• 대한한방소아과학회지
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• 제27권3호
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• pp.29-40
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• 2013

Objectives The purpose of this study is to evaluate the effect of hot spring bath in obese children. Methods The study was conducted with 20 obese children whose BMI were over 20 ($kg/m^2$). The hot spring bath program was performed in the hot-spring facilities with temperature of $32{\sim}36^{\circ}C$. The children bathed four times from June to July, 2012. Prior to their bath, their heights, weights, and body compositions were measured every time. They were also confirmed their obesity index and obesity degree during the program. Results After the bathing program, degree of obesity has changed, three obesity judgment index (BMI, RI and OI) of the children have decreased (BMI, RI, OI on the $1^{st}$ day: $25.99{\pm}3.47$, $177.63{\pm}17.43$, $37.74{\pm}13.42$; on the $4^{th}$ day: $25.06{\pm}3.08$, $168.4{\pm}14.8$, $30.60{\pm}12.12$), so have body fat mass and percent body fat (BFM, PBF on the $1^{st}$ day: $21.83{\pm}7.03$, $38.24{\pm}3.36$; on the $4^{th}$ day:$19.55{\pm}6.35$, $34.20{\pm}3.77$), but skeletal muscle mass has increased (SMM on the $1^{st}$ day: $18.37{\pm}4.24$ ; on the $4^{th}$ day: $19.80{\pm}4.44$). Conclusions This study shows that hot spring bath could be an effective way of managing and treating obesity.

• Structural Monitoring and Maintenance
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• 제1권2호
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• pp.183-195
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• 2014

Scour is one of the leading causes of overwater bridge failures worldwide. While monitoring systems have already been implemented or are still being developed, they suffer from limitations such as high costs, inaccuracies, and low reliability, among others. Also, most sensors only measure scour depth at one location and near the pier. Thus, the objective is to design a simple, low cost, scour hole topography monitoring system that could better characterize the entire depth, shape, and size of bridge scour holes. The design is based on burying a robust, waterproofed, piezoelectric sensor strip in the streambed. When scour erodes sediments to expose the sensor, flowing water excites it to cause the generation of time-varying voltage signals. An algorithm then takes the time-domain data and maps it to the frequency-domain for identifying the sensor's resonant frequency, which is used for calculating the exposed sensor length or scour depth. Here, three different sets of tests were conducted to validate this new technique. First, a single sensor was tested in ambient air, and its exposed length was varied. Upon verifying the sensing concept, a waterproofed prototype was buried in soil and tested in a tank filled with water. Sensor performance was characterized as soil was manually eroded away, which simulated various scour depths. The results confirmed that sensor resonant frequencies decreased with increasing scour depths. Finally, a network of 11 sensors was configured to form a distributed monitoring system in the lab. Their exposed lengths were adjusted to simulate scour hole formation and evolution. Results showed promise that the proposed sensing system could be scaled up and used for bridge scour topography monitoring.

• Structural Monitoring and Maintenance
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• 제4권1호
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• pp.17-31
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• 2017

Since extensometers are used to determine the absolute deformation of foundation and abutments and all results are obtained in reference to the base rod, the accuracy of these results has been constantly a subject of debate. In this regard, locating and installing extensometers outside the range of effect zone is also another challenge. The main purpose of this paper is to investigate and modify extensometers results based on the mentioned issues. For this aim, the concrete RCC Zhaveh dam in Iran was selected as the case study. To study the results of extensometers installed in this dam, first, the 3DEC_DP 5.00 software was applied for numerical modeling. Parameters such as discontinuities, dead load and piezometric pressure in the interface of concrete and rock were considered. Next, using the results obtained from 6 extensometers in foundation and abutments and 4 clinometers in dam body, the numerical model was calibrated through back analysis method. The results indicate that the base rod is moved and is not recommended being used as the base point. In other words, because installation of base anchor outside the range of effect zone is not possible due to the operational and economic considerations, the obtained results are not accurate enough. The results indicate a considerable 2-3 mm displacement of the base rod (location of the base anchor) in reference to the real zero point location, which must be added to the base rod results.

• Structural Monitoring and Maintenance
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• 제1권3호
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• pp.249-271
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• 2014

This paper presents a unique study of Structural Health Monitoring (SHM) for the maintenance decision making about a real life movable bridge. The mechanical components of movable bridges are maintained on a scheduled basis. However, it is desired to have a condition-based maintenance by taking advantage of SHM. The main objective is to track the operation of a gearbox and a rack-pinion/open gear assembly, which are critical parts of bascule type movable bridges. Maintenance needs that may lead to major damage to these components needs to be identified and diagnosed timely since an early detection of faults may help avoid unexpected bridge closures or costly repairs. The fault prediction of the gearbox and rack-pinion/open gear is carried out using two types of Artificial Neural Networks (ANNs): 1) Multi-Layer Perceptron Neural Networks (MLP-NNs) and 2) Fuzzy Neural Networks (FNNs). Monitoring data is collected during regular opening and closing of the bridge as well as during artificially induced reversible damage conditions. Several statistical parameters are extracted from the time-domain vibration signals as characteristic features to be fed to the ANNs for constructing the MLP-NNs and FNNs independently. The required training and testing sets are obtained by processing the acceleration data for both damaged and undamaged condition of the aforementioned mechanical components. The performances of the developed ANNs are first evaluated using unseen test sets. Second, the selected networks are used for long-term condition evaluation of the rack-pinion/open gear of the movable bridge. It is shown that the vibration monitoring data with selected statistical parameters and particular network architectures give successful results to predict the undamaged and damaged condition of the bridge. It is also observed that the MLP-NNs performed better than the FNNs in the presented case. The successful results indicate that ANNs are promising tools for maintenance monitoring of movable bridge components and it is also shown that the ANN results can be employed in simple approach for day-to-day operation and maintenance of movable bridges.

• Structural Monitoring and Maintenance
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• 제1권1호
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• pp.131-157
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• 2014

Special track systems used to divert a train to other directions or other tracks are generally called 'railway turnout'. A traditional turnout system consists of steel rails, switches, crossings, steel plates, fasteners, screw spikes, timber bearers, ballast and formation. The wheel rail contact over the crossing transfer zone has a dip-like shape and can often cause detrimental impact loads on the railway track and its components. The large impact also emits disturbing noises (either impact or ground-borne noise) to railway neighbors. In a brown-field railway track where an existing aged infrastructure requires renewal or maintenance, some physical constraints and construction complexities may dominate the choice of track forms or certain components. With the difficulty to seek for high-quality timbers with dimensional stability, a methodology to replace aged timber bearers in harsh dynamic environments is to adopt an alternative material that could mimic responses and characteristics of timber in both static and dynamic loading conditions. A critical review has suggested an application of an alternative material called fibre-reinforced foamed urethane (FFU). The full-scale capacity design makes use of its comparable engineering characteristics to timber, high-impact attenuation, high damping property, and a longer service life. A field trial to investigate in-situ behaviours of a turnout grillage system using an alternative material, 'fibre-reinforced foamed urethane (FFU)' bearers, has been carried out at a complex turnout junction under heavy mixed traffics at Hornsby, New South Wales, Australia. The turnout junction was renewed using the FFU bearers altogether with new special track components. Influences of the FFU bearers on track geometry (recorded by track inspection vehicle 'AK Car'), track settlement (based on survey data), track dynamics, and acoustic characteristics have been measured. Operational train pass-by measurements have been analysed to evaluate the effectiveness of the replacement methodology. Comparative studies show that the use of FFU bearers generates higher rail and sleeper accelerations but the damping capacity of the FFU help suppress vibration transferring onto other track components. The survey data analysis suggests a small vertical settlement and negligible lateral movement of the turnout system. The static and dynamic behaviours of FFU bearers appear to equate that of natural timber but its service life is superior.

• 한국미생물·생명공학회지
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• 제17권3호
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• pp.213-218
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• 1989

Cloning을 위한 host와 vector의 이용 가능성을 타진하기 위해 호알칼리성 Bacillus속 K-17을 host로, pUB110과 pBD64를 vector로 사용하여 Bacillus속 K-17의 protoplast 형질전환조건을 검토하였다. 원형질체의 형성은 200$\mu\textrm{g}$/$m\ell$의 Iysozyme 을 처리하였으며, 원형질체 형성의 최적 온도, PH및 배양시간은 각각 4$0^{\circ}C$, 7.0 및 4시간으로 나타났다. 원형질체는 DM3 재생배지에서 재생시켰으며 0.8% agar, 0.5M sodium succinate 농도에서 가장재생이 좋았다. 형질전환시 PEG의 농도는 40%(w/v) PEG 6,000 30%(v/v)가 최적으로 나타났다. 형질전환체의 특성을 조사한 결과, plasmid 안정성은 pUB110이 pBD64보다 더 안정하였으며, 최대 효소활성은 비슷하였지만 효소 분비시간은 pUB110 은 2.5일, pBD64의 경우는 3일로 Bacillus속 K-17의 2일에 비해 약간 지연되었다.

• Structural Monitoring and Maintenance
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• 제2권4호
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• pp.319-338
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• 2015

The electro-mechanical impedance (EMI) technique makes use of surface-bonded lead zirconate titanate (PZT) patches as impedance transducers measuring impedance variations monitored on host structural components. The present experimental work further evaluate an alternative to the conventional EMI technique which performs measurements of the variations in the output voltage of PZT transducers rather than computing electromechanical impedance (or admittance) itself. This paper further evaluates a variant of the EMI approach presented in a previous work of the present authors, suitable, for low-cost concrete structures monitoring applications making use of a credit card-sized Raspberry Pi single board computer as core hardware unit. This monitoring approach is also deployed by introducing a new damage identification index based on the ratio between the area of the 2-D error ellipse of specific probability of EMI-based measurements containment over that of the 2-D error circle of equivalent probability. Experimental results of damages occurring in concrete cubic and beam specimens are investigated under increasing loading conditions. Results illustrate that the proposed technique is an efficient approach for identification and early detection of damage in concrete structures.

• Structural Monitoring and Maintenance
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• 제6권4호
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• Structural Monitoring and Maintenance
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• 제6권4호
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• pp.365-387
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• 2019

This study aims to provide useful information on the fatigue assessment of a top-tensioned riser (TTR) subjected to vortex-induced vibration (VIV) by performing parametric study. The effects of principal design parameters, i.e., riser diameter, wall thickness, water depth (related to riser length), top tension, current velocity, and shear rate (or shear profile of current) are investigated. To prepare the base model of TTR for parametric studies, three (3) riser modelling techniques in the OrcaFlex were investigated and validated against a reference model by Knardahl (2012). The selected riser model was used to perform parametric studies to investigate the effects of design parameters on the VIV fatigue damage of TTR. From the obtained comparison results of VIV analysis, it was demonstrated that a model with a single line model ending at the lower flex joint (LFJ) and pinned connection with finite rotation stiffness to simulate the LFJ properties at the bottom end of the line model produced acceptable prediction. Moreover, it was suitable for VIV analysis purposes. Findings from parametric studies showed that VIV fatigue damage increased with increasing current velocity, riser outer diameter and water depth, and decreased with increasing shear rate and top tension of riser. With regard to the effects of wall thickness, it was not significant to VIV fatigue damage of TTR. The detailed outcomes were documented with parametric study results.

• Smart Structures and Systems
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• 제24권5호
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.