• Wind and Structures
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• v.35 no.3
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• pp.177-191
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• 2022

Trains emerging on a streamlined bridge-girder may have salient interference effects on the aerodynamic properties of the bridge. The present paper aims at investigating these interferences by wind tunnel measurements, covering surface pressure distributions, near wake profiles, and flow visualizations. Experimental results show that the above interferences can be categorized into two primary effects, i.e., an additional angle of attack (AoA) and an enhancement in flow separation. The additional AoA effect is demonstrated by the upward-moved stagnation point of the oncoming flow, the up-shifted global symmetrical axis of flow around the bridge-girder, and the clockwise-deflected orientation of flow approaching the bridge-girder. Due to this additional AoA effect, the two critical AoAs, where flow around the bridge-girder transits from trailing-edge vortex shedding (TEVS) to impinging leading-edge vortices (ILEV) and from ILEV to leading-edge vortex shedding (LEVS) of the bridge-girder are increased by 4° with respect to the same bridge-girder without trains. On the other hand, the underlying flow physics of the enhancement in flow separation is the large-scale vortices shedding from trains instead of TEVS, ILEV, and LEVS governed the upper half bridge-girder without trains in different ranges of AoA. Because of this enhancement, the mean lift and moment force coefficients, all the three fluctuating force coefficients (drag, lift, and moment), and the aerodynamic span-wise correlation of the bridge-girder are more significant than those without trains.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Smart Structures and Systems
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• v.29 no.1
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• pp.77-91
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• 2022

Various monitoring systems have been implemented in civil infrastructure to ensure structural safety and integrity. In long-term monitoring, these systems generate a large amount of data, where anomalies are not unusual and can pose unique challenges for structural health monitoring applications, such as system identification and damage detection. Therefore, developing efficient techniques is quite essential to recognize the anomalies in monitoring data. In this study, several machine learning techniques are explored and implemented to detect and classify various types of data anomalies. A field dataset, which consists of one month long acceleration data obtained from a long-span cable-stayed bridge in China, is employed to examine the machine learning techniques for automated data anomaly detection. These techniques include the statistic-based pattern recognition network, spectrogram-based convolutional neural network, image-based time history convolutional neural network, image-based time-frequency hybrid convolution neural network (GoogLeNet), and proposed ensemble neural network model. The ensemble model deliberately combines different machine learning models to enhance anomaly classification performance. The results show that all these techniques can successfully detect and classify six types of data anomalies (i.e., missing, minor, outlier, square, trend, drift). Moreover, both image-based time history convolutional neural network and GoogLeNet are further investigated for the capability of autonomous online anomaly classification and found to effectively classify anomalies with decent performance. As seen in comparison with accuracy, the proposed ensemble neural network model outperforms the other three machine learning techniques. This study also evaluates the proposed ensemble neural network model to a blind test dataset. As found in the results, this ensemble model is effective for data anomaly detection and applicable for the signal characteristics changing over time.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.913-916
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• 2010

Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors send data from CH (Cluster Head) and then to BS (Base Station). BCDCP works well in small-scale network but in large scale network it is not appropriated since it uses much energy for long distance wireless communication. We propose a routing protocol - Triangular Clustering Routing Protocol (TCRP) - to prolong network life time through the balanced energy consumption. TCRP selects cluster head of triangular shape. The sensor field is divided into energy level and in every level we choose one node as a gate node. This gate node collects data and sends it to the leader node. Finally the leader node sends the aggregated data to the BS. We show TCRP outperforms BCDCP with several experiments.

• Journal of Practical Agriculture & Fisheries Research
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• v.9 no.1
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• pp.13-25
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• 2007

The present study analyzed the spatial characteristics of S village according to the Feng-Shui theory(風水理論). People's life span is affected by several factors including hereditary constitution, dietary life and life habits but recently there is an opinion that longevity village in Korea are commonly located in areas at a proper altitude. The objective of the present study was to basic investigate the characteristics of S village from the viewpoint of Feng-Shui(風水). As for this study, it will be given help to a longevity village plan. For this purpose, we conducted field survey and map investigation of the natural geographic situation of S village focused on Ryong(龍, contiguous line of terrestrial stratum), Hull(穴, village location), Sa(砂, geographical feature of surrounding mountains), Su(水, water flow) and Hyang(向), which are Feng-Shui(風水) objects to be observed. According to the result of this research, S Village, which has mountains in the rear and a river in the front, was found to be in fine geographic situation equipped with Sashinsa(四神砂). According to the Feng-Shui theory(風水理論), the village was hang-ju-hyoung(行舟形), which means that people and properties flourish together. A shortcoming of the village was the absence of Ahnsan(案山) to block harmful winds blowing to the fore of the village. In addition, another shortcoming of the village in terms of Feng-Shui(風水) was the large variation of temperature because of its location surrounded by high mountains as if the village was situated inside a bowl. The Hyang(向) of village houses were arranged by the geographical feature and not by Feng-Shui(風水).

• Structural Monitoring and Maintenance
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• v.10 no.1
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• pp.1-23
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• 2023

Various efforts have been made to reduce the weight of concrete slabs while preserving their flexural strength. This will result in reducing deflection and allows the utilization of longer spans. The top zone of the slab requires concrete to create the compression block for flexural strength, and the tension zone needs concrete to join with reinforcing for flexural strength. Also, the top and bottom slab faces must be linked to transmit stresses. Voided slab systems were and are still used to make long-span slab buildings lighter. Eight slab specimens of (1000^*1000 (1000^*1000 mm²) were cast and tested as two-way simply supported slabs in this research. The tested specimens consist of one solid slab and seven voided slabs with the following variables (type of slab solid and voided), thickness of slab (100 and 125 mm), presence of steel fibers (0% and 1%), and the number of GFRP layers). The voids in slabs were made using high-density polystyrene of dimensions (200^*200^*50 mm) with a central hole of dimensions (50^*50^*50 mm) at the ineffective concrete zones to give a reduction in weight by (34% to 38%). The slabs were tested as simply supported slabs under partial uniform loading. The results of specimens subjected to monotonic loading show that the combined strengthening by steel fibers and GFRP sheets of the concrete specimen (V-125-2GF-1%) shows the least deflection, deflection (4.6 mm), good ultimate loading capacity (192 MPa), large stiffness at cracking and at ultimate (57 and 41.74) respectively, more ductility (1.44), and high energy absorption (1344.83 kN.mm); so it's the best specimen that can be used as a voided slab under this type of loading.

• Analytical Science and Technology
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• v.19 no.1
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• pp.18-30
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• 2006

This paper describes the cumulative deposition of fallout Pu in soil and lichen at the present time and give the characteristics of fallout Pu deposits in the soil. In the soil of the forest, the accumulated depositions of $^{239,240}Pu$ were estimated to be in the range of 34.0 to $101.2Bq\;m^{-2}$ with an average value of $65.3{\pm}21.6Bq\;m^{-2}$. The average inventory of $^{239,240}Pu$ in the forest was calculated to be two times higher than that in the hill. Also, the deposited activities of $^{239,240}Pu$ in cultivated soil were significantly lower than those in the hill or forest. However, the cumulative depositions of fallout Pu in the volcanic ash soil on Cheju Island were much higher than those in the forest and hill soils. The measured activity concentrations of Pu isotopes in lichens and mosses showed large variations, due to characteristics of species and life span of lichen and moss colonies. From depth profiles, it was found that most of the fallout Pu has been accumulated in upper 10 cm layer of soil. Except for a few cases, the concentrations of $^{239,240}Pu$ in soil tended to decrease exponentially with increasing soil depth. Among parameters affecting the cumulative deposition of fallout Pu, organic substances and rainfall play an important role in the retention and relative mobility of fallout Pu in the soil. However, pH showed a weak correlation with the deposition of fallout Pu in the soil. From sequential leaching experiments, Pu was found to be associated predominantly with the "organic" and "oxy-hydroxy" fractions. Both the activity ratios of $^{238}Pu/^{239,240}Pu$ and $^{241}Pu/^{239,240}Pu$ in soils, lichens and mosses and the atomic ratios of $^{240}Pu/^{239}Pu$ in soils are close to those observed in the cumulative deposit global fallout from nuclear weapon testings. The results obtained from this research make it possible to interpret and predict the behavior of fallout Pu under natural conditions.

• Smart Structures and Systems
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• v.30 no.5
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• pp.479-500
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• 2022

In this study, a new type of isolation bearing is proposed by combining S-shaped steel plate dampers (SSDs) with a spherical steel bearing, and the seismic control effect of a five-span standard high-speed railway bridge is investigated. The advantages of the proposed S-shaped steel damping friction bearing (SSDFB) are that it cannot only lengthen the structural periods, dissipate the seismic energy, but also prevent bridge unseating due to the restraint effectiveness of SSDs in the large relative displacements between the girders and piers. This study first presents a detailed description and working principle of the SSDFB. Then, mechanical modeling of the SSDFB was derived to fundamentally define its cyclic behavior and obtain key mechanical parameters. The numerical model of the SSDFB's critical component SSD was verified by comparing it with the experimental results. After that, parameter studies of the dimensions and number of SSDs, the friction coefficient, and the gap length of the SSDFBs were conducted. Finally, the longitudinal seismic responses of the bridge with SSDFBs were compared with the bridge with spherical bearing and spherical bearing with strengthened shear keys. The results showed that the SSDFB can not only significantly mitigate the shear force responses and residual displacement in bridge substructures but also can effectively reduce girder displacement and prevent bridge unseating, at a cost of inelastic deformation of the SSDs, which is easy to replace. In conclusion, the SSDFB is expected to be a cost-effective option with both multi-stage energy dissipation and restraint capacity, making it particularly suitable for seismic isolation application to high-speed railway bridges.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.91-97
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• 2023

Aging construction machinery and vehicles with old diesel engines usually have a long life span, so they continue to emit harmful emissions. Therefore, replacing these older diesel engines with engines that meet the latest emisstion standard is expected to help improve air quality, and engines with propane fuels, which are easily available at construction sites, can be an appropriate alternative. In this study, a propane fueled engine was developed based on a 6.8-liter CNG engine, and technologies such as gas injectors, exhaust gas recirculation (EGR), and enhanced catalysts were applied. As a result, nitrogen oxides achieved half of the emission performance at the Stage-V level, the latest emission standard, while securing diesel engine output and torque in the same class.

• Computers and Concrete
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• v.33 no.3
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• pp.251-264
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• 2024

The present study pertains to the effects of variations in the location and size of drilled web openings on the behavior of fixed-fixed reinforced concrete (RC) beams. For this purpose, a reference bending beam with a transverse opening in each half span was tested to failure. Later, the same beam was modeled and analyzed with the help of finite element software using ABAQUS. Upon achieving close agreement between the experimental and numerical results, the location and size of the web opening were altered to uncover the effects of these factors on the shear strength and load-deflection behavior of RC beams. The experimental failure mode of the tested beam and the numerical results were also verified by theoretical calculations. In numerical analysis, when compared to the reference (D0) specimen, if the distance of the opening center from the support is 0 or h or 2h, reduction in load-bearing capacity of 1.5%-22.8% or 2.0%-11.3% or is 4.1%-40.7%. In other words, both the numerical analyses and theoretical calculations indicated that the beam behavior shifted from shear-controlled to flexure-controlled as the openings approached the supports. Furthermore, the deformation capacities, energy absorption values, and the ductilities of the beams with different opening diameters also increased with the decreasing distance of the opening from supports. Web compression failure was shown to be the predominant mode of failure of beams with large diameters due to the lack of sufficient material in the diagonal compression strut of the beam. The present study indicated that transverse openings with diameters, not exceeding about 1/3 of the entire beam depth, do not cause the premature shear failure of RC beams. Finally, shear damage should be prevented by placing special reinforcements in the areas where such gaps are opened.