• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2234-2241
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• 2015

This study has been undertaken to develop a relationship between the shear strength coefficients and the cone index. The theoretic mathematical equations for the relationship were rigorously investigated, and then a Artificial Neural Network(ANN) analysis was adapted to enhance the reliability of the investigation. The theoretical investigation involved various assumptions resulting in the significant error involvement of geotechnical behaviors of ground. Therefore, a model using the ANN has been learned to enhance the prediction of the cone index form the shear strength parameters. Site investigation reports from various construction fields were used for ANN model learning. The results of the study show that the model predicts the cone index from the shear strength parameters of soils very well. The further study that is undertaking has a potential promise of the generalized prediction technique for the cone index from the soil parameters.

• The Journal of Advanced Prosthodontics
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• v.10 no.4
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• pp.308-314
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• 2018

PURPOSE. Plasma activation of hydrophobic zirconia surfaces might be suitable to improve the bond strength of luting materials. The aim of this study was to analyze the influence of nonthermal argon-plasma on the shear bond strength (SBS) between zirconia and different combinations of 10-MDP adhesive systems and luting composites after artificial aging. MATERIALS AND METHODS. Two hundred forty Y-TZP specimens were ground automatically with $165{\mu}m$ grit and water cooling. Half of the specimens received surface activation with nonthermal argon-plasma. The specimens were evenly distributed into three groups according to the adhesive systems ([Futurabond U, Futurabond M, Futurabond M + DCA], VOCO GmbH, Germany, Cuxhaven) and into further two subgroups according to the luting materials ([Bifix SE, Bifix QM], VOCO GmbH). Each specimen underwent artificial aging by thermocycling and water storage. SBS was measured in a universal testing machine. Statistical analysis was performed using ANOVA and $Scheff{\grave{e}}$ procedure with the level of significance set to 0.05. RESULTS. Surface activation with nonthermal plasma did not improve the bond strength between zirconia and the tested combinations of adhesive systems and luting materials. The plasma-activation trended to reveal higher bond strength if the self-etch luting material (Bifix SE) was used, irrespective of the adhesive system. CONCLUSION. Plasma-activation seems to be suitable to improve bond strength between zirconia and self-etch resin materials. However, further research is necessary to identify the influence of varying plasma-parameters.

• Atmosphere
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• v.26 no.3
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• pp.423-433
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• 2016

In this study, performance of a computational fluid dynamics (CFD) model is assessed from analysis on air flow pattern which is observed in the artificial street canyon. Field observations focusing on flows were conducted at an artificial street canyon in Magok region. For the observation of three-dimensional airflow structures, twelve three-dimensional wind anemometers (hereafter, CSAT3) were installed inside the street canyon. The street canyon was composed of two rectangular buildings with 35-m length, 4-m width, and 7-m height. The street width (distance between the buildings) is 7 m, making the street aspect ratio (defined by the ratio of building height to street width) of 1. For the observation of above-building wind, a CSAT3 was installed above the northwest-side building. Southwesterly, westerly and northwesterly were dominant in the street canyon during the observations. Because wind direction is parallel to the street canyon in the southwesterly case, westerly and northwesterly were selected as inflow directions in numerical simulations using a computational fluid dynamics model developed through the collaborative research project between National Institute of Meteorological Sciences and Seoul National University (CFD_NIMR_SNU). The observations showed that a well-structured vortex flow (skimming flow) and an evidence of a small eddy at the corner of the downwind building and ground appeared. The CFD_NIMR_SNU reproduced both the observed flow patterns reasonably well, although wind speeds inside the street canyon were underestimated.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.1
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• pp.21-27
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• 2008

Triangular structure is used as basic shape of artificial structures for generating the upwelling current in order to make rich fishing ground at sea. Artificial upwelling current could bring the deep sea water containing a lot of nutrients from the bottom up to the surface. The purpose of this study is to examine the flow characteristics around underwater triangular structure with various stratification parameter. An experimental study was carried out for the triangular structure model in the circulating water channel to investigate flow characteristics by flow visualization method. A velocity fields around the underwater structure were measured by particle image velocimetry(PIV). The experimental results showed that the upwelling effect at the back and upper region of the structure could be best when the water depth was 2 times of the structure height and the stratification parameter was approximately 3.0. These quantitative data will be useful to determine the functional efficiency cf artificial upwelling structures.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09b
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• pp.21-31
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• 2010

Although it is important to reflect the accurate information of the ground condition in the tunnel design, the analysis and design are conducted by limited information because it is very difficult to get it practically on considering various geography and geotechnical condition. So construction management of information concept is required to manage immediately on the field condition because it is very time-consuming to establish the countermeasure of underground reinforcement and the pattern change of Bo. Therefore, when construction is on tunnel area, examination of accurate safety and prediction of behavior is performed to overcomes the limit of predicting behavior by using Artificial Neural Network(ANN) in this study. Firstly, the field data was secured. Secondly, suitable structure was made on multi-layer perceptrons among the ANN. Thirdly, learning algorithm-propagated applies to ANN. The data for the learn of field application using ANN was used by considering impact factors, which influenced the behavior of tunnel, and performing credibility analysis. crown displacement, spring displacement, subsurfacement, and rock bolt axial force are predicted at the tunnel construction and on-site application was confirmed by using ANN from analyzing and comparing with measurement value of on-site. In this study, the data from Seoul Highway $\bigcirc\bigcirc$ tunnel section was applied to the ANN Theory, and the analysis on the investigate value and the reasoning for the value associated with field application was performed.

• Journal of the Korea Concrete Institute
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• v.13 no.2
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• pp.175-183
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• 2001

Immersion tests with artificial seawater were carried out to investigate the resistance to seawater attack of 5 types of cement matrices. From the results of compressive strength and length change, it was found that blended cement mortars due to mineral admixtures, were superior to portland cement mortars with respect to the resistance to seawater attack. Moreover, XRD analysis indicated that the peak intensity ratio of low heat portland cement(LHC) paste, in portland cement pastes, had better results, and so did that of blended cement Paste. Pore volume of pastes by mercury intrusion porosimetry method demonstrated that total pore volume of ordinary portland cement(OPC) paste had a remarkable increase comparing with that of other pastes. In case of immersion of artificial seawater, the use of ground granulated blast-furnace slag and fly ash, however, showed the beneficial effects of 56% and 32% in reduction of total pore volume, respectively.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.1 no.1
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• pp.141-150
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• 1998

This study was conducted to find out the possibility of seeding of Zoysia japonica and woody plants for the revegetation of rock-exposed-cutslopes by Natural Topsoil Restoration Methods (NTRM). The 5cm thick layer of artificial soil was attached at rock-exposed cutslopes for the growth of Zoysia japonica and native woody plants by NTRM. The main results were summarized as follows. 1. Artificial soil attached at rock-exposed-slopes by NTRM was not eroded until recovered by Zoysia japonica and native woody plants. It shows extremely low soil erodibility. 2. One year later after seeding, woody plants show 100% ground coverage. But, in early stage, they grew more quickly at northwest slopes than at southeast slopes. 3. In seeding of Zoysia japonica, it grew more quickly at southeast slopes than at northwest slopes. Also, it grew better at lower part of the slopes than at middle part of the slopes. 4. After one year from seeding, the height of Lespedeza cyrtobotrya and Indigo/era pseudo-tinctoria were longer than any other plants. The next were Albizzia julibrissin, Lespedeza cuneata and wild flowers. The tree height of Rhus chinensis shows 28cm length, so it has enough possibility to be used for roadside revegetation works. 5. Lespedeza cyrtobotrya and Indigo/era pseudo-tinctoria show different importance values according to slope aspect. But, they show tendency to outweigh the other plants at all slope-aspects. 6. Most of the plants seeded by NTRM were germinated well and they covered rock-exposed-slopes so quickly and effectively. Thus it leads to conclusion that the revegetation methods used in this experiment was a very effective methods to recover rock-exposed-slopes by seeding of zoysia japonica and native woody plants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.364-371
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• 2016

We developed a prediction model of assistance force for the opening/closing of an automobile door depending on the condition of the parking ground. The candidates of the learning models for the operating assistance force were compared to determine the proper force according to the slope and user's force, etc. The reduced experimental model was developed to obtain learning data for the estimation model. The learning algorithm was composed to predict the assistance force to incorporate real assistance force data. Among these algorithms, an Artificial Neural Network (ANN) and Support Vector Machine(SVM) were applied and the adaptability was compared between these models. The SVM provided more adaptability for the learning process of the door assistance force prediction. This paper proposes a system for determining the assistance force to control a door motor to compensate for the deviation of required door force in the slope condition, as needed in the plane condition.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.2
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• pp.89-99
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• 2019

In order to increase the seismic safety of nuclear power plant (NPP) structures, a technique to reduce the seismic load transmitted to the NPP structure by using a seismic isolation device such as a lead-rubber bearing has recently been actively researched. In seismic design of NPP structures, three directional (two horizontal and one vertical directions) artificial synthetic earthquakes (G0 group) corresponding to the standard design spectrum are generally used. In this study, seismic analysis was performed by using three directional artificial synthetic earthquakes (M0 group) corresponding to the maximum-minimum spectrum reflecting uncertainty of incident direction of earthquake load. The design basis earthquake (DBE) and the beyond design basis earthquakes (BDBEs are equal to 150%, 167%, and 200% DBE) of G0 and M0 earthquake groups were respectively generated for 30 sets and used for the seismic analysis. The purpose of this study is to compare seismic responses and seismic fragility curves of seismically isolated NPP structures subjected to DBE and BDBE. From the seismic fragility curves, the probability of failure of the seismic isolation system when the peak ground acceleration (PGA) is 0.5 g is about 5% for the M0 earthquake group and about 3% for the G0 earthquake group.