• 유체기계공업학회:학술대회논문집
• /
• 2005.12a
• /
• pp.324-330
• /
• 2005

For axial-type turbines which operate at partial admission, a performance prediction model is developed. In this study, losses generated within the turbine are classified to windage loss, expansion loss and mixing loss. The developed loss model is compared with experimental results. Particularly, if a turbine operates at a very low partial admission rate, a circular-type nozzle is more efficient than a rectangular-type nozzle. For this case, a performance prediction model is developed and an experiment is conducted with the circular-type nozzle. The predicted result is compared with the measured performance, and the developed model quite well agrees with the experimental results. So the developed model could be applied to predict the performance of axial-type turbines which operate at various partial admission rates or with different nozzle shape.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.05a
• /
• pp.738-741
• /
• 2003

In general, the essential requirement for cruisers or car ferries is the reduction in noise to ensure high quality and comfort. Recently, the Ro-Ro Passengers Ferry (ROPAX) was built in Hyundai Heavy Industries. In order to minimize the noise levels, careful attention have to De paid by the special committee of experts from the initial design stage to the sea trial. Proper countermeasures, considering the characteristics of sources and receiver spaces, were applied from the noise prediction and various experiment results. Finally, this ship was successfully delivered with excellent noise properties. This paper describes the procedure of noise analysis, the countermeasures of noise control, and the measurement results of the sea trial. Onboard noise analysis had been carried out by statistical energy analysis program and outdoor noise prediction program based on ISO9614. The prediction results are in good agreements with the measurement results. The technology to minimize the noise levels for cruisers or car ferries has been established throughout the construction of this ship.

• The KSFM Journal of Fluid Machinery
• /
• v.9 no.4 s.37
• /
• pp.13-19
• /
• 2006

For axial-type turbines which operate at partial admission, a performance prediction model is developed. In this study, losses generated within the turbine are classified to windage loss, expansion loss and mixing loss. The developed loss model is compared with experimental results. Particularly, if a turbine operates at a very low partial admission rate, a circular-type nozzle is more efficient than a rectangular-type nozzle. For this case, a performance prediction model is developed and an experiment is conducted with the circular-type nozzle. The predicted result is compared with the measured performance, and the developed model quite well agrees with the experimental results. So the developed model could be applied to predict the performance of axial-type turbines which operate at various partial admission rates or with different nozzle shape.

• Journal of Applied Reliability
• /
• v.17 no.2
• /
• pp.103-111
• /
• 2017

Purpose: Accelerated degradation tests can speed time to market and reduce the test time and costs associated with long term reliability tests to verify the required service life of a product or material. This paper proposes a service life prediction method for components or materials using an accelerated degradation tests based on the relationships between temperature and the rate of failure-causing chemical reaction. Methods: The relationship between performance degradation and the rate of a failure-causing chemical reaction is assumed and least square estimation is used to estimate model parameters from the degradation model. Results: Methods of obtaining acceleration factors and predicting service life using the degradation model are presented and a numerical example is provided. Conclusion: Service life prediction of a component or material is possible at an early stage of the degradation test by using the proposed method.

• Journal of Information Processing Systems
• /
• v.15 no.5
• /
• pp.1231-1242
• /
• 2019

This paper presents a two-dimensional attention-based long short-memory (2D-ALSTM) model for stock index prediction, incorporating input attention and temporal attention mechanisms for weighting of important stocks and important time steps, respectively. The proposed model is designed to overcome the long-term dependency, stock selection, and stock volatility delay problems that negatively affect existing models. The 2D-ALSTM model is validated in a comparative experiment involving the two attention-based models multi-input LSTM (MI-LSTM) and dual-stage attention-based recurrent neural network (DARNN), with real stock data being used for training and evaluation. The model achieves superior performance compared to MI-LSTM and DARNN for stock index prediction on a KOSPI100 dataset.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.10
• /
• pp.1-10
• /
• 2009

Precise branch predictor has a profound impact on system performance in modern processor architectures. Recent works show that prediction latency as well as prediction accuracy has a critical impact on overall system performance as well. However, prediction latency tends to be overlooked. In this paper, we propose Branch Pre-Prediction policy to tolerate branch prediction latency. The proposed solution allows that branch predictor can proceed its prediction without any information from the fetch engine, separating the prediction engine from fetch stage. In addition, we propose newly modified BTE structure to support our solution. The simulation result shows that proposed solution can hide most prediction latency with still providing the same level of prediction accuracy. Furthermore, the proposed solution shows even better performance than the ideal case, that is the predictor which always takes a single cycle prediction latency. In our experiments, IPC improvement is up to 11.92% and 5.15% in average, compared to conventional predictor system.

• Journal of Korea Water Resources Association
• /
• v.43 no.8
• /
• pp.721-731
• /
• 2010

The rainfall-runoff relationship is very difficult to predict because it is complicate factor affected by many temporal and spatial parameters of the basin. In recent, models which is based on artificial intelligent such as neural network, genetic algorithm fuzzy etc., are frequently used to predict discharge while stochastic or deterministic or empirical models are used in the past. However, the discharge data which are generally used for prediction as training and validation set are often estimated from rating curve which has potential error in its estimation that makes a problem in reliability. Therefore, in this study, water stage is predicted from antecedent rainfall and water stage data for short term using three models of neural network which trained by error back propagation algorithm and optimized by genetic algorithm and training error back propagation after it is optimized by genetic algorithm respectively. As the result, the model optimized by Genetic Algorithm gives the best forecasting ability which is not much decreased as the forecasting time increase. Moreover, the models using stage data only as the input data give better results than the models using precipitation data with stage data.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.15 no.6
• /
• pp.2109-2124
• /
• 1991

A simulation program is developed to analyse the performance of an axial flow turbine stage based on the meanline prediction method. The gradient projection method is utilized to minimize the aerodynamic losses under the specified constraints on such as flow coefficient, total pressure ratio, stage power and blade loading coefficient. After obtaining the optimum point for minimizing the stage loss, a sensitivity analysis is carried out ground the optimum point to find the effects of the design variables and the design constraints on the stage performance. The result of the senitivity analysis under a constant blade loading coefficient shows that the total loss is more sensitive to the mean diameter, the absolute flow angle at nozzle outlet, the relative flow angle at rotor outlet and the axial mean velocity compared to the chords and the pitches. Moreover, the design constraints on the degree of reaction at root and the blade length-to-diameter ratio are found to be most influencial on the maximization of the overall aerodynamic efficiency.

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.365-372
• /
• 2021

The purpose of this study was to examine the statements characteristics of the pressure ulcer nursing record by natural langage processing and assess the prediction accuracy for each pressure ulcer stage. Nursing records related to pressure ulcer were analyzed using descriptive statistics, and word cloud generators (http://wordcloud.kr) were used to examine the characteristics of words in the pressure ulcer prevention nursing records. The accuracy ratio for the pressure ulcer stage was calculated using deep learning. As a result of the study, the second stage and the deep tissue injury suspected were 23.1% and 23.0%, respectively, and the most frequent key words were erythema, blisters, bark, area, and size. The stages with high prediction accuracy were in the order of stage 0, deep tissue injury suspected, and stage 2. These results suggest that it can be developed as a clinical decision support system available to practice for nurses at the pressure ulcer prevention care.

• Journal of KSNVE
• /
• v.3 no.2
• /
• pp.155-161
• /
• 1993

The vibration generated by the machinery on board is transmitted to the hull and into the water. At the early design stage, the prediction of the hull vibration and the radiated noise level is very important to reduce their levels. In this study, SAE(Statistical Energy Analysis) technique is applied to predict structureborne noise level of the hull considering fluid loading. Rayleigh integral is applied to predict the radiated noise level. The results of comparision between the predictions and measurements for the reinforced cylindrical shell have shown good agreements.