• Structural Monitoring and Maintenance
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• v.7 no.3
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.

• Structural Monitoring and Maintenance
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• v.7 no.3
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• pp.233-259
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• 2020

Using bonded fiber-reinforced polymer laminates for strengthening wooden structural members has been shown to be an effective and economical method. In this research, properties of suitable composite materials (sika wrap), adhesives and two ways of strengthening beams exposed to bending moment are presented. Passive or slack reinforcement is one way of strengthening. The most effective way of such a strengthening was to place reinforcement laminates in the stretched part of the wooden beam (lower part in our case), in order to investigate the effectiveness of externally bonding FRP to their soffits. The model is based on equilibrium and deformations compatibility requirements in and all parts of the strengthened beam, i.e., the wooden beam, the sika wrap composite plate and the adhesive layer. The theoretical predictions are compared with other existing solutions. This research is helpful for the understanding on mechanical behaviour of the interface and design of the composite-wooden hybrid structures. The results showed that the use of the new strengthening system enhances the performance of the wooden beam when compared with the traditional strengthening system.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.357-369
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• 2014

In the existing bridge management systems, assessment of the structural behavior is based on the results of visual inspections in which corresponding condition states are assigned to individual elements. In this process, limited attention is given to the correlation between bridge elements from structural perspective. Also, the uncertainty of parameters which affect the structural capacity is ignored. A system reliability-based assessment model is potentially an appropriate replacement for the existing procedures. The aim of this research is to evaluate the system reliability of existing conventional Steel-Reinforced bridge decks over time. The developed method utilizes the reliability theory and evaluates the structural safety for such bridges based on their failure mechanisms. System reliability analysis has been applied to simply-supported concrete bridge superstructures designed according to the Canadian Highway Bridge Design Code (CHBDC-S6) and the deterioration pattern is achieved based on the reliability estimates. Finally, the bridge condition index of an old existing bridge in Montreal has been estimated using the developed deterioration pattern. The results obtained from the developed reliability-based deterioration model and from the evaluation done by bridge engineers have been found to be in accordance.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.313-323
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• 2018

The presence of water inside concrete structures is an essential condition for the deterioration of the structures. The free water in the concrete pores and micro-cracks is the culprit for the durability related problems, such as alkali-aggregate reaction, carbonation, freeze-thaw damage, and corrosion of steel reinforcement. To ensure the integrity and safe operation of the concrete structures, it is very important to monitor water seepage inside the concrete. This paper presents the experimental investigation of water seepage monitoring in a concrete slab using piezoelectric-based smart aggregates. In the experimental setup, an $800mm{\times}800mm{\times}100mm$ concrete slab was fabricated with 15 SAs distributed inside the slab. The water seepage process was monitored through interrogating the SA pairs. In each SA pair, one SA was used as actuator to emit harmonic sine wave, and the other was used as sensor to receive the transmitted stress wave. The amplitudes of the received signals were able to indicate the water seepage process inside the concrete slab.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.273-295
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• 2018

In this study, an investigation of a damage detection methodology for global condition assessment is presented. A particular emphasis is put on the utilization of wireless sensors for more practical, less time consuming, less expensive and safer monitoring and eventually maintenance purposes. Wireless sensors are deployed with a sensor roving technique to maintain a dense sensor field yet requiring fewer sensors. The time series analysis method called ARX models (Auto-Regressive models with eXogeneous input) for different sensor clusters is implemented for the exploration of artificially induced damage and their locations. The performance of the technique is verified by making use of the data sets acquired from a 4-span bridge-type steel structure in a controlled laboratory environment. In that, the free response vibration data of the structure for a specific sensor cluster is measured by both wired and wireless sensors and the acceleration output of each sensor is used as an input to ARX model to estimate the response of the reference channel of that cluster. Using both data types, the ARX based time series analysis method is shown to be effective for damage detection and localization along with the interpretations and conclusions.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.243-260
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• 2018

Detection of damages in fibre reinforced plastic (FRP) composite structures is important from the safety and serviceability point of view. Usually, damage is realized as a local reduction of stiffness and if dynamic responses of the structure are sensitive enough to such changes in stiffness, then a well posed inverse problem can provide an efficient solution to the damage detection problem. Usually, such inverse problems are solved within the framework of pattern recognition. Support Vector Machine (SVM) Algorithm is one such methodology, which minimizes the weighted differences between the experimentally observed dynamic responses and those computed using the finite element model- by optimizing appropriately chosen parameters, such as stiffness. A damage detection strategy is hereby proposed using SVM which perform stepwise by first locating and then determining the severity of the damage. The SVM algorithm uses simulations of only a limited number of damage scenarios and trains the algorithm in such a way so as to detect damages at unknown locations by recognizing the pattern of changes in dynamic responses. A rectangular fiber reinforced plastic composite plate has been investigated both numerically and experimentally to observe the efficiency of the SVM algorithm for damage detection. Experimentally determined modal responses, such as natural frequencies and mode shapes are used as observable parameters. The results are encouraging since a high percentage of damage cases have been successfully determined using the proposed algorithm.

• Structural Monitoring and Maintenance
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• v.7 no.1
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• pp.1-12
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• 2020

Railway tracks are the direct supporting structures of the trains, which are vulnerable to produce large deformation under the temperature stress or subgrade settlement. The health status of track is critical, and the track should be routinely monitored to improve safety, lower the risk of excess deformation and provide reliable maintenance strategy. In this paper, the distributed optical fiber sensor was proposed to monitor the continuous deformation of the track. In order to validate the feasibility of the monitoring method, two deformation monitoring tests on one steel rail model in laboratory and on one real railway tack in outdoor were conducted respectively. In the model test, the working conditions of simply supported beam and continuous beam in the rail model under several concentrated loads were set to simulate different stress conditions of the real rail, respectively. In order to evaluate the monitoring accuracy, one distributed optical fiber sensor and one fiber Bragg grating (FBG) sensor were installed on the lower surface of the rail model, the strain measured by FBG sensor and the strain calculated from FEA were taken as measurement references. The model test results show that the strain measured by distributed optical fiber sensor has a good agreement with those measured by FBG sensor and FEA. In the outdoor test, the real track suffered from displacement and temperature loads. The distributed optical fiber sensor installed on the rail can monitor the corresponding strain and temperature with a good accuracy.

• Structural Monitoring and Maintenance
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• v.7 no.1
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• pp.13-25
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• 2020

One of the most important aspects in structural health monitoring is the detection of fatigue damage. Structural components such as heavy-duty bolts work under high dynamic loads, and thus are prone to accumulate fatigue damage and cracks may originate. Those heavy-duty bolts are used, for example, in wind power generation and mining equipment. Therefore, the investigation of new and more effective monitoring technologies attracts a great interest. In this study the acoustic emission (AE) technology was employed to detect incipient damage during fatigue testing of a M36 bolt. Initial results showed that the AE signals have a high level of background noise due to how the load is applied by the fatigue testing machine. Thus, an advanced signal processing method in the time-frequency domain, the Hilbert-Huang Spectrum (HHS), was applied to reveal AE components buried in background noise in form of high-frequency peaks that can be associated with damage progression. Accordingly, the main contribution of the present study is providing insights regarding the detection of incipient damage during fatigue testing using AE signals and providing recommendations for further research.

• Microbiology and Biotechnology Letters
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• v.23 no.2
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• pp.156-163
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• 1995

Bacillus sphaericus 1593 is pathogenic to the larvae of a number of mosquito species that are known as important vectors for the transmission of certain human and animal diseases. As a preliminary experiment for developing a multfunctional B. sphaericus 1593 as a potent antagonist, we investigated the conditions for the protoplast transformation system of B. sphaericus 1593 using the plasmid pGB215-110$\Delta$B. The protoplast of B. sphaericus 1593 were obtained most efficiency by treating the cells with 500 $\mu$g/ml of lysozyme in the SMM buffer containing 0.5 M sucrose at pH 8.0 and 40$\circ$C for 60 minutes. The cell wall was regenerated on the plate containing 1.2% agar and 0.8 M mannitol. Under the best condition for protoplast formation and regeneration established in the work the highest frequency of transformation was achieved with the 40% PEG (M.W 4,000) treatment for 15 minutes of incubation at 4$\circ$C, and subsequently for 120 minutes incubation at 30$\circ$C for phenotypic expression. The highest transformation efficiency were observed at 1.0 $\mu$g/ml of the final concentration of the plasmid DNA and the plasmids were found to be fairly stable since about 70% of the plasmids were maintained after 8 successive daily transfers onto the fresh medium.

• Korean Journal of Veterinary Service
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• v.18 no.3
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• pp.13-28
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• 1995

This study was carried out to explore the most sensitive and useful method for simultaneous determination of five sulfa drugs(sulfamethazine, sulfamerazine, sulfamonomethoxine, sulfadimethoxine, sulfaquinoxaline) in livestock productions(pork muscle, bovine muscle, chicken muscle, milk ) by HPLC with UV detector and reverse phase column. The results obtained were as follows：1. For mobile phase acetonitrile-0.01M ammonium acetate (23：77) showed more applicable sensitivity and retention times than acetonitrile-1% acetic acid(23：77). Thus acetonitrile-0.01M ammonium acetate(23：77) selected and applied to the modification test, from which it was found pH 6.75 was the most adequate. 2. Optimal wavelength of UV for SMT(sulfamethazine), SMR(sulfamerazine), SMM(sulfamonomethoxine), SD(sulfadimethoxine), and SQ(sulfaquinoxaline) were 266, 266, 265, 269 and 250nm, respectively, and that for simultaneous application it was 263nm. 3. The average recovery rate by extractant(chloroform, dichloromethane, chlorform+dich-loromethane) in the classic method was not significantly different(p>0.05) but that by chloroform higher than the others. Thus chloroform was found to be adequate as extractant in this classic method. 4. The average recovery rate was 86.5% by the MSPD(matrix solid phase disperse) method, which was significantly higher than that by the classic method(p<0.05). Also the recovery rates by method were significantly different(p<0.05) in accordance with sample and type of drug. The MSPD method was much superior to classic method on clean-up.