https://www.cfd-online.com/W/index.php?title=Special:Contributions/Marcolovatto&feed=atom&limit=50&target=Marcolovatto&year=&month=
CFD-Wiki - User contributions [en]
2018-01-19T21:11:55Z
From CFD-Wiki
MediaWiki 1.16.5
https://www.cfd-online.com/Wiki/K-omega_models
K-omega models
2011-10-12T12:43:13Z
<p>Marcolovatto: </p>
<hr />
<div>{{Turbulence modeling}}<br />
== Introduction ==<br />
<br />
The K-omega model is one of the most commonly used [[Turbulence modeling|turbulence models]]. It is a [[Two equation models|two equation model]], that means, it includes two extra transport equations to represent the turbulent properties of the flow. This allows a two equation model to account for history effects like convection and diffusion of turbulent energy.<br />
<br />
The first transported variable is turbulent kinetic energy, <math>k</math>. The second transported variable in this case is the specific dissipation, <math>\omega</math>. It is the variable that determines the scale of the turbulence, whereas the first variable, <math>k</math>, determines the energy in the turbulence.<br />
<br />
To calculate boundary conditions for this model see [[Turbulence free-stream boundary conditions|turbulence free-stream boundary conditions]].<br />
<br />
== Common used K-omega models ==<br />
<br />
# [[Wilcox's k-omega model]]<br />
# [[Wilcox's modified k-omega model]]<br />
# [[SST k-omega model]]<br />
<br />
== Miscellaneous ==<br />
<br />
# [[Near-wall treatment for k-omega models]]<br />
<br />
[[Category:Turbulence models]]</div>
Marcolovatto
https://www.cfd-online.com/Wiki/Overset_grids
Overset grids
2011-08-29T14:12:45Z
<p>Marcolovatto: </p>
<hr />
<div>== Introduction ==<br />
A common difficulty in simulating complex fluid flow problems is that not every geometry can be well represented using a single, contiguous (structured or unstructured) grid. In many cases, different geometrical features are best represented by different grid types. One approach these difficulties is the construction of a grid system made up of blocks of overlapping structured grids. This technique is referred to as the ''Chimera'' or ''overset'' grid approach. In a full Chimera grid system, a complex geometry is decomposed into a system of geometrically simple overlapping grids. Boundary information is<br />
exchanged between these grids via interpolation of the flow variables, and many gridpoints may not be used in the solution (these points are sometimes called ''hole points''). Each block has boundary or ''fringe points'', which lie in the interior of a neighboring block (or blocks) and will require information from that containing block. The data that must be generated to successfully complete a Chimera-type calculation is not insignificant, and thus has been automated to a high degree. In very general terms, there are three steps to setting up an overset simulation:<br />
<br />
# Grid generation<br />
# Hole cutting<br />
# Determination of interpolation weights<br />
<br />
Note that in some systems, one or more (or all) of these steps may be combined. Finally, while the Chimera technique is most often associated with traditional finite volume/difference CFD codes, it can in principle be applied with other discretization schemes.<br />
<br />
== Grid generation ==<br />
Grids for an overset simulation are generally simple and structured, and are often generated hyperbolic or marching techniques. (''Add more here'')<br />
<br />
== Hole Cutting ==<br />
''Add example here''<br />
<br />
== Chimera interpolation ==<br />
Many of the tools required to compute the data required to do an overset simulation can be built upon the trilinear interpolation formula. The discussion here assumes hexahedral cells with nodal representation of flow variables available. Given a hexahedral cell formed by eight points<br />
<math>\vec{x}_1,\vec{x}_2,\ldots\vec{x}_8</math> (see figure, which needs to be redrawn), the coordinates of any point in the interior of this cell may be written as<br />
<br />
:<math><br />
\begin{matrix}<br />
\vec{x}=\vec{x}_1 & + &\left(-\vec{x}_1+\vec{x}_2\right)dj\\<br />
& + &\left(-\vec{x}_1+\vec{x}_4\right)dk\\<br />
& + &\left(-\vec{x}_1+\vec{x}_5\right)dl\\<br />
& + &\left(\vec{x}_1-\vec{x}_2-\vec{x}_4+\vec{x}_3\right)dj\ dk\\<br />
& + &\left(\vec{x}_1-\vec{x}_2-\vec{x}_4+\vec{x}_3\right)dj\ dk\\<br />
& + &\left(\vec{x}_1-\vec{x}_2-\vec{x}_5+\vec{x}_6\right)dj\ dl\\<br />
& + &\left(\vec{x}_1-\vec{x}_4-\vec{x}_5+\vec{x}_8\right)dk\ dl\\<br />
& + &\left(-\vec{x}_1+\vec{x}_2-\vec{x}_3+\vec{x}_4<br />
+\vec{x}_5-\vec{x}_6+\vec{x}_7-\vec{x}_8\right)dj\ dk\ dl,\\<br />
<br />
\end{matrix}<br />
</math><br />
<br />
(''This equation is really ugly'')<br />
<br />
where <math>dj</math>, <math>dk</math>, and <math>dl</math> are the interpolation weights and are in<br />
the interval <math>[0,1]</math>. For any boundary point <math>\vec{x}_b</math> and any cell base point <math>\vec{x}_1</math> we can solve the interpolation for for the weights. If the cell does not contain <math>\vec{x}_b</math>, then one or more of the weights will not be in the proper range. This can be used to construct a Newton-like gradient search technique. For more details, the reader is referred to the chapter by [[#References|Meakin (1999)]] and the references contained therein. In practice, the initial condition for this solution procedure is quite important. It is usually best to perform some spatial partitioning to narrow the search range.<br />
<br />
== Software ==<br />
To use the overset approach, one will generally need two software components: a preprocessing program to generate the overset data (cut holes, interpolation weights, etc.) and a compatible flow solver. <br />
<br />
=== Preprocessors ===<br />
A number of preprocessing packages have been developed, with varying levels of complexity. NASA's PEGASUS [Suhs et al 2002], which is primarily a grid joining code, takes an existing grids and prepares it for use in an overset simulation. The grid is generated separately. Another program is [http://www.na.chalmers.se/~andersp/chalmesh/chalmesh.html Chalmesh] [[#References|[Petersson (1999)]]], which generates grids and the interpolation data simultaneously. A comprehensive package, called [http://people.nas.nasa.gov/~rogers/cgt/doc/man.html Chimera Grid Tools (CGT)], has been developed (primarily by NASA employees) that is intended cover all aspects of the preprocessing , including grid generation. The CGT package includes many utilities, including PEGASUS [[#References|[Suhs et al (2002)]]], that automate most of the process of going from CAD model to simulation. Of these three packages, only Chalmesh is freely available. Unfortuately, the other two are subject to U.S. goverment export controls, and are thus not generally available (see [http://people.nas.nasa.gov/~rogers/cgt/doc/RESTRICTIONS.html here] for more on this). However, since most of the algorithms and techniques used are described in the literature, it is possible to do this sort of simulation without access to these packages. (''Commercial Packages?'')<br />
<br />
=== Solvers ===<br />
* INS2/3D<br />
* OVERFLOW<br />
* OVERTURE/OVERBLOWN<br />
* CFDSHIP-IOWA<br />
* TAU-Code (DLR)<br />
<br />
== References ==<br />
{{reference-paper|author=Meakin, Robert L.|year=1999|title=Composite Overset Structured Grids|rest=Chapter 11, Handbook of Grid Generation, CRC Press}}<br />
<br />
{{reference-paper|author=Petersson, N. Anders|year=1999|title=Hole-Cutting for Three-Dimensional Overlapping Grids|rest=SIAM Journal on Scientific Computing, Vol. 21, No. 2, pp 646-665}}<br />
<br />
{{reference-paper|author = Suhs, Norman E. and Rogers, Stuart E. and Dietz, W. E.|year=2002|title = PEGASUS 5: An Automatic Pre-Processor for Overset-Grid CFD|rest = AIAA Paper 2002-3186, AIAA 32nd Fluid Dynamics Conference, St. Louis}}<br />
<br />
== External links ==<br />
* [http://www.na.chalmers.se/~andersp/chalmesh/chalmesh.html Chalmesh]<br />
* [http://people.nas.nasa.gov/~rogers/cgt/doc/man.html Chimera Grid Tools]<br />
* [http://people.nas.nasa.gov/~rogers/pegasus/intro.html Pegasus 5]</div>
Marcolovatto
https://www.cfd-online.com/Wiki/Hall_of_fame
Hall of fame
2011-08-05T09:39:24Z
<p>Marcolovatto: </p>
<hr />
<div>This section presents short biographical sketches of the people who were the pillars in CFD. Here is an elementary list of some of these people. Please feel free to add more names to the list or research any of the names presented here and include a short sketch of their lives along with their contributions to CFD. Here is a good resource for biographies http://www-groups.dcs.st-and.ac.uk/~history/BiogIndex.html<br />
<br />
*Claude Navier<br />
*George Stokes<br />
*Daniel Bernoulli<br />
*Leonard Euler<br />
*Ludwig Prandtl<br />
*Osborne Reynolds<br />
*Theodore Von Karman<br />
*Boris Grigorievich Galerkin<br />
*John Von Neumann<br />
*Lejeune Dirichlet<br />
*D Brian Spalding (DBS or Brian to his students)<br />
*Brian Launder<br />
*Rhie C.M.(needs a first name!)<br />
*Chow W.L.(needs a first name!)<br />
*Suhas V Patankar<br />
*Milovan Peric<br />
*Andre-Louis Cholesky<br />
*Richard Courant<br />
*Kurt Friedrichs<br />
*Hans Lewy<br />
*Peter D. Lax<br />
*Burton Wendroff<br />
*Olga Ladyschenskaya<br />
*Jean Baptiste Joseph Fourier<br />
*Carl Gustav Jacob Jacobi<br />
*Nikolai Mitrofanovich Krylov<br />
*Martin Wilhelm Kutta <br />
*Carl Friedrich Gauss<br />
*Andrey Nikolaevich Kolmogorov<br />
*John Henry Michell<br />
*Ernest Oliver Tuck<br />
*John Nicholas Newman<br />
*Touvia Miloh<br />
*John V. Wehausen<br />
*Fritz Ursell<br />
*Horace Lamb<br />
*Hajime Maruo<br />
*Georg P. Weinblum<br />
*Thomas H. Havelock<br />
*Carl David TolmÃ© Runge<br />
*A.M.O. Smith<br />
*John Hess<br />
*Som D. Sharma<br />
*J. J. Stoker<br />
*Hermann Schlichting<br />
*W.C.S. Wigley<br />
*Marshall P. Tulin<br />
*Klaus W.H. Eggers<br />
*Louis Landweber<br />
*M.J. Lighthill<br />
*Tuncer Cebeci<br />
*A.A. Townsend<br />
*K. Stewartson<br />
*L. Morino<br />
*T. Inui<br />
*W. Froude<br />
*Gopal R. Shevare<br />
*Sergei K. Godunov<br />
*G.I. Taylor<br />
*G.K. Batchelor<br />
*S. Osher<br />
*R. Whitcomb<br />
*R.T. Jones<br />
*Edward Norton Lorenz (creator of Predicability and Strange Attractor thories)<br />
*Joseph Smagorinsky (developped first Large Eddy Simulation model, in 1963)<br />
<br />
<br />
<br />
<br />
<br />
<br />
......... <br><br />
''Please add all the people that made famous contributions in you area of specialization''<br />
<br />
{{stub}}</div>
Marcolovatto
https://www.cfd-online.com/Wiki/Hall_of_fame
Hall of fame
2011-08-05T09:37:20Z
<p>Marcolovatto: </p>
<hr />
<div>This section presents short biographical sketches of the people who were the pillars in CFD. Here is an elementary list of some of these people. Please feel free to add more names to the list or research any of the names presented here and include a short sketch of their lives along with their contributions to CFD. Here is a good resource for biographies http://www-groups.dcs.st-and.ac.uk/~history/BiogIndex.html<br />
<br />
*Claude Navier<br />
*George Stokes<br />
*Daniel Bernoulli<br />
*Leonard Euler<br />
*Ludwig Prandtl<br />
*Osborne Reynolds<br />
*Theodore Von Karman<br />
*Boris Grigorievich Galerkin<br />
*John Von Neumann<br />
*Lejeune Dirichlet<br />
*D Brian Spalding (DBS or Brian to his students)<br />
*Brian Launder<br />
*Rhie C.M.(needs a first name!)<br />
*Chow W.L.(needs a first name!)<br />
*Suhas V Patankar<br />
*Milovan Peric<br />
*Andre-Louis Cholesky<br />
*Richard Courant<br />
*Kurt Friedrichs<br />
*Hans Lewy<br />
*Peter D. Lax<br />
*Burton Wendroff<br />
*Olga Ladyschenskaya<br />
*Jean Baptiste Joseph Fourier<br />
*Carl Gustav Jacob Jacobi<br />
*Nikolai Mitrofanovich Krylov<br />
*Martin Wilhelm Kutta <br />
*Carl Friedrich Gauss<br />
*Andrey Nikolaevich Kolmogorov<br />
*John Henry Michell<br />
*Ernest Oliver Tuck<br />
*John Nicholas Newman<br />
*Touvia Miloh<br />
*John V. Wehausen<br />
*Fritz Ursell<br />
*Horace Lamb<br />
*Hajime Maruo<br />
*Georg P. Weinblum<br />
*Thomas H. Havelock<br />
*Carl David TolmÃ© Runge<br />
*A.M.O. Smith<br />
*John Hess<br />
*Som D. Sharma<br />
*J. J. Stoker<br />
*Hermann Schlichting<br />
*W.C.S. Wigley<br />
*Marshall P. Tulin<br />
*Klaus W.H. Eggers<br />
*Louis Landweber<br />
*M.J. Lighthill<br />
*Tuncer Cebeci<br />
*A.A. Townsend<br />
*K. Stewartson<br />
*L. Morino<br />
*T. Inui<br />
*W. Froude<br />
*Gopal R. Shevare<br />
*Sergei K. Godunov<br />
*G.I. Taylor<br />
*G.K. Batchelor<br />
*S. Osher<br />
*R. Whitcomb<br />
*R.T. Jones<br />
*Edward Norton Lorenz (creator of Predicability and Strange Attractor thories)<br />
<br />
<br />
<br />
<br />
<br />
<br />
......... <br><br />
''Please add all the people that made famous contributions in you area of specialization''<br />
<br />
{{stub}}</div>
Marcolovatto
https://www.cfd-online.com/Wiki/K-epsilon_models
K-epsilon models
2011-06-18T16:03:31Z
<p>Marcolovatto: /* References */</p>
<hr />
<div>{{Turbulence modeling}}<br />
== Introduction ==<br />
<br />
The K-epsilon model is one of the most common [[Turbulence modeling|turbulence models]], although it just doesn't perform well in cases of large adverse pressure gradients (Reference 4). It is a [[Two equation models|two equation model]], that means, it includes two extra transport equations to represent the turbulent properties of the flow. This allows a two equation model to account for history effects like convection and diffusion of turbulent energy.<br />
<br />
The first transported variable is turbulent kinetic energy, <math>k</math>. The second transported variable in this case is the turbulent dissipation, <math>\epsilon</math>. It is the variable that determines the scale of the turbulence, whereas the first variable, <math>k</math>, determines the energy in the turbulence.<br />
<br />
There are two major formulations of K-epsilon models (see [[#References|References]] 2 and 3). That of Launder and Sharma is typically called the [[Standard k-epsilon model | "Standard" K-epsilon Model]]. The original impetus for the K-epsilon model was to improve the mixing-length model, as well as to find an alternative to algebraically prescribing turbulent length scales in moderate to high complexity flows.<br />
<br />
As described in [[#References|Reference]] 1, the K-epsilon model has been shown to be useful for free-shear layer flows with relatively small pressure gradients. Similarly, for wall-bounded and internal flows, the model gives good results only in cases where mean pressure gradients are small; accuracy has been shown experimentally to be reduced for flows containing large adverse pressure gradients. One might infer then, that the K-epsilon model would be an inappropriate choice for problems such as inlets and compressors. <br />
<br />
To calculate boundary conditions for these models see [[Turbulence free-stream boundary conditions|turbulence free-stream boundary conditions]].<br />
<br />
== Usual K-epsilon models ==<br />
# [[Standard k-epsilon model]]<br />
# [[Realisable k-epsilon model]]<br />
# [[RNG k-epsilon model]]<br />
<br />
== Miscellaneous ==<br />
# [[Near-wall treatment for k-epsilon models]]<br />
<br />
==References==<br />
[1] {{reference-paper|author=Bardina, J.E., Huang, P.G., Coakley, T.J.|year=1997|title=Turbulence Modeling Validation, Testing, and Development|rest=NASA Technical Memorandum 110446}}<br />
<br />
[2] {{reference-paper|author=Jones, W. P., and Launder, B. E.|year=1972|title=The Prediction of Laminarization with a Two-Equation Model of <br />
Turbulence|rest= International Journal of Heat and Mass Transfer, vol. 15, 1972, pp. 301-314}}<br />
<br />
[3] {{reference-paper|author=Launder, B. E., and Sharma, B. I.|year=1974|title=Application of the Energy Dissipation Model of Turbulence to <br />
the Calculation of Flow Near a Spinning Disc|rest=Letters in Heat and Mass Transfer, vol. 1, no. 2, pp. 131-138}} <br />
<br />
[4] '''Wilcox, David C (1998)'''. "Turbulence Modeling for CFD". Second edition. Anaheim: DCW Industries, 1998. pp. 174.<br />
<br />
[[Category:Turbulence models]]<br />
<br />
{{stub}}</div>
Marcolovatto
https://www.cfd-online.com/Wiki/K-epsilon_models
K-epsilon models
2011-06-18T16:00:15Z
<p>Marcolovatto: /* Introduction */</p>
<hr />
<div>{{Turbulence modeling}}<br />
== Introduction ==<br />
<br />
The K-epsilon model is one of the most common [[Turbulence modeling|turbulence models]], although it just doesn't perform well in cases of large adverse pressure gradients (Reference 4). It is a [[Two equation models|two equation model]], that means, it includes two extra transport equations to represent the turbulent properties of the flow. This allows a two equation model to account for history effects like convection and diffusion of turbulent energy.<br />
<br />
The first transported variable is turbulent kinetic energy, <math>k</math>. The second transported variable in this case is the turbulent dissipation, <math>\epsilon</math>. It is the variable that determines the scale of the turbulence, whereas the first variable, <math>k</math>, determines the energy in the turbulence.<br />
<br />
There are two major formulations of K-epsilon models (see [[#References|References]] 2 and 3). That of Launder and Sharma is typically called the [[Standard k-epsilon model | "Standard" K-epsilon Model]]. The original impetus for the K-epsilon model was to improve the mixing-length model, as well as to find an alternative to algebraically prescribing turbulent length scales in moderate to high complexity flows.<br />
<br />
As described in [[#References|Reference]] 1, the K-epsilon model has been shown to be useful for free-shear layer flows with relatively small pressure gradients. Similarly, for wall-bounded and internal flows, the model gives good results only in cases where mean pressure gradients are small; accuracy has been shown experimentally to be reduced for flows containing large adverse pressure gradients. One might infer then, that the K-epsilon model would be an inappropriate choice for problems such as inlets and compressors. <br />
<br />
To calculate boundary conditions for these models see [[Turbulence free-stream boundary conditions|turbulence free-stream boundary conditions]].<br />
<br />
== Usual K-epsilon models ==<br />
# [[Standard k-epsilon model]]<br />
# [[Realisable k-epsilon model]]<br />
# [[RNG k-epsilon model]]<br />
<br />
== Miscellaneous ==<br />
# [[Near-wall treatment for k-epsilon models]]<br />
<br />
==References==<br />
[1] {{reference-paper|author=Bardina, J.E., Huang, P.G., Coakley, T.J.|year=1997|title=Turbulence Modeling Validation, Testing, and Development|rest=NASA Technical Memorandum 110446}}<br />
<br />
[2] {{reference-paper|author=Jones, W. P., and Launder, B. E.|year=1972|title=The Prediction of Laminarization with a Two-Equation Model of <br />
Turbulence|rest= International Journal of Heat and Mass Transfer, vol. 15, 1972, pp. 301-314}}<br />
<br />
[3] {{reference-paper|author=Launder, B. E., and Sharma, B. I.|year=1974|title=Application of the Energy Dissipation Model of Turbulence to <br />
the Calculation of Flow Near a Spinning Disc|rest=Letters in Heat and Mass Transfer, vol. 1, no. 2, pp. 131-138}} <br />
<br />
<br />
<br />
[[Category:Turbulence models]]<br />
<br />
{{stub}}</div>
Marcolovatto
https://www.cfd-online.com/Wiki/Near-wall_treatment_for_k-omega_models
Near-wall treatment for k-omega models
2011-06-18T12:11:24Z
<p>Marcolovatto: </p>
<hr />
<div>{{Turbulence modeling}}<br />
Both k- omega models (std and sst) are available as low-Reynolds-number models as well as high-Reynolds-number models. <br><br />
<br />
The wall boundary conditions for the k equation in the k- omega models are treated in the same way as the k equation is treated when enhanced wall treatments are used with the k- epsilon models. <br><br />
<br />
This means that all boundary conditions for <br><br />
- '''wall-function meshes''' will correspond to the wall function approach, while for the <br><br />
- '''fine meshes''', the appropriate low-Reynolds-number boundary conditions will be applied. <br><br />
<br />
In Fluent, that means:<br />
<br />
If the '''Transitional Flows option is enabled '''in the Viscous Model panel, low-Reynolds-number variants will be used, and, in that case, mesh guidelines should be the same as for the enhanced wall treatment <br><br />
''(y+ at the wall-adjacent cell should be on the order of '''y+ = 1'''. However, a higher y+ is acceptable as long as it is well inside the viscous sublayer (y+ < 4 to 5).)''<br><br />
<br />
If '''Transitional Flows option is not active''', then the mesh guidelines should be the same as for the wall functions.<br><br />
''(For [...] wall functions, each wall-adjacent cell's centroid should be located within the log-law layer, 30 < y+ < 300. A y+ value close to the lower bound '''y+ = 30''' is most desirable.)''<br />
<br />
<br><br />
<br />
Reference: <br />
FLUENT 6.2 Documentation, 2006 <br></div>
Marcolovatto