• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.11-19
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• 2006

In this study ship collision risk analysis is performed to determine the design vessel for collision impact analysis of suspension bridge. Method II in AASHTO LRFD bridge design specifications which is a more complicated probability based analysis procedure is used to select the design vessel for collision impact. From the assessment of ship collision risk for each bridge pier exposed to ship collision, the design impact lateral strength of bridge pier is determined. The analysis procedure is an iterative process in which a trial impact resistance is selected for a bridge component and a computed annual frequency of collapse(AF) is compared to the acceptance criterion, and revisions to the analysis variables are made as necessary to achieve compliance. The acceptance criterion is allocated to each pier using allocation weights based on the previous predictions. This AF allocation method is compared to the pylon concentration allocation method to obtain safety and economy in results. This method seems to be more reasonable than the pylon concentration allocation method because AF allocation by weights takes the design parameter characteristics quantitatively into consideration although the pylon concentration allocation method brings more economical results when the overestimated design collision strength of piers compared to the strength of pylon is moderately modified. The design vessel for each pier corresponding with the design impact lateral strength obtained from the ship collision risk assessment is then selected. The design impact lateral strength can vary greatly among the components of the same bridge, depending upon the waterway geometry, available water depth, bridge geometry, and vessel traffic characteristics. Therefore more researches on the allocation model of AF and the selection of design vessel are required.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.1-9
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• 2006

An analysis of the annual frequency of collapse(AF) is performed for each bridge pier exposed to ship collision. From this analysis, the impact lateral resistance can be determined for each pier. The bridge pier impact resistance is selected using a probability-based analysis procedure in which the predicted annual frequency of bridge collapse, AF, from the ship collision risk assessment is compared to an acceptance criterion. The analysis procedure is an iterative process in which a trial impact resistance is selected for a bridge component and a computed AF is compared to the acceptance criterion, and revisions to the analysis variables are made as necessary to achieve compliance. The distribution of the AF acceptance criterion among the exposed piers is generally based on the designer's judgment. In this study, the acceptance criterion is allocated to each pier using allocation weights based on the previous predictions. To determine the design impact lateral resistance of bridge components such pylon and pier, the numerical analysis is performed iteratively with the analysis variable of impact resistance ratio of pylon to pier. The design impact lateral resistance can vary greatly among the components of the same bridge, depending upon the waterway geometry, available water depth, bridge geometry, and vessel traffic characteristics. More researches on the allocation model of AF and the determination of impact resistance are required.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.289-301
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• 2009

In this work, wave run-up heights and resultant wave forces on a vertical revetment due to tsunami (solitary wave) are investigated numerically using a numerical wave tank model called CADMAS-SURF (CDIT, 2001. Research and Development of Numerical Wave Channel (CADMAS-SURF). CDIT library, No. 12, Japan.), which is based on a 2-D Navier-Stokes solver, coupled to a volume of fluid (VOF) method. The third order approximate solution (Fenton, 1972. A ninth-order solution for the solitary wave. J. of Fluid Mech., Vol. 53, No.2, pp.257-271) is used to generate solitary waves and implemented in original CADMAS-SURF code. Numerical results of the wave profiles and forces are in good agreements with available experimental data. Using the numerical results, the regression curves determined from the least-square analysis are proposed, which can be used to determine the maximum wave run-up height and force on a vertical revetment due to tsunami. In addition, the capability of CADMAS-SURF is demonstrated for tsunami wave forces acting on an onshore structure using various configuration computations including the variations of the crown heights of the vertical wall and the position of the onshore structure. Based on the numerical results such as water level, velocity field and wave force, the direct effects of tsunami on an onshore structure are discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.179-189
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• 2010

This paper presents a numerical investigation of vorticity generation in fully vegetated open-channel flows. The Reynolds stress model is used for the turbulence closure. Open-channel flows with rough bed-smooth sidewalls and smooth bed-rough sidewalls are simulated. The computed vectors show that in channel flows with rough bed and rough sidewalls, the free-surface secondary currents become relatively smaller and larger, respectively, compared with that of plain channel flows. Also, open-channel flows over vegetation are simulated. The computed bottom vortex occupies the entire water depth, while the free-surface vortex is reduced. The contours of turbulent anisotropy and Reynolds stress are presented with different density of vegetation. The budget analysis of vorticity equation is carried out to investigate the generation mechanism of secondary currents. The results of the budget analysis show that in plain open-channel flow, the production by anisotropy is important in the vicinity of the wall and free-surface boundaries, and the production by Reynolds stress is important in the region away from the boundaries. However, this rule is not effective in vegetated channel flows. Also, in plain channel flows, the vorticity is generated mainly in the vicinity of the free-surface and the bottom, while in vegetated channel flows, the regions of the bottom and vegetation height are important to generate the vorticity.

• Journal of Veterinary Science
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• v.24 no.4
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• pp.52.1-52.13
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• 2023

Background: Mesenchymal stem cells (MSCs) have been investigated as therapeutic agents for inflammatory bowel disease (IBD). Stimulation of MSCs with pro-inflammatory cytokines is an approach to enhance their immunomodulatory effects. However, further investigation is required to support their application in immune-mediated disorders and companion animals. Objectives: This study aimed to assess the therapeutic effect of tumor necrosis factor (TNF)-α-stimulated feline adipose tissue-derived MSCs (fAT-MSCs) in a dextran sulfate sodium (DSS)-induced colitis mouse model. Methods: Colitis mice was made by drinking water with 3% DSS and fAT-MSCs were injected intraperitoneally. Colons were collected on day 10. The severity of the disease was evaluated and compared. Raw 264.7 cells were cultured with the conditioned medium to determine the mechanism, using quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay. Results: TNF-α-stimulated fAT-MSCs more improved severity of DSS-induced colitis in disease activity, colon length, histologic score, and inflammatory cytokine. In sectionized colon tissues, the group comprising TNF-α-stimulated fAT-MSCs had higher proportion of CD11b⁺CD206⁺ macrophages than in the other groups. In vitro, TNF-α-stimulation increased cyclooxygenase-2 (COX-2) expression and prostaglandin E₂ (PGE₂) secretion from fAT-MSCs. The conditioned medium from TNF-α-stimulated fAT-MSCs enhanced the expression of interleukin-10 and arginase-1 in LPS-activated Raw 264.7 cells. Conclusions: These results represent that TNF-α-stimulated fat-mscs ameliorate the inflamed colon more effectively. Furthermore, we demonstrated that the effectiveness was interlinked with the COX-2/PGE₂ pathway.

• Journal of Soil and Groundwater Environment
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• v.28 no.6
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• pp.71-89
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• 2023

A groundwater potential map (GPM) was built for the Nakdonggang River Basin based on ten variables, including hydrogeologic unit, fault-line density, depth to groundwater, distance to surface water, lineament density, slope, stream drainage density, soil drainage, land cover, and annual rainfall. To integrate the thematic layers for GPM, the criteria were first weighted using the Analytic Hierarchical Process (AHP) and then overlaid using the Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) model. Finally, the groundwater potential was categorized into five classes (very high (VH), high (H), moderate (M), low (L), very low (VL)) and verified by examining the specific capacity of individual wells on each class. The wells in the area categorized as VH showed the highest median specific capacity (5.2 m³/day/m), while the wells with specific capacity < 1.39 m³/day/m were distributed in the areas categorized as L or VL. The accuracy of GPM generated in the work looked acceptable, although the specific capacity data were not enough to verify GPM in the studied large watershed. To create GPMs for the determination of high-yield well locations, the resolution and reliability of thematic maps should be improved. Criterion values for groundwater potential should be established when machine learning or statistical models are used in the GPM evaluation process.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1693-1705
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• 2023

Rural areas, which account for about 90% of the country's land area, are increasing in importance and value as a space that performs various public functions. However, facilities that adversely affect residents' lives, such as livestock facilities, factories, and solar panels, are being built indiscriminately near residential areas, damaging the rural environment and landscape and lowering the quality of residents' lives. In order to prevent disorderly development in rural areas and manage rural space in a planned manner, detection and monitoring of hazardous facilities in rural areas is necessary. Data can be acquired through satellite imagery, which can be acquired periodically and provide information on the entire region. Effective detection is possible by utilizing image-based deep learning techniques using convolutional neural networks. Therefore, U-Net model, which shows high performance in semantic segmentation, was used to classify potentially hazardous facilities in rural areas. In this study, KOMPSAT ortho-mosaic optical imagery provided by the Korea Aerospace Research Institute in 2020 with a spatial resolution of 0.7 meters was used, and AI training data for livestock facilities, factories, and solar panels were produced by hand for training and inference. After training with U-Net, pixel accuracy of 0.9739 and mean Intersection over Union (mIoU) of 0.7025 were achieved. The results of this study can be used for monitoring hazardous facilities in rural areas and are expected to be used as basis for rural planning.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.

• Advances in nano research
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• v.16 no.4
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• pp.325-340
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• 2024

There are several novel uses for dispersing many nanoparticles into a conventional fluid, including dynamic sealing, damping, heat dissipation, microfluidics, and more. Therefore, melting heat and mass transfer characteristics of a 3-D MHD Hybrid Nanofluid flow over a rotating disc with presenting dufour and soret effects are assessed numerically in this study. In this instance, we investigated both ferric sulfate and molybdenum disulfide as nanoparticles suspended within base fluid water. The governing partial differential equations are transformed into linked higher-order non-linear ordinary differential equations by the local similarity transformation. The collection of these deduced equations is then resolved using a Chebyshev spectral collocation-based algorithm built into the Mathematica software. To demonstrate how different instances of hybrid/ nanofluid are impacted by changes in temperature, velocity, and the distribution of nanoparticle concentration, examples of graphical and numerical data are given. For many values of the material parameters, the computational findings are shown. Simulations conducted for different physical parameters in the model show that adding hybrid nanoparticle to the fluid mixture increases heat transfer in comparison to simple nanofluids. It has been identified that hybrid nanoparticles, as opposed to single-type nanoparticles, need to be taken into consideration to create an effective thermal system. Furthermore, porosity lowers the velocities of simple and hybrid nanofluids in both cases. Additionally, results show that the drag force from skin friction causes the nanoparticle fluid to travel more slowly than the hybrid nanoparticle fluid. The findings also demonstrate that suction factors like magnetic and porosity parameters, as well as nanoparticles, raise the skin friction coefficient. Furthermore, It indicates that the outcomes from different flow scenarios correlate and are in strong agreement with the findings from the published literature. Bar chart depictions are altered by changes in flow rates. Moreover, the results confirm doctors' views to prescribe hybrid nanoparticle and particle nanoparticle contents for achalasia patients and also those who suffer from esophageal stricture and tumors. The results of this study can also be applied to the energy generated by the melting disc surface, which has a variety of industrial uses. These include, but are not limited to, the preparation of semiconductor materials, the solidification of magma, the melting of permafrost, and the refreezing of frozen land.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.2
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• pp.82-91
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• 2006

We investigated the possibility of using effluents from a municipal sewage treatment plant (STP) as tracers a tracer for hydrologic studies of rivers. The possibility was checked in a 12-km long reach downstream of Jeonju Municipal Sewage Treatment Plant (JSTP). Time-series monitoring of the water chemistry reveals that chemical compositions of the effluent from the JSTP are fluctuating within a relatively wide range during the sampling period. In addition, the signals from the plant were observed at the downstream stations consecutively with increasing time lags, especially in concentrations of the conservative chemical parameters (concentrations f3r chloride and sulfate, total concentration of major cations, and electric conductivity). Based on this observation, we could estimate the stream flow (Q), velocity (v), and dispersion coefficient (D). A 1-D nonreactive solute-transport model with automated optimization schemes was used for this study. The values of Q, v, and D estimated from this study varied from 6.4 to $9.0m^3/sec$ (at the downstream end of the reach), from 0.06 to 0.10 m/sec, and from 0.7 to $6.4m^2/sec$, respectively. The results show that the effluent from a large-scaled municipal STP frequently provides good, multiple natural tracers far hydrologic studies.