• Geomechanics and Engineering
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• v.37 no.1
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• pp.21-29
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• 2024

The effective management of damage in tunnels is crucial for ensuring their safety, longevity, and operational efficiency. In this paper, we propose an educational management model tailored specifically for addressing damage in tunnels, utilizing numerical solution techniques. By leveraging advanced computational methods, we aim to develop a comprehensive understanding of the factors contributing to tunnel damage and to establish proactive measures for mitigation and repair. The proposed model integrates principles of tunnel engineering, structural mechanics, and numerical analysis to facilitate a systematic approach to damage assessment, diagnosis, and management. Through the application of numerical solution techniques, such as finite element analysis, we demonstrate the efficacy of the proposed model in simulating various damage scenarios and predicting their impact on tunnel performance. Additionally, the educational component of the model provides valuable insights and training opportunities for tunnel management personnel, empowering them to make informed decisions and implement effective strategies for ensuring the structural integrity and safety of tunnel infrastructure. Overall, the proposed educational management model represents a significant advancement in tunnel management practices, offering a proactive and knowledge-driven approach to addressing damage and enhancing the resilience of tunnel systems.

• Journal of Environmental Policy
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• v.10 no.1
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• pp.49-70
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• 2011

The numerous efforts have been made in understanding generation and transportation mechanism of nonpoint source pollutants from agricultural areas. Also, the water quality degradation has been exacerbated over the years in many parts of Korea as well as other countries. Nonpoint source pollutants are transported into waterbodies with direct runoff and baseflow. It has been generally thought that groundwater quality is not that severe compared with surface water quality. However its impacts on groundwater in the vicinity of stream quality is not negligible in agricultural areas. The SWAT model has been widely used in hydrology and water quality studies worldwide because of its flexibilities and accuracies. The spatial property of each HRU, which is the basic computational element, is not presented. Thus, the SWAT HRU mapping module was developed in this study and was applied to the study watershed to evaluate recharge rate and $NO_3-N$ loads in groundwater. The $NO_3-N$ loads in groundwater on agricultural fields were higher than on forests because of commercial fertilizers and manure applied in agricultural fields. The $NO_3-N$ loads were different among various crops because of differences in crop nutrient uptake, amount of fertilizer applied, soil properties in the field. As shown in this study, the SWAT HRU mapping module can be efficiently used to evaluate the pollutant contribution via baseflow in agricultural watershed.

• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.331-340
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• 2007

Mobile network environments are the environments where mobile devices are distributed invisible in our daily lives so that we can conventionally use mobile services at my time and place. The fact that we can work with mobile devices regardless of time and place, however, means that we are also in security threat of leaking or forging the information. In particular, without solving privacy concern, the mobile network environments which serve convenience to use, harmonized without daily lives, on the contrary, will cause a serious malfunction of establishing mobile network surveillance infrastructure. On the other hand, as the mobile devices with various sizes and figures, public key cryptography techniques requiring heavy computation are difficult to be applied to the computational constrained mobile devices. In this paper, we propose efficient PKI-based user authentication and java-based cryptography module for the privacy-preserving in mobile network environments. Proposed system is support a authentication and digital signature to minimize encrypting and decrypting operation by compounding session key and public key based on Korean standard cryptography algorithm(SEED, KCDSA, HAS160) and certificate in mobile network environment. Also, it has been found that session key distribution and user authentication is safety done on PDA.

• Journal of Technology Innovation
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• v.23 no.2
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• pp.33-54
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• 2015

Supercomputing performance demand forecasting at the national level is an important information to the researchers in fields of the computational science field, the specialized agencies which establish and operate R&D infrastructure, and the government agencies which establish science and technology infrastructure. This study derived the factors affecting the scientific and technological capability through the analysis of supercomputing performance prediction research, and it proposed a hybrid forecasting model of applying the super-computer technology trends. In the cross-sectional analysis, multiple regression analysis was performed using factors with GDP, GERD, the number of researchers, and the number of SCI papers that could affect the supercomputing performance. In addition, the supercomputing performance was predicted by multiplying in the cross-section analysis with technical progress rate of time period which was calculated by time series analysis using performance(Rmax) of Top500 data. Korea's performance scale of supercomputing in 2016 was predicted using the proposed forecasting model based on data of the top500 supercomputer and supercomputing performance demand in Korea was predicted using a cross-sectional analysis and technical progress rate. The results of this study showed that the supercomputing performance is expected to require 15~30PF when it uses the current trend, and is expected to require 20~40PF when it uses the trend of the targeting national-level. These two results showed significant differences between the forecasting value(9.6PF) of regression analysis and the forecasting value(2.5PF) of cross-sectional analysis.

• Ecology and Resilient Infrastructure
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• v.6 no.2
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• pp.109-119
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• 2019

Eutrophication has occurred due to the inflow of various water pollutants in many Korean reservoirs with low depth, and algal blooms of surface layer and low oxygenation of deep layer have repeated every year. There are several existing technologies to alleviate the stratification of reservoirs, but it is difficult to apply them in field sites due to the necessity of electric power and low economic efficiency. In this study, a non-powered water circulation system using natural energy of wind and water flow has been developed, and two test-beds constructed in the reservoirs with different conditions and examined its field applicability. Through computational fluid dynamics (CFD) simulation, it has been shown that the water circulation system could induce the downward flow to mitigate the stratification between surface and deep layers, and its influence radius could reach about 30 m. As a result of long-term monitoring of the test-beds, various water quality improvement effects have been observed such as moderation of DO fluctuation by water circulation, reduction of DO supersaturation and prevention of excessive pH rising. In order to improve the applicability of the water circulation system, it is considered necessary to review countermeasures against flood and depth conditions of each reservoir.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.37-44
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• 2012

Numerous scientists who are engaged in compute-intensive researches require more computing facilities than before, while the computing resource and techniques are increasingly becoming more advanced. For this reason, many works for e-Science environment have been actively invested and established around the world, but still the scientists look for an intuitive experimental environment, which is guaranteed the improved environmental facilities without additional configurations or installations. In this paper, we present an integrated scientific workflow execution environment for Scientific applications supporting workflow design with high performance computing infrastructure and accessibility for web browser. This portal supports automated consecutive execution of computation jobs in order of the form defined by workflow design tool and execution service concerning characteristics of each job to batch over distributed grid resources. Workflow editor of the portal presents a high-level frontend and easy-to-use interface with monitoring service, which shows the status of workflow execution in real time so that user can check the intermediate data during experiments. Therefore, the scientists can take advantages of the environment to improve the productivity of study based on HTC.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.425-433
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• 2016

The construction of a light rail transit (LRT) system is a large and complex infrastructure project involving hundreds of billions of won in construction costs for a single route, and it is very important to carry out such a project from a life-cycle perspective because of its long-term operation. Systems engineering is a means and methodology to successfully implement customers' needs, and it is useful in large projects such as light rail transit. An application model called Systems Engineering for Light Rail Transit (SELRT) was developed to support systems engineering activities in light rail transit projects. In order to utilize SELRT, it is necessary to ensure that system requirements are met. As such, in this paper, we present a verification procedure and architecture based on a systems engineering-based methodology, thereby identifying the system requirements and deriving the verification requirements to confirm the SELRT model for the proposed method. The results show that the traceability of the system requirements and verification requirements, the verification method for each requirement, and the demonstration results for computerized tools are mutually connected, and that the initial requirements are clearly implemented in the SELRT. The proposed method is valid for verifying the SELRT, which can also be utilized in a LRT project.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.4
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• pp.307-312
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• 2017

In this study, we proposed a method to generate a maintenance documents for railway track through Construction Operations Building information exchange(COBie) which is a subset of Industry Foundation Classes(IFC), a data model for Building Information Modeling(BIM). In order to define the items necessary for railway track maintenance document generation, we analyzed the guideline of maintenance and management to track by the Ministry of Land, Infrastructure and Transport(MLTM), and defined the way to refer to the information items in the COBie spreadsheet. The additional properties not supported in IFC, were created for generation of an Information model that reflecting maintenance information items of railway track by applying user-defined property set within the IFC framework. An IFC-based Information model reflecting the user-defined property was implemented through BIM software, and rail track maintenance information items were transferred to COBie spreadsheet according to the defined approach. It is tested that the information can be transferred from the IFC-based as-built model to the COBie spreadsheet, which can be used to generate the necessary documents for railway facility maintenance work.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.507-514
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• 2017

As BIM has been widely used in the field of architecture, efforts to apply BIM to civil engineering structures are increasing rapidly. Since commercial BIM softwares are focused on building structure, it is difficult to apply to alignment-based civil infrastructures. In this study, we proposed a method to generate an information model that reflects cant by sharing information between alignment-centered modeling tools and BIM authoring tools to manage information of railway track. The railway track modeling process consists of classifying structures into continuous and non-continuous structures, creating continuous structures by alignment-centered modeling tools, and using the shared alignment information to generate information model of the non-continuous structures. Non-continuous structures were generated by an algorithm that calculates the position and rotation information of each structure based on discretized railway alignment and cant information transmitted to the BIM authoring tools. The availabilities of proposed method were studied by applying to the osong test-line. Using the test model, it was shown that the objects were identified, the properties were extracted, and the quantities of each structure were calculated.