• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.6
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• pp.220-229
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• 1985

This paper proposes a new optimal unit commitment algorithm for the rational operation of electric power systems. Especially, the algorithm is improved by considering transmission line capacity limits and load forecasting uncertainty with the consideration of the participation factors of each units, so that the method becomes more reliable and flexible one. The transmission losses are considered by using updated penalty factors obtained from the constant matrixes of the fast decoupled load flow method, the system loads are distributed at each buses, and the several necessary operational constraints are also considered for the purpose of presenting a more practicable scheme. Finally, the effectiveness of the proposed algorithm has been demonstrated by applying to the 23-bus model system.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.70-79
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• 2015

With the rise of the interest in a renewable system, the importance of the Life Cycle Cost Analysis(LCCA), an economic evaluation tool, has been increasing. However, there is an inevitable gap between a real cost and an estimation from LCCA because of the uncertainty of the external environment in real world. As the input variables in an analysis, such as a real discount rate and an energy cost, ares subject to change as time goes by, strategic decision on the current operating system is made depending on the real cost. Current economic evaluation approaches have treated only the fluctuation of input variables without consideration of the flexibility in operation, which has consequently led to the impairment on the reliability of LCCA. Therefore, new approach needs to be proposed to consider both the uncertainty of input variables and operational flexibility. To address this issue, the application of the Real Option to LCCA is presented in this study. Through a case analysis of LCCA of a solar heating system, the limits and current status of LCCA are identified. As a result, quantitative presentation of strategic decisions has been added in the new approach to implement the traditional approach.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.629-634
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• 2016

In this study, we investigated the effect of factors that influence the measurement of smoke density using synthetic rubber flooring. The characteristics of rolling stock in an enclosed environment can cause enormous loss of life by smoke inhalation during fires inside passenger cars. The amount of smoke generation from interior materials for rolling stock is strictly restricted domestically and in other countries. Precise measurement of smoke density is therefore required to assess the fire performance of interior materials. Major factors that influence the measurement of smoke density include the uniformity of the specimen, the variations in conditions and instruments, and the operational and maintenance environment of the instruments. The contribution of factors was analyzed by estimating the uncertainty to investigate the contribution ratios of the major factors. The results show a contribution ratio of about 86% for the variation from the measurement of light transmission using a photomultiplier tube. Thus, this factor was the most representative for the measurement of smoke density. The contribution ratio of the other factors was low at about 11%, including irradiant flux conditions (${\pm}0.5 kW/m^2$) and the influence of the operational and maintenance environment of the instrument. These results were obtained using specimens with high uniformity.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.423-431
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• 2011

Warfighting experimentation is an important process for identifying requirements against changing military environment and for verifying proposed measures for reforming military service. The wargame simulation experiment is regarded as one of the most effective means to warfighting experimentation, and its importance is increasing than ever. On the other hand, the results of wargame experiments could be unreliable due to the uncertainty involved in the experimental procedure. To improve the reliability of the experimental results, systematic experimental procedures and analysis methods must be employed, and the design and analysis of experiments technique can be used effectively for this purpose. In this paper, AWAM, a wargame simulator, is used to optimize the organization of operational troops. The simulation model describes a warfighting situation in which the 'survival rate of our force' and the 'survival rate of the enemy force' are considered as responses, 'the numbers of weapons in the squad' as control factors, and 'the uncontrollable variables of the battlefield' as noise factors. In addition, for the purpose of effective experimentation, the product array approach in which the inner and outer orthogonal arrays are crossed is adopted. Then, the signal-to-noise-ratio for each response and the desirabilities for the means and standard deviations of responses are calculated and used to determine a compromise optimal solution. The experimental procedures and analysis methods developed in this paper can provide guidelines for designing and analyzing wargame simulation experiments for similar warfighting situations.

• Smart Structures and Systems
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• v.24 no.5
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• pp.631-639
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• 2019

Finite element analysis is one of the important methods to study the structural performance. Due to the simplification, discretization and error of structural parameters, numerical model errors always exist. Besides, structural characteristics may also change because of material aging, structural damage, etc., making the initial finite element model cannot simulate the operational response of the structure accurately. Based on Bayesian methods, the initial model can be updated to obtain a more accurate numerical model. This paper presents the work on the field test, modal identification and model updating of a Chinese reinforced concrete pagoda. Based on the ambient vibration test, the acceleration response of the structure under operational environment was collected. The first six translational modes of the structure were identified by the enhanced frequency domain decomposition method. The initial finite element model of the pagoda was established, and the elastic modulus of columns, beams and slabs were selected as model parameters to be updated. Assuming the error between the measured mode and the calculated one follows a Gaussian distribution, the posterior probability density function (PDF) of the parameter to be updated is obtained and the uncertainty is quantitatively evaluated based on the Bayesian statistical theory and the Metropolis-Hastings algorithm, and then the optimal values of model parameters can be obtained. The results show that the difference between the calculated frequency of the finite element model and the measured one is reduced, and the modal correlation of the mode shape is improved. The updated numerical model can be used to evaluate the safety of the structure as a benchmark model for structural health monitoring (SHM).

• Hwankyungkyoyuk
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• v.15 no.1
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• pp.68-82
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• 2002

My responses to Kim Kyung-Ok's Critique on my critique on the Hungerford approach can be summarized as follows; First, it was argued that possible confusions and misunderstandings around the concept of behavior in REB were mainly caused by Hungerford himself who has used the word in several different ways, from a bunch of overt actions to almost all kinds of responses including cognitive skills, without any clear operational definition of it for more than 20 years. It seems to be needed for future users of the word, 'Behavior' to Prevent unnecessary confusions by providing their operational definition of it. Second, REB is too ambiguous to be a legitimate goal of environmental education and too outcome-oriented to be a meaningful measure for environmental education research. Anyone who accept REB as a goal of EE or a measure for research should clearly suggest procedures and criteria for judging the environmental responsibility of actions under consideration. Third, the Hungerford approach has begun by realizing the limit of a linear traditional behavior change system and has been evolving toward a complex model with dynamic interactions among/between cognitive variables and affective variables. However, it still has one-way structural orientation toward 'Behavior' with no feedbacks. Addition of some feedback processes would make the model more flexible and realistic. Finally, both the Hines model and the Hungeford model were established based on a series of behavioristic studies including three doctoral dissertations equiped with a list of actions which were prejudged to be environmentally responsible by the researchers, not by the learners. What they were primarily interested in was not how mind functions during the learning processes but how learners' behavior can be effectively changed. Considering uncertainty and complexity associated with environmental problems, a great deal of efforts ought to be made toward more context-based and less normative studies applying cognitive psychology and quantitative approaches.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.641-649
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• 2021

Fuel oil consumption (FOC) must be minimized to determine the economic route of a ship; hence, the ship power must be predicted prior to route planning. For this purpose, a numerical method using test results of a model has been widely used. However, predicting ship power using this method is challenging owing to the uncertainty of the model test. An onboard test should be conducted to solve this problem; however, it requires considerable resources and time. Therefore, in this study, a deep feed-forward neural network (DFN) is used to predict ship power using deep learning methods that involve data pattern recognition. To use data in the DFN, the input data and a label (output of prediction) should be configured. In this study, the input data are configured using ocean environmental data (wave height, wave period, wave direction, wind speed, wind direction, and sea surface temperature) and the ship's operational data (draft, speed, and heading). The ship power is selected as the label. In addition, various treatments have been used to improve the prediction accuracy. First, ocean environmental data related to wind and waves are preprocessed using values relative to the ship's velocity. Second, the structure of the DFN is changed based on the characteristics of the input data. Third, the prediction accuracy is analyzed using a combination comprising five hyperparameters (number of hidden layers, number of hidden nodes, learning rate, dropout, and gradient optimizer). Finally, k-means clustering is performed to analyze the effect of the sea state and ship operational status by categorizing it into several models. The performances of various prediction models are compared and analyzed using the DFN in this study.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.41-46
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• 2023

Smart factory construction projects are continuously being carried out domestically and abroad. In particular, in times of increasing uncertainty, interest in smart factories is increasing to improve corporate productivity. Currently, the government-led smart factory construction project is continuously being promoted in Korea. The tangible results of this construction project are very positive in indicators such as productivity improvement, quality improvement, and cost reduction. On the other hand, various contents are revealed in the survey to identify operational difficulties after building a smart factory. In this study, we analyzed difficulties (problems) in operation after establishing the system shown in the survey conducted in 2017 and 2020, and derived improvement plans for them. If these improvement measures are implemented in the relevant process of the smart factory construction project, it is expected that the operational difficulties felt by companies will be reduced, and a system with higher satisfaction than before will be established.

• Structural Monitoring and Maintenance
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• v.10 no.1
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• pp.87-105
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• 2023

Seismic regulations have been updated from time to time to accommodate an increase in seismic hazards. Comparison of seismic fragility of the existing bridges in Indonesia from different historical periods since the era before 1990 will be the basis for seismic assessment of the bridge stock in Indonesia, most of which are located in earthquake-prone areas, especially those built many years ago with outdated regulations. In this study, seismic fragility curves were developed using incremental non-linear time history analysis and more holistically according to the actual strength of concrete and steel material in Indonesia to determine the uncertainty factor of structural capacity, βc. From the research that has been carried out, based on the current seismic load in SNI 2833:2016/Seismic Map 2017 (7% probability of exceedance in 75 years), the performance level of the bridge in the era before SNI 2833:2016 was Operational-Life Safety whereas the performance level of the bridge designed with SNI 2833:2016 was Elastic - Operational. The potential for more severe damage occurs in greater earthquake intensity. Collapse condition occurs at As = F_PGA x PGA value of bridge Era I = 0.93 g; Era II = 1.03 g; Era III = 1.22 g; Era IV = 1.54 g. Furthermore, the fragility analysis was also developed with geometric variations in the same bridge class to see the effect of these variations on the fragility, which is the basis for making bridge risk maps in Indonesia.