Heungbae Gil

Renovation of Structural Health Monitoring System for Seohae Bridge, Seoul, South Korea

After years of research and development, the structural health monitoring system for the Seohae Bridge was installed in 2000 in South Korea. This steel–concrete composite cable-stayed bridge has a main span of 470 m. To monitor the long-term structural behavior and anomalies of the bridge, the system was composed of hundreds of sensors, including accelerometers, anemometers, and strain gauges. These sensors were installed on critical elements of the bridge, such as the stay cables, a stiffening girder, and the main pylons. After the development and stabilization phase, which lasted almost a year, the system has been successfully operated and has helped in understanding the structural characteristics and long-term behavior of the bridge. After more than 9 years of operation, however, the system started to show signs of aging and deterioration. Some gauges and sensors have worn out and have become malfunctioning. To fix these problems and upgrade the system, the renovation work was planned and carried out with a budget estimated at US

Multiple-Presence Statistics of Heavy Trucks Based on High-Speed Weigh-in-Motion Data

2 million. The main goals of the renovation work were to optimize sensor deployments, improve graphical user interfaces, and deploy state-of-the-art sensors and technologies. Although the number and types of sensors were minimized, a monitoring system based on a global navigational satellite system was newly installed to monitor deformation and geometry change of the bridge.

Thermal-Structure Interaction Parallel Fire Analysis for Steel-Concrete Composite Structures under Bridge Exposed to Fire Loading

The simultaneous presence of multiple heavy trucks on road bridges causes a higher stress to the structural members of bridges than the presence of a single heavy truck. Truck traffic data acquired using weigh-in-motion systems are typically used to assess the multiple-presence probability for side-by-side and following trucks. A number of high-speed weigh-in-motion (HS-WIM) systems are installed in the Korean Expressway Network to control overloaded vehicles and obtain long-term truck weight data. In this study, the multiple-presence probabilities for following and side-by-side trucks were determined using data from two HS-WIM sites. The correlation probability between the gross vehicle weights (GVWs) of successive trucks was also calculated. To determine the characteristics of heavier truck loads, the multiple-presence probabilities for the overweight trucks, which exceed the legal weight limit, were calculated separately. The analysis of the HS-WIM data showed that the multiple-presence probabilities of the trucks increased with the headway distance of following or side-by-side trucks, and the probability of following truck events was lower than that of side-by-side truck events. The probability of side-by-side truck events increased with the increase of daily truck traffic (DTT), whereas the probability of following truck events was only slightly affected by the DTT. The full correlation probabilities of the GVW for the following and side-by-side trucks were low.

Fire Risk Assessment for Highway Bridges in South Korea

The objective of this research is to evaluate of global and local damage for steel-concrete composite structures under highway bridge exposed to fire loading. To enhance the accuracy and efficiency of the numerical analysis, the proposed transient nonlinear thermal structure interaction(TSI) parallel fire analysis method is implemented in ANSYS. To validate the TSI parallel fire analysis method, a comparison is made with the standard fire test results. The proposed TSI parallel fire analysis method is applied to fire damage analysis and performance evaluation for Buchen highway bridge. The result of analysis, temperature of low flange and web are exceed the critical temperature. The deflection and deformation state show good agreement with the fire accident of buchen highway bridge.

Vibration Monitoring of Stay Cables Using Image Making and Pattern Recognition

The study presented in this paper developed a sequential and universal bridge fire risk assessment procedure for constructed bridges, as well as countermeasures to reduce the risk level. Of interest were concrete and steel bridges on highways, except for certain special types of bridges. The fire risk assessment procedure consisted of three steps: (a) preliminary risk analysis (PRA), which was a screening step to determine the likelihood of bridge fire events; (b) simplified risk analysis (SRA), which was performed with the use of bridge inventory databases and checklists; and (c) detailed risk analysis (DRA), which made use of computer simulation and collected data. A PRA determines whether a bridge requires an SRA on the basis of bridge clearance height and roadway conditions under the bridge. An SRA has three parts: analysis of fire occurrence, vulnerability to fire, and bridge importance. Itemized details were developed to evaluate the three parts and determine risk scoring. The SRA procedure identified which parts contributed to the resultant risk level. Reliability indexes concurrent with the latest ISO DP 10252 design code were used to determine the score of a given bridge and to perform an analysis to determine the risk level of 8,267 bridges in South Korea. The DRA was the final step, a detailed analysis of occurrence and vulnerability of a bridge mainly on the basis of computer simulation. This study provided guidelines to determine the DRA levels. Countermeasures also were developed for each of three risk levels (i.e., occurrence, vulnerability, and importance); the application of the countermeasures depended on the factors causing the risk.

Interactive shear buckling behavior of trapezoidally corrugated steel webs

The statistically processed results are sometimes not intuitive for the structural health monitoring systems of cable-stayed bridges which process voluminous data from a lot of sensors. For this reason, the signals-image recognition algorithm using images more intuitive than numerical values is presented in this study. The signals-image here means not a photograph taken by any camera but the artificial image which consists of measured signals and their process results. It is applied to extract the features from signals and identify the cable vibrations. Consequently, identifying and classifying signals-images have been successfully performed.