• Journal of Korean Association for Spatial Structures
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• v.7 no.3 s.25
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• pp.133-140
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• 2007

Spatial structures is a appropriate shape that resists external force with only inplane force by reducing the influence of bending moment, and it maximizes the effect of structure system. An economic analysis is one of the most important factors to determine the project feasibility. Large spatial structures project is more need to comprehensive technology than a general construction project. In order to result in success of these project, it is desired that analyze an essential elements(for example, large budget, professional engineer, construction method, etc.) in the whole life cycle of buildings by schematic preparation from the early feasible study steps. We collect the data and analyze construction cost through this study which examines general remarks of existing spatial structures and researches its examples. This study is aimed to apply basic data to establish database the spatial structures.

• The magazine of the Korean Society for Advanced Composite Structures
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• v.1 no.2
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• pp.13-18
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• 2010

• Journal of Information Science Theory and Practice
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• v.1 no.1
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• pp.69-82
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• 2013

Although MAchine Readable Cataloging (MARC) and Functional Requirements for Bibliographic Records (FRBR) are currently the most broadly used bibliographic structures for generating bibliographic data in the library community, each has its own weaknesses in describing information resources in diverse media. If the MARC format could be implemented in a structure that reflects the multi-layered characteristics of FRBR, its use could address current problems and limitations in resource description. The purpose of this research is to propose an alternative approach that can integrate the heterogeneous bibliographic structures of MARC and FRBR through the applications of facet and facet analysis. The proposed faceted data model is expected to function as a conceptual structure that can mediate between MARC data elements and FRBR attributes in order to utilize these structures in a more reliable and comprehensive way.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.04a
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• pp.89-96
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• 1997

Most civil engineering structures, such as highway bridges, towers, power plants and offshore structures suffer structural damages over their service lives caused by adverse loading such as heavy transportation loads, machine vibrations, earthquakes, wind and wave forces. Especially, if excessive load would be acted on the structure, general or partial stiffness should be degraded suddenly and service lives should be shortened eventually For realistic damage assessment of these civil structures, System Identification method using only structure dynamic response data with unknown input excitation is required and thus becoming more challenging problem. In this paper, an improved Iterative Least Squares method is proposed, which seems to be very efficient and robust method, because only the dynamic response data such as acceleration, velocity and displacement is used without input data, and no information on the modal properties is required. The efficiency and robustness of the proposed method is proved by numerical problems and real single span beam model test.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.49-62
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• 2016

In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.73-74
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• 2022

Concrete structures occupy the largest proportion of modern infrastructure, and concrete structures often have cracking problems. Existing concrete crack diagnosis methods have limitations in crack evaluation because they rely on expert visual inspection. Therefore, in this study, we design a deep learning model that detects, visualizes, and outputs cracks on the surface of RC structures based on image data by using a CNN (Convolution Neural Networks) model that can process two- and three-dimensional data such as video and image data. do. An experimental study was conducted on an algorithm to automatically detect concrete cracks and visualize them using a CNN model. For the three deep learning models used for algorithm learning in this study, the concrete crack prediction accuracy satisfies 90%, and in particular, the 'InceptionV3'-based CNN model showed the highest accuracy. In the case of the crack detection visualization model, it showed high crack detection prediction accuracy of more than 95% on average for data with crack width of 0.2 mm or more.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.559-563
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• 2024

Currently, in Korea, large-scale, deep excavations are being carried out adjacent to structures due to overcrowding in urban areas. for adjacent excavations in urban areas, it is very important to ensure the safety of earth retaining structures and underground structures. accordingly, an automated measurement system is being introduced to manage the safety of subway tunnel structures. however, the utilization of automated measurement system results is very low. existing evaluation techniques rely only on the maximum value of measured data, which can overestimate abnormal behavior. accordingly, in this study, a vast amount of automated measurement data was analyzed using the Gaussian probability density function, a technique that can quantitatively evaluate. highly reliable results were derived by applying probabilistic statistical analysis methods to a vast amount of data. therefore, in this study, the safety evaluation of subway tunnel structures due to adjacent excavation work was performed using a technique that can process a large amount of data.

• Smart Structures and Systems
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• v.4 no.5
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• pp.517-530
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• 2008

This paper deals with civil infrastructures in general, sensor and smart structure technology, and smart steel structures in particular. Smart structures technology, an integrated engineering field comprising sensor technology, structural control, smart materials and structural health monitoring, could dramatically transform and revolutionize the design, construction and maintenance of civil engineering structures. The central core of this technology is sensor and sensor networks that provide the essential data input in real time for condition assessment and decision making. Sensors and robust monitoring algorithms that can reliably detect the occurrence, location, and severity of damages such as crack and corrosion in steel structures will lead to increased levels of safety for civil infrastructure, and may significantly cut maintenance or repair cost through early detection. The emphasis of this paper is on sensor technology with a potential use in steel structures.

• Journal of the Korea Computer Graphics Society
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• v.5 no.2
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• pp.43-52
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• 1999

In this paper, we present an animation toolkit based on motion mapping technique in a graphics user interface that can represent data structures necessary for generating character motions. The motion mapping means that an animation sequence generated once can be mapped to another object directly according a data structure in the graphics user interface. Users can generate animation sequences interactively using a mouse. These are obtained automatically by modifying motion data structures interactively. Compared with other conventional tools, the toolkit has different features that two hierarchical structures necessary for representing modeling and animation data are managed independently each other, and that animations generated can be applied to any other characters by connecting the two hierarchical structures in the user interface.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.331-351
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• 2012

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.