Large Eddy Simulation - Science topic

The Reynolds number UD/nu=2300 is based on a smooth circular pipe of diameter D, with STEADY mean flow velocity U and fluid of kinematic viscosity nu. Below this critical Reynolds number any perturbation due to an obstacle will not cause persistent turbulence to occur far downstream of the obstacle. Of course locally the wake of a blunt body placed in the pipe can be turbulent, but soon the flow will relaminarize if we travel further downstream. Above Re=2300 the flow does not need to be turbulent. It can be turbulent if there is a sufficiently large initial upstream perturbation. In principle the flow can remain laminar if the inlet is very smooth and care is taken to avoid vibrations. Experimentally fully developed laminar pipe flows have been achieved for Re=500. 000. It is important to realize that this critical Reynolds number does depend on the geometry of the cross-section of the channel. For a rectangular channel of height h and width w >>h, usually one considers a Reynolds number Re=Uh/nu based on the channel heigth. The critical Reynolds number for allowing turbulence is around Re=hU/nu=1100. There is however much less literature on flows through slit shaped channels than circular pipes. If you consider an open channel flow, clearly the critical Reynolds number will be quite different from Re=2300 and of course it does depend on the length scale used in the definition of this Reynolds number!

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.

Yes there is, however it depends on the DES model being used. From what I can check in the manuals:

If you use DES, DDES, IDDES you have a turbulence quantity named DES TKE Dissipation Multiplier which represent a blending function multiplying in the definition of the length scale.

If you use the SBES or SDES if you have a turbulence quantity named Shielding Function for SBES or SDES which goes from 0 to 1 depending if you are in DES or RANS, which is easier to check.

For the DES with BSL/SST or Transition SST in the Fluent Users guide 2021 R1 p1824 it is said that the function represents F_DES or F_IDDES and when F_DES >1 you're in a LES region.

I recommend also you look to 13.2.2.2 in the Users guide which helps to choose the adequate DES model.

More details about these parameters are in the Fluent Theory Guide in chapters 4.12, 4.13 and 4.14 and in Fluent Users Guide chapter 13.20.

I also would like to know if there is a more clear way to see if we're in RANS or LES region with the DES TKE Dissipation Multiplier.

First of all, what about the textbooks you are already considering to understand LES?

In general you have to consider first the idea of the evolution of LES into DES and then into DDES:

P.R. Spalart, S. Deck, M.L. Shur, K.D. Squires, M.K. Strelets, and A. Travin. A New Version of Detached-eddy Simulation, Resistant to Ambiguous Grid Densities. Theoretical and Computational Fluid Dynamics, 20(3):181–195, 2006.

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.

The answer depends on a scale of your problem. In some application there is a lot of emphasis on representation of the extremely fine details. Please see for example

In the end, it all depends on the capacity of your computer and the ability to digitize complex structures.

For a problem shown in your figure, you can represent the effect of a missing structure by appropriate parameterization of the surface roughness.

Ok, I can't stop making some practical comments.

To "Refinement in this scenario should give a converged result for the chosen filter width etc": Theoretically maybe, but not in numerical practice. If you do not fully resolve, without modelling, you have to be lucky for a simple physical behavior of the filtered/averaged part. Sometimes this holds, and/or the error is not significant, and modelling works well for some aspects of the flow.

"... admit different types of modelling strategies?": Formally yes in my view, but eventually it is always about how to view/sell the result. There are many LES modellings (SGS, or with explicit or implicit filtering, or with designing the truncation error to 'exactly' model the missing parts, or ...), and still, no one is definitely superior in numerical practice other than for the cases shown by the designers for which they know what to do. Also, the numerical implementation may play a role especially for compressible flow.

So you see, I am a DNS guy, and methods with less resolution need

be stable and can be more or less acceptable; the reasonings for the behavior varies with the method.

The late J. Ferziger (Stanford) once said: "FDs of second order with Smagorinsky is the best", at a time where higher order was used already, so he was convinced of the method he used as a well reputated specialist. The same was said by a German group one decade later, comparing 2nd and higher-order FDs in a LES journal paper. At the same it turned out however that switching-off the model yielded virtually the same results in the latter case. Oops, but this is not untypical.

Thanks Janet

Dear Sir, thank you for your reply. We have already defined the properties of the sCO2 by using Fluent Console (NIST tables for CO2 is current in the Fluent database). Although the entire graph is very reasonable, the pressure change along the flow direction is interesting as seen in the attached file. When calculated theoretically (considered friction depending on both wall shear and momentum change) by using Ansys data (wall shear stress, density, axial velocity, etc.), the pressure drop is found as expected (full decreasing along flow direction).

The turbulent flow is indeed characterized by spinning structures in the form of entangled vorticity tubes. When observing the evolution of the fluid, we can easily notice that these tubes meander, oscillate and change their connectivity in result of the process known as the vortex reconnection.

The mechanical model explaining the behaviour of the vorticity filaments was investigated by Da Rios in close collaboration with Levi-Civita. One of the first publication on the subject is available in Italian: L.S. Da Rios, Sul Moto d’un liquido indefinito con un filetto vorticoso di forma qualunque, Rend. Circ. Mat. Palermo 22 (1906) 117–135. where Da Rios derived the equations of the vortex filaments in the turbulent flow. The mechanical processes expressed in these equations answer the original question.

Levi Civitta continued work on the geometric model of turbulence, but unfortunately most of the results remained obscure for more than half a century and were only rediscovered in the 1960s. The theory is elaborated in the review article by Renzo L. Ricca (1996)

“The contributions of Da Rios and Levi-Civita to Asymptotic Potential Theory and Vortex Filament Dynamics, (Fluid Dynamics Research, vol. 18, pp 245-268).

This review also contains some references to modern publications but I think it is a good idea to familiarize yourself with the original contributions of Da Rios and Levi-Civita. It is perhaps important to mention that the renewed interest in the geometrical methods developed by these authors ultimately led to the topological fluid dynamics and to the description of turbulence based on the theory of knots (Moffat's articles are a excellent introduction to this area).

Are you looking at density variation (compressible) and phase change at super critical temperature ?

Gravitational effects in horizontal ducts are observed at very low velocities such as free-forced convection situations .

i would advise dense phase model in cfd to assess such situations.

please elaborate the problem so that we can discuss in detail.

i would suggest to look into physics so that we can choose appropriate model for analysis

Please use satellite soil moisture such as SMAP soil moisture profile data if 9 km spatial resolution is not too coarse for your study. You can also download in situ data from international soil moisture network, but only one station is available India. https://ismn.geo.tuwien.ac.at/en/data-access/

ANSYS has a good Multiphysics capabilities. I did a structural-thermal-electrical analysis in conjunction with CDF analysis. However I don't know much about electro magnetic simulation. A few Multiphysics elements are available in WB that you can have degrees of freedom in different physics. In addition to that, there is methode called "Load Transfer" that you can you use. Basically you Perform a simulation in a physic and then transfer the result to another physic. You need to identify which method is the best in your application based on a lot of parameters such as complexity, computational resources, time and etc. Hope this information helps.

LES is so wide but also so niche that, in my opinion, a course is only useful if targeting basic stuff only (but with useful insights). Once you build that background correctly, the student can go deep in the preferred direction without the risk of being messed up by the so common copy&paste sources in the field.

Also, base material is nowadays largely available on most topics. To be really useful and new on a niche topic, that material should instead include also the minimal details, including implementations. Basically, the one who prepared it should have worked on that beforehand.

You can think of a two-part course. A first, basic one, but wide enough to cover all the LES arguments, giving the correct view. And then a second one, with each lecture dedicated to a single topic.

But you see how this can easily require a huge effort, not proportionate with respect to the scope (i.e., how many students are going to be interested in, say, implementation details of inlet specification methods, or commutation error treatment, or whatever?).

Hi Maurits,

I think it is safe to say that time/ensemble averaging is never performed in an actual RANS simulation, just like explicit filtering is not (or rarely) performed in practical large-eddy simulations. It is mostly the turbulence model that makes all the difference, and provides the variables in each formulation with the proper meaning.

In RANS, the eddy viscosity is such that the velocity field obtained from the numerical solution represents (a reasonable approximation of) the time/ensemble-averaged flow field of the problem under study. Since the expected velocity field is typically smooth and often two-dimensional, considerable simplifications are allowed, including 2D domains, coarse grids, and low-order/dissipative numerics.

Francesco

Dear Shahin,

The original and dynamic Smagorinsky-Lilly models are essentially algebraic models in which subgrid-scale stresses are parameterized using the resolved velocity scales. The underlying assumption is the local equilibrium between the transferred energy through the grid-filter scale and the dissipation of kinetic energy at small subgrid scales. The subgrid-scale turbulence can be better modeled by accounting for the transport of the subgrid-scale turbulence kinetic energy.

Wall-Adapting Local Eddy-viscosity (WALE) model is designed to return the correct wall asymptotic behavior for wall bounded flows.

Here is a good paper where 3 (SGS) models are compared:

“Assessment of SubGrid-Scale Modeling for Large-Eddy Eimulation of a Spatially-Evolving Compressible Turbulent Boundary Layer”.

Regards

Have a look to this paper:

Dear Professor Ivan Kovalets,

Thanks for the answer. Data assimilation for modification of boundary conditions at the measured surface would be a great idea. I will try in this way.

Definitely you will get better results in comparison to EVM's. Through RSM you can get complete turbulence structure, since we are solving six additional transport equations for each independent components of Reynold stress. but computational cost will be high.

I suggest to have a look to the user guide (the references) but also having a look to some specific textbook about LES (for example Sagaut's book)

In the book "Turbulent Flows" by S.B. Pope (2001), the author explains non-dimensional wall units in physical terms instead of computational. The Reynolds stress at the wall must be zero, so the stress at the wall must be purely viscous (i.e. frictional). One can define a length scale for the purely viscous stress at the wall called the viscous length scale, defined as

d_v = nu*(rho/tau_w)^(1/2) = nu/u_tau, viscous length scale [m],

nu = kinematic viscosity (molecular), [m^2/s],

rho = fluid density, [kg/m^3],

tau_w = wall stress, [N/m^2],

u_tau = (tau_w/rho)^(1/2) friction velocity, [m/s],

A friction Reynolds number can be defined as

Re_tau = u_tau*d/nu, dimensionless,

d = a distance, [m],

such that if the distance is the viscous length scale d=d_v, Re_tau = 1. Non-dimensional "wall units" are x+ = x/d_v, y+=y/d_v, z+=z/d_v, so if you estimate the viscous lengthscale d_v then you can estimate normalized grid dimensions for your simulation.

The spanwise and streamwise resolution needed for turbulent boundary layer LES depends on your choice of wall model / your choice of SGS model. For incompressible LES, I recommend taking a look at the chapter on LES wall models in the book "LES for incompressible flows" by P. Saguat (2006). The author does a thorough review of the contemporary state of the art for LES wall models, and the author notes that part of the problem for LES of turbulent boundary layers is that turbulent kinetic energy is produced in the "buffer layer" just outside of the viscous sub layer in a turbulent boundary layer (Re_tau = order(1-10)). Therefore you either have to have a very fine resolution LES, like the y+=1 requirement that you stated, and/or use a wall model.

Thank professors; very interesting your comments.  Indeed, I am using  a stencil of 3x3x3. Far from boundaries, the discrete filtering is the same as other researchers have done. I used the Simpson rule to obtain the discrete representation of the convolution integral.

I did not use compact scheme, since the code was written by my advisor. Nonetheless, I have several ideas that I want to test in a more controlled problem (i.e: 1D Burger equation) with compact schemes and many other factors.

Thanks for your kindness.

You already have some tracks to follow with the first two answer, but I would like to present a different track for explaining this.

Fully resolving the NS equations (DNS) involves that you are able to resolve, with your mesh, all turbulent scales down to the smaller one: the Kolmogorov length scale. However, the latter greatly depends on the Reynolds number of your flow which explains why it is not practical (or even feasable) to solve high Re number flows using DNS.

To tackle this problem, the idea is to seperate the scales (large/small) by spacially/temporally filtering your field. That way you actually only need to have a mesh fine enough to solve the large scales, and then, model the small scales. Thus, the cost of the simulation can be greatly reduced. 

Also, I would like to support the reference suggestion from Leonardo Araujo as it is a great reference for LES. There is also a version covering compressible flows if you need.

"Large Eddy Simulation for Compressible Flows", Garnier, Eric, Adams, Nikolaus, Sagaut, P.

yes, you can use LES formulation using the dynamic SGS model (an option in ANSYS/FLUENT). However, use second order discretization (time and space) and refine the grid near the wall to ensure to have at least 3-4 nodes within y+=1

Have you though about using paraview?. I Think it is easier to do what you want. In fact I have already done that kind of post processing before and I can help you a lot.

so you produce also an adverse pressure gradient .... If your computational power is sufficient, I suggest using a wall-resolved LES and a dynamic SGS model. A mixed model is advisable

first, you did not provide details about your problem so that discussing BC.s in your setup is not possible...

In general:

1) Use dynamic SGS model, the turbulent viscosity will be determined by the flow conditions

2) Walls:Use natual BC.s for velocity if you have 3-4 grid nodes within y+<1

3) Inflow: many proposals exist, depending on your computational resource you can choose the best for you. Have a look at the Sagaut's book

COMSOL is based on Finite elements to solve equations, and LES is focused for 3D grid mesh. In this context, you need a software based on Finite volumes as OpenFOAM, ANSYS Fluent, ANSYS CFX, etc. I think you can start with OpenFOAM for a better understanding of turbulence models.

kind regards

Dear Yuli,

Thank you for sharing your experience and insights.

I hear you are advocating for closer mutli-disciplinary research.

As you are coming from the fluid dynamics community, I'd like to share some of  the experience I have had.

Research focused on hydrothermal vents, all aspects of them has become truly multidisciplinary a long time ago now, so that you may find your happiness through linking with this most active and friendly community.

In the 1990s, I was working in the UK and was hired to focus on the fluid dynamics of hydrothermal plumes with funding for about 5 years (and work for about 7 years) from NERC. The programme was called the BRIDGE programme.

The BRIDGE Community has been a most active one and brought together scientists from all disciplines. This led to considerable advances in understanding of hydrothermal vents as systems and as systems of systems and became an important crucible of frontiers'science.

In the BRIDGE Community our group at Bristol was the main one that contributed to fluid dynamics work on hydrothermal plumes (with BRIDGE funding) in my recollections. There was also one other main  group (Cambridge) which focused on trying to understand the fluid dynamics of growth of vent constructs, and had considerable expertise on hydrothermal plume modelling. Besides you will no doubt be familiar with the DAMTP (Herbert Huppert, Andy Woods, et al), who revolutionized geophysical and environmental fluid dynamics together with relatively few other groups (eg. ANU at Canberra...).

Then there was already too little fundamental fluid dynamics in the mix of hydrothermal plume research which was generally truly exciting nonetheless.

Perhaps this was because hydrothermal vent research was still in the age of discovery of most vent sites on the planet (I believe this is still the case). This has been under the great impetus of colleagues such as Chris German and fairly numerous coworkers who discovered a huge number of sites in a rather short time.

Hence much more work, it is only natural I believe, focused on discovering and documenting all the new vent sites, from all viewpoints. This is also why there is now a considerable repository of datasets which still need to be fully mined by fluid dynamics modellers who may consider teaming up with these pioneers of the deep-sea. A most exciting venture that I recommend.

The BRIDGE Programme is only a part of a much larger programme that was called "Inter-Ridge" which preceded it and continues today. The Inter-Ridge Programme has been funded by NSF in the USA and has brought, just as for BRIDGE, many communities together and greatly contributed to advancing frontiers science and generally Earth Systems science.

If one puts all this together, there is a huge amount of data available today for fluid dynamics modellers. A few modellers have been dedicated to focusing on analyses of such data and I recommend, once again, that you consider contacting these colleagues and contribute your extensive expertise in fluid mechanics to joint ventures.

In the USA, fluid dynamics modelling authorities who have focused on hydrothermal plumes include Kevin Speer, Peter Rona and Bill Lavelle.

In the UK, many colleagues at Cambridge continue to make crucial contributions. You may want to contact Harry Elderfield, Mark Rudnicki and their colleagues. Formerly Steve Sparks has also contributed important modelling aspects with Chris German. 

This could be a starting point for your exploration of potential collaborations, if you will.

Then, there are also in the Inter-Ridge community those experts who have focused on deep-sea velocity field measurements. I was hoping to hear from them. I have no doubt that evidence for "wake tornadoes" around hydrothermal plumes has already been collected long ago, but as I have not been following developments closely enough I cannot recall a particular name. These are also colleagues who may be keen to explore collaborating with you and with other fluid mechanics experts.

Traditionally in the plume in crossflow problem, the focus has been to try and understand how crossflows interact with and disperse plumes. Comparatively little attention has focused on how plumes affect cross-currents and change the whole velocity field. The wake tornadoes are an illustration of what one can find out when considering the latter angle of view.

In fluid mechanics, a classic problem is that of studying the interaction of hard obstacles in crossflows, such as cylinders or tapered cylinders. A turbulent jet or plume in a transverse crossflow is a special case where one can learn from the above provided the compliant nature of the plume is also taken into account.

When such an analysis is considered, one can account for why turbulent bent-over jets or plumes initially bifurcate (Ernst et al 1994, Bull Volcanol) and one can anticipate that bifurcation of hydrothermal plumes is common even though logistically this is difficult to document (eg. Ernst et al 2000, EPSL).

I am curious as to whether colleagues may now have documented more bifurcating hydrothermal plumes in this respect ?

When hydrothermal plumes behave as an obstacle to a crossflow, wake tornadoes are anticipated to occur and this can be regarded as an extension of vortex shedding by cylinders in crossflow to some form of vortex stretching and shedding by compliant tapered cylinders in crossflows.

I am still curious to find out if hydrothermal venting colleagues have considered this and their data accordingly ?

I shall leave you with these further réflexions.

I 'd still love to hear from Inter-Ridge colleagues.

With best regards and kind regards to all,

Gerald

Addtional to the paper above, you can have a feel about possible errors in estimatint the full EP flux and EP flux divergence based on reanalysis data sets from the followng paper:

Hua Lu, Thomas J. Bracegirdle, Tony Phillips, and John Turner, 2015: A Comparative Study of Wave Forcing Derived from the ERA-40 and ERA-Interim Reanalysis Datasets. J. Climate, 28, 2291–2311. doi: http://dx.doi.org/10.1175/JCLI-D-14-00356.1

Hello, 

I have a question similar to above question. I run LES for 1000 time steps and I save my fluent files every 100 time steps. I have 2 questions:

1. I would like to calculate turbulent dissipation rate. However, it is not available in fluent. Does anyone know how to calculate it in fluent?

2. I would like to calculate average value of a parameter lets say fluctuating velocites from those fluent files. is there a way that fluent opens all those files that I save in different time steps and take the average of those and give me the averaged value?

Thank you,

In so far as explicit LES is concerned, there are no practical obstacles to combine it with AMR. Say, set the filter length to the local size of the grid and the model will run stably. There are, however, theoretical (and thus accuracy) issues related to commutativity of filtering and differencing operations. For discussion see Marsden,  Vasilyev, and Moin, Construction of commutative filters for LES on unstructured meshes, J. Comput. Phys. 175 (2002) 584–603, and references therein.

Piotr

Here is an example of gas turbulent flow charged with solid particles.

Also is valid for gas with drops without evaporation.

It is difficult to apply LES to a flow with no disperse phase. You have to detect when the finite volume is gas or liquid. When you have gas the LES acts. When you have liquid the method attenuates by the density and viscosity.

Thanks for your reply.

I have read about the index of Resolution Quality required for LES. And it was pointed out before that a good LES is that which tends to DNS as the grid Resolution tends to the smallest scale i.e Kolmogorov scales. Therefore there is no such things as grid-Independent LES in theory, because a grid-Independent LES is essentially DNS. And therefore, the philosophy of LES loses it's meaning if it is grid Independent.

(the Advantage of LES over DNS being that LES is much more economical while it only requires the Resolution of the most energetic Eddies that determine the essential flow properties)

Hi Tamer Raef

Here is a PDF about nozzle simulation by ANSYS FLUENT.

There is nothing different practically. Theoretically there is since turbulence is always 3D

Hi Vipin

Maybe you could consider an aluminium alloy, since aluminium itself is a good conductor and would yet contribute for the parasite currents.

Good luck.

Mesoscale eddies can influence internal waves in a variety of ways. The exact effects depend on the locations you care about. For instance, near topography, particularly rough topography, where internal tides or some near-inertial oscillations can be generated, the deep-reaching mesoscale eddies can modulate the generation processes. In ocean interior, due to the change of stratification as well as of relative vorticity that are associated with the moving mesoscale eddies, the propagation and dissipation of internal waves will also be modulated. My thesis mentioned a little bit of these questions. If you are interested, it can be found in the following link: https://www.researchgate.net/publication/264860859_Influence_of_Mesoscale_Eddies_on_the_Deep_Ocean_Dynamics_Over_the_East_Pacific_Rise_near_10N

A coherent structure is a large scale vortex structure which conserves its spatial and temporal features during a  long time in comparison  with eddy timescales (typiccaly the eddy turn over time). If eddies are the core of the academic studies in turbulence, because of their role in turbulence fundamental processes as energy cascade and/or small scale intermittency (the local departure to isotropy), the coherent structures form the keystone of mechanical engineering, because they are application-dependant (aero or hydrodynamics, flow stability, large scale mixing, all these problems proceed from a better understanding of coherent structures).  Coherent structure control the mass, momentum and heat transfer at the larger scale of the cascade towards dissipation and diffusion ones. You can consider also that eddies are all embedded or intricated into themselves leading to a continuous complex medium whereas coherent structures separate the flow in distinct dynamic regions.