• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.191-199
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• 2007

In order to construct a data warehouse of process plant equipment, a classification structure should be defined first, identifying not only the equipment categories but also attributes of an each equipment to represent the specifications of equipment. ISO 15926 Process Plants is an international standard dealing with the life-cycle data of process plant facilities. From the viewpoints of defining classification structure, Part 2 data model and Reference Data Library (RDL) of ISO 15926 are seen to respectively provide standard syntactic structure and semantic vocabulary, facilitating the exchange and sharing of plant equipment's life-cycle data. Therefore, the equipment data warehouse with an ISO 15926-based classification structure has the advantage of easy integration among different engineering systems. This paper introduces ISO 15926 and then discusses how to define a classification structure with ISO 15926 Part 2 data model and RDL. Finally, we describe the development result of an ISO 15926-based classification structure for a variety of equipment consisting in the reactor coolant system (RCS) of APR 1400 nuclear plant.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.6 s.113
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• pp.78-89
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• 2006

This study was conducted to analyze the planting structure and ecological characteristics of greon spaces on the grounds of e Dangjin steam power plant. To achieve these goals, we surveyed existing vegetation, plant community structure, Plant volume and growth rate. Based on e vegetation analysis, existing vegetation was classified into six types: herbaceous species $(70.54\%)$, evergreen coniferous trees $(21.17\%)$, deciduous broad-leaved trees $(5.10\%)$, deciduous coniferous trees $(1.47\%)$, shrubs $(0.12\%)$, and other types $(1.59\%)$. The coal storage, office, and playground areas were community is the natural forest area where a Pinus thunbergii / Pinus densiflora community is distributed in terms of vegetation structure, species diversity, plant volume, and growth rate. The artificial green spaces(near the coal storage, office, playground areas) had a single-layer structure. Species diversity indices of the artificial green areas were $0.1655\~0.4807$ compared to 0.8628 in the natural forest, which presented a good growth environment. Also, the plant volume in the artificial green space was lower than that of the natural green space. Therefore, it would be desirable to develope a multi-layer structure similar to that of the vegetation in the natural green space in order to improve the amount of plant volume. The plant-damage ratio of Pinus thunbergii was $52.48\%$ in the coal storage area, and $8.48\~ 11.52\%$, in the other survey areas. Also, the vitality of Pinus thunbergii was $15.45k{\Omega}$ in the coal storage areas, which indicates bad growing conditions. This suggests that soil characteristics and dust have a bad impact on growth. The investigation into deciduous tres' growth status showed that appropriate plants would be Albizzia julibrissin, Acer palmatum var. sanguineum, Acer palmatum, Malus spp., Prunus sargentii.

• Journal of Korean Association for Spatial Structures
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• v.24 no.3
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• pp.43-51
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• 2024

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson's ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.208-212
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• 1991

LQG/LTR method cannot applied to nonminimum phase plant. In this paper, we present a new approximation method which guaratee the approximation error equal to zero and exact loop transfer recovery. Zero structure of plant and approximated plant are considered in approximation procedure. It is shown that the properties of plant and approximated plant at pole and zero frequency response are exactly same. It is shown by example that the suggested method can avoide the NMP plant constraint arised in designing LQG/LTR.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.10a
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• pp.148-155
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• 1992

A method to verify seismic qualification of the plant protection system cabinet for a nuclear power plant is presented. A finite element model of the cabinet is developed and correlated to the dynamic properties observed during in-situ vibration test of the actual structure. The results of the modal analysis provide insight into the fundamental dynamic properties of the structure. Techniques for verifying structural integrity and operability are exemplified by summarizing response spectrum and time history analyses of the structure.

• The Plant Pathology Journal
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• v.33 no.6
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• pp.529-542
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• 2017

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

• Journal of the Korean Society of Safety
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• v.7 no.4
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• pp.33-43
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• 1992

A methodology to develop an expert system for chemical plant fault diagnosis based on functional-structure of chemical plant is proposed. A methodology to generalize and utilize the heuristic know-edge of plant operators is also developed. A plant can be seen as a Hierarchical set of subsystems. Each subsystem is called a SCOPE. The state of the plant and the behavior of each subsystem is managed by the SCOPES. An expert system based on this functional structure and knowledge base has been developed and ar plied to the subprocess of etylene plant to evaluate the effectiveness of the methodology.

• Journal of Microbiology and Biotechnology
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• v.20 no.9
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• pp.1339-1347
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• 2010

In this study, the identity and distribution of plants and the structure of their associated rhizobacterial communities were examined in an oil-contaminated site. The number of plant species that formed a community or were scattered was 24. The species living in soil highly contaminated with total petroleum hydrocarbon (TPH) (9,000-4,5000 mg/g-soil) were Cynodon dactylon, Persicaria lapathifolia, and Calystegia soldanella (a halophytic species). Among the 24 plant species, the following have been known to be effective for oil removal: C. dactylon, Digitaria sanguinalis, and Cyperus orthostachyus. Denaturing gradient gel electrophoresis (DGGE) profile analysis showed that the following pairs of plant species had highly similar (above 70%) rhizobacterial community structures: Artemisia princeps and Hemistepta lyrata; C. dactylon and P. lapathifolia; Carex kobomugi and Cardamine flexuosa; and Equisetum arvense and D. sanguinalis. The major groups of rhizobacteria were Beta-proteobacteria, Gamma-proteobacteria, Chloroflexi, Actinobacteria, and unknown. Based on DGGE analysis, P. lapathifolia, found for the first time in this study growing in the presence of high TPH, may be a good species for phytoremediation of oil-contaminated soils and in particular, C. soldanella may be useful for soils with high TPH and salt concentrations. Overall, this study suggests that the plant roots, regardless of plant species, may have a similar influence on the bacterial community structure in oil-contaminated soil.

• Mycobiology
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• v.35 no.4
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• pp.186-190
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• 2007

This study was conducted to investigate the effects of foliar endophytic fungi and arbuscular mycorrhizal fungi (AMF) on plant community structure in experimental microcosms containing an assemblage of five species of plants (Oenothera odorata, Plantago asiatica, Trifolium repens, Isodon japonicas and Aster yomena). Leaves of Sasa borealis, Potentilia fragarioides, and Viola mandshurica were collected in Chungbuk, Korea. Endophytic fungi were isolated from the surface sterilized leaves and identified to species level using molecular and morphological techniques. Four isolates of the endophytic fungi were inoculated to the leaves of host plants in the microcosms. Also, three species of AMF spores were extracted from pure cultures and the mixture of the three species inoculated to the roots of the plants. After four months of growth in a green house, effects of both symbiotic fungi on plant species diversity, community composition and productivity were examined. The plant species diversity showed significant differences with inoculation of the symbiotic fungi. Results indicate that AMF significantly affect plant productivity and plant community structure.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.610-613
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• 2009

Uldolmok tidal current power plant was constructed on May 2009 at Jindo Gun in Korea. However it had much trouble in installing structure due to the extremely fast tidal current velocity(max. 5.5m/sec) and the jacket type plant structure. Therefore in this paper, The characteristics of tidal current and sea bed topography at Uldolmok tidal current plant site are investigated, and the detailed foundation work process of the plant is described.