Transitional and Turbulent Flow Modeling in a Tesla Valve

2013 ◽  
Author(s):  
Scott M. Thompson ◽  
Tausif Jamal ◽  
Basil J. Paudel ◽  
D. Keith Walters
Keyword(s):  
Experimental Data ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Flow Speed ◽  
Flow Modeling ◽  
Ansys Fluent ◽  
Local Flow ◽  
Turbulent Characteristics ◽  
Minor Losses ◽  
Tesla Valve

A Tesla valve is a fluidic dioide that may be used in a variety of mini/micro channel applications for passive flow rectification and/or control. The valve’s effectiveness is quantified by the diodicity, which is primarily governed by the incoming flow speed, its design and direction-dependent minor losses throughout its structure during forward and reverse flows. It has been previously shown that the Reynolds number at the valve inlet is not representative of the entire flow regime throughout the Tesla structure. Therefore, pure-laminar solving methods are not necessarily accurate. Local flow instabilities exist and exhibit both transitional and turbulent characteristics. Therefore, the current investigation seeks to identify a suitable RANS-based flow modeling approach to predict Tesla valve diodicity via three-dimensional (3D) computational fluid dynamics (CFD) for inlet Reynolds numbers up to Re = 2,000. Using ANSYS FLUENT (v. 14), a variety of models were employed, including: the Realizable k-ε, k-kL-ω and SST k-ω models. All numerical simulations were validated against available experimental data obtained from an identically-shaped Tesla valve structure. It was found that the k-ε model drastically under-predicts experimental data for the entire range of Reynolds numbers investigated and cannot accurately model the Tesla valve flow. The k-kL-ω and SST k-ω models approach the experimentally-measured diodicity better than regular 2D CFD. The k-kL-ω demonstrates exceptional agreement with experimental data for Reynolds numbers up to approximately 1,500. However, both the k-kL-ω and k-ω SST models over-predict experimental data for Re = 2,000.

Measurements and Numerical Simulations of Heat Transfer and Pressure Drop in a Duct With Smooth Walls

2017 ◽  
Author(s):  
Puxuan Li ◽  
Steve J. Eckels
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Numerical Models ◽  
Convective Heat Transfer Coefficient ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Inlet Temperature ◽  
Ansys Fluent

Accurate measurements of heat transfer and pressure drop play important roles in thermal designs in a variety of pipes and ducts. In this study, the convective heat transfer coefficient was measured with a semi-local surface average based on Newton’s Law of cooling. Flow and heat transfer data for different Reynolds numbers were collected and compared in a duct with smooth walls. Pressure drop was measured with a pressure transducer from OMEGA Engineering Inc. The experimental results were compared with numerical estimations generated in ANSYS Fluent. Fluent contains the broad physical modeling capabilities needed to model heat transfer and pressure drop in the duct. Thermal conduction and convection in the three-dimensional (3D) duct are simulated together. Special cares for selecting the viscosity models and the near-wall treatments are discussed. The goal of the paper is to find appropriate numerical models for simulating heat conduction, heat convection and pressure drop in the duct with different Reynolds numbers. The relationship between the heat transfer coefficient and Reynolds numbers is discussed. Heat flux and inlet temperature measured in the experiment are applied to the boundary conditions. The study provides the unique opportunity to verify the accuracy of numerical models on heat transfer and pressure drop in ANSYS Fluent.

On the Computational Modeling of Unfluidized and Fluidized Bed Dynamics

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Lindsey C. Teaters ◽  
Francine Battaglia
Keyword(s):  
Experimental Data ◽  
Pressure Drop ◽  
Multiphase Flow ◽  
Fluidized Bed ◽  
Void Fraction ◽  
Volume Fraction ◽  
Flow Modeling ◽  
Ansys Fluent ◽  
Minimum Fluidization Velocity ◽  
Two Factors

Two factors of great importance when considering gas–solid fluidized bed dynamics are pressure drop and void fraction, which is the volume fraction of the gas phase. It is, of course, possible to obtain pressure drop and void fraction data through experiments, but this tends to be costly and time consuming. It is much preferable to be able to efficiently computationally model fluidized bed dynamics. In the present work, ANSYS Fluent® is used to simulate fluidized bed dynamics using an Eulerian–Eulerian multiphase flow model. By comparing the simulations using Fluent to experimental data as well as to data from other fluidized bed codes such as Multiphase Flow with Interphase eXchanges (MFIX), it is possible to show the strengths and limitations with respect to multiphase flow modeling. The simulations described herein will present modeling beds in the unfluidized regime, where the inlet gas velocity is less than the minimum fluidization velocity, and will deem to shed some light on the discrepancies between experimental data and simulations. In addition, this paper will also include comparisons between experiments and simulations in the fluidized regime using void fraction.

scholarly journals Three-dimensional Lagrangian Voronoï analysis for clustering of particles and bubbles in turbulence

2012 ◽  
Vol 693 ◽  
pp. 201-215 ◽  
Author(s):  
Yoshiyuki Tagawa ◽  
Julián Martínez Mercado ◽  
Vivek N. Prakash ◽  
Enrico Calzavarini ◽  
Chao Sun ◽  
...  
Keyword(s):  
Experimental Data ◽  
Isotropic Turbulence ◽  
Response Times ◽  
Three Dimensional ◽  
Voronoi Cell ◽  
Reynolds Numbers ◽  
Point Particle ◽  
Heavy Particles ◽  
Data Set ◽  
Light Particles

AbstractThree-dimensional Voronoï analysis is used to quantify the clustering of inertial particles in homogeneous isotropic turbulence using data sets from numerics in the point particle limit and one experimental data set. We study the clustering behaviour at different density ratios, particle response times (i.e. Stokes numbers $\mathit{St}$) and two Taylor–Reynolds numbers (${\mathit{Re}}_{\lambda } = 75$ and 180). The probability density functions (p.d.f.s) of the Voronoï cell volumes of light and heavy particles show different behaviour from that of randomly distributed particles, i.e. fluid tracers, implying that clustering is present. The standard deviation of the p.d.f. normalized by that of randomly distributed particles is used to quantify the clustering. The clustering for both light and heavy particles is stronger for higher ${\mathit{Re}}_{\lambda } $. Light particles show maximum clustering for $\mathit{St}$ around 1–2 for both Taylor–Reynolds numbers. The experimental data set shows reasonable agreement with the numerical results. The results are consistent with previous investigations employing other approaches to quantify the clustering. We also present the joint p.d.f.s of enstrophy and Voronoï volumes and their Lagrangian autocorrelations. The small Voronoï volumes of light particles correspond to regions of higher enstrophy than those of heavy particles, indicating that light particles cluster in higher vorticity regions. The Lagrangian temporal autocorrelation function of Voronoï volumes shows that the clustering of light particles lasts much longer than that of heavy or neutrally buoyant particles. Due to inertial effects arising from the density contrast with the surrounding liquid, light and heavy particles remain clustered for much longer times than the flow structures which cause the clustering.

Multistage Simulation by an Adaptive Finite Element Approach Using Structured Grids

1999 ◽  
Vol 121 (2) ◽  
pp. 450-459 ◽  
Author(s):  
M. Sleiman ◽  
A. Tam ◽  
M. P. Robichaud ◽  
M. F. Peeters ◽  
W. G. Habashi
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Large Scale ◽  
Three Dimensional ◽  
Mesh Adaptation ◽  
Navier Stokes ◽  
Interface Plane ◽  
Adaptive Finite Element ◽  
Local Flow ◽  
Edge Based

This paper presents the application of a three-dimensional Navier-Stokes finite element code (NS3D) in the context of turbomachinery rotor-stator multistage interaction. A mixing-plane approach is used, in which boundary conditions at a common interface plane between adjacent blade rows are iteratively adjusted to yield a flow satisfying the continuity, momentum, and energy conservation equations, in an average sense. To further improve the solutions, a mesh adaptation technique then redistributes the mesh points of the structured grid within each component, according to an a posteriori edge-based error estimate based on the Hessian of the local flow solution. This matrix of second derivatives controls both the magnitude and direction of the required mesh movement at each node, is then implemented using an edge-based spring analogy. The methodology is demonstrated for two test cases with two types of data: a well-instrumented experimental large-scale rotating rig for a second stage compressor at UTRC and an actual engine. The latter, a two-stage compressor of a turboprop, has been only tested as a single-stage configuration, because of the quality of the experimental data available. All results compare well to the data and demonstrate the utility of the approach. In Particular, the mesh adaptation shows large improvements in agreement between the calculations and the experimental data.

Unsteady Propulsor Force Prediction for Spatially and Temporally Varying Inflow

2002 ◽  
Author(s):  
Stephen A. Huyer ◽  
Stephen R. Snarski
Keyword(s):  
Experimental Data ◽  
Three Dimensional ◽  
Axial Direction ◽  
Time Varying ◽  
Massachusetts Institute Of Technology ◽  
Mean Flow ◽  
Turbulent Inflow ◽  
Turbulent Characteristics ◽  
Unsteady Force ◽  
Institute Of Technology

A method to compute unsteady propulsor forces for spatially and temporally varying inflows is presented. A propulsor flow prediction code, previously developed by the Massachusetts Institute of Technology, was modified and upgraded to account for time varying inflow and multiple blade rotations. The original code utilizes lifting surface theory and discretizes the propulsor surface as boundary elements to compute the unsteady potential flow. Experimental data characterizing the full unsteady, three-dimensional turbulent inflow to a Swirl-Induced Stator Upstream of Propulsor (SISUP) propulsor, were used as inflow boundary conditions. Experimental data recorded the periodic velocity fluctuations due to the stator wakes as well as the broadband turbulent characteristics of the inflow. Blade force, integrated shaft force, and blade pressure are computed based on the experimental inflow. The effect of periodic variations in the inflow was examined to determine the effect on unsteady blade forces. For these cases, the time mean experimental effective inflow is used and a fluctuating component is added for flow in the axial direction. This may be viewed as an effectively fluctuating freestream. Comparisons of unsteady force and radiated noise are then made with the baseline mean flow case to gauge the time-varying effects. Fluctuating velocity dramatically altered the force spectra even at frequencies different from the velocity fluctuation frequency. This modified algorithm can now be utilized to examine a wider set of time-dependent propulsor flow problems and to calculate the associated performance due to these unsteady flows.

Effects of 3-D Local Unsteadiness on Heat Transfer Prediction in Turbulated Passages

2003 ◽  
Author(s):  
Pamela A. McDowell ◽  
William D. York ◽  
D. Keith Walters ◽  
James H. Leylek
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Turbulence Model ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Navier Stokes ◽  
Successful Outcome ◽  
Small Scale ◽  
Cross Sectional ◽  
Fully Implicit

A newly developed unsteady turbulence model was used to predict heat transfer in a turbulated passage typical of turbine airfoil cooling applications. Comparison of fullyconverged computational solutions to experimental measurements reveal that accurate prediction of heat transfer coefficient requires the effects of local small-scale unsteadiness to be captured. Validation was accomplished through comparison of the time- and area-averaged Nusselt number on the passage wall between adjacent ribs with experimental data from the open literature. The straight channel had a square cross-sectional area with multiple rows of staggered and rounded-edge ribs on opposite walls that were orthogonal to the flow. Simulations were run for Reynolds numbers of 5500, 16500, and 25000. Computational solutions were obtained on a multi-block, multi-topology, unstructured, and adaptive grid, using a pressure-correction based, fully-implicit Navier-Stokes solver. The computational results include two-dimensional (2-D) and three-dimensional (3-D) steady and unsteady simulations with viscous sublayers resolved (y+ ≤ 1) on all the walls in every case. Turbulence closure was obtained using a new turbulence model developed in-house for the unsteady simulations, and a realizable k-ε turbulence model was used for the steady simulations. The results obtained from the unsteady simulations show greatly improved agreement with the experimental data, especially at realistically high Reynolds numbers. The key 3-D physics mechanisms responsible for the successful outcome include: (1) shear layer roll-up over the turbulators; (2) recirculation zones both upstream and downstream of the rib faces; and (3) reattachment regions between each rib pair. Results from the unsteady case are superior to those of the steady because they capture the aforementioned mechanisms, and therefore more accurately predict the heat transfer.

Analysis of Different Radiation Models in a Swirl Stabilized Combustor

2014 ◽  
Author(s):  
Aayush K. Sharma ◽  
Chandrachur Bhattacharya ◽  
Swarnendu Sen ◽  
Achintya Mukhopadhyay ◽  
Amitava Datta
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Computational Study ◽  
Radiation Heat Transfer ◽  
Three Dimensional ◽  
Numerical Data ◽  
Ansys Fluent ◽  
Wall Functions ◽  
Radiation Modelling ◽  
Model Gas Turbine Combustor

A computational study on spray combustion, using kerosene (C12H23) as fuel, in a model gas turbine combustor has been carried out. The numerical modelling of radiation heat transfer is carried out in a three-dimensional swirl stabilized, liquid-fuelled combustor. The Favre-averaged governing equations are solved using Ansys Fluent 14.5 as the CFD package. The turbulence parameters are computed using realizable k-ε with standard wall functions model. Eulerian-Lagrangian approach is used to track stochastically the motion of the evaporation species in the continuous gas phase. The effect of different radiation models — Discrete Ordinate (DO), P1 and Discrete Transfer Radiation Model (DTRM) along with Soot are analysed in the present study. To validate the results of radiation modelling carried out in the present work, the computational results have been compared with previous experimental data for the same combustor geometry. The numerical data considering effect of soot along with radiation is shown to closely approximate the experimental data. An attempt has also been made to introduce a liner in the combustor and evaluate its effect and the heat transfer across the liner for the present numerical model.

Viscous Flow Computations on a Smooth Cylinders: A Detailed Numerical Study With Validation

2007 ◽  
Author(s):  
Guilherme Vaz ◽  
Christophe Mabilat ◽  
Remmelt van der Wal ◽  
Paul Gallagher
Keyword(s):  
Experimental Data ◽  
Viscous Flow ◽  
Numerical Study ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Navier Stokes ◽  
Detached Eddy Simulation ◽  
Time Step ◽  
Drag Forces

The objective of this paper is to investigate several numerical and modelling features that the CFD community is currently using to compute the flow around a fixed smooth circular cylinder. Two high Reynolds numbers, 9 × 104 and 5 × 105, are chosen which are in the so called drag-crisis region. Using a viscous flow solver, these features are assessed in terms of quality by comparing the numerical results with experimental data. The study involves grid sensitivity, time step sensitivity, the use of different turbulence models, three-dimensional effects, and a RANS/DES (Reynolds Averaged Navier Stokes, Detached Eddy Simulation) comparison. The resulting drag forces and Strouhal numbers are compared with experimental data of different sources. Major flow features such as velocity and vorticity fields are presented. One of the main conclusions of the present study is that all models predict forces which are far from the experimental values, particularly for the higher Reynolds numbers in the drag-crisis region. Three-dimensional and unsteadiness effects are present, but are only fully captured by sophisticated turbulence models or by DES. DES seems to be the key to better solve the flow problem and obtain better agreement with experimental data. However, its considerable computational demands still do not allow to use it for engineering design purposes.

Numerical Investigation of Multistaged Tesla Valves

2014 ◽  
Vol 136 (8) ◽  
Author(s):  
S. M. Thompson ◽  
B. J. Paudel ◽  
T. Jamal ◽  
D. K. Walters
Keyword(s):  
Reynolds Number ◽  
High Performance ◽  
Three Dimensional ◽  
Check Valve ◽  
Reynolds Numbers ◽  
Fitting Procedures ◽  
In Series ◽  
Computational Fluid Dynamics Cfd ◽  
Using Data ◽  
Tesla Valve

The Tesla valve is a passive-type check valve used for flow control in micro- or minichannel systems for a variety of applications. Although the design and effectiveness of a singular Tesla valve is somewhat well understood, the effects of using multiple, identically shaped Tesla valves in series—forming a multistaged Tesla valve (MSTV)—have not been well documented in the open literature. Therefore, using high-performance computing (HPC) and three-dimensional (3D) computational fluid dynamics (CFD), the effectiveness of an MSTV using Tesla valves with preoptimized designs was quantified in terms of diodicity for laminar flow conditions. The number of Tesla valves/stages (up to 20), valve-to-valve distance (up to 3.375 hydraulic diameters), and Reynolds number (up to 200) was varied to determine their effect on MSTV diodicity. Results clearly indicate that the MSTV provides for a significantly higher diodicity than a single Tesla valve and that this difference increases with Reynolds number. Minimizing the distance between adjacent Tesla valves can significantly increase the MSTV diodicity, however, for very low Reynolds number (Re < 50), the MSTV diodicity is almost independent of valve-to-valve distance and number of valves used. In general, more Tesla valves are required to maximize the MSTV diodicity as the Reynolds number increases. Using data-fitting procedures, a correlation for predicting the MSTV diodicity was developed and shown to be in a power-law form. It is further concluded that 3D CFD more accurately simulates the flow within the Tesla valve over a wider range of Reynolds numbers than 2D simulations that are more commonly reported in the literature. This is supported by demonstrating secondary flow patterns in the Tesla valve outlet that become stronger as Reynolds number increases. Plots of the pressure and velocity fields in various MSTVs are provided to fully document the complex physics of the flow field.

Numerical and Experimental Study of the Flow Around Two Ship Sections Side-by-Side

2014 ◽  
Author(s):  
Tufan Arslan ◽  
Jan Visscher ◽  
Bjørnar Pettersen ◽  
Helge I. Andersson ◽  
Chittiappa Muthanna
Keyword(s):  
Three Dimensional ◽  
Cross Flow ◽  
Reynolds Numbers ◽  
Ansys Fluent ◽  
Circulating Water ◽  
Eddy Simulation ◽  
Numerical Predictions ◽  
Large Eddy ◽  
Close Proximity ◽  
Cross Current

This paper reports calculations of three dimensional (3D) unsteady cross flow over two ship sections in close proximity and compares the results with measurements. The ship sections have different breadth and draft, and represent typical situations in a ship-to-ship marine operation in a cross current. The behavior of the vortex-shedding around the two different ship hull sections is investigated numerically by CFD methods and experiments. For the two sections, simulations are done for several Reynolds numbers by using the dynamic Smagorinsky Large Eddy Simulation (LES) turbulence model. Finally the cross flow past the ship sections in side-by-side position is simulated and vortex interaction between the sections is found by using the software (Ansys) FLUENT. The numerical predictions are compared with PIV results taken in a circulating water tunnel.

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