• Journal of the Earthquake Engineering Society of Korea
• /
• v.23 no.6
• /
• pp.301-309
• /
• 2019

A methodology to assess seismic fragility of a nuclear power plant (NPP) using a conditional mean spectrum is proposed as an alternative to using a uniform hazard response spectrum. Rather than the single-scenario conditional mean spectrum, which is the conventional conditional mean spectrum based on a single scenario, a multi-scenario conditional mean spectrum is proposed for the case in which no single scenario is dominant. The multi-scenario conditional mean spectrum is defined as the weighted average of different conditional mean spectra, each one of which corresponds to an individual scenario. The weighting factors for scenarios are obtained from a deaggregation of seismic hazards. As a validation example, a seismic fragility assessment of an NPP containment structure is performed using a uniform hazard response spectrum and different single-scenario conditional mean spectra and multi-scenario conditional mean spectra. In the example, the number of scenarios primarily influences the median capacity of the evaluated structure. Meanwhile, the control frequency, a key parameter of a conditional mean spectrum, plays an important role in reducing logarithmic standard deviation of the corresponding fragility curves and corresponding high confidence of low probability of failure (HCLPF) capacity.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.22 no.5
• /
• pp.27-43
• /
• 2019

This study applied the LANDIS-II model to the forest vegetation of the study area in Yeongdong-gun, Korea to identify climate effects on ecosystems of forest vegetation. The main purpose of the study is to examine the long-term changes in forest aboveground biomass(AGB) under three different climate change scenarios; The baseline climate scenario is to maintain the current climate condition; the RCP 4.5 scenario is a stabilization scenario to employ of technologies and strategies for reducing greenhouse gas emissions; the RCP 8.5 scenario is increasing greenhouse gas emissions over time representative with 936ppm of $CO_2$ concentration by 2100. The vegetation survey and tree-ring analysis were conducted to work out the initial vegetation maps and data for operation of the LANDIS model. Six types of forest vegetation communities were found including Quercus mongolica - Pinus densiflora community, Quercus mongolica community, Pinus densiflora community, Quercus variabilis-Quercus acutissima community, Larix leptolepis afforestation and Pinus koraiensis afforestation. As for changes in total AGB under three climate change scenarios, it was found that RCP 4.5 scenario featured the highest rate of increase in AGB whereas RCP 8.5 scenario yielded the lowest rate of increase. These results suggest that moderately elevated temperatures and $CO_2$ concentrations helped the biomass flourish as photosynthesis and water use efficiency increased, but huge increase in temperature ($above+4.0^{\circ}C$) has resulted in the increased respiration with increasing temperature. Consequently, Species productivity(Biomass) of trees decrease as the temperature is elevated drastically. It has been confirmed that the dominant species in all scenarios was Quercus mongolica. Like the trends shown in the changes of total AGB, it revealed the biggest increase in the AGB of Quercus mongolica under the RCP 4.5 scenario. AGB of Quercus mongolica and Quercus variabilis decreased in the RCP 4.5 and RCP 8.5 scenarios after 2050 but have much higher growth rates of the AGB starting from 2050 under the baseline scenario. Under all scenarios, the AGB of coniferous species was eventually perished in 2100. In particular they were extinguished in early stages of the RCP 4.5 and RCP 8.5 scenarios. This is because of natural selection of communities by successions and the failure to adapt to climate change. The results of the study could be expected to be effectively utilized to predict changes of the forest ecosystems due to climate change and to be used as basic data for establishing strategies for adaptation climate changes and the management plans for forest vegetation restoration in ecological restoration fields.

• Journal of Power Electronics
• /
• v.15 no.5
• /
• pp.1367-1379
• /
• 2015

A hybrid HVDC system that is composed of line commutated converter (LCC) at the rectifier side and voltage source converter (VSC) in series with LCC at the inverter side is studied in this paper. The start-up strategy, DC fault ride-through capability, and fault recovery strategy for the hybrid HVDC system are proposed. The steady state and dynamic performances under start-up, AC fault, and DC fault scenarios are analyzed based on a bipolar hybrid HVDC system. Furthermore, the immunity of the LCC inverter in hybrid HVDC to commutation failure is investigated. The simulation results in PSCAD/EMTDC show that the hybrid HVDC system exhibits favorable steady state and dynamic performances, in particular, low susceptibility to commutation failure, excellent DC fault ride-through, and fast fault recovery capability. Results also indicate that the hybrid HVDC system can be a good alternative for large-capacity power transmission over a long distance byoverhead line.

• Journal of Distribution Science
• /
• v.18 no.8
• /
• pp.35-45
• /
• 2020

Purpose: Do close linkages among employees during service encounters always enhance customer satisfaction? Drawing on literature in social psychology, this research argues that under certain circumstances close linkages among employees undermine customer satisfaction. More specifically, this research explores a service failure context and shows that higher task interaction among employees during service encounters leads to higher perceived firm entitativity, resulting in an individual employee's service failure being detrimental to customer satisfaction with the firm. Data and research methodology: A series of experiments using scenarios across different service contexts was used in order to test hypotheses. Data was collected via Amazon Mechanical Turk and the models were tested using Hayes PROCESS. Results: The results show that interactions among employees during service result in 1) lower satisfaction with the firm and 2) lower revisit intentions in the future when there is a service failure by an individual employee. Following the main effects analysis, mediation analysis shows that the effect of employee interaction on customer satisfaction with the firm and revisit intention is mediated by perceived firm entitativity. Implications: By examining contexts where employee interaction may be detrimental to firms, this research provides novel insights on how to manage communications among service employees.

• Journal of Applied Reliability
• /
• v.17 no.2
• /
• pp.92-102
• /
• 2017

Purpose: Reliability prediction standards consider environmental conditions, such as temperature, humidity and vibration in order to predict the reliability of the electronics components. There are many types of standards, and each standard has a different failure rate prediction model, and requires different environmental conditions. The purpose of this study is to make a sensitivity analysis by changing the temperature which is one of the environmental conditions. By observing the relation between the temperature and the failure rate, we perform the sensitivity analysis for standards including MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES. Methods: we establish environmental conditions in accordance with maneuver weapon systems's OMS/MP and mission scenarios then predict the reliability using MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES through the case of DC-DC Converter. Conclusion: Reliability prediction standards show different sensitivities of their failure rates with respect to the changing temperatures.

• ETRI Journal
• /
• v.44 no.3
• /
• pp.361-378
• /
• 2022

In 5G, the required target for interruption time during a handover (HO) is 0 ms. However, when a handover failure (HOF) occurs, the interruption time increases significantly to more than hundreds of milliseconds. Therefore, to fulfill the requirement in as many scenarios as possible, we need to minimize HOF rate as close to zero as possible. 3GPP has recently introduced conditional HO (CHO) to improve mobility robustness. In this study, we propose "ZEro handover failure with Unforced and automatic time-to-execute Scaling" (ZEUS) algorithm to optimize HO parameters easily in the CHO. Analysis and simulation results demonstrate that ZEUS can achieve a zero HOF rate without increasing the ping-pong rate. These two metrics are typically used to assess an HO algorithm because there is a tradeoff between them. With the introduction of the CHO, which solves the tradeoff, only these two metrics are insufficient anymore. Therefore, to evaluate the optimality of an HO algorithm, we define a new integrated HO performance metric, mobility-aware average effective spectral efficiency (MASE). The simulation results show that ZEUS provides higher MASE than LTE and other CHO variants.

• Journal of Korea Water Resources Association
• /
• v.52 no.10
• /
• pp.719-728
• /
• 2019

Valve in water distribution network (WDN), that controls the flow in pipes, is used to isolate a segment (a part of WDN) under abnormal water supply conditions (e.g., pipe breakage, water quality failure event). The segment isolation degrades pressure and water serviceability in neighboring area during the water service outage of the segment. Recent hydraulic and water quality failure events reported encouraging WDN valve installation based on various abnormal water supply scenarios. This study introduces a scenario-based optimal valve installation approach to optimize the number of valves, the amount of undelivered water, and a shortest water supply path indicator (i.e., Hydraulic Geodesic Index). The proposed approach is demonstrated in the valve installation of Pescara network, and the optimal valve sets are obtained under multiple scenarios and compared to the existing valve set. Pressure-driven analysis (PDA) scheme is used for a network hydraulic simulation. The optimal valve set derived from the proposed method has 19 fewer valves than the existing valve set in the network and the amount of undelivered water was also lower for the optimal valve set. Reducing the reservoir head requires a greater number of valves to achieve the similar functionality of the WDN with the optimal valve set of the original reservoir head. This study also compared the results of demand-driven analysis (DDA) and the PDA and confirmed that the latter is required for optimal valve installation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.2
• /
• pp.224-232
• /
• 2018

According to government policy, renewable energy facility such as solar power generation is being implemented for newly constructed buildings. In recent years, the introduction of Energy Storage System (ESS) served as an emergency power for replacing an existing diesel generator has been increasing. Furthermore, in order to expand the efficacy of the ESS operation, operation in combination with renewable energy sources such as solar and wind power generation is increasing. Hence, development of the ESS operation algorithms for emergency mode as well as the peak power cut mode, which is the essential feature of ESS, are necessary. The operational scenarios of ESS need to consider load power requirement and the amount of the power generation by renewable energy sources. For the verification of the developed scenarios, tests under the actual situation are demanded, but there is a difficulty in simulating the emergency operation situation such as system failure in the actual site. Therefore, this paper proposes simulation models for the HILS(Hardware In the Loop Simulation) and operation modes developed through HILS for the ESS operated with renewable energy source under peak power reduction and emergency modes. The paper shows that the ESS operation scenarios developed through HILS work properly at the actual site, and it verifies the effectiveness of the control logic developed by the HILS.

• Journal of the Korea Safety Management & Science
• /
• v.16 no.4
• /
• pp.81-90
• /
• 2014

Modern systems can be characterized by ever-increasing complexity of both the functionality and system scale. Thus, due to the complexity the chances of accidents resulting from systems failure can then be growing. Even worse is that those accidents could result in disastrous damage to the human being and properties as well. Therefore, the need for the developed systems to be assured with systems safety is apparent in a variety of industries such as rail, automobiles, airplanes, ships, oil refinery, chemical production plants, and so on. To this end, in the industry an appropriate safety standard has been published for its own safety-assured products. One of the core activities included in the most safety standards is hazard analysis. A conventional approach to hazard analysis seems to depend upon the scenarios derived from the ones used previously in similar systems or based on former experience. The objective of this paper is to study an improved process for scenario-based hazard analysis. To achieve the goal, the top-level safety requirements have first been reflected in the scenarios. By analyzing and using them, the result has then lead to the development of safety-assured systems. The method of modeling and simulation has been adopted in the generation and verification of scenarios to check whether the safety requirements are reflected properly in the scenarios. Application of the study result in the case of rail safety assurance has also been discussed.

• Journal of the Society of Naval Architects of Korea
• /
• v.60 no.2
• /
• pp.95-109
• /
• 2023

In the 4th industrial revolution, changes in the technological paradigm have had a direct impact on the maintenance system of ships. The 2-stroke low speed engine system integrates with the core equipment required for propulsive power. The Condition Based Management (CBM) is defined as a technology that predictive maintenance methods in existing calender-based or running time based maintenance systems by monitoring the condition of machinery and diagnosis/prognosis failures. In this study, we have established a framework for CBM technology development on our own, and are engaged in engineering-based failure analysis, data development and management, data feature analysis and pre-processing, and verified the reliability of failure mode DB using LSTM algorithms. We developed various simulated failure mode scenarios for 2-stroke low speed engine and researched to produce data on onshore basis test_beds. The analysis and pre-processing of normal and abnormal status data acquired through failure mode simulation experiment used various Exploratory Data Analysis (EDA) techniques to feature extract not only data on the performance and efficiency of 2-stroke low speed engine but also key feature data using multivariate statistical analysis. In addition, by developing an LSTM classification algorithm, we tried to verify the reliability of various failure mode data with time-series characteristics.