Density Wave Instability of Sodium Boiling Two-phase Flow in a Vertical Annulus at Low Pressure

2003 ◽  
Vol 40 (7) ◽  
pp. 493-500 ◽  
Author(s):  
Suizheng QIU ◽  
Minoru TAKAHASHI ◽  
Dounan JIA ◽  
Guanghui SU
Keyword(s):  
Two Phase Flow ◽  
Density Wave ◽  
Low Pressure ◽  
Phase Flow ◽  
Wave Instability ◽  
Two Phase ◽  
Vertical Annulus

Experimental Study on Density Wave Instability of Sodium Boiling Two-Phase Flow in an Annulus

2002 ◽  
Author(s):  
Suizheng Qiu ◽  
Minoru Takahashi ◽  
Dounan Jia
Keyword(s):  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Two Phase Flow ◽  
Density Wave ◽  
Inlet Temperature ◽  
Phase Flow ◽  
Wave Instability ◽  
Two Phase ◽  
System Pressure

Experiments of density wave instability in a liquid sodium boiling two-phase flow experiments in an annulus were carried out in the following parameters range: heat flux from 80kW/m2 to 976kW/m2, inlet subcooling from 25.6°C to 226.8°C, mass flow rate from 7.92kg/h to 68.9kg/h, system pressure from 2600Pa to 0.12Mpa. Not only the mechanism of the instability, critical conditions and oscillation period, but also the effects of pressure, mass flow rate and inlet subcooling on the density wave instability were explored experimentally and theoretically. From the experimental data, it was found that the lower the inlet temperature was, the higher the system pressure and the mass flow rate that could result in a more stable boiling two-phase flow were. A correlation for the density wave instability was obtained on from the dimensional analysis for the conservation equations of mass, momentum and energy.

Flow regime development analysis in adiabatic upward two-phase flow in a vertical annulus

2011 ◽  
Vol 32 (1) ◽  
pp. 164-175 ◽  
Author(s):  
J. Enrique Julia ◽  
Basar Ozar ◽  
Jae-Jun Jeong ◽  
Takashi Hibiki ◽  
Mamoru Ishii
Keyword(s):  
Flow Regime ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Vertical Annulus ◽  
Development Analysis

Research on Two-Phase Flow Instability in Evaporator of Refrigeration System

2010 ◽  
Author(s):  
Nan Liang ◽  
Changqing Tian ◽  
Shuangquan Shao
Keyword(s):  
Pressure Drop ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Two Phase Flow ◽  
Density Wave ◽  
Phase Flow ◽  
Constant Mass ◽  
Refrigeration System ◽  
Two Phase

As one kind of fluid machinery related to the two-phase flow, the refrigeration system encounters more problems of instability. It is essential to ensure the stability of the refrigeration systems for the operation and efficiency. This paper presents the experimental investigation on the static and dynamic instability in an evaporator of refrigeration system. The static instability experiments showed that the oscillatory period and swing of the mixture-vapor transition point by observation with a camera through the transparent quartz glass tube at the outlet of the evaporator. The pressure drop versus mass flow rate curves of refrigerant two phase flow in the evaporator were obtained with a negative slope region in addition to two positive slope regions, thus making the flow rate a multi-valued function of the pressure drop. For dynamic instabilities in the evaporation process, three types of oscillations (density wave type, pressure drop type and thermal type) were observed at different mass flow rates and heat fluxes, which can be represented in the pressure drop versus mass flow rate curves. For the dynamic instabilities, density wave oscillations happen when the heat flux is high with the constant mass flow rate. Thermal oscillations happen when the heat flux is correspondingly low with constant mass flow rate. Though the refrigeration system do not have special tank, the accumulator and receiver provide enough compressible volume to induce the pressure drop oscillations. The representation and characteristic of each oscillation type were also analyzed in the paper.

Flow Regime Identification in Boiling Two-Phase Flow in a Vertical Annulus

2011 ◽  
Vol 133 (9) ◽  
Author(s):  
Leonor Hernández ◽  
J. Enrique Julia ◽  
Basar Ozar ◽  
Takashi Hibiki ◽  
Mamoru Ishii
Keyword(s):  
Flow Regime ◽  
Two Phase Flow ◽  
Chord Length ◽  
Axial Position ◽  
Cumulative Probability ◽  
Phase Flow ◽  
Global Flow ◽  
Two Phase ◽  
Local Flow ◽  
Vertical Annulus

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 the 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 from 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, cap-slug 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.

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