• Journal of Korean Society for Atmospheric Environment
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• v.25 no.6
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• pp.523-538
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• 2009

Recently, there has been a keen demand for real-time automatic monitoring of VOCs not only in Korea but other developed countries. We carried out this study to evaluate and to optimize the performance of a continuous automatic monitoring system for hazardous VOCs (HVOCs) in the ambient atmosphere, using an on-line GC system. The online system normally consisted of a Nafion dryer prior to a cold trap of an automatic thermal desorption apparatus and a GC system equipped with two detectors, i.e. PID and ECD. Preliminary tests conducted to check out any contamination of the system revealed an evidence of significant artifact formation of benzene, and it was found that the Nafion dryer (even brand new one) is the source of the benzene artifact. Thus, all the subsequent experiments in this study was carried out inevitably by removing the Nafion dryer. The on-line GC method was investigated with a variety of QC/QA performance criteria such as repeatability, linearity, lower detection limits, and accuracy. In order to find out the best operating condition for the on-line GC system, three different types (in terms of adsorption strength) of cold trap combinations were tested, i.e. (i) Tenax-TA and Carbopack-B combination (weak and hydrophobic); (ii) Tenax-TA, Carbopack-X and Carboxen-1000 combination (strong and hydrophilic); and (iii) Tenax-TA and Carbopack-X combination (medium and hydrophobic/hydrophilic). The USEPA TO-17 manual method was selected as a reference method to evaluate the performance of the on-line method. A series of experiments revealed that the system performance was superior to others when a cold trap packed with hydrophilic adsorbents (Tenax-TA/Carbopack-X/Carboxen-1000 combination) was used and operated at $25^{\circ}C$. However, the system with a cold trap packed with a combination of Tenax-TA and Carbopack-X is more recommended for field applications since the carboxen-1000 adsorbent is too sensitive to water vapor, and hence the performance of the system might be very unstable to humid samples or during rainy days. Furthermore, the precision and accuracy criteria of the Tenax-TA/ Carbopack-X combination were generally compatible with the triple adsorbents cold trap. The continuous automatic monitoring method is, thus, considered very useful to real-time monitoring to understand the variations of VOCs concentrations in ambient air, as it adopts much simpler procedures in sampling, analysis, and data integration steps than manual monitoring methods. However, it should be noted that there is a high possibility of benzene artifacts formation through the Nafion dryer, which is often installed to remove water vapor in air samples before being adsorbed onto the cold trap. Therefore, if a Nafion dryer is used in any studies of monitoring VOCs, the benzene contamination should be carefully examined before carrying out obtaining the data.

• 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.

• Advances in concrete construction
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• v.1 no.3
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• pp.227-237
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• 2013

Modal testing, widely accepted and applied method for determining the dynamic characteristics of structures for operational conditions, uses known or unknown vibrations in structures. The method's common applications includes estimation of dynamic characteristics and also damage detection and monitoring of structural performance. In this study, the structural identification of concrete arch dams is determined using ambient vibration tests which is one of the modal testing methods. For the purpose, several ambient vibration tests are conducted to an arch dam. Sensitive accelerometers were placed on the different points of the crest and a gallery of the dam, and signals are collected for the process. Enhanced Frequency Domain Decomposition technique is used for the extraction of natural frequencies, mode shapes and damping ratios. A total of eight natural frequencies are attained by experimentally for each test setup, which ranges between 0-12 Hz. The results obtained from each ambient vibration tests are presented and compared with each other in detail. There is a good agreement between the results for all measurements. However, the theoretical fundamental frequency of Berke Arch Dam is a little different from the experimental.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.5
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• pp.108-122
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• 2001

As bridge design is advancing toward the performance-based design. it becomes increasingly important to monitor and re-evaluate the long-term structural performance of bridges. Such information is essential in developing performance criteria for design. In this research. sensor systems for long-term structural performance monitoring have been installed on two highway bridges. Pre1iminary vibration measurement and data analysis have been performed on these instrumented bridges. On one bridge, ambient vibration data have been collected. based on which natural frequencies and mode shapes have been extracted using various methods and compared with those obtained by the preliminary finite element analysis. On the other bridge, braking and bumping vibration tests have been carried out using a water truck In addition to ambient vibration tests. Natural frequencies and mode shapes have been derived and the results by the breaking and bumping vibration tests have been compared. For the development of a three dimensional baseline finite element model, the new methodology using a neural network is proposed. The proposed one have been verified and applied to develop the baseline model of the bridge.

• Structural Engineering and Mechanics
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• v.69 no.3
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• pp.347-359
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• 2019

This paper aims to evaluate the behavior of Dorim-Goh bridge in Seoul, Korea, under static and dynamic loads effects by ambient trucks. The prestressed concrete (PSC) girders and reinforcement concrete (RC) slab of the bridge are evaluated and assessed. A short period monitoring system is designed which comprises displacement, strain and accelerometer sensors to measure the bridge performance under static and dynamic trucks loads. The statistical analysis is used to assess the static behavior of the bridge and the wavelet analysis and probabilistic using Weibull distribution are used to evaluate the frequency and reliability of the dynamic behavior of the bridge. The results show that the bridge is safe under static and dynamic loading cases. In the static evaluation, the measured neutral axis position of the girders is deviated within 5% from its theoretical position. The dynamic amplification factor of the bridge girder and slab are lower than the design value of that factor. The Weibull shape parameters are decreased, it which means that the bridge performance decreases under dynamic loads effect. The bridge girder and slab's frequencies are higher than the design values and constant under different truck speeds.

• Particle and aerosol research
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• v.14 no.4
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• pp.191-203
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• 2018

IIn this study, we have developed drying systems for reducing the error by humidity on measuring particulate matter (PM) in the ambient air with optical particle measuring instruments. Two types of drying systems were designed: drying systems using heating and dilution methods. In addition, 3 types of drying systems using a heating method were designed: Type A (1 hole), B (3 holes) and C (7 holes). After making them, the laboratory and field tests were carried out to evaluate the developed drying systems. As a result, it was shown that the PM concentrations obtained by PM monitoring devices with drying systems agree well with that of the reference devices. Therefore, it could be concluded that the drying systems can be applied to PM monitoring devices for real-time monitoring of the ambient aerosols.

• Particle and aerosol research
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• v.14 no.4
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• pp.107-119
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• 2018

In this study, we have developed a real-time monitoring device for measuring PM10 and PM2.5 of ambient aerosol particles. The real-time PM monitor (SENTRY Dust Monitor) uses the optical scattering method and has 16 channels in particle size. The laboratory and field tests were carried out to evaluate the developed SENTRY Dust Monitor. Arizona Test Dust particles were used as test particles in the laboratory test and the field test was carried out at the Jongno-gu Observatory in Seoul. The measurements of PM10 and PM2.5 concentrations obtained by SENTTRY Dust Monitor were compared with Grimm Dust Monitor (Model 1.108) and a beta ray gauge. It was shown that the PM10 and PM2.5 concentrations obtained by SENTRY Dust Monitor agree well with that of the reference devices. Based on the results obtained in this study, it could be concluded that the SENTRY Dust Monitor can be used as a PM monitoring device for real-time monitoring of the ambient aerosols.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.375-391
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• 2012

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

• Smart Structures and Systems
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• v.22 no.1
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• pp.57-70
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• 2018

For the long-term structural health monitoring of civil structures, the effect of ambient temperature variation has been regarded as one of the critical issues. In this study, a principal component analysis (PCA)-based algorithm is proposed to filter out temperature effects on electromechanical impedance (EMI) monitoring of prestressed tendon anchorages. Firstly, the EMI monitoring via a piezoelectric interface device is described for prestress-loss detection in the tendon anchorage system. Secondly, the PCA-based temperature filtering algorithm tailored to the EMI monitoring of the prestressed tendon anchorage is outlined. The proposed algorithm utilizes the damage-sensitive features obtained from sub-ranges of the EMI data to establish the PCA-based filter model. Finally, the feasibility of the PCA-based algorithm is experimentally evaluated by distinguishing temperature changes from prestress-loss events in a prestressed concrete girder. The accuracy of the prestress-loss detection results is discussed with respect to the EMI features before and after the temperature filtering.