Abstract
The application of computational fluid dynamics (CFD), particularly Large Eddy Simulation, for the modelling of buoyant turbulent plumes, has been demonstrated to be very accurate, but computationally expensive. Here a more basic, and therefore more generally practicable, approach is presented. Commercial CFD software is used to model such plumes using Reynolds-Averaged Navier-Stokes (RANS) turbulence models. A careful comparison is made between the numerical predictions and well-established results regarding the bulk properties of plumes. During this process, we are able to observe the well-known approximate Gaussian nature of the plume and achieve quantitative agreement with empirical plume spread coefficients. The use of numerical modelling allows for the investigation of the flow field and turbulence in those regions of the plume of most interest—the plume edge and near source regions. A comprehensive sensitivity study is conducted to identify the limits of applicability of this modelling approach. It is shown that the standard modelling approach of Morton, Taylor and Turner, which introduced the well-known entrainment assumption, pertains in a region well above the source region. At the plume edge, the levels of turbulence are contrasted with the value of the entrainment parameter. Finally, the effects of forcing the plumes with additional momentum at the source are considered, including the case of a pure jet. We show how these forced plumes eventually lose their momentum excess and tend to the behaviour of a pure, buoyant plume.
Similar content being viewed by others
References
Abdalla IE, Cook MJ, Hunt G (2009) Numerical study of thermal plume characteristics and entrainment in an enclosure with a point heat source. Eng Appl Comput Fluid Dyn 3(4): 608–630
ASME (2008) Procedure for estimation and reporting of uncertainty due to discretization in CFD applications. ASME J Fluids Eng 130:078001-1
Baines WD (1983) A technique for the direct measurement of volume flux of a plume. J Fluid Mech 132: 247–256
Blocken B, Stathopoulos T, Saathoff P, Wang X (2008) Numerical evaluation of pollutant dispersion in the built environment: comparisons between models and experiments. J Wind Eng Ind Aero 96(10–11): 1817–1831
Carazzo G, Kaminski E, Tait S (2006) The route to self-similarity in turbulent jets and plumes. J Fluid Mech 547: 137–148
Chu A, Kwok R, Yu K (2005) Study of pollution dispersion in urban areas using computational fluid dynamics (CFD) and geographic information system (GIS). Env Model Softw 20: 273–277
Churchill S (2000) Progress in the thermal sciences: AIChE institute lecture. AIChE J 46: 1704–1722
Combest D, Ramachandran P, Dudukovic M (2011) On the gradient diffusion hypothesis and passive scalar transport in turbulent flows. Ind Eng Chem Res 50: 8817–8823
Cook MJ, Lomas KJ (1998) Buoyancy-driven displacement flow: evaluation of two eddy viscosity turbulence models for prediction. Build Serv Eng Res Technol 19(1): 15–23
Goldberg U, Palaniswamy S, Batten P, Gupta V (2010) Variable turbulent Schmidt and Prandtl number modeling. Eng Appl Comput Fluid Mech 4(4): 511–520
Gousseau P, Blocken B, Stathopoulos T, van Heist G (2011) CFD simulation of near-field pollutant dispersion on a high-resolution grid: a case study by LES and RANS for a building group in downtown Montreal. Atmos Env 45: 428–438
Hunt GR, Kaye NG (2001) Virtual origin correction for lazy turbulent plumes. J Fluid Mech 435: 377–396
Hunt GR, Kaye NG (2005) Lazy plumes. J Fluid Mech 533: 329–338
Ji Y, Cook MJ, Hanby V (2007) CFD modelling of natural displacement in an enclosure connected to an atrium. Build Env 42: 1158–1172
Kaminski E, Tait S, Carazzo G (2005) Turbulent entrainment in jets with arbitrary buoyancy. J Fluid Mech 526: 361–376
Morton BR (1968) Turbulent structure in cumulus clouds. In: International conference on cloud physics. ICCP, Toronto
Morton BR, Taylor G, Turner J (1956) Turbulent gravitational convection from maintained and instantanous sources. Proc R Soc Lond A 234: 1–23
Pospisil J, Katolicky J, Jicha M (2004) A comparison of measurements and CFD model predictions for pollutant dispersion in cities. Sci Total Env 334–335: 185–195
Roache P. (1997) Quantification of uncertainty in computational fluid dynamics. Annu Rev Fluid Mech 29: 126–160
Rouse H, Yih C, Humphreys H (1952) Gravitational convection from a boundary source. Tellus 4: 201–210
Scase MM, Aspden A, Caulfield C (2009) The effect of sudden source buoyancy flux increases on turbulent plumes. J Fluid Mech 635: 137–169
Scase MM, Caulfield CP, Dalziel SB, Hunt J (2006) Time-dependent plumes and jets with decreasing source strengths. J Fluid Mech 563: 443–461
Shabbir A, George W (1994) Experiments on a round turbulent buoyant plume. J Fluid Mech 275: 1–32
Shih TH, Liou WW, Shabbir A, Yang Z, Zhu J (1995) A new k−ε eddy viscosity model for high Reynolds number turbulent flows. Comput Fluids 24(3): 227–238
Turner J (1973) Buoyancy effects in fluids. Cambridge monographs on mechanics and applied mathematics. Cambridge University Press, Cambridge
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hargreaves, D.M., Scase, M.M. & Evans, I. A simplified computational analysis of turbulent plumes and jets. Environ Fluid Mech 12, 555–578 (2012). https://doi.org/10.1007/s10652-012-9250-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10652-012-9250-7