• 한국지진공학회논문집
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• 제25권5호
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• pp.191-199
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• 2021

In seismic design, hollow section concrete columns offer advantages by reducing the weight and seismic mass compared to concrete section RC bridge columns. However, the flexure-shear behavior and spirals strain of hollow section concrete columns are not well-understood. Octagonal RC bridge columns of a small-scale model were tested under cyclic lateral load with constant axial load. The volumetric ratio of the transverse spiral hoop of all specimens is 0.00206. The test results showed that the structural performance of the hollow specimen, such as the initial crack pattern, initial stiffness, and diagonal crack pattern, was comparable to that of the solid specimen. However, the lateral strength and ultimate displacement of the hollow specimen noticeably decreased after the drift ratio of 3%. The columns showed flexure-shear failure at the final stage. Analytical and experimental investigations are presented in this study to understand a correlation confinement steel ratio with neutral axis and a correlation between the strain of spirals and the shear resistance capacity of steel in hollow and solid section concrete columns. Furthermore, shear strength components (V_c, V_s·, V_p) and concrete stress were investigated.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.164-167
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• 2005

This paper present ZVS Half-Bridge converter Using IM(Integrated Magnetics). In converter system, magnetic components are important devices used for energy storage, energy transfer, galvanic isolation and filtering. The purposes of IM(Integrated Magnetics) are to reduce the number of magnetic components and voltage/current ripple. This topology is use of three magnetics components thus increasing the cost and size of the system. A prototype featuring 300V input, 15V output, 400kHz switching frequency, and 150W output power.

• Smart Structures and Systems
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• 제17권4호
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• Smart Structures and Systems
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• 제31권4호
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Smart Structures and Systems
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• 제33권3호
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• pp.189-199
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• 2024

To properly extract the strain components under varying operational conditions is very important in bridge health monitoring. The abnormal sensor readings can be correctly identified and the expected operational performance of the bridge can be better understood if each strain components can be accurately quantified. In this study, strain components under varying load conditions, i.e., temperature variation and live-load variation are evaluated based on field strain measurements collected from a real concrete box-girder bridge. Temperature-induced strain is mainly regarded as the trend variation along with the ambient temperature, thus a smoothing technique based on the wavelet packet decomposition method is proposed to estimate the temperature-induced strain. However, how to effectively extract the vehicle-induced strain is always troublesome because conventional threshold setting-based methods cease to function: if the threshold is set too large, the minor response will be ignored, and if too small, noise will be introduced. Therefore, an autoencoder framework is proposed to evaluate the vehicle-induced strain. After the elimination of temperature and vehicle-induced strain, the left of which, defined as the model error, is used to assess the operational performance of the bridge. As empirical techniques fail to detect the degraded state of the structure, a clustering technique based on Gaussian Mixture Model is employed to identify the damage occurrence and the validity is verified in a simulation study.

• Structural Engineering and Mechanics
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• 제66권4호
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• pp.515-529
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• 2018

Multiple hazards (multihazard) conditions may cause significant risk to structures that are originally designed for individual hazard scenarios. Such a multihazard condition arises when an earthquake strikes to a bridge pre-exposed to scour at foundations due to flood events. This study estimates the impact spectrum of flood-induced scour on seismic vulnerability of bridges. Characteristic river-crossing highway bridges are formed based on the information obtained from bridge inventories. These bridges are analyzed under earthquake-only and the abovementioned multihazard conditions, and bridge fragility curves are developed at component and system levels. Research outcome shows that bridges having pile shafts as foundation elements are protected from any additional seismic vulnerability due to the presence of scour. However, occurrence of floods can increase seismic fragility of bridges at lower damage states due to the adverse impact of scour on bridge components at superstructure level. These findings facilitate bridge design under the stated multihazard condition.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.311-316
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• 2007

The improvement of speed and ride comfort requires a very horizontally and vertically rigid and non-flexible alignment. It is inevitable to construct many bridges depending on the topography of landscapes and obliged to lay turnouts on the bridges. In that case, special considerations have to be taken into account, i.e. permissible stresses of turnout components and limitations of displacements of bridge and turnouts. In this studies, numerical analyses for turnout/bridge interaction are carried out using commercial program LUSAS. The target of analytical model is the turnout layed near Pyeongrae-Hopyeng station on Kyeongchun line. The lead rail, stock rails, and the bridge are modelled using beam elements. Fasteners and ballast resistances are modelled using bi-linear spring elements. The turnout behaviors are investigated by varying the parameters such as span length of bridge, spring coefficients, and thermal loads.

• 한국산업융합학회 논문집
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• 제10권1호
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• pp.47-54
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• 2007

Bridge decks are one of the main structural components that are most suitable for utilizing the advantages of FRP materials due to the high strength weight ratio of FRP materials. Design codes for the design of FRP bridge decks should be established to apply FRP materials for bridge decks effectively. At present, design codes are relatively well established for the use of FRP materials as reinforcements in concrete structures. However, design codes have not yet been provided for the structures made of FRP as a main construction material. In this study, for the purpose of preparing design code provisions, reliability analyses were performed to evaluate target level of safety and serviceability on GFRP decks. Based on the results, several guidelines for the development of design codes are suggested.

• 한국BIM학회 논문집
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• 제12권1호
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• pp.10-22
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• 2022

Prefabricated bridges require strict management of tolerance during fabrication and assembly. In this paper, digital engineering models for prefabricated bridge components such as deck, girder, pier, abutment are suggested to support information delivery through the life-cycle of the bridge. Rule-based modeling is used to define geometry of the members considering variable dimensions due to fabrication and assembly error. DfMA(design for manufacturing and assembly) provides the rules for ease of fabrication and assembly. The digital engineering model consists of geometry, constraints and corresponding parameters for each phase. Alignment and control points are defined to manage tolerances of the prefabricated bridge during fabrication and assembly. Quality control by digital measurement of dimensions was also considered in the model definition. A pilot bridge was defined virtually to validate the suggested digital engineering models. The digital engineering models for DfMA showed excellent potential to realize prefabricated bridges.