• Journal of the Korean Society for Railway
• /
• v.10 no.6
• /
• pp.717-722
• /
• 2007

Most of DC 1500V electric railway substations have adopted diode rectifiers to supply stable DC power. However, the diode rectifiers operate in the first quadrant of the voltage-current plane and thus need regenerative inverters which transfer the surplus regenerative power caused by regenerative braking of electric train sets into the grid. In order to select the proper capacity and installation position of regenerative inverter, it needs to investigate the consumed and regenerative energy of the electric traction substations in advance. This paper presents an analysis of regenerative energy in two substations operating in Seoul Seolleung and Kwangju Yangdong substations. DC line voltage and feeder currents are measured for a day to calculate consumed and regenerative power far four feeders. We calculated an amount of regenerative energy consumed in other feeders and estimated the cost reduction in energy consumption due to the reuse of regenerative energy

• New & Renewable Energy
• /
• v.8 no.1
• /
• pp.44-51
• /
• 2012

Due to a high tidal range of up to 10 m on the west coast of Korea, numerous tidal current projects are being planned and constructed. The turbine, which initially converts the tidal energy, is an important component because it affects the efficiency of the entire system. Its performance is determined by design variables such as the number of blades, the shape of foils, and the size of a hub. To design a turbine that can extract the maximum power on the site, the depth and duration of current velocity with respect to direction should be considered. Verifying the performance of a designed turbine is important, and requires a circulating water channel (CWC) facility. A physical model for the performance test of the turbine should be carefully designed and compared to results from computational fluid dynamics (CFD) analysis. In this study, a horizontal axis tidal current turbine is designed based on the blade element theory. The proposed turbine's performance is evaluated using both CFD and a CWC experiment. The sealing system, power train, measuring devices, and generator are arranged in a nacelle, and the complete TCP system is demonstrated in a laboratory scale.

• Journal of Korean Society of Disaster and Security
• /
• v.5 no.2
• /
• pp.81-87
• /
• 2012

Critical infrastructures (energy, information technology and communications, banking, transportation, public government services, etc.) are now more vital to modern society. Citizens, businesses and governments all rely on an array of interlinked physical and information infrastructures to satisfy their needs and perform their daily operations. At the same time, these infrastructures are becoming increasingly interdependent, such that failure of one of them can often propagate and result in domino effects. Recent dramatic episodes, from 9/11 to the Madrid train bombings, the April 2010 ash cloud the power cuts in Korea in 2011, and the cyber-attacks have highlighted the need for a comprehensive, internationally coordinated policy for the protection of critical infrastructures. For the purposes of this report, we define critical infrastructure as infrastructure whose failure would result in substantial damage to society and/or the economy.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.15 no.6
• /
• pp.498-505
• /
• 2010

In-Wheel System is a high-efficiency system to supply a new concept of platform which raises the efficiency of motor drive system and applies it to an environment-friendly automobile by installing a highly efficient electric motor directly to wheels and removing factors of power train. The proliferation of these systems is directly related to the safety of our lives, so check the reliability of the part in the development phase and should be certified. Reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time. This paper presents to the verification methods for durability, one of reliability assessments of the Motor, the study calculated acceleration and deceleration torque and the effective torque from driving conditions of In-Wheel Motor, and based on this, it reduced the test time and suggested the verification methods of In-Wheel Motor reliability through the accelerated life test.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.331-334
• /
• 2011

This is a study about a platform realization measuring the extent of reaction in nerve, as giving a electrical impulse on a nerve pulp regulating a function of muscle, about a measurement of nerve reaction in the amount of current, the lasting time of current, and the position of electrode from a electrical impuls.The position of an electrode in a electrical nerve impuls have nothing to do with all nerves from exercise to all things. There is the Single Twitch Stimulation(STS), Train-of-four(TOF), and Double Burst Stimulation(DBS) in the form of nerve stimulation. This report is needed for selecting MCU of low electric power for a base in embedded system and measuring the extent of reaction after making a sensor interface to know sensitivity of measuring sensor in basic reaction of nerve impuls. The platform is realized to select a high efficiency AD Convertor for raising accuracy in measured data. As the platform in this report was developed for a medical appliances, it was designed to consider user safety in electric power Isolation when making electric power circuit.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.4
• /
• pp.93-99
• /
• 2019

A cross drilling/milling Unit is an important mechanical part which is widely used in many kinds of machining tool, and various gear trains with good accuracy and reliability features are widely used in power transmission systems. A study on a novel power transmission optimization method for driving gear trains in cross drilling/milling units is presented in this paper. A commercial program for gear system simulation, Romax Designer, was used in this research to intuitively observe the gear meshing and the load distribution conditions on the gear teeth. We obtained the optimal modification value through comparing the results of repeated experiments. For validation, optimized gears were fabricated and then measured with a precision tester.

• Journal of the Korean Society of Systems Engineering
• /
• v.18 no.2
• /
• pp.75-93
• /
• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.374-388
• /
• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.1681-1698
• /
• 2011

According to the demands of the times, Inchon international airport railroad opened up step by step but It is situation that much government subsidies are paid because It does not competitive power with road traffic by decline of schedule speed. Inchon international airport railroad users will convert by other transportation and minimize damage their time as travel time is prolonged. Therefore, need high speedization of airport railroad, this may act big role competitive power security as well as airport railroad activation with another public transportation. Thus, this paper suggests that a high speedization possibility section in the sections of airport railroad and train speed elevation effect analysis by roadbed, railroad, system improvement and the most efficient operation intervals analyzing each vehicles (AREX (120km/h), KTX (230km/h), EMU(Electric Multiple Unit, 180km/h) train running pattern.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.12
• /
• pp.237-246
• /
• 2019

The Electro-Mechanical Brake (EMB) is the next generation braking system for automobiles and railway vehicles. Current brake systems for high-speed trains generate a braking force using a pneumatic cylinder, but EMB systems produce that force through a combination of an electric motor and a gear. In this study, an EMB operation mechanism capable of generating a high braking force was proposed, and structural and vibration analyses of the gears and shafts, which are the core parts of the mechanisms, were performed. Dynamic structural analysis confirmed that the maximum stress in the analysis model was within the yield strength of the material. In addition, the design that maximizes the diameter of the motor shaft was found to be advantageous in strength, and large shear stress could be generated in the bolt fixing the gear and eccentric shaft. In addition, a test apparatus that can reproduce the mechanism of the analytical model was fabricated to measure the strain of the fixed bolt part, which is the most vulnerable part. The strain measurement results showed that the error between the analysis and measurement was within 10%, which could verify the accuracy of the analytical model.