Simultaneous velocity and temperature measurements in a premixed flame

Heitor, M. V.; Taylor, A. M. K. P.; Whitelaw, J. H.

doi:10.1007/bf01830191

Cited by 75 publications

(8 citation statements)

References 37 publications

(27 reference statements)

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“…With the exception of the study by Schefer et al (1987), there is little or no information on the behavior of the single and joint probability density functions of concentration and velocities in a nonreacting flow. On the other hand, a number of studies in flames and reacting flows yield data on single probability density functions of temperature, density and mixture mass fraction (Gouldin and Danekar 1984;Heitor et al 1985;Heitor and Whitelaw 1986;Drake et al 1986) and joint probability density functions of species concentration and velocities (Mudford and Bilger 1984;Schefer and Dibble 1985;Dibble et al 1987a, b).…”

mentioning

confidence: 99%

Behavior of probability density functions in a binary gas jet

Zhu

Otugen³

et al. 1991

Experiments in Fluids

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A helium/air mixture free round jet into still air was invesSubscripts tigated using a laser Doppler anemometer and a hot-wire type concentration probe. The jet Reynolds number was 4,300 and the a h jet-to-ambient fluid density ratio was set at 0.64. Simultaneous measurements of the mixture density and the axial and radial velocities J were carried out in both the near and far fields of the jet. A detailed 0 analysis of the turbulent mass transfer and jet characteristics has been presented by So et al. (1990). This paper reports on the higher Overscores order statistics and the characteristics of the single and joint probability density distributions of the mixture density and the axial and radial velocities. The behavior of these distributions across and along the jet is analyzed and compared with other single and joint probability density distributions.

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mentioning

confidence: 99%

Behavior of probability density functions in a binary gas jet

Zhu

Otugen³

et al. 1991

Experiments in Fluids

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“…The anemometer time constant M w depends on temperature, velocity and gas composition. A numerical compensation was preferred to an analogue circuit because it can take into account some of these dependencies (Heitor, 1985). We apply first the Nyquist interpolation formula to reconstruct the thermoanemometer signal and then the numerical compensation algorithm.…”

Section: Thermal=turbulence Time Scale Ratios 45mentioning

confidence: 99%

Thermal/Turbulence Time Scale Ratios in Low Exothermic Reacting and Non-reacting Flows

Bounif

Senouci

Gökalp

2008

Combustion Science and Technology

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The aim of this work is to contribute to the study of chemistry effects on the turbulent scalar field that is, here, the temperature, through a better knowledge of the ratio between the scalar time scale and the mechanical time scale (R t ) in the distributed reaction regime characterized by a Damkö hler number lower than unity. The numerical studies are performed by calculating the order of magnitude of R t in both low exothermic reacting and nonreacting case. Propane has been chosen as a typical hydrocarbon for this study. The molar fractions are computed by the IEM (Interaction Exchange with the Mean) model in which the probability density function is calculated from its transport equation. The models and the numerical simulations are used to describe a jet stirred reactor with subsonic jet injection. The predictions are validated by comparison with experimental data for temperature and concentrations fields. It is pointed that in the non-reacting case, R t parameter is around unity; the temporal scales dynamics and scalar are coupled. In this case, the transport of the passive scalar is ensured by the dynamic field. In the reactive case, however, this coupling is not assured any more. Indeed, the chemical reaction, characterized by a non-linear source term, affects the scalar field by decreasing its characteristic scales, which results in R t lower than unity. The CFD-PDF predictions were within engineering accuracy of experimental data. It can be summarized that the results of exercise are satisfactory, and the CPU-time and RAM memory savings encouraging. INTRODUCTIONTemporal and spatial macroscopic velocity inhomogeneities or fluctuations are ubiquitous in turbulent flows. Large time and length scales (also termed integral scales) are associated to the external (initial=boundary conditions) or internal (flow instabilities) turbulence-triggering mechanisms. At the other end, the Kolmogorov time and length microscales characterize the viscous dissipation of kinetic energy into heat. The transfer of energy between large and small structures or eddies takes place across a wide range of intermediate scales.Heterogeneities in scalar fields can also be induced by injection process (initial and boundary conditions) and=or by the driving fluctuating velocity field. Local chemical source terms can also contribute to generate scalar fluctuations. The ratio of integral length to the Kolmogorov microscale is proportional to the turbulence Reynolds number to the power three-fourths, while the integral time over the Kolmogorov one scales as the Reynolds number to one-half (Dopazo & O'Brien, 1987). In order to resolve the smallest features of fluctuating fields, while keeping integral length scale inside the domain. The required computer storage is thus proportional to the Reynolds number to the nine-fourths power and the computational time goes a power slightly larger than eleven-fourths. This approach to the solutions of turbulent flows is named direct numerical simulation (DNS), as the governing equations are numericall...

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“…In the mixi-ng region studied by the latter authors, the influence of organized structures may make prediction difficult. The recommended flows are summarized in Tables 4 and 5 The flows of Heitor (1985) and Heitor et al(1983) and of McDannel et al (1982) and Brum and Samuelson (1983) treatment. In all premixed combustion flows, care must be taken to ensure H that the calculations and measurements correspond to the same type of averaging, the differences between unweighted and density-weighted averages can be significant.…”

Section: E E Ementioning

confidence: 99%

Evaluation of Data on Simple Turbulent Reacting Flows

Strahle¹,

Lekoudis²

1985

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Simultaneous velocity and temperature measurements in a premixed flame

Cited by 75 publications

References 37 publications

Behavior of probability density functions in a binary gas jet

Behavior of probability density functions in a binary gas jet

Thermal/Turbulence Time Scale Ratios in Low Exothermic Reacting and Non-reacting Flows

Evaluation of Data on Simple Turbulent Reacting Flows

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