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Turbulence modeling

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SST (Menter's shear stress transport) turbulence model is a widely used and robust two-equation eddy-viscosity turbulence model used in computational fluid dynamics. The model combines the k-omega turbulence model and K-epsilon turbulence model such that the k-omega is used in the inner region of the
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In computational fluid dynamics, the k–omega (k–ω) turbulence model is a common two-equation turbulence model that is used as a closure for the Reynolds-averaged Navier–Stokes equations (RANS equations). The model attempts to predict turbulence by two partial differential equations for two variables,
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K-epsilon (k-ε) turbulence model is the most common model used in computational fluid dynamics (CFD) to simulate mean flow characteristics for turbulent flow conditions. It is a two-equation model which gives a general description of turbulence by means of two transport equations (PDEs). The original
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The Spalart–Allmaras model is a one-equation model that solves a modelled transport equation for the kinematic eddy turbulent viscosity. The Spalart–Allmaras model was designed specifically for aerospace applications involving wall-bounded flows and has been shown to give good results for boundary
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due to turbulence act in the same direction as the shear stresses produced by the averaged flow). It has since been found to be significantly less accurate than most practitioners would assume. Still, turbulence models which employ the Boussinesq hypothesis have demonstrated significant practical
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Eddy viscosity based closures cannot account for the return to isotropy of turbulence, observed in decaying turbulent flows. Eddy-viscosity based models cannot replicate the behaviour of turbulent flows in the Rapid Distortion limit, where the turbulent flow essentially behaves like an elastic
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models have significant shortcomings in complex engineering flows. This arises due to the use of the eddy-viscosity hypothesis in their formulation. For instance, in flows with high degrees of anisotropy, significant streamline curvature, flow separation, zones of recirculating flow or flows
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Boussinesq, J. (1903). Thōrie analytique de la chaleur mise en harmonie avec la thermodynamique et avec la thōrie mc̄anique de la lumi_re: Refroidissement et c̄hauffement par rayonnement, conductibilit ̄des tiges, lames et masses cristallines, courants de convection, thōrie mc̄anique de la
673: 1270:{\displaystyle \nu _{t}=\Delta x\Delta y{\sqrt {\left({\frac {\partial u}{\partial x}}\right)^{2}+\left({\frac {\partial v}{\partial y}}\right)^{2}+{\frac {1}{2}}\left({\frac {\partial u}{\partial y}}+{\frac {\partial v}{\partial x}}\right)^{2}}}} 898:. For wall-bounded turbulent flows, the eddy viscosity must vary with distance from the wall, hence the addition of the concept of a 'mixing length'. In the simplest wall-bounded flow model, the eddy viscosity is given by the equation: 881:
terms. Beyond this, most eddy viscosity turbulence models contain coefficients which are calibrated against measurements, and thus produce reasonably accurate overall outcomes for flow fields of similar type as used for calibration.
321:. In 1877 Boussinesq proposed relating the turbulence stresses to the mean flow to close the system of equations. Here the Boussinesq hypothesis is applied to model the Reynolds stress term. Note that a new proportionality constant 867:
The Boussinesq hypothesis – although not explicitly stated by Boussinesq at the time – effectively consists of the assumption that the Reynolds stress tensor is aligned with the strain tensor of the mean flow (i.e.: that the
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The Reynolds stress equation model (RSM), also referred to as second moment closure model, is the most complete classical turbulence modelling approach. Popular eddy-viscosity based models like the
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k and ω, with the first variable being the turbulence kinetic energy (k) while the second (ω) is the specific rate of dissipation (of the turbulence kinetic energy k into internal thermal energy).
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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.
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In the context of Large Eddy Simulation, turbulence modeling refers to the need to parameterize the subgrid scale stress in terms of features of the filtered velocity field. This field is called
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govern the velocity and pressure of a fluid flow. In a turbulent flow, each of these quantities may be decomposed into a mean part and a fluctuating part. Averaging the equations gives the
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use turbulent models to predict the evolution of turbulence. These turbulence models are simplified constitutive equations that predict the statistical evolution of turbulent flows.
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Mishra, Aashwin; Girimaji, Sharath (2013). "Intercomponent energy transfer in incompressible homogeneous turbulence: multi-point physics and amenability to one-point closures".
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Mishra, Aashwin; Girimaji, Sharath (2013). "Intercomponent energy transfer in incompressible homogeneous turbulence: multi-point physics and amenability to one-point closures".
149:. Turbulent flows are commonplace in most real-life scenarios. In spite of decades of research, there is no analytical theory to predict the evolution of these turbulent flows. 352: 846: 709: 1351: 738: 901: 706: 300: 267: 1038: 1444:
influenced by rotational effects, the performance of such models is unsatisfactory. In such flows, Reynolds stress equation models offer much better accuracy.
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To obtain equations containing only the mean velocity and pressure, we need to close the RANS equations by modelling the Reynolds stress term
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value. In cases with well-defined shear layers, this is likely due the dominance of streamwise shear components, so that considerable
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Absi, R. (2021) "Reinvestigating the Parabolic-Shaped Eddy Viscosity Profile for Free Surface Flows" Hydrology 2021, 8(3), 126.
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Absi, R. (2019) "Eddy Viscosity and Velocity Profiles in Fully-Developed Turbulent Channel Flows" Fluid Dyn (2019) 54: 137.
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governing turbulent flows can only be solved directly for simple cases of flow. For most real-life turbulent flows,
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Townsend, A. A. (1980) "The Structure of Turbulent Shear Flow" 2nd Edition (Cambridge Monographs on Mechanics),
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viscosity with an eddy viscosity. This can be a simple constant eddy viscosity (which works well for some free
46: 1647:"Smagorinsky, Joseph. "General circulation experiments with the primitive equations: I. The basic experiment" 1379:
layers subjected to adverse pressure gradients. It is also gaining popularity in turbomachinery applications.
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as a function of the mean flow, removing any reference to the fluctuating part of the velocity. This is the
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Spalart, Philippe R.; Allmaras, Steven R. (1992). "A one-equation turbulence model for aerodynamic flows".
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is the partial derivative of the streamwise velocity (u) with respect to the wall normal direction (y)
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The following is a brief overview of commonly employed models in modern engineering applications.
821: 269:. Its effect on the mean flow is like that of a stress term, such as from pressure or viscosity. 82: 35: 1329: 716: 1079: 1537: 1488: 681: 275: 242: 1960: 1917: 1865: 1807: 1765: 1722: 1658: 1619: 1016: 2044:
Wilcox, C. D. (1998), "Turbulence Modeling for CFD" 2nd Ed., (DCW Industries, La Cañada),
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Bradshaw, P. (1971) "An introduction to turbulence and its measurement" (Pergamon Press),
8: 2064: 1489: 1326:–omega) models and offers a relatively low cost computation for the turbulence viscosity 1964: 1921: 1869: 1843:
Modelling Turbulence in Engineering and the Environment: Second-Moment Routes to Closure
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Lumley, John; Newman, Gary (1977). "The return to isotropy of homogeneous turbulence".
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models, based on the local derivatives of the velocity field and the local grid size:
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Prandtl, Ludwig (1925). "Bericht uber Untersuchungen zur ausgebildeten Turbulenz".
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introduced the additional concept of the mixing length, along with the idea of a
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Wilcox, D. C. (2008). "Formulation of the k-omega Turbulence Model Revisited".
1711:"A Reynolds stress model of turbulence and its application to thin shear flows" 1579: 1060: 964:{\displaystyle \nu _{t}=\left|{\frac {\partial u}{\partial y}}\right|l_{m}^{2}} 895: 891: 134: 1929: 1734: 1588: 856:
In this model, the additional turbulence stresses are given by augmenting the
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was the first to attack the closure problem, by introducing the concept of
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boundary layer and switches to the k-epsilon in the free shear flow.
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have evolved over time, with most modern turbulence models given by
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Pope, Stephen. "Turbulent Flows". Cambridge University Press, 2000.
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was the first who proposed a formula for the eddy viscosity in
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flows such as axisymmetric jets, 2-D jets, and mixing layers).
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from the convective acceleration. This term is known as the
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10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2
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errors in flow-normal components are still negligible in
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John J. Bertin; Jacques Periaux; Josef Ballmann (1992),
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Smagorinsky model for the sub-grid scale eddy viscosity
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Use of mathematical models to simulate turbulent flow
1561: 49:. Unsourced material may be challenged and removed. 1539:Advances in Hypersonics: Modeling hypersonic flows 1345: 1269: 1032: 1003: 963: 885: 840: 804: 732: 700: 667: 548: 346: 294: 261: 227: 1688:30th Aerospace Sciences Meeting and Exhibit, AIAA 1495:. Cambridge: Cambridge University Press. p.  2056: 1004:{\displaystyle {\frac {\partial u}{\partial y}}} 171:Reynolds-averaged Navier–Stokes (RANS) equations 1840: 1708: 1685: 1950: 1855: 1300:The Boussinesq hypothesis is employed in the 1993: 1907: 740:is the (kinematic) turbulence eddy viscosity 1841:Hanjalić, Hanjalić; Launder, Brian (2011). 1644: 1519: 1491:Computational fluid dynamics for engineers 2014:https://doi.org/10.1134/S0015462819010014 1670: 1587: 1486: 109:Learn how and when to remove this message 2020:https://doi.org/10.3390/hydrology8030126 1044:This simple model is the basis for the " 120: 1994:Sagaut, Pierre; Cambon, Claude (2008). 1609: 2057: 1790: 1755: 1487:Andersson, Bengt; et al. (2012). 1411:SST (Menter’s Shear Stress Transport) 556:which can be written in shorthand as 356:(kinematic) turbulence eddy viscosity 1471: 47:adding citations to reliable sources 18: 13: 1709:Hanjalic, K.; Launder, B. (1972). 1245: 1237: 1222: 1214: 1173: 1165: 1135: 1127: 1111: 1105: 992: 984: 933: 925: 594: 579: 496: 474: 452: 430: 398: 383: 214: 199: 160: 14: 2081: 309: 141:is the construction and use of a 1364: 23: 1996:Homogeneous Turbulence Dynamics 1987: 1944: 1901: 1892: 1849: 1834: 1784: 1749: 886:Prandtl's mixing-length concept 34:needs additional citations for 1702: 1679: 1638: 1603: 1555: 1529: 1513: 1480: 1465: 1418:Reynolds stress equation model 1: 1453: 347:{\displaystyle \nu _{t}>0} 1645:Smagorinsky, Joseph (1963). 1562:François G. Schmitt (2007), 841:{\displaystyle \delta _{ij}} 797: 600: 489: 445: 404: 220: 7: 1520:Boussinesq, Joseph (1903). 125:A simulation of a physical 10: 2086: 1953:Journal of Fluid Mechanics 1910:Journal of Fluid Mechanics 1858:Journal of Fluid Mechanics 1715:Journal of Fluid Mechanics 1580:10.1016/j.crme.2007.08.004 710:mean rate of strain tensor 315:Joseph Valentin Boussinesq 145:to predict the effects of 1930:10.1017/s0022112077000585 1735:10.1017/S002211207200268X 814:turbulence kinetic energy 2006: 1632:10.1002/zamm.19250050212 1568:Comptes Rendus MĂ©canique 1458: 1346:{\displaystyle \nu _{t}} 733:{\displaystyle \nu _{t}} 1065:Navier–Stokes equations 167:Navier–Stokes equations 1791:Menter, F. R. (1994). 1651:Monthly Weather Review 1472:Pope, Stephen (2000). 1376:Spalart–Allmaras (S–A) 1347: 1282:subgrid-scale modeling 1271: 1034: 1005: 965: 842: 806: 734: 702: 701:{\displaystyle S_{ij}} 669: 550: 348: 296: 295:{\displaystyle R_{ij}} 263: 262:{\displaystyle R_{ij}} 229: 130: 1348: 1272: 1080:Large Eddy Simulation 1040:is the mixing length. 1035: 1033:{\displaystyle l_{m}} 1006: 966: 843: 807: 735: 703: 670: 551: 349: 297: 264: 230: 124: 58:"Turbulence modeling" 1973:10.1017/jfm.2013.343 1878:10.1017/jfm.2013.343 1612:Z. Angew. Math. Mech 1330: 1089: 1017: 978: 902: 822: 746: 717: 682: 560: 364: 325: 276: 243: 177: 43:improve this article 1965:2013JFM...731..639M 1922:1977JFM....82..161L 1870:2013JFM...731..639M 1812:1994AIAAJ..32.1598M 1770:2008AIAAJ..46.2823W 1727:1972JFM....52..609H 1663:1963MWRv...91...99S 1624:1925ZaMM....5..136P 1525:. Gauthier-Villars. 1361:–ω models use two. 960: 795: 782: 598: 583: 402: 387: 218: 203: 139:turbulence modeling 1696:10.2514/6.1992-439 1589:20.500.12210/73178 1343: 1288:Spalart–Allmaras, 1267: 1076:Joseph Smagorinsky 1050:pressure gradients 1030: 1001: 961: 946: 838: 802: 783: 770: 765: 730: 698: 665: 647: 584: 569: 546: 388: 373: 344: 292: 259: 225: 204: 189: 143:mathematical model 131: 2070:Turbulence models 1764:(11): 2823–2838. 1574:(9–10): 617–627, 1506:978-1-107-01895-2 1265: 1252: 1229: 1203: 1180: 1142: 1057:turbulence models 999: 940: 800: 764: 646: 603: 528: 510: 492: 466: 448: 407: 223: 119: 118: 111: 93: 2077: 2000: 1999: 1991: 1985: 1984: 1948: 1942: 1941: 1905: 1899: 1896: 1890: 1889: 1853: 1847: 1846: 1838: 1832: 1831: 1806:(8): 1598–1605. 1797: 1788: 1782: 1781: 1753: 1747: 1746: 1706: 1700: 1699: 1683: 1677: 1676: 1674: 1642: 1636: 1635: 1607: 1601: 1600: 1591: 1559: 1553: 1552: 1533: 1527: 1526: 1517: 1511: 1510: 1494: 1484: 1478: 1477: 1469: 1352: 1350: 1349: 1344: 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21: 20: 1995: 1989: 1956: 1952: 1946: 1913: 1909: 1903: 1894: 1861: 1857: 1851: 1842: 1836: 1803: 1800:AIAA Journal 1799: 1786: 1761: 1758:AIAA Journal 1757: 1751: 1718: 1714: 1704: 1687: 1681: 1654: 1650: 1640: 1615: 1611: 1605: 1571: 1567: 1557: 1542:, Springer, 1538: 1531: 1521: 1515: 1490: 1482: 1473: 1467: 1438: 1434: 1427: 1423: 1420: 1401: 1397: 1387: 1383: 1368: 1358: 1354: 1323: 1317: 1312: 1306: 1299: 1293: 1289: 1279: 1074: 1054: 1043: 889: 878: 874: 866: 855: 360: 355: 313: 303: 271: 164: 138: 132: 105: 96: 86: 79: 72: 65: 53: 41:Please help 36:verification 33: 1959:: 639–681. 1916:: 161–178. 1864:: 639–681. 127:wind tunnel 2065:Turbulence 2059:Categories 2050:0963605100 2040:0080166210 2030:0521298199 1618:(2): 136. 1454:References 147:turbulence 69:newspapers 1981:122537381 1886:122537381 1828:120712103 1743:122631170 1430:–epsilon) 1390:–epsilon) 1335:ν 1296:–ω models 1246:∂ 1238:∂ 1223:∂ 1215:∂ 1174:∂ 1166:∂ 1136:∂ 1128:∂ 1112:Δ 1106:Δ 1094:ν 993:∂ 985:∂ 934:∂ 926:∂ 907:ν 858:molecular 827:δ 798:¯ 722:ν 654:δ 635:− 613:ν 601:¯ 595:′ 580:′ 564:− 535:δ 518:− 497:∂ 490:¯ 475:∂ 453:∂ 446:¯ 431:∂ 414:ν 405:¯ 399:′ 384:′ 368:− 330:ν 221:¯ 215:′ 200:′ 184:ρ 181:− 1938:39228898 1598:32637068 879:absolute 875:relative 793:′ 780:′ 1961:Bibcode 1918:Bibcode 1866:Bibcode 1808:Bibcode 1766:Bibcode 1723:Bibcode 1659:Bibcode 1620:Bibcode 1523:lumi_re 1447:medium. 1441:–omega) 1404:–omega) 1357:–ε and 1304:(S–A), 1292:–ε and 890:Later, 848:is the 812:is the 708:is the 83:scholar 2048:  2038:  2028:  1979:  1936:  1884:  1826:  1741:  1596:  1546:  1503:  971:where 675:where 354:, the 85:  78:  71:  64:  56:  2007:Other 1977:S2CID 1934:S2CID 1882:S2CID 1824:S2CID 1796:(PDF) 1739:S2CID 1594:S2CID 1459:Notes 862:shear 90:JSTOR 76:books 2046:ISBN 2036:ISBN 2026:ISBN 1544:ISBN 1501:ISBN 1437:–ω ( 1426:–ε ( 1400:–ω ( 1386:–ε ( 818:and 339:> 165:The 62:news 1969:doi 1957:731 1926:doi 1874:doi 1862:731 1816:doi 1774:doi 1731:doi 1692:doi 1667:doi 1628:doi 1584:hdl 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785:v 776:i 772:v 762:2 759:1 753:= 750:k 726:t 694:j 691:i 687:S 661:j 658:i 650:k 644:3 641:2 630:j 627:i 623:S 617:t 609:2 606:= 590:j 586:v 575:i 571:v 542:j 539:i 531:k 526:3 523:2 514:) 505:i 501:x 485:j 481:v 469:+ 461:j 457:x 441:i 437:v 424:( 418:t 410:= 394:j 390:v 379:i 375:v 342:0 334:t 288:j 285:i 281:R 255:j 252:i 248:R 210:j 206:v 195:i 191:v 112:) 106:( 101:) 97:( 87:· 80:· 73:· 66:· 39:.

Index


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"Turbulence modeling"
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JSTOR
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wind tunnel
fluid dynamics
mathematical model
turbulence
The equations
CFD simulations
Navier–Stokes equations
Reynolds-averaged Navier–Stokes (RANS) equations
Reynolds stress
Joseph Valentin Boussinesq
eddy viscosity
mean rate of strain tensor
turbulence kinetic energy
Kronecker delta
molecular
shear
shear stresses
Ludwig Prandtl

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