• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.323-328
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• 2005

Bridge structures are properly designed in accordance with the design specifications with required safety margin. However, due to the heavy vehicle traffic and environmental attacks, bridge often requires repairs and the deteriorated one should be replaced or rehabilitated. In this paper, a prior ranking algorithm is proposed to assist a decision making process in bridge management at network level. Based on the literature survey for the existing studuies, two important factors which affect the decision making procedure for bridge management at network level are identified. These factors are implemented into the algorithm as a load carrying capacity function and traffic function, respectively.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.469-472
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• 2008

In general, structures in service gradually lose original performance according to time due to initial defects in design and construction, or exposure to unfavorable external conditions such as repeated loading or deteriorating environment, and in extreme cases, may collapse in large disaster. Therefore, in order to maintain the serviceability of structures at optimal level, advanced structure measuring system which can inform optimal time point and method of maintenance is required in addition to accurate prediction of residual life the structure by periodic inspection. To guarantee the safety level of bridge structure and to prevent from disaster, the integration of safety network for bridge structures are needed. Therefore in this study, to enhance the effectiveness of safety network for bridge, the connection methodologies between safety network and pre-installed bridge monitoring system are investigated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1030-1050
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• 2021

The edges with "bridge characteristic" play the role of connecting the communication between regions in power optical cable network. To solve the problem of mining edges with "bridge characteristic" in provincial power optical cable network, the complex power optical cable network model is constructed. Firstly, to measure the generated potential energy of all nodes in n-level neighborhood local structure for one edge, the n-level neighborhood local structure topological potential is designed. And the minimum connected chain attenuation is designed to measure the attenuation degree caused by substituted edges. On the basis of that, the minimum connected chain attenuation topological potential based measurement is designed. By using the designed measurement, a bridge-edges mining algorithm is proposed to mine edges with "bridge characteristic". The experiments are conducted on the physical topology of the power optical cable network in Jilin Province. Compared with that of other three typical methods, the network efficiency and connectivity of the proposed method are decreased by 3.58% and 28.79% on average respectively. And the proposed method can not only mine optical cable connection with typical "bridge characteristic" but also can mine optical cables without obvious characteristics of city or voltage, but it have "bridge characteristic" in the topology structure.

• Journal of Power Electronics
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• v.13 no.2
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• pp.296-303
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• 2013

This paper proposes a high efficiency three-phase cascaded phase shifted H-bridge multi-level inverter without DC/DC converters for grid-tied multi string photovoltaic (PV) applications. The cascaded H-bridge topology is suitable for PV applications since each PV module can act as a separate DC source for each cascaded H-bridge module. The proposed phase shifted H-bridge multi-level topology offers advantages such as operation at a lower switching frequency and a lower current ripple when compared to conventional two level topologies. It is also shown that low ripple sinusoidal current waveforms are generated with a unity power factor. The control algorithm permits the independent control of each DC link voltage with a maximum power point for each string of PV modules. The use of the controller area network (CAN) communication protocol for H-bridge multi-level inverters, along with localized PWM generation and PV voltage regulation are implemented. It is also shown that the expansion and modularization capabilities of the H-bridge modules are improved since the individual inverter modules operate more independently. The proposed topology is implemented for a three phase 240kW multi-level PV power conditioning system (PCS) which has 40kW H-bridge modules. The experimental results show that the proposed topology has good performance.

• Smart Structures and Systems
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• v.11 no.5
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• pp.453-476
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• 2013

DuraMote is a remote sensing system developed for the "NIST TIP project: next generation SCADA for prevention and mitigation of water system infrastructure disaster". It is designed for supervisory control and data acquisition (SCADA) of ruptures in water pipes. Micro-electro mechanical (MEMS) accelerometers, which record the vibration of the pipe wall, are used detect the ruptures. However, the performance of Duramote cannot be verified directly on a water distribution system because it lacks an acceptable recordable level of ambient vibration. Instead, a long-span cable-stayed bridge is an ideal test-bed to validate the accuracy, the reliability, and the robustness of DuraMote because the bridge has an acceptable level of ambient vibration. The acceleration data recorded on the bridge were used to identify the modal properties of the structure and to verify the performance of DuraMote. During the test period, the bridge was subjected to heavy rain, wind, and a typhoon but the system demonstrates its robustness and durability.

• Smart Structures and Systems
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• v.31 no.5
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• pp.501-516
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• 2023

Dynamic irregularity and acceleration of bridges subjected to high-speed trains provide crucial information for comprehensive evaluation of the health state of under-track structures. This paper proposes a novel approach for real-time estimation of vertical track dynamic irregularity and bridge acceleration using deep generative adversarial network (GAN) and vibration data from in-service train. The vehicle-body and bogie acceleration responses are correlated with the two target variables by modeling train-bridge interaction (TBI) through least squares generative adversarial network (LSGAN). To realize supervised learning required in the present task, the conventional LSGAN is modified by implementing new loss function and linear activation function. The proposed approach can offer pointwise and accurate estimates of track dynamic irregularity and bridge acceleration, allowing frequent inspection of high-speed railway (HSR) bridges in an economical way. Thanks to its applicability in scenarios of high noise level and critical resonance condition, the proposed approach has a promising prospect in engineering applications.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.1
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• pp.33-40
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• 2016

In this study, using the Cost Prediction Model and Performance Prediction Model have developed a way to estimate future management costs and performance for bridge and tunnel by Network Level. Studies to date have primarily focused on the single facility, it is difficult to apply to the analysis of the Network Level. This study, items used as an index of 'Special Act for the Safety Control of Public Structures' was added to Usability and Functionality to Status. Action period and annual budget for each facility can be estimated through the Basic and Advanced analysis. In addition, we verified the technical feasibility through case analysis.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.118-124
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• 2023

Objectives : Depressive disorder and anxiety disorder frequently co-occur, even at sub-threshold level. This study aims to identify network structure of co-morbid depression and anxiety at symptom level in nonclinical population and to reveal the central symptoms and bridge symptoms of the co-morbidity. Methods : This study was based on 2022 Asan Youth Mental Health Screening. Patient health questionnaire (PHQ-9) and Generalized anxiety disorder scale (GAD-7) were used to assess depressive and anxiety symptoms of 810 young adult participants from community sample. Network structure of co-morbid depressive and anxiety symptoms was estimated by Isingfit model. Results : Depressed mood, Restlessness and Nervousness were the most central symptoms in the network. Bridge symptoms between anxiety and depression were Restlessness and Irritability. Conclusions : This study revealed key central symptoms and bridge symptoms of co-morbid depression and anxiety in nonclinical population and provided potential insight for treatment targets to reduce co-morbidity.

• Smart Structures and Systems
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• v.12 no.6
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• pp.679-694
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• 2013

In this paper the application of the Interpolation Damage Detection Method to the numerical model of a suspension bridge instrumented with a network of Micro-Electro-Mechanical System sensors is presented. The method, which, in its present formulation, belongs to Level II damage identification method, can identify the presence and the location of damage from responses recorded on the structure before and after a seismic damaging event. The application of the method does not require knowledge of the modal properties of the structure nor a numerical model of it. Emphasis is placed herein on the influence of recorded signals noise on the reliability of the results given by the Interpolation Damage Detection Method. The response of a suspension bridge to seismic excitation is computed from a numerical model and artificially corrupted with random noise characteristic of two families of Micro-Electro-Mechanical System accelerometers. The reliability of the results is checked for different damage scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3025-3047
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• 2021

This paper presents the latest Ethernet standardization of in-vehicle network and the future trends of automotive Ethernet technology. The proposed system provides design and optimization algorithms for automotive networking technology related to AVB (Audio Video Bridge) technology. We present a design of in-vehicle network system as well as the optimization of AVB for automotive. A proposal of Reduced Latency of Machine to Machine (RLMM) plays an outstanding role in reducing the latency among devices. RLMM's approach to real-world experimental cases indicates a reduction in latency of around 41.2%. The setup optimized for the automotive network environment is expected to significantly reduce the time in the development and design process. The results obtained in the study of image transmission latency are trustworthy because average values were collected over a long period of time. It is necessary to analyze a latency between multimedia devices within limited time which will be of considerable benefit to the industry. Furthermore, the proposed reliable camera and video streaming through optimized AVB device settings would provide a high level of support in the real-time comprehension and analysis of images with AI (Artificial Intelligence) algorithms in autonomous driving.