Fluid Flow Applications Research Articles

Couette flow of micropolar fluid in a channel filled with anisotropic porous medium

This paper presents a mathematical model for the flow of micropolar fluid in a horizontal channel filled with an anisotropic porous medium, bounded by two parallel plates—where the upper plate is stationary, and the lower plate moves at a constant velocity. The flow, driven by both a constant pressure gradient and the movement of the lower plate, is governed by the Darcy-Brinkman equation. Using no-slip and no-spin boundary conditions, we analytically derive expressions for the velocity, microrotational velocity, and stress distributions. The study provides a graphical analysis of the flow behavior influenced by key parameters such as the Darcy number, porous medium anisotropy, anisotropy angle, and the micropolar fluid’s material parameters. Furthermore, the effects of the material parameters and Darcy number on shear stress and couple stress are thoroughly investigated. The findings have applications in modeling fluid flow in striated or fractured rock formations.

Solving the Hele–Shaw flow using the Harrow–Hassidim–Lloyd algorithm on superconducting devices: A study of efficiency and challenges

The development of quantum processors for practical fluid flow problems is a promising yet distant goal. Recent advances in quantum linear solvers have highlighted their potential for classical fluid dynamics. In this study, we evaluate the Harrow–Hassidim–Lloyd (HHL) quantum linear systems algorithm (QLSA) for solving the idealized Hele–Shaw flow. Our focus is on the accuracy and computational cost of the HHL solver, which we find to be sensitive to the condition number, scaling exponentially with problem size. This emphasizes the need for preconditioning to enhance the practical use of QLSAs in fluid flow applications. Moreover, we perform shots-based simulations on quantum simulators and test the HHL solver on superconducting quantum devices, where noise, large circuit depths, and gate errors limit performance. Error suppression and mitigation techniques improve accuracy, suggesting that such fluid flow problems can benchmark noise mitigation efforts. Our findings provide a foundation for future, more complex application of QLSAs in fluid flow simulations.

Numerical investigation of unsteady MHD immiscible Casson micropolar and Jeffery fluid in a horizontal channel with heat transfer using MCB-DQM approach

The dynamics of immiscible Casson micropolar and Jeffery fluid flow offer new possibilities for enhancing momentum and heat transfer efficiencies. Motivated by numerous applications of immiscible fluid flows in natural and industrial systems, the current work presents a numerical investigation of unsteady, incompressible, magnetohydrodynamic (MHD) flow involving two immiscible fluids, namely, Casson micropolar and Jeffery fluid, in a horizontal channel. The flow, driven by a uniform pressure gradient, assumes no-slip conditions at the channel walls and a continuous, nondeformable interface between the immiscible fluids. The well-established rapid converging modified cubic B-spline differential quadrature method (MCB-DQM) is applied to solve the partial differential equations governing the flow. The impact of crucial fluid parameters comprising the Casson micropolar fluid parameter, Jeffery fluid parameter, thermal, magnetic, and various other fluid parameters on temperature, microrotation, and velocity profile is illustrated graphically. Notably, the parameters of each fluid influence the profiles in both fluid zones. The flow dynamics are significantly affected by viscous dissipation, Lorentz force, fluid–wall interactions, and interfacial conditions. Key parameters such as time, Jeffery fluid, Casson micropolar, ion slip and Hall parameters, Reynolds number, Eckert number, the ratio of viscosities, the ratio of densities, and pressure gradient show significant impacts on the velocity, microrotation, and temperature profiles. However, reverse or mixed behavior is observed for other parameters. The novelty of current work lies in modeling the unsteady, immiscible, MHD flow of Casson micropolar and Jeffery fluid and proposing a numerical solution by deploying the MCB-DQM method. The findings have potential applications in various industrial and engineering processes, such as the design of oil extraction, optimizing processes in the food processing and cosmetics industry, and developing effective strategies for environment conservation.

Prediction of Flow Properties of Porous Triply Periodic Minimal Surface (TPMS) Structures

The flow through geometrically complex structures is an important engineering problem. In this work, the laminar flow through Triply Periodic Minimal Surface (TPMS) structures is numerically analyzed using Computational Fluid Dynamics (CFD) simulations. Two different TPMS structures were designed, and their porosity was characterized as a function of the isovalue. Then, CFD simulations were implemented to compute the pressure drop by systematically varying the flow velocity and the porosity of the structure. A Darcy–Forchheimer model was fitted to CFD results to calculate the inertial and permeability coefficients as functions of the porosity. These types of results can be very useful for designing fluid flow applications and devices (for instance, heat exchangers), as well as for integrating these TPMS structures since the flow can be very well estimated when using the porous medium model.

A novel perfusion bioreactor promotes the expansion of pluripotent stem cells in a 3D-bioprinted tissue chamber

While the field of tissue engineering has progressed rapidly with the advent of 3D bioprinting and human induced pluripotent stem cells (hiPSCs), impact is limited by a lack of functional, thick tissues. One way around this limitation is to 3D bioprint tissues laden with hiPSCs. In this way, the iPSCs can proliferate to populate the thick tissue mass prior to parenchymal cell specification. Here we design a perfusion bioreactor for an hiPSC-laden, 3D-bioprinted chamber with the goal of proliferating the hiPSCs throughout the structure prior to differentiation to generate a thick tissue model. The bioreactor, fabricated with digital light projection, was optimized to perfuse the interior of the hydrogel chamber without leaks and to provide fluid flow around the exterior as well, maximizing nutrient delivery throughout the chamber wall. After 7 days of culture, we found that intermittent perfusion (15 s every 15 min) at 3 ml min−1 provides a 1.9-fold increase in the density of stem cell colonies in the engineered tissue relative to analogous chambers cultured under static conditions. We also observed a more uniform distribution of colonies within the tissue wall of perfused structures relative to static controls, reflecting a homogeneous distribution of nutrients from the culture media. hiPSCs remained pluripotent and proliferative with application of fluid flow, which generated wall shear stresses averaging ∼1.0 dyn cm−2. Overall, these promising outcomes following perfusion of a stem cell-laden hydrogel support the production of multiple tissue types with improved thickness, and therefore increased function and utility.

Multiscale graph neural network autoencoders for interpretable scientific machine learning

The goal of this work is to address two limitations in autoencoder-based models: latent space interpretability and compatibility with unstructured meshes. This is accomplished here with the development of a novel graph neural network (GNN) autoencoding architecture with demonstrations on complex fluid flow applications. To address the first goal of interpretability, the GNN autoencoder achieves reduction in the number nodes in the encoding stage through an adaptive graph reduction procedure. This reduction procedure essentially amounts to flowfield-conditioned node sampling and sensor identification, and produces interpretable latent graph representations tailored to the flowfield reconstruction task in the form of so-called masked fields. These masked fields allow the user to (a) visualize where in physical space a given latent graph is active, and (b) interpret the time-evolution of the latent graph connectivity in accordance with the time-evolution of unsteady flow features (e.g. recirculation zones, shear layers) in the domain. To address the goal of unstructured mesh compatibility, the autoencoding architecture utilizes a series of multi-scale message passing (MMP) layers, each of which models information exchange among node neighborhoods at various lengthscales. The MMP layer, which augments standard single-scale message passing with learnable coarsening operations, allows the decoder to more efficiently reconstruct the flowfield from the identified regions in the masked fields. Analysis of latent graphs produced by the autoencoder for various model settings are conducted using unstructured snapshot data sourced from large-eddy simulations in a backward-facing step (BFS) flow configuration with an OpenFOAM-based flow solver at high Reynolds numbers.

Optimisation of pipes with constant diameter using the heuristic optimality criterion

Background: Minimising internal pressure drop in pipes is crucial for energy efficiency of fluid flow applications. Numerous computational optimisation tools that are capable of modifying flow geometries to reduce the pressure drop have been developed. Among these is a comparably simple heuristic optimisation algorithm which mimics erosion and sedimentation processes based on the shear stress in the vicinity of the domain boundaries. Although this method succeeds in modifying flow geometries for reduced pressure drop, it allows the fluid domain to widen during the reshaping process. Therefore, a reported reduction of pressure drop is not only caused by an improvement of the flow path, but also by an increase in the domain width. However, pipes with a constant circular diameter are favoured in many applications because they can be easily manufactured. Methods: Here we combine the heuristic optimisation approach with a new geometrical constraint that kept the average diameter constant. This way, a reduction of pressure drop caused solely by the modification of the flow path can be assessed. We determined the applicability of the modified algorithm for 2D channel and 3D pipe geometries, conducting numerical simulations using the Lattice Boltzmann method with Reynolds numbers ranging from 40 to 500. Results: For all investigated cases, potentially optimal shapes could be derived at all tested Reynolds numbers. However, the shape originally derived at a simulated flow with Re = 40 yielded a smaller pressure drop even for flows at Re ≥ 100 than shapes derived specifically at these higher Reynolds numbers. Conclusions: This observed trend should be kept in mind when employing this approach as a simple way to improve channel and pipe layouts.

Fluid flow shear stress and tissue remodeling-an orthodontic perspective: evidence synthesis and differential gene expression network analysis.

Introduction: This study aimed to identify and analyze in vitro studies investigating the biological effect of fluid-flow shear stress (FSS) on cells found in the periodontal ligament and bone tissue. Method: We followed the PRISMA guideline for systematic reviews. A PubMed search strategy was developed, studies were selected according to predefined eligibility criteria, and the risk of bias was assessed. Relevant data related to cell source, applied FSS, and locus-specific expression were extracted. Based on this evidence synthesis and, as an original part of this work, analysis of differential gene expression using over-representation and network-analysis was performed. Five relevant publicly available gene expression datasets were analyzed using gene set enrichment analysis (GSEA). Result: A total of 6,974 articles were identified. Titles and abstracts were screened, and 218 articles were selected for full-text assessment. Finally, 120 articles were included in this study. Sample size determination and statistical analysis related to methodological quality and the ethical statement item in reporting quality were most frequently identified as high risk of bias. The analyzed studies mostly used custom-made fluid-flow apparatuses (61.7%). FSS was most frequently applied for 0.5h, 1h, or 2h, whereas FSS magnitudes ranged from 6 to 20dyn/cm2 depending on cell type and flow profile. Fluid-flow frequencies of 1Hz in human cells and 1 and 5Hz in mouse cells were mostly applied. FSS upregulated genes/metabolites responsible for tissue formation (AKT1, alkaline phosphatase, BGLAP, BMP2, Ca2+, COL1A1, CTNNB1, GJA1, MAPK1/MAPK3, PDPN, RUNX2, SPP1, TNFRSF11B, VEGFA, WNT3A) and inflammation (nitric oxide, PGE-2, PGI-2, PTGS1, PTGS2). Protein-protein interaction networks were constructed and analyzed using over-representation analysis and GSEA to identify shared signaling pathways. Conclusion: To our knowledge, this is the first review giving a comprehensive overview and discussion of methodological technical details regarding fluid flow application in 2D cell culture in vitro experimental conditions. Therefore, it is not only providing valuable information about cellular molecular events and their quantitative and qualitative analysis, but also confirming the reproducibility of previously published results.

A Review of Fluid Flow Applications and Hydraulic Performance of Sustainable Drip Irrigation to Improve Water Resource Management

Fluid flow applications to improve water resource management towards sustainable irrigation are one of the main targets of engineers nowadays, especially with global climate change. The performance assessment of the irrigation system is an important area of research to improve water resource management. Through drip irrigation systems, this review evaluated the application uniformity of water and nutrients to sustain agricultural production and protect the environment’s natural resources. To achieve these goals, the adequate use of nutrients and water must be emphasized by utilizing sufficient water and nutrient management approaches, including a drip irrigation system that supplies the inputs immediately to the crop’s root zone. The process operating pressure and the drip line length are the two most crucial aspects that affect the uniformity of the water and nutrient distribution in fields. Inconsistent or inadequate applications of fertilizers and water in the fields contribute to the incorrect supply of useful water and nutrients in the soil profile along the drip line length resulting in a significant decrease in crop yields and poor product quality. The main cause behind the operating pressures in a “micro-irrigation system” is the inadequate distribution of fertilizers and water in the fields. Therefore, the effects of such non-uniform distribution must be carefully quantified and studied to understand the reasons behind soil degradation and groundwater contamination, which occurs due to excess nutrient leaching from the crop’s root zone. Data on the distribution and movement of water and nutrients in the soil is essential for designing efficient fertilization systems. Drip irrigation can reduce water exposure and input costs, making agribusiness more resilient, profitable, and successful. This paper discusses the uniformity of the nutrients and water application for crops grown in various agro-climatic regions. In addition, an effort was made to compare the findings’ quality of various commonly used methods of water and nutrient application under different climatic conditions.

S-CO2 flow in vertical tubes of large-diameter: Experimental evaluation and numerical exploration for heat transfer deterioration and prevention

Heat transfer deterioration (HTD) problems can undermine the thermal safety of heating tubes for supercritical carbon dioxide (S-CO2) flows. Relevant experimental evidence is highly desired, but most cases were investigated for small tube diameters (below 10 mm) and under limited operation parameters, far from the industry-scale applications. In the present work, large tubes (24 mm) are investigated experimentally with pressures of 7.5–15 MPa, mass flow rates of 100–1200 kg·m−2·s−1 and heat fluxes of 30–350 kW·m−2. The seriousness of HTD in large tubes was experimentally confirmed, and the mechanism is explored via a carefully-designed comprehensive comparison between present numerical simulations and experimental tests. Detailed analysis of vapor-like film development inspires us to mitigate the problem using structured-inner-surface, from the viewpoint of “supercritical pseudo-boiling”. This inspiration is further evaluated numerically: five types of enhancement structures are proposed to interfere with the development of vapor-like film. It was found that the proposed methods can fully prevent HTD problems, and especially the conical strips can achieve a high heat transfer performance (with performance evaluation criteria PEC of 1.21–1.35) and are thus recommended for HTD prevention in vertical large-diameter tubes under near-critical conditions. Overall, the experimental tests and numerical explorations can deliver more evidence on the theory and applications of supercritical fluid flow and heat transfer.

Imposing slip conditions on curved boundaries for 3D incompressible flows with a very high-order accurate finite volume scheme on polygonal meshes

The conventional no-slip boundary condition does not always hold in several fluid flow applications and must be replaced with appropriate slip conditions according to the wall and fluid properties. However, not only slip boundary conditions are still a subject of discussion among fluid dynamicists, but also their numerical treatment is far from being well-developed, particularly in the context of very high-order accurate methods. The complexity of these conditions significantly increases when the boundary is not aligned with the chosen coordinate system and, even more challenging, when the fluid slips along a curved boundary. The present work proposes a simple and efficient numerical treatment of general slip boundary conditions on arbitrary curved boundaries for three-dimensional fluid flow problems governed by the incompressible Navier–Stokes equations. In that regard, two critical challenges arise: (i) achieving very high-order of convergence with arbitrary curved boundaries for the classical no-slip boundary conditions and (ii) extending the developed numerical techniques to impose general slip boundary conditions. The conventional treatment of curved boundaries relies on generating curved meshes to eliminate the geometrical mismatch between the physical and computational boundaries and achieve high-order of convergence. However, such an approach requires sophisticated meshing algorithms, cumbersome quadrature rules on curved elements, and complex non-linear transformations. In contrast, the reconstruction for off-site data (ROD) method handles arbitrary curved boundaries approximated with linear piecewise elements while employing polynomial reconstructions with specific linear constraints to fulfil the prescribed boundary conditions. For that purpose, the general slip boundary conditions are reformulated on a local orthonormal basis to allow a straightforward application of the ROD method with scalar boundary conditions. The Navier–Stokes equations are discretised with a staggered finite volume method, and the numerical fluxes are computed solely on the polygonal mesh elements. Several benchmark test cases of fluid flow problems in non-trivial three-dimensional curved domains are addressed and confirm that the proposed method effectively achieves up to the eighth-order of convergence.

Super-resolution analysis via machine learning: a survey for fluid flows

This paper surveys machine-learning-based super-resolution reconstruction for vortical flows. Super resolution aims to find the high-resolution flow fields from low-resolution data and is generally an approach used in image reconstruction. In addition to surveying a variety of recent super-resolution applications, we provide case studies of super-resolution analysis for an example of two-dimensional decaying isotropic turbulence. We demonstrate that physics-inspired model designs enable successful reconstruction of vortical flows from spatially limited measurements. We also discuss the challenges and outlooks of machine-learning-based super-resolution analysis for fluid flow applications. The insights gained from this study can be leveraged for super-resolution analysis of numerical and experimental flow data.Graphical abstract

Electroosmosis-driven heat transfer in Jeffrey fluid flow through tapered porous channel

The present research offers a physical explanation for the intricate movement in porous media. It details the electroosmotic factors that drive momentum transmission and regulate the mixing process, as well as the flow and thermal properties such as velocity, flow rate, streamlines, pressure, and temperature. This model is founded on an investigation of non-Newtonian fluid flow by electroosmosis in a tapering duct influenced by porosity. Modeling the momentum, continuity, and heat equations involves combining Gauss’s law, the Poisson equation, Darcy’s resistance, and the Jeffrey model equation. To recommend a physical interpretation, exact solutions are calculated for partial differential equations. Examining the controlling parameters enables the identification of the appropriate fluctuations in the temperature field, velocity field, and pressure gradient. The governing equations are solved using approximations for low Reynold number, long wavelength, and Debye–Huckel linearization. For the purpose of demonstrating thermal analysis, contours are utilized to discuss the entrapment process and temperature profile fluctuations caused by various factors. In addition, a comparison is made between electroosmotic flow in uniform and nonuniform channels for intrauterine fluid flow and other industrial applications, such as the transmission of industrial fluids under complex regimes for a variety of thermal systems.

A Review of Practical Applications of Fluid Flow and Associated Heat Transfer Modeling in Wellbores

Investigations on two-phase gas/liquid flow in pipes have been under study for nearly six decades. These studies have significantly assisted in managing fluid flow in the wellbore and surface networks, leading to the separation of phases and transmission of oil and gas into the market. This study summarizes some of the main lessons learned in flow through wellbores. Besides understanding some of the fundamental principles, we focused on the practical items of interest: Conventional production scenarios for oil and gas wells; Liquid loading in gas wells; Production in geothermal wells; Heat flow from fluid flow; Transient non-isothermal wellbore modeling; Well blowout in drilling operation; Estimating static geothermal and flowing-temperature gradients in gas wells; Heat mining with fluid circulation in wellbores. Given the diversity of the methods mentioned above, understanding flows in the wellbore and the reservoir becomes equally important. One critical item is the fluid temperature measurement associated with the fluid flow that enables validation of the fluid flow rate, besides revealing information about the reservoir characteristics.

Investigation of fluid flow pattern in a 3D meandering tube

Several types of meandering channels and their mathematical simulation have been proposed and discussed widely in the open literature. In the present study, the impact of a novel meandering tube geometry on streamwise vortices and pressure losses have been determined. Using a simplified Poiseuille flow simulation approach with a sinusoidal wavy meandering tube of non-uniform radius, the onset flow separation, vertex formation, and the impact of Reynolds number on field variables and stream function has been analyzed. Moreover, the linear stability theory has been implemented to trace the vertex formation. A decrease in wavelength leads to flow separation near the tube’s surface, but the flow becomes rectilinear with a sudden disturbance caused by the meander, becoming independent of vertex generating centrifugal forces. Novel insights are provided on the impact of meandering tube geometry on fluid flow and potential applications for enhancing flow conditions are suggested.

Characterization of three-dimensional bone-like tissue growth and organization under influence of directional fluid flow.

The transition in the field of bone tissue engineering from bone regeneration to in vitro models has come with the challenge of recreating a dense and anisotropic bone-like extracellular matrix (ECM). Although the mechanism by which bone ECM gains its structure is not fully understood, mechanical loading and curvature have been identified as potential contributors. Here, guided by computational simulations, we evaluated cell and bone-like tissue growth and organization in a concave channel with and without directional fluid flow stimulation. Human mesenchymal stromal cells were seeded on donut-shaped silk fibroin scaffolds and osteogenically stimulated for 42 days statically or in a flow perfusion bioreactor. After 14, 28, and 42 days, constructs were investigated for cell and tissue growth and organization. As a result, directional fluid flow was able to improve organic tissue growth but not organization. Cells tended to orient in the tangential direction of the channel, possibly attributed to its curvature. Based on our results, we suggest that organic ECM production but not anisotropy can be stimulated through the application of fluid flow. With this study, an initial attempt in three-dimensions was made to improve the resemblance of in vitro produced bone-like ECM to the physiological bone ECM.

Seismic characterization of a fluid escape structure in the North Sea: the Scanner Pockmark complex area

SUMMARYSubsurface fluid escape structures are geological features which are commonly observed in sedimentary basins worldwide. Their identification and description have implications for various subsurface fluid flow applications, such as assuring integrity of overburden rocks to geological CO2 storage sites. In this study, we applied 3-D first-arrival traveltime tomography to a densely sampled wide-azimuth and wide-angle ocean bottom seismometer (OBS) data set collected over the Scanner Pockmark complex, a site of active gas venting in the North Sea. Seismic reflection data show a chimney structure underlying the Scanner Pockmark. The objective of this study was to characterize this chimney as a representative fluid escape structure in the North Sea. An area of 6$\times $6 km2 down to a depth of 2 km below sea level was investigated using a regularized tomography algorithm. In total, 182 069 manually picked traveltimes from 24 OBS were used. Our final velocity model contains compressional wave velocity perturbations ranging from −125 to +110 ms−1 relative to its average 1-D model and compares favourably with a coincident seismic reflection data set. The tomographic velocity model reveals that the chimney as observed in seismic reflection data is part of a larger complex fluid escape structure, and discriminates the genuine chimney from seismic artefacts. We find that part of the seeping gas migrates from a deep source, accumulates beneath the Crenulate Reflector unconformity at ∼250 m below seafloor (mbsf) before reaching the porous sediments of the Ling Bank and Coal Pit formation at <100 mbsf. In addition, the model shows that the venting gas at Scanner Pockmark is also being fed laterally through a narrow NW–SE shallow channel. Quantitative velocity analysis suggests a patchy gas saturation within the gas-charged sediments of the Ling Bank and the Coal Pit formations. Confined to the well-resolved regions, we estimate a base case average gas saturation of ∼9 per cent and in-situ gas volume of ∼1.64 $\times {10^6}\ {{\rm{m}}^3}$ across the Ling Bank and Coal Pit Fm. that can sustain the observed methane flux rate at the Scanner Pockmark for about 10 to 17 yr.

Modified far-upwind reconstruction methods for the implementation of NVSF schemes on unstructured grids

Based on the analysis of the existing far-upwind reconstruction methods, three modified far-upwind reconstruction methods, named as NM-1, NM-2 and NM-3, are developed for the implementation of Normalized Variable and Space Formulation (NVSF) schemes on arbitrary unstructured grids. In the modified reconstruction methods, the locations of the cell centroids around the upwind cell are considered for the position reconstruction. And three interpolation techniques, including the nearest point interpolation, the inverse distance weighted interpolation and the gradient-considered inverse distance weighted interpolation are adopted for the value reconstruction. Moreover, a modified boundedness limitation is proposed to constrain the reconstructed value of the far-upwind node within a more reasonable scope. The pure advection tests demonstrate that NM-3 leads to a better overall performance in terms of accuracy and convergence comparing with the previous and the other modified reconstruction methods for seven classic NVSF schemes. Such advantage of NM-3 retains in the applications of multiphase flow (dam-break flow) and incompressible fluid flow (backward step flow and lid-driven cavity flow). Theoretical analysis implies that the good performance of NM-3 mainly attributes to that its position reconstruction better represents the ‘average position’ of the adjacent cell centroids around the upwind cell and its value reconstruction combines the advantages of the nearest point interpolation and the inverse distance weighted interpolation simultaneously.

On the Unsteady Rotationally Symmetric Flow Between a Stationary and a Finite Rotating Disk With a Given Change in the Axial Velocity

Abstract We consider the scenario of an unsteady viscous flow between two coaxial finite disks, one stationary and the other rotating with an axial velocity changing impulsively from zero to a constant value. The three-dimensional (3D) incompressible Navier–Stokes equations are analytically solved by postulating the polynomial profiles for the axial and circumferential velocity components and by employing the open-end condition of zero pressure difference and an integral approach. It is shown that the time-dependent squeezing of the fluid between the disks and the edge effects of the finite open-ended disks in the flow domain are determined by the compressing Reynolds number and the rotating Reynolds number for the case of laminar flow at low Reynolds numbers and small aspect ratios. The general explicit formulae are derived for the velocity and pressure distributions as a function of the compressing and rotating Reynolds numbers in this unsteady flow process (and the steady-state solutions are then obtainable as the compressing Reynolds number vanishes). A simple theoretical relationship between the radial and axial pressure gradients is deduced to hinge the radial and circumferential velocity components together. The values of the compression and rotation Reynolds numbers suitable to this theory are also suggested for the problem of rotating disk flows at low Reynolds numbers. The validity of the theoretical predictions for the circumferential, radial, and axial velocity components is partially verified through comparison with previous steady experimental and numerical results. These analytical results have the immediate engineering applications of fluid flows with varying gap widths, including wet brakes, wet clutches, hydrostatic bearings, face seals, and rotating heat exchangers.

Adaptive neuro-fuzzy inference system based data interpolation for particle image velocimetry in fluid flow applications

This paper presents an adaptive neuro-fuzzy inference system (ANFIS) approach for recovering the missing velocity vectors that commonly occur during fluid flow measurements in fluid mechanics. The capability of ANFIS in refilling the missing data is demonstrated with two case studies. First, the ANFIS is applied to estimate the velocity field data within the masked region of an available particle image velocimetry (PIV) experiment. Then, the ANFIS is trained using the data from outside the masked region and learns the relationship between the velocity vectors. Thus, it predicts the fluid patterns within the gappy area based on its understanding. ANFIS is also applied in another study to capture the small feature in the fluid flow. The vortices within a small area behind an obstacle are removed, and the rest of the data is introduced into the ANFIS model. The efficacy of the proposed ANFIS algorithm in predicting the missing velocity vectors is compared to both artificial neural network (ANN) and 2D cubic interpolation algorithms. It is found that intelligent algorithms (ANFIS and ANN) can predict the presence of vortices in the fluid flow even when there is no information about a circulating flow in the training dataset. The performance of ANFIS (R2= 0.91) in accurately predicting the velocity vectors is superior to the conventional ANN (R2= 0.86).