Prediction Of Flow Characteristics Research Articles

Analysis of the influence of the daily regulation of power stations on navigable flow conditions at river confluences using the LSTM model

The daily operations of large hydropower stations on rivers induce frequent variations in downstream water levels and flow velocities, resulting in unsteady and complex hydraulic characteristics at the confluence of the main stream and its tributaries, which adversely affect navigation safety. The continuity and momentum equations, along with the RNG k-ϵ turbulence model and the VOF model, were employed to simulate the river flow process at the confluence under unsteady flow conditions. The simulated results for water levels and velocity vector fields are in good agreement with experimental data. Variations in hydraulic characteristics, including water level, flow velocity, and longitudinal gradient at the confluence of the main stream and its tributaries, were analysed. The results indicated that the water level at the confluence decreases when the tributary merges with the main stream. As the confluence ratio increases, fluctuations in the water level at the confluence decrease. However, an increase in the staggered period results in greater fluctuations in the water level within this region. Moreover, a crescent-shaped high-speed flow region is formed at the confluence of the tributary and the main stream. As the unsteady flow discharge of the main stream increases, the relative area of this region correspondingly enlarges, reaching its maximum at peak discharge, and subsequently gradually diminishes as the discharge decreases. Based on these simulation data, a Long Short-Term Memory (LSTM) model was developed to effectively predict water levels and flow velocities, providing a more convenient and accurate method for obtaining real-time information on confluence areas than traditional mathematical and statistical approaches. This study provides novel insights into predicting flow characteristics in confluence areas, thereby offering a basis for formulating navigation safety plans.

Stability patterns in plane porous Poiseuille flow with uniform vertical cross-flow: A dual approach

In this study, we examine the effects of a porous parameter and a uniform vertical cross-flow on the onset of instability in a plane Poiseuille flow (PPF) subjected to infinitesimal disturbances. The linearized Navier-Stokes (N–S) equations, which govern the stability of the fluid flow system, are addressed using the Chebyshev collocation method (CCM). Our approach includes both modal and non-modal analyses, each providing distinct insights into the system's behavior. The modal analysis involves a linear stability assessment using both non-normalized and normalized basic velocity approaches. Assuming a constant pressure gradient, the first approach aligns with the traditional Poiseuille flow framework, where a uniform pressure difference drives the flow. This simplifies calculations and aids in predicting flow characteristics. The second approach, which varies the pressure gradient to maintain a constant maximum streamwise velocity, offers a different perspective by focusing on a specific flow velocity profile through the porous medium. This variation in the pressure gradient allows us to explore changes in flow behavior and the system's responses under these conditions. This analysis includes examining the eigenspectrum, neutral stability curves, and determining critical triplets. On the non-modal front, we explore the intricacies of the non-normal Orr-Sommerfeld (O–S) operator. This involves studying the pseudospectrum and transient energy growth rate (G(t)) plots for optimal perturbations. Identification of regions of stability, potential instability, and instability is achieved using contour plots of maximum transient energy growth (Gmax). Interestingly, our results reveal that the porous parameter acts as a stabilizing agent, mitigating instability. In contrast, the uniform vertical cross-flow plays a dual role, contributing to both stabilization and destabilization of the system. Additionally, our study highlights the impact of examining basic velocity through both normalized and non-normalized approaches, leading to different stability predictions.

Enhancing convergence and accuracy: A comparative study of preconditioning for steady, laminar, and high gradient flows over a wide range of Mach numbers

This paper introduces a novel platform that integrates three preconditioning matrices based on conservative variables: the Turkel, Choi–Merkle and Onur matrices. The platform aims to compare these matrices in terms of accuracy and robustness by investigating their performance in solving three distinct and challenging high-gradient laminar flow problems: (i) Bi-Plane NACA0012 airfoil, (ii) lid-driven flow in a square cavity and (iii) flow in a planar T-junction. These problems serve as new and challenging test cases to accurately determine the abilities of the preconditioning matrices. The preconditioning matrices are applied to evaluate the numerical solutions, and their performance in complex flow fields is assessed in terms of accuracy and efficiency. By solving these flow problems, the effectiveness of the preconditioning matrices is thoroughly analyzed. By integrating these preconditioning matrices into a single platform, this paper significantly contributes to the field. The approach enables a direct and meaningful comparison of the performance of the Turkel, Choi–Merkle and Onur matrices in solving these new and challenging laminar flow problems. While all three matrices demonstrate comparable accuracy in predicting flow characteristics like pressure coefficients, Turkel’s method shows superior convergence acceleration across the almost test cases due to alpha parameter and modifications of the momentum equations. In the external flow case, Turkel converges 22–53% faster than the other matrices by adjusting momentum terms with an alpha parameter. For the internal lid-driven cavity case, Turkel again accelerates convergence up to 38% over Choi–Merkle as Reynolds and Mach numbers increase. However, Onur’s method stalls at high Reynolds/Mach numbers. At low values of Reynolds and Mach numbers, Onur reduces computational cost by 17%. Finally, for the T-junction case, Turkel and Choi–Merkle perform almost identically, decreasing CPU time by 55% vs Onur, which lacks convergence robustness. While the preconditioning matrices have similar accuracy, Turkel offers the best convergence improvement by accounting for momentum effects. Onur works well at low Reynolds/Mach numbers but shows limitations at higher values. The selection of the optimal preconditioning matrix should be based on whether momentum or viscosity dominates in the flow field, as well as the intensity of the viscosity gradient rate.

Evaluation of several liquid–vapor phase change models for numerical simulation of subcooled flow boiling

The phase change model has recently attracted attention for use in flow-boiling numerical simulation research. Comparison and evaluation of the calculation accuracies and resource consumptions of phase change models are essential for developing an efficient and high-precision phase change model. In this study, the Dong and Chen models, were added to the FLUENT software as two new models by introducing a unique user-defined function (UDF). The two unique models and the Lee model served as the foundation for numerical research, and the values of dependabilities and properties for flow and heat transmission predicted by these models were compared. Visual studies and flow-boiling heat transfer correlations were used to validate the results. The results reveal that the Chen model, which considers the active nucleation density site of bubbles, has a significant advantage over the other two models in terms of predicting flow characteristics. The Lee and Dong models are better suited for forecasting the changing tendency of the heat transfer coefficient, whereas the values obtained with the Chen model are closer to the reference values for the Liu–Winterton correlation. Besides, the two novel models also have higher computational costs.

Anode analysis and modelling hydrodynamic behaviour of the multiphase flow field in circular PEM water electrolyzer

A numerical study of the behaviour of the multiphase flow of an anode-porous transport layer of an aqueous electrolyzer with a proton-exchange membrane (PEM) of an aqueous electrolyzer is presented. A mixture model was used to study the flow behaviour in a circular-shaped anode box to determine the efficient design of a PEM water electrolyzer. As a result of the simulation, it was found that the model pressure drop profiles obtained by computational fluid dynamics (CFD) are in good agreement with the corresponding experimental data. In addition, the performance profile was predicted considering various PEM water electrolyzer cell improvement factors compared to the Bassline model. The results of the behaviour of two-phase flows with different velocity, pressure and volume fraction profiles, as well as with porous regions in the centre, are presented, which showed a key difference in the flow profile for various inlet and outlet flow configurations. In addition, the flow volume fraction behaviour was obtained at higher and lower water and oxygen rates. Three-dimensional (3D) modelling predicted flow characteristics for three different cell configurations. In this article, we also run simulations over a wide range of flow rates. The main results of the numerical study were discussed to shed light on the design of a high-performance PEM water electrolyzer.

Characterization of interfacial waves in stratified turbulent gas-liquid pipe flow using Particle Image Velocimetry and controlled disturbances

The work reports an experimental investigation on stratified gas-liquid pipe flow characteristics in the presence of controlled interfacial waves. Studies of this flow regime with controlled interfacial waves are scarce in the literature. Here, the disturbances are excited at the liquid interface by an oscillating paddle. The waves are synchronized with image acquisitions, enabling the utilization of phase-locked measurements and ensemble averaging techniques. Off-axis Particle Image Velocimetry (PIV) and Shadowgraph techniques were applied to provide information about mean and wave-induced modifications on the velocity fields. Results show that mean flow velocities in the liquid and gas phases close to the pipe walls adhere well to the single-phase flow log-law profile. In the liquid layer, this agreement was observed up to half of the water depth. Controlled disturbances enabled the estimation of the wave amplitude thresholds for the appearance of relevant nonlinear wave effects on the flow field. Results suggest that such a threshold can be fairly represented by a constant value of the non-dimensional parameter proposed in the work of Kirby (2008). Within the non-linear wave regimes investigated, noticeable changes in the flow field were observed close to the interface. However, near the wall the flow was weakly affected by the presence of waves, suggesting that interfacial wave effects are weakly coupled with near-wall disturbances and might be modelled independently. Moreover, contributions to interfacial shear stress due to the presence of waves were obtained experimentally. The results presented here are useful for validation and improvement of models used to predict flow characteristics in stratified flows. In addition, they contribute to shed further light on the physical mechanisms involved in the phenomenon.

A novel trussed fin-and-elliptical tube heat exchanger with periodic cellular lattice structures

PurposeThis study aims to computational numerical simulations to clarify and explore the influences of periodic cellular lattice (PCL) morphological parameters – such as lattice structure topology (simple cubic, body-centered cubic, z-reinforced body-centered cubic [BCCZ], face-centered cubic and z-reinforced face-centered cubic [FCCZ] lattice structures) and porosity value ( ) – on the thermal-hydraulic characteristics of the novel trussed fin-and-elliptical tube heat exchanger (FETHX), which has led to a deeper understanding of the superior heat transfer enhancement ability of the PCL structure.Design/methodology/approachA three-dimensional computational fluid dynamics (CFD) model is proposed in this paper to provide better understanding of the fluid flow and heat transfer behavior of the PCL structures in the trussed FETHXs associated with different structure topologies and high-porosities. The flow governing equations of the trussed FETHX are solved by the CFD software ANSYS CFX® and use the Menter SST turbulence model to accurately predict flow characteristics in the fluid flow region.FindingsThe thermal-hydraulic performance benchmarks analysis – such as field synergy performance and performance evaluation criteria – conducted during this research successfully identified demonstrates that if the high porosity of all PCL structures decrease to 92%, the best thermal-hydraulic performance is provided. Overall, according to the obtained outcomes, the trussed FETHX with the advantages of using BCCZ lattice structure at 92% porosity presents good thermal-hydraulic performance enhancement among all the investigated PCL structures.Originality/valueTo the best of the authors’ knowledge, this paper is one of the first in the literature that provides thorough thermal-hydraulic characteristics of a novel trussed FETHX with high-porosity PCL structures.

Computational Examination of Unsteady Cavitating Flow Characteristics on a 2D NACA66 Profile by Utilizing OpenFOAM®

The complexity of the flow mechanism is one of the crucial problems in cavitation. In this present study, detailed computational examinations of cavitating flow around a NACA66 hydrofoil were performed by using OpenFOAM® software. Dynamic and unsteady behaviours of cavitating flow were solved utilizing the k-ω SST turbulence model. Schnerr-Sauer cavitation model was used for the calculations. Numerical simulations were performed for 6° and 8° angle of attack with different cavitation numbers and the outlet pressure conditions, the cases are called “Case 1” and “Case 2” respectively. The results were compared with the studies performed by Leroux et. al. Oscillation cycles and flow characteristics were obtained successfully in both cases. The mechanism called the re-entrant jet was shown to be primarily responsible for cavitation break-off in two cases. This mechanism consists of two steps: 1) an interplay between the re-entrant flow and the cavity contact surface in the occlusion region, resulting in recurrent secondary cloud shedding until the primary cloud detachment, and 2) a shock wave triggered by the primary cloud collapsing, which affects the development of the remnant cavity.
 The main contribution of this study is to examine the impact of using the k-ω SST turbulence model with the Schnerr-Sauer cavitation model on predicting flow characteristics such as cavitation dynamics, pressure distribution and cavity form. Acceptable accuracy has been observed for pressure fluctuations and cavitation dynamics.

Numerical Analysis on a Constant Rate of Kinetic Energy Change Based a Two-Stage Ejector-Diffuser System

Supersonic ejector energy flow devices are extensively used in various applications, such as pumping, mixing, compression, etc. The conventional single-stage ejector (SSE) design approaches are inefficient for modelling an efficient ejector because of their inefficiency in minimizing mixing losses in the mixing chamber, thermodynamic shock in constant area diffuser, and utilization of redundant discharged momentum at the exit of the first stage. The physics-based single-stage ejector design has better solutions because it minimizes irreversibility due to thermodynamic shocks. The present study utilizes the constant rate of a kinetic energy change physics-based approach to design a two-stage ejector (TSE) for water vapour. The computational fluid dynamics (CFD) tool ANSYS-Fluent has been utilized to predict flow characteristics. The performance of the ejector-diffuser system has also been compared with a single-stage ejector. It is found that the performance of TSE is 70 % higher than that of the performance of SSE.

CNN-based flow control device modelling on aerodynamic airfoils

Wind energy has become an important source of electricity generation, with the aim of achieving a cleaner and more sustainable energy model. However, wind turbine performance improvement is required to compete with conventional energy resources. To achieve this improvement, flow control devices are implemented on airfoils. Computational fluid dynamics (CFD) simulations are the most popular method for analyzing this kind of devices, but in recent years, with the growth of Artificial Intelligence, predicting flow characteristics using neural networks is becoming increasingly popular. In this work, 158 different CFD simulations of a DU91W(2)250 airfoil are conducted, with two different flow control devices, rotating microtabs and Gurney flaps, added on its Trailing Edge (TE). These flow control devices are implemented by using the cell-set meshing technique. These simulations are used to train and test a Convolutional Neural Network (CNN) for velocity and pressure field prediction and another CNN for aerodynamic coefficient prediction. The results show that the proposed CNN for field prediction is able to accurately predict the main characteristics of the flow around the flow control device, showing very slight errors. Regarding the aerodynamic coefficients, the proposed CNN is also capable to predict them reliably, being able to properly predict both the trend and the values. In comparison with CFD simulations, the use of the CNNs reduces the computational time in four orders of magnitude.

Experimental and Numerical Study of the Discharge Performance of Particle-Laden Turbulent Flow

In the marine fire suppression system, continuous delivery of dry chemical powder to the fire source with long powder discharge range and high dispersion concentration is essential. The work is devoted to experimental and numerical studies of the flow characteristics of the dry chemical powder jet from a horizontal injector with a wide range of Stokes numbers between 6 to 30 and Reynolds numbers between 4792 to 23,960 by considering the effect of gravitational acceleration. A CFD-based Eulerian–Eulerian multiphase model combined with Standard k-ω turbulence model was used to predict flow characteristics of particle-laden jet using dimensionless numbers, including the solid volume fraction, the normalized velocity magnitude, and the turbulent viscosity ratio. Experimental studies have been carried out for three different inflow velocities (2.06, 2.45, and 2.81 m/s). The results indicate that the particle density plays a significant role in the dispersion of the particles in the radial and axial directions. The transition from U-shaped to V-shaped solid dispersion structure on the ground can be captured with the increase of particle density. Moreover, the higher level turbulence intensity enhances the solid dispersion concentration. Finally, it was found that the Portland cement powder exhibits better discharge performance in terms of solid discharge range and dispersion concentration in comparison with other dry powders. These results have implications in the design of powder-based fire suppression system. Further studies should aim to the in-depth research on the fire extinguishing mechanism of the Portland cement powder, especially the fire suppression effectiveness and thermal decomposition process.

Simulation of Internal Pipe Flows in Gasoline Port Fuel Injection System under Steady State Condition

Fluid flow models developed for pipe flows in gasoline port fuel injection system with different number of injectors working under steady state condition was simulated in this study using Flow Master Software. Using existing equations, theoretical analysis were computed for the same flow parameters and the results obtained for each parameter for both the simulation and theoretical approach were compared accordingly. The results obtained for theoretical approach and that of simulation had not shown much correlation due to the assumptions and computational errors. The pipe flow was simulated under steady state and the inlet pressure flowing across the circular pipe increased per unit time while fluctuations characterised by sinusoidal pattern were observed on the plot of total pressure at bends against time. The normal pressure while flowing along the pipe duct increased proportionally with the pipe length but suddenly experience a decline and picks up again as it encounters a bend. The mass flow rate of gasoline was observed to increases gradually as the simulation time progressed. For the three simulated outcomes, decrease were observed as the flow approaches bends along the circular pipe. Hence, the use of FLOWMASTER software in Computational Fluid Dynamics (CFDs) can help in predicting flow characteristics in hydraulic computations.

Assessment of BSL kω Turbulence Model for Predicting Flow Characteristics in a Solitary Wave Motion

A deep understanding of boundary layer characteristics under wave motion, especially bottom shear stress on the seabed, is critical in sediment transport calculation and modeling. In this present study, boundary layer characteristics under solitary wave motion over the smooth bed are investigated through the Baseline (BSL) kω model. It will also consider the result of a laboratory experiment performed in a closed conduit generation system. The conclusion said that the BSL kω model can replicate well on horizontal and vertical velocity distribution at Reynolds number (Re) = 2.25 x 105. In addition, a turbulent spike which was occurred during decelerating phases of oscillatory motion can be predicted well also by the BSL kω model at Reynolds number (Re) = 6.06 x 105.

Lattice Boltzmann Method for Simulations of Nozzle Flows in Coastal Environments

Sun, P.; Zhou, J.; Liu, Y., and Wang, Y., 2022. Lattice Boltzmann method for simulations of nozzle flows in coastal environments. Journal of Coastal Research, 38(1), 204–217. Coconut Creek (Florida), ISSN 0749-0208. A better understanding of flow in pipes is considered to be critical for marine equipment because it helps to improve pipe performance related to vibration and structure problems. In this study, flow simulations were conducted using a large–eddy-simulation lattice Boltzmann method (LES-LBM) in a nozzle under various Reynolds numbers (Re) and the effect of the three-dimensional cubic lattice models D3Q15, D3Q19, and D3Q27 was examined. The results show that when Re < 200 (i.e. the asymmetry of the results calculated using lattice models D3Q15 and D3Q19 is below 5%) or when the lattice model D3Q27 is adopted, computational results can satisfy the requirement of rotational invariance. When 250 < Re < 300 or the flow suddenly traverses an abrupt expansion, the isotropy of lattice models D3Q15 and D3Q19 experience “collapse”. Defective planes cannot be used to completely solve complex flows and accurately transfer flow information. The resultant problems in the computational results include preference in the circumferential distribution of axial velocity and contraction effects of the phase portrait of axial and radial velocities. More complex flows (e.g., for situations with large Re or fluid traversing abrupt expansion) universally cause more significant lattice model effects, where nonlinear flow phenomena become dominant. Therefore, it is necessary to ensure that solutions in the entire computational domain are independent of lattice orientation during flow simulation using LBM. Overall, the results in this paper have important potential applications in predicting flow characteristics for pipe flows in marine structures such as marine risers in coastal environments and zones farther out to sea.

CFD Analysis of the Optimization of Length of Capillary Tube for a Vapor Compression Refrigeration System

Abstract: The capillary tube is commonly employed in refrigerant flow control systems. As a result, the capillary tube's performance is optimal for good refrigerant flow. Many scholars concluded performance utilising experimental, theoretical, and analysis-based methods. This paper examines the flow analysis of a refrigerant within a capillary tube under adiabatic flow circumstances. For a given mass flow rate, the suggested model can predict flow characteristics in adiabatic capillary tubes. In the current work, R-134a refrigerant has been replaced by R600a refrigerant as a working fluid inside the capillary tube, and the capillary tube design has been modified by altering length and diameter, which were obtained from reputable literature. The analysis is carried out using the ANSYS CFX 16.2 software. The results show thatutilising a small diameter and a long length (R600a refrigerant flow) is superior to the present helical capillary tube. The most appropriate helical coiled design with a diameter of 0.8 mm and a length of 3 m is proposed. Keywords: Capillary Tube, Condenser, Refrigeration effect, CFD.

Influence of various aspects of low-Reynolds number turbulence models on predicting flow characteristics and transport variables in a horizontal direct-chill casting

Computational Fluid Dynamics (CFD) was used to simulate the solidification in a horizontal direct-chill (HDC) casting using five low-Re k-ɛ turbulence model: including the v2¯−f model of Durbin (V2F), Yang-Shih (YS), Chang-Hsieh-Chen (CHC), Abid (AB), and Abe-Kondoh-Nagano (AKN). The model incorporated turbulence energy production due to buoyancy in the k and ɛ equations to predict flow pattern, eddy viscosity ratio, turbulence intensity, turbulence velocity, turbulence energy production due to buoyancy, solid fraction, and temperature. Three sets of grids were systematically chosen in such a way that the grid refinement factor was above 1.3. The results obtained indicate that the solution was independent of grid size. The flow pattern predicted using the turbulence models are generally similar, but the V2F indicated additional minor counter-clockwise recirculating cells toward the bottom mold. Further, the solutions indicate that turbulence energy production due to buoyancy contributes to the strong turbulence levels predicted towards the top mold region. The predicted velocity of the mean flow for the V2F model in the flow domain is higher, followed by the YS model and least for the CHC, AB, and AKN models. The eddy viscosity ratio is highest with a value of 144 at y+<100 for the CHC model, followed by AKN and AB with eddy viscosity ratios of 144 and 137 respectively. Then, the YS has a maximum eddy viscosity ratio of 114 at y+<50, V2F has the least maximum eddy viscosity ratio of 78 at y+<150. The turbulence intensity, the turbulence velocity, and the turbulence energy production due to buoyancy were highest towards the top mold for the CHC, AB, and AKN than the YS and V2F models. The V2F and YS predicted lower temperature curves and higher solid fraction curves towards the mid-section of the profiles than the CHC, AB, and AKN models.

Automated terrain generation for precise atmospheric boundary layer simulation in the wind tunnel

This study presents a two-stage framework to characterize boundary layer wind tunnel (BLWT) approach flows naturally developed over grid roughness for partial atmospheric boundary layer (ABL) simulation. The first stage applies curve fitting techniques to a comprehensive series of high-resolution spatially-averaged velocity profile measurements to estimate aerodynamic roughness parameters (ARPs) for a wide range of homogeneous (i.e., equal height) roughness element configurations. For this study, an automated (i.e., computer-controlled) 62 ​× ​18 roughness element array called the Terraformer was used to generate 33 unique roughness element fields. The mean flow structure was captured downwind to the Terraformer, where key ARPs—i.e., the urban canopy attenuation coefficient, zero-plane displacement height, shear (friction) velocity, roughness length, and Coles’ wake strength coefficient—were estimated. In contrast to previous ABL modeling methods that primarily focused on curve fitting of the inertial sublayer (ISL), the proposed approach applies the urban canopy exponential profile within the roughness sublayer (RSL), the log law in the ISL, and the law of the wake in the outer wake layer to model full-depth (i.e., floor to freestream) rough-wall turbulent boundary layers. Further, the method explicitly captures potential variability of Reynolds shear stress in the ISL and the wake strength in the outer layer to generalize characterization of naturally-developed BLs produced by traditional tunnel designs. The second stage applies a morphometric model for each ARP—calibrated with estimates from Stage 1—to predict flow characteristics for a wide range of roughness element configurations, with the goal of producing a deterministic solution for selecting an element configuration to satisfy user-specified aerodynamic objectives for the approach flow. The calibrated models effectively interpolate between estimates, e.g., ARPs estimated for open and suburban terrains can be applied in the second stage model calibration to predict ARPs for a “rough-open” condition without further experimentation. The findings of this study demonstrate that coupling the proposed framework with a mechanized roughness element grid can significantly reduce the trial-and-error required to commission a BLWT, while improving the quality of flow characterization.

Predicting Network Flow Characteristics Using Deep Learning and Real-World Network Traffic

We present a processing pipeline for flow-based traffic classification using a machine learning component leveraging Deep Neural Networks (DNNs). The system is trained to predict likely characteristics of real-world traffic flows from a campus network ahead of time, e.g., a flow’s throughput or duration. Training and evaluation of DNN models are continuously performed on a flow data stream collected from a university data center. Instead of the common binary classification into “mice” and “elephant” (throughput) or “short-term” and “long-term” (duration) flows, predicted flow characteristics are quantized into three classes. Various communication contexts (subset of network traffic, e.g., only TCP) and flow feature groups (subset of flow features, e.g., only a flow’s 5-tuple), which are supported through an enrichment strategy, are considered and investigated. An in-depth description of the data acquisition process, including preprocessing steps and anonymization used to protect sensitive information, is given. Additionally, we employ an accelerated variant of t-distributed Stochastic Neighbor Embedding (t-SNE) to visualize network traffic data. This enables the understanding of traffic characteristics and relations between communication flows at a glance. Furthermore, possible use-cases and a high-level architecture for flow-based routing scenarios utilizing the developed pipeline are proposed.

Boiling flow patterns and dry-out characteristics of R-1234ze(E) in a plate heat exchanger

ABSTRACT In this study, boiling flow patterns and dry-out characteristics of R-1234ze(E) in a plate heat exchanger (PHE) are investigated through visualizations and surface temperature measurements. The boiling flow patterns in the PHE are classified into three regimes by reflecting an evident flow direction and intermittent flooding (IF): rough liquid film flow, pulsating annular flow, and steady annular flow. Boiling mechanisms in the liquid-preferred and vapor-preferred paths are analyzed in a single channel. A boiling flow pattern map of R-1234ze(E) in the PHE is developed in terms of liquid and vapor superficial momentums, and the criteria for the transitions of the flow regimes are proposed to provide a reference for predicting flow characteristics during phase changes. Based on the measured surface temperatures, the partial dry-out is observed at medium to high vapor qualities in the center of the vapor-preferred path owing to the lack of the liquid phase. In addition, the relationships between the IF, partial dry-out, and heat transfer coefficients are comprehensively analyzed with physical interpretations.

Mathematical Modeling of Lymph Flow in a network of Lymphatic Vessels

IntroductionLymphatic system is an important part of the circulation system. Assessment of alterations in lymphatic flow in diseased conditions could lead to better treatment strategies. In vivo determination of the flow and pressure in the lymphatic vessels can be challenging. Computational modeling can be used to simulate the lymph flow in silico. The goal of this study was to develop a platform whereby the lymphatic flow in a network of vessels can be simulated. The mathematical model was based on animal experiments.MethodsWe conducted swine experiments whereby the connections between lymphatic vessels in the hind limb were visualized. The length and dimeter of the vessels were also determined from animal experiments. Finite element (FE) method was used to discretize one dimensional lymph flow equations. The lymph vessels were considered as extensible cylinders where the relation between pressure drop and flow was based on experimental data. Also, for valves, the relation between pressure drop and flow was based on experimental data. At junctions we assumed pressure drop is negligible and the flow in the proximal vessel is equal to the sum of flow in distal vessels. The inflow velocities at the distal vessels and the pressure at the proximal vessel were used as boundary conditions. We conducted a time‐dependent analysis where the initial conditions were obtained from a steady state solution.Results and DiscussionWhen number of the elements and time steps were increased the solution converged. For a steady‐state rigid vessel, the results were in agreement with the Poiseuille's law. Also, for a branch with rigid vessels the results were in agreement with analytical solutions. For models with extensible vessels, the computed pressure and velocities corresponded to the experimental data. The platform was applicable to junctions with different number of vessels. Because the dimension of lymphatic vessels is noticeably small, measurement of diameters, flow and pressure is challenging, which limits the data that can be fed to the numerical model. As a future direction, this platform could be used to predict flow characteristics in different disease conditions, and possibility to perform more efficient amputations.ConclusionComputational modeling was utilized to simulate flow and pressure in lymphatic vessels. There are limitations in measurements of flow characteristics in the lymphatic vessels. Our computational framework could be used to better understanding of lymphatic system functionality in health and disease, and to simulate outcomes which are difficult to determine experimentally.Support or Funding InformationThis work was supported by the Office of the Assistant Secretary of Defense for Health Affairs, through the Defense Medical Research and Development Program under Award No. W81XWH‐19‐1‐0087. Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the Department of Defense