• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.301-329
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• 2017

Impedance-based damage detection method has been known as an innovative tool with various successful implementations for structural health monitoring of civil structures. To monitor the local critical area of a structure, the impedance-based method utilizes the high-frequency impedance responses sensed by piezoelectric sensors as the local dynamic features. In this paper, current advances and future challenges of the impedance-based structural health monitoring are presented. Firstly, theoretical background of the impedance-based method is outlined. Next, an overview is given to recent advances in the wireless impedance sensor nodes, the interfacial impedance sensing devices, and the temperature-effect compensation algorithms. Various research works on these topics are reviewed to share up-to-date information on research activities and implementations of the impedance-based technique. Finally, future research challenges of the technique are discussed including the applicability of wireless sensing technology, the predetermination of effective frequency bands, the sensing region of impedance responses, the robust compensation of noise and temperature effects, the quantification of damage severity, and long-term durability of sensors.

• Toxicological Research
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• v.22 no.4
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• pp.423-429
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• 2006

Recent reports on the photocarcinogenicity and photogerotoxicity of many compounds led to an increasing awareness for the need of a standard approach to test for photogenotoxicity. The comet assay has been recently validated as a sensitive and specific test system for the quantification of DNA damage. Thus, the objectives of this study are to investigate the utility of photo-comet assay for detecting photo-mutagens, and to evaluate its ability to predict rodent photo-carcinogenicity. Photo-comet assays were performed using L5178Y $Tk^{+/-}$ mouse lymphoma cells on five test substances (8-methoxypsoralen, chlorpromazine, lomefloxacin, anthracene and retinoic acid) that demonstrated positive results in photocarcinogenicity tests. For the best discrimination between the test substance-mediated DNA damage and the undesirable DNA damage caused by direct UV absorption, a UV dose-response of the cells in the absence of the test substances was firstly fnalized. Out of 5 test substances, positive comet results were obtained for chlorpromazine, lomefloxacin, anthracene and retinoic acid while 8-methoxypsoralen found negative. An investigation into the predictive value of this photo-comet assay for determining the photocarcinogenicity showed that photo-comet assay has relatively high sensitivity. Therefore, the photo-comet assay with mammalian cells seems to be a good and sensitive predictor of the photocarcinogenic potential of new substances.

• Structural Engineering and Mechanics
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• v.72 no.5
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• pp.585-595
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• 2019

Foundations are a vital part of structures. Over time, the foundations can deteriorate due to unforeseen overloads and/or settlements, resulting in the appearance of cracks in the concrete. These cracks produce changes in the static and dynamic behavior of the affected foundation, which alter its load carrying capacity. In this work, non-destructive techniques of relative simplicity of application are presented for the detection, location, and quantification of damage, using numerical models, solved with the finite element method and Power Series. For this, two types of parameters are used: static (displacement and elastic curvature) and dynamics (natural frequencies). In the static analysis, the damage detection is done by means of a finite elements model representing a beam supported on an elastic foundation with a discrete crack that varies in length and location. With regard to dynamic analysis, the governing equations of the model are presented and a method based on Power Series is used to obtain the solution for a data set, which could be the Winkler coefficient, the location of the crack or the frequency. In order to validate the proposed methodologies, these techniques are applied to data obtained from laboratory tests.

• 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.

• Structural Engineering and Mechanics
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• v.84 no.4
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• pp.489-502
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• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.126-135
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• 2000

Probabilistic Safety Assessment (PSA) is an engineering analysis method to identify possible contributors to the risk from a nuclear power plant and now it has become a standard tool in safety evaluation of nuclear power plants. PSA consists of three phases named as Level 1, 2 and 3. Level 2 PSA, mainly focused in this paper, uses a step-wise approach. At first, plant damage states (PDSs) are defined from the Level 1 PSA results and they are quantified. Containment event tree (CET) is then constructed considering the physico-chemical phenomena in the containment. The quantification of CET can be assisted by a decomposition event tree (DET). Finally, source terms are quantitatively characterized by the containment failure mode. As the main benefit of PSA is to provide insights into plant design, performance and environmental impacts, including the identification of the dominant risk contributors and the comparison of options for reducing risk, this technique is expected to be applied to the industrial safety area.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.444-455
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• 2009

Great concerns on geotechnical risk & hazard assessment have been increased due to human and economic damage by natural disasters with recent global climate changes. In this paper, geotechnical problems in particular, landslides which is interested in European countries and North America, were mainly discussed. For these, 18 key topics on geotechnical risk and hazards which had been discussed at the LARAM 2008 workshop in Italy were analyzed after grouping by subjects. Main topic contents consisted of applications such as field measurement, early warning systems, uncertainty analysis of parameters using radar, optical data and statistical theory and so on. And the problems related to analysis of vulnerability and deformation due to earthquakes, investigation of gas zone using seismic reflection data in a landslide area, risk quantification and hazard assessment of landslide movements and multi-dimensional analysis for stability of complex slopes were attracted. Also, there were studies on risk matters of cultural heritage, the blockglide of clayey ground, simulations of debris flows based on GIS, quantification of the failure processes of rock slopes, a meshless method for 3D crack modelling, and finally risk assessment for cryological processes due to global warming.

• Journal of Conservation Science
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• v.31 no.3
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• pp.287-298
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• 2015

The formaldehyde is damage to the metal are known universally. However, the quantification of the damage level and degree of damage is not clear. This study was conducted to test the following steps using a gas corrosion tester, and then evaluated by the optical, chemical and physical measurement. First, it was confirmed the damage level of the metal specimen(silver, copper, iron, lead, brass) by the formaldehyde(0.5, 1, 10, 100, 500ppm). Second, weighted damage to the metal specimens were tested according to the temperature and humidity conditions under damage levels. Third, the damage of accelerated degradation metal specimens were examined under damage levles. As a result, at 500ppm / day, the optical, chemical and physical damage of lead have been identified, the optical damage of all metals are was observed. The optical damage of some specimens were weighted in $25^{\circ}C-50%$, $30^{\circ}C-50%$. Chemical damage to the lead specimen is 2.8 times, 1.3 times were weighted in $30^{\circ}C-80%$, $25^{\circ}C-80%$. Referring to formate ion concentration of the accelerated degradation metal, corrosion products of iron and brass were actived the reaction of the formaldehyde gas, oxide film of lead was blocked the reaction of formaldehyde gas.

• Smart Structures and Systems
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• v.31 no.4
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• pp.393-407
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• 2023

To assess structural condition in a non-destructive manner, computer vision-based structural health monitoring (SHM) has become a focus. Compared to traditional contact-type sensors, the advantages of computer vision-based measurement systems include lower installation costs and broader measurement areas. In this study, we propose a novel computer vision-based vibration measurement and coarse-to-fine damage assessment method for truss bridges. First, a deep learning model FairMOT is introduced to track the regions of interest (ROIs) that include joints to enhance the automation performance compared with traditional target tracking algorithms. To calculate the displacement of the tracked ROIs accurately, a normalized cross-correlation method is adopted to fine-tune the offset, while the Harris corner matching is utilized to correct the vibration displacement errors caused by the non-parallel between the truss plane and the image plane. Then, based on the advantages of the stochastic damage locating vector (SDLV) and Bayesian inference-based stochastic model updating (BI-SMU), they are combined to achieve the coarse-to-fine localization of the truss bridge's damaged elements. Finally, the severity quantification of the damaged components is performed by the BI-SMU. The experiment results show that the proposed method can accurately recognize the vibration displacement and evaluate the structural damage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.218-226
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• 2020

An experimental study was conducted on baseline model updating and damage estimation techniques for the health monitoring of offshore wind turbine tripod substructures. First, a procedure for substructure health monitoring was proposed. An initial baseline model for a scaled model of a tripod substructure was established. A baseline model was updated based on the natural frequencies and the mode shapes measured in the healthy state. A training pattern was then generated using the updated baseline model, and the damage was estimated by inputting the modal parameters measured in the damaged state into the trained neural network. The baseline model could be updated reasonably using the effective fixity model. The damage tests were performed, and the damage locations could be estimated reasonably. In addition, the estimated damage severity also increased as the actual damage severity increased. On the other hand, when the damage severity was relatively small, the corresponding damage location was detected, but it was more difficult to identify than the other cases. Further studies on small damage estimation and stiffness reduction quantification will be needed before the presented method can be used effectively for the health monitoring of tripod substructures.