• Journal of Ocean Engineering and Technology
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• v.32 no.6
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• pp.411-418
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• 2018

This paper introduces a new method of ice load generation in the time domain for the station-keeping performance evaluation of Arctic offshore structures. This method is based on the ice load spectrum and mean ice load. Recently, there has been increasing interest in Arctic offshore technology for the exploration and exploitation of the Arctic region because of the better accessibility to the Arctic ocean provided by the global warming effect. It is essential to consider the ice load during the development of an Arctic offshore structure. In particular, when designing a station-keeping system for an Arctic offshore structure, a consideration of the ice load acting on the vessel in the time domain is essential to ensure its safety and security. Several methods have been developed to consider the ice load in the time domain. However, most of the developed methods are computationally heavy because they consider every ice floe in the sea ice field to calculate the ice load acting on the vessel. In this study, a new approach to generate the ice load in the time domain with computational efficiency was suggested, and its feasibility was examined. The ice load spectrum and mean ice load were acquired from a numerical analysis with GPU-event mechanics (GEM) software, and the ice load with the varying heading of a vessel was reconstructed to show the feasibility of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.699-703
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• 1999

It is known that the LDC(Line-Drop Compensator) becomes to lose the function of proper voltage regulation for its load currents due to the real and reactive power generated by DGS(Dispersed Generation System), when DGS is introduced into the power distribution system of which the voltage is controlled by LDC. Therefore, in that case, it is very difficult to regulate the distribution line voltage properly by using LDC. One possible solution for this problem is the real-time voltage regulation method which is to optimally regulate the sending-end voltage in real-time by collecting the real-time load data of each load data of each load section between measuring points and by calculating the optimal seding-end voltage value from them. For this, we must know the real-time load data of each load section. In this paper, a modeling method of representing a load section on high voltage line with DGSs as an equivalent lumped load is proposed for gaining the real-time load data. In addition a method of locating the measuring points is proposed. Then, these proposed methods are evaluated through computer simulations.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.76-83
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• 2004

This study aimed to empirically investigate perceived discomfort depending upon external load, upper limb postures and their holding time. Discomfort was obtained through an experiment, in which external load, wrist flexion/extension, elbow flexion, shoulder flexion and adduction/abduction were used as experimental variables. The subjects were instructed to hold given postures for 60s and to rate their subjective discomfort scores at 5s, 20s, 40s and 60s by using the free modulus method of magnitude estimation. The results showed that while only external load and elbow flexion were statistically significant at the holding time of 5s at ${\alpha}=0.05$ or 0.10, external load and upper limb postures excluding shoulder adduction/abduction significantly affected discomfort ratings at 20s, 40s and 60s at ${\alpha}=0.01$ or 0.05. Discomfort scores were also significantly different between four posture holding times at ${\alpha}=0.01$. The effects of external load and holding time were much larger than those of upper limb postures. Based on the results of this study, it is recommended that external load and holding time as well as working postures betaken into consideration to precisely quantify postural load in industry.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.71-82
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• 2009

As a solution to spectrum under-utilization problem, Cognitive radio (CR) introduces a dynamic spectrum access technology. In the area, one of the most important problems is how secondary users (SUs) should choose between the available channels, which means how to achieve load balancing between channels. We consider spectrum load balancing problem for CR system in frequency domain and especially in time domain. Our objective is to balance the load among the channels and balance the occupied time length of slots for a fixed channel dynamically in order to obtain a user-optimal solution. In frequency domain, we refer to Dynamic Noncooperative Scheme with Communication (DNCOOPC) used in distributed system and a distributed Dynamic Spectrum Load Balancing algorithm (DSLB) is formed based on DNCOOPC. In time domain, Spectrum Load Balancing method with QoS support is proposed based on Dynamic Feed Back theory and Hash Table (SLBDH). The performance of DSLB and SLBDH are evaluated. In frequency domain, DSLB is more efficient compared with existing Compare_And_Balance (CAB) algorithm and gets more throughput compared with Spectrum Load Balancing (SLB) algorithm. Also, DSLB is a fair scheme for all devices. In time domain, SLBDH is an efficient and precise solution compared with Spectrum Load Smoothing (SLS) method.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.594-597
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• 2007

We present in this paper a novel mid and long term power load prediction method using temporal pattern mining from AMR (Automatic Meter Reading) data. Since the power load patterns have time-varying characteristic and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Also, research on data mining for analyzing electric load patterns focused on cluster analysis and classification methods. However despite the usefulness of rules that include temporal dimension and the fact that the AMR data has temporal attribute, the above methods were limited in static pattern extraction and did not consider temporal attributes. Therefore, we propose a new classification method for predicting power load patterns. The main tasks include clustering method and temporal classification method. Cluster analysis is used to create load pattern classes and the representative load profiles for each class. Next, the classification method uses representative load profiles to build a classifier able to assign different load patterns to the existing classes. The proposed classification method is the Calendar-based temporal mining and it discovers electric load patterns in multiple time granularities. Lastly, we show that the proposed method used AMR data and discovered more interest patterns.

• Journal of Korean Association for Spatial Structures
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• v.5 no.1 s.15
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• pp.81-89
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• 2005

Walking loads are influenced by various parameters so that they need to be measured considering such parameters. Walking frequency(rate) is experimentally investigated as the most important parameter in determining the walking load expressed with dynamic load factor. This study focuses on the derivation of continuous walking load-time functions at any walking frequency ranging from 1.30Hz to 2.70Hz. Experiments were conducted to obtain time-histories of walking loads at the increment of 0.1Hz, which are decomposed into harmonic loads by the Fourier transformation. The polynomial load-time functions are proposed representing the relationship between harmonic coefficients and walking frequencies, thereby easily formulating walking load-time histories for dynamic load factor with various walking frequencies.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.11
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• pp.596-603
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• 2004

This paper proposes an expert system based on the pattern recognition method which can enhance the accuracy and effectiveness of real-time bus reconfiguration strategy for the transfer of faulted load when a main transformer fault occurs in the automated substation. The minimum distance classification method is adopted as the pattern recognition method of expert system. The training pattern set is designed MTr by MTr to minimize the searching time for target load pattern which is similar to the real-time load pattern. But the control pattern set, which is required to determine the corresponding bus reconfiguration strategy to these trained load pattern set is designed as one table by considering the efficiency of knowledge base design because its size is small. The training load pattern generator based on load level and the training load pattern generator based on load profile are designed, which are can reduce the size of each training pattern set from max L/sup (m+f)/ to the size of effective level. Here, L is the number of load level, m and f are the number of main transformers and the number of feeders. The one reduces the number of trained load pattern by setting the sawmiller patterns to a same pattern, the other reduces by considering only load pattern while the given period. And control pattern generator based on exhaustive search method with breadth-limit is designed, which generates the corresponding bus reconfiguration strategy to these trained load pattern set. The inference engine of the expert system and the substation database and knowledge base is implemented in MFC function of Visual C++ Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and pattern recognition solution based on diversity event simulations for typical distribution substation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.407-410
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• 2010

This paper presents an advanced load allocation algorithm in Direct Load Control(DLC) system. It is important to aggregate a various demand side resource which is surely controllable at the peak power time for a successful DLC system. Previous load allocation algorithm appropriate for DLC system is based on interchanged information, but, this algorithm can not derive optimal solutions. In this paper, we develop the optimal algorithm and the new load allocation algorithm in polynomial time. The simulation results show that the proposed heuristic algorithm for DLC system is very effective.

• Tribology and Lubricants
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• v.39 no.2
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• pp.35-42
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• 2023

Bearing is a mechanical component that supports loads and transmits rotation. As the application of high-value-added products such as semiconductors, aviation, and robots have recently become diverse and more precise, an accurate bearing performance prediction and evaluation technology is required. Bearing performance evaluation can be divided into evaluations based on bearing theory and on numerical analysis. An evaluation based on numerical analysis is a technique that has been highlighted because the problems that remained unsolved owing to time problems can be solved through recent developments in computers. However, current studies have the disadvantage of not considering the essential changes over time and bearing rotation. In this study, bearing performance evaluation based on rigid body dynamic analysis considering rotation and load over time is performed. Rigid body dynamic analysis is performed for deep groove ball bearing to calculate the load applied by the ball. The reliability of the analysis is verified by comparing it with the results calculated using bearing theory. In addition, rigid body dynamic analysis is performed for automotive wheel bearings to calculate the contact angle and load applied by the ball for cases where axial load and radial load are applied, respectively. The effect of rotation and load over time is evaluated from these results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.24-31
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• 2012

This study is designed to predict the overall electric power load, to apply the method of time sharing and to reduce simultaneous load factor of electric power when authorized by user entering demand plans and using schedules into the user's interface for a certain period of time. This is about smart grid, which reduces electric power load through simultaneous load factor of electric power reduction system supervision agent. Also, this study has the following characteristics. First, it is the user interface which enables authorized users to enter and send/receive such data as demand plan and using schedule for a certain period of time. Second, it is the database server, which collects, classifies, analyzes, saves and manages demand forecast data for a certain period of time. Third, is the simultaneous load factor of electric power control agent, which controls usage of electric power by getting control signal, which is intended to reduce the simultaneous load factor of electric power by the use of the time sharing control system, form the user interface, which also integrate and compare the data which were gained from the interface and the demand forecast data of the certain period of time.