• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.567-578
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• 2014

The study suggested a method to improve analysis accuracy such that the interactive effects of transportation changes between outside and inside of sub-areas were sequentially considered in the analysis by linking a macroscopic network analysis and a microscopic traffic simulation. A dynamic O/D estimation method was developed for practical implement of sub-area microscopic simulation analysis by using the results of macroscopic network analysis, the results of selected link analysis at the cordon line of the sub-area, departure time data of household travel survey, timely observed traffic volume data at the cordon. This estimated dynamic O/D for the sub-area made it possible to analyze traffic phenomena in details. Various detailed phenomena such as traffic queues, delay at intersection, and conflicts between vehicles, which is impossible to be grasped through a macroscopic analysis, can be analyzed with the dynamic microscopic traffic analysis. Through implementing an empirical study and validation, the study provided a reference result about accuracy of a microscopic traffic simulation of a sub-area to help its application for real transportation policy analysis.

• Journal of KIBIM
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• v.2 no.1
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• pp.27-39
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• 2012

Public construction projects need complex and multi-functional management skill, since the most of public construction projects are comprised of multi-project and mega-projects. In order to effectively manage construction projects, PMIS is widely used. However the majority of the current PMIS have been developed as a single project-oriented business management system. Thus compatibility problems are encountered during the process of integrating the entire systems to manage the multi-complex projects. In addition, the form of orders applying BIM are increased recently, but the research and development of BIM based PMIS are still lacking. In this study, therefore, the functions of PMIS main objectives based on the analysis of PMIS As-Is and To-Be of PMIS, the dual management system utilizing Internet and Intranet will be proposed to integrate the individual PMIS with Integrated Program Management System. Rather than combining commercial BIM tool and PMIS directly, which is the common method of failure, the sequential process model to adopt BIM based PMIS is also explained. Step-by-step development method of BIM based PMIS is suggested to prepare for the activation of BIM technology in the nearest future.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.5
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• pp.511-516
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• 2008

Since 1989, Advanced drinking water treatment processes began to build in Korea, especially the water treatment plants around the Nak-dong river stream due to sequential pollutant accidents. Moreover, Advanced drinking water treatment processes, ozone and GAC, are again to be built in water treatment plants around Han-river stream to control taste and odor, micro pollutants. However, there are still a lot of discussion to decide the processes to apply for advanced treatment. Thus there are still need to understand clearly on the cost evaluation of each advanced treatment processes. The cost evaluation was accomplished based on the data of six water treatment plants which are currently being either operating or constructing. Exceptionally, PAC(Powdered Activated Carbon) process was evaluated with cost estimation from construction company. The capital cost per unit volume of ozone process was significantly decreased as the treatment capacity increased. The capital cost was in the order of GAC, ozone and GAC. The operation cost decreased in the order of PAC, GAC and ozone. The total cost considering present value shows that ozone process covers 84% of ozone and GAC process for $30,000m^3/d$ capacity while it covers less than 35% for over 140 thousands $m^3/d$ capacity. Comparing GAC only, and ozone/GAC process, ozone/GAC process is more cost effective for high capacity water treatment plant.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.915-920
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• 2005

In this paper we expanded a existing web based B2B system to support users in low speed network. To guarantee shared dat a consistency between clients and a server, we proposed a method of data change detection by using a time stamp tree and the performance analysis of the proposed method was proved by a simulation. Under the worst condition that leaf nodes of a times tamp tree were changed uniform distribution, the simulation result showed that the proposed method was more efficient than a sequential detection until the percentage of changed nodes were below $15\%$. According to our observation, the monthly average of data change was below $7\%$ on a web-based construction MRO B2B system or a company A from April 2004 to August 2004. Therefore the Proposed method improved performance of data change detection in practice. The proposed method also reduced storage consumption in a server because it didn't require a server to store replicated data for every client.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.861-874
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• 2012

To fulfill applicability of Soil and Water Assessment Tool (SWAT) model, it is important that this model passes through a careful calibration and uncertainty analysis. In recent years, many researchers have come up with various uncertainty analysis techniques for SWAT model. To determine the differences and similarities of typical techniques, we applied three uncertainty analysis procedures to Chungju Dam watershed (6,581.1 $km^2$) of South Korea included in SWAT-Calibration Uncertainty Program (SWAT-CUP): Sequential Uncertainty FItting algorithm ver.2 (SUFI2), Generalized Likelihood Uncertainty Estimation (GLUE), Parameter Solution (ParaSol). As a result, there was no significant difference in the objective function values between SUFI2 and GLUE algorithms. However, ParaSol algorithm shows the worst objective functions, and considerable divergence was also showed in 95PPU bands with each other. The p-factor and r-factor appeared from 0.02 to 0.79 and 0.03 to 0.52 differences in streamflow respectively. In general, the ParaSol algorithm showed the lowest p-factor and r-factor, SUFI2 algorithm was the highest in the p-factor and r-factor. Therefore, in the SWAT model calibration and uncertainty analysis of the automatic methods, we suggest the calibration methods considering p-factor and r-factor. The p-factor means the percentage of observations covered by 95PPU (95 Percent Prediction Uncertainty) band, and r-factor is the average thickness of the 95PPU band.

• Journal of the Korean Geotechnical Society
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• v.25 no.4
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• pp.19-29
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• 2009

In this study, a numerical analysis was performed to predict the sequential behavior of anchored retaining wall where the failure accident took place, and verified accuracy of prediction through the comparisons between prediction and field measurement. The emphasis was given to the wall behaviors and the variation of sliding surface based on the two different methods of elasto-plastic and finite element (shear strength reduction technique). Through the comparison study, it is shown that the bending moment and the soil pressure at construction stages produce quite similar results in both the elasto-plastic and finite element method. However, predicted wall deflections using elasto-plastic method show underestimate results compared with measured deflections. This demonstrates that the elasto-plastic method does not clearly consider the influence of soil-wall-reinforcement interaction, so that the tension force (anchor force and earth pressure) on the wall is overestimated. Based on the results obtained, it is found that finite element method using shear strength reduction method can be effectively used to perform the back calculation analysis in the anchored retaining wall, whereas elasto-plastic method can be applicable to the preliminary design of retaining wall with suitable safety factor.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• Ecology and Resilient Infrastructure
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• v.3 no.1
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• pp.35-45
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• 2016

The correlation relationships and their corresponding equations between the geomorphological parameters and the Soil Water Assessment Tool (SWAT) model parameters by Sequential Uncertainty Fitting - version 2 (SUFI-2) algorithm of SWAT Calibration and Uncertainty Programs (SWAT-CUP) were developed at the Seom-river experimental watershed. The parameters of the SWAT model at the Soksa-river experimental watershed were estimated by the developed equations. The SWAT model parameters were estimated by SUFI-2 algorithm of SWAT-CUP with rainfall-runoff data from the Soksa-river experimental watershed from 2000 to 2007. Rainfall-runoff simulation of the SWAT model was carried out at the Soksa-river experimental watershed from 2000 to 2007 for the applicability of the estimated parameters by the developed equations. The root mean square errors (RMSE) between the observed and the simulated rainfall-runoffs using the estimated parameters by developed equations of correlation analysis and the optimum parameters by SUFI-2 of SWAT-CUP were $1.09m^3/s$ and $0.93m^3/s$ respectively at the Soksa-river experimental watershed from 2000 to 2007. Therefore, it is considered that the parameter estimation of the SWAT model by the geomorphological characteristics parameters has applicability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.167-178
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• 2020

The purpose of this study is to examine the relationship between internal corporate, supplier, and customer integrations for domestic SMEs on non-financial and financial performance through SCM performance such as flexibility and reduction of uncertainties. To this end, data was collected on 286 SMEs in Korea, and the structural relationships between SCM integration level, SCM performances, and management performance were analyzed. As a result of the analysis, first, it was found that the SCM integration level had a significant positive effect on the flexibility and reduction of uncertainties, which are SCM performances. Second, the flexibility and reduction of uncertainties showed significantly positive effects on the non-financial performance of the companies, but did not directly affect the financial performance positively. Third, the non-financial performance was found to have a positive effect on the financial performance. In addition, the SCM integration level did not have a direct effect on the financial and non-financial performance, but it was found that it affected management performance by mediating the flexibility and reduction of uncertainties, which are SCM performances. That is, although the SCM integration level did not directly affect financial and non-financial performance, it was confirmed that it affects management performance by mediating SCM performances, flexibility and uncertainty reduction. In other words, it was confirmed that the SCM integration level directly or indirectly affects SCM performances and overall management performance. These results imply the necessity to focus on competency in the supply chain management area according to the SCM performance expected by SMEs, and the step by step approaches to the expected effects. In a situation where prior SCM related studies have not been able to present SCM performances and management performance of SMEs that are relatively lacking in their capital and SCM construction capabilities, the findings of this study could suggest the importance of SCM integration from the perspective of SMEs. In addition, from the viewpoint of SMEs, this study suggested that a sequential approach for performance measurement is required (SCM performance → management performance) in relation to the performance factors to be established through SCM.