Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-23T09:15:09.516Z Has data issue: false hasContentIssue false

Experimental investigation of the effects of mean shear and scalar initial length scale on three-scalar mixing in turbulent coaxial jets

Published online by Cambridge University Press:  16 March 2017

W. Li
Affiliation:
Department of Mechanical Engineering, Clemson University, Clemson, SC 29634, USA
M. Yuan
Affiliation:
Department of Mechanical Engineering, Clemson University, Clemson, SC 29634, USA
C. D. Carter
Affiliation:
Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, OH 45433, USA
C. Tong*
Affiliation:
Department of Mechanical Engineering, Clemson University, Clemson, SC 29634, USA
*
Email address for correspondence: [email protected]

Abstract

In a previous study we investigated three-scalar mixing in a turbulent coaxial jet (Cai et al. J. Fluid Mech., vol. 685, 2011, pp. 495–531). In this flow a centre jet and a co-flow are separated by an annular flow; therefore, the resulting mixing process approximates that in a turbulent non-premixed flame. In the present study, we investigate the effects of the velocity and length scale ratios of the annular flow to the centre jet, which determine the relative mean shear rates between the streams and the degree of separation between the centre jet and the co-flow, respectively. Simultaneous planar laser-induced fluorescence and Rayleigh scattering are employed to obtain the mass fractions of the centre jet scalar (acetone-doped air) and the annular flow scalar (ethylene). The results show that varying the velocity ratio and the annulus width modifies the scalar fields through mean-flow advection, turbulent transport and small-scale mixing. While the evolution of the mean scalar profiles is dominated by the mean-flow advection, the shape of the joint probability density function (JPDF) was found to be largely determined by the turbulent transport and molecular diffusion. Increasing the velocity ratio results in stronger turbulent transport, making the initial scalar evolution faster. However, further downstream the evolution is delayed due to slower small-scale mixing. The JPDF for the higher velocity ratio cases is bimodal at some locations while it is always unimodal for the lower velocity ratio cases. Increasing the annulus width delays the progression of mixing, and makes the effects of the velocity ratio more pronounced. For all cases the diffusion velocity streamlines in the scalar space representing the effects of molecular diffusion generally converge quickly to a curved manifold, whose curvature is reduced as mixing progresses. The curvature of the manifold increases significantly with the velocity and length scale ratios. Predicting the observed mixing path along the manifold as well as its dependence on the velocity and length scale ratios presents a challenge for mixing models. The results in the present study have implications for understanding and modelling multiscalar mixing in turbulent reactive flows.

Type
Papers
Copyright
© 2017 Cambridge University Press 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Barlow, R. S. & Frank, J. H. 1998 Effects of turbulence on species mass fractions in methane/air jet flames. Proc. Combust. Inst. 27, 10871095.Google Scholar
Bryant, R. A., Donbar, J. M. & Driscoll, J. F. 2000 Acetone laser induced fluorescence for low pressure low temperature flow visualization. Exp. Fluids 28, 471476.CrossRefGoogle Scholar
Cai, J., Barlow, R. S., Karpetis, A. N. & Tong, C. 2010 Noise correction and length scale estimation for scalar dissipation rate measurements in turbulent partially premixed flames. Flow Turbul. Combust. 85, 309332.Google Scholar
Cai, J., Dinger, J. M., Li, W., Carter, D. C., Ryan, D. M. & Tong, C. 2011 Experimental study of three-scalar mixing in a turbulent coaxial jet. J. Fluid Mech. 685, 495531.Google Scholar
Cai, J. & Tong, C. 2009 A conditional-sampling-based method for noise and resolution corrections for scalar dissipation rate measurements. Phys. Fluids 21, 065104.CrossRefGoogle Scholar
Cai, J., Wang, D., Tong, C., Barlow, R. S. & Karpetis, A. N. 2009 Investigation of subgrid-scale mixing of mixture fraction and temperature in turbulent partially premixed flames. Proc. Combust. Inst. 32, 15171525.Google Scholar
Clemens, N. T. 2002 Flow imaging. In Encyclopedia of Imaging Science and Technology, pp. 390419. Wiley.Google Scholar
Dunn, M. J., Masri, A. & Bilger, B. W. 2007 A new piloted premixed jet burner to study strong finite-rate chemistry effects. Combust. Flame 151, 4660.Google Scholar
Hall, P. 1990 Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems. J. Multivariate Anal. 32, 177203.CrossRefGoogle Scholar
Juneja, A. & Pope, S. B. 1996 A DNS study of turbulent mixing of two passive scalars. Phys. Fluids 8, 21612184.Google Scholar
Panchapakesan, N. R. & Lumley, J. L. 1993 Turbulence measurements in axisymmetric jet of air and helium. Part 2. Helium jet. J. Fluid Mech. 246, 225247.Google Scholar
Pope, S. B. 1985 PDF methods for turbulent reacting flows. Prog. Energy Combust. Sci. 11, 119192.CrossRefGoogle Scholar
Pope, S. B. 2000 Turbulent Flows. Cambridge University Press.Google Scholar
Prausnitz, J. M., Poling, B. E. & O’Connell, J. P. 2001 The Properties of Gases and Liquids. McGraw-Hill.Google Scholar
Rajagopalan, A. G. & Tong, C. 2003 Experimental investigation of scalar-scalar-dissipation filtered joint density function and its transport equation. Phys. Fluids 15, 227244.Google Scholar
Reid, R. C., Prausnitz, J. M. & Poling, B. E. 1989 The Properties of Gases and Liquids. McGraw-Hill.Google Scholar
Rowinski, D. H. & Pope, S. B. 2013 An investigation of mixing in a three-stream turbulent jet. Phys. Fluids 25, 105105.Google Scholar
Ruppert, D. 1997 Empirical-bias bandwidths for local polynomial nonparametric regression and density estimation. J. Am. Stat. Assoc. 92, 10491062.Google Scholar
Shetty, D. A., Chandy, A. J. & Frankel, S. H. 2010 A new fractal interaction by exchange with the mean mixing model for large eddy simulation/filtered mass density function applied to a multiscalar three-stream turbulent jet. Phys. Fluids 22, 025102.CrossRefGoogle Scholar
Sirivat, A. & Warhaft, Z. 1982 The mixing of passive helium and temperature fluctuations in grid turbulence. J. Fluid Mech. 120, 475504.CrossRefGoogle Scholar
Tennekes, H. & Lumley, J. L. 1972 A First Course in Turbulence. MIT.Google Scholar
Tong, C. 2001 Measurements of conserved scalar filtered density function in a turbulent jet. Phys. Fluids 13, 29232937.Google Scholar
Tong, C. & Warhaft, Z. 1995 Scalar dispersion and mixing in a jet. J. Fluid Mech. 292, 138.Google Scholar
Wand, M. P. & Jones, M. C. 1995 Kernel Smoothing. Chapman & Hall.Google Scholar
Wang, D. & Tong, C. 2002 Conditionally filtered scalar dissipation, scalar diffusion, and velocity in a turbulent jet. Phys. Fluids 14, 21702185.CrossRefGoogle Scholar
Wang, D. & Tong, C. 2005 Experimental study of velocity-scalar filtered joint density function for les of turbulent combustion. Proc. Combust. Inst. 30, 567574.Google Scholar
Wang, D., Tong, C., Barlow, R. S. & Karpetis, A. N. 2007a Experimental study of scalar filtered mass density function in turbulent partially premixed flames. Proc. Combust. Inst. 31, 15331541.Google Scholar
Wang, G. H. & Clemens, N. T. 2004 Effects of imaging system blur on measurements of flow scalars and scalar gradients. Exp. Fluids 37, 194205.Google Scholar
Wang, G.-H., Clemens, N. T., Barlow, R. S. & Varghese, P. L. 2007b A system model for assessing scalar dissipation measurement accuracy in turbulent flows. Meas. Sci. Technol. 18, 12871303.Google Scholar
Warhaft, Z. 1984 The interference of thermal fields from line sources in grid turbulence. J. Fluid Mech. 144, 363387.Google Scholar
Warhaft, Z. 2000 Passive scalars in turbulent flows. Annu. Rev. Fluid Mech. 32, 203240.Google Scholar