• Journal of Applied Reliability
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• v.16 no.2
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• pp.90-97
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• 2016

Purpose: Majority of bridges and roads in Gangwon Province have been carrying loads associated with heavy materials such as rocks, mining products, and cement. This location-specific live loads have contributed to the present situation of overloading, compared to other provinces in Korea. However, the bridges in Gangwon province are designed by national bridge design specification, without considering the location-specific live load characteristics. Therefore, this study focuses on the real traffic data accumulated on regional weighing station to verify the live load characteristics, including actual live load gross vehicle weight, axle weight axle spacings, and number of trucks. Methods: In order to take into account the location specific live load, a governmental weigh station (38th national highway Miro) have been selected and the passing truck data are processed. Based on the truck survey, trucks are categorized into 3 different shapes, and each shape has been idealized into normal distribution. Then, the resulting survey data are processed to predict the target maximum live load values, including the axle loads and gross vehicle weights in 75 years service life span. Results: The results are compared to the nationally used DB-24 live loads, and the results show that nationally recognized DB-24 live load does not sufficiently represent real traffic in mountaineous region in Gangwon province. Conclusion: The comparison results in the recommendation of location-specific live load that should be taken into account for bridge design and evaluation.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.171-177
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• 2021

In terms of distribution planning, accurate electric load prediction is one of the most important factors. The future load prediction has manually been performed by calculating the maximum electric load considering loads transfer/switching and multiplying it with the load increase rate. In here, the risk of human error is inherent and thus an automated maximum electric load forecasting system is required. Although there are many existing methods and techniques to predict future electric loads, such as regression analysis, many of them have limitations in reflecting the nonlinear characteristics of the electric load and the complexity due to Photovoltaics (PVs), Electric Vehicles (EVs), and etc. This study, therefore, proposes a method of predicting future electric loads on distribution lines by using Machine Learning (ML) method that can reflect the characteristics of these nonlinearities. In addition, predictive models were developed based on actual data collected at KEPCO's existing distribution lines and the adequacy of developed models was verified as well. Also, as the distribution planning has a direct bearing on the investment, and amount of investment has a direct bearing on the maximum electric load, various baseline such as maximum, lowest, median value that can assesses the adequacy and accuracy of proposed ML based electric load prediction methods were suggested.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.2
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• pp.128-136
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• 2008

It is necessary to estimate the cooling load of the next day for effective control of ice thermal storage system. In this paper, new methodology is proposed to estimate the cooling load using design parameters of building and predicted weather data. Only six input parameters such as sensible heat coefficient and constant, latent heat coefficient and constant, maximum and minimum temperature are necessary to obtain hourly distribution of cooling load for the next day. Two benchmarking buildings(hospital and research institute) are selected to validate the performance of the proposed method, and the estimated cooling loads in hourly and daily bases are calculated and compared with the measured data for E hospital. The estimated results show fairly good agreement with the measured data for both buildings.

• Geomechanics and Engineering
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• v.7 no.1
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• pp.37-53
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• 2014

A Web-based pile load test (WBPLT) system was developed and implemented in this study. Object-oriented and concept-based software design techniques were adopted to integrate the pile load test database into the system. A total of 673 case histories of pile load test were included in the database. The data consisted of drilled shaft and driven precast concrete pile axial load tests in drained, undrained, and gravel loading conditions as well as pre-analyzed data and back-calculated design parameters. Unified modeling language, a standard software design tool, was utilized to design the WBPLT system architecture with five major concept-based components. These components provide the static structure and dynamic behavior of system message flows in a visualized manner. The open-source Apache Web server is the building block of the WBPLT system, and PHP Web programming language implements the operation of the WBPLT components, particularly the automatic translation of user query into structured query language. A simple search and inexpensive query can be implemented through the Internet browser. The pile load test database is helpful, and data can be easily retrieved and utilized worldwide for research and advanced applications.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.231-234
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• 2008

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in load demand data. The main aim of our work is to forecast customers' contract information from capacity of daily power consumption patterns. According to the result, we try to evaluate the contract information's suitability. The proposed our approach consists of three stages: (i) data preprocessing: noise or outlier is detected and removed (ii) cluster analysis: SOMs clustering is used to create load patterns and the representative load profiles and (iii) classification: we applied the K-NNs classifier in order to predict the customers' contract information base on power consumption patterns. According to the our proposed methodology, power load measured from AMR(automatic meter reading) system, as well as customer indexes, were used as inputs. The output was the classification of representative load profiles (or classes). Lastly, in order to evaluate KNN classification technique, the proposed methodology was applied on a set of high voltage customers of the Korea power system and the results of our experiments was presented.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.466-471
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• 2014

An asynchronous optical packet-switching (AOPS) node with load-balancing capability can achieve better performance in reducing the high packet-loss ratio (PLR) and time delay caused by unbalanced traffic. This paper proposes a novel dynamic load-balancing algorithm for an AOPS node with limited buffer and without wavelength converters, and considering the data flow distribution and service levels. By calculating the occupancy state of the output ports, load state of the input ports, and priorities for data flow, the traffic is balanced accordingly. Simulations demonstrate that asynchronous variant data packets and output traffic can be automatically balanced according to service levels and the data flow distribution. A PLR of less than 0.01% can be achieved, as well as an average time delay of less than 0.46 ns.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1039-1046
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• 2022

After the COVID-19 pandemic, the spread of the untact culture and the Fourth Industrial Revolution, which generates various types of data, generated so much data that it was not compared to before. This led to higher data throughput, revealing little by little the limitations of the existing network system centered on vendors and hardware. Recently, SDN technology centered on users and software that can overcome these limitations is attracting attention. In addition, SDN-based load balancing techniques are expected to increase efficiency in the load balancing area of the server cluster in the data center, which generates and processes vast and diverse data. Unlike existing SDN load distribution studies, this paper proposes a load distribution technique in which a controller checks the state of a server according to the occurrence of an event rather than periodic confirmation through a monitoring technique and allocates a user's request by weighting it according to a load ratio. As a result of the desired experiment, the proposed technique showed a better equal load balancing effect than the comparison technique, so it is expected to be more effective in a server cluster in a large and packet-flowing data center.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.4
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• pp.255-261
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• 2016

Korean Power System are operating a load shedding system to prevent voltage instability phenomenon caused by severe line contingencies. In order to apply the load shedding scheme should be selected a location, amount, delay time. Current load shedding system is load shedding amount that has been calculated in the steady-state analysis to load shed the total amount in first level, load shedding amount calculated in advance, it is possible to perform an unnecessary load shedding. In this paper, set a multi-level load shedding control strategy step-by-step selection of load shedding amount for the prevention of excessive load shedding. In addition, through a voltage resilience analysis of the power system by applying motor load ratio and sensitivity parameter to selection the multi level load shedding ratio and delay time. For this reason, to take advantage of the limit data of interchange power, by utilizing interface power flow data to set a multi-level load shedding control strategy for the stabilization of the Korean Power System.

• Transactions of the KSME C: Technology and Education
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• v.5 no.2
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• pp.115-126
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• 2017

This paper proposes an accelerated life evaluation of drive shaft for the power train parts of special purpose vehicle. It is necessary the real load data of usage level driving load condition for life evaluation of power train parts, but we can't get the load spectrum data for evaluation in many case of special purpose vehicle. So, in this paper, the road load spectrum data for evaluation is created by modeling and simulation based on vehicle data and special road condition. The inverse power model is used for accelerated life test. The equivalent torque of load spectrum is achieved using the Miner's Rule. This paper also proposes the calibrated acceleration life test method for drive shaft. The fatigue test is performed through three stress levels. The lifetime at normal stress level is predicted by extrapolation, and is verified through comparison of experimental results and load spectrum data.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.539-548
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• 1998

This study was intended to develop a load spectrum acting on a transmission of agricultural tractors. Transmission loads were measured at the input shaft of the transmission and final drive shaft of the tractors. The measurement were conducted in five field conditions at two speed levels under plowing operations in Korea. Two torque transducers were developed for the respective load measurements and other necessary instrumentations were made to collect the data and store them in a data logger. The time-histories of the torque loads were analyzed and transformed into the load spectra using the rainflow counting and Smith-Watson-Topper methods. Comparisons of the load spectra developed under different conditions were made to investigate their characteristics. The effects on the load levels of soil and plowing speeds were also investigated. Finally, a load spectrum combining the results of the spectrum analysis was developed and proposed as a load source for the reliability test of transmissions.