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This study has investigated the axial development of flow regime of adiabatic upward air-water two-phase flow in a vertical annulus. The inner and outer diameters of the annulus are 19.1 mm and 38.1 mm, respectively. The hydraulic diameter of the flow channel, [D.sub.H], is 19.0 mm and the total length is 4.37 m. The flow regime map includes 72 flow conditions within a range of 0.01 m/s < < 30 m/s and 0.2 m/s < < 3.5 m/ s, where and are, respectively, superficial gas and liquid velocities. The flow regime has been classified into four categories: bubbly, cap-slug, churn, and annular flows. In order to study the axial development of flow regime, area-averaged void fraction measurements have been performed using impedance void meters at three axial positions corresponding to z/[D.sub.H] = 52, 149, and 230 simultaneously, where z represents the axial position. The flow regime indicator has been chosen to be statistical parameters from the probability distribution function of the area-averaged void fraction signals from the impedance meters, and self-organized neural networks have been used as the mapping system. This information has been used to analyze the axial development of flow regime as well as to check the predictions given by the existing flow regime transition models. The axial development of flow regime is quantified using the superficial gas velocity and void fraction values where the flow regime transition takes place. The predictions of the models are compared for each flow regime transition. In the current test conditions, the axial development of flow regime occurs in the bubbly to cap-slug (low superficial liquid velocities) and cap-slug to churn (high superficial liquid velocities)flow regime transition zones. [DOI: 10.1115/1.3059701] Keywords: two-phase flow, flow regime, flow pattern, annulus, neural network

A heat transfer correlation of flow boiling at low liquid Reynolds number for small diameter channels is developed. The developed heat transfer correlation works satisfactorily with mean deviation and rms errors of 19.1% and 24.3%, respectively, under different channel geometries like circular and rectangular and flow orientations like vertical and horizontal for some test fluids such as water, R11, R12 and R113.

An accurate and practical approach is necessary for predicting oil fraction in horizontal oil-water flows. In this study, a concept of a drift-flux model is adopted to develop a predictive method for the oil fraction in the horizontal oil-water flows due to its simplicity and practicality. A new drift-flux correlation for the horizontal oil-water flows is developed based on the least square method using collected experimental data. The distribution parameter is determined to be 1.05 for the data with the ratio of oil density to water density ranging from 0.787 to 1.00, whereas the oil fraction weighted mean drift velocity is set at 0 m/s due to the flow direction perpendicular to the gravity direction. The physical meaning for the order of unity of the distribution parameter is explained by introducing a simple model. The predictive capability of the new drift-flux correlation is examined using the collected database of oil-water flows in horizontal pipes under a variety of test conditions. It is demonstrated that the new drift-flux correlation can predict the existing oil fractions in the horizontal pipe channels with the mean absolute error, standard deviation, mean relative deviation, and mean absolute relative deviation being -722;0.0124, 0.0338, -722;3.25%, and 9.57%, respectively. [ABSTRACT FROM AUTHOR]

This work describes the application of an artificial neural network to process the signals measured by local conductivity probes and classify them into their corresponding global flow regimes. Experiments were performed in boiling upward two-phase flow in a vertical annulus. The inner and outer diameters of tire annulus were 19.1 mm and 38.1 mm. respectively. The hydraulic diameter of the flow channel, DH. was 19.0 mm and the total length is 4.477 m. The test section was composed of an injection port and five instrumentation ports, the first three were in the heated section (z/DH = 52, 108 and 149 where z represents the axial position) and the upper ones in the unheated sections (z/DH = 189 and 230). Conductivity measurements were performed in nine radial positions for each of the five ports in order to measure the bubble chord length distribution for each flow condition. The measured experiment matrix comprised test cases at different inlet pressure, ranging from 200 kPa up to 950 kPa. A total number of 42 different flow conditions with superficial liquid velocities from 0.23 m/s to 2.5 m/s and superficial gas velocities from 0.002 m/s to 1.7 m/s and heat flux from 55 kW/m² to 247 kW/m² were measured in the five axial ports. The flow regime indicator has been chosen to be statistical parameters front the cumulative probability distribution function of the bubble chord length signals from the conductivity probes. Self-organized neural networks (SONN) have been used as the mapping system. The flow regime has been classified into three categories." bubbly, capslug and churn. A SONN has been first developed to map the local flow regime (LFR) of each radial position. The obtained LFR information, conveniently weighted with their corresponding significant area, was used to provide the global flow regime (GFR) classification. These final GFR classifications were then compared with different flow regime transition models. [ABSTRACT FROM AUTHOR]

Flow regime maps were obtained for adiabatic air-water two-phase flow through a flow channel with 8 x 8 rod bundle, which simulated a typical rod bundle in a boiling water reactor. Impedance void meters were used to measure the area averaged void fraction at various axial locations in the flow channel. The Cumulative Probability Distribution Functions of the signals from the impedance meters were utilized along with self organizing neural network methodology to identify the flow regimes. The flow regimes were identified at five axial locations in the channel in order to understand the development of the flow regimes in axial direction. The experimental flow regime transition boundaries for bubbly to cap-bubbly and part of the cap-turbulent to churn-turbulent agreed with the theoretical boundaries of bubbly to slug and slug to churn-turbulent in round pipes. In addition, the two impedance void meters located across a spacer grid, revealed the nature of change in the flow regime across the spacer grid. [ABSTRACT FROM AUTHOR]

In view of significance of a heat transfer correlation of flow boiling under the conditions of low liquid Reynolds number or liquid laminar flow, and very few correlations in principle suitable for such flow conditions, this study is aiming at developing a heat transfer correlation of flow boiling at low liquid Reynolds number for small diameter channels. The correlation is developed based on superimposition of two main flow boiling mechanisms, namely nucleate boiling and forced convection. In the correlation, two terms corresponding to nucleate boiling and forced convection are obtained from the pool boiling correlation by Forster and Zuber and the analytical annular flow model by Hewitt and Hall-Taylor, respectively. An extensive comparison with a collected database indicates that the developed correlation works satisfactorily with mean deviation and rms errors of 19.1% and 24.3%, respectively, under many experimental conditions such as different channel geometries (circular and rectangular) and flow orientations (vertical and horizontal)for some test fluids (water, R11, R12, and R113). A detailed discussion reveals that existing correlations for turbulent flow boiling such as Chen's correlation, Schrock and Grossman's correlation, and Dengler and Addoms's correlation may be derived from a generalized form of the newly developed correlation. [ABSTRACT FROM AUTHOR]