• Wind and Structures
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• v.33 no.6
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• pp.423-435
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• 2021

Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China.

• The Journal of Bigdata
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• v.7 no.2
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• pp.217-224
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• 2022

Since online shopping has become common, people can easily buy fashion goods anytime, anywhere. Therefore, consumers quickly respond to various environmental variables such as weather and sales prices. Therefore, utilizing big data for efficient inventory management has become very important in the fashion industry. In this paper, the changes in sales volume of fashion goods due to changes in temperature is analyzed via the proposed big data analysis algorithm by utilizing actual big data from Korean fashion company 'A'. According to the simulation results, it was confirmed that Bidirectional-LSTM(Bi-LSTM) compared to LSTM(Long Short-Term Memory) takes more simulation time about more than 50%, but the prediction accuracy of non-periodic time series data such as clothing product sales data is the same.

• Journal of Ecology and Environment
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• v.47 no.2
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• pp.49-62
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• 2023

Background: Over the past three decades, gradual eustatic sea-level rise has been considered a primary exogenous factor in the increased frequency of flooding and biological changes in several salt marshes. Under this paradigm, the potential importance of short-term events, such as ocean storminess, in coastal hydrology and ecology is underrepresented in the literature. In this study, a simulation was developed to evaluate the influence of wind waves driven by atmospheric oscillations on sedimentary and vegetation dynamics at the Skallingen salt marsh in southwestern Denmark. The model was built based on long-term data of mean sea level, sediment accretion, and plant species composition collected at the Skallingen salt marsh from 1933-2006. In the model, the submergence frequency (number yr^-1) was estimated as a combined function of wind-driven high water level (HWL) events (> 80 cm Danish Ordnance Datum) affected by the North Atlantic Oscillation (NAO) and changes in surface elevation (cm yr^-1). Vegetation dynamics were represented as transitions between successional stages controlled by flooding effects. Two types of simulations were performed: (1) baseline modeling, which assumed no effect of wind-driven sea-level change, and (2) experimental modeling, which considered both normal tidal activity and wind-driven sea-level change. Results: Experimental modeling successfully represented the patterns of vegetation change observed in the field. It realistically simulated a retarded or retrogressive successional state dominated by early- to mid-successional species, despite a continuous increase in surface elevation at Skallingen. This situation is believed to be caused by an increase in extreme HWL events that cannot occur without meteorological ocean storms. In contrast, baseline modeling showed progressive succession towards the predominance of late-successional species, which was not the then-current state in the marsh. Conclusions: These findings support the hypothesis that variations in the NAO index toward its positive phase have increased storminess and wind tides on the North Sea surface (especially since the 1980s). This led to an increased frequency and duration of submergence and delayed ecological succession. Researchers should therefore employ a multitemporal perspective, recognizing the importance of short-term sea-level changes nested within long-term gradual trends.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.239-248
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• 2006

The interaction between ground water and structure is complicated behavior which cannot be easily investigated In the laboratory and monitored in the fields. In this study numerical simulation of the interactive behavior was performed using sophisticated coupled-finite element method. Hydraulic behavior of structure is modeled using solid elements with finite Permeability. Recovery of ground water table in the long-term is considered by controlling hydraulic boundary conditions. The results showed that the interaction effect is significant. Particularly non-symmetry in the lining permeability resulted in highly unbalanced pore water pressure which may cause detrimental effects on inner linings of tunnels acting as drains.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.8
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• pp.308-316
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• 1985

This paper proposes an analytic tool for long-term generation expansion planning based on the maximum principle. Many research works have been performed in the field of generation expansion planning. But few works can be found with the maxinmum principle. A recently published one worked by professor Young Moon Park et al. shows remarkable improvements in modeling and computation. But this modeling allows only thermal units. This paper has extended Professor Park's model so that the optimal pumped-storage operation is taken into account. So the ability for practical application is enhanced. In addition, the analytic supply-shortage cost function is included. The maximum principle is solved by gradient search due to its simplicity. Every iteration is treated as if mathematical programming such that all controls from the initial to the terminal time are manipulated within the same plane. Proposed methodology is tested in a real scale power system and the simulation results are compared with other available package. Capability of proposed method is fully demonstrated. It is expected that the proposed method can be served as a powerful analytic tool for long-term generation expansion planning.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.398-400
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• 2002

This paper presents long-term electricity market analysis simulation considering Genco's strategy using P-POOL. In the competitive electricity market, system operation and/or market operation is highly depended on the participants' intention and his planning. We focus on the Genco's strategy, including maintenance scheduling and bidding strategy. And we represent his profit using 3-Bus sample system.

• Special Issue of the Society of Naval Architects of Korea
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• 2006.09a
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• pp.59-64
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• 2006

Most important factor to consider funnel performance is exhaust gas temperature and exhaust gas concentration Electric equipments on the wheelhouse top affected exhaust gas temperature. So, it is important that electric equipments keep away from high temperature. Though exhaust gas concentration is not a regulation and restraint, the exhaust 9as can cause serious problems for the on-board air quality and result in irreversible damage to the ship and people. So, we pocus on the exhaust gas concentration also. When judge whether a measured concentration is acceptable or not, criteria based on the LTEL (Long Term Exposure Limit). In this paper, we carried out the smoke simulation study. For this analysis, we used FLUENT which is commercial CFD (Computational Fluid Dynamics) code.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.10
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• pp.500-506
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• 2005

With the advent of electric power systems moving to a deregulated retail electricity market environment, calculating distribution service tariffs has become a challenging theme for distribution industries and tariff regulators. As distribution business remains as a monopoly, it is necessary to be regulated. And as multiple distribution companies compete with each other, it would be efficient to adopt competition to the determination of distribution service tariffs. This paper proposes a method to calculate distribution service tariffs using yardstick regulation, which can lead to competition among multiple distribution companies. The proposed method takes into account not only recovering revenue requirements but also the advantages of the yardstick regulation based on long-term marginal costs of distribution network expansion algorithms. A computer simulation is carried out to illustrate effectiveness of the proposed method and it is estimated that the algorithm can be applied to compute the distribution service tariffs under retail electricity markets.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1083-1087
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• 1997

Every effort is now being exerted in industrialized and developing countries to reduce emission of greenhouse gases from electric power sector. In this paper, we provide supply-side resource mix strategies in the long-term generation expansion planning under the expected greenhouse gas regulations. Under the environmental regulations, we explore the least-cost generation expansion plan of Korea and determine the composition of future resource mixes. Our analysis is performed on the basis of the revised WASP package which can evaluate emission of carbon dioxide from each power plant. The evaluation process of carbon dioxide emissions, which can consider the efficiency and operating conditions of each generator simultaneously, has been incorporated into the probabilistic production cost simulation module of WASP.

• ETRI Journal
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• v.45 no.2
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• pp.329-337
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• 2023

For safe last-mile autonomous robot delivery services in complex environments, rapid and accurate collision prediction and detection is vital. This study proposes a suitable neural network model that relies on multiple navigation sensors. A light detection and ranging technique is used to measure the relative distances to potential collision obstacles along the robot's path of motion, and an accelerometer is used to detect impacts. The proposed method tightly couples relative distance and acceleration time-series data in a complementary fashion to minimize errors. A long short-term memory, fully connected layer, and SoftMax function are integrated to train and classify the rapidly changing collision countermeasure state during robot motion. Simulation results show that the proposed method effectively performs collision prediction and detection for various obstacles.