• Structural Monitoring and Maintenance
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• v.2 no.3
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• pp.181-197
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• 2015

Assessing the condition of paint on civil structures is an important but challenging and costly task, in particular when it comes to large and complex structures. Current practices of visual inspection are labour-intensive and time-consuming to perform. In addition, this task usually relies on the experience and subjective judgment of individual inspectors. In this study, hyperspectral imaging and classification techniques are proposed as a method to objectively assess the state of the paint on a civil or other structure. The ultimate objective of the work is to develop a technology that can provide precise and automatic grading of paint condition and assessment of degradation due to age or environmental factors. Towards this goal, we acquired hyperspectral images of steel surfaces located at long (mid-range) and short distances on the Sydney Harbour Bridge with an Acousto-Optics Tunable filter (AOTF) hyperspectral camera (consisting of 21 bands in the visible spectrum). We trained a multi-class Support Vector Machines (SVM) classifier to automatically assess the grading of the paint from hyperspectral signatures. Our results demonstrate that the classifier generates highly accurate assessment of the paint condition in comparison to the judgement of human experts.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2017.10a
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• pp.59-60
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• 2017

• Journal of the Korea institute for structural maintenance and inspection
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• v.4 no.4
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• pp.101-107
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• 2000

In this study, the Ground Penetrating Radar(GPR) was tested to evaluate the condition of concrete decks. Test results obtained by CPR were compared with values measured from drilled cores and damage mapping by the visual survey. It is shown that GPR can provide highly accurate measurements of layer properties of concrete decks and can map areas of deterioration in bridge decks by dielectric constants. The deck condition can be grouped into categories of "good" or "distressed". The ground penetrating radar data shows promise for producing rapid and accurate condition assessment for bridge decks. And these data can be used to evaluate highway bridge condition and make cost-effective bridge deck rehabilitation by accurately estimating the quantity of deteriorated concrete.

• Structural Monitoring and Maintenance
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• v.10 no.2
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• pp.133-154
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• 2023

Obscured structural members are mostly under-evaluated during condition assessment due to lack of visual inspection capability. Insufficient information about the integrity of these structural members poses a significant risk for public safety. Time domain reflectometry (TDR) is a novel approach in structural health monitoring (SHM). Ordinary coaxial cables "as is" without a major modification are not suitable for SHM with TDR. The objective of this study is to propose a practical and cost-effective modification approach to commercially available coaxial cables in order to use them as a "cable sensor" for damage detection with the TDR equipment for obscured structural members. The experimental validation and assessment of the proposed modification approach was achieved by conducting 3-point bending tests of the model piles as a representative obscured structural member. It can be noted that the RG59/U-6 and RG6/U-4 cable sensors expose higher strain sensitivity in comparison with non-modified "as is" versions of the cables used. As a result, the cable sensors have the capability of sensing both the presence and the location of a structural damage with a maximum aberration of 3 cm. Furthermore, the crack development can be monitored by the RG59/U-6 cable sensor with a simple calibration.

• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.115-132
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• 2015

This paper presents a new method for seismic vulnerability assessment of buildings with reference to their operational limit state. The importance of this kind of evaluation arises from the civil protection necessity that some buildings, considered strategic for seismic emergency management, should retain their functionality also after a destructive earthquake. The method is based on the identification of experimental modal parameters from ambient vibrations measurements. The knowledge of the experimental modes allows to perform a linear spectral analysis computing the maximum structural drifts of the building caused by an assigned earthquake. Operational condition is then evaluated by comparing the maximum building drifts with the reference value assigned by the Italian Technical Code for the operational limit state. The uncertainty about the actual building seismic frequencies, typically significantly lower than the ambient ones, is explicitly taken into account through a probabilistic approach that allows to define for the building the Operational Index together with the Operational Probability Curve. The method is validated with experimental seismic data from a permanently monitored public building: by comparing the probabilistic prediction and the building experimental drifts, resulting from three weak earthquakes, the reliability of the method is confirmed. Finally an application of the method to a strategic building in Italy is presented: all the procedure, from ambient vibrations measurement, to seismic input definition, up to the computation of the Operational Probability Curve is illustrated.

• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.5
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• pp.83-93
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• 2017

This study proposed the new weighting values and fault points of condition assessment items for reinforced earth retaining walls based on the combination the inspection data and hybrid weighting technique. Utilizing the inspection data of 161 reinforced earth retaining walls, multi regression analysis and entropy technique were applied to gain the weighting values of condition assessment items. In addition, the weighting values by AHP technique was analyzed based on the opinion of experts. By appling hybrid weighting technique to the calculated weighting values obtained by the individual technique, the new weighting values of condition assessment items were proposed, and the fault points and fault indices of reinforced earth retaining walls were proposed. Results showed that the rank of the weighting value of the condition evaluation items was fluctuated according to the multiple regression analysis, AHP technique, and entropy technique. There was no duplication of the rank of the weighting value while the current weighting value was overlapped. Specially, in the rsults of multi regression analysis, two condition assessment items were occupied 70% of the total weights. When the proposed weighting values were applied to existing reinforced earth retaining wall of 161, 16 reinforced earth retaining walls showed the increased risk rank and 31 represented the decreased risk rank.

• Special Issue of the Society of Naval Architects of Korea
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• 2006.09a
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• pp.89-96
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• 2006

The objective of this paper is to find out a reasonable method for docking analysis of ships. The characteristics of reaction force distribution under docking condition are investigated by carrying out parametric study. To assess the allowable reaction force on keel block from structural strength point of view, two kinds of structural assessment methods are proposed in accordance with expected collapse pattern. In order to verify the proposed method, linear buckling and elasto-plastic large deflection analyses of typical double bottom structure are carried out and the results are compared.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.100-107
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• 1999

This paper describes a probabilistic remaining life assessment program for the creep crack growth. The probabilistic life assessment program is developed to increase the reliability of life assessment. The probabilistic life assessment involves some uncertainties, such as, initial crack size, material properties, and loading condition, and a triangle distribution function is used for random variable generation. The resulting information provides the engineer with an assessment of the probability of structural failure as a function of operating time given the uncertainties in the input data. This study forms basis of the probabilistic life assessment technique and will be extended to other damage mechanisms.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.3
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• pp.121-128
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• 2018

Severe earthquakes can cause damage to society both socially and economically. An appropriate initial response can alleviate damage from severe earthquakes. In order to formulate an appropriate initial response, it is necessary to identify damage situations in societies; however, it is difficult to grasp this information immediately after an earthquake event. In this study, an earthquake damage assessment methodology for buildings is proposed for estimating damage situations immediately after severe earthquakes. A response spectrum database is constructed to provide response spectra at arbitrary locations from earthquake measurements immediately after the event. The fragility curves are used to estimate the damage of the buildings. Earthquake damage assessment is performed from the response spectrum database at the building scale to provide enhanced damage condition information. Earthquake damage assessment for Gyeongju city and Pohang city were conducted using the proposed methodology, when an earthquake occurred on September 12, 2016, and November 15, 2017. Results confirm that the proposed earthquake damage assessment effectively represented the earthquake damage situation in the city to decide on an appropriate initial response by providing detailed information at the building scale.