Global Flow Regime Identification in a Rod Bundle Geometry

Author(s):  
Sidharth Paranjape ◽  
Damian Stefanczyk ◽  
Yong Liang ◽  
Takashi Hibiki ◽  
Mamoru Ishii

Flow regime maps were obtained for an adiabatic air-water two phase flow through a flow channel with 8×8 rod bundle, which simulated a typical rod bundle in a BWR. 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 (CPDF) of the signals from the impedance meters were fed to a self organizing neural network to identify the flow regimes. The flow regimes were identified at seven axial locations in the channel in order to understand the development of the flow regimes in axial direction. The experimental flow regime transition boundaries agreed well with the theoretical ones obtained using Mishima and Ishii (1984) model. In addition, the two impedance void meters located across a spacer grid, which were used to study the change in the flow regime across the spacer grid.

2011 ◽  
Vol 133 (9) ◽  
Author(s):  
Sidharth Paranjape ◽  
Shao-Wen Chen ◽  
Takashi Hibiki ◽  
Mamoru Ishii

Flow regime maps were obtained for adiabatic air-water two-phase flow through a flow channel with 8 × 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.


2020 ◽  
Vol 368 ◽  
pp. 110815
Author(s):  
Yue Jin ◽  
Fan-Bill Cheung ◽  
Koroush Shirvan ◽  
Stephen M. Bajorek ◽  
Kirk Tien ◽  
...  

2003 ◽  
Vol 125 (4) ◽  
pp. 544-544 ◽  
Author(s):  
Sang Young Son ◽  
Jeffrey S. Allen ◽  
Kenneth O. Kihm

Author(s):  
Xu Han ◽  
Xiuzhong Shen ◽  
Toshihiro Yamamoto ◽  
Ken Nakajima ◽  
Takashi Hibiki

Author(s):  
Darin J. Sharar ◽  
Arthur E. Bergles ◽  
Nicholas R. Jankowski ◽  
Avram Bar-Cohen

A non-intrusive optical method for two-phase flow pattern identification was developed to validate flow regime maps for two-phase adiabatic flow in a small diameter tube. Empirical measurements of film thickness have been shown to provide objective identification of the dominant two-phase flow regimes, representing a significant improvement over the traditional use of exclusively visual and verbal descriptions. Use of this technique has shown the Taitel-Dukler, Ullmann-Brauner, and Wojtan et al. phenomenological flow regime mapping methodologies to be applicable, with varying accuracy, to small diameter two-phase flow.


Author(s):  
Paul J. Kreitzer ◽  
Michael Hanchak ◽  
Larry Byrd

Flow regime Identification is an integral aspect of modeling two phase flows as most pressure drop and heat transfer correlations rely on a priori knowledge of the flow regime for accurate system predictions. In the current research, two phase R-134a flow is studied in a 7mm adiabatic horizontal tube over a mass flux range of 100–400 kg/m2s between 550–750 kPa. Electric Capacitance Tomography results for 196 test points were analyzed using statistical methods and neural networks. This data provided repeatable normalized permittivity ratio signatures based on the flow distributions. The first four temporal moments from the mean scaled permittivity data were utilized as input variables. Results showed that only 80 percent of flow regimes could be correctly identified using seven flow regime classifications. However reducing to five more commonly used regimes resulted in an improvement to 99 percent of the flow regimes correctly identified. Both methods of neural network training resulted in errors that were off by mostly one flow regime classification. Further analysis shows that transition cases can oscillate between two separate flow regimes at the same time.


Author(s):  
Seok Cho ◽  
Sang-Ki Moon ◽  
Ki-Yong Choi ◽  
Se-Young Chun ◽  
Moon-Ki Chung ◽  
...  

A series of bottom reflood tests were carried out to investigate thermal-hydraulic characteristics during the reflood phase. This paper includes descriptions of three related groups of reflood tests categorized by the geometry of a flow channel and an electric power shape of heater rods. A centrally-heated annular geometry with an outer-visualizing tube was adopted for the first two groups of tests (group-A and -B), and a 6×6 rod bundle geometry for the other group of tests (group-C). The ranges of experimental parameters are 2∼8 cm/s of flooding velocity, 20∼80 °C of inlet subcooling temperature, and 500∼700 °C of initial wall temperature. In the single rod annular flow channel reflood test, quench front behavior can be easily observed through the visualizing window and a dominant flow regime near downstream of quench front is inverted annular film boiling regardless of the flooding velocity. For the case of the 6×6 rod bundle experiments, on the other hand, the dominant flow regime is dispersed flow film boiling (DFFB), and therefore the thermal hydraulic behavior becomes more complicated and chaotic due to the interaction between liquid phase such as droplet and liquid film and vapor phase generated from liquid-wall heat transfer.


Author(s):  
Christian Weinmu¨ller ◽  
Dimos Poulikakos

Microfluidics has experienced a significant increase in research activities in recent years with a wide range of applications emerging, such as micro heat exchangers, energy conversion devices, microreactors, lab-on-chip devices and micro total chemical analysis systems (μTAS). Efforts to enhance or extend the performance of single phase microfluidic devices are met by two-phase flow systems [1, 2]. Essential for the design and control of microfluidic systems is the understanding of the fluid/hydrodynamic behavior, especially pressure drop correlations. These are well established for single phase flow, however, analytical correlations for two-phase flow only reflect experimentally obtained values within an accuracy of ± 50% [3, 4]. The present study illustrates the effect of two-phase flow regimes on the pressure drop. Experimental measurement data is put into relation of calculated values based on established correlations of Lockhart-Martinelli with Chisholm modifications for macroscopic flows [5, 6] and Mishima-Hibiki modifications for microscale flows [7]. Further, the experimental pressure drop data is superimposed onto two-phase flow maps to identify apparent correlations of pressure drop abnormalities and flow regimes. The experiments were conducted in a square microchannel with a width of 200 μm. Optical access is guaranteed by an anodically bonded glass plate on a MEMS fabricated silicon chip. Superficial velocities range from 0.01 m/s to 1 m/s for the gas flow and from 0.0001 m/s to 1 m/s for the liquid flow with water as liquid feed and CO2 as gas. The analysis of the flow regimes was performed by imaging the distinct flow regimes by laser induced fluorescence microscopy, employing Rhodamine B as the photosensitive dye. The pressure drop was synchronically recorded with a 200 mbar, 2.5 bar and 25 bar differential pressure transmitter and the data was exported via a LabView based software environment, see Figure 1. Figure 2 illustrates the experimentally obtained pressure drop in comparison to the calculated values based on the Lockhard-Martinelli correlation with the Chisholm modification and the Mishima-Hibiki modification. For both cases the predications underestimate the two-phase pressure drop by more than 50%. Nevertheless, the regression of the experimental data has an offset of linear nature. Two-phase flow is assigned to flow regime maps of bubbly, wedging, slug or annular flow defined by superficial gas and liquid velocities. In Figure 3 the pressure drop is plotted as a surface over the corresponding flow regime map. Transition lines indicate a change of flow regimes enclosing an area of an anticline in the pressure data. In the direct comparison between the calculated and the measured values, the two surfaces show a distinct deviation. Especially, the anticline of the experimental data is not explained by the analytical correlations. Figure 4 depicts the findings of Figure 3 at a constant superficial velocity of 0.0232 m/s. The dominant influence of the flow regimes on the pressure drop becomes apparent, especially in the wedging flow regime. The evident deviation of two-phase flow correlations for the pressure drop is based on omitting the influence of the flow regimes. In conclusion, the study reveals a strong divergence of pressure drop measurements in microscale two-phase flow from established correlations of Lockhart-Martinelli and recognized modifications. In reference to [8, 9], an analytical model incorporating the flow regimes and, hence, predicting the precise pressure drop would be of great benefit for hydrodynamic considerations in microfluidics.


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