• Nuclear Engineering and Technology
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• 제53권6호
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• pp.1796-1809
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• 2021

The subchannel of a research reactor used to generate high power density is designed to be narrow and rectangular and comprises plate-type fuels operating under downward flow conditions. Critical heat flux (CHF) is a crucial parameter for estimating the safety of a nuclear fuel; hence, this parameter should be accurately predicted. Here, machine learning is applied for the prediction of CHF in a narrow rectangular channel. Although machine learning can effectively analyze large amounts of complex data, its application to CHF, particularly for narrow rectangular channels, remains challenging because of the limited flow conditions available in existing experimental databases. To resolve this problem, we used four CHF correlations to generate pseudo-data for training an artificial neural network. We also propose a network architecture that includes pre-training and prediction stages to predict and analyze the CHF. The trained neural network predicted the CHF with an average error of 3.65% and a root-mean-square error of 17.17% for the test pseudo-data; the respective errors of 0.9% and 26.4% for the experimental data were not considered during training. Finally, machine learning was applied to quantitatively investigate the parametric effect on the CHF in narrow rectangular channels under downward flow conditions.

• 한국대기환경학회지
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• 제15권5호
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• pp.625-638
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• 1999

Air quality modeling for coastal urban region has been composed of a complex system including meteorological, chemical and physical processes and emission characteristics in complex terrain. In this study, we studied about an effect prediction for deposition phenomenon affecting on air quality in Pusan metopolitan metropolitan city. In air quality modeling including ship sources, a situation considered deposition process habe better result than not considered when compared with observed value. Air pollutants emitted into urban air during the daytime nearly removed through urban atmosphere polluted. Also these phenomena correlated concentration variation connent with sea/land breezes and terrain effect. Therefore we conclude that the concentration was low at daytime when deposition flux is high, and deposition effect on industrial complex and Dongrae region is considerable in particular.

• 설비공학논문집
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• 제19권12호
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• pp.831-841
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• 2007

This work is to extend the elliptic operator, which has been already adopted in turbulent stress model, to fully developed turbulent buoyant channel flows with changing the orientation of the buoyancy vector to be perpendicular to the channel walls. The turbulent heat flux models based on the elliptic concept are employed and closely linked to the elliptic blending second moment closure which is used for the prediction of Reynolds stresses. In order to reflect the stable or unstable stratification conditions, the present model introduces the gradient Richardson number into the thermal to mechanical time scale ratio and model coefficients. The present model has been applied for the computation of stably and unstably stratified turbulent channel flows and the prediction results are directly compared to the DNS data.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 춘계학술발표회논문집(1)
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• pp.362-367
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• 1997

To assess the coolability of particle bed, which is formed in reactor cavity, it is important to assess the prediction capabilities of Dryout Heat flux correlations. The existing DHF correlations (Sowa et al., Dhir-Catton (a), Dhir-Catton (b), Hardee-Nilson, Ostesen, Shires-Stevens, Lipinski, Jones et al., Dhir-Barleon, Theofanous-Saito, Henry-Fauske) for particle beds are assessed using developed DHF database. Eleven DHF correlations are chosen for assessment based on literature survey. Among them, five are based on flooding correlation, which are used for chemical engineering and others are based on conservation equations. The parameters in DHF correlations are directly substituted into correlations. Totally 202 data are classified into 6 groups based on bed thickness and particle diameter. In each group, prediction capabilities of correlations are assessed and shown by standard deviation and root mean square (RMS) error. Prediction capability of each correlation depends on the data group and none of correlations shows best prediction capability on entire groups. According to present study, even if those correlations show poor prediction capability, Lipinski correlation is best correlation considering entire groups.

• 한국군사과학기술학회지
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• 제12권3호
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• pp.396-405
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• 2009

The experimental research was conducted to setup a performance prediction logic for the regenerative cooling system on a small scale liquid rocket engine using kerosene and LOX. Total heat flux of the combustion gas side was determined for the flow rate of the coolant, combustion pressure using the calorimeter thrust chamber. Based on the experimental investigation, a performance prediction scheme for the regenerative cooling system is setup in our own way. A performance prediction logic for the regenerative cooling system has been developed by the correction scheme of the combustion gas side. The key parameters determining the temperature limitation of the coolant are the mass flow rate of the coolant and the length of the combustion chamber and the nozzle. And the parameters to control the limitation of the usable wall temperature are the number of channels and wall thickness.

• Nuclear Engineering and Technology
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• 제34권4호
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• pp.382-395
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• 2002

An experimental study on transient critical heat flux (CHF) under flow coastdown has been performed for the water flow in a non-uniformly heated vertical annulus under low flow and a wide range of pressure conditions. The objectives of this study are to systematically investigate the effect of the flow transient on the CHF and to compare the transient CHF with steady-state CHF The transient CHF experiments have been performed for three kinds of flow transient modes based on the coastdown data of a nuclear power plant reactor coolant pump. At the same inlet subcooling, system pressure and heat flux, the effect of the initial mass flux on the critical mass flux can be negligible. However, the effect of the initial mass flux on the time-to- CHF becomes large as the heat flux decreases. The critical mass flux has the largest value for slow flow reduction rate. There is a pressure effect on the ratio of the transient CHF data to steady-state CHF data. Except under low system pressure conditions, the flow transient CHF was revealed to be conservative compared with the steady-state CHF data. Bowling CHF correlation and thermal hydraulic system code MARS show promising results for the prediction of CHF occurrence .

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 춘계학술발표회논문집(1)
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• pp.356-361
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• 1997

To investigate parametric effect on CHF and to get CHF data, experimental study has been performed with vertical round tubes under the condition of low pressure and low flow (LPLF). Test sections are made of Inconel-625 tube and have the geometry of 8 and 10 mm in diameter, and 0.5 and 1.0 m in heated length. All experiments have been conducted at the pressure of under 9 bar, the mass flux of under 250 kg/$m^2$ and the inlet subcooling of 350 and 450 kJ/kg, for stable upward flow with water as a coolant. Flow regime analysis has been performed for obtained CHF data with Mishima's flow regime map, which reveals that most of the CHF occur in the annular-mist flow regime. General parametric trends of the collected CHF data are consistent with those of previous studies. However, for the pressure effect on CHF, two different are observed; For relatively high mass flux, CHF increases with pressure and far lower mass flux, CHF decrease with pressure. Using modern data regression tool, ACE algorithm, two new CHF correlations for LPLF condition are developed based on local condition and inlet condition, respectively. The developed CHF correlations show better prediction accuracy compared with existing CHF prediction methods.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3962-3973
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• 2022

Several critical heat flux (CHF) correlations including the look-up table in the MARS code have been assessed for the prediction of CHF in a downward-flow narrow rectangular channel. For the assessment, we built an experiment database that covers pressures between 1.01 and 39.0 bar, gap sizes between 1.09 and 6.53 mm, mass fluxes up to 25,772 kg/m²s, and under one-sided and two-sided heating conditions. The results of the assessment showed that the Kaminaga correlation has the best overall prediction compared to others. However, because the correlation uses global variables, such as inlet and outlet subcooling and total heat transfer area, it is difficult to use in a system code. A new CHF correlation is then proposed by replacing the global variables in the Kaminaga correlation with local ones and adding correction factors to consider the effect of gap size, mass flux, and the number of heating walls. Additional correction factor is added to consider the effect of inlet subcooling. It is shown that the new one is better than the Kaminaga correlation and it is easy to implement to any system code.

• 대한기계학회논문집B
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• 제29권11호
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• pp.1265-1276
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• 2005

The elliptic conceptual second moment models for turbulent heat fluxes, which are proposed on the basis of elliptic-blending and elliptic-relaxation equations, are applied to calculate the combined forced and natural turbulent convection in a vertical plane channel. The models satisfy the near-wall balance between viscous diffusion, viscous dissipation and temperature-pressure gradient correlation, and also have the characteristics of approaching its respective conventional high Reynolds number model far away from the wall. Also the models are closely linked to the elliptic blending model which is used for the prediction of Reynolds stress. In order to calibrate the heat flux models, firstly, the distributions of mean temperature and scala flux in fully developed channel flow with constant wall difference temperature are solved by the present models. The buoyancy effect on the turbulent characteristics including the mean velocity and temperature, the Reynolds stress tensor, and the turbulent heat flux vector are examined. In the opposing flow, the turbulent transport is greatly enhanced with both the Reynolds stresses and the turbulent heat fluxes being remarkably increased; whereas, in the aiding flow, the opposite change is observed. The results of prediction are directly compared to the DNS to assess the performance of the model predictions and show that the behaviors of the turbulent heat transfer in the whole flow region are well captured by the present models.

• 천문학회보
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• 제36권2호
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• pp.97.1-97.1
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• 2011

In this study we have examined the probability of solar proton events (SPEs) and their peak fluxes depending on flare (flux, longitude and impulsive time) and CME parameters (linear speed, longitude, and angular width). For this we used the NOAA SPE list and their associated flare data from 1976 to 2006 and CME data from 1997 to 2006. We find that about 3.5% (1.9% for M-class and 21.3% for X-class) of the flares are associated with SPEs. It is also found that this fraction strongly depends on longitude; for example, the fraction for $30W^{\circ}$ < L < $90W^{\circ}$ is about three times larger than that for $30^{\circ}E$ < L < $90^{\circ}E$. The SPE probability with long duration (${\geq}$ 0.3 hours) is about 2 (X-class flare) to 7 (M-class flare) times larger than that for flares with short duration (< 0.3 hours). In case of halo CMEs with V ${\geq}$ 1500km/s, 36.1% are associated with SPEs but in case of partial halo CME ($120^{\circ}$ ${\leq}$ AW < $360^{\circ}$) with 400 km/s ${\leq}$ V < 1000 km/s, only 0.9% are associated with SPEs. The relationships between X-ray flare peak flux and SPE peak flux are strongly dependent on longitude and impulsive time. The relationships between CME speed and SPE peak flux depend on longitude as well as direction parameter. From this study, we suggest a new SPE forecast method with three-steps: (1) SPE occurrence probability prediction according to the probability tables depending on flare and CME parameters, (2) SPE flux prediction from the relationship between SPE flux and flare (or CME) parameters, and (3) SPE peak time.