Velocity and Mass Flux Distribution Measurements of Spherical Glass Beads in Air Flow in a 90° Vertical-to-Horizontal Bend

In this study a method to predict CHF (Critical Heat Flux) in vertical round tubes with cosine heat flux distribution was examined. For this purpose a uniform correlation, based on local condition hypothesis, was developed from 9,366 CHF data points of uniform heat flux heaters. The CHF data points used were collected from 13 different sources had the following parameter ranges: 1.01 ≤ P (pressure) ≤ 206.79 bar, 9.92 ≤ G (mass flux) ≤ 18,619.39 kg/m2s, 0.00102 ≤ D (diameter) ≤ 0.04468 m, 0.0254 ≤ L (length) ≤ 4.966 m, 0.11 ≤ qc (CHF) ≤ 21.42 MW/m2, and −0.87 ≤ X (exit qualities) ≤ 1.58. The result of this work showed that the uniform CHF correlation could be used to predict CHF accurately in a non-uniform heat flux heater for wide flow conditions. Furthermore, the location, where CHF occurs in non-uniform heat flux distribution, can also be determined accurately with the local variables: the system pressure (P), tube diameter (D), mass flux of water (G), and true mass flux of vapor (GXt). The new correlation predicted CHF with cosine heat flux, 297 data points from 5 different published sources, within the root mean square error of 12.42% and average error of 1.06% using the heat balance method.

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Numerical investigation of heat flux distribution in a deep gap based on chemical equilibrium

International Journal of Numerical Methods for Heat &amp Fluid Flow ◽

10.1108/hff-03-2016-0119 ◽

2017 ◽

Vol 27 (8) ◽

pp. 1662-1674 ◽

Cited By ~ 2

Author(s):

Guo Huang ◽

Haiming Huang

Keyword(s):

Heat Flux ◽

Flow Field ◽

Chemical Equilibrium ◽

Flux Distribution ◽

Thermal Protection ◽

Air Flow ◽

Hypersonic Vehicles ◽

Heat Flux Distribution ◽

Content Type ◽

Gap Flow

Purpose The purpose of this paper is to perform the simulation to explore the gap flow field under a hypersonic air flow. Thermal protection systems of hypersonic vehicles generally consist of thermal insulation tiles, and gaps between these tiles probably cause a severe local aerodynamic thermal effect. Design/methodology/approach The discretizations of convection flux term and temporal term in the governing equation with chemical equilibrium, respectively, take AUSM+-up flux-vector splitting scheme and the implicit lower-upper symmetric Gauss–Seidel method. Based on these, the flow field in a deep gap is simulated by means of the computer codes that the authors have written. Findings The numerical results show that the heat flux distribution in a gap has a good agreement with experimental results. Importantly, the distribution of heat flux is “U” shaped and the maximum of the heat flux occurs at the windward corner of a gap. Originality/value To explore the gap flow field under a hypersonic air flow, which is a chemically reacting, all speed and viscous flow, a novel model with an equivalent ratio of specific heats is presented. The investigation in this paper has a guide for the design of the thermal protection system in hypersonic vehicles.

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Fluctuations in a quasi-stationary shallow cumulus cloud ensemble

Nonlinear Processes in Geophysics Discussions ◽

10.5194/npgd-1-1223-2014 ◽

2014 ◽

Vol 1 (2) ◽

pp. 1223-1282 ◽

Cited By ~ 4

Author(s):

M. Sakradzija ◽

A. Seifert ◽

T. Heus

Keyword(s):

Weibull Distribution ◽

Mass Flux ◽

Flux Distribution ◽

Deep Convection ◽

Convective Cloud ◽

Cloud Base ◽

Cumulus Clouds ◽

Large Eddy Simulation Model ◽

Shallow Cumulus ◽

Distribution Mode

Abstract. We propose an approach to stochastic parameterization of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect the information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal due to the different shallow cloud subtypes. Each distribution mode can be approximated with a Weibull distribution, explaining the deviation from a single-parameter exponential shape through the diversity in cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterization is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive – the smaller the grid size, the broader the distribution.

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