• Journal of the Korean Society of Propulsion Engineers
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• v.14 no.3
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• pp.16-22
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• 2010

The gas turbine engine performance relies greatly on its component performance characteristics. Generally, engine manufacturers do not provide engine purchasers the component performance characteristics which can be obtained by lots of experimental tests at various operating conditions and big amount of expenses. In previous works the component maps have mostly been generated by scaling from a similar component map. However this scaling method has large error at off design points, specially in high altitude operation. Therefore this work proposes an inverse modeling method that can generate components maps of PT6A-67A turboprop engine using performance data provided by the engine manufacturer. In addition, evaluation can be made through comparison between performance analysis results using the performance simulation program including the generated compressor map and performance data.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.1
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• pp.70-79
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• 2013

In this work, a steady-state performance modeling and off-design performance analysis of the 2-spool separate-flow turbofan engine named (BR715-56) which is a power plant for the narrow body commercial aircraft is carried out for engine performance behaviors investigation and condition monitoring using a commercial code MATLAB/SIMULINK. Firstly, the engine component maps of fan, high pressure compressor, high pressure turbine and low pressure turbine are generated from similar component maps using the scaling method, and then the off-design performance simulation model is constructed by the mass flow matching and the work matching between components. The model is developed using SIMULINK, which has advantages of easy steady-stare and dynamic modelling and user friendly interface function. It is found that the off-design performance analysis results using the proposed model are well agreed with the performance analysis results by GASTURB at various operating conditions.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.3
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• pp.330-337
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• 2016

In this paper, component sizing and analysis of the novel plug-in hybrid electric vehicle powertrain configuration is conducted. Newly proposed powertrain configuration in prior study has an internal combustion engine and two electric motors. To optimize component size of the vehicle system and reduction gear ratio, component sizing methodology is proposed and conducted. Required power for vehicle's dynamic performance is calculated to decide minimum power requirement of powertrain component combination. Component size of engine and electric motor are optimized using vehicle simulation to maximize fuel economy performance. Optimized powertrain configuration and vehicle simulation results present validation of newly proposed vehicle system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.5
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• pp.576-582
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• 2015

Generally, the fuel economy of hybrid electric vehicle (HEV) is effected by the size of each component. In this study the fuel economy for HEV of our own making is evaluated using backward simulator, where dynamic programming is applied. In a competition, the vehicle is running through the road course that includes many speed bumps and steep grade. Therefore, the new driving cycle including road grade is developed for the simulation. The backward simulator is also developed through modeling each component. A performance map of engine and motor for component sizing is made from the existing engine map and motor map adapted to the HEV of our own making. For optimal component sizing, the feasible region is defined by restricting the power range of power sources. Optimal component size for best fuel economy is obtained within the feasible region through the backward simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.473-476
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• 2005

This paper is proposed a robust various feature parameters in noise. Feature parameter MFCC(Mel Frequency Cepstral Coefficient) used in conventional speech recognition shows good performance. But, parameter transformed feature space that uses PCA(Principal Component Analysis)and ICA(Independent Component Analysis) that is algorithm transformed parameter MFCC's feature space that use in old for more robust performance in noise is compared with the conventional parameter MFCC's performance. The result shows more superior performance than parameter and MFCC that feature parameter transformed by the result ICA is transformed by PCA.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.11
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• pp.943-956
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• 2003

A numerical program has been developed for the simulation of automotive engine cooling system. The program determines the mass flow rate of engine coolant circulating the engine cooling system and radiator cooling air when the engine speed is adopted by appropriate empirical correlation. The program used the method of thermal balance at individual element through the model for radiator component in radiator analysis. This study has developed the program that predicts the coolant mass flow rate, inlet and outlet temperatures of each component in the engine cooling system (engine, transmission, radiator and oil cooler) in its state of thermal equilibrium. This study also combined the individual programs and united into the total performance analysis program of the engine cooling system operating at a constant vehicle speed. An air conditioner system is also included in this engine cooling system so that the condenser of the air conditioner faces the radiator. The effect of air conditioner to the cooling performance, e.g., radiator inlet temperature, of the radiator and engine system was examined. This study could make standards of design of radiator capacity using heat rejection with respect to the mass flow rate of cooling air. This study is intended to predict the performance of each component at design step or to simulate the system when specification of the component is modified, and to analyze the performance of the total vehicle engine cooling system.

• Earthquakes and Structures
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• v.16 no.5
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• pp.575-588
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• 2019

Seismic design method based on bearing capacity has been widely adopted in building codes around the world, however, damage and collapse state of structure under strong earthquake can not be reflected accurately. This paper aims to present a deformation-based seismic design method based on the research of RC component deformation index limit, which combines with the feature of Chinese building codes. In the proposed method, building performance is divided into five levels and components are classified into three types according to their importance. Five specific design approaches, namely, "Elastic Design", "Unyielding Design", "Limit Design", "Minimum Section Design" and "Deformation Assessment", are defined and used in different scenarios to prove whether the seismic performance objectives are attained. For the components which exhibit ductile failure, deformation of components under strong earthquake are obtained quantitatively in order to identify the damage state of the components. For the components which present brittle shear failure, their performance is guaranteed by bearing capacity. As a case study, seismic design of an extremely irregular twin-tower high rise building was carried out according to the proposed method. The results evidenced that the damage and anti-collapse ability of structure were estimated and controlled by both deformation and bearing capacity.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.709-718
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• 2019

The international nuclear industry has undergone a lot of changes since the Fukushima, Chernobyl and TMI nuclear power plant accidents. However, there are still large and small component deficiencies at nuclear power plants in the world. There are many causes of electrical equipment defects. There are also factors that cause component failures due to human errors. This paper analyzed the root causes of failure and types of human error in 300 cases of electrical component failures. We analyzed the operating experience of electrical components by methods of root causes in K-HPES (Korean-version of Human Performance Enhancement System) and by methods of human error types in HuRAM+ (Human error-Related event root cause Analysis Method Plus). As a result of analysis, the most electrical component failures appeared as circuit breakers and emergency generators. The major causes of failure showed deterioration and contact failure of electrical components by human error of operations management. The causes of direct failure were due to aged components. Types of human error affecting the causes of electrical equipment failure are as follows. The human error type group I showed that errors of commission (EOC) were 97%, the human error type group II showed that slip/lapse errors were 74%, and the human error type group III showed that latent errors were 95%. This paper is meaningful in that we have approached the causes of electrical equipment failures from a comprehensive human error perspective and found a countermeasure against the root cause. This study will help human performance enhancement in nuclear power plants. However, this paper has done a lot of research on improving human performance in the maintenance field rather than in the design and construction stages. In the future, continuous research on types of human error and prevention measures in the design and construction sector will be required.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.717-724
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• 2005

We often extract a new feature from the original features for the purpose of reducing the dimensions of feature space and better classification. In this paper, we show feature extraction method based on independent component analysis can be used for classification. Entropy and mutual information are used for the selection of ordered features. Performance of classification based on independent component analysis is compared with principal component analysis for three real data sets.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.05a
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• pp.105-109
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• 2003

A new scaling method for the prediction of gas turbine components characteristics using experimental data of gas turbine test unit has been proposed. In order to minimize the analyzed performance error in the this study, firstly component maps were constructed by real experimental performance data at some operating conditions and a polynomial obtained from scaling factors at given conditions, and then the simulated performance using the identified maps was compared with the performance result using the currently used traditional scaling method. In comparison, the performance analysis result by the currently used traditional scaling method was met well agreed with the real engine performance at most off-design points except for the design point. However the performance analysis result using the newly proposed scaling method had good agreement with the experimental results within maximum 5％ error.