• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.737-746
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• 2008

Recently, NDTs (Non-Destructive Techniques) using electromagnetic(EM) properties are applied to the performance evaluation for RC (Reinforced Concrete) structures. Since nonmetallic materials which are cement-based system have their unique dielectric constant and conductivity, they can be characterized and changed with different mixture conditions like W/C (water to cement) ratios and unit cement weight. In a room condition, cement mortar is generally dry so that porosity plays a major role in EM properties, which is determined at early-aged stage and also be affected by curing condition. In this paper, EM properties (dielectric constant and conductivity) in cement mortar specimens with 4 different W/C ratios are measured in the wide region of 0.2 GHz~20 GHz. Each specimen has different submerged curing period from 0 to 28 days and then EM measurement is performed after 4 weeks. Furthermore, porosity at the age of 28 days is measured through MIP (Mercury Intrusion Porosimeter) and saturation is also measured through amount of water loss in room condition. In order to evaluate the porosity from the initial curing stage, numerical analysis based on the modeling for the behavior in early-aged concrete is performed and the calculated results of porosity and measured EM properties are analyzed. For the convenient comparison with influencing parameters like W/C ratios and curing period, EM properties from 5 GHz to 15 GHz are averaged as one value. For 4 weeks, the averaged dielectric constant and conductivity in cement mortar are linearly decrease with higher W/C ratios and they increase in proportion to the square root of curing period regardless of W/C ratios.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.259-267
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• 2008

The ultimate strengths of reinforced concrete deep beams are governed by the capacity of the shear resistance mechanism composed of concrete and shear reinforcing bars, and the structural behaviors of the beams are mainly controlled by the mechanical relationships according to the shear span-to-effective depth ratio, flexural reinforcement ratio, load and support conditions, and material properties. In this study, a simple indeterminate strut-tie model reflecting all characteristics of the ultimate strengths and complicated structural behaviors is presented for the design of simply supported reinforced concrete deep beams. In addition, a load distribution ratio, defined as a magnitude of load transferred by a vertical truss mechanism, is proposed to help structural designers perform the design of simply supported reinforced concrete deep beams by using the strut-tie model approaches of current design codes. In the determination of a load distribution ratio, a concept of balanced shear reinforcement ratio requiring a simultaneous failure of inclined concrete strut and vertical steel tie is introduced to ensure the ductile shear failure of reinforced concrete deep beams, and the prime design variables including the shear span-to-effective depth ratio, flexural reinforcement ratio, and compressive strength of concrete influencing the ultimate strength and behavior are reflected upon based on various and numerous numerical analysis results. In the companion paper, the validity of presented model and load distribution ratio was examined by employing them to the evaluation of the ultimate strengths of various simply supported reinforced concrete deep beams tested to failure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.699-707
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• 2008

For most structural evaluation of bridge integrity, it is very important to measure the geometric profile, which is a major factor representing the global behavior of civil structures, especially bridges. In the past, because of the lack of appropriate methods to measure the deflection profile of bridges on site, the measurement of deflection has been restricted to just a few discrete points along the bridge, and the measuring points have been limited to the locations installed with displacement transducers. Thus, some methods for predicting the static deflection by using fiber optic strain sensors has been applied to simply supported bridges. In this study, a method of estimating the static deflection profile by using strains measured from suspension bridges was proposed. Based on the classical deflection theory of suspension bridges, an equation of deflection profile was derived and applied to obtain the actual deflection profile on Namhae suspension bridge. Field load tests were carried out to measure strains from FBG strain sensors attached inside the stiffening girder of the bridge. The predicted deflection profiles were compared with both precise surveying data and numerical analysis results. Thus, it is found that the equation of predicting the deflection profiles proposed in this study could be applicable to suspension bridges and the FBG strain sensors could be reliable on acquiring the strain data from bridges on site.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1C
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• pp.43-52
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• 2006

Despite several constitutive models have been proposed and applied, it is still difficult to choose a suitable model and to estimate adequate analysis parameters. Furthermore, a cyclic shear behavior under the volume change caused by the seepage is more complex. None of the constitutive model is available at present in the expression of the cyclic behavior of soil under an additional volume change condition by seepage. Therefore, a new geotechnical hybrid simulation system which can control the pore water immigration was developed. The system enables a quantitative evaluation of the residual deformation such as lateral spreading and settlement caused by the liquefaction. The seismic responses in a one-dimensional slightly inclined multilayered soil system are taken into consideration, and the soils are governed by both equation of motion and the continuity equation. Furthermore, the estimation and the selection of the soil parameter for the representation of the strong nonlinearity of the material are not required, because soil behaviors under the earthquake motions are directly introduced instead of a numerical soil constitutive model. This paper presents the concept and specifications of the system. By applying the system to an example problem, the permeability effect on the seismic response during cyclic shear is studied. The importance of the volume change characteristics of sandy soil during and after cyclic shear is shown in conclusion.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.770-778
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• 2023

Sea surface wind is an important variable for elucidating the atmospheric-ocean interactions and predicting the dangerous weather conditions caused by oceans. Accurate sea surface wind data are required for making correct predictions; however, there are limited observational datasets for oceans. Therefore, this study aimed to obtain long-period high-resolution sea surface wind data. First, the ERA5 reanalysis wind field, which can be used for a long period at a high resolution, was regridded and synthesized using the asymmetric typhoon wind field calculated via the Generalized Asymmetric Holland Model of the numerical model named ADvanced CIRCulation model. The accuracy of the asymmetric typhoon synthesized wind field was evaluated using data obtained from Korea Meteorological Administration and Japan Meteorological Administration. As a result of the evaluation, it was found that the asymmetric typhoon synthetic wind field reproduce observations relatively well, compared with ERA5 reanalysis wind field and symmetric typhoon synthetic wind field calculated by the Holland model. The sea surface wind data produced in this study are expected to be useful for obtaining storm surge data and conducting frequency analysis of storm surges and sea surface winds in the future.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.19 no.3
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• pp.1-13
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• 2023

Hydronic heated road pavement (HHP) systems have been well established and documented to provide road safety in winter season over the past two decades. However, most of the systems run on asphalt, only a few are tested with concrete, and there rarely is a comparison between those two common road materials in their performance. The aim of this study is to investigate the thermal performance of the concrete HHP systems, including surface temperature variations of experimental pavements in winter season. For preliminary study a small-scale experimental system was installed to evaluate the heat transfer characteristics of the concrete HHP in the test field. The system consists of 3 concrete slabs made of 1 m in width, 1 m in length, and 0.25 m in height. In these slabs, circulating water piping was embedded with different pipe depths of 0.08 m (Case A), 0.12 m (Case B), and 0.20 m (Case C) and same horizontal space of 0.16 m. Heating performance in winter season was tested with different inlet temperatures of 25℃, 30℃, 35℃ and 40℃ during the entire measurement period. Overall, the surface temperature of the concrete HHPs remained above 3℃ in all experimental conditions applied in this study. The results of the surface temperature measurement with respect to the pipe depth showed that Case B was the highest among the three cases. However, the closer the circulating water pipe was to the pavement surface, the greater the heat exchange rate. This results is considered that the heat is continuously accumulated inside the pavements and then the temperature inside the pavements increases, while the amount of heat dissipation decreases as the temperature difference between the inlet and outlet of circulating water decreases. In this preliminary test the applicability of the concrete HHP on road deicing was confirmed. Finally, the results can be used as a basis for studying the effects of various variables on road pavements through numerical analysis and for conducting large-scale empirical experiments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.689-693
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• 2023

Domestic bridges with a service life of more than 30 years are expected to account for approximately 54% of all bridges within the next 10 years. As bridges rapidly deteriorate, it is necessary to establish an appropriate maintenance plan. Recent domestic and international research have focused on the integration of BIM to digitize bridge maintenance information and then enhance accessibility and usability of the information. Accordingly, this study developed a BIM-FEM interoperability algorithm for bridge decks to convert maintenance information into data and efficiently manage the history of maintenance. After creating an initial crack BIM based on an exterior damage map, bridge specification and damage information were linked to a numerical analysis that performs damage analysis considering damage scenarios and design loads. The spread of cracks obtained from the analysis results were updated into the BIM. Based on the damage spread information on the BIM, an automated technology was also developed to assess both the current and future condition ratings of the bridge deck. This approach can enable an efficient maintenance of the deck using the history data from bridge inspection and diagnosis as well as future information on cracks and defects. The expected early detection and prevention would ultimately improve the lifespan and safety of bridges.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.