• Smart Structures and Systems
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• v.15 no.2
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• pp.315-334
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• 2015

A main goal of this study is to propose a damage detection technique to detect and localize damages of a top-tensioned riser. In this paper, the top-tensioned finite element (FE) model is considered as an analytical model of the riser, and a vibration-based damage detection method is proposed. The present method consists of a FE model updating and damage index method. In order to accomplish the goal of this study, first, a sensitivity-based FE model updating method using natural frequencies and zero frequencies is introduced. Second, natural frequencies and zero frequencies of the axial mode on the top-tensioned riser are estimated by eigenvalue analysis. Finally, the locations and severities of the damages are estimated from the damage index method. Three numerical examples are considered to verify the performance of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2127-2137
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• 2017

A virtual power plant (VPP) is a system that virtually integrates power resources based on the VPP participating customer (VPC) unit and operates as a power plant. When VPP operators manage resources to maximize their benefits, load reduction instructions may focus on more responsive VPCs, or those producing high profitability, by using VPC resources with high operation efficiency. VPCs may thus encounter imbalance problems during operation. This imbalance in operation time would bring more participation for some VPCs, causing potential degradation of their resources. Such an operation strategy would be not preferable for VPP operators in managing the relationship with VPCs. This issue impedes both continual VPC participation and economical and reliable VPP operation in the long term. An operation algorithm is therefore proposed that considers the operation time of VPC generators for mandatory reduction of power resource consumption. The algorithm is based on constraints of daily and annual operation times when VPP operators of local generators perform capacity-market power transactions. The algorithm maximizes the operator benefit through VPP operations. The algorithm implements a penalty parameter for imbalances in operation times spent by VPC generators in fulfilling their obligations. An evaluation was conducted on VPP operational effects by applying the algorithm to the Korean power market.

• Journal of the Ergonomics Society of Korea
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• v.25 no.3
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• pp.85-96
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• 2006

Main control room(MCR) man-machine interface(MMI) design of advanced nuclear power plants(NPPs) such as APR(advanced power reactor)-1400 can be validated through performance-based tests to determine whether it acceptably supports safe operation of the plant. In this work, plant performance, personnel task, situation awareness, workload, teamwork, and anthropometric/physiological factor are considered as factors for the human performance evaluation. For development of measures in each of the factors, techniques generally used in various industries and empirically proven to be useful are adopted as main measures and some helpful techniques are developed in order to complement the main measures. Also the development of the measures is addressed based on the theoretical background. Finally we discuss the way in which the measures can be effectively integrated and then HUPESS(HUman Performance Evaluation Support System) which is in development based on the integrated way is briefly introduced.

• Journal of the Korean Society of Combustion
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• v.18 no.3
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• pp.44-53
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• 2013

In this study, the economic evaluation for imported coals was conducted for power plant based on thermo-dynamical performance analysis. The number of coal types considered was 1,755 imported by five power generation companies in Korea during the 2010-2012. The higher heating value (HHV) of the coals ranged 4,000-6,500 kcal/kg, mostly sub-bituminous. The 1D thermo-dynamical performance modeling was performed for a 500 MWe standard power plant using PROATES code. It was founded that the low rank coals had negative effects on the plant efficiency mainly due to the increased heat loss by moisture, hydrogen and flue gas. Based on the performance analysis, the economic performance of the coals was evaluated. The apparent price of low-rank coals tended to be significantly lower than design coal; for example, the unit price of coal with a HHV of 4,000 kcal/kg was 57% of the reference coal having 6,080 kcal/kg. Considering the negative effects leading to a decrease in the thermal performance, heating value compensation, and increased parasite load, the corrected unit cost for the coal with 4,000 kcal/kg was 90.7% of the reference coal. Overall, the cost saving by imported coals was not high as expected.

• The Plant Pathology Journal
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• v.35 no.4
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• pp.301-312
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• 2019

Sorghum is the fifth most important cereal worldwide, spreading from Africa throughout the world. It is particularly important in the semi-arid tropics due to its drought tolerance, and when cultivated in Southeast Asia commonly occurs as a second crop during the dry season. We recovered Fusarium from sorghum in Thailand and found F. proliferatum, F. thapsinum and F. verticillioides most frequently, and intermittent isolates of F. sacchari and F. beomiforme. The relatively high frequencies of F. proliferatum and F. verticillioides, suggest mycotoxin contamination, particularly fumonisins and moniliformin, should be evaluated. Genetic variation within the three commonly recovered species was characterized with vegetative compatibility, mating type, Amplified Fragment Length Polymorphisms (AFLPs), and female fertility. Effective population number ($N_e$) was highest for F. verticillioides and lowest for F. thapsinum with values based on mating type allele frequencies higher than those based on female fertility. Based on AFLP genetic variation, the F. thapsinum populations were the most closely related, the F. verticillioides populations were the most distantly related, and the F. proliferatum populations were in an intermediate position. The genetic variation observed could result if F. thapsinum is introduced primarily with seed, while F. proliferatum and F. verticillioides could arrive with seed or be carried over from previous crops, e.g., rice or maize, which sorghum is following. Confirmation of species transmission patterns is needed to understand the agricultural systems in which sorghum is grown in Southeast Asia, which are quite different from the systems found in Africa, Australia, India and the Americas.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.115-120
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• 2023

Plant leaf diseases and destructive insects are major challenges that affect the agriculture production of the country. Accurate and fast prediction of leaf diseases in crops could help to build-up a suitable treatment technique while considerably reducing the economic and crop losses. In this paper, Convolutional Neural Network based model is proposed to detect leaf diseases of a plant in an efficient manner. Convolutional Neural Network (CNN) is the key technique in Deep learning mainly used for object identification. This model includes an image classifier which is built using machine learning concepts. Tensor Flow runs in the backend and Python programming is used in this model. Previous methods are based on various image processing techniques which are implemented in MATLAB. These methods lack the flexibility of providing good level of accuracy. The proposed system can effectively identify different types of diseases with its ability to deal with complex scenarios from a plant's area. Predictor model is used to precise the disease and showcase the accurate problem which helps in enhancing the noble employment of the farmers. Experimental results indicate that an accuracy of around 93% can be achieved using this model on a prepared Data Set.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.107-112
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• 2024

Plant leaf diseases and destructive insects are major challenges that affect the agriculture production of the country. Accurate and fast prediction of leaf diseases in crops could help to build-up a suitable treatment technique while considerably reducing the economic and crop losses. In this paper, Convolutional Neural Network based model is proposed to detect leaf diseases of a plant in an efficient manner. Convolutional Neural Network (CNN) is the key technique in Deep learning mainly used for object identification. This model includes an image classifier which is built using machine learning concepts. Tensor Flow runs in the backend and Python programming is used in this model. Previous methods are based on various image processing techniques which are implemented in MATLAB. These methods lack the flexibility of providing good level of accuracy. The proposed system can effectively identify different types of diseases with its ability to deal with complex scenarios from a plant's area. Predictor model is used to precise the disease and showcase the accurate problem which helps in enhancing the noble employment of the farmers. Experimental results indicate that an accuracy of around 93% can be achieved using this model on a prepared Data Set.

• Smart Structures and Systems
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• v.31 no.3
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• pp.259-273
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• 2023

Real-time hybrid simulation (RTHS) is an effective experimental technique for structural dynamic assessment. However, time delay causes displacement de-synchronization at the interface between the numerical and physical substructures, negatively affecting the accuracy and stability of RTHS. To this end, the authors have proposed a model-based adaptive control strategy with a Kalman filter (MAC-KF). In the proposed method, the time delay is mainly mitigated by a parameterized feedforward controller, which is designed using the discrete inverse model of the control plant and adjusted using the KF based on the displacement command and measurement. A feedback controller is employed to improve the robustness of the controller. The objective of this study is to further validate the power of dealing with a nonlinear control plant and to investigate the potential challenges of the proposed method through actual experiments. In particular, the effect of the order of the feedforward controller on tracking performance was numerically investigated using a nonlinear control plant; a series of actual RTHS of a frame structure equipped with a magnetorheological damper was performed using the proposed method. The findings reveal significant improvement in tracking accuracy, demonstrating that the proposed method effectively suppresses the time delay in RTHS. In addition, the parameters of the control plant are timely updated, indicating that it is feasible to estimate the control plant parameter by KF. The order of the feedforward controller has a limited effect on the control performance of the MAC-KF method, and the feedback controller is beneficial to promote the accuracy of RTHS.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.53-72
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• 2023

This study aimed to develop educational material on the proper use of plant-based milk alternatives in the form of a card news, based on a focus group interview(FGI) with adult consumers. The FGI participants were individuals who had directly purchased cow's milk, soy milk, or other plant-based milk alternatives within the past three months and consumed them at least once a month. The study consisted of 17 adults between the ages of 19 and 63 years who met these criteria(9 males and 8 females). It was identified what participants were curious about, interested in, and needed information regarding the proper use of plant-based milk alternatives through FGI. A 10-page card news was developed that was highly usable, taking into account the FGI results and the latest literature. In conclusion, this study developed a card news aimed at promoting the proper use of plant-based milk alternatives, which can be easily disseminated online in line with the trends in food consumption and digitization. The results of this study suggest that the continuous development and distribution of educational materials that reflect food consumption trends and maximize their usability should be provided for dietary life education, such as school subjects or out-of-school programs.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.1
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• pp.7-23
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• 2016

Plant engineering industry is considered as a key industry which will drive the future of Korea. However, Korean plant engineering companies have recently made huge losses in overseas businesses and the lack of engineering capability is pointed out as a main cause of this situation. Unlike Korean plant engineering companies, world leading engineering companies such as Flour and Bechtel have their own systems Engineering Standards/Guides ensuring successful fulfillments of the concept and basic design processes. An engineering standard for an organization is an essential means to shorten the time for engineering design, to maintain the engineering quality and to secure the engineering efficiency in the development of the complex system. Korean plant engineering companies'lack of engineering capability comes from the absence of the engineering standard. In the paper, we have developed a steel-making plant engineering standard based on a systems engineering standard. We chose both ISO/IEC/IEEE 15288 and NASA SE Handbook as main reference standards. First, we have introduced a life-cycle definition and a physical hierarchy of a general steel-making plant. Then we have introduced detailed engineering processes of each life-cycle stage. The full scope of the study was from the feasibility study to the basic design but in the paper, we have only introduced detailed engineering processes and exit criteria for the feasibility study and the concept design.