• Advances in concrete construction
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• v.3 no.2
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• pp.91-102
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• 2015

In this paper, the load-deflection analysis of the Carbon Fiber Reinforced Polymer (CFRP) strengthened Reinforced Concrete (RC) slab using Recurrent Neural Network (RNN) is investigated. Six reinforced concrete slabs having dimension $1800{\times}400{\times}120mm$ with similar steel bar of 2T10 and strengthened using different length and width of CFRP were tested and compared with similar samples without CFRP. The experimental load-deflection results were normalized and then uploaded in MATLAB software. Loading, CFRP length and width were as neurons in input layer and mid-span deflection was as neuron in output layer. The network was generated using feed-forward network and a internal nonlinear condition space model to memorize the input data while training process. From 122 load-deflection data, 111 data utilized for network generation and 11 data for the network testing. The results of model on the testing stage showed that the generated RNN predicted the load-deflection analysis of the slabs in acceptable technique with a correlation of determination of 0.99. The ratio between predicted deflection by RNN and experimental output was in the range of 0.99 to 1.11.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1221-1226
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• 2015

This paper proposes a multiple switch mode power supply (SMPS) system based on the wireless network which controls variable load. The system enables power supply of up to 600W using 200W SMPS as a unit module and provides a controlling function of output power based on variable load and a monitoring function based on wireless network. The controlling function for output power measures the variation of output power and facilitates efficient power supply by controlling output power based on the measured variation value. The monitoring function guarantees a stable power supply by observing the multiple SMPS system in real time via wireless network. The performance of the proposed system was examined by various experiments. In addition, it was verified through standardized test of Korea Testing Certification. The results were given and discussed.

• Proceedings of the KIEE Conference
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• summer
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• pp.560-562
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• 2004

$SF_6$ gas has been increasingly used as the insulating and arc-suppressing medium in switchgears which are used as the protection devices of power system. Nowadays, most of power companies adopted the $SF_6$ gas-type load break switch for increasing the reliability of distribution network by its superior durability against external environmental condition, in substitution for air-type and oil-type switches. But, it is important to establish the general estimation process for the testing and estimation for long-term reliability Accordingly, the national standard(RS C0031) was made for the reliability assessment of $SF_6$ gas load break switch and the testing facilities were also set in KERI(Korea Electrotechlology Research Institute). This paper presents the requirements of RS C0031 for reliability assessment of $SF_6$ gas load break switch and synopsis of the accelerated life testing facilities for $SF_6$ gas load break switch.

• Structural Engineering and Mechanics
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• v.59 no.4
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• pp.703-718
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• 2016

Masonry arch bridges present a large segment of Iranian railway bridge stock. The ever increasing trend in traffic requires constant health monitoring of such structures to determine their load carrying capacity and life expectancy. In this respect, the performance of one of the oldest masonry arch bridges of Iranian railway network is assessed through field tests. Having a total of 11 sensors mounted on the bridge, dynamic tests are carried out on the bridge to study the response of bridge to test train, which is consist of two 6-axle locomotives and two 4-axle freight wagons. Finite element model of the bridge is developed and calibrated by comparing experimental and analytical mid-span deflection, and verified by comparing experimental and analytical natural frequencies. Analytical model is then used to assess the possibility of increasing the allowable axle load of the bridge to 25 tons. Fatigue life expectancy of the bridge is also assessed in permissible limit state. Results of F.E. model suggest an adequacy factor of 3.57 for an axle load of 25 tons. Remaining fatigue life of Veresk is also calculated and shown that a 0.2% decrease will be experienced, if the axle load is increased from 20 tons to 25 tons.

• Tribology and Lubricants
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• v.11 no.3
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• pp.24-30
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• 1995

This paper was undertaken to recognize the pattern of the wear debris by neural network as a link for the development of diagnosis system for movable condition of the lubricated machine surface. The wear test was carried out under different experimental conditions using the wear test device was made in laboratory and wear testing specimen of the pin-on-disk type were rubbed in paraffine series base oil, by varying applied load, sliding distance and mating material. The neural network has been used to pattern recognition of four parameter (diameter, elongation, complex and contrast) of the wear debris and learned the friction condition of five values (material 3, applied load 1, sliding distance 1). The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by the neural network. The characteristic parameter of the large wear debris over a few micron size enlarged recognition ability.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.452-454
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• 2003

$SF_6$ gas has been increasingly used as the insulating and arc-suppressing medium in switchgears which are used as the protection devices of power system. Nowadays, most of power companies adopted the $SF_6$ gas-type load break switch for increasing the reliability of distribution network by its superior durability against external environmental condition, in substitution for air-type and oil-type switches. But, it is important to establish the general estimation process for the testing and estimation for long-term reliability. Accordingly, this paper presents the reliability testing method for $SF_6$ gas load break switch which is based on the analysis of the failure mode and the statistics.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.3975-3984
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• 2022

Distributed control system architecture is adopted for I&C systems of Prototype Fast Breeder Reactor, where the geographically distributed control systems are connected to centralized servers & display stations via switched Ethernet networks. TCP/IP communication plays a significant role in the successful operations of this architecture. The communication tasks at control nodes are taken care by TCP/IP offload modules; local area switched network is realized using layer-2/3 switches, which are finally connected to network interfaces of centralized servers & display stations. Safety, security, reliability, and fault tolerance of control systems used for safety-related applications of nuclear power plants is ensured by indigenous design and qualification as per guidelines laid down by regulatory authorities. In the case of commercially available components, appropriate suitability analysis is required for getting the operation clearances from regulatory authorities. This paper details the proposed approach for the suitability analysis of TCP/IP communication nodes, including control systems at the field, network switches, and servers/display stations. Development of test platform using commercially available tools and diagnostics software engineered for control nodes/display stations are described. Each TCP link behavior with impaired packets and multiple traffic loads is described, followed by benchmarking of the network switch's routing characteristics and security features.

• The KIPS Transactions:PartD
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• v.14D no.6
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• pp.649-656
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• 2007

Today, controller area network(CAN) is a field bus that is nowadays widespread in distributed embedded systems due to its electrical robustness, low price, and deterministic access delay. However, its use safety-critical applications has been controversial due to dependability limitation, such as those arising from its bus topology. Thus it is important to analyze the performance of the network in terms of load of data bus, maximum time delay, communication contention, and others during the design phase of the controller area network. In this paper, a simulation algorithm is introduced to evaluate the communication performance of the vehicle network and apply software base fault injection techniques. This can not only reduce any erratic implementation of the vehicle network but it also improves the reliability of the system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.6
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• pp.47-52
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• 2012

DAS(Distribution Automation System) is equipped with several software applications such as service restoration, loss minimization, and protective relay coordination. The software applications of DAS are very sensitive to the amount of section load being carried by a particular section of distribution lines. Moreover, each software application requires a different parameter of the section load according to its purpose. Therefore, This paper proposes a new section load management method using real-time measurement data of the distribution lines. In order to provide accurate data to DAS applications, this method considers section loads in terms of the relationship of power versus time. In order to establish that the proposed method is feasible, a performance-testing simulator was developed, and case studies were conducted for a modified real distribution network.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1042-1047
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• 2004

Voltage control is an essential part of the electric energy transmission and distribution system to maintain proper voltage limit at the consumer's terminal. Besides the generating units that provide the basic voltage control, there are many additional voltage-controlling agents e.g., shunt capacitors, shunt reactors, static VAr compensators, regulating transformers mentioned in [1], [2]. The most popular one, among all those agents for controlling voltage levels at the distribution and transmission system, is the on-load tap changer transformer. It serves two functions-energy transformation in different voltage levels and the voltage control. Artificial Neural Network (ANN) has been realized as a convenient tool that can be used in controlling the on load tap changer in the distribution transformers. Usage of the ANN in this area needs suitable training and testing data for performance analysis before the practical application. This paper briefly describes a procedure of processing the data to train an Artificial Neural Network (ANN) to control the tap changer operating decision of parallel transformers for a closed primary bus. The data set are used to train a two layer ANN using three different neural net learning algorithms, namely, Standard Backpropagation [3], Bayesian Regularization [4] and Scaled Conjugate Gradient [5]. The experimental results are presented including performance analysis.