• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.101-104
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• 2008

Recently, the serious damage by earthquakes is increased around the world. SOC fo city is established to minimize the loss of lives and assets by earthquakes, which an objective standard is required. Generally, bridges damage by earthquakes occurred the inelastic hinge under the column. Nonlinear element model of inelastic hinge have been used to Bilinear model, but Takeda model for material characterization of concrete is a little. In this study, railway bridge was performed seismic fragility analysis for Takeda model and Bilinear model comparatively. This analysis shows that damage probability of Takeda model is larger than Bilinear model. And analysis of Takeda model in longitudinal direction and transverse direction are different. Therefore developed analysis for concrete column of bridge is expected to apply to material characterization.

• Computational Structural Engineering
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• v.7 no.3
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• pp.153-166
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• 1994

A methodology to assess damage prediction accuracy as a function of model uncertainty in structures is presented. In the first part, a theory of approach is outlined. First, a damage detection algorithm to locate and size damage in structures using few modal responses of the structures is summarized. Next, methods to quantify model uncertainty and the damage detection accuracy are formulated. In the second part, a methodology to assess the effect of model uncertainty on the damage detection accuracy of real structures is designed. In the last part, the feasibility of the assessment methodology is demonstrated by using a plate-girder bridge for which only information on a single mode is available.

• Current Optics and Photonics
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• v.3 no.6
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• pp.502-509
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• 2019

Based on the typical pixel structure and parameters of a polysilicon uncooled bolometer, the absorption rate of a polysilicon microbridge infrared detector for 10.6 ㎛ laser energy was calculated through the optical admittance method, and the thermal coupling model of a polysilicon microbridge component irradiated by far infrared laser was established based on theoretical formulas. Then a numerical simulation study was carried out by means of finite element analysis for the actual working environment. It was found that the maximum temperature and maximum stress of the microbridge component are approximately exponentially changing with the laser power of the irradiation respectively and that they increase monotonically. The highest temperature zone of the model is gradually spread by the two corners of the bridge surface that are not connected to the bridge legs, and the maximum stress acts on both sides of the junction of the microbridge legs and the substrate. The mechanism of laser-induced hard damage to polysilicon detectors is the melting damage caused by high temperature. This paper lays the foundation for the subsequent study of the interference mechanism of the laser on working state polysilicon detectors.

• Structural Engineering and Mechanics
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• v.7 no.4
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• pp.387-400
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• 1999

Damage detection in civil engineering structures using the change in dynamic system parameters has gained a lot of scientific interest during the last decade. By repeating a dynamic test on a structure after a certain time of use, the change in modal parameters can be used to quantify and qualify damages. To be able to use the modal parameters confidentially for damage evaluation, the effect of other parameters such as excitation type, ambient conditions,... should be considered. In this paper, the influence of excitation type on the dynamic system parameters of a highway prestressed concrete bridge is investigated. The bridge, B13, lies between the villages Vilvoorde and Melsbroek and crosses the highway E19 between Brussels and Antwerpen in Belgium. A drop weight and ambient vibration are used to excite the bridge and the response at selected points is recorded. A finite element model is constructed to support and verify the dynamic measurements. It is found that the difference between the natural frequencies measured using impact weight and ambient vibration is in general less than 1%.

• Steel and Composite Structures
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• v.14 no.4
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• pp.367-377
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• 2013

Damage in structures often leads to failure. Thus it is very important to monitor structures for the occurrence of damage. When damage happens in a structure the consequence is a change in its modal parameters such as natural frequencies and mode shapes. Artificial Neural Networks (ANNs) are inspired by human biological neurons and have been applied for damage identification with varied success. Natural frequencies of a structure have a strong effect on damage and are applied as effective input parameters used to train the ANN in this study. The applicability of ANNs as a powerful tool for predicting the severity of damage in a model steel girder bridge is examined in this study. The data required for the ANNs which are in the form of natural frequencies were obtained from numerical modal analysis. By incorporating the training data, ANNs are capable of producing outputs in terms of damage severity using the first five natural frequencies. It has been demonstrated that an ANN trained only with natural frequency data can determine the severity of damage with a 6.8% error. The results shows that ANNs trained with numerically obtained samples have a strong potential for structural damage identification.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.5
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• pp.19-27
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• 2002

Dynamic responses of a multi-span simply supported bridge are investigated to examine the effect of bearing damage under seismic excitations. The damaged bearings are modeled as sliding elements with friction between the superstructure and the top of the pier. Various values of the friction coefficients are examined to figure out the effect of damaged bearings with various levels of peak ground accelerations. It is found that the global seismic behaviors are significantly influenced by the occurrence of bearing damage. It should be noticed that the most possible location of unseating failure of superstructures differs from that in the bridge model without considering the bearing damage. It can be concluded that the bearing damage may play the major role in the unseating failure of a bridge system, so that the damage of bearings should be included to achieve more rational seismic safety evaluation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.235-242
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• 2004

Bridge Management System (BMS) requires a more objective condition assessment over the lifespan of a given bridge. Thus, a quantitative assessment model of resistance capacity was developed here to meet the requirement for deteriorated concrete bridges. The model focuses on damage mechanisms of concrete bridges deteriorated by traffic loads and environment factors such as chloride and carbonation attacks. Also, it was applied to a typical concrete slab bridge which was severely damaged due to both load and environmental conditions. It was shown that the proposed quantitative model simulates well the deterioration level considering the two damage criteria.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1490-1495
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• 2005

In this study, Model test of concrete frame structures with various shapes and locations are carried out by means of applying Peck's(1969) settlement method. The results of the model test indicated that important correlations existed between the behavior of frame structure and ground movement. Also, the damage level of frame structure closely influenced by the phase of excavation. Therefore, prediction of damage level at early phase of construction should be very precise. The damage level graph by Cording et al.(2001), the angular distortion provided gradually more serious damage to frame structures for the all cases. But the damage level graph by Burland(1997), was difficult to confirm because of very small amount of deflection ratio.

• Earthquakes and Structures
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• v.15 no.6
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• pp.701-713
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• 2018

Many bridges in Algeria were constructed without taking into account the seismic effect in the design. The implantation of a new regulation code RPOA-2008 requires a higher reinforcement ratio than with the seismic coefficient method, which is a common feature of the existing bridges. For better perception of the performance bridge piers and evaluation of the risk assessment of existing bridges, fragility analysis is an interesting tool to assess the vulnerability study of these structures. This paper presents a comparative performance of bridge piers designed with the seismic coefficient method and the new RPOA-2008. The performances of the designed bridge piers are assessed using thirty ground motion records and incremental dynamic analysis. Fragility curves for the bridge piers are plotted using probabilistic seismic demand model to perform the seismic vulnerability analysis. The impact of changing the reinforcement strength on the seismic behavior of the designed bridge piers is checked by fragility analysis. The fragility results reveal that the probability of damage with the RPOA-2008 is less and perform well comparing to the conventional design pier.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.107-116
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• 2022

Recently, research has been actively conducted on the technology of inspection facilities through image-based analysis assessment of human-inaccessible facilities. This research was conducted to study the conditions of deep learning-based imaging data on bridges and to develop an evaluation prototype program for bridges. To develop a deep learning-based bridge damage detection prototype, the Semantic Segmentation model, which enables damage detection and quantification among deep learning models, applied Mask-RCNN and constructed learning data 5,140 (including open-data) and labeling suitable for damage types. As a result of performance modeling verification, precision and reproduction rate analysis of concrete cracks, stripping/slapping, rebar exposure and paint stripping showed that the precision was 95.2 %, and the recall was 93.8 %. A 2^nd performance verification was performed on onsite data of crack concrete using damage rate of bridge members.