• The KSFM Journal of Fluid Machinery
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• v.9 no.3 s.36
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• pp.14-21
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• 2006

Leakage reduction through annular type seals of turbomachinery is necessary for enhancing their efficiency and the precise prediction method of seal leakage is needed. The analysis based on Bulk-flow concept has been mainly used in predicting seal leakage. However, full Navier-Stokes Equations with turbulent model derived in the seal flow passage have to be solved for improving the prediction of seal leakage. FLUENT 6 which is commercial CFD(Computational Fluid Dynamics) code based on FVM(Finite Volume Method) and SIMPLE algorism has been used to analyze leakage of various non-contact-type seals in this presentation. Comparing with the results of Bulk-flow model analysis and experiment, the result of CFD analysis shows good agreement with that of existing theoretical analysis for the incompressible grooved seal and compressive plain and staggered seal. The CFD analysis also shows improvement on the leakage prediction of the incompressible plain seal and compressive see-through-type labyrinth seal.

• Tribology and Lubricants
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• v.25 no.3
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• pp.150-156
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• 2009

Precise leakage prediction for annular type seals of turbomachinery is necessary for enhancing their efficiency and various prediction methods have been developed. As the seal passage is designed intricately, the analysis based on Bulk-flow concept which has been mainly used in predicting seal leakage is limited. In order to improve the seal leakage prediction, full Navier-Stokes Equations with turbulent model derived in the seal flow passage have to be solved. In this study, 3D CFD (Computational Fluid Dynamics) analysis has been performed for predicting leakage of various non-contact type anular seals using FLUENT. Compared to the results by Bulk-flow model analysis, experiment, and 2D CFD analysis, the result of 3D CFD analysis shows improvement in predicting seal leakage, especially for the parallel grooved pump seal.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.7
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• pp.364-369
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• 2004

In this Paper, a flashover prediction method using the leakage current in the contaminated EPDM distribution polymer insulator is proposed. The leakage currents on the insulator were measured simultaneously with the different salt fog application such as 25g, 50g, and 75g per liter of deionized water. Then, the measured leakage currents were enveloped and transformed as the CDFS using the Hilbert transform and the level crossing rate, respectively. The obtained CDFS having different gradients(angles) were used as a important factor for the flashover prediction of the contaminated polymer insulator. Thus, the average angle change with an identical salt fog concentration was within a range of 20 degrees, and the average angle change among the different salt fog concentrations was 5 degrees. However, it is hard to be distinguished each other because the gradient differences among the CDFS were very small. So, the new weighting value was defined and used to solve this problem. Through simulation, it Is verified that the proposed method has the capability of the flashover prediction.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.562-564
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• 2004

The containment leakage rate test performed on the nuclear power plants consists of following phases : pressurizing the containment, stabilizing the atmosphere, conducting a Type A test, conducting a verification test, depressurizing the containment. It takes more than 48 hours from the pressurization to the depressurization and the prediction of the results will help to prepare the next test phase. In this paper, to predict the leakage rate, the prediction methods based on the least square method are evaluated according to the input variables and the measurement period.

• Tribology and Lubricants
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• v.22 no.2
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• pp.66-72
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• 2006

Leakage reduction through annular type labyrinth seals of steam turbine is necessary for enhancing their efficiency and the precise prediction method of seal leakage is needed. In this study, numerical analysis for leakage prediction of the combination-type-staggered-labyrinth seal has been carried out using FLUENT 6 which is commercial CFD (Computational Fluid Dynamics) code based on FVM (Finite Volume Method) and SIMPLE algorism. The present CFD results are verified with the theoretical analysis based on Bulk-flow concept which has been mainly used in predicting seal leakage. Comparing with the result of Bulk-flow model analysis, the leakage result of CFD analysis shows good agreement within 7.1% error.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.963-971
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• 2022

Water pipeline network in local and metropolitan area is buried underground, by which it is hard to know the degree of pipe aging and leakage. In this study, assuming various sensor combinations installed in the water pipeline network, the optimal algorithm was derived by predicting the water flow rate and pressure through artificial intelligence algorithms such as linear regression and neuro fuzzy analysis to examine the possibility of detecting pipe leakage according to the data combination. In the case of leakage detection through water supply pressure prediction, Neuro fuzzy algorithm was superior to linear regression analysis. In case of leakage detection through water supply flow prediction, flow rate prediction using neuro fuzzy algorithm should be considered first. If flow meter for prediction don't exists, linear regression algorithm should be considered instead for pressure estimation.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1725-1732
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• 2024

In nuclear power plants, reactor coolant leakage can occur due to various reasons. Early detection of leaks is crucial for maintaining the safety of nuclear power plants. Currently, a detection system is being developed in Korea to identify reactor coolant system (RCS) leakage of less than 0.5 gpm. Typically, RCS leaks are detected by monitoring temperature, humidity, and radioactivity in the containment, and a water level in the sump. However, detecting small leaks proves challenging because the resulting changes in the containment humidity and temperature, and the sump water level are minimal. To address these issues and improve leak detection speed, it is necessary to quantify the leaks and develop an artificial intelligence-based leak detection system. In this study, we employed bidirectional long short-term memory, which are types of neural networks used in artificial intelligence, to predict the relative humidity in the leakage area for leak quantification. Additionally, an optimization technique was implemented to reduce learning time and enhance prediction performance. Through evaluation of the developed artificial intelligence model's prediction accuracy, we expect it to be valuable for future leak detection systems by accurately predicting the relative humidity in a leakage area.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.10
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• pp.843-851
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• 2003

The present paper studies the leakage flow model used in the performance prediction of a scroll compressor. Two leakage flow models, isentropic and Fanno flow model, are studied in detail. Their predictions are also compared with CFD solutions to check the validity as a leakage flow model. Comparison with CFD solutions shows that the isentropic flow model predicts excessive leakage flow rate, while the Fanno flow model shows acceptable agreement with CFD solutions. The excessive leakage flow rate by isentropic flow model results in under-prediction of the overall performance of a scroll compressor.

• The KSFM Journal of Fluid Machinery
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• v.15 no.3
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• pp.64-69
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• 2012

Generally the Shrouded type impeller is considered to free from the loss of tip leakage flow, but it is actually not possible to complete sealing between the rotating impeller and the sealing which is stay still. As a result, there is the possibility of flow leaking between impeller exit to entrance, especially with high pressure ratio compressor machine. The Cavity leakage flow is expected to influence negative effect on a machine performance and also inner flow structure. In this study, Impeller with shroud-casing gap leakage flow is simulated by numerical method (Using CFX 12.1). The influence of leakage flow on compressor performance and efficiency will be analysed, also detail flowfield change will posted.

• The KSFM Journal of Fluid Machinery
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• v.20 no.2
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• pp.11-16
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• 2017

The accurate prediction of leakage flow through the brush element of brush seal at the steam turbine is important to find optimum design parameters for increasing an efficiency. In this study, CFD analysis method using commercial software FLUENT is proposed to predict leakage through the brush element. Since the brush element has a complex three-dimensional shape with many bristle assemblies, it is difficult to analyze the flow field. Therefore, if the brush element is assumed to be porous medium region, the analysis time can be shortened. Two determination methods of resistance coefficients of the Darcian porous medium equation are suggested. By comparing the 2D and 3D CFD analysis results for the leakage of the brush element using the two resistance coefficient determination methods, the effectiveness of the analysis for the porous medium assumption is proved.