Science topics: Fluid DynamicsTurbulence
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# Turbulence - Science topic

In fluid dynamics, turbulence or turbulent flow is a flow regime characterized by chaotic and stochastic property changes. This includes low momentum diffusion, high momentum convection, and rapid variation of pressure and velocity in space and time. Nobel Laureate Richard Feynman described turbulence as "the most important unsolved problem of classical physics."
Questions related to Turbulence
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I would like to compare theoretical and observed
1. Total energy
2. 2D energy
3. slab energy
With increasing heliocentric distance by using coupled solar wind equation and quasi-2D and NI-slab trubulence model equations by using 4th order runge kutta method.
You can go through this link https://cdaweb.gsfc.nasa.gov/
And choose your spacecraft data set
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I've seen one book and I've uploaded picture of wondering part.
(Statistical Fluid Mechanics: Mechanics of Turbulence, Volume 1, P.278)
Actually I can't understand whole part eventhough I've read it.
But I can talk main wondering point of this part.
At Eq(5. 27), we can see that RMS value is function of distance from the wall and is proportional to friction velocity which represent mean wall shear stress.
I want to know why.
Is it proved mathematically? Or just assumption by observation and intuition for turbulence?
Why RMS fluctuation is proportional to mean wall shear stress and should be determined by distance from the wall.
I want to know physical reason.
What I've guessed is below.
First thing is relation between RMS fluctuation and mean wall shear stress.
If wall shear stress is high, it means that velocity gradient is high because wall shear stress is multiplication of viscosity and velocity gradient.
And if velocity gradient is high, it means that production of turbulence is active. We can see it from both k-epsilon model and LES model.
I think this can be reason why RMS fluctuation is proportional to friction velocity which represents wall shear stress.
Second one is function of distance from the wall.
As leave away from the wall, turbulence is activated because vicinity of the wall, turbulence is suppresed by dominant molecule viscosity.
We can see it from viscous sublayer.
So as leave away from the wall, because we leave away from the viscous sublayer, production of turbulence can be more activated.
Here are my physical guess but I'm not sure. Please let me know right thing.
Thanks :)
As the distance from the wall increases, there is more space for the fluctuations to occupy. As wall shear increases, the tendency to create and sustain fluctuations in the stream increases because this is what drives the fluctuations. Here's an old paper on the subject http://dudleybenton.altervista.org/publications/A%20Turbulent%20Burst%20Model%20for%20Boundary%20Layer%20Flows%20with%20Pressure%20Gradient.pdf
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More specifically, I want the comparison in wavenumber-based power spectra, opposed to frequency-based. That would include converting multiple signals into a cross spectrum, finding the phase, and then the final conversion to wavenumber.
Extra points if it is in the field of plasma physics and magnetic signals.
I would recommend and references within. There is a reasonably extensive discussion in the first Sections including Fourier--Wavelet Comparison (with pointers to selected literature).
Best Regards
Alexander
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Hello dear Professors, Doctors, Programmers, ...
I am a PhD student and I am working on a hybrid photovoltaic/thermal (PVT) solar collector tilted at a given angle. I'm writing python (or possibly fortran) code that solves equations for heat, vorticity, turbulent energy and dissipation rate in two-dimensional transient, laminar and turbulent regime under python (or possibly Fortran ).
Indeed, the work consists in simulating the conjugate thermal transfers (conduction and convection) and the two-dimensional transitory air flow inside the sensor channel. I would like to ask for your help. If any of you have a copy of this code or a website where I can get this code, help me. Thanks.
Here is a neat python recipe regarding solving 2D heat equation numerically:
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Can anybody give a sample file for extracting turbulent energy spectrum from LES simulation in OpenFOAM. I am struggling to get it.
You can sample a fluctuating velocity from open Foam by putting a probe on appropriate spatial point (x,y,z). Then you will have a time series of a fluctuating velocity and you can use power spectral density (PSD) function of MATLAB to plot a spectrum.
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I want to verify the experiment in an article of ampofo(Experimental benchmark data for turbulent natural convection in an air filled square cavity)
it is a two-dimensional square cavity, Ra=1.58e+9, I tried various turbulence models and various grids, but they did not converge, residual up to 1e+2, Does anyone know why this is?
I think it depends on the dimensions, for small dimensions use laminar model, but for large one use k-w SST with clustering mesh near to walls
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when I tried to simulate a tesla valve with the compressible turbulent fluid flow for hydrogen (single-phase standard k-ε turbulent physic and heat transfer in fluid physic are used, and the study is stationary), I got the following error:
"Undefined value found.
- Detail: NaN or Inf found when solving linear system using SOR line."
What is the problem?
Bonjour, one of the reasons is the type of mesh implemented and the computer processor you use. To solve these types of equations your computer must be powerful. I recommend you to work with as few meshes as possible.
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Hi, i've been working on a VAWT simulation trying some models, and I want to obtain the Power Curve, how has to be the wind input?
The model in use is a icewind turbin, savonius type, working with low velocity air and high turbulence()
Rigth now Im testing the turbine with an Step function, and making some python curve smoothing, i will attach a couple of plots that im obtaining.
Should I enter just a fixed velocity, adding +1 tu each velocity and take meausures and then make an average? Or should use a ramp input function?
Hope someone can help me ,
Thanks and regards
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For a given Reynolds number, how does the Kolmogorov scale change with jet diameter of a flame?
Why do you think that the jet diameter has effects on the smallest dissipation length?
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I am trying to simulate a confined swirl premixed flame with two inhomogeneous inlets using ANSYS-Fluent (RANS). I need some recommendations for the turbulence and combustion models for this specific case. I use Methane-Air premixed mixtures with different equivalence ratios for each inlet. I may perform steady and unsteady simulations. Also, I may use a 2D or 3D model.
What about using the SST-Kw model in combination with a partially premixed model.
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hi everybodyi model a courtyard. when i add tree to model this error found:Error: Turbulence Updating got unstable **Max Change of E :247.57847 @ 3,22,13 (incl. Nest-Grids)Max Change of eps :7319.07903 @ 3,35,15 (incl. Nest-Grids)** The relax factor is 0.1, no sense in going lower !!**** There is nothing I can do from here 😞(** You will nedd to increase the model domain or the grid spacing !!** It might help, to turn of the buoyancy term on the "Advanced Settings" -Tab !!** ENVI-met will continiue form here, but will probably fail soon !!** PANIC DUMP TURB was written for your information. Maybe you can fix the problem
Hi, I got the same trouble too.. anybody knows how to fix it?
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It is admitted that the (-5/3) law of the turbulent energy spectrum in single-phase flow changes into a law around (-8/3) in bubbly flow. The fact remains that it is difficult to understand why this (-8/3) bubbly flow law remains unchanged with various void fractions and with bubbles of different sizes. It's counterintuitive, isn't it? Maybe there is a simple explanation that escapes me?
Lance and Bataille (1991) were the first to report, from their homogeneous bubbly turbulence experiments (JFM, 1991), that the (-5/3) law of the turbulent energy spectrum in single-phase flow changes into a law around (-8/3) in bubbly flow. They analyzed the spectral equation and succeeded, by simplifying it and by developing scale analysis, to explain the phenomenon. Many experimental works followed later, in particular in pipe bubbly flows, and yielded the same result : all confirmed the existence of almost (-8/3) in bubbly flow. The same for all the exprimental investigations
Dear Readers, I am pleased to announce the latest publication of our work on turbulence and interfacial transfers in bubbly flows.
On turbulence and interfacial momentum transfer in dispersed gas-liquid flows:
(8) Combined Effects of the Turbulence and Interfacial Momentum Transfer On Two-Phase Turbulent Bubbly Flows | Request PDF (researchgate.net)
Just request.
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Hello everyone,
My goal is to know how accurate is my simulation using the Wall Modeled Large Eddy Simulation (WMLES) S-omega and to calculate the total turbulent kinetic energy.
Therefore I would like to know if I'm resolving 80% of the turbulent kinetic energy with my grid and to do that I need to compute the SGS turbulent kinetic energy and compute the ratio between the resolved and total turbulent kinetic energy (k_resolved / (k_resolved + k_sgs) )
Assuming the resolved turbulent kinetic energy can be calculated by:
• k_resolved = 0.5 * (U_RMSE ^2 + V_RMSE ^2 + W_RMSE ^2 )
Is there a way to compute k_sgs using the various parameters given by Fluent ?
The turbulent parameters that Fluent has available are:
• Subgrid Turbulent Viscosity
• Subgrid Effective Viscosity
• Subgrid Turbulent Viscosity Ratio
• Subgrid Filter Length
• Effective Thermal Conductivity
• Effective Prandtl Number
• Wall Yplus
The article referenced in the Fluent user theory guide is (PDF) A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities (researchgate.net)
According to the guide, the subgrid filter length is given by the equation (4) and the subgrid turbulent viscosity is given by equation (19).
Greetings.
Depending on the type of simulation that is performed, many features appear. In the “run calculation” tab, the variables can be extrapolated, and more parameters can be added. These are located by pressing the “other/add variables” button. In case what you need does not appear, it can be accessed through the console and even perform the operations you mention. However, there are many hidden options, perhaps you can find some more information in the user guide. Remember that it is commercial software, which means that it is closed source and many of the calculations are black box, so what you are looking to calculate would be very complicated.
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Many seniors scientists are working turbulence in solar winds. They are doing research independently and giving their own theories. Is it possible to work together in close colaboration and make a concise universal theory and observational agreement on it.
Pageni@
What I feel that you first search : Turbulent and Fast Solar wind, see the group , then contact with that group and check their latest papers, select the sub area and prepare a note on what sub area or topic you want to work with some writing showing your interest and proposed idea you want to do some work with that group.
Hope , you will get response.
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Hello,
I am doing a parameter study for different grids doing wall modeled large eddy simulation for a channel flow. Could someone recommend me some papers which discuss the recommendations for such grids? I read papers which give clear recommendations but I dont find a lot why specific grids perform well. Its clear that at some point the grid is just too coarse, so I relate to fine enough grids with different aspect ration for example. I thought maybe it has to do with typical sizes of eddies in the turbulent channel flow but could not find many information about this. I know that it has much to do with the numerics used but are there also some physical reasons eg. elongated eddies in streamwise direction so that x+/y+ > 1 is reasonable? . Also I wonder about some results, eg. a 160*160*160 (x+*y+*z+) grid performing better than a way finer 40*40*40 grid in means of the mean velocity results. The simulations are carried out at Re_tau = 2000 on a finite volume code using WALE and Werner Wengle wall model.
As stated by Filippo, in my experience, comparing the velocity profile is never enough in LES, especially for implicitly filtered LES in the channel flow. For example, with certain codes and discretizations, a mass error due to the pressure discretization can directly affect the mean velocity profile and make it look good while all the other quantities would signal a completely wrong solution.
For what concerns the wall and SGS model, in my opinion, a single combination doesn't allow to really take effects apart. Also, there isn't much around on the Werner & Wengle model, which makes it more difficult to understand.
Are you using a specific code or is this an in-house solver?
More generally, you want to build confidence on your tool for this case, but you are exploring a very little portion of the parameter space that is known to strongly affect results, especially at high Re.
The main rule of thumb that I can suggest is that, because the main dynamics at the wall is due to the streamwise streaks, you don't want to represent it uncorrectly. Now, dx+ = 40 is kind of good also for a wall resolved LES so, one effect you might be observing is that your choice of completely equal grid sizes in the 3 coordinate directions is kind of altering (trough the numerics etc.) a local dynamics that is obviously anisotropic and demands a different aspect ratio for the cells. But, again, this is just a guess. There are no two LES codes that perform the same given identical conditions.
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In my study, I have two cases for CFD which I performed on Ansys Fluent,
1) oscillating flow over a solid cylinder (blunt face perpendicular to flow direction)
and
2) solid cylinder (blunt face perpendicular to flow direction) oscillating in the stationary fluid. It involves dynamic meshing.
In both of the above cases, I am using the SST k-w turbulence model for this simulation.
[ ie what should be the input value for Turbulent Kinetic Energy and Specific dissipation rate? ]
What does it means if both these values are equal to 1.0?
I have attached a graph representing drag force as a function of time [calculated from the case (2)]. I want to know what might be the possible reason for this behavior in the initial time.
My UFD (equation for velocity of moving cylinder): V = 1.0 * cos(2*3.1415*1.55*t) m/s.
The initial spike? why does this occur?
The decreasing amplitude?
What would be the expected output if this was calculated for longer time values (amplitude behavior after 5 secs)?
Fluid: incompressible (water)
calculation settings:
time-steps = 500, time-step size = 0.01 sec, maximum iterations = 500.
Meshing (element size = 1.0 mm, element shape = triangles)
Pradyumn Chiwhane I am not used to performing calculations with CFX. Researchers in my group do.
If this is the total force exerted by the fluid on the cylinder, you should in my opinion deduce the added mass force to obtain the net Drag. You may consult academic references within the following research projects:
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Hi Professionals,
I am doing the project for academic purpose and there are no right or wrong assumptions but in business if your assumptions have to based on solid ground of data and predictions.
What are the assumptions that would work of aviation industry in the next till 2050?
How should one approach business and customer value proposition in turbulences and very pierce competition and rising costs ?
Thanks and regards,
Eugine
Kindly have a look here...
Indian Aviation Industry, Aviation Sector in India, About, Analysis
Indian Aviation Industry Report
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How to calculate the turbulence velocities along three axes (x, y, z) of an airplane? The effect of turbulence is considered as disturbance to the system model. I am trying to estimate the turbulence velocities using Dryden wind model which contains power spectral density functions (There are three equations). I would like to generate the wind velocity components (u, v, w) in the body frame. Could you please tell me how to generate the wind velocity components using dryden spectral equations?
The question is clear, provided you have a certain spectral content, how to reconstruct a velocity signal? For example, that is a technique ofte used to reproduce the initial conditions in homogeneous isotropic turbulence.
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Reynolds number of a VAWT is defined as Re = (UX)/v. Savonius VAWT uses bucket diameter as X, while Darrieus VAWT uses airfoil chord length as X. However, I haven't found any formula to determine the Reynolds number of a combined (Savonius within Darrieus rotor) turbine. The lift and drag coefficients of VAWT rotors are sensitive to turbulence, hence to Reynolds number. In addition, when the radius ratio and attachment angle change, so does the Reynolds number. So, how can I figure out the combined turbine's Reynolds number?
I believe you may take average of chord length of Darrieus aerofoil and radius of Savonius bucket VAWT as characteristic length for Reynolds number calculations.
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I am simulating flow through converging nozzle with subsonic conditions. Turbulent, transient, density based implicit solver with time step size of e-5 is used. I have given 0.4 Mach as inlet velocity.
Initially the solution converges but as the simulation proceeds, it diverges. I also run another simulation with the same specification and change the inlet velocity to 0.16 mach, now the solution converges. Please help me to know why this is happening and how can i overcome it?
I am facing the same problem.
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I am currently working on Nozzle CFD analysis using ANSYS FLUENT application; I have since been able to plot some flow parameters contours and profile. Now, I am having challenges plotting the turbulence intensity contour.
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Jagdeep Singh well the viscous force - but as the Reynolds number of these large eddies is high, the amount of energy that is dissipated at this scale is very small. By far most kinetic energy is transferred to smaller scales as smaller eddies are formed from the larger ones, and at each smaller scale the contribution of energy dissipation becomes more significant until you hit the very smallest scales. Still, everywhere along the cascade dissipation is viscous - it's just insignificant at the largeeddy end.
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Dear all,
I am trying to run a Stress-Blended Eddy Simulation with a modified turbulent viscosity for the RANS part, only.
However, when I use DEFINE_TURBULENT_VISCOSITY to modify the RANS turbulent viscosity, it also modifies the LES subgrid model (what I want to avoid)...
I tried a simple if/else statement based on the value of the SBES blending function:
DEFINE_TURBULENT_VISCOSITY(user_mu_t,c,t)
{
if(SBES_BlendingFunction == 1)
{
mu_t = compute_my_RANS_mu_t(...);
}
else
{
mu_t = C_MU_T(c,t);
}
return mu_t;
}
But It does not give the expected results... I also tried to loop over cells and compute it locally but had issues with the implementation...
Any help or advices would be highly appreciated !
Leo Cotteleer use DEFINE_TURBULENT_VISCOSITY macro and after writing the UDF, you may hook it in define/model/viscous panel.To be honest, DEFINE_TURBULENT_VISCOSITY macro replaces the new definition of viscosity in turbulent model. If you would like use the default one and add some extra expression, you can do it by this macro, too. You can combine the default turbulent viscosity and others. Please find the attached manual herewith.
best regards
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Hi, I am not a physician but curious about the bipolar activity in the brain whether a focal turbulent activity and having a fixed place in the cortex or a wandering turbulent activity in the brain.
In literature is it correlated with some two polar EEG activities which have antagonist effect for the person or is it a psychological interpretation of person according to his mood for an irregular activity in the brain.
If the activity could be defined with its place and type, is it possible to distract the activity pattern through an invasive thin rod which has an electromagnetic effect to affect the electrical deviation of the neuronal activity causing bipolarity? or via wireless way such as TMS?
Thank you,
Lack of concentration is a common symptom of bipolar disorder. People with bipolar disorder find they are easily distracted or feel lost and confused whether they are at home, at work, or in school.
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Dear CFD Fellows,
Is there a decision table, diagram or software you use for turbulence model selection? What I'm looking for is not a table with information for each model, but rather a visual with decision steps such as "if the flow contains a-b-c, these models can be used". In the relevant case, after following the characteristic factors of your flow, I expect turbulence models to be proposed in the last section that can best define the flow.
Best regards,
Güven
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Hi all,
I'm planning to simulate flow past a floating body using CFD method with the main purpose of investigating its stability against hydrodynamic forces. A sketch of the problem is presented the the figure attached.
It seems that an accurate estimation of pressure field, and therefore hydrodynamic forces, is heavily dependent on correct prediction of flow topology, particularly separation and reattachment of the flow.
I'm wondering what turbulent models would best handle this problem. I would appreciate it if you provide details and specific reasoning.
Regards,
Armin
The Reynolds Stress Model is the most complete turbulence model with regards to representing turbulent flow.
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I am interested in studying haboob dust storms that occur in Middle East and Arabian Peninsula. These storms that advancing like a wall of turbulent eddies and which are caused by the thunderstorm activities in spring and summer. I would appreciate any suggestions from you before starting such a topic?
Thank you
Follow
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In 2010, Dr. Khmelnik has found the suitable method of resolving of the Navier-Stokes equations and published his results in a book. In 2021, already the sixth edition of his book was released that is attached to this question for downloading. Here it is worce to mention that the Clay Mathematics Institute has included this problem of resolving of the Navier-Stokes equations in the list of seven important millennium problems. Why the Navier-Stokes equations are very important?
I finally could check the PDF, Prof. Aleksey Anatolievich Zakharenko
Dr. Khmelnik uses a variational principle to solve the NS equation, which is very powerful indeed.
He also discusses and gives examples & a reason for turbulence.
I know that the solution of NS is a non-linear problem that involves several modes and that it depends on the source.
However, my knowledge of the foundations of NS is very limited to a few linear/non-linear problems on non-equilibrium gas dynamics& MHD solved by the method, Prof. Miguel Hernando Ibanez had.
Thank you for sharing the link. I recovered my account.
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I want to make a model for turbulence in Ansys. In the project a fan is used which is completely submerged in water. How to proceed in this situation ?
In my case, the k-w SST model works well. The application of this model, as well as comparisons with other turbulence models, can be found in
"Simulations of the aerodynamic response of circular segments with different corner angles by means of 2D URANS. Impact of turbulence modeling approaches. Eng. Appl. Comput. Fluid Mech. 12(1), 750–779 (2018)."
If you are a beginner, you can try all the turbulence models available in Ansys and check which modeling results providing you the best validation.
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I have been trying to estimate the Kolmogorov length scale in turbulent mixing layer. I was using the energy spectrum for estimating length scale, but it gives just one value for a specified time. Since the mixing layer is not isotropic, i believe the length scale varies spatially and i was wondering if anyone can help explain how to estimate these values for each point at a specified time. Any help is appreciated!!
There are standard formulas for the dissipation rate derived from TKE equation, (~products of velocity gradients). you can also estimate the dissipation rate using the local TKE production rate (assuming the TKE production rate is balanced by dissipation rate ~U'^3/l, this is a very crude approximation); you can also estimate dissipation rate using structural function and Kolmogorov 4/5 law. Pope's turbulence book has all these formulas. Which method to use depending on what information you have available.
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As the quantum detectors get more sensitivity they should be picking up fluctuations in the local gravitational potential and electromagnetic background fields of the earth. But I have not seen anyone running a detector continuously for the days or weeks or months needed to do the required correlations to trace things out. Nor, do I see anyone using time of flight (array imaging with speed of light and speed of gravity) to correlate and image and characterize sources.
For many years I have been tracking every new gravimeter design - traditional sensitive accelerometers, atom interferometer gravimeters, MEMS gravimeters, electrochemical gravimeters, electron interferometer gravimeters, Bose Einstein gravimeters, and many others. If I left out your favorite gravimeter (also gradiometer and other names), tell me and I will add it to my list.
The problem with most of them is they are too slow to sort out natural, man-made and purpose build signals. You need at least Msps (mega samples per second) which is 300 meters resolution for many global sources. But there are many ADCs (analog to digital converters) that can do Gsps (giga sps) for relatively easy correlations.
The seismometer networks pick up a small bit of gravitational noise, as do the magnetometer networks, as do many electromagnetic sensor networks. It is taking a long time for all the groups to sort out, mostly "not my job". But if there were some decent, low cost sensors that were sensitivity enough to track acceleration in real time (Gsps is real time for these sorts of things) maybe we could separate and characterize the sources.
I am writing to everyone, so some groups are very sophisticated but don't do practical things. And other groups have practical problems, but no time or resources for theory. And all the groups are struggling with sharing data and models, ideas and problems globally.
Anyway, I know there are lots of "quantum" and "condensate" and other devices out there that have noise. I am asking all the groups to share their noise and sort it out. Much of the "kT" noise is partly magnetic, partly gravitational and much human activity. It is possible to separate. But it means serious effort for global correlations. Now the radio telescope groups have "correlators" and seismic groups have their methods, and electromagnetic groups their methods, and gravitational groups their methods. But it is just one field.
Regardless. If you have noise that propagates at the speed of light and gravity, then all the other groups are picking up part, or all your signals too. If you are tracking signals propagating at acoustic speeds and particle speeds then you should also be checking the speed of light and gravity signals - because there are almost always couplings - that show up in correlations.
And, if you are one of those rare people who also check for instantaneous signals (or ones that are billions of times the speed of light scale) then there are screens and checks for those too.
But here I am particularly asking for those "quantum" groups who find analog signals in their devices when they try to reduce the size, increase the frequency, lower the temperature -- and all the thing people are doing to get to "nano", "pico", "femto", "atto", "zepto". "yocto" scale phenomena.
Please update your notes on noise. Those strong millivolt, microvolt and nanovolt signals are just the start of many levels of tracking noise sources. If you have distributed sources it looks more like diffusion than shock waves or pulses. The signal from an earthquake is going to propagate at the speed of light and gravity, but it is going to have cubic kilometers of source. It is trackable, but it needs low cost detectors of high sensitivity and high sampling rates - then the arrays can image and track the seismic waves. That is just one of many hundreds of outstanding problems that need better detectors. I am hoping some of the groups who have been pushing hard to make "quantum device" will take a few moments to look at their noise seriously and think of the practical applications and problems of using those for imaging.
The signal at a superconducting gravimeter is about 95% sun moon tidal signal. That is about +/- 1000 nanometers per second squared (nm/s2) at one sample per second (sps). And the remaining 5% is from the atmosphere and nearby water and a tiny bit of magma. There will be the usual magnetic noise and electromagnetic noise from nanoHertz to GigaHertz. But some of it is gravitational - at least it shows up as a signal in a gravimeter or gradiometer or direct gravitational potential sensor (time dilation, Mossbauer, LIGO type detectors).
A "good" gravimeter array can image the local atmospheric density, flows, radiation field. That is a strong signal. You can convert gravitational signals to magnetic units by using B = 38.7083 g, where B is in Tesla and g is in meters/second^2. The earth field, 9.8 m/s2 comes to about 379 Tesla. That is why gravity is so fine grained and powerful. And why it is so hard to make strong magnets in the fluctuating earths gravitational field.
The tidal gravitational field is fairly smooth, but it can also be turbulent. You are just as likely to see "flow noise" than "sparks" or "shocks" or "pulses". And lots of slow drifts and sudden changes of levels. It is not hard, but requires care and effort.
I have been at this for several decades. I take this unusual step of asking "anyone with noise" to contact me. If you have shielded your device from electric field variations, and done some magnetic shielding and still getting drift and variations, then it is "gravitational".
I can tell you the rough size at the surface of the earth. A lot of the "kT" noise is gravitational flow noise. It is actually moving at the speed of light and gravity but you only see the net as a slow motion. The potential is smooth and has tiny gradients. You can see the gradients fairly easily. The "grain" is about one 7 millionth the mass of the electron and the size is picometers. The ultimate grain is not as small as the Planck scale, but on the order of 10^-24 meters. For practical things it is only necessary to work at 10^-18 scale. But use them all and you don't have to stop at boundaries.
Electrons have mass, charge and magnetic moment - so they pick up electric, electromagnetic, acoustic and gravitational noise (signals if you know where it comes from). Just as electron paramagnetic resonance has advantages of higher speeds and greater sensitivity, so too does any electron or hole based device have advantages for detection and characterization of fast and tiny signals. I spent several years checking - the camera electron (or hole) wells are sensitive enough to use for detecting gravitational variations - and there are plenty of tiny escape events to work with. The same for all the memory devices - they are just small floating islands of a few electrons each. Sorting out the noise in the memory chips will help shrink those down to single electron charge levels and below.
It is possible to image the atmosphere with gravitational arrays. Since I am lumping magnetic and gravitational fields together now, that means any combinations of "gravimeters" or "magnetometers" or "electromagnetic (from nanoHertz to PetaHertz or more). Moving sensors get a synthetic aperture advantage. So if someone would boost the GRACE type satellites to monitor the motion of electrons at Gsps rates we could get clear, real time images of the earths interior. Likewise moving sensor detectors arrays for volcanoes, ocean currents, density variations, magma and other things. The "moving" can be from seismic or natural vibrations, just measure it carefully for correlations and corrections. It jinks the position of the sensor so you can use subpixel methods. Deliberate movements are fine, but random but measured ones work too.
Richard Collins, Director, The Internet Foundation
Of course you would since all named are possible local hidden variables. Quantum fluctuations are the biggest noise along with fermion spin and neutrinos, all of which would also roil the background field and would be perceived as noise.
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I have watched videos about wall function on youtube but still confused about understanding viscous sublayer, logarithmic region, and wall functions. I couldn't find relevant material. Where do I find these topics? Can someone suggest some material regarding viscous sub-layer/logarithmic region and to understand y+ (wall functions)?
I would add that the meaning of y+ is very very simple. It is nothing but that the local Reynolds number measured along a normal-to-wall direction. That is, y+=0 is the wall position and then the value increases according to y+=(u_tau/vi)*y.
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Hello, I went through the Fluent Theory Guide and other Ansys learning resources, however I couldn't find the answers to the following issues.
Let's discuss the problem on the example of a general steady RANS k-omega case.
No slip Wall
U is set to zero, k is set to zero, omega is given by a specific equation.
1. What about pressure? Does Fluent use the zeroGradient condition for pressure on a wall? It's done by default in OpenFOAM.
2. NS momentum equations are 2nd order in space, so the boundary conditions should involve the normal derivative (e.g. dUn/dn=0), if I am not mistaken ?
3. Consequently, the turbulence transport equations are 2nd order in space as well, so should their respective derivatives be specified on a wall?
Velocity Inlet
U, k and omega are specified.
5. Refering to question 2,3 - should a Neumann BC be specified for U, k, omega?
Pressure outlet
Fluent Theory guide says that all variables (apart from pressure) are extrapolated from the interior. However, that does not sound right. Imagine a highly diffusive system, wherein turbulence (or any other scalar) is diffused upstream, faster than the downstream convection. In such a case, turbulence properties at the outlet would affect the solution in the domain.
6. As a consequence, what BC are imposed for U, k, omega? Mentzer suggests "intervals" which freestream turbulence properties should be taken from. https://turbmodels.larc.nasa.gov/sst.html
Symmetry
Fluent specifies zero convective/diffusive flux across the symmetry plane.
7. We should specify a value of k and omega at the symmetry anyway... right? It has to be done in OpenFOAM...
Thank you very much for your time and effort, feel free to make a comment on that.
The boundary conditions depend on the case by case basis. It also depends on whether you are doing for incompressible flows or compressible.
Suppose you are working with incompressible flows and you have no idea about the initial pressure condition in that case you can opt for velocity inlets. In the same way if you don't have any idea about the velocity at inlet then opt for pressure inlets or mass flow inlet. If you use pressure inlet then always try to provide pressure outlet condition at the outlet. The distance between the inlet and the outlet should be enough to monitor the development of the flow. If the flow is not developed then the boundary conditions will not work for you so the geometry is also important to be understood. In such cases where you assume the the distance between inlet and outlet is very large but you provide a definite small value then try using Zero gradient boundary condition at the outlet to let the system extrapolate values from the region inside the flow domain.
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I have wind data of ten minutes interval. How can I calculate wind turbulence intensity, gust, etc. from this data, where they are prerequisite for wind turbine class selection?
To capture the real turbulence intensity in the atmospheric boundary layer, the span of the data needs to be sufficiently long to ensure the ergodicity but needs to be short enough to avoid the stochasticity of atmospheric wind conditions. The first step is to look at the entire data sequence and identify the proper window size during which the turbulence is considered to be stationary.
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I have a machine that includes a workpiece which can be considered as 1200 degree Celcius and it is rotating around its center. I have around 2.5 million mesh and the minimum orthogonal quality is 0.152. Can anyone help me? The continuity residual diverges after 2000 iterations. The machine is made up of steel my enclosure is air. I have used discrete ordinates for radiation and moving wall boundary condition for the workpiece and the angular speed is 1000 rpm. I assign 1200 degree Celcius for boundary and heat flux BC is automatically selected for its shadow. I always get the message that the turbulent viscosity ratio is limited by 1e+05 for xxx number of cells. The number fluctuates throughout the iterations. I am using the k-epsilon model for turbulence. All cell zones are selected as participants in radiation. Since radiation is activated, I am using PRESTO! for the pressure solution method. The others are set as default.
In this case, the maximum temperature should be around 1200 degrees but in TUI, it is said the temperature is limited to 3273 degrees in 3 cells on zone 16114 which is the enclosure basicallly. I have added my residuals after 4500 iterations using the k-epsilon model.
Regards.
Furkan Enes.
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In Ansys Fluent Lee Model, when turbulent viscosity problem occurs and system diverges and stopped. If the same simulation is started from the previous time step where there was no problem of turbulent viscosity or temperature or reverse flow, the simulation will start working again normally. Why is that? What is the scientific reason behind it?
How to deal with this turbulence, temperature and finally divergence problem in Lee Model? One way is to change the "to & from" frequency values (Lee Model). But if need to keep the frequency constant then how to manage turbulence, change in what parameters could solve the problem?
I think, there is no physical reason behind it and the question needs to be asked to the ANSYS Fluent developers directly.
Usually, if the "turbulent viscosity problem" occurs, than the solution process has already almost diverged and the resulting velocity field became physically meaningless (nonsens). Consequently so large velocity gradients occur, that the turbulence model starts to predict such extreme turbulent viscosities. It is rather rare, that the ANSYS Fluent solver can recover from such a solver situation and usually in the next few iterations/time steps the solver entirely diverges.
If you restart from a DAT file, where there were not yet any signs of a diverging solver, than most likely (I do not have deep insights into the Lee model implementation since I do no longer work for this company; it's more a guess from my previous experience) the solver does not store all relevant information in the DAT file which would be required for a 1:1 restart. Instead some required solver information for the continuation of the solution process needs to be recomputed or reconstructed from the primary physical values stored in the DAT file and by that the solver takes a different path in its solution route for the governing equations then before. A pure implementation error could be possible as well.
Regards,
Dr. Th. Frank.
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Can we use spectral amplitude code-optical code division multiple access (SAC-OCDMA) system in the underwater channel?
Possible answer: Since polarization is a big factor in the turbulent underwater channel so SAC-OCDMA is not a good choice. We can use unipolar code based OCDMA system instead of SAC-OCDMA system.
After researching more about SAC-OCDMA, I found that we can use it for under-water communication system since we can use incoherent sources like LED as broadband source at the transmitter side. So, with the use of zero cross-correlation code (ZCC) in SAC-OCDMA systems we have a good technology which we can use for 6G communications.
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Do not be used from the boundary layer mesh in structured mesh (ansys meshing), when the fluid flow is turbulence ?
Because it is important in the turbulent flow checking the amount Y+
Are the correct simulation results without a boundary layer mesh in structured mesh?
Thank you
In unstructured mesh, you can set the first layer height using the inflation option.
Also, in a structured mesh, you can set that using edge sizing and proper "number of divisions" and "bias factor."
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Dear friends, I am simulating spray injection in a pipe. My model is multiphase/ DPM/ K-W and the step size is 0.0001 with 350 iteration per step time. by now, I can get convergence in continuity(10e-4)/ u(10e-6)/ v(10e-5)/ w(10e-5)/ k(10e-5)/ and omg(10e-5) at about 3 time steps and it will continue till 30-35 time steps but the continuity then starts to fluctuate . I have already decreased URF ( momentum, Turbulent kinetic energy and specific dissipation rate to 0.3, 0.3, 0.3, respectively).
Any suggestion on what can I do to get continuously convergence at each time step?
I attached the text file of residuals.
Taha
my model runs for 1.5s with the time step size of 0.0001s which means 15000 time steps in total. What you mean is I have to change the time step size by checking the residuals during simulation ?
it affects my results, doesn't it?
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When a surface wave is superimposed over turbulent current, a periodic velocity fluctuation is observed and the conventional Reynolds decomposition of the velocity field is not satisfactory and phase-averaging of the velocity signal needs to perform why?
Why phase averaging is necessary for such type of flow?
Dear Professor Denaro
Thank you very much for your explanation. Yes, I am not talking about decomposition's validity, and I am fully convinced of your explanation. However, I have one more issue on my question, for e.g., the decomposition of velocity, u = u1+u2+u3, where u1, u2, and u3 are the averaged-velocity, turbulent fluctuation, and periodic wave velocity respectively. For the calculation of turbulence statistics of such flow, we have to remove wave velocity from the turbulence by ensemble phase-averaging. My concern is why this is necessary to do the phase-averaging. We can easily compute the time-averaged turbulence statistics with this wave component.
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I am working on a shell and helically coil tube heat exchanger as shown. The flow through the shell is laminar and through the coil is turbulent. Which model should I select from Fluent to solve this problem. Is it possible to differentiate the laminar and turbulent regions in fluent and then applying the models?
You can do it by
1. Split the laminar and turbulent regions manually by using the BC panel.
2. Use a transition model
for more help, you can used this link where a similar question has been asked
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I dont know i should use the laminar model or the turbulent one. I have read several papers in this regards. they have used both methods. i am totally confused which method to use.
thank you
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As the ANSYS FLUENT Theory guide mentioned, there exists a transition of Turbulent Viscosity Ratio from the minimun to the maximum and then back to the minor value again, however, in my simulation ( a circular tube with diameter of 10mm and inlet velocity of 10m/s, the fluid flow is air under the standard condition, it's obvious that the flow is turbulent), the transition phenomenon does not appear, but with the a trend of inreasing from the minimum at the near all region to the maximum in the tube center. So, can someone please explain what's wrong with my simulation ?
BEST REGARDS
The fluid which flows is air, so the velocity has big values in the cross section at your diameter. The turbulent zone is very extended to the walls. I am sure that your Reynolds number has a very big value, so the velocity distribution in the cross section is almost uniform, like for an ideal fluid. It appears normal that nothing special happends.
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I have a case, which is about internal flow with constant heat flux. Although the inlet boundary condition is laminar, the flow is passing transition and turbulent regime along the tube. As known, the intermittency term is 1 (so, admitted as turbulent inlet BC) for freestream velocity for external flow, I would like to learn that whether using the transitional SST model by laminar inlet boundary condition in the pipe is the corrects way or not.
Best regards,
The problem I faced while using SST I need to put the value of turbulence intensity at the entrance, and if I specify it to zero then my solution does not converge.
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Hi,
I am using transient simulation in fluent. In the inlet boundary condition, I have to put the value of turbulent length scale. How can I decide it for wind turbine blade model?
Thank You.
Thank You
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Dear all,
I just saw this example in FB on the difference between laminar flow and turbulent flow. The flow from a pipe hits the sink and scattered. The flow from the pipe is characterized as laminar flow while the scattered flow is marked as turbulent.
I understood that based on the properties like unsteady, zigzag manner, random and chaotic movement the flow is described as turbulent.
But my doubt is
1)It was mentioned that Reynolds number greater than 4000. What is the characteristic length used to determine the Reynolds number? The scattered flow is not a pipe flow and it is in the basin. So we need to consider dimension of sink or diameter of tap from which it falls to determine the characteristics length?
2)The flow is no more in pipe, then how come limit of 4000 can be used. Now the flow is free atmosphere, so the limit should not be changed to 1e5 (like normal flow over airfoil)
3)I feel that this flow is PSEUDO TURBULENT flow. Am I correct in my assumption?
The very trait of turbulent flow is velocity gradient in the flow. As long as we have a velocity gradient, the flow is likely to be turbulent. By way of explanation, rather than sticking to the Reynolds number, the presence of eddies is the best indicator for turbulent flow. So in the case of your example, flow in the pipe is not experiencing velocity gradient, but when it comes to sink and scattered flow, velocity gradient is manifest. Hope it can be helpful.
Regards,
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What do you think about the further growth of gold price? Do you think that the upward trend is coming to an end? Or may be we observe a temporary turbulences caused by the US presidential elections and some other political reasons? The COVID situation is not optimistic, nor the debt problems. All such facts should cause further growth of safe asset prices...
In my opinion, if, thanks to the ongoing programs of vaccination of citizens for the SARS-CoV-2 (Covid-19) coronavirus, in a few months the majority of the planet Earth's population is vaccinated and the level of collective social immunity increases significantly, the problem of the pandemic in 2021 can be solved. In a positive pandemic scenario, the impact of the SARS-CoV-2 (Covid-19) coronavirus pandemic on economic processes will decline rapidly in the coming months. The governments of individual countries will abandon the use of lockdowns imposed on individual industries and sectors of the economy by mid-2021 at the latest and the pace of economic growth will increase quickly. By that time, a significant part of countries will come out of the recession and the government will end the application of interventionist financial instruments of public aid to economic entities as part of anti-crisis socio-economic, budget, fiscal, sectoral policies, etc. In addition, the use of interventionist monetary policy consisting in maintaining record low interest rates and the direct purchase of Treasury bonds by the central bank may also end soon. As a result, the risk of another secondary crisis, ie a debt crisis in the public finance system, will not increase significantly in most countries. In the event of a significant improvement in the economic situation and avoiding the risk of another financial crisis in 2021, the situation on the financial markets will stabilize and improve. Therefore, investing in safe assets, such as gold, some currencies, bank deposits and treasury bonds, will not be attractive. Nothing spectacular should happen on the gold market in 2021.
Have a nice day, Stay healthy! Best wishes,
Dariusz Prokopowicz
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Hi everyone,
I'm simulating a 3D turbulent pipe flow using the SST K-W turbulence model in ANSYS Fluent. Is there any quantity among the postprocessing quantities that represent "eddy size" or "eddy length scale"? If there is not such a quantity, How can I define it in Fluent?
Thank you.
You have to define for example your desired Kolmogorov scale through UDF.
Cheers,
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I know many textbooks include empirical relations between Nu, Re_x, and Pr inside a turbulent boundary layer on a flat wall.
However, I want to directly calculate h from known boundary layer information, e.g. velocity, pressure, turbulence intensity, and else.
Is there any textbook or paper I can refer to?
Sincerely, DH.
As mentioned by M.M. Hathal, for fast reasonable ansers you can use an integral method. Basic is discussed in the excellent book of A. Bejan "Heat Transfer". For more advanced models you should use a numerical model...If you do such calculations, do compare your results with simple empirical scaling laws or results of integral methods. At least: DO PRESENT YOUR RESULTS IN DIMENSIONLESS FORM! You will avoid dramatic errors and limit calculations to a minimum if you are interested in the influence of the variations of specific parameters. Good luck. Mico
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Kappa is defined as the ratio of (k=l/y), l is mixing length and y is the vertical distance in the flow filed. What does it means? How does the variation in k affect the turbulent velocity profile or turbulent characteristics and what are their physical significance in turbulent flow analysis?
Virtual Bed level (dz) or Reference bed level has got much importance in literature but what does virtual bed level in fluvial hydraulics exactly means?
Computation of the k and dz from the procedure described by Dey et al. 2012, I am getting highest regression coefficient when dz is negative. It indicates virtual bed level is above actual bed, which is physically unjustifiable. What could be the probable reasons for that?
Kappa is adimentional function then may define several ratios. Taken as function of U (velocity) and S (Slope in square root of U*) it behaves as a "State function" whereas it follows Schwatrz condition. The function value 0.382 has a special meanning because the longitudinal spreading of tracer is complete.
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qq
You cannot compensate using a large number of images, the sampling frequency of 8Hz will cut away the most relevant part of your wavenumber content...
If I understand, you get 0.42m/s of average velocity and you have water, right? What about the characteristic lenght dimension to estimate the Re number? Have you estimated the Kolmogorov frequency to evaluate where your Nyquist cut-off lie?
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Dear Experts
I am trying to solve a Turbulent water flow inside a tube with a 1cm diameter utilizing a twisted-tape as a heat transfer enhancer. I have tried the SST k-omega model as well as the RSM model in fluent, both methods show sharp vibrating behavior in residuals which lead to non-convergence.
The files are attached if find them wanting.
It would be very kind of you to guide me in resolving this issue.
Reducing the timestep of course helps the solver to obtain a converged solution, since it reduces the potential changes in flow variables from one timestep to the next.
You mentioned, that you obtained fully developed flow conditions by using a higher viscosity material (Ethylene Glycole). That is not surprising, since by that you reduced accordingly the Reynolds number of the flow. Please check, whether with that changed material and your governing flow conditions the Reynolds number is still in the range of a turbulent flow regime /Re calculation based on the hydraulic diameter of your cross section).
Regards,
Dr. Th. Frank.
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Hello,
this question is not as trivial as it may seem.
The Laminar model in Fluent/CFX is pretty stable even when the physics are not laminar at all (internal flow, Re=20k, bifurcations/pipe bends that turbulise the flow even further...)
If it were a simple direct solver, undamped turbulence (combined with a typical RANS grid and a large timestep) should cause divergence, as it is the case with icoFoam.
If you know what the "Laminar" model is based on or you have any references, please let me know.
Adrian Lungu Thomas Frank thank you for your help. I forgot to change the discretisation scheme to higher order. I have just rerun the case using higher order discretisation ( QUICK for momentum, Second Order for pressure). Now, the solution is definately unsteady.
Filippo Maria Denaro thank you for clarifying that.
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For the RANS/LES hybrid turbulence model, is it possible to theoretically determine the distribution of grid nodes, including the RANS part near the wall and the respective grids of the LES part in the turbulent core area?
Documents that analyze LES grids like this: "Grid-point requirements for large eddy simulation: Chapman’s estimates revisited" or "Grid Construction Strategies for Wall-Resolving Large Eddy Simulation and Estimates of the Resulting Number of Grid Points".
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As we know,Strehl Ratio(SR) is a measure of turbulence is a medium.How to calculate SR of a medium mathematically?
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Hi, I am currently studying turbulence theory,
and eddy viscosity keeps bothering me.
Is there any way to estimate scale of eddy viscosity?
For example, textbook proposes \nu_T ~ ul,
in which u is a characteristic turbulence velocity
and l is a characteristic turbulence length.
But, how can I know size of turbulence velocity or turbulence length?
Thank you.
Hi Donghyun,
Estimation of eddy viscosity falls in the general topic of turbulence modeling. This is quite a broad topic and the learning curve is somewhat steep. It will be helpful to take some graduate-level courses in turbulence and read some textbooks (e.g., Wilcox's <Turbulence modeling for CFD>, Lumley's <A First Course in Turbulence>, Pope's <Turbulent Flows>, among many others) as a first step.
Regarding your question, the answer depends on how accurate the estimation is:
• Rough estimation, pen-paper level
This scenario corresponds to the mixing length model with prescribed u and l, as well as the more recent k-epsilon model with prescribed k and epsilon. k can be measured by dynamic velocity probes with a post-process of Reynolds/Favre-averaging. Epsilon can be calculated either from the measured energy spectrum of turbulence, or from the estimated turbulence length scale l (e.g., 22% of boundary layer thickness, and many other rules of thumb).
It is not possible to estimate eddy viscosity without knowing k and epsilon/l (either by measurement or by empiricism, the latter depends on the case of interest and the engineering experience). Once k and epsilon/l are known, the following calculator can be used:
Such a level of estimation is routinely practiced by CFD engineers in order to prescribe the boundary conditions for turbulence models.
• Reasonably accurate for engineering purposes, requires an iterative process of RANS CFD
In real-world problems, turbulence quantities (e.g., nut, k, epsilon) have different values in the flow domain. To predict the turbulence field, RANS CFD with a turbulence model of one or more transport equations is needed. The transport equations of turbulence quantities have advection, diffusion, production and destruction terms just like the one governing the conservation of mass, momentum and energy. However, it should be kept in mind that a transport equation for some turbulence quantities (e.g., epsilon) is not physically sound since there is no conservation law behind it. That is the main reason for calling it a model rather than pure physics.
The most popular turbulence models for engineering applications are SA and SST. One can always learn something new from reading its original papers (DOI: 10.2514/6.1992-439; DOI: 10.2514/3.12149). One of the keys of the models is the scaling of eddy viscosity with the wall distance in wall-attached flows (e.g., nut~S d**2). The following YouTube videos will be a good start of learning these models:
• Is there a ground-truth value of eddy viscosity?
The concept of eddy viscosity is proposed along with the Boussinesq assumption, which assumes a linear correlation between the Reynolds stress tensor and the traceless mean strain rate tensor. It provides a means of predicting the Reynolds stress components. While we do have a ground-truth value for the Reynolds stress components by DNS or measurements, it may not convert to the ground-truth value of eddy viscosity since the conversion is based on the Boussinesq assumption. You may find useful discussions about the limit of Boussinesq assumption in real-world problems from Wilcox’s book. In other words, an estimation of eddy viscosity for 100% accuracy does not exist – there is even no ground-truth value for eddy viscosity.
If a high resolution of the turbulent phenomena is of high interest, then scale-resolving methods (e.g., DNS, LES) are preferred over RANS. The former resolves the turbulent fluctuation directly with minimal effects of modeling. These approaches are commonly used in combustion/heat transfer applications where the turbulent mixing effect is crucial to the problem.
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I am trying to plot BER vs transmit power for BPSK modulation under the Malaga Turbulence channel, and In my simulation result, I observe that for a fixed value of power, BER is increasing with increasing propagation distance.
@ Md. Imtiaz Ahmed
As the propagation distance increases, the optical signal carrying information experiences more signal power loss due to atmospheric attenuation effects expressed in dB/km. This results in a weak received optical signal and makes it difficult for the demodulator units to reliably intercept the information. Thus, the BER increases.
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I am trying to validate the experimental results from a paper but I am not able to replicate the profile of turbulence intensity in the domain. I have explained the entire problem statement in the following word documents and also attached the relevant UDF and papers. It would be really helpful if anyone could give some insights as to how I could change my UDF/simulation setup in order to get accurate results. Thank you.
There are a few parameters missing from your udf,
You can get it from the udf attached below.
This worked with the test condition I have used.
Cheers
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Hello,
I am starting to simulate DNS simulation of Decaying Homogeneous Isotropic Turbulence in a periodic cube.
After going through some of papers I have noticed that in almost every paper people address usage of Rogallo's procedure for generating initial divergence free velocity field for this type of problems.
Can anybody please explain what is Rogallo's procedure and how it is implemented?
Any kind of feedback will be of great help!!
Thank you.
Prof. RS Cant's document attached here has good info on the implementation issues.
I think the magnitude of velocities is less because of factor (nx*ny*nz ie total number of grid points) that needs to be added after inverse transform. Check energy content of Fourier space and real space after this.
I also wrote a program in Matlab and obtained a turbulent field. It lacks zero-divergence feature that is so essential. It causes fluctuations in Urms is this field is allowed to decay with time. I'm attaching the program as well.
It will be helpful if anybody can comment on this.
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UPD (29/08/2018): Is the RANS/LES way of turbulence modeling a converging process, i.e. will it hypothetically converge to a hypothetical big but single PDE system? Or will it inevitably disassemble into several non-overlapping PDE systems/approaches each of which is valid only for a certain turbulent regime?
After more than 5 decades of active search, it seems that the hierarchy of moment equations for the Reynolds stress and higher moments derived from the Navier-Stokes equations does not have a universal closure that could be applied to more or less wide range of flows. Numerous closures have been proposed since then. All of them contain heuristic arguments which are usually changed from case to case. So, does it mean that our understanding of turbulence will never be complete? Or do people still believe that a “magic closure” exists which can explain everything?
Completely agree with you in the computational context, not for the real-world scenarios. What I mean is somehow deal with the butterfly effect which implies even the farthest smallest decimals may have a role to play in the holistic simulation of turbulence like in nature.
Regards,
Hamed
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Dear All,
I am trying to visualize vortices of the CFD simulation and for this purpose I use the lambda2 criterion but I faced a problem with this method: there are big vortices and a lot of small vortices. And these small vortices spoil visual quality hiding big vortices for ANY VALUE of the lambda2 ISOSURFACES. How is wise to use smoothing operators before using lambda2 criterion? When I read articles in turbulence there are nice pictures without small vortices. How they achieved it?
Are there any recipes that are not written in articles?
I am using Paraview
Best regards,
Evgenii
Evgenii,
I think the word "honest" is likely to be less relevant here. I hope those articles do explain in their methods how do they get the results they show. For this particular reason I insist in many reviews to see the data and the code used, for the sake of reproducible science.
Regarding lambda2 method or any other method - all those will identify what you define - meaning that if you filter out some sizes, it is okay if it's reported, and it will specifically filter out (as suggested Filippo Maria Denaro ) the small sizes. If you smooth the result after the selection - it's also possible, again you're requested to explain it in the paper.
If you use PIV, there is a nice package called PIVMAT and if Python, we try to develop (disclaimer - I'm one of the developers) PIVMAT's clone, called PIVPy (https://github.com/alexlib/pivpy). For CFD data I do not have recommendations.
Regards
Alex
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Hello all,
I'm simulating a pulse jet engine by building a MATLAB code, in this code I need a Mixing Model. I have found Linear Eddy Mixing (LEM) Model, but it needs some turbulent quantities that has to be assumed (which is NOT practical). So, does anyone know a 1D Mixing model that can be easily implemented in such a simulation ?
Hello, I suggest you follow the generalized k-w model for matching the mixing model. you can simplify it for 1-D.
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How can the Social Cost Benefit-SCB Analysis be used in Cloud adoption? Perhaps, it is equally important as the Return on Investment-ROI?
Interesting
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Hello Everyone!!
I hope everyone doing well.
While i was studying Phenomenology and Turbulence Scaling , total energy in the system for the largest eddies was approximated to U^2/2. Where U is the Rotational velocity of largest eddies.
I ddint find how or on what basis Spectral energy was approximated to U^2/2 ?
let me know if anybody has an idea about it.
Thank you
You can find all updater articles details about turbulence via Sciencedirect here
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In heat transfer enhancement techniques, various passive techniques such as the insertion of various types of turbulators/inserts in the heat exchanger are used. How to decide the hydraulic diameter for the case in which turbulator insert is being used for calculating the Reynolds number? For the same flow rate, the Reynolds number would be different for different cases (Tube with turbulators and without turbulators). So, effectively we have two unknowns: one is flow rate and the other is the hydraulic diameter for achieving a given Reynolds number.
So, I need to know how to plot the curve of Nu Vs Re for all cases at a fixed Reynolds number value, and is there any standard formula for calculating hydraulic diameter in case of complex shapes such as louvered strip insert or twisted tape insert?
Usually the available in literature correlations are based on the Re at the inlet. The Dh is the inlet hydraulic diameter. Most of these correlations are expressed as ratio of Nu turbolaters / Nu without turbolators or so.
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I have problem in making my turbine simulation work with SST turbulence model
the other models: k-e, k-omega, BSL converge without problems
Another and similar approach would be to make a very coarse mesh solution. Due to high numerical diffusion on coarse meshes this is usually easier to converge. Than this coarse mesh SST solution could be interpolated on the productive mesh as a flow initialization. The coarse mesh could be extremely coarse for this purpose.
Regards,
Dr. Th. Frank.
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Maybe a stupid question but I wonder if this assumption has some limit that intrinsically affect the NS equations.
Just a simple example of an airfoil moving in air where the "particles" has no macroscopic velocity and, hence, no macroscopic kinetic energy (no energy other than the agitation of the molecules due to internal energy). Now consider the same airfoil in a wind tunnel where the same "particles" are accelerated and acquire macroscopi kinetic energy.
In the former case, the airfoil transfers kinetic energy to the particles, in the latter case are the particles to lose kinetic energy close to the wall. Is this mechanism (macroscopically governed by the friction) still exactly described under Galilean invariance?
I can think to the field of hypersonic flows where this is not true. So what should be the limit for the correct assumption? And should we suppose to change something in the macroscopic model of the friction? Has that some relelvance in natural transition from laminar to turbulence state?
Dear Prof. Filippo Maria Denaro, in the development of the microscopic theory of superfluidity, that is fluid motion without viscosity, the Galilean invariance assumption allowed L. Landau to carry out successfully a mathematical theory of superfluidity that explains the properties of liquid helium II at a temperature below 2.17 K.
The theory of L. Landau is based on the Galilean invariance of energy transformation and impulse. Using the Galilean invariance, he established the criterion for superfluidity, that is, the relative speed between fluid and capillary is smaller than the critical value, V < Vc . Above Vc viscosity or dissipation exists in 4He.
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I want to plot the graph of turbulence intensity vs height of domain. How to do that in Ansys cfx for steady state analysis?
On CFD-Post you need to create a line, from the bottom to the top of the domain.
Then insert a chart. On data series tab, select the line you created on location. On X axis tab, select Turbulence Kinetic Energy. On Y axis, select the vertical coordinate (Z). Then apply.
You can also export the TKE values on File -> export -> export, selecting the variables and the location (line).
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