• Food Engineering Progress
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• v.21 no.3
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• pp.267-272
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• 2017

To improve dispersibility of cereal powder without additives, granulation of cereal powder was conducted using fluidized-bed granulator. Operation condition was sample 300 g, internal temperature $40^{\circ}C$, ventilation speed $30-90m^3/h$, inlet temperature $90^{\circ}C$ and spray pressure 2.5 bar. The amount of distilled water (20-45%) as binder, granulation time (10-15 min) and drying time (3-10 min) were controlled. Mean diameter over volume (Brouckere mean, $D_{4,3}$) was increased from $123{\mu}m$ to $263{\mu}m$ and dispersibility was improved from 73% to 92.25% at experiment conditions. Wettability (wetting time) was drastically decreased from 5,000 second to 7 second. Granulation of cereal powder did not affect sinkability and mean diameter over volume as wet analysis was about the same between raw and granulated cereals. Such phenomenon means that granulation with only water as binder enables cereal powder to disperse in water or milk without rapid sedimentation.

• Tunnel and Underground Space
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• v.31 no.5
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• pp.309-332
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• 2021

Natural barrier systems surrounding the geological repository for the high-level radioactive waste should guarantee the hydraulic performance for preventing or delaying the leakage of radionuclide. In the case of the behavior of a crystalline rock, the hydraulic performance tends to be decided by the existence of discontinuities, so the coupled hydro-mechanical(HM) processes on the discontinuities should be characterized. The discontinuum modelling can describe the complicated behavior of discontinuities including creation, propagation, deformation and slip, so it is appropriate to model the behavior of a crystalline rock. This paper investigated the coupled HM processes in discontinuum modelling such as UDEC, 3DEC, PFC, DDA, FRACOD and TOUGH-UDEC. Block-based discontinuum methods tend to describe the HM processes based on the fluid flow through the discontinuities, and some methods are combined with another numerical tool specialized in hydraulic analysis. Particle-based discontinuum modelling describes the overall HM processes based on the fluid flow among the particles. The discontinuum methods that are currently available have limitations: exclusive simulations for two-dimension, low hydraulic simulation efficiency, fracture-dominated fluid flow and simplified hydraulic analysis, so it could be improper to the modelling the geological repository. Based on the concepts of various discontinuum modelling compiled in this paper, the advanced numerical tools for describing the accurate coupled HM processes of the deep geological repository should be developed.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.238-247
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• 2020

This study aims to examine the causes of the rapid expansion of riparian vegetation in river channels in recent years. Accordingly, the changes in the monthly rainfall were analyzed at 19 locations over the period of 1984 to 2018. Moreover, the changes in the water levels of the target river sections of Seom River, Cheongmi River, and Naeseong River were analyzed. The results showed that rainfall increased by 30% in April and decreased by up to 49% in the May-September period since 2012. Between 2012 and 2018, when rainfall decreased, the inundation time of the floodplains of the target rivers decreased considerably. The floodplains of Seom River and Cheongmi River were not inundated since 2012 and 2013, respectively. In the case of Naeseong River, the inundation time of the low-water channel drastically decreased since 2013, and there was no inundation in 2015. Consequently, riparian vegetation settled rapidly on the floodplain without any disturbance and continued to expand. The settling and expansion of riparian vegetation reduce the flood capacity of the river channel and can also lead to the loss of the water ecosystem due to terrestrialization.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.3
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• pp.167-174
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• 2021

Recent investigation into the integrity of nuclear containment buildings has highlighted the importance of developing an elaborate diagnostic method to evaluate the distribution and size of cavities inside concrete walls. As part of developing such a method, this paper presents a finite element approach to modeling elastic waves propagating in the containment building walls of a nuclear power plant. We introduce a perfectly matched layer (PML) wave-absorbing boundary to limit the large-scale nuclear containment wall to the region of interest. The formulation results in a semi-discrete form with symmetric damping and stiffness matrices. The transient elastic wave equations for a mixed unsplit-field PML were solved for displacement and stresses in the time domain. Numerical results show that the sensitivity of displacement, velocity, acceleration, and stresses is large depending on the size and location of the cavity. The dynamic response of the wall slightly differs depending on the existence of the containment liner plate. The results of this study can be applied to a full-waveform inversion approach for characterizing cavities inside a containment wall.

• Journal of the Korean Wood Science and Technology
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• v.49 no.4
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• pp.315-327
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• 2021

Purpose of this study is reviewing the use method for the sawdust (sawmilling by-product) and rice husk (Agriculture by-product) by adding charcoal, an eco-friendly material. Mixed composite boards were manufactured with those materials with each density and mixing ratio, and bending performance was investigated. When the addition ratio of sawdust, rice husk and charcoal is 50:20:20 and the resin addition ratio is 10%, as the density of the prepared mixed board ranges from 0.5 g/cm³ to 0.7 g/cm³, the bending strength was 0.42~3.24 N/mm², dynamic modulus of elasticity was 94.5~888.4 N/mm², and the static modulus of elasticity was in the range of 31.4~220.7 N/mm². As the density increased, the bending performance increased, indicating that the density had a significant effect on the bending performance. In a board prepared by setting the density of 0.6 g/cm³, the addition ratio of sawdust to 50%, and the addition ratio of rice husk and charcoal at different ratios, the bending performance showed a tendency to decrease as the addition ratio of charcoal increased. The relationship between the addition ratio of rice husk and charcoal, bending strength, resonance frequency, and dynamic and static bending modulus showed a rather low correlation with the values of the coefficient of determination (R²) of 0.4562, 0.4310, 0.4589, and 0.5847, respectively. Thus, we found that the effect of the addition ratio on the bending performance was small.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.77-84
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• 2021

A sampling-based approach was devised as a nuclear seismic probabilistic risk assessment (SPRA) method to account for the partially correlated relationships between components. However, since this method is based on sampling, there is a limitation that a large number of samples must be extracted to estimate the results accurately. Thus, in this study, we suggest an effective approach to improve the existing sampling method. The main features of this approach are as follows. In place of the existing Monte Carlo sampling (MCS) approach, the Latin hypercube sampling (LHS) method that enables effective sampling in multiple dimensions is introduced to the SPRA method. In addition, the degree of segmentation of the seismic intensity is determined with respect to the final seismic risk result. By applying the suggested approach to an actual nuclear power plant as an example, the accuracy of the results were observed to be almost similar to those of the existing method, but the efficiency was increased by a factor of two in terms of the total number of samples extracted. In addition, it was confirmed that the LHS-based method improves the accuracy of the solution in a small sampling region.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.1
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• pp.13-24
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• 2021

Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

• Food Engineering Progress
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• v.23 no.2
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• pp.118-124
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• 2019

This study aims to investigate the physical properties of extruded psyllium husk upon the addition of emulsifiers. Three different emulsifiers-glycerol monostearate (GMS), polyglycerol ester (PGE), and sugar ester (SE)-were added to the mixture of psyllium husk and rice powder before extrusion. Extrusion was performed using a twin-screw extruder at 140℃ die temperature, 200 rpm screw speed, and 16% feed moisture content. The physical properties of psyllium husk extrudates including expansion ratio, specific length, piece density, texture profile, color properties, water soluble index, and water absorption index were evaluated. It was observed that the expansion ratio was the highest while the specific length and piece density were the lowest in the control which had no emulsifiers. Texture profile analysis showed that the apparent elastic modulus and breaking strength were highest in the extrudate with a PGE of 0.1%. The adhesiveness was found to be lowest in the extrudates with an SE of 0.1% and GMS of 0.5%. Lightness value was highest in the extrudate with a PGE of 0.1%. Color difference, water soluble index, and water absorption index were highest in the control. The results reveal that some physical properties of extruded psyllium husk were improved with the addition of emulsifiers. This finding provides useful information for the development of psyllium snacks with good physical characteristics.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.1-8
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• 2021

A surface image velocimeter (SIV) measures the velocity of a particle group by calculating the intensity distribution of the particle group in two consecutive images of the water surface using a cross-correlation method. Therefore, to increase the accuracy of the flow velocity calculated by a SIV, it is important to accurately calculate the displacement of the particle group in the images. In other words, the change in the physical distance of the particle group in the two images to be analyzed must be accurately calculated. In the image of an actual river taken using a camera, camera lens distortion inevitably occurs, which affects the displacement calculation in the image. In this study, we analyzed the effect of camera lens distortion on the displacement calculation using a dense and uniformly spaced grid board. The results showed that the camera lens distortion gradually increased in the radial direction from the center of the image. The displacement calculation error reached 8.10% at the outer edge of the image and was within 5% at the center of the image. In the future, camera lens distortion correction can be applied to improve the accuracy of river surface flow rate measurements.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.9-15
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• 2021

With the recent development of 5G and artificial intelligence technologies, it is interested in AIOT technology to collect, process, and analyze information in cloud edge environments. AIIoT technology is being applied to various smart environments, but research is needed to perform fast response processing through accurate analysis of collected information. In this paper, we propose a technique to minimize bandwidth and processing time by blocking the connection processing between AIOT information through fast processing and accurate analysis/forecasting of information collected in the smart environment. The proposed technique generates seeds for data indexes on AIOT devices by multipointing information collected by blockchain, and blocks them along with collection information to deliver them to the data center. At this time, we deploy Deep Neural Network (DNN) models between cloud and AIOT devices to reduce network overhead. Furthermore, server/data centers have improved the accuracy of inaccurate AIIoT information through the analysis and predicted results delivered to minimize latency. Furthermore, the proposed technique minimizes data latency by allowing it to be partitioned into a layered multilayer network because it groups it into blockchain by applying weights to AIOT information.