• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.129-150
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• 2018

This paper presents the structural performance monitoring of an urban footbridge located in Hangzhou, China. The structural health monitoring (SHM) system is designed and implemented for the footbridge to monitor the structural responses of the footbridge and to ensure the structural safety during the period of operation. The monitoring data of stress and displacement measured by the fiber Bragg grating (FBG)-based sensors installed at the critical locations are used to analyze and assess the operation performance of the footbridge. A linear regression method is applied to separate the temperature effect from the stress monitoring data measured by the FBG-based strain sensors. In addition, the static vertical displacement of the footbridge measured by the FBG-based hydrostatic level gauges are presented and compared with the dynamic displacement remotely measured by a machine vision-based measurement system. Based on the examination of the monitored stress and displacement data, the structural safety evaluation is executed in combination with the defined condition index.

• Structural Engineering and Mechanics
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• v.15 no.3
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• pp.285-297
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• 2003

Complementing recent advances made in the field of structural health monitoring and damage detection, the concept of a wireless sensing network with distributed computational power is proposed. The fundamental building block of the proposed sensing network is a wireless sensing unit capable of acquiring measurement data, interrogating the data and transmitting the data in real time. The computational core of a prototype wireless sensing unit can potentially be utilized for execution of embedded engineering analyses such as damage detection and system identification. To illustrate the computational capabilities of the proposed wireless sensing unit, the fast Fourier transform and auto-regressive time-series modeling are locally executed by the unit. Fast Fourier transforms and auto-regressive models are two important techniques that have been previously used for the identification of damage in structural systems. Their embedment illustrates the computational capabilities of the prototype wireless sensing unit and suggests strong potential for unit installation in automated structural health monitoring systems.

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.33-49
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• 2016

Structural Health Monitoring (SHM) has been attracting numerous research efforts around the world because it targets at monitoring structural conditions and performance to prevent catastrophic failure, and to provide quantitative data for engineers and infrastructure owners to design a reliable and economical asset management strategy. In the past decade, with supports from Australian Research Council (ARC), Cooperative Research Center for Infrastructure and Engineering Asset Management (CIEAM), CSIRO and industry partners, intensive research works have been conducted in the School of Civil, Environmental and Mining Engineering, University of Western Australia and Centre for Infrastructural Monitoring and Protection, Curtin University on various techniques of SHM. The researches include the development of hardware, software and various algorithms, such as various signal processing techniques for operational modal analysis, modal analysis toolbox, non-model based methods for assessing the shear connection in composite bridges and identifying the free spanning and supports conditions of pipelines, vibration based structural damage identification and model updating approaches considering uncertainty and noise effects, structural identification under moving loads, guided wave propagation technique for detecting debonding damage, and relative displacement sensors for SHM in composite and steel truss bridges. This paper aims at summarizing and reviewing the recent research advances on SHM of civil infrastructure in Western Australia.

• Smart Structures and Systems
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• v.19 no.5
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• pp.499-512
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• 2017

Traditional structural dynamic analysis and Structural Health Monitoring (SHM) of large scale concrete civil structures rely on manufactured embedding transducers to obtain structural dynamic properties. However, the embedding of manufactured transducers is very expensive and low efficiency for signal acquisition. In dynamic structural analysis and SHM areas, piezoelectric transducers are more and more popular due to the advantages like quick response, low cost and adaptability to different sizes. In this paper, the applicable feasibility assessment of the designed "artificial" piezoelectric transducers called Concrete Piezoelectric Smart Module (CPSM) in dynamic structural analysis is performed via three major experiments. Experimental Modal Analysis (EMA) based on Ibrahim Time Domain (ITD) Method is applied to experimentally extract modal parameters. Numerical modal analysis by finite element method (FEM) modeling is also performed for comparison. First ten order modal parameters are identified by EMA using CPSMs, PCBs and FEM modeling. Comparisons are made between CPSMs and PCBs, between FEM and CPSMs extracted modal parameters. Results show that Power Spectral Density by CPSMs and PCBs are similar, CPSMs acquired signal amplitudes can be used to predict concrete compressive strength. Modal parameter (natural frequencies) identified from CPSMs acquired signal and PCBs acquired signal are different in a very small range (~3%), and extracted natural frequencies from CPSMs acquired signal and FEM results are in an allowable small range (~5%) as well. Therefore, CPSMs are applicable for signal acquisition of dynamic responses and can be used in dynamic modal analysis, structural health monitoring and related areas.

• Smart Structures and Systems
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• v.1 no.4
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• pp.355-368
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• 2005

Large and complex structures are being built now-a-days and, they are required to be functional even under extreme loading and environmental conditions. In order to meet the safety and maintenance demands, there is a need to build sensors integrated structural system, which can sense and provide necessary information about the structural response to complex loading and environment. Sophisticated tools have been developed for the design and construction of civil engineering structures. However, very little has been accomplished in the area of monitoring and rehabilitation. The employment of appropriate sensor is therefore crucial, and efforts must be directed towards non-destructive testing techniques that remain functional throughout the life of the structure. Fiber optic sensors are emerging as a superior non-destructive tool for evaluating the health of civil engineering structures. Flexibility, small in size and corrosion resistance of optical fibers allow them to be directly embedded in concrete structures. The inherent advantages of fiber optic sensors over conventional sensors include high resolution, ability to work in difficult environment, immunity from electromagnetic interference, large band width of signal, low noise and high sensitivity. This paper brings out the potential and current status of technology of fiber optic sensors for civil engineering applications. The importance of employing fiber optic sensors for health monitoring of civil engineering structures has been highlighted. Details of laboratory studies carried out on fiber optic strain sensors to assess their suitability for civil engineering applications are also covered.

• Computational Structural Engineering
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• v.20 no.1 s.75
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• pp.65-70
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• 2007

• Computational Structural Engineering
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• v.33 no.3
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• pp.7-15
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• 2020

• Journal of Korean Academy of Nursing
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• v.40 no.3
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• pp.389-399
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• 2010

Purpose: The aim of this study was to construct a structural equation model that would further explain the mental health status of Korean immigrants living in Canada. Methods: Survey using a structured questionnaire was conducted with 386 people in Canada (Vancouver and Toronto). Six instruments were used in this model. The analysis of data was done with both SPSS 14.0 for descriptive statistics and AMOS 5.0 for covariance structure analysis. Results: Based on the constructed model, physical health status, immigrant life stress, self esteem, and quality of life were found to have significant direct effect on mental health. In addition, factors such as physical health status, immigrant life stress, quality of life, English proficiency, family cohesion and social support were found to indirectly affect mental health. The final modified model yielded Chi-square=34.79 (p<.001), df=13, $x^2$/df=2.68, GFI=0.98, AGFI=0.94, NFI=0.95, PNFI=0.44, PGFI=0.35, RMSE=0.07 and exhibited good fit indices. Conclusion: This structural equation model is a comprehensive theoretical model that explains the related factors and their relationship with mental health in Korean immigrants. Findings of this study can contribute to the designing of an appropriate prevention strategy to further improve the mental health of immigrants in Canada.

• Journal of the Korean Society of Food Culture
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• v.22 no.5
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• pp.590-596
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• 2007

The purpose of this study was to measuring the effects of health involvement, attitude, perceived behavioral control (PBC), behavioral intention on seafood consumption. A total of 235 questionnaires were completed. Structural equation model was used to measure the causal relationships among constructs. Results of the study demonstrated that the structural analysis result for the data also indicated excellent model fit. The direct effect of health involvement on attitude was statistically significant. The direct effects of health involvement, attitude and PBC on consumption were statistically significant. As expected, attitude, PBC and behavioral intention had significant direct effects on consumption. Moreover, health involvement had a significant indirect effect on behavioral intention through attitude and PBC. Health involvement also had a significant indirect effect on consumption through attitude, PBC and behavioral intention. Attitude and PBC had significant indirect effects on consumption through behavioral intention. In conclusion, based on structural analysis, a model was proposed of interrelations among health involvement, attitude, PBC, behavioral intention and seafood consumption. Other variables(sensory variable, habit, norm etc) may be incorporated to form models that consist of new antecedent and consequence pairs.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.20 no.2
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• pp.14-17
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• 2016