volume and higher efficiency in heat and mass transfer compared to other pipe geometries. They are commonly encountered in heat exchangers, [...] Read more.

Helically coiled pipes are widely used in many industrial and engineering applications because of their compactness, larger heat transfer area per unit volume and higher efficiency in heat and mass transfer compared to other pipe geometries. They are commonly encountered in heat exchangers, steam generators in power plants and chemical reactors. The most notable feature of flow in helical pipes is the secondary flow (i.e., the cross-sectional circulatory motion) caused by centrifugal forces due to the curvature. Other important features are the stabilization effects of turbulent flow and the higher Reynolds number at which the transition from a laminar to a turbulent state occurs compared to straight pipes. A survey of the open literature on helical pipe flows shows that a good deal of experimental and theoretical work has been conducted to derive appropriate correlations to predict frictional pressure losses under laminar and turbulent conditions as well as to study the dependence of the flow characteristics and heat transfer capabilities on the Reynolds number, the Nusselt number and the geometrical parameters of the helical pipe. Despite the progress made so far in understanding the flow and heat transfer characteristics of helical pipe flow, there is still much work to be completed to address the more complex problem of multiphase flows and the impact of pipe deformation and corrugation on single- and multiphase flow. The aim of this paper is to provide a review on the state-of-the-art experimental and theoretical research concerning the flow in helically coiled pipes. Full article

(This article belongs to the Special Issue Pipe Flow: Research and Applications)

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16 pages, 1167 KB

Open AccessEditor’s ChoiceReview

Can Artificial Intelligence Accelerate Fluid Mechanics Research?

by Dimitris Drikakis and Filippos Sofos

Fluids 2023, 8(7), 212; https://doi.org/10.3390/fluids8070212 - 19 Jul 2023

Cited by 43 | Viewed by 12752

Abstract

The significant growth of artificial intelligence (AI) methods in machine learning (ML) and deep learning (DL) has opened opportunities for fluid dynamics and its applications in science, engineering and medicine. Developing AI methods for fluid dynamics encompass different challenges than applications with massive [...] Read more.

The significant growth of artificial intelligence (AI) methods in machine learning (ML) and deep learning (DL) has opened opportunities for fluid dynamics and its applications in science, engineering and medicine. Developing AI methods for fluid dynamics encompass different challenges than applications with massive data, such as the Internet of Things. For many scientific, engineering and biomedical problems, the data are not massive, which poses limitations and algorithmic challenges. This paper reviews ML and DL research for fluid dynamics, presents algorithmic challenges and discusses potential future directions. Full article

(This article belongs to the Special Issue Machine Learning and Artificial Intelligence in Fluid Mechanics)

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17 pages, 15365 KB

Open AccessEditor’s ChoiceArticle

Thermorheological Behavior of κ-Carrageenan Hydrogels Modified with Xanthan Gum

by Pietro Renato Avallone, Simona Russo Spena, Stefano Acierno, Maria Giovanna Esposito, Andrea Sarrica, Marco Delmonte, Rossana Pasquino and Nino Grizzuti

Fluids 2023, 8(4), 119; https://doi.org/10.3390/fluids8040119 - 1 Apr 2023

Cited by 28 | Viewed by 7370

Abstract

Hydrocolloids are long-chain biopolymers that can form viscous solutions or gels when dissolved in water. They are employed as rheological modifiers in various manufacturing processes or finished products. Due to its unique gelation properties, animal gelatin is one of the most widely used [...] Read more.

Hydrocolloids are long-chain biopolymers that can form viscous solutions or gels when dissolved in water. They are employed as rheological modifiers in various manufacturing processes or finished products. Due to its unique gelation properties, animal gelatin is one of the most widely used hydrocolloids, finding applications in several fields such as food, pharmaceutical, and photographic. Nowadays, the challenge of finding valid alternatives to animal products has become a crucial issue, for both ethical and environmental reasons. The aim of this work, is to propose a green hydrocolloidal network, able to reproduce the gelation features of animal gelatin gels. κ-carrageenan gels may be an interesting alternative to gelatin, due to their attractive gelling features. We investigate the thermorheological behavior of κ-carrageenan aqueous solutions at various concentrations, focusing on gel features such as transition temperature and gel strength. To improve the viscoelastic response of such gels, we add a viscosity-enhancing hydrocolloid, i.e., xanthan gum. The results show that the gel strength increases exponentially with xanthan concentration, thus suggesting a synergistic interaction between the two networks. We also study the effect of sucrose on the thermal and mechanical properties of modified gels, finding a marked increase in transition temperatures and gel elasticity. In recent years, three-dimensional (3D) food printing has been extensively studied in the food industry, due to its many advantages, such as customized food design, personalized nutrition, simplified supply chain, and the expansion of available food materials. In view of this growing interest for additive manufacturing, we also study the printability of the complete formulation composed of κ-carrageenan, xanthan gum and sucrose. Full article

(This article belongs to the Section Non-Newtonian and Complex Fluids)

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17 pages, 7480 KB

Open AccessEditor’s ChoiceArticle

Turbulence Modeling for Physics-Informed Neural Networks: Comparison of Different RANS Models for the Backward-Facing Step Flow

by Fabian Pioch, Jan Hauke Harmening, Andreas Maximilian Müller, Franz-Josef Peitzmann, Dieter Schramm and Ould el Moctar

Fluids 2023, 8(2), 43; https://doi.org/10.3390/fluids8020043 - 26 Jan 2023

Cited by 54 | Viewed by 13174

Abstract

Physics-informed neural networks (PINN) can be used to predict flow fields with a minimum of simulated or measured training data. As most technical flows are turbulent, PINNs based on the Reynolds-averaged Navier–Stokes (RANS) equations incorporating a turbulence model are needed. Several studies demonstrated [...] Read more.

Physics-informed neural networks (PINN) can be used to predict flow fields with a minimum of simulated or measured training data. As most technical flows are turbulent, PINNs based on the Reynolds-averaged Navier–Stokes (RANS) equations incorporating a turbulence model are needed. Several studies demonstrated the capability of PINNs to solve the Naver–Stokes equations for laminar flows. However, little work has been published concerning the application of PINNs to solve the RANS equations for turbulent flows. This study applied a RANS-based PINN approach to a backward-facing step flow at a Reynolds number of 5100. The standard k-

ω

model, the mixing length model, an equation-free

ν_{t}

and an equation-free pseudo-Reynolds stress model were applied. The results compared favorably to DNS data when provided with three vertical lines of labeled training data. For five lines of training data, all models predicted the separated shear layer and the associated vortex more accurately. Full article

(This article belongs to the Special Issue Machine Learning and Artificial Intelligence in Fluid Mechanics)

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26 pages, 5886 KB

Open AccessEditor’s ChoiceArticle

Evaluation of RANS-DEM and LES-DEM Methods in OpenFOAM for Simulation of Particle-Laden Turbulent Flows

by Atul Jaiswal, Minh Duc Bui and Peter Rutschmann

Fluids 2022, 7(10), 337; https://doi.org/10.3390/fluids7100337 - 21 Oct 2022

Cited by 17 | Viewed by 6840

Abstract

CFD-DEM modelling of particle-laden turbulent flow is challenging in terms of the required and obtained CFD resolution, heavy DEM computations, and the limitations of the method. Here, we assess the efficiency of a particle-tracking solver in OpenFOAM with RANS-DEM and LES-DEM approaches under [...] Read more.

CFD-DEM modelling of particle-laden turbulent flow is challenging in terms of the required and obtained CFD resolution, heavy DEM computations, and the limitations of the method. Here, we assess the efficiency of a particle-tracking solver in OpenFOAM with RANS-DEM and LES-DEM approaches under the unresolved CFD-DEM framework. Furthermore, we investigate aspects of the unresolved CFD-DEM method with regard to the coupling regime, particle boundary condition and turbulence modelling. Applying one-way and two-way coupling to our RANS-DEM simulations demonstrates that it is sufficient to include one-way coupling when the particle concentration is small (O ~

10^{- 5}

). Moreover, our study suggests an approach to estimate the particle boundary condition for cases when data is unavailable. In contrast to what has been previously reported for the adopted case, our RANS-DEM results demonstrate that simple dispersion models considerably underpredict particle dispersion and previously observed reasonable particle dispersion were due to an error in the numerical setup rather than the used dispersion model claiming to include turbulence effects on particle trajectories. LES-DEM may restrict extreme mesh refinement, and, under such scenarios, dynamic LES turbulence models seem to overcome the poor performance of static LES turbulence models. Sub-grade scale effects cannot be neglected when using coarse mesh resolution in LES-DEM and must be recovered with efficient modelling approaches to predict accurate particle dispersion. Full article

(This article belongs to the Section Flow of Multi-Phase Fluids and Granular Materials)

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21 pages, 1280 KB

Open AccessEditor’s ChoiceArticle

Dimples for Skin-Friction Drag Reduction: Status and Perspectives

by Federica Gattere, Alessandro Chiarini and Maurizio Quadrio

Fluids 2022, 7(7), 240; https://doi.org/10.3390/fluids7070240 - 13 Jul 2022

Cited by 22 | Viewed by 6634

Abstract

Dimples are small concavities imprinted on a flat surface, known to affect heat transfer and also flow separation and aerodynamic drag on bluff bodies when acting as a standard roughness. Recently, dimples have been proposed as a roughness pattern that is capable of [...] Read more.

Dimples are small concavities imprinted on a flat surface, known to affect heat transfer and also flow separation and aerodynamic drag on bluff bodies when acting as a standard roughness. Recently, dimples have been proposed as a roughness pattern that is capable of reducing the turbulent drag of a flat plate by providing a reduction of skin friction that compensates the dimple-induced pressure drag and leads to a global benefit. The question whether dimples do actually work to reduce friction drag is still unsettled. In this paper, we provide a comprehensive review of the available information, touching upon the many parameters that characterize the problem. A number of reasons that contribute to explaining the contrasting literature information are discussed. We also provide guidelines for future studies by highlighting key methodological steps required for a meaningful comparison between a flat and dimpled surface in view of drag reduction. Full article

(This article belongs to the Special Issue Drag Reduction in Turbulent Flows)

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15 pages, 6812 KB

Open AccessEditor’s ChoiceReview

Deep Learning for Computational Hemodynamics: A Brief Review of Recent Advances

by Amirtahà Taebi

Fluids 2022, 7(6), 197; https://doi.org/10.3390/fluids7060197 - 9 Jun 2022

Cited by 42 | Viewed by 14976

Abstract

Computational fluid dynamics (CFD) modeling of blood flow plays an important role in better understanding various medical conditions, designing more effective drug delivery systems, and developing novel diagnostic methods and treatments. However, despite significant advances in computational technology and resources, the expensive computational [...] Read more.

Computational fluid dynamics (CFD) modeling of blood flow plays an important role in better understanding various medical conditions, designing more effective drug delivery systems, and developing novel diagnostic methods and treatments. However, despite significant advances in computational technology and resources, the expensive computational cost of these simulations still hinders their transformation from a research interest to a clinical tool. This bottleneck is even more severe for image-based, patient-specific CFD simulations with realistic boundary conditions and complex computational domains, which make such simulations excessively expensive. To address this issue, deep learning approaches have been recently explored to accelerate computational hemodynamics simulations. In this study, we review recent efforts to integrate deep learning with CFD and discuss the applications of this approach in solving hemodynamics problems, such as blood flow behavior in aorta and cerebral arteries. We also discuss potential future directions in the field. In this review, we suggest that incorporating physiologic understandings and underlying fluid mechanics laws in deep learning models will soon lead to a paradigm shift in the development novel non-invasive computational medical decisions. Full article

(This article belongs to the Special Issue Advances in Biological Flows and Biomimetics, Volume II)

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25 pages, 15387 KB

Open AccessEditor’s ChoiceReview

Computational Methods for Fluid-Structure Interaction Simulation of Heart Valves in Patient-Specific Left Heart Anatomies

by Trung Bao Le, Mustafa Usta, Cyrus Aidun, Ajit Yoganathan and Fotis Sotiropoulos

Fluids 2022, 7(3), 94; https://doi.org/10.3390/fluids7030094 - 4 Mar 2022

Cited by 17 | Viewed by 9530

Abstract

Given the complexity of human left heart anatomy and valvular structures, the fluid–structure interaction (FSI) simulation of native and prosthetic valves poses a significant challenge for numerical methods. In this review, recent numerical advancements for both fluid and structural solvers for heart valves [...] Read more.

Given the complexity of human left heart anatomy and valvular structures, the fluid–structure interaction (FSI) simulation of native and prosthetic valves poses a significant challenge for numerical methods. In this review, recent numerical advancements for both fluid and structural solvers for heart valves in patient-specific left hearts are systematically considered, emphasizing the numerical treatments of blood flow and valve surfaces, which are the most critical aspects for accurate simulations. Numerical methods for hemodynamics are considered under both the continuum and discrete (particle) approaches. The numerical treatments for the structural dynamics of aortic/mitral valves and FSI coupling methods between the solid

Ω_{s}

and fluid domain

Ω_{f}

are also reviewed. Future work toward more advanced patient-specific simulations is also discussed, including the fusion of high-fidelity simulation within vivo measurements and physics-based digital twining based on data analytics and machine learning techniques. Full article

(This article belongs to the Special Issue Computational Biofluiddynamics: Advances and Applications)

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21 pages, 636 KB

Open AccessEditor’s ChoiceTutorial

A CFD Tutorial in Julia: Introduction to Compressible Laminar Boundary-Layer Flows

by Furkan Oz and Kursat Kara

Fluids 2021, 6(11), 400; https://doi.org/10.3390/fluids6110400 - 5 Nov 2021

Cited by 19 | Viewed by 7749

Abstract

A boundary-layer is a thin fluid layer near a solid surface, and viscous effects dominate it. The laminar boundary-layer calculations appear in many aerodynamics problems, including skin friction drag, flow separation, and aerodynamic heating. A student must understand the flow physics and the [...] Read more.

A boundary-layer is a thin fluid layer near a solid surface, and viscous effects dominate it. The laminar boundary-layer calculations appear in many aerodynamics problems, including skin friction drag, flow separation, and aerodynamic heating. A student must understand the flow physics and the numerical implementation to conduct successful simulations in advanced undergraduate- and graduate-level fluid dynamics/aerodynamics courses. Numerical simulations require writing computer codes. Therefore, choosing a fast and user-friendly programming language is essential to reduce code development and simulation times. Julia is a new programming language that combines performance and productivity. The present study derived the compressible Blasius equations from Navier–Stokes equations and numerically solved the resulting equations using the Julia programming language. The fourth-order Runge–Kutta method is used for the numerical discretization, and Newton’s iteration method is employed to calculate the missing boundary condition. In addition, Burgers’, heat, and compressible Blasius equations are solved both in Julia and MATLAB. The runtime comparison showed that Julia with

f o r

loops is 2.5 to 120 times faster than MATLAB. We also released the Julia codes on our GitHub page to shorten the learning curve for interested readers. Full article

(This article belongs to the Collection Feature Paper for Mathematical and Computational Fluid Mechanics)

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17 pages, 3567 KB

Open AccessEditor’s ChoiceArticle

Galilean-Invariant Characteristic-Based Volume Penalization Method for Supersonic Flows with Moving Boundaries

by Nurlybek Kasimov, Eric Dymkoski, Giuliano De Stefano and Oleg V. Vasilyev

Fluids 2021, 6(8), 293; https://doi.org/10.3390/fluids6080293 - 20 Aug 2021

Cited by 13 | Viewed by 3906

Abstract

This work extends the characteristic-based volume penalization method, originally developed and demonstrated for compressible subsonic viscous flows in (J. Comput. Phys. 262, 2014), to a hyperbolic system of partial differential equations involving complex domains with moving boundaries. The proposed methodology is shown to [...] Read more.

This work extends the characteristic-based volume penalization method, originally developed and demonstrated for compressible subsonic viscous flows in (J. Comput. Phys. 262, 2014), to a hyperbolic system of partial differential equations involving complex domains with moving boundaries. The proposed methodology is shown to be Galilean-invariant and can be used to impose either homogeneous or inhomogeneous Dirichlet, Neumann, and Robin type boundary conditions on immersed boundaries. Both integrated and non-integrated variables can be treated in a systematic manner that parallels the prescription of exact boundary conditions with the approximation error rigorously controlled through an a priori penalization parameter. The proposed approach is well suited for use with adaptive mesh refinement, which allows adequate resolution of the geometry without over-resolving flow structures and minimizing the number of grid points inside the solid obstacle. The extended Galilean-invariant characteristic-based volume penalization method, while being generally applicable to both compressible Navier–Stokes and Euler equations across all speed regimes, is demonstrated for a number of supersonic benchmark flows around both stationary and moving obstacles of arbitrary shape. Full article

(This article belongs to the Special Issue Wavelets and Fluid Dynamics)

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19 pages, 39580 KB

Open AccessEditor’s ChoiceArticle

Thermo-Environmental Performance of Four Different Shapes of Solar Greenhouse Dryer with Free Convection Operating Principle and No Load on Product

by Edwin Villagran, Juan Camilo Henao-Rojas and German Franco

Fluids 2021, 6(5), 183; https://doi.org/10.3390/fluids6050183 - 13 May 2021

Cited by 25 | Viewed by 6738

Abstract

Solar drying using greenhouse dryers is a viable method from the technical, economic, and environmental perspectives, allowing the drying of agricultural products for conservation purposes in different regions of the world. In Colombia, the drying of aromatic plants such as mint (Mentha [...] Read more.

Solar drying using greenhouse dryers is a viable method from the technical, economic, and environmental perspectives, allowing the drying of agricultural products for conservation purposes in different regions of the world. In Colombia, the drying of aromatic plants such as mint (Mentha spicata) is usually done directly and in open fields, which exposes the product to contamination and loss of quality. Therefore, the objective of this research was to use a three-dimensional computational fluid dynamics (CFD-3D) model previously successfully validated and implemented in this work to study the performance of air flow patterns, temperature, and humidity inside four greenhouse-type dryers contemplated for a region with hot and humid climatic conditions. The results found allowed us to observe that the spatial distribution of temperature and relative humidity are related to the air flows generated inside each dryer, therefore, there were differences of up to 7.91 °C and 23.81% for the same evaluated scenario. The study also allowed us to conclude that the CFD methodology is an agile and precise tool that allows us to evaluate prototypes that have not been built to real scale, which allows us to generate useful information for decision-making regarding the best prototype to build under a specific climate condition. Full article

(This article belongs to the Special Issue Advances in Thermo-Fluid Dynamics of Industrial Systems)

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17 pages, 1030 KB

Open AccessEditor’s ChoiceArticle

Characterising Momentum Flux Events in High Reynolds Number Turbulent Boundary Layers

by Rahul Deshpande and Ivan Marusic

Fluids 2021, 6(4), 168; https://doi.org/10.3390/fluids6040168 - 20 Apr 2021

Cited by 12 | Viewed by 4075

Abstract

The momentum flux in a canonical turbulent boundary layer is known to have a time-series signature that is characterised by a highly intermittent variation, which includes very short periods of intense flux activity. Here, we study the variation in these flux signal characteristics [...] Read more.

The momentum flux in a canonical turbulent boundary layer is known to have a time-series signature that is characterised by a highly intermittent variation, which includes very short periods of intense flux activity. Here, we study the variation in these flux signal characteristics across almost a decade of flow Reynolds number (

R e_{τ}

) by analysing datasets acquired using miniature cross-wire probes with matched spatial resolution. The analysis is facilitated by conditionally sampling the signal based on the quadrant (Qi; i = 1–4) and magnitude of the flux, revealing fractional cumulative contribution from Q4 to increase at a much faster rate than from Q2 with

R e_{τ}

. An episodic description of the flux signal is subsequently undertaken, which associates this rapid increase in Q4 contributions with the emergence of extreme and rare flux events with

R e_{τ}

. The same dataset is also used to test Townsend’s hypothesis on the active and inactive components of the momentum flux, which are obtained for the first time by implementing a spectral linear stochastic estimation-based decomposition methodology. While the active component is found to be the dominant contributor to the mean momentum flux consistent with Townsend’s hypothesis, the inactive component is found to be small but non-zero, owing to the non-linear interactions associated with the modulation phenomenon. Finally, an episodic description of the active and inactive momentum flux signal is undertaken to highlight the starkly different time series characteristics of the two flux components. The inactive flux signal is found to comprise individual statistically significant events associated with all four quadrants, leading to a small net contribution to the total flux. Full article

(This article belongs to the Special Issue Turbulent Flows at Solid and Free Surface Boundaries in Memory of William W. Willmarth)

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20 pages, 7279 KB

Open AccessEditor’s ChoiceArticle

Experimental and Numerical Study of Swirling Diffusion Flame Provided by a Coaxial Burner: Effect of Inlet Velocity Ratio

by Sawssen Chakchak, Ammar Hidouri, Hajar Zaidaoui, Mouldi Chrigui and Toufik Boushaki

Fluids 2021, 6(4), 159; https://doi.org/10.3390/fluids6040159 - 16 Apr 2021

Cited by 11 | Viewed by 5865

Abstract

This paper reports an experimental and numerical investigation of a methane-air diffusion flame stabilized over a swirler coaxial burner. The burner configuration consists of two tubes with a swirler placed in the annular part. The passage of the oxidant is ensured by the [...] Read more.

This paper reports an experimental and numerical investigation of a methane-air diffusion flame stabilized over a swirler coaxial burner. The burner configuration consists of two tubes with a swirler placed in the annular part. The passage of the oxidant is ensured by the annular tube; however, the fuel is injected by the central jet through eight holes across the oxidizer flow. The experiments were conducted in a combustion chamber of 25 kW power and 48 × 48 × 100 cm³ dimensions. Numerical flow fields were compared with stereoscopic particle image velocimetry (stereo-PIV) fields for non-reacting and reacting cases. The turbulence was captured using the Reynolds averaged Navier-Stokes (RANS) approach, associated with the eddy dissipation combustion model (EDM) to resolve the turbulence/chemistry interaction. The simulations were performed using the Fluent CFD (Computational Fluid Dynamic) code. Comparison of the computed results and the experimental data showed that the RANS results were capable of predicting the swirling flow. The effect of the inlet velocity ratio on dynamic flow behavior, temperature distribution, species mass fraction and the pollutant emission were numerically studied. The results showed that the radial injection of fuel induces a partial premixing between reactants, which affects the flame behavior, in particular the flame stabilization. The increase in the velocity ratio (R_v) improves the turbulence and subsequently ameliorates the mixing. CO emissions caused by the temperature variation are also decreased due to the improvement of the inlet velocity ratio. Full article

(This article belongs to the Special Issue Fluid Flow and Its Impact on Combustion)

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14 pages, 1108 KB

Open AccessEditor’s ChoiceArticle

Precise Method to Estimate the Herschel-Bulkley Parameters from Pipe Rheometer Measurements

by Elie Magnon and Eric Cayeux

Fluids 2021, 6(4), 157; https://doi.org/10.3390/fluids6040157 - 14 Apr 2021

Cited by 36 | Viewed by 12672

Abstract

Accurate characterization of the rheological behavior of non-Newtonian fluids is critical in a wide range of industries as it governs process efficiency, safety, and end-product quality. When the rheological behavior of fluid may vary substantially over a relatively short period of time, it [...] Read more.

Accurate characterization of the rheological behavior of non-Newtonian fluids is critical in a wide range of industries as it governs process efficiency, safety, and end-product quality. When the rheological behavior of fluid may vary substantially over a relatively short period of time, it is desirable to measure its viscous properties on a more continuous basis than relying on spot measurements made with a viscometer on a few samples. An attractive solution for inline rheological measurements is to measure pressure gradients while circulating fluid at different bulk velocities in a circular pipe. Yet, extracting the rheological model parameters may be challenging as measurement uncertainty may influence the precision of the model fitting. In this paper, we present a method to calibrate the Herschel-Bulkley rheological model to a series of differential pressure measurements made at variable bulk velocities using a combination of physics-based equations and nonlinear optimization. Experimental validation of the method is conducted on non-Newtonian shear-thinning fluid based on aqueous solutions of polymers and the results are compared to those obtained with a scientific rheometer. It is found that using a physics-based method to estimate the parameters contributes to reducing prediction errors, especially at low flow rates. With the tested polymeric fluid, the proportion difference between the estimated Herschel-Bulkley parameters and those obtained using the scientific rheometer are −24% for the yield stress, 0.26% for the consistency index, and 0.30% for the flow behavior index. Finally, the computation requires limited resources, and the algorithm can be implemented on low-power devices such as an embedded single-board computer or a mobile device. Full article

(This article belongs to the Special Issue Complex Fluids and Flows: Algorithms and Applications)

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15 pages, 5118 KB

Open AccessEditor’s ChoiceArticle

Gas–Liquid Two-Phase Flow and Heat Transfer without Phase Change in Microfluidic Heat Exchanger

by Maksim P. Vasilev and Rufat Sh. Abiev

Fluids 2021, 6(4), 150; https://doi.org/10.3390/fluids6040150 - 9 Apr 2021

Cited by 7 | Viewed by 5567

Abstract

This work presents an experimental study of the possibility of intensifying in microfluidic heat exchangers (MFHE) by creating a two-phase segmented flow (gas–liquid). Measurements of convective heat transfer were carried out using an MFHE, consisting of six channels 1 × 1 mm. Experimental [...] Read more.

This work presents an experimental study of the possibility of intensifying in microfluidic heat exchangers (MFHE) by creating a two-phase segmented flow (gas–liquid). Measurements of convective heat transfer were carried out using an MFHE, consisting of six channels 1 × 1 mm. Experimental studies have shown that segmented flow makes it possible to increase the Nusselt number of a laminar flow in MFHE up to 1.67 and reduce thermal resistance up to 1.7 times compared to single-phase flow. At the same time, it was found that the intensification of heat exchange by a two-phase flow is observed only for the range of the volume fraction of gas from 10 to 30%. In addition, the calculation of the thermal performance criterion, including both thermal and hydraulic parameters (friction factor), also confirmed the promise of using the Taylor segmented flow as a method for single-phase heat transfer intensifying in microchannels. Full article

(This article belongs to the Special Issue Flow and Heat Transfer Intensification in Chemical Engineering)

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13 pages, 2175 KB

Open AccessEditor’s ChoiceArticle

Numerical Simulation of Propagation and Run-Up of Long Waves in U-Shaped Bays

by Sri R. Pudjaprasetya, Vania M. Risriani and Iryanto

Fluids 2021, 6(4), 146; https://doi.org/10.3390/fluids6040146 - 8 Apr 2021

Cited by 9 | Viewed by 3553

Abstract

Wave propagation and run-up in U-shaped channel bays are studied here in the framework of the quasi-1D Saint-Venant equations. Our approach is numerical, using the momentum conserving staggered-grid (MCS) scheme, as a consistent approximation of the Saint-Venant equations. We carried out simulations regarding [...] Read more.

Wave propagation and run-up in U-shaped channel bays are studied here in the framework of the quasi-1D Saint-Venant equations. Our approach is numerical, using the momentum conserving staggered-grid (MCS) scheme, as a consistent approximation of the Saint-Venant equations. We carried out simulations regarding wave focusing and run-ups in U-shaped bays. We obtained good agreement with the existing analytical results on several aspects: the moving shoreline, wave shoaling, and run-up heights. Our findings also confirm that the run-up height is significantly higher in the parabolic bay than on a plane beach. This assessment shows the merit of the MCS scheme in describing wave focusing and run-up in U-shaped bays. Moreover, the MCS scheme is also efficient because it is based on the quasi-1D Saint-Venant equations. Full article

(This article belongs to the Special Issue Theory and Applications of Ocean Surface Waves)

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48 pages, 8203 KB

Open AccessEditor’s ChoiceReview

An Overview of the Lagrangian Dispersion Modeling of Heavy Particles in Homogeneous Isotropic Turbulence and Considerations on Related LES Simulations

by Daniel G. F. Huilier

Fluids 2021, 6(4), 145; https://doi.org/10.3390/fluids6040145 - 8 Apr 2021

Cited by 23 | Viewed by 7614

Abstract

Particle tracking is a competitive technique widely used in two-phase flows and best suited to simulate the dispersion of heavy particles in the atmosphere. Most Lagrangian models in the statistical approach to turbulence are based either on the eddy interaction model (EIM) and [...] Read more.

Particle tracking is a competitive technique widely used in two-phase flows and best suited to simulate the dispersion of heavy particles in the atmosphere. Most Lagrangian models in the statistical approach to turbulence are based either on the eddy interaction model (EIM) and the Monte-Carlo method or on random walk models (RWMs) making use of Markov chains and a Langevin equation. In the present work, both discontinuous and continuous random walk techniques are used to model the dispersion of heavy spherical particles in homogeneous isotropic stationary turbulence (HIST). Their efficiency to predict particle long time dispersion, mean-square velocity and Lagrangian integral time scales are discussed. Computation results with zero and no-zero mean drift velocity are reported; they are intended to quantify the inertia, gravity, crossing-trajectory and continuity effects controlling the dispersion. The calculations concern dense monodisperse spheres in air, the particle Stokes number ranging from 0.007 to 4. Due to the weaknesses of such models, a more sophisticated matrix method will also be explored, able to simulate the true fluid turbulence experienced by the particle for long time dispersion studies. Computer evolution and performance since allowed to develop, instead of Reynold-Averaged Navier-Stokes (RANS)-based studies, large eddy simulation (LES) and direct numerical simulation (DNS) of turbulence coupled to Generalized Langevin Models. A short review on the progress of the Lagrangian simulations based on large eddy simulation (LES) will therefore be provided too, highlighting preferential concentration. The theoretical framework for the fluid time correlation functions along the heavy particle path is that suggested by Wang and Stock. Full article

(This article belongs to the Special Issue Numerical Methods and Physical Aspects of Multiphase Flow)

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12 pages, 555 KB

Open AccessEditor’s ChoiceArticle

Effect of Wall Boundary Conditions on a Wall-Modeled Large-Eddy Simulation in a Finite-Difference Framework

by H. Jane Bae and Adrián Lozano-Durán

Fluids 2021, 6(3), 112; https://doi.org/10.3390/fluids6030112 - 10 Mar 2021

Cited by 27 | Viewed by 4983

Abstract

We studied the effect of wall boundary conditions on the statistics in a wall-modeled large-eddy simulation (WMLES) of turbulent channel flows. Three different forms of the boundary condition based on the mean stress-balance equations were used to supply the correct mean wall shear [...] Read more.

We studied the effect of wall boundary conditions on the statistics in a wall-modeled large-eddy simulation (WMLES) of turbulent channel flows. Three different forms of the boundary condition based on the mean stress-balance equations were used to supply the correct mean wall shear stress for a wide range of Reynolds numbers and grid resolutions applicable to WMLES. In addition to the widely used Neumann boundary condition at the wall, we considered a case with a no-slip condition at the wall in which the wall stress was imposed by adjusting the value of the eddy viscosity at the wall. The results showed that the type of boundary condition utilized had an impact on the statistics (e.g., mean velocity profile and turbulence intensities) in the vicinity of the wall, especially at the first off-wall grid point. Augmenting the eddy viscosity at the wall resulted in improved predictions of statistics in the near-wall region, which should allow the use of information from the first off-wall grid point for wall models without additional spatial or temporal filtering. This boundary condition is easy to implement and provides a simple solution to the well-known log-layer mismatch in WMLES. Full article

(This article belongs to the Special Issue Turbulent Flows at Solid and Free Surface Boundaries in Memory of William W. Willmarth)

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44 pages, 8408 KB

Open AccessEditor’s ChoiceReview

Physical Background, Computations and Practical Issues of the Magnetohydrodynamic Pressure Drop in a Fusion Liquid Metal Blanket

by Sergey Smolentsev

Fluids 2021, 6(3), 110; https://doi.org/10.3390/fluids6030110 - 8 Mar 2021

Cited by 69 | Viewed by 7326

Abstract

In blankets of a fusion power reactor, liquid metal (LM) breeders, such as pure lithium or lead-lithium alloy, circulate in complex shape blanket conduits for power conversion and tritium breeding in the presence of a strong plasma-confining magnetic field. The interaction of the [...] Read more.

In blankets of a fusion power reactor, liquid metal (LM) breeders, such as pure lithium or lead-lithium alloy, circulate in complex shape blanket conduits for power conversion and tritium breeding in the presence of a strong plasma-confining magnetic field. The interaction of the magnetic field with induced electric currents in the breeder results in various magnetohydrodynamic (MHD) effects on the flow. Of them, high MHD pressure losses in the LM breeder flows is one of the most important feasibility issues. To design new feasible LM breeding blankets or to improve the existing blanket concepts and designs, one needs to identify and characterize sources of high MHD pressure drop, to understand the underlying physics of MHD flows and to eventually define ways of mitigating high MHD pressure drop in the entire blanket and its sub-components. This article is a comprehensive review of earlier and recent studies of MHD pressure drop in LM blankets with a special focus on: (1) physics of LM MHD flows in typical blanket configurations, (2) development and testing of computational tools for LM MHD flows, (3) practical aspects associated with pumping of a conducting liquid breeder through a strong magnetic field, and (4) approaches to mitigation of the MHD pressure drop in a LM blanket. Full article

(This article belongs to the Special Issue Fluids in Magnetic/Electric Fields)

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18 pages, 8052 KB

Open AccessEditor’s ChoiceArticle

Numerical Investigation of Spray Collapse in GDI with OpenFOAM

by Jan Wilhelm Gärtner, Ye Feng, Andreas Kronenburg and Oliver T. Stein

Fluids 2021, 6(3), 104; https://doi.org/10.3390/fluids6030104 - 4 Mar 2021

Cited by 22 | Viewed by 4746

Abstract

During certain operating conditions in spark-ignited direct injection engines (GDI), the injected fuel will be superheated and begin to rapidly vaporize. Fast vaporization can be beneficial for fuel–oxidizer mixing and subsequent combustion, but it poses the risk of spray collapse. In this work, [...] Read more.

During certain operating conditions in spark-ignited direct injection engines (GDI), the injected fuel will be superheated and begin to rapidly vaporize. Fast vaporization can be beneficial for fuel–oxidizer mixing and subsequent combustion, but it poses the risk of spray collapse. In this work, spray collapse is numerically investigated for a single hole and the spray G eight-hole injector of an engine combustion network (ECN). Results from a new OpenFOAM solver are first compared against results of the commercial CONVERGE software for single-hole injectors and validated. The results corroborate the perception that the superheat ratio

R_{p}

, which is typically used for the classification of flashing regimes, cannot describe spray collapse behavior. Three cases using the eight-hole spray G injector geometry are compared with experimental data. The first case is the standard G2 test case, with iso-octane as an injected fluid, which is only slightly superheated, whereas the two other cases use propane and show spray collapse behavior in the experiment. The numerical results support the assumption that the interaction of shocks due to the underexpanded vapor jet causes spray collapse. Further, the spray structures match well with experimental data, and shock interactions that provide an explanation for the observed phenomenon are discussed. Full article

(This article belongs to the Special Issue Modelling of Reactive and Non-reactive Multiphase Flows)

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16 pages, 5619 KB

Open AccessEditor’s ChoiceArticle

Experimental Study on Coherent Structures by Particles Suspended in Half-Zone Thermocapillary Liquid Bridges: Review

by Ichiro Ueno

Fluids 2021, 6(3), 105; https://doi.org/10.3390/fluids6030105 - 4 Mar 2021

Cited by 10 | Viewed by 3039

Abstract

Coherent structures by the particles suspended in the half-zone thermocapillary liquid bridges via experimental approaches are introduced. General knowledge on the particle accumulation structures (PAS) is described, and then the spatial–temporal behaviours of the particles forming the PAS are illustrated with the results [...] Read more.

Coherent structures by the particles suspended in the half-zone thermocapillary liquid bridges via experimental approaches are introduced. General knowledge on the particle accumulation structures (PAS) is described, and then the spatial–temporal behaviours of the particles forming the PAS are illustrated with the results of the two- and three-dimensional particle tracking. Variations of the coherent structures as functions of the intensity of the thermocapillary effect and the particle size are introduced by focusing on the PAS of the azimuthal wave number

m = 3

. Correlation between the particle behaviour and the ordered flow structures known as the Kolmogorov–Arnold—Moser tori is discussed. Recent works on the PAS of

m = 1

are briefly introduced. Full article

(This article belongs to the Special Issue Thermal Flows)

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16 pages, 4249 KB

Open AccessEditor’s ChoiceArticle

Machine Learning Techniques for Fluid Flows at the Nanoscale

by Filippos Sofos and Theodoros E. Karakasidis

Fluids 2021, 6(3), 96; https://doi.org/10.3390/fluids6030096 - 1 Mar 2021

Cited by 16 | Viewed by 4082

Abstract

Simulations of fluid flows at the nanoscale feature massive data production and machine learning (ML) techniques have been developed during recent years to leverage them, presenting unique results. This work facilitates ML tools to provide an insight on properties among molecular dynamics (MD) [...] Read more.

Simulations of fluid flows at the nanoscale feature massive data production and machine learning (ML) techniques have been developed during recent years to leverage them, presenting unique results. This work facilitates ML tools to provide an insight on properties among molecular dynamics (MD) simulations, covering missing data points and predicting states not previously located by the simulation. Taking the fluid flow of a simple Lennard-Jones liquid in nanoscale slits as a basis, ML regression-based algorithms are exploited to provide an alternative for the calculation of transport properties of fluids, e.g., the diffusion coefficient, shear viscosity and thermal conductivity and the average velocity across the nanochannels. Through appropriate training and testing, ML-predicted values can be extracted for various input variables, such as the geometrical characteristics of the slits, the interaction parameters between particles and the flow driving force. The proposed technique could act in parallel to simulation as a means of enriching the database of material properties, assisting in coupling between scales, and accelerating data-based scientific computations. Full article

(This article belongs to the Special Issue Fluid Flows at the Nanoscale)

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11 pages, 1697 KB

Open AccessEditor’s ChoiceArticle

Velocity Profile and Turbulence Structure Measurement Corrections for Sediment Transport-Induced Water-Worked Bed

by Jaan H. Pu

Fluids 2021, 6(2), 86; https://doi.org/10.3390/fluids6020086 - 16 Feb 2021

Cited by 43 | Viewed by 5064

Abstract

When using point measurement for environmental or sediment laden flows, there is well-recognised risk for not having aligned measurements that causes misinterpretation of the measured velocity data. In reality, these kinds of mismeasurement mainly happen due to the misinterpretation of bed orientation caused [...] Read more.

When using point measurement for environmental or sediment laden flows, there is well-recognised risk for not having aligned measurements that causes misinterpretation of the measured velocity data. In reality, these kinds of mismeasurement mainly happen due to the misinterpretation of bed orientation caused by the complexity of its determination in natural flows, especially in bedload laden or rough bed flows. This study proposes a novel bed realignment method to improve the measured data benchmarking by three-dimensional (3D) bed profile orientation and implemented it into different sets of experimental data. More specifically, the effects of realignment on velocity profile and streamwise turbulence structure measurements were investigated. The proposed technique was tested against experimental data collected over a water-worked and an experimentally arranged well-packed beds. Different from the well-packed rough bed, the water-worked bed has been generated after long sediment transport and settling and hence can be used to verify the proposed bed-alignment technique thoroughly. During the flow analysis, the corrected velocity, turbulence intensity and Reynolds stress profiles were compared to the theoretical logarithmic law, exponential law and linear gravity (universal Reynolds stress distribution) profiles, respectively. It has been observed that the proposed method has improved the agreement of the measured velocity and turbulence structure data with their actual theoretical profiles, particularly in the near-bed region (where the ratio of the flow measurement vertical distance to the total water depth, z/h, is limited to ≤0.4). Full article

(This article belongs to the Special Issue Environmental Sediment Transport: Methods and Applications)

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15 pages, 4818 KB

Open AccessEditor’s ChoiceArticle

Time-Periodic Cooling of Rayleigh–Bénard Convection

by Lyes Nasseri, Nabil Himrane, Djamel Eddine Ameziani, Abderrahmane Bourada and Rachid Bennacer

Fluids 2021, 6(2), 87; https://doi.org/10.3390/fluids6020087 - 16 Feb 2021

Cited by 6 | Viewed by 4214

Abstract

The problem of Rayleigh–Bénard’s natural convection subjected to a temporally periodic cooling condition is solved numerically by the Lattice Boltzmann method with multiple relaxation time (LBM-MRT). The study finds its interest in the field of thermal comfort where current knowledge has gaps in [...] Read more.

The problem of Rayleigh–Bénard’s natural convection subjected to a temporally periodic cooling condition is solved numerically by the Lattice Boltzmann method with multiple relaxation time (LBM-MRT). The study finds its interest in the field of thermal comfort where current knowledge has gaps in the fundamental phenomena requiring their exploration. The Boussinesq approximation is considered in the resolution of the physical problem studied for a Rayleigh number taken in the range 10³ ≤ Ra ≤ 10⁶ with a Prandtl number equal to 0.71 (air as working fluid). The physical phenomenon is also controlled by the amplitude of periodic cooling where, for small values of the latter, the results obtained follow a periodic evolution around an average corresponding to the formulation at a constant cold temperature. When the heating amplitude increases, the physical phenomenon is disturbed, the stream functions become mainly multicellular and an aperiodic evolution is obtained for the heat transfer illustrated by the average Nusselt number. Full article

(This article belongs to the Special Issue Thermal Flows)

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16 pages, 8028 KB

Open AccessEditor’s ChoiceArticle

Gas–Liquid Mass Transfer around a Rising Bubble: Combined Effect of Rheology and Surfactant

by Gaelle Lebrun, Feishi Xu, Claude Le Men, Gilles Hébrard and Nicolas Dietrich

Fluids 2021, 6(2), 84; https://doi.org/10.3390/fluids6020084 - 15 Feb 2021

Cited by 21 | Viewed by 6952

Abstract

The influence of viscosity and surface tension on oxygen transfer was investigated using planar laser-induced fluorescence with inhibition (PLIF-I). The surface tension and the viscosity were modified using Triton X-100 and polyacrylamide, respectively. Changes in the hydrodynamic parameters of millimetric bubbles were identified, [...] Read more.

The influence of viscosity and surface tension on oxygen transfer was investigated using planar laser-induced fluorescence with inhibition (PLIF-I). The surface tension and the viscosity were modified using Triton X-100 and polyacrylamide, respectively. Changes in the hydrodynamic parameters of millimetric bubbles were identified, and transfer parameters were calculated. The results revealed a decrease in the mass transferred in the presence of a contaminant. For modified viscosity, the decrease in mass transferred was allowed for by current correlations, but the presence of surfactant led to a sharp decrease in the liquid side mass transfer coefficient, which became even lower when polymer was added. An explanation for the gap between classical correlations and experimental values of k_L is discussed, and a hypothesis of the existence of an accumulation of contaminant in the diffusion layer is proposed. This led to the possibility of a decrease in the diffusion coefficient and oxygen saturation concentration in the liquid film, explaining the discrepancy between models and experience. Adapted values of D_O2 and [O₂] * in this layer were estimated. This original study unravels the complexity of mass transfer from an air bubble in a complex medium. Full article

(This article belongs to the Special Issue Flow and Heat Transfer Intensification in Chemical Engineering)

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