Fluid Flow Control Research Articles

PLUG KNOT PROCESSING OF GLOBE VALVE

Globe valves are essential components in fluid control systems, widely used in various industries for regulating flow. This paper provides an overview of globe valves, focusing on their design, operation, and applications. The distinctive spherical body shape of globe valves allows for precise control of fluid flow through the system. The paper discusses the internal components of globe valves, including the valve stem, disk, seat, and bonnet, highlighting their roles in the valve's functionality. Furthermore, it examines different types of globe valves, such as straight pattern, angle pattern, and Y-pattern valves, along with their specific applications and advantages. Additionally, the paper addresses common materials used in globe valve construction, emphasizing the importance of selecting materials suitable for the operating conditions and the fluid being controlled. Lastly, maintenance and troubleshooting tips are provided to ensure optimal performance and longevity of globe valves in industrial settings. Emphasis is placed on their operational mechanisms, wherein the movement of the plug, controlled by the stem, modulates flow rates precisely. Overall, this paper serves as a comprehensive guide to understanding globe valves and their significance in fluid control systems Keywords: Globe vаlve (type) , valve body, bonnet, plug , disk ,valve seat, stem.

CAVITATION PROCESSES IN THE MULTIPORT BALL VALVE SYSTEMS

Valves are essential components of a fluid management system, and their proper functioning is critical to ensuring the system's efficiency and durability. Multiport ball valves are versatile and commonly used in various industries to control fluid flows. These valves have multiple ports or outlets, allowing for different flow paths and configurations. One of the key considerations when using multiport ball valves is the flow characteristics within the valve itself. The flow within multiport ball valves is governed by several factors, including the design of the valve and the pressure drop across it. Understanding the flow behavior in multiport ball valves is crucial for optimizing their performance and ensuring efficient fluid handling. Different flow paths and configurations in multiport ball valves result in varying flow characteristics. For example, in a three-way multiport ball valve, there are typically two inlet ports and one outlet port. The flow can be diverted from one inlet to the outlet, or it can be split between the two outlets. This flow behavior is influenced by the presence of a constant throttling channel in the valve design.The constant throttling channel helps regulate the flow rate through the valve, and its size and shape can impact the flow characteristics. Additionally, the flow behavior in multiport ball valves can be further influenced by factors such as the material properties of the valve and the flow conditions. Furthermore, the overall flow behavior in multiport ball valves can have an impact on mass transfer and chemical reactions in the system. Different flow patterns and configurations within multiport ball valves can affect the mass transfer and transport characteristics in a system. For example, if the flow is not well-distributed or if there are areas of stagnant flow, it can lead to uneven mixing and reaction rates. Keywords: Multiport ball valve, cavitation, fluid characteristics, control of cavitation processes.

Shape matters: Convection and entropy generation in magneto-hydrodynamic nanofluid flow in constraint-based analogous annular thermal systems

This work analyzes the performance of annular thermal systems of distinct geometries to understand their shape impacts using a novel constraint-based methodology. This research fills the gap in the literature by analyzing the geometrical shape impact of magnetohydrodynamic CuO/water nanofluid flow on fluid flow, heat transfer, and thermodynamic irreversibility. Through computational simulations, the outcome results demonstrate that the circular annuli (Case 1 and Case 2) outperform the analogous square system in terms of fluid velocity, heat transfer, and irreversibility. The analysis is carried out for a range of Rayleigh numbers (Ra = 103 to 106), nanoparticle concentrations (ζ = 0 to 4%), magnetic fields (Ha = 0 to 100), and magnetic field inclinations (γ = 0° to 180°). Additionally, a significant improvement in heat transfer is observed by augmenting nanoparticles of the working fluid, while the magnetic field intensity plays a crucial role in controlling fluid flow and heat transfer. The study provides valuable insights into how various parameters affect the nanofluidic heat and flow characteristics of equivalent annular geometries and contributes to the development of more efficient and effective designs of thermal systems. The novelty of the study lies in its comprehensive approach in the use of a constraint-based methodology that matches the flow areas or cooling lengths while maintaining the same heating length to analyze the impact of geometric shapes on heat transport and accompanying irreversibility during MHD nanofluid flow. Furthermore, the energy-flux vectors are utilized to delve into the insights. The maximum value of heat transfer noted for Case 1 and Case 2 is approximately 7% and 11%, respectively, compared to the square annulus (Base Case). The inclusion of nanoparticles in the carrier fluid causes a significant enhancement in heat transfer by up to 11%, compared to pure fluid (ζ = 0).

Flipping: A Valve-Free Strategy to Control Fluid Flow in Centrifugal Microfluidic Systems

Centrifugal microfluidics has emerged as a technology to automate fluid handling at the microliter scale in bioassays. It has been mostly developed for point-of-care diagnostic applications, where assays involve a well-defined workflow. By contrast, this study introduces a microfluidic strategy that allows multiple workflows within the same device, thereby addressing the requirements of sample preparation steps in R&D settings. The corresponding device is a microfluidic chip that can be inserted either in a lab-on-a-disk or in the swinging-bucket of a commercial centrifuge. The control of liquid transfers from one chamber to the next is achieved by flipping the chip, thereby reorienting it in the centrifugal force field. The present experimental study describes the fluid instability that triggers the transfer upon flipping. A semi-empirical physical model is developed that predicts the acceleration threshold of the instability as a function of design parameters. By contrast to most existing control strategies in centrifugal microfluidics, the present strategy does not involve any valve. Consequently, it is robust to variations of material and sample properties, and it yields minimal fabrication constraints. Designing appropriately sized chambers enables flexible implementation of complex workflows. This strategy brings the miniaturization benefits of centrifugal microfluidics to sample preparation workflows.

Thermophysical dynamics of magnetohydrodynamic electroosmotic two phase mixed convective flow in vertical annulus: neuro computation

ABSTRACT The thermophysical dynamics of electro – magnetohydrodynamic mixed convective electrically conducting fluid flow in the vertical cylindrical annulus are explored with electric and magnetic fields. The flow and heat transfer properties are explicitly examined in viscous fluid and electroosmotic flow regions. The coupling between an external pressure gradient, electroosmosis, and an extended electromagnetic field can control fluid flow and heat transfer. The governing equations associated with the physical phenomenon are addressed with the Galerkin finite element method. Eloquently, the analysis revealed that, in the absence of a lateral electric field, the flow velocity decelerates as the Hartmann number increases, which in turn ultimately, causes the Nusselt number to rise. Since a lateral electric field is involved, the flow field, temperature field, and Nusselt number profiles are presented in two regions. The artificial neural network model discusses the thermal transport phenomenon in both regions. The artificial neural network models regression, performance plots, weights, and bias are presented. The research outcome can be utilized to design exquisite and efficacious electromagnetic devices, particularly within a particular range of thermal physical properties.

Thermal dynamics assessment for multi-phase flow analysis with motile cilia and electric double layer effects: Application of Levenberg–Marquardt backpropagation NNs

Ciliary movement holds substantial importance in the realm of biomedical research. Disorders arising from impaired ciliary motion, such as primary ciliary dyskinesia and specific respiratory ailments, underscore the critical need to investigate both the normal functioning and dysfunction of cilia. Such research is fundamental to the development of effective treatments and therapies. This work explores the application of Levenberg–Marquardt backpropagation neural networks (LMBP-NNs) for simulating the flow of a non-Newtonian Jeffery fluid in peristaltic motion. Inspired by synchronous ciliary movement, microfluidic systems mimicking cilia functionality have been developed. These artificial cilia can generate controlled fluid flow patterns, enabling various applications such as drug delivery, mixing, and particle sorting in lab-on-a-chip devices. The present study focuses on measuring thermal and mass transfer in beating cilia during multiphase peristaltic pumping of Jeffery fluid in two- and three-dimensional channels using transverse magnetohydrodynamics in a porous medium. The governing equations for the non-Newtonian Jeffery fluid in both the fluid and dusty phases are formulated, and exact solutions are calculated for fluid phase velocity, particulate phase velocity, temperature, concentration, and pressure gradient. The physical behavior is investigated by graphing dimensionless parameters for velocity, temperature, and concentration profiles in both solid and liquid phases. The trapping phenomena is depicted by showing streamlines of various dimensionless characteristics such as porosity velocity and volume percentage. The LMBP-NNs approach is then used to train, test, and verify the neural network models using the reference datasets. The accuracy of the LMBP-NN is assessed using statistical data such as mean square error, curve fitting graphs, regression plots, and error histograms. The study also investigates flow model limits for momentum, temperature, and concentration profiles using visual representations. This study illustrates the computational capability of LMBP-NNs in modeling the peristaltic flow of Jeffery fluid and gives useful insights into fluid flow behavior in microfluidic devices containing artificial cilia. The findings help to better understand and optimize these systems for a variety of fluid manipulation and transportation applications.

Fabrication and simulation of a microvalve for molecular communication control on a chip

In recent years, microvalves have become increasingly significant in microfluidic structures. In microfluidic devices, these microvalves are crucial to controlling fluid flow. Due to their ability to precisely manipulate and adjust the fluid, these structures are more efficient in applications, particularly in medicine, drug delivery, protein analysis, microscale communication, and chemical processes. Utilizing a numerical model for the design and fabrication of a microvalve results in the development of a more optimized and efficient structure. Microvalves can be generally divided into active and passive categories. This research focuses on the design and fabrication of a pneumatic microvalve, which falls under the category of active microvalves. This structure has two distinct chambers that allow for microscale communication. The microvalve is constructed using two layers, where the upper layer controls the lower layer, which contains fluid flow through pneumatic pressure. The performance of the system was evaluated through experimental analysis. The microchannel passage remained obstructed when the flow rates were set to 0.2 ml/h and when maintaining a constant pump pressure of 15 psi. However, the fluid flow is connected even when the pressure is cut off. We believe this structure will impact diverse applications, including molecular communication.

Gravimetric and morpho-structural analyses in the superhot geothermal system Los Humeros: an example from central Mexico

The influence of deep and regional geological structures is becoming increasingly important in superhot geothermal systems due to their proximity to the transition between brittleness and ductility. In the Los Humeros geothermal field in Mexico, where subsurface fluids reach temperatures of over 350 °C, the surface structures resulting from the collapse of calderas have so far only been interpreted at the local scale. The aim of this work is to place the recent tectonic and volcano-tectonic geomorphologic evolution and structures in the Los Humeros volcanic area in a regional context. NE- and NW-striking dominant structures resulting from a morpho-structural analysis on a regional scale are confirmed by negative and positive anomalies, respectively, after Butterworth filtering of gravity field data with different wavelengths over a local area of about 1000 km2. By analyzing the slip and dilation trends of the observed directions, we show the relevance of the regional context for reservoir exploration. The magnitudes of the principal stresses we estimate indicate a trans-tensional fault regime, a combination of strike-slip and normal faulting. The structures derived from the gravity and morpho-structural analyses, which are parallel to the maximum horizontal stress, have the highest potential for tensile and shear failure. Therefore, the corresponding negative gravity anomalies could be related to fracture porosity. Consequently, we hypothesize that these structures near the transition between brittleness and ductility control fluid flow in the Los Humeros geothermal field.

Liquid Plug Motion Noninvasive Detecting in Opaque Microchannels via Grating Electrodes‐Based Liquid‐Solid Nanogenerator

AbstractThe precision in controlling fluid flow is crucial for the efficiency of microchannel devices. Consequently, it is essential to monitor the fluid within microchannels in real time. However, the microchannel flow's susceptibility to disturbance and small size present challenges in sensing. A Liquid‐Solid Triboelectric Nanogenerator (TENG) with grating electrodes is proposed for non‐invasive sensing of liquid plug movements in microchannels and is suitable for use with opaque channels. This sensor operates on the principle of initiating multiple pulse signals via grating electrodes. And analyze the motion of the liquid plug by the time difference between the signal peaks. It facilitates the measurement of liquid plug count, average speed, average acceleration, and the detection of flow direction. The liquid plug counters, and flow direction sensors yielded clear and distinguishable signals. The liquid plug average speed sensor achieves a 95% accuracy rate, and the acceleration sensor accurately distinguishes speed trends of the liquid plug with more than 85% precision. Grating electrodes are effectively employed for motion sensing. Analyzing the motion of an object by the time difference between voltage peaks offers greater stability than voltage magnitude analysis. Four portable prototypes are designed to make them applicable for fluid sensing in microchannel devices.

Complex cilia-generated flow of hybrid nanofluid with electroosmosis, viscous dissipation and slippage

In this study, we investigated how electroosmsis, viscous dissipation, and slippage affect the peristaltic flow of complex cilia-generated flow of hybrid nanofluid in a ciliated tube. The complex cilia-generated flow is characterized by a complex sinusoidal wave that transmits along the wall of the tube with a uniform speed having distinct amplitudes. The main objective of this work is to examine how this complex cilia on the wall drives the hybrid nanofluid flow under electroosmosis. The Helmholtz–Smoluchowski equation is used to model the electroosmosis, and the Poisson equation is solved analytically using the Debye-Huckel approximation. The lubrication approach is utilized to simplify the governing equations. The governing non-dimensional equations for hybrid nanofluid are solved exactly using the DSolve command of Mathematica. The results are presented graphically to accomplish the theoretical results from the complex-cilia wave evolution from the necessary flow parameters in an asymmetric tube. The study shows that increasing the electroosmotic parameter leads to an increase in the velocity profile at the boundary and a decrease in the middle of the tube. Conversely, the Helmholtz–Smoluchowski velocity parameter has the opposite effect. The Brinkman parameter increases the temperature of the hybrid nanofluid. The study also presents a graphical analysis of pressure rise and pressure gradient for various values of the parameters. The pressure rise against volumetric flow is rate and pressure gradient increases by increasing the electroosmotic parameter and Helmholtz-Smoluchowski parameter, while it decreases for increasing the velocity slip parameter. The streamlines are drawn to study the trapping phenomena of blood in the hybrid nanofluid flow in an asymmetric tube by the formation of bolus and the division of streamlines. It is observed that the size and number of bolus close to the artery walls increases for electroosmotic parameter while reverse behavior is observed for Helmholtz-Smoluchowski parameter. The tabular presentation of the heat transfer coefficient at the wall is presented. The current results can be used in bio mathematical models to control fluid flow through micro-channels and to investigate ways to cure artery blockages and cancer tumors in biomedicine. The study can also be used to design and optimize microfluidic devices for drug delivery, lab-on-a-chip devices, and other biomedical applications.

Perspectives on predicting and controlling turbulent flows through deep learning

The current revolution in the field of machine learning is leading to many interesting developments in a wide range of areas, including fluid mechanics. Fluid mechanics, and more concretely turbulence, is an ubiquitous problem in science and engineering. Being able to understand and predict the evolution of turbulent flows can have a critical impact on our possibilities to tackle a wide range of sustainability problems (including the current climate emergency) and industrial applications. Here, we review recent and emerging possibilities in the context of predictions, simulations, and control of fluid flows, focusing on wall-bounded turbulence. When it comes to flow control, we refer to the active manipulation of the fluid flow to improve the efficiency of processes such as reduced drag in vehicles, increased mixing in industrial processes, enhanced heat transfer in heat exchangers, and pollution reduction in urban environments. A number of important areas are benefiting from ML, and it is important to identify the synergies with the existing pillars of scientific discovery, i.e., theory, experiments, and simulations. Finally, I would like to encourage a balanced approach as a community in order to harness all the positive potential of these novel methods.

Numerical study of hydromagnetic bioconvection flow of micropolar nanofluid past an inclined stretching sheet in a porous medium with gyrotactic microorganism

The present article centers on the examination of novel bioconvection phenomena involving gyrotactic microorganisms and a micropolar nanofluid model with hydro-magnetic flow. The flow traversed a stretchable inclined plate within the permeable medium. Heat absorption and thermal radiation are considered. The objective of this study is to assess the rate of heat transfer exhibited by nanofluid when unicellular microorganisms are present. Mathematical complex flow model is converted to nonlinear dimensional less system of differential equation through adopting the appropriate similarity variables. For the non-linear nanofluid problem, the (FDM) finite difference method (Lobatto IIIA) is applied with a range of collocation sites and an accuracy of order 4–5. (Lobatto IIIA) excels in solving coupled differential equations, even those with high nonlinearities. Nanofluid containing gyrotactic microbes is highly applicable in bioscience, geoscience and eco science. The effects of dimensional less parameters on flow field, energy distribution, nanofluid concentration and density of microorganism concentration profiles analyzed through the graphical and tabulation representation. This basic research will aid scientists and engineers in controlling fluid flow and improving complex systems that make use of it.

Shape-memory microfluidic chips for fluid and droplet manipulation.

Fluid manipulation is an important foundation of microfluidic technology. Various methods and devices have been developed for fluid control, such as electrowetting-on-dielectric-based digital microfluidic platforms, microfluidic pumps, and pneumatic valves. These devices enable precise manipulation of small volumes of fluids. However, their complexity and high cost limit the commercialization and widespread adoption of microfluidic technology. Shape memory polymers as smart materials can adjust their shape in response to external stimuli. By integrating shape memory polymers into microfluidic chips, new possibilities for expanding the application areas of microfluidic technology emerge. These shape memory polymers can serve as actuators or regulators to drive or control fluid flow in microfluidic systems, offering innovative approaches for fluid manipulation. Due to their unique properties, shape memory polymers provide a new solution for the construction of intelligent and automated microfluidic systems. Shape memory microfluidic chips are expected to be one of the future directions in the development of microfluidic technology. This article offers a summary of recent research achievements in the field of shape memory microfluidic chips for fluid and droplet manipulation and provides insights into the future development direction of shape memory microfluidic devices.

A hybrid numerical model for coupled hydro-mechanical analysis during CO2 injection into heterogeneous unconventional reservoirs

This paper presents a hybrid numerical model for simulating compressible multiphase multicomponent transport in deformable, heterogeneous unconventional reservoirs. A fully implicit theoretical framework for coupled hydromechanical behaviour is established, in which the flash calculation is avoided. To preserve the local mass conversation, an element based finite volume method is used to spatially discretize mass conversation equations. Linear momentum equilibrium equation is discretized with finite element method. Two numerical approaches are coupled through sharing the same shape functions. An implicit mid-interval backwards difference algorithm is used to handle the temporal derivative. Reliability and efficiency of the developed model have been examined by verification tests against available analytical or numerical solutions. The coupled hydromechanical processes in heterogeneous reservoirs were simulated. The results of numerical experiments show that oscillatory problem for saturation in heterogeneous media can be eliminated, demonstrating better performance of developed model for heterogeneous reservoir simulations. Reservoir performance is significantly shaped by its heterogeneity through controlling fluid flow and time for CO2–CH4 displacement. Simulation results show that the time required for completion of CO2–CH4 displacement increases by about 250 days when considering heterogeneity effect. In conclusion, this study offers a valuable tool for facilitating the development of CO2-enhanced unconventional gas recovery.

Simulation and performance prediction of partially naturally fractured reservoirs under solution gas drive primary recovery and gas injection processes

The study presented in this paper has multiple objectives. First, a simulation model for partially naturally fractured reservoirs under solution gas drive is developed. The model considers the major key parameters controlling fluid flow in the reservoir, including fracture intensity and distribution, instantaneous gas/oil segregation due to vertical capillary continuity, gas/oil gravity drainage, and reinfiltration of the drained oil to the lower matrix. Once the model is well-established, it is used to study the reservoir performance under two recovery processes: primary depletion and gas injection. A detailed investigation of the sensitivity of the ultimate oil recovery to the fracture intensity, oil production rates, and gas injection rates is performed. The findings of this study indicate that the ultimate oil recovery of low-fracture intensity reservoirs subjected to the depletion drive process is insensitive to production rates. However, for moderate- to high-fracture intensity reservoirs and low production rates, the recovery increases with increasing fracture intensity. Conversely, for moderate- to high-fracture intensity reservoirs and high production rates, the recovery is not significantly affected. For the gas injection mechanism, it is found that the ultimate oil recovery is a function of both the fracture intensity and gas injection rate. Furthermore, three fracture intensity ranges are identified: low, medium, and high. For the low- and high-fracture intensity ranges, the recovery increases with increasing gas injection rates and fracture intensity. However, for the medium fracture intensity ranges, the recovery behaves differently. It increases at low gas injection rates and decreases at high injection rates as the fracture intensity increases. New equations relating the cumulative oil production to the production rates, gas injection rates, and fracture intensity are also presented.

Comparative analysis of entropy generation and heat transfer in a tilted partially heated square enclosure using the finite difference method

PurposeIn recent times, there has been a growing interest in buoyancy-induced heat transfer within confined enclosures due to its frequent occurrence in heat transfer processes across diverse engineering disciplines, including electronic cooling, solar technologies, nuclear reactor systems, heat exchangers and energy storage systems. Moreover, the reduction of entropy generation holds significant importance in engineering applications, as it contributes to enhancing thermal system performance. This study, a numerical investigation, aims to analyze entropy generation and natural convection flow in an inclined square enclosure filled with Ag–MgO/water and Ag–TiO2/water hybrid nanofluids under the influence of a magnetic field. The enclosure features heated slits along its bottom and left walls. Following the Boussinesq approximation, the convective flow arises from a horizontal temperature difference between the partially heated walls and the cold right wall.Design/methodology/approachThe governing equations for laminar unsteady natural convection flow in a Newtonian, incompressible mixture is solved using a Marker-and-Cell-based finite difference method within a customized MATLAB code. The hybrid nanofluid’s effective thermal conductivity and viscosity are determined using spherical nanoparticle correlations.FindingsThe numerical investigations cover various parameters, including nanoparticle volume concentration, Hartmann number, Rayleigh number, heat source/sink effects and inclination angle. As the Hartmann and Rayleigh numbers increase, there is a significant enhancement in entropy generation. The average Nusselt number experiences a substantial increase at extremely high values of the Rayleigh number and inclination.Practical implicationsThis numerical investigation explores advanced applications involving various combinations of influential parameters, different nanoparticles, enclosure inclinations and improved designs. The goal is to control fluid flow and enhance heat transfer rates to meet the demands of the Fourth Industrial Revolution.Originality/valueIn a 90° tilted enclosure, the addition of 5% hybrid nanoparticles to the base fluid resulted in a 17.139% increase in the heat transfer rate for Ag–MgO nanoparticles and a 16.4185% increase for Ag–TiO2 nanoparticles compared to the base fluid. It is observed that a 5% nanoparticle volume fraction results in an increased heat transfer rate, influenced by variations in both the Darcy and Rayleigh numbers. The study demonstrates that the Ag–MgO hybrid nanofluid exhibits superior heat transfer and fluid transport performance compared to the Ag–TiO2 hybrid nanofluid. The simulations pertain to the use of hybrid magnetic nanofluids in fuel cells, solar cavity receivers and the processing of electromagnetic nanomaterials in enclosed environments.

Magneto-Stefan blow enhanced heat and mass transfer flow in non-Newtonian ternary hybrid nanofluid across the nonlinear elongated surface

The present article explores the flow and heat transfer properties of a non-Newtonian ternary nanofluid over a nonlinear stretched surface by considering magnetic, chemical reaction, and Stefan blow effects. The ternary nanoliquid considered here are of three distinct nanoparticles such as Ag, MoS2, and SiO2 due to their high thermal conductivity, thermal stability and lubricating particles each dispersed in a base fluid (H2O). Using similarity transformations, the governing partial differential equations (PDEs) that describe the flow, heat transfer, and nanoparticle concentration distribution are turned into a system of ordinary differential equations (ODEs). In order to deal with this system, the shooting strategy is utilized – a numerical method renowned for its efficacy in solving nonlinear boundary value problems. Furthermore, the effects of critical parameters such as the Jeffrey parameters, magnetic field strength, Stefan blow parameter, and nanoparticle volume percentage on flow and heat transmission characteristics are comprehensively investigated. It is observed that the velocity field augments when Stefan blow parameter Sb > 0 (mass blowing) and reduces when Sb < 0(mass suction). It is noteworthy to observe that an increase in the Prandtl number (Pr) corresponds to a decrease in the temperature field. The findings of this research possess the potential to provide practical ramifications in diverse technical, biomedical, and industrial sectors, including but not limited to polymer processing and nanomaterial creation. These findings hold significant value in situations where precise control of fluid flow and heat transfer is essential for maximizing overall performance and efficiency.

Fluid Flow Dynamics in Partially Saturated Paper.

This study presents an integrated approach to understanding fluid dynamics in Microfluidic Paper-Based Analytical Devices (µPADs), combining empirical investigations with advanced numerical modeling. Paper-based devices are recognized for their low cost, portability, and simplicity and are increasingly applied in health, environmental monitoring, and food quality analysis. However, challenges such as lack of flow control and the need for advanced detection methods have limited their widespread adoption. To address these challenges, our study introduces a novel numerical model that incorporates factors such as pore size, fiber orientation, and porosity, thus providing a comprehensive understanding of fluid dynamics across various saturation levels of paper. Empirical results focused on observing the wetted length in saturated paper substrates. The numerical model, integrating the Highly Simplified Marker and Cell (HSMAC) method and the High Order accuracy scheme Reducing Numerical Error Terms (HORNET) scheme, successfully predicts fluid flow in scenarios challenging for empirical observation, especially at high saturation levels. The model effectively mimicked the Lucas-Washburn relation for dry paper and demonstrated the increasing time requirement for fluid movement with rising saturation levels. It also accurately predicted faster fluid flow in Whatman Grade 4 filter paper compared with Grade 41 due to its larger pore size and forecasted an increased flow rate in the machine direction fiber orientation of Whatman Grade 4. These findings have significant implications for the design and application of µPADs, emphasizing the need for precise control of fluid flow and the consideration of substrate microstructural properties. The study's combination of empirical data and advanced numerical modeling marks a considerable advancement in paper-based microfluidics, offering robust frameworks for future development and optimization of paper-based assays.

The analysis of electromagnetic maxwell nanofluid flow over an axisymmetric cylindrical surface using artificial neural networks for active and passive control

ABSTRACT This work presents a novel approach to active and passive control of fluid flow on a stretching cylinder, considering the collective effects of electromagnetism, and chemical reactivity. The Maxwell fluid flow over the stretched surface of a cylinder is responsible for the improvement in heat transfer. The proposed methodology leverages the power of Artificial Neural Networks (ANN) to effectively manipulate and optimize fluid flow behavior in this complex system. By integrating ANN into the control strategy, we achieve enhanced propulsion system design and optimization capabilities, enabling improved performance around cylinders. Additionally, insights into the interconnection of electromagnetic effects and heat sources provide valuable implications for thermal management systems, where understanding and controlling fluid flow behavior are essential for efficient heat transfer. The design approach for addressing different aspects of the fluid problem consists of a sequence of operations, which encompass training, testing, and validation using a reference dataset. Furthermore, visual representations are employed to portray the flow model parameters concerning momentum, energy, and concentration profiles, effectively illustrating the results of the investigation, all of which are closely aligned with each other on average 10−8.

CFD Analysis for Valve-Holding Camber Permanent Inhaler Spacer (AerospaAcer) with Different Valves

During the COVID-19 pandemic, data statistics showed that patients with respiratory problems become infected. One of the therapy techniques for the respiratory condition was the use of a metered-dose inhaler and spacer. The objective of this paper is to determine the flow parameters of three types of valves which is duckbill valve, cross slit valve and umbrella valve in inhaler spacer to compare fluid flow between valve Previous researchers chose the duckbill valve to control fluid flow in inhaler spacer. The flow characteristics are unaffected by the materials used in the new disposable inhaler spacers, such as paper and polylactic acid (PLA). Several design valves reduced the skewness below 0.94 by suppressing the fillet and chamfer. ANSYS Workbench Fluent 19.2 is used to calculate flow parameters such as turbulence kinetic energy (TKE), turbulence eddy dissipation (TED), velocity, particle velocity magnitude, streamline, and vector velocity. The setup input data is based on the previous researcher's specified parameters such as viscosity model, drug characteristics (salbutamol and propellant), discrete phase model (DPM) equal to 80, boundary condition model, and SIMPLE technique. For the three types of valves, the nozzle injection used a 0.50-millimetre dimension. The simulation work is cross-checked against the results of prior simulations. Within each iteration, the transient flow employed a time step size of 0.01 for 200 steps. The results show that computational analysis can distinguish between models of varying complexity. The TED, TKE, and velocity graphs showed the approximate value between the model geometries. Overall, the study was successful in achieving the desired velocity magnitude in terms of visual and graph representations of the various valve.