• International conference on construction engineering and project management
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• 2022.06a
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• pp.269-276
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• 2022

The robustness of a supply chain (i.e., the ability to cope with external and internal disruptions and disturbances) becomes more critical in ensuring the success of a construction project because the supply chain of today's construction project includes more and diverse suppliers. Previous studies indicate that topological features of the supply chain critically affect its robustness, but there is still a great challenge in characterizing and quantifying the impact of network topological features on its robustness. In this context, this study aims to identify network measures that characterize topological features of the supply chain and evaluate their impact on the robustness of the supply chain. Network centrality measures that are commonly used in assessing topological features in social network analysis are identified. Their validity in capturing the impact on the robustness of the supply chain was evaluated through an experiment using randomly generated networks and their simulations. Among those network centrality measures, the PageRank centrality and its standard deviation are found to have the strongest association with the robustness of the network, with a positive correlation coefficient of 0.6 at the node level and 0.74 at the network level. The findings in this study allows for the evaluation of the supply chain network's robustness based only on its topological design, thereby enabling practitioners to better design a robust supply chain and easily identify vulnerable links in their supply chains.

• Korean Journal of Construction Engineering and Management
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• v.19 no.3
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• pp.33-42
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• 2018

In the aftermath of an earthquake, seismic-damaged infrastructure systems loss estimation is the first step for the disaster response. However, lifeline systems' ability to supply service can be volatile by external factors such as disturbances of nearby facilities, and not by own physical issue. Thus, this research develops the bayesian model for probabilistic inference on common-cause and cascading failure of seismic-damaged lifeline systems. In addition, the authors present network robustness estimation metrics in the context of failure propagation. In order to quantify the functional loss and observe the effect of the mitigation plan, power and water supply system in Daegu-Gyeongbuk in South Korea is selected as case network. The simulation results show that reduction of cascading failure probability allows withstanding the external disruptions from a perspective of the robustness improvement. This research enhances the comprehensive understanding of how a single failure propagates to whole lifeline system performance and affected region after an earthquake.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2179-2183
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• 2009

As urbanization is progressed, the network for distributing water in a basin become complex due to the spatial expansion and parameter uncertainties of water supply systems. When a long range water supply plan is determined, the total construction and operation cost has to be evaluated with the system components and parameter uncertainties as many as possible. In this paper, the robust optimization approach of Bertsimas and Sim is applied in a hypothetical system to find a solution which remains feasible under the possible parameter uncertainties having the correlation effect between the uncertain coefficients. The system components to supply, treatment, and transport water are included in the developed water supply system and construction and expansion of the system is allowed for a long-range period. In this approach, the tradeoff between system robustness and total cost of the system is evaluated in terms of the degree of conservatism which can be converted to the probability of constraint violation. As a result, the degree of conservatism increases, the total cost is increased due to the installation of large capacity of treatment and transportation systems. The applied robust optimization technique can be used to determine a long-range water supply plan with the consideration of system failure.

• IE interfaces
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• v.13 no.4
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• pp.658-667
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• 2000

Seasonal variation of natural gas demand coupled with rigid and stable import pattern of gas represents the characteristic feature of the Korean Liquified Natural Gas(LNG) industry. This attribute has required a huge amount of investment for the construction of storage facility. Thus, to minimize the supply cost, it is legitimate to reduce storage requirement itself. In this study, we combine three alternative methods to deal with the storage requirement to minimize the supply cost. Those are (1) adding additional storage tanks, (2) inducing large firm customers, and (3) constructing gas-turbine self generation facilities. Methodologically, we employ the mixed integer program (MIP) to optimize the system. The model also consider demand and price-setting scheme in separate modules. From the results, it is shown that if alternatives are combined optimally, a number of storage tanks can be reduced substantially compared with the original capacity plan set by the industry authorities. We perform various sensitivity analyses to check the robustness of the results. The methodology presented in this study can be applied to the other physical network industry, such as hydraulics. The empirical results will shed some light on the rationalization of capacity planning of the Korean natural gas industry.

• Smart Structures and Systems
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• v.28 no.6
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1645-1655
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• 2016

A Dynamic Voltage Restorer (DVR) model is proposed to eliminate the short-term voltage disturbances that occur in the grid-connected mode, the switching between grid-connected mode and the stand-alone mode of a Microgrid. The proposed DVR structure is based on a conventional cascaded H-bridge multilevel inverter (MLI) topology; a novel composite control strategy is presented, which could ensure the compensation ability of voltage sag by the DVR. Moreover, the compensation to specified order of harmonic is added to implement effects that zero-steady error compensation to harmonic voltage in specified order of the presented control strategy; utilizing wind turbines-batteries units as DC energy storage components in the Microgrid, the operation cost of the DVR is reduced. When the Microgrid operates under stand-alone mode, the DVR can operate on microsource mode, which could ease the power supply from the main grid (distribution network) and consequently be favorable for energy saving and emission reduction. Simulation results validate the robustness and effective of the proposed DVR system.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.8 s.338
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• pp.35-42
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• 2005

This paper describes novel flip-flops with improved robustness and reduced power consumption. Variable sampling window flip-flop (VSWFF) adjusts the width of the sampling window according to input data, providing robust data latching as well as shorter hold time. The flip-flop also reduces power consumption for higher input switching activities as compared to the conventional low-power flip-flop. Clock swing-reduced variable sampling window flip-flop (CSR-VSWFF) reduces clock power consumption by allowing the use of a small swing clock. Unlike conventional reduced clock swing flip-flops, it requires no additional voltage higher than the supply voltage, eliminating design overhead related to the generation and distribution of this voltage. Simulation results indicate that the proposed flip-flops provide uniform latency for narrower sampling window and improved power-delay product as compared to conventional flip-flops. To evaluate the performance of the proposed flip-flops, test structures were designed and implemented in a $0.3\mu m$ CMOS process technology. Experimental result indicates that VSWFF yields power reduction for the maximum input switching activity, and a synchronous counter designed with CSR-VSWFF improves performance in terms of power consumption with no use of extra voltage higher than the supply voltage.