Journal Description
Fluids
Fluids
is an international, peer-reviewed, open access journal on all aspects of fluids. It is published monthly online by MDPI. The Portuguese Society of Rheology (SPR) is affiliated with Fluids and the society members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: CiteScore - Q2 (Mechanical Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.6 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the first half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
1.9 (2022);
5-Year Impact Factor:
1.8 (2022)
Latest Articles
Efficient Scale-Resolving Simulations of Open Cavity Flows for Straight and Sideslip Conditions
Fluids 2023, 8(8), 227; https://doi.org/10.3390/fluids8080227 - 08 Aug 2023
Abstract
This study aims to facilitate a physical understanding of resonating cavity flows with efficient numerical treatments of turbulence. It reinforces the efficiency and affordability of scale-adaptive numerical techniques for simulating open cavity flows with a separated shear layer consisting of a wide range
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This study aims to facilitate a physical understanding of resonating cavity flows with efficient numerical treatments of turbulence. It reinforces the efficiency and affordability of scale-adaptive numerical techniques for simulating open cavity flows with a separated shear layer consisting of a wide range of flow scales. Visualization of the resonant modes occurring due to the acoustic feedback loop aids in a better understanding of large-scale flow oscillations. Under this scope, scale-adaptive simulation (SAS) based on the k- SST RANS model with different turbulence treatments has been studied for an open cavity configuration with a length-to-depth ratio of featuring Mach number ( ) and Reynolds number ( ) . It is shown that the essential cavity flow physics has been captured using the SAS approach with more than improved computational efficiency compared to commonly used hybrid RANS-LES approaches. In addition, wall-modeled SAS when supplemented with an artificial forcing concept to trigger the model provides very good spectral estimates comparable with hybrid RANS-LES results. Following the validation of numerical approaches, the directional dependence of the cavity resonance is investigated under asymmetric flow conditions, and spanwise interference of waves due to the lateral walls of the cavity has been observed.
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(This article belongs to the Special Issue Recent Advances in Aerodynamics and Aeroacoustics: Towards Greener Aviation)
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Rapid Hydrate Formation Conditions Prediction in Acid Gas Streams
Fluids 2023, 8(8), 226; https://doi.org/10.3390/fluids8080226 - 05 Aug 2023
Abstract
Sour gas in hydrocarbon reservoirs contains significant amounts of H2S and smaller amounts of CO2. To minimize operational costs, meet air emission standards and increase oil recovery, operators revert to acid gas (re-)injection into the reservoir rather than treating
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Sour gas in hydrocarbon reservoirs contains significant amounts of H2S and smaller amounts of CO2. To minimize operational costs, meet air emission standards and increase oil recovery, operators revert to acid gas (re-)injection into the reservoir rather than treating H2S in Claus units. This process requires the pressurization of the acid gas, which, when combined with low-temperature conditions prevailing in subsurface pipelines, often leads to the formation of hydrates that can potentially block the fluid flow. Therefore, hydrates formation must be checked at each pipeline segment and for each timestep during a flow simulation, for any varying composition, pressure and temperature, leading to millions of calculations that become more intense when transience is considered. Such calculations are time-consuming as they incorporate the van der Walls–Platteeuw and Langmuir adsorption theory, combined with complex EoS models to account for the polarity of the fluid phases (water, inhibitors). The formation pressure is obtained by solving an iterative multiphase equilibrium problem, which takes a considerable amount of CPU time only to provide a binary answer (hydrates/no hydrates). To accelerate such calculations, a set of classifiers is developed to answer whether the prevailing conditions lie to the left (hydrates) or the right-hand (no hydrates) side of the P-T phase envelope. Results are provided in a fast, direct, non-iterative way, for any possible conditions. A set of hydrate formation “yes/no” points, generated offline using conventional approaches, are utilized for the classifier’s training. The model is applicable to any acid gas flow problem and for any prevailing conditions to eliminate the CPU time of multiphase equilibrium calculations.
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(This article belongs to the Special Issue Multiphase Flow and Granular Mechanics)
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The Emptying of a Perforated Bottle: Influence of Perforation Size on Emptying Time and the Physical Nature of the Process
Fluids 2023, 8(8), 225; https://doi.org/10.3390/fluids8080225 - 04 Aug 2023
Abstract
An inverted bottle empties in a time through a process called “glugging”, whereby gas and liquid compete at the neck (of diameter ). In contrast, an open-top container empties in a much shorter time through
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An inverted bottle empties in a time through a process called “glugging”, whereby gas and liquid compete at the neck (of diameter ). In contrast, an open-top container empties in a much shorter time through “jetting” due to the lack of gas–liquid competition. Experiments and theory demonstrate that, by introducing a perforation (diameter ), a bottle empties through glugging, jetting, or a combination of the two. For a certain range of , the perforation increases the emptying time, and a particular value of is associated with a maximum emptying time . We show that the transition from jetting to glugging is initiated by the jet velocity reaching a low threshold, thereby allowing a slug of air entry into the neck that stops jetting and starts the glugging. Once initiated, the glugging proceeds as though there is no perforation. Experimental results covered a range of Eötvös numbers from Eo∼ 20–200 (equivalent to a range of 4–15, where is the capillary length). The phenomenon of bottle emptying with a perforation adds to the body of bottle literature, which has already considered the influence of shape, inclination, liquid properties, etc.
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(This article belongs to the Special Issue Advances in Multiphase Flow Science and Technology, 2nd Edition)
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Wavelet Transforms and Machine Learning Methods for the Study of Turbulence
Fluids 2023, 8(8), 224; https://doi.org/10.3390/fluids8080224 - 03 Aug 2023
Abstract
This article investigates the applications of wavelet transforms and machine learning methods in studying turbulent flows. The wavelet-based hierarchical eddy-capturing framework is built upon first principle physical models. Specifically, the coherent vortex simulation method is based on the Taylor hypothesis, which suggests that
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This article investigates the applications of wavelet transforms and machine learning methods in studying turbulent flows. The wavelet-based hierarchical eddy-capturing framework is built upon first principle physical models. Specifically, the coherent vortex simulation method is based on the Taylor hypothesis, which suggests that the energy cascade occurs through vortex stretching. In contrast, the adaptive wavelet collocation method relies on the Richardson hypothesis, where the self-amplification of the strain field and a hierarchical breakdown of large eddies drive the energy cascade. Wavelet transforms are computational learning architectures that propagate the input data across a sequence of linear operators to learn the underlying nonlinearity and coherent structure. Machine learning offers a wealth of data-driven algorithms that can heavily use statistical concepts to extract valuable insights into turbulent flows. Supervised machine learning needs “perfect” turbulent flow data to train data-driven turbulence models. The current advancement of artificial intelligence in turbulence modeling primarily focuses on accelerating turbulent flow simulations by learning the underlying coherence over a low-dimensional manifold. Physics-informed neural networks offer a fertile ground for augmenting first principle physics to automate specific learning tasks, e.g., via wavelet transforms. Besides machine learning, there is room for developing a common computational framework to provide a rich cross-fertilization between learning the data coherence and the first principles of multiscale physics.
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(This article belongs to the Special Issue Wavelets and Fluids)
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Trapped Solitary Waves in a Periodic External Force: A Numerical Investigation Using the Whitham Equation and the Sponge Layer Method
Fluids 2023, 8(8), 223; https://doi.org/10.3390/fluids8080223 - 01 Aug 2023
Abstract
This paper concerns the interaction between solitary waves on the surface of an ideal fluid and a localized external force, which models a moving disturbance on the free surface or an obstacle moving at the bottom of a channel. Previous works have investigated
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This paper concerns the interaction between solitary waves on the surface of an ideal fluid and a localized external force, which models a moving disturbance on the free surface or an obstacle moving at the bottom of a channel. Previous works have investigated this interaction under the assumption that the external force moves with variable speed and constant acceleration. However, in this paper we adopt a different approach and consider the scenario in which the external force moves with variable speed and non-constant acceleration. Using the Whitham equation framework, we investigate numerically trapped waves excited by a periodic external force. Our experiments reveal regimes in which solitary waves are spontaneously generated and trapped for large times at the external force. In addition, we compare the results predicted by the Whitham equation with those of the Korteweg–de Vries equation.
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(This article belongs to the Section Mathematical and Computational Fluid Mechanics)
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Numerical Assessment of Flow Energy Harvesting Potential in a Micro-Channel
Fluids 2023, 8(8), 222; https://doi.org/10.3390/fluids8080222 - 30 Jul 2023
Abstract
A micro-energy harvesting device proposed in the literature was numerically studied. It consists of two bluff bodies in a micro-channel and a flexible diaphragm at its upper wall. Vortex shedding behind bodies induces pressure fluctuation causing vibration of the diaphragm that converts mechanical
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A micro-energy harvesting device proposed in the literature was numerically studied. It consists of two bluff bodies in a micro-channel and a flexible diaphragm at its upper wall. Vortex shedding behind bodies induces pressure fluctuation causing vibration of the diaphragm that converts mechanical energy to electrical by means of a piezoelectric membrane. Research on enhancing vortex shedding was justified due to the low power output of the device. The amplitude and frequency of the unsteady pressure fluctuation on the diaphragm were numerically predicted. The vortex shedding severity was mainly assessed in terms of pressure amplitude. The CFD model set-up was described in detail, and appropriate metrics to assess the energy harvesting potential were defined. Several 2D cases were simulated to study the effect of the inlet Reynolds number and channel blockage ratio on the prospective performance of the device. Furthermore, the critical blockage ratio leading to the vortex shedding suppression was sought. A higher inlet velocity for a constant blockage ratio was found to enhance vortex shedding and the pressure drop. Great blockage ratio values but lower than the critical ones seemed to provide great pressure amplitudes at the expense of a moderate pressure drop. There is evidence that the field is fruitful for further research and relevant directions were provided.
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(This article belongs to the Section Mathematical and Computational Fluid Mechanics)
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Numerical Evaluation of the Flow within a Rhomboid Tessellated Pipe Network with a 3 × 3 Allometric Branch Pattern for the Inlet and Outlet
by
, , , and
Fluids 2023, 8(8), 221; https://doi.org/10.3390/fluids8080221 - 30 Jul 2023
Abstract
This study presents a comprehensive assessment of the hydrodynamic performance of a novel pipe network with tessellated geometry and allometric scales. Numerical simulations were used to evaluate flow behaviour and pressure drop. The comparison geometry featured a Parallel Pipe Pattern (PPP), while the
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This study presents a comprehensive assessment of the hydrodynamic performance of a novel pipe network with tessellated geometry and allometric scales. Numerical simulations were used to evaluate flow behaviour and pressure drop. The comparison geometry featured a Parallel Pipe Pattern (PPP), while the proposed design employed a Rhombic Tessellation Pattern (RTP). Steady-state simulations were conducted under identical boundary conditions, examining water mass flows ranging from 0.01 to 0.06 kg/s. The results revealed RTP significant advantages over the PPP. The RTP, integrated with a fractal tree pattern, demonstrated remarkable capabilities in achieving uniform flow distribution and maintaining laminar flow regimes across the mass flow rates. Additionally, exhibited an average reduction in pressure drop of 92% resulting in improved efficiency. The Reynolds number at PPP inlet was 5.4 times higher than in the RTP, explaining the considerably higher pressure drop. At a mass flow rate of 0.06 kg/s, the PPP experienced a pressure drop of up to 3.43 kPa, while the RTP’s pressure drop was only 0.350 kPa, highlighting a remarkable decrease of 91.5%. These findings underscore the RTP superior performance in minimizing pressure drop, making it suitable for accommodating higher mass flow rates, thus highlighting its exceptional engineering potential.
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(This article belongs to the Special Issue Pipe Flow: Research and Applications)
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Dynamics of a Laser-Induced Cavitation Bubble near a Cone: An Experimental and Numerical Study
Fluids 2023, 8(8), 220; https://doi.org/10.3390/fluids8080220 - 29 Jul 2023
Abstract
A bubble’s motion is strongly influenced by the boundaries of tip structures, which correspond to the bubble’s size. In the present study, the dynamic behaviors of a cavitation bubble near a conical tip structure are investigated experimentally and numerically. A series of experiments
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A bubble’s motion is strongly influenced by the boundaries of tip structures, which correspond to the bubble’s size. In the present study, the dynamic behaviors of a cavitation bubble near a conical tip structure are investigated experimentally and numerically. A series of experiments were carried out to analyze the bubble’s shape at different relative cone distances quantitatively. Due to the crucial influence of the phase change on the cavitation bubble’s dynamics over multiple cycles, a compressible two-phase model taking into account the phase change and heat transfer implemented in OpenFOAM was employed in this study. The simulation results regarding the bubble’s radius and shape were validated with corresponding experimental photos, and a good agreement was achieved. The bubble’s primary physical features (e.g., shock waves, liquid jets, high-pressure zones) were well reproduced, which helps us understand the underlying mechanisms. Meanwhile, the latent damage was quantified by the pressure load at the cone apex. The effects of the relative distance γ and cone angle θ on the maximum temperature, pressure peaks, and bubble position are discussed and summarized. The results show that the pressure peaks during the bubble’s collapse increase with the decrease in γ. For a larger γ, the first minimum bubble radius increases while the maximum temperature decreases as θ increases; the pressure peak at the second final collapse is first less than that at the first final collapse and then much greater than that one. For a smaller γ, the pressure peaks at different θ values do not vary very much.
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(This article belongs to the Special Issue Numerical Modeling and Experimental Studies of Two-Phase Flows)
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Dynamic Mixed Modeling in Large Eddy Simulation Using the Concept of a Subgrid Activity Sensor
Fluids 2023, 8(8), 219; https://doi.org/10.3390/fluids8080219 - 28 Jul 2023
Abstract
Following the relative success of mixed models in the Large Eddy Simulation of complex turbulent flow configurations, an alternative formulation is suggested here which incorporates the concept of a local subgrid activity sensor. The general idea of mixed models is to combine the
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Following the relative success of mixed models in the Large Eddy Simulation of complex turbulent flow configurations, an alternative formulation is suggested here which incorporates the concept of a local subgrid activity sensor. The general idea of mixed models is to combine the advantages of structural models (superior alignment properties), usually of the scale similarity type, and functional models (superior stability), usually of the eddy viscosity type, while avoiding their disadvantages. However, the key question is the mathematical realization of this combination, and the formulation in this work accounts for the local level of underresolution of the flow. The justification and evaluation of the newly proposed mixed model is based on a priori and a posteriori analysis of homogeneous isotropic turbulence and laminar–turbulent transition in the Taylor–Green vortex, respectively. The suggested model shows a robust and accurate behavior for the cases investigated. In particular, it outperforms the separate structural and functional base models as well as the simulation without an explicit subgrid-scale model.
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(This article belongs to the Collection Feature Paper for Mathematical and Computational Fluid Mechanics)
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Comprehensive Perturbation Approach to Nonlinear Viscous Gravity–Capillary Surface Waves at Arbitrary Wavelengths in Finite Depth
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and
Fluids 2023, 8(8), 218; https://doi.org/10.3390/fluids8080218 - 27 Jul 2023
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This study presents a comprehensive analysis of the second-order perturbation theory applied to the Navier–Stokes equations governing free surface flows. We focus on gravity–capillary surface waves in incompressible viscous fluids of finite depth over a flat bottom. The amplitude of these waves is
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This study presents a comprehensive analysis of the second-order perturbation theory applied to the Navier–Stokes equations governing free surface flows. We focus on gravity–capillary surface waves in incompressible viscous fluids of finite depth over a flat bottom. The amplitude of these waves is regarded as the perturbation parameter. A systematic derivation of a nonlinear-surface-wave equation is presented that fully takes into account dispersion, while nonlinearity is included in the leading order. However, the presence of infinitely many over-damped modes has been neglected and only the two least-damped modes are considered. The new surface-wave equation is formulated in wave-number space rather than real space and nonlinear terms contain convolutions making the equation an integro-differential equation. Some preliminary numerical results are compared with computational-modelling data obtained via open source CFD software OpenFOAM.
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Improving Pump Characteristics through Double Curvature Impellers: Experimental Measurements and 3D CFD Analysis
by
, , , , , and
Fluids 2023, 8(8), 217; https://doi.org/10.3390/fluids8080217 - 27 Jul 2023
Abstract
The outlet angle and shape of impeller blades are important parameters in centrifugal pump design. There is a lack of detailed studies related to double curvature impellers in centrifugal pumps in the current literature; therefore, an experimental and numerical analysis of double curvature
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The outlet angle and shape of impeller blades are important parameters in centrifugal pump design. There is a lack of detailed studies related to double curvature impellers in centrifugal pumps in the current literature; therefore, an experimental and numerical analysis of double curvature impellers was performed. Six impellers were made and then assessed in a centrifugal pump test bed and simulated via 3D CFD simulation. The original impeller was also tested and simulated. One of the manufactured impellers had the same design as the original, and the other five impellers had a double curvature. Laboratory tests and simulations were conducted with three rotation speeds: 1400, 1700, and 1900 RPM. Head and performance curve equations were obtained for the pump–engine unit based on the flow of each impeller for the three rotation speeds. The results showed that a double curvature impeller improved pump head by approximately 1 m for the range of the study and performance by about 2% when compared to basic impeller. On the other hand, it was observed that turbulence models such as k-ε and SST k-ω reproduced similar physical and numerical results.
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(This article belongs to the Special Issue Computational Fluid Dynamics in Fluid Machinery)
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CFD Simulation of SCR Systems Using a Mass-Fraction-Based Impingement Model
Fluids 2023, 8(8), 216; https://doi.org/10.3390/fluids8080216 - 25 Jul 2023
Abstract
Computational fluid dynamics (CFD) are an essential tool for the development of diesel engine aftertreatment systems using selective catalytic reduction (SCR) to reduce nitrous oxides ( ). In urea-based SCR, liquid urea–water solution (UWS) is injected into the hot exhaust gas,
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Computational fluid dynamics (CFD) are an essential tool for the development of diesel engine aftertreatment systems using selective catalytic reduction (SCR) to reduce nitrous oxides ( ). In urea-based SCR, liquid urea–water solution (UWS) is injected into the hot exhaust gas, where it transforms into gaseous ammonia. This ammonia serves as a reducing agent for . CFD simulations are used to predict the ammonia distribution in the exhaust gas at the catalyst inlet. The goal is to achieve the highest possible uniformity to realize homogeneous reduction across the catalyst cross section. The current work focuses on the interaction of UWS droplets with the hot walls of the exhaust system. This is a crucial part of the preparation of gaseous ammonia from the injected liquid UWS. Following experimental investigations, a new impingement model is described based on the superposition of four basic impingement behaviors, each featuring individual secondary droplet characteristics. The droplet–wall heat transfer, depending on surface temperature and impingement behavior, is also calculated using a newly parameterized model. Applying the presented approach, the cooling of a steel plate from intermittent spray impingement is simulated and compared to measurements. The second validation case is the distribution of ammonia at the catalyst inlet of an automotive SCR system. Both applications show good agreement and demonstrate the quality of the new model.
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(This article belongs to the Special Issue Industrial CFD and Fluid Modelling in Engineering)
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An Analysis of CFD-DEM with Coarse Graining for Turbulent Particle-Laden Jet Flows
Fluids 2023, 8(7), 215; https://doi.org/10.3390/fluids8070215 - 22 Jul 2023
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This paper presents the results of simulations of particle-laden air–solid jet flow in long straight tubes using CFD-DEM, along with an analysis of coarse-graining. Although previous studies have used CFD-DEM for similar flows, these have typically been in a dilute flow regime where
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This paper presents the results of simulations of particle-laden air–solid jet flow in long straight tubes using CFD-DEM, along with an analysis of coarse-graining. Although previous studies have used CFD-DEM for similar flows, these have typically been in a dilute flow regime where uncoupled simulations can be used effectively. However, fully coupled simulations can introduce issues, necessitating validation studies to ensure that all coupling parameters are effectively used and that the physics is accurately represented. This paper validated the simulations against two different experimental studies, with fluid Reynolds numbers between 10,000 and 40,000 and Stokes numbers between and 50. Interestingly, the profiles of the mean particle velocity exhibited fewer discrepancies as the Stokes number increased, but more discrepancies for the root-mean-squared velocity compared to the experiments. The particle number flux was consistent with the experiments after the nozzle exit. Coarse-graining was also applied to the same simulations, achieving relatively accurate results. However, as expected, the scaling of contact collision frequencies, forces, and stresses could not be achieved, meaning that coarse-graining may be useful for comparing designs or operating parameters on an industrial scale, but falls short when measuring the total energy dissipation of one experiment.
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(This article belongs to the Topic Computational Fluid Dynamics (CFD) and Its Applications)
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Bulk Cavitation in Model Gasoline Injectors and Their Correlation with the Instantaneous Liquid Flow Field
by
, , , and
Fluids 2023, 8(7), 214; https://doi.org/10.3390/fluids8070214 - 22 Jul 2023
Abstract
It is well established that spray characteristics from automotive injectors depend on, among other factors, whether cavitation arises in the injector nozzle. Bulk cavitation, which refers to the cavitation development distant from walls and thus far from the streamline curvature associated with salient
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It is well established that spray characteristics from automotive injectors depend on, among other factors, whether cavitation arises in the injector nozzle. Bulk cavitation, which refers to the cavitation development distant from walls and thus far from the streamline curvature associated with salient points on a wall, has not been thoroughly investigated experimentally in injector nozzles. Consequently, it is not clear what is causing this phenomenon. The research objective of this study was to visualize cavitation in three different injector models (designated as Type A, Type B, and Type C) and quantify the liquid flow field in relation to the bulk cavitation phenomenon. In all models, bulk cavitation was present. We expected this bulk cavitation to be associated with a swirling flow with its axis parallel to that of the nozzle. However, liquid velocity measurements obtained through particle image velocimetry (PIV) demonstrated the absence of a swirling flow structure in the mean flow field just upstream of the nozzle exit, at a plane normal to the hypothetical axis of the injector. Consequently, we applied proper orthogonal decomposition (POD) to analyze the instantaneous liquid velocity data records in order to capture the dominant coherent structures potentially related to cavitation. It was found that the most energetic mode of the liquid flow field corresponded to the expected instantaneous swirling flow structure when bulk cavitation was present in the flow.
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(This article belongs to the Special Issue Numerical Modeling and Experimental Studies of Two-Phase Flows)
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Simulation of Dynamic Rearrangement Events in Wall-Flow Filters Applying Lattice Boltzmann Methods
Fluids 2023, 8(7), 213; https://doi.org/10.3390/fluids8070213 - 21 Jul 2023
Abstract
Wall-flow filters are applied in the exhaust treatment of internal combustion engines for the removal of particulate matter (PM). Over time, the pressure drop inside those filters increases due to the continuously introduced solid material, which forms PM deposition layers on the filter
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Wall-flow filters are applied in the exhaust treatment of internal combustion engines for the removal of particulate matter (PM). Over time, the pressure drop inside those filters increases due to the continuously introduced solid material, which forms PM deposition layers on the filter substrate. This leads to the necessity of regenerating the filter. During such a regeneration process, fragments of the PM layers can potentially rearrange inside single filter channels. This may lead to the formation of specific deposition patterns, which affect a filter’s pressure drop, its loading capacity and the separation efficiency. The dynamic formation process can still not consistently be attributed to specific influence factors, and appropriate calculation models that enable a quantification of respective factors do not exist. In the present work, the dynamic rearrangement process during the regeneration of a wall-flow filter channel is investigated. As a direct sequel to the investigation of a static deposition layer in a previous work, the present one additionally investigates the dynamic behaviour following the detachment of individual layer fragments as well as the formation of channel plugs. The goal of this work is the extension of the resolved particle methodology used in the previous work via a discrete method to treat particle–particle and particle–wall interactions in order to evaluate the influence of the deposition layer topology, PM properties and operating conditions on dynamic rearrangement events. It can be shown that a simple mean density methodology represents a reproducible way of determining a channel plug’s extent and its average density, which agrees well with values reported in literature. The sensitivities of relevant influence factors are revealed and their impact on the rearrangement process is quantified. This work contributes to the formulation of predictions on the formation of specific deposition patterns, which impact engine performance, fuel consumption and service life of wall-flow filters.
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(This article belongs to the Special Issue Industrial CFD and Fluid Modelling in Engineering)
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Can Artificial Intelligence Accelerate Fluid Mechanics Research?
by
and
Fluids 2023, 8(7), 212; https://doi.org/10.3390/fluids8070212 - 19 Jul 2023
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
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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.
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(This article belongs to the Special Issue Machine Learning and Artificial Intelligence in Fluid Mechanics)
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Experimental Analysis of a Cracked Cardan Shaft System under the Influence of Viscous Hydrodynamic Forces
Fluids 2023, 8(7), 211; https://doi.org/10.3390/fluids8070211 - 18 Jul 2023
Abstract
Accurate prediction of the dynamic behavior of coupled shafts in a fluid medium is crucial to accurately estimate equipment life and enable safe operation. However, this task is far from trivial due to the vibrations induced by the highly nonlinear nature of the
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Accurate prediction of the dynamic behavior of coupled shafts in a fluid medium is crucial to accurately estimate equipment life and enable safe operation. However, this task is far from trivial due to the vibrations induced by the highly nonlinear nature of the machine system. This paper presents an experimental analysis of a cardan shaft under the influence of viscous hydrodynamic forces. An experimental setup was created using a cardan shaft rig installed in a plexiglas tank, with a self-aligned crack simulator supporting the driveshaft for crack extraction. Adequate instrumentation was used to measure the rotor’s fluctuation under industrial viscous fluid at various motor speeds. By analyzing the changes of unwanted high vibration, the obtained results demonstrated that the characteristics of the cracks in the fluid medium can be efficiently extracted from multiple tests using the wavelet synchrosqueezing transform and energy spectrum. This latter aspect, in particular, implies that the responses that can be observed in practice are highly sensitive to the values of the system parameters: average flow velocity, mass eccentricity, and shaft stiffness, among others. Finally, the study provides conclusions on practical applications for the reliable identification of cracks in a viscous fluid to validate the recently published theoretical study.
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(This article belongs to the Special Issue Wavelets and Fluids)
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Mechanical Design and Numerical Analysis of a New Front Wing for a Formula One Vehicle
by
, , , , , , and
Fluids 2023, 8(7), 210; https://doi.org/10.3390/fluids8070210 - 18 Jul 2023
Abstract
In motorsports, the correct design of every device that constitutes a vehicle is a significant task for engineers because the car’s efficiency on the track depends on making it competitive. However, the physical integrity of the pilot is also at stake, since a
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In motorsports, the correct design of every device that constitutes a vehicle is a significant task for engineers because the car’s efficiency on the track depends on making it competitive. However, the physical integrity of the pilot is also at stake, since a bad vehicle design can cause serious mishaps. To achieve the correct development of a front wing for a single-seater vehicle, it is necessary to adequately simulate the forces that are generated on a car to evaluate its performance, which depends on the aerodynamic forces of the front wing that are present due to its geometry. This work provided a new design and evaluation through the numerical analysis of three new front wings for single-seater vehicles that comply with the regulations issued by the International Automobile Federation (FIA) for the 2022 season. Additionally, a 3D-printed front wing prototype was developed to be evaluated in an experimental study to corroborate the results obtained through computer simulations. A wind tunnel experiment test was performed to validate the numerically simulated data. Also, we developed a numerical simulation and characterization of three front wings already used in Formula One from a previous season (the end of the 2021 season). This work defined how these devices perform, and in the same way, it identified how their evolution over time has provided them with substantial benefits and greater efficiency. All the numerical simulations were carried out by applying the Finite Volume Method, allowing us to obtain the values of the aerodynamic forces that act on the front wing. Also, it was possible to establish a comparison between the three newly designed proposals from the most aerodynamic advantages to produce a prototype and perform an experimental test. The results of the experimental test showed similarity to those of the numerical analyses, making it clear that the methodology followed during the development of the work was correct. In addition, the mechanical designs carried out to develop the front wing can be considered ideal, because the results showed that the front wing could be competitive, and applying it caused a downforce to be favored that prevented the car from being thrown off the track. Additionally, the results indicate this is an effective proposal for use in a single-seater vehicle and that the design methodology delivers optimal results.
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(This article belongs to the Topic Computational Fluid Dynamics (CFD) and Its Applications)
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Marangoni Flow Investigation in Foam Fractionation Phenomenon
Fluids 2023, 8(7), 209; https://doi.org/10.3390/fluids8070209 - 18 Jul 2023
Abstract
In this study, a numerical investigation of the Marangoni flow in foam fractionation was conducted, with a specific focus on the film of micro-foams in both the interior and exterior regions. A three-dimensional node–film–plateau border system was employed to model the system, utilizing
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In this study, a numerical investigation of the Marangoni flow in foam fractionation was conducted, with a specific focus on the film of micro-foams in both the interior and exterior regions. A three-dimensional node–film–plateau border system was employed to model the system, utilizing time-dependent mass conservation equations. The study emphasized the influence of the surfactant concentration in the foam fractionation column and the mobility of the air–liquid interface on the Marangoni velocity within the film. The results indicated that higher surfactant concentration in the reflux column resulted in a significant increase in Marangoni velocities. Furthermore, a mobile interface enhanced the Marangoni flow, whereas a rigid interface reduced its intensity. The behaviour of the Marangoni flow was explored in both interior and exterior foams, revealing distinct characteristics. The presence of a wall in the exterior foam altered the flow dynamics, leading to a reduced Marangoni velocity compared to interior films.
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(This article belongs to the Section Mathematical and Computational Fluid Mechanics)
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Parallel Bootstrap-Based On-Policy Deep Reinforcement Learning for Continuous Fluid Flow Control Applications
by
and
Fluids 2023, 8(7), 208; https://doi.org/10.3390/fluids8070208 - 14 Jul 2023
Abstract
The coupling of deep reinforcement learning to numerical flow control problems has recently received considerable attention, leading to groundbreaking results and opening new perspectives for the domain. Due to the usually high computational cost of fluid dynamics solvers, the use of parallel environments
[...] Read more.
The coupling of deep reinforcement learning to numerical flow control problems has recently received considerable attention, leading to groundbreaking results and opening new perspectives for the domain. Due to the usually high computational cost of fluid dynamics solvers, the use of parallel environments during the learning process represents an essential ingredient to attain efficient control in a reasonable time. Yet, most of the deep reinforcement learning literature for flow control relies on on-policy algorithms, for which the massively parallel transition collection may break theoretical assumptions and lead to suboptimal control models. To overcome this issue, we propose a parallelism pattern relying on partial-trajectory buffers terminated by a return bootstrapping step, allowing a flexible use of parallel environments while preserving the on-policiness of the updates. This approach is illustrated on a CPU-intensive continuous flow control problem from the literature.
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(This article belongs to the Section Mathematical and Computational Fluid Mechanics)
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