• Membrane Journal
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• v.32 no.4
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• pp.253-263
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• 2022

This study suggests a guideline for designing unit process of wastewater reuse in terms of a maintenance of the process based on critical parameters to draw a high quality performance of RO unit. Defining the parameters was done by applying membrane integrity test (MIT) in pretreatment process utilizing lab-scale MF. SDI is utilized for judging whether permeate is suitable to RO unit. However, result said TOC concentration matching with particle count analysis is better for judging the permeate condition. When membrane test pressure (P_test) was measured to derive log removal value in PDT, virgin state of membrane fiber was used to measure dynamic contact angle utilizing surface tension of the membrane fiber. Actually, foulant affects to the state of membrane surface, and it decreases the P_test value along with time elapsed. Consequently, LRV_DIT is also affected by P_test value. Thus, sensitivity of direct integrity test descends with result of P_test value change, so P_test value should be considered not the virgin state of the membrane but its current state. Overall, this study focuses on defining design parameters suitable to MF pretreatment for RO process in wastewater reuse by assessing its impact. Therefore, utilities can acknowledge that the membrane surface condition must be considered when users conduct the direct integrity test so that P_test and other relative parameter used to calculate LRV_DIT are adequately measured.

• Nuclear Engineering and Technology
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• v.25 no.1
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• pp.91-101
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• 1993

To predict accurately the thermal hydraulic behavior of light water reactors during normal or abnormal operation, the accurate estimation of the void distribution is required. Up to date, many techniques for predicting void fraction of two-phase flow systems have been suggested. Among these techniques, the drift-flux model is widely used because of its exact calculation ability and simplicity. However, to get more accurate prediction of void fraction using drift-flux model, slip and flow regime effects must be considered more properly In the drift-flux method, these two effects are accounted for by two drift-flux parameters ; $C_{o}$ and (equation omitted). At earlier stage, $C_{o}$ is measured in a circular tube. In this study, $C_{o}$ is experimentally determined by measuring local void fraction and vapor velocity distribution in a rectangular subchannel having 4 heating rods which simulates nuclear subchannels. The measurements are peformed with two-electrical conductivity probes which are known to be adequate for measuring local parameters. The experiments are performed at low flow rate and the system pressure less than 3 atmo spheric pressure. In this experiment, (equation omitted), is not measured, but quoted from well-known empirical correlation to formulate $C_{o}$. Finally, $C_{o}$ is expressed as a function of channel averaged void fraction. fraction.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• Journal of the Korean Geotechnical Society
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• v.25 no.2
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• pp.55-66
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• 2009

At the mudstone slope located on the roadside of the Seokri area in Donghae-myeon, Pohang, Gyeongsangbuk-do, this study was performed to analyze the effects of rainfall on the stability of slope through seepage analysis according to the precipitation type of the mudstone slope, referring to the actual case of slope failure. For this, precise geological survey, geophysical exploration and drilling survey for the slope where the failure occurred were performed and followed by analysis of detailed soil layer. For the section where failure surface located, the durability reduction of rocks was measured through slaking/swelling tests and the permeability was measured through in-situ permeability tests for each soil layer. In addition, the change of strength parameter and process of instability were analyzed by back analysis, using Talren 97 and Slope/W programs, in the slope. By applying different precipitation conditions to the geographical conditions of the slope that had actual failure records, the slope stability was analyzed by seepage analysis according to duration of rainfall and rise of groundwater level resulting from the flow of rainfall caused by development of geological structures and the slope surface condition.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.669-676
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• 2023

This study analyzed the relationship between major parameters and numerical analysis results according to various excavations conducted around the urban railway, application of machine learning techniques and verified the scope of influence of the adjacent excavation on the existing urban railway box structure and the appropriateness of the safety area. This study targeted the actual negotiated adjacent excavation works and box structures around the urban railway, and the analysis was conducted on the most representative two-line box structures. The analysis confirmed that the difference in depth of urban railway, excavation depth of adjacent excavation, and depth of underground water level are important parameters, and the difference in excavation depth of adjacent excavation is the parameter that affects the behavior of underground box structures and is an important requirement for setting safety areas. In particular, the deeper the depth of the adjacent excavation work, the greater the effect on the deflection of the underground box structure, and the horizontal separation distance, one of the important requirements for determining the management grade of the existing adjacent excavation work, is relatively small.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1C
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• pp.43-52
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• 2006

Despite several constitutive models have been proposed and applied, it is still difficult to choose a suitable model and to estimate adequate analysis parameters. Furthermore, a cyclic shear behavior under the volume change caused by the seepage is more complex. None of the constitutive model is available at present in the expression of the cyclic behavior of soil under an additional volume change condition by seepage. Therefore, a new geotechnical hybrid simulation system which can control the pore water immigration was developed. The system enables a quantitative evaluation of the residual deformation such as lateral spreading and settlement caused by the liquefaction. The seismic responses in a one-dimensional slightly inclined multilayered soil system are taken into consideration, and the soils are governed by both equation of motion and the continuity equation. Furthermore, the estimation and the selection of the soil parameter for the representation of the strong nonlinearity of the material are not required, because soil behaviors under the earthquake motions are directly introduced instead of a numerical soil constitutive model. This paper presents the concept and specifications of the system. By applying the system to an example problem, the permeability effect on the seismic response during cyclic shear is studied. The importance of the volume change characteristics of sandy soil during and after cyclic shear is shown in conclusion.

• 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.

• Korean Chemical Engineering Research
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• v.56 no.4
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• pp.479-495
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• 2018

This study was carried out to research the multimedia fate modeling, concentration distribution and impact assessment of polycyclic aromatic hydrocarbons (PAHs) emitted from automobiles, which are known as carcinogenic and mutation chemicals. The amount of emissions of PAHs was determined based on the census data of automobiles at a target S-city and emission factors of PAHs, where multimedia fugacity modeling was conducted by the restriction of PAHs transfer between air-soil at the impervious area. PAHs' Concentrations and their distributions at several environmental media were predicted by multimedia fugacity model (level III). The residual amounts and the distributions of PAHs through mass transfer of PAHs between environment media were used to assess the health risk of PAHs at unsteady state (level IV), where the sensitivity analyses of the model parameter of each variable were conducted based on Monte Carlo simulation. The experimental result at S-city showed that Fluoranthene among PAHs substances are the highest residual concentrations (60%, 53%, 32% and 34%) at all mediums (atmospheric, water, soil, sediment), respectively, where most of the PAHs were highly accumulated in the sediment media (more than 80%). A result of PAHs concentration changes in S-city over the past 34 years identified that PAHs emissions from all environmental media increased from 1983 to 2005 and decreased until 2016, where the emission of heavy-duty vehicle including truck revealed the largest contribution to the automotive emissions of PAHs at all environment media. The PAHs concentrations in soil and water for the last 34 years showed the less value than the legal standards of PAHs, but the PAHs in air exceeded the air quality standards from 1996 to 2016. The result of this study is expected to contribute the effective management and monitoring of toxic chemicals of PAHs at various environment media of Metropolitan city.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.697-707
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• 2007

In this study, we estimated the PMP(Probable Maximum Precipitation) and its transition in case of the typhoon Rusa which happened the biggest damage of all typhoons in the Korea. Specially, we analysed the moisture maximizing rate under the consideration of meteorological condition based on the orographic property when it hits in Gangneung region. The PMP is calculated by the rate of the maximum persisting 12 hours 1000 hPa dew points and representative persisting 12 hours 1000 hPa dew point. The former is influenced by the moisture inflow regions. These regions are determined by the surface wind direction, 850 hPa moisture flux and streamline, which are the critically different aspects compared to that of previous study. The latter is calculated using statistics program (FARD2002) provided by NIDP(National Institute for Disaster Prevention). In this program, the dew point is calculated by reappearance period 50-year frequency analysis from 5% of the level of significant when probability distribution type is applied extreme type I (Gumbel distribution) and parameter estimation method is used the Moment method. So this study indicated for small basin$(3.76km^2)$ the difference the PMP through new method and through existing result of established storm transposition and DAD(Depth-Area-Duration). Consequently, the moisture maximizing rate is calculated in the moisture inflow regions determined by meteorological fields is higher $0.20{\sim}0.40$ range than that of previous study. And the precipitation is increased $16{\sim}31%$ when this rate is applied for calculation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.