• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.588-593
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• 2011

The Main design parameters of ship HVAC systems are pressure drop and noise analysis of ducts. The Noise prediction for HVAC(Heating, Ventilating and Air Conditioning) systems are normally performed by empirical method suggested by NEBB(National Environmental Balancing Bureau, 1994), but NEBB's method is not suitable for the ship HVAC systems. In this paper, numerical analysis methods are used to develop a noise prediction method for the ship HVAC systems, especially for large ducts. To develop regression formula of attenuation of sound pressure level in large duct, Boundary Element Method(BEM) is used. Using dynamic loss coefficient which is suggested by ASHRAE fitting data base and numerical methods of HVAC noise analysis, integrated HVAC noise analysis of Program is developed. The developed program can present pressure drop and noise analysis of the ship HVAC systems. To verify the accuracy and convenience of the developed program, prediction of HVAC system for Semi-Submersible Drilling RIG is carried out and the results are compared with measurement of noise level during sea trial.

• International Journal of Fluid Machinery and Systems
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• v.8 no.4
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• pp.221-229
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• 2015

For efficient design process of regenerative blower, the present study provides new generalized pressure and leakage flow loss models, which can be used in the performance analysis method of regenerative blower. The present performance analysis on designed blower is made by incorporating momentum exchange theory between impellers and side channel with mean line analysis method, and its pressure loss and leakage flow models are generalized from the related fluid mechanics correlations which can be expressed in terms of blower design variables. The present performance analysis method is applied to four existing models for verifying its prediction accuracy, and the prediction and the test results agreed well within a few percentage of relative error. Furthermore, the present performance analysis method is also applied in developing a new blower used for fuel cell application, and the newly designed blower is manufactured and tested through chamber-type test facility. The performance prediction by the present method agreed well with the test result and also with the CFD simulation results. From the comparison results, the present performance analysis method is shown to be suitable for the actual design practice of regenerative blower.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.1109-1112
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• 2017

The precise prediction of radiation embrittlement of aged reactor pressure vessels (RPVs) is a prerequisite for the long-term operation of nuclear power plants beyond their original design life. The expiration of the operation licenses for Korean reactors the RPVs of which are made from SA533B-1 plates and welds is imminent. Korean regulatory rules have adopted the US Nuclear Regulatory Commission's transition temperature shift (TTS) models to the prediction of the embrittlement of Korean reactor pressure vessels. The applicability of the TTS model to predict the embrittlement of Korean RPVs made of SA533B-1 plates and welds was investigated in this study. It was concluded that the TTS model of 10 CFR 50.61a matched the trends of the radiation embrittlement in the SA533B-1 plates and welds better than did that of Regulatory Guide (RG) 1.99 Rev. 2. This is attributed to the fact that the prediction performance of 10 CFR 50.61a was enhanced by considering the difference in radiation embrittlement sensitivity among the different types of RPV materials.

• Wind and Structures
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• v.36 no.6
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• pp.367-377
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• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Transactions of Materials Processing
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• v.18 no.1
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• pp.59-66
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• 2009

In this study, V-notch part has been considered as one of safety components in rectangular cup used for mobile device. This kind of safety component in rectangular cup with the V-notch part, which controls adequately the increased internal pressure in the rectangular cup, plays an important role to prevent the explosion from the excessive internal pressure. The protecting mechanism on the mobile device against the explosion is that a series of fracture on the V-notch part at the critical internal pressure level occurs. Therefore, it is very crucial to estimate accurately the working pressure range of the safety device. Relationship between the working internal pressure and fracture phenomenon at V-Notch part was investigated through numerical analysis using ductile fracture criteria. Integral value, I, of the used ductile fracture criteria was calculated from effective stress and strain, and then the bursting pressure of the V-notch part was extracted. Comparisons between the estimated and experimental results show that this systematic approach to predict bursting pressure using the ductile fracture criteria gives fairly good agreements.

• Atmosphere
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• v.33 no.4
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• pp.355-365
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• 2023

To proactively manage climate risk, near-term climate predictions on annual to decadal time scales are of great interest to various communities. This study evaluates the near-term climate prediction skills in East Asia with DePreSys4 retrospective decadal predictions. The model is initialized every November from 1960 to 2020, consisting of 61 initializations with ten ensemble members. The prediction skill is quantitatively evaluated using the deterministic and probabilistic metrics, particularly for annual mean near-surface temperature, land precipitation, and sea level pressure. The near-term climate predictions for May~September and November~March averages over the five years are also assessed. DePreSys4 successfully predicts the annual mean and the five-year mean near-surface temperatures in East Asia, as the long-term trend sourced from external radiative forcing is well reproduced. However, land precipitation predictions are statistically significant only in very limited sporadic regions. The sea level pressure predictions also show statistically significant skills only over the ocean due to the failure of predicting a long-term trend over the land.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.591-598
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• 2000

In the present study, the variation of settlement, pore water pressure and undrained shear strength through model tests were measured. Also, the variation of water content, unit weight and shear strength by the vane shear tests were observed. In this study, appropriate deposit time of construction equipments used in treatment of hydraulic fills is determined from the prediction curve of increased shear strength in dredged fills.

• Journal of the korean Society of Automotive Engineers
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• v.6 no.2
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• pp.47-54
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• 1984

The predictions of the mean effective pressure and the exhaust emission of NOx in hydrogen fueled spark ignition engine were studied. And the predictions were compared to the experimental results of D.B. Kittelson and H.S.Homan. The modeling was based on Otto cycle and the prediction of NOx was performed by extended Zeldovich mechanism. The differences between predictions and experimental results were 20 - 30% in the mean effective pressure and 10 - 20% in the concentration of NOx where the equivalence ratio .phi. was 0.6 - 0.8.

• Geomechanics and Engineering
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• v.1 no.1
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• pp.75-84
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• 2009

Artificial neural networks (ANNs) are a new type of information processing system based on modeling the neural system of human brain. The prediction of swell pressures from easily determined soil properties, namely, initial dry density, initial water content, and plasticity index, have been investigated by using artificial neural networks. The results of the constant volume swell tests in oedometers, performed on statically compacted specimens of Bentonite-Kaolinite clay mixtures with varying soil properties, were trained in an ANNs program and the results were compared with the experimental values. It is observed that the experimental results coincided with ANNs results.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.27-36
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• 2004

A Numerical analysis has been used to predict the performance in the automotive water pump with double discharge single suction. The influence of parameters such as coolant flow rate, rotational speed, ratio of blade height and clearance has been investigated. Also, the prediction of hydraulic performances such as static pressure rise, shaft power, hydraulic power and pump efficiency is carried out on the water pump including an impeller and a volute casing. A full size water pump test bench has been developed to validate the CFD flow model. Discharge flow rate, suction pressure, discharge pressure, rotational speed and torque measurements are provided. Coolant temperature is 8$0^{\circ}C$, water tank pressure is 1 kgf/$\textrm{cm}^2$ and flow rates vary.