• Smart Structures and Systems
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• v.15 no.3
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• pp.523-541
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• 2015

Structural health monitoring of steel truss bridge based on changes in modal properties was investigated in this study. Vibration measurements with five sensors were conducted at an existing Warren truss bridge with partial fractures in diagonal members before and after an emergency repair work. Modal properties identified by the Eigensystem Realization Algorithm showed evidences of increases in modal damping due to the damage in diagonal member. In order to understand the dynamic behavior of the bridge and possible mechanism of those increases in modal damping, theoretical modal analysis was conducted with three dimensional frame models. It was found that vibrations of the main truss could be coupled internally with local vibrations of diagonal members and the degree of coupling could change with structural changes in diagonal members. Additional vibration measurements with fifteen sensors were then conducted so as to understand the consistency of those theoretical findings with the actual dynamic behavior. Modal properties experimentally identified showed that the damping change caused by the damage in diagonal member described above could have occurred in a diagonal-coupled mode. The results in this study imply that damages in diagonal members could be detected from changes in modal damping of diagonal-coupled modes.

• Smart Structures and Systems
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• v.15 no.3
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• pp.593-608
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• 2015

In many of the industrialized countries an increasing amount of infrastructure is ageing. This has become specifically critical to bridges which are a major asset with respect to keeping an economy alive. Life of this infrastructure is scattering but often little quantifiable information is known with respect to its damage condition. This article describes how a damage tolerance approach used in aviation today may even be applied to civil infrastructure in the sense that operational life can be applied in the context of modern life cycle management. This can be applied for steel structures as a complete process where much of the damage accumulation behavior is known and may even be adopted to concrete structures in principle, where much of the missing knowledge in damage accumulation has to be substituted by enhanced inspection. This enhanced and continuous inspection can be achieved through robotic systems in a first approach as well as built in sensors in the sense of structural health monitoring (SHM).

• YAKHAK HOEJI
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• v.51 no.1
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• pp.1-6
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• 2007

The aim of this study was to examine whether administration of glutamine are able to prevent the methotrexate induced gut barrier damage, bacterial translocation, and weight changes. The animals with glutamine were fed with L-glutamine (1.2 and 2.4 mg/kg/day) for 7 days before methotrexate administration (20 mg/kg orally). 48 hour after methotrexate administration, intestinal permeability were measured for an assessment of the gut barrier dysfunction. Also, enteric aerobic bacterial counts, number of gram-negatives in mesenteric lymph node (MLN), liver spleen, kidney and heart were measured for an assessment of the enteric bacterial number and bacterial translocation. Amounts of food intake, body weight changes and organ weight changes of liver spleen, kidney and heart were measured. Methotrexate administration caused body and liver weight loss regardless amounts of food intakes. Methotrexate induced increasing intestinal permeability, enteric bacterial undergrowth and bacterial translocation to MLN, liver and spleen, but not kidney and heart. The supplements with glutamine reduced the intestinal permeability bacterial translocation, and not influences enteric bacterial number, and body and liver weight changes. This study suggested that glutamine might effectively reduce methotrexate induced intestinal damage and bacterial translocation, but not influence body and organ weight loss.

• Journal of Radiation Industry
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• v.10 no.4
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• pp.199-204
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• 2016

The dependence of cell survival on exposure dose and the duration of the liquid-holding recovery (LHR) was obtained for diploid yeast cells irradiated with ionizing radiation of different linear energy transfer (LET) and recovering from radiation damage without and with various concentrations of cisplatin - the most widely used anticancer drug. The ability of yeast cells to recover from radiation damage was less effective after cell exposure to high-LET radiation, when cells were irradiated without drug. The increase in cisplatin concentration resulted in the disappearance of this difference whereas the fraction of irreversible damage was permanently enlarged independently of radiation quality. The probability of cell recovery was shown to be constant for various conditions of irradiation and recovery. A new mechanism of cisplatin action was suggested according with which the inhibition of cell recovery after exposure to ionizing radiations was completely explained by the production of irreversible damage.

• Steel and Composite Structures
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• v.29 no.6
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• pp.703-716
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• 2018

Rapid detection of damages in civil engineering structures, in order to assess their possible disorders and as a result produce competent decision making, are crucial to ensure their health and ultimately enhance the level of public safety. In traditional intelligent health monitoring methods, the features are manually extracted depending on prior knowledge and diagnostic expertise. Inspired by the idea of unsupervised feature learning that uses artificial intelligence techniques to learn features from raw data, a two-stage learning method is proposed here for intelligent health monitoring of civil engineering structures. In the first stage, $Nystr{\ddot{o}}m$ method is used for automatic feature extraction from structural vibration signals. In the second stage, Moving Kernel Principal Component Analysis (MKPCA) is employed to classify the health conditions based on the extracted features. In this paper, KPCA has been implemented in a new form as Moving KPCA for effectively segmenting large data and for determining the changes, as data are continuously collected. Numerical results revealed that the proposed health monitoring system has a satisfactory performance for detecting the damage scenarios of a three-story frame aluminum structure. Furthermore, the enhanced version of KPCA methods exhibited a significant improvement in sensitivity, accuracy, and effectiveness over conventional methods.

• 대한예방의학회:학술대회논문집
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• 2002.10a
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• pp.298-299
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• 2002

• Smart Structures and Systems
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• v.20 no.4
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• pp.427-440
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• 2017

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

• Journal of Nutrition and Health
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• v.37 no.4
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• pp.281-290
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• 2004

The purpose of this project was to evaluate whether daily fruit juice consumption could reduce the DNA damage in healthy subjects. The study was performed using 67 healthy volunteers (29 smokers, 38 nonsmokers) who were supple-mented with 480 m1 of grape juice for 8 weeks. Eight weeks of grape juice consumption did not change any anthropometric parameters. Lymphocyte DNA damage before the study was significantly greater (p<0.05) in smoker than nonsmoker, but, grape juice consumption significantly reduced DNA damage in both smoker (26%) and nonsmoker (I7%) to the level where there was no difference remained between the two groups after the intervention trial. This preventive effect of grape juice against DNA damage was not affected by sex of the subjects in non-smokers. Plasma $\alpha$-carotene, Iyco-pene and ${\gamma}$-totopherol was significantly increased after the trial in smokers, while erythrocyte catalase was significan-tly increased in both smokers and nonsmokers. Total radical-trapping antioxidant potential (TRAP) level in all subjects was significantly reduced after the intervention, while GSH-Px activity was increased only in nonsmokers. These results suggests that daily consumption of grape juice may protect DNA damage in peripheral lymphocytes, and supports the hypothesis that grape juice might exert their effect partially via a decrease in oxidative damage to DNA in humans partly by improving their antioxidative defense system.

• Smart Structures and Systems
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• v.11 no.1
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• pp.87-102
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• 2013

Vibration-based damage detection methods are popular for structural health monitoring. However, they can only detect fairly large damages. Usually impact pulse, ambient vibrations and sine-wave forces are applied as the excitations. In this paper, we propose the method to use the chaotic excitation to vibrate structures. The attractors built from the output responses are used for the minor damage detection. After the damage is detected, it is further quantified using the Kalman Filter. Simulations are conducted. A 5-story building is subjected to chaotic excitation. The structural responses and related attractors are analyzed. The results show that the attractor distances increase monotonously with the increase of the damage degree. Therefore, damages, including minor damages, can be effectively detected using the proposed approach. With the Kalman Filter, damage which has the stiffness decrease of about 5% or lower can be quantified. The proposed approach will be helpful for detecting and evaluating minor damages at the early stage.

• Structural Engineering and Mechanics
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• v.25 no.1
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• pp.39-52
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• 2007

This paper describes an experimental study on structural health monitoring of a 1:3-scaled one-story concrete frame subjected to seismic damage and retrofit. The structure is tested on a shaking table by exerting successively enhanced earthquake excitations until severe damage, and then retrofitted using fiber-reinforced polymers (FRP). The modal properties of the tested structure at trifling, moderate, severe damage and strengthening stages are measured by subjecting it to a small-amplitude white-noise excitation after each earthquake attack. Making use of the measured global modal frequencies and a validated finite element model of the tested structure, a neural network method is developed to quantitatively identify the stiffness reduction due to damage and the stiffness enhancement due to strengthening. The identification results are compared with 'true' damage severities that are defined and determined based on visual inspection and local impact testing. It is shown that by the use of FRP retrofit, the stiffness of the severely damaged structure can be recovered to the level as in the trifling damage stage.