• International conference on construction engineering and project management
• /
• 2011.02a
• /
• pp.58-65
• /
• 2011

Construction Productivity is one of the most important elements in construction management. It is used in construction process scheduling and cost management, which are significant sector in construction management. It is important to make appropriate schedule and monitor how works are done within schedule. But construction project contains uncertainty and inexactitude, modifying construction schedule is being an issue to manage construction works well. Even though prediction and monitoring of productivity can be principal activity, it is hard to predict productivity with manager's experience and a standard of estimate. A large number of factors influencing productivity, such as drawing, construction method, weather, labor, material, equipment, etc. But current calculation of productivity depends on empirical probability, not consider difference of each influencing factor. In this research, the aim is to present a productivity predicting regression model of form work, which includes effectiveness of influences factors. 5 variables existed inside form work are selected by interview and site research based on literature review of existed various productivity influencing factors. The effectiveness and correlation of productivity influencing factors are analyzed by statistical approach, and it is used to make productivity regression model. The finding of this research will improves monitoring and controlling of project schedule in construction phase.

• Journal of Korea Trade
• /
• v.25 no.1
• /
• pp.89-111
• /
• 2021

Purpose - The U.S. Trade Preference Expansion Act (TPEA) of 2015 enables the US Department of Commerce (DOC) to inflate dumping margin when the particular market situation (PMS) exists in the exporter's home market. DOC applied PMS provisions to the steel products from Korea. This paper analyzes whether DOC's calculation by using the regression analysis is consistent with WTO rules. Design/methodology - This paper analyzes the PMS application in law and regression analysis that extends the data period from 10 years to 18 years using the same economic model with DOC, and changes the country group according to the quantities of steelmaking capacity. Findings - Results show that DOC's argument conflating the sales-based with cost-based PMS designed to inflate dumping margins might not be consistent with WTO Antidumping Agreement Article 2.2 and 2.2.1.1 in which costs shall normally be calculated on the basis of records kept by the exporter, providing generally accepted accounting principles and reasonably reflection of the costs and PMS that exists in the Korean steel product markets. Even if it will be consistent, DOC's calculated margin by the regression analysis using a 10-year data is a big gap (5 times) compared with an 18-year data projection and different countries' data through the same methodology, which is a huge gap of regression coefficient. It means that dumping margin would be very wide range from 7.8% to 38.54% and unstable to calculate. Inflating dumping margin by DOC using regression analysis would not only be inconsistent with WTO rules, but also projection result is unreliable. Originality/value - Literature papers have mainly analyzed WTO law itself. This paper however, would be the first attempt to analyze the DOC's new way of dumping margin calculation in both manners of law and an empirical methodology perspective at the same time.

• Korean Journal of Construction Engineering and Management
• /
• v.24 no.3
• /
• pp.3-11
• /
• 2023

This research examines the need for a quantitative and objective method of calculating baseline productivity in the construction industry, which is known for its high volatility in performance and productivity. The existing literature's baseline productivity calculation methods rely heavily on subjective criteria, limiting their effectiveness. Additionally, data collection methods such as the "Five-minute Rating" are costly and time-consuming, making it challenging to collect detailed data at construction sites. To address these issues, this study proposes an objective baseline calculation method using unimpacted productivity BP, a work check sheet to systematically record detailed data, and a data collection and utilization process that minimizes cost and time requirements. This paper also suggests using unimpacted productivity BP and comparative analysis to address the objectivity and reliability issues of existing baseline productivity calculation methods.

• Journal of Korean Society of Water and Wastewater
• /
• v.37 no.6
• /
• pp.409-423
• /
• 2023

In this study, we analyzed how the revenue water ratio(RWR) is affected by changes in conditions of the water supply area, such as the ratio of aging pipes, maintenance conditions, and revenue water. As a result of analyzing the impact of pipe aging and maintenance conditions on the RWR, it was confirmed that the RWR could be decreased if the pipe replacement project to improve the aging pipe ratio was not carried out and proper maintenance costs were not secured. It was also confirmed that an increase in the revenue water could be operated to facilitate the achievement of the project's target RWR. In contrast, a decrease in the revenue water due to a population reduction could affect the failure of the target RWR. In addition to analyzing the causes of variation in the RWR, the calculation of estimated project costs was considered by using leakage reduction instead of RWR from recent RWR improvement project cost data. From this analysis, it was reviewed whether the project costs planned to achieve the target RWR of the RWR improvement project in A city were appropriate. In conclusion, the RWR could be affected by variations in the ratio of aging pipes, maintenance conditions, and revenue water, and it was reasonable to consider not only the construction input but also the input related to RWR improvement, such as leakage reduction, when calculating the project cost.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.1
• /
• pp.183-192
• /
• 2024

The purpose of this study is to empirically analyze the determining factors (economy, security, domestic politics, administration, and international politics) that affect the ROK-US defense cost sharing decision. Through this, we will gain a deeper understanding of the defense cost sharing decision process and improve the efficiency of defense cost sharing calculation and execution. The scope of the study is ROK-US defense cost sharing from 1991 to 2021. The data used in the empirical analysis were various secondary data such as Ministry of National Defense, government statistical data, SIPRI, and media reports. As an empirical analysis method, multiple regression analysis using time series was used and the data was analyzed using an autoregressive model. As a result of empirical research through multiple regression analysis, we derived the following results. It was analyzed that the size of Korea's economy, that is, GDP, the previous year's defense cost share, and the number of U.S. troops stationed in Korea had a positive influence on the decision on defense cost sharing. This indicates that Korea's economic growth is a major factor influencing the increase in defense cost sharing, and that the gradual increase in the budget and the negotiation method of the Special Agreement (SMA) for cost sharing of stationing US troops in Korea play an important role. On the other hand, the political tendencies of the ruling party, North Korea's military threats, and China's defense budget were found to have no statistically significant influence on the decision to share defense costs.

• Structural Engineering and Mechanics
• /
• v.65 no.2
• /
• pp.173-181
• /
• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.

• Journal of KIBIM
• /
• v.1 no.2
• /
• pp.6-11
• /
• 2011

In domestic construction industry, there is lack of the communication between planning, design, construction and maintenance. This problem makes the omission of information and the loss of cost. Therefore, the introduction of BIM can be a solution about that. BIM manages all information generated during all life-cycle of a structure and consequently maximizes the efficiency of utilizing information. This is done through 3D information model associated with a three-dimensional(3D) parametric CAD. This study proposes the design process of steel box bridge for structural design work of bridge construction project based on BIM. This process has 3D modeling progress done by using the information decided in design phase. When the subject for the proposed process is superstructure of steel box bridge in construction, the structural calculation sheet can be derived with the structural design process based on BIM.

• Nuclear Engineering and Technology
• /
• v.56 no.2
• /
• pp.715-727
• /
• 2024

During fast neutron imaging, besides the dark current noise and readout noise of the CCD camera, the main noise in fast neutron imaging comes from high-energy gamma rays generated by neutron nuclear reactions in and around the experimental setup. These high-energy gamma rays result in the presence of high-density gamma white spots (GWS) in the fast neutron image. Due to the microscopic quantum characteristics of the neutron beam itself and environmental scattering effects, fast neutron images typically exhibit a mixture of Gaussian noise. Existing denoising methods in neutron images are difficult to handle when dealing with a mixture of GWS and Gaussian noise. Herein we put forward a deep learning approach based on the Swin Transformer UNet (SUNet) model to remove high-density GWS-Gaussian mixture noise from fast neutron images. The improved denoising model utilizes a customized loss function for training, which combines perceptual loss and mean squared error loss to avoid grid-like artifacts caused by using a single perceptual loss. To address the high cost of acquiring real fast neutron images, this study introduces Monte Carlo method to simulate noise data with GWS characteristics by computing the interaction between gamma rays and sensors based on the principle of GWS generation. Ultimately, the experimental scenarios involving simulated neutron noise images and real fast neutron images demonstrate that the proposed method not only improves the quality and signal-to-noise ratio of fast neutron images but also preserves the details of the original images during denoising.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.13 no.1
• /
• pp.21-34
• /
• 2015

Source term analysis should be carried out to prepare the decommissioning of the nuclear power plant. In the planning phase of decommissioning, the classification of decommissioning wastes and the cost evaluation are performed based on the results of source term analysis. In this study, the verification of MCNP/ORIGEN-2 model is carried out for preliminary source term calculation for Wolsung Unit 1. The inventories of actinide nuclides and fission products in fuel bundles with different burn-up were obtained by the depletion calculation of MCNPX code modelling the single channel. Two factors affecting the accuracy of source terms were investigated. First, the neutron spectrum effect on neutron induced activation calculation was reflected in one-group microscopic cross-sections of relevant radio-isotopes using the results of MCNP simulation, and the activation source terms calculated by ORIGEN-2 using the neutron spectrum corrected library were compared with the results of the original ORIGEN-2 library (CANDUNAU.LIB) in ORIGEN-2 code package. Second, operation history effect on activation calculation was also investigated. The source terms on both pressure tubes and calandria tubes replaced in 2010 and calandria tank were evaluated using MCNP/ORIGEN-2 with the neutron spectrum corrected library if the decommissioning wastes can be classified as a low level waste.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.2
• /
• pp.802-809
• /
• 2021

To cope with the increasing maintenance costs due to aging, the maintenance cost was evaluated from the perspective of asset management. The maintenance cost can be predicted based on the condition of the bridge, and the life cycle cost is used as an index. In general, the condition of a bridge has a wide distribution characteristic depending on the deterioration, load, and material characteristics. In this paper, to evaluate the effect of the bridge conditions on the life cycle cost, condition prediction models were constructed considering the service life, deterioration rate, and inspection error, which are the main variables of the bridge condition and life cycle cost calculation. In addition, condition prediction models were constructed based on the distribution of the health index to estimate the upper and lower bounds of the life cycle costs that can occur in individual bridges. Life cycle cost analysis showed that the life cycle cost differed significantly according to the condition of the bridge. Accordingly, research will be needed to increase the reliability of predicting the life cycle cost of individual bridges.