Korean Journal of Construction Engineering and Management
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v.10
no.4
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pp.87-100
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2009
The quality of early cost estimates is critical to the feasibility analysis and budget allocation decisions for public capital projects. Various researches have been attempted to develop cost prediction models in the early stage of a construction project. However, existing studies are limited on its applicability to actual projects because they focus primarily on a specific phase as well as utilize restricted information while the amount of information collectable differs from one another along with the project stages. This research aims to develop two-staged cost estimation model for the schematic planning and preliminary design process of a construction projects, considering the available information of each phase. In the schematic planning stage where outlined information of a project is only available, the Case-Based Reasoning model is used for easy and rapid elicitation of a project cost based on the extensive database of more than 90 actual highway construction projects. Then, the representing quantity-based model is proposed for the preliminary design stage where more information on the quantities and unit costs are collectable based on the alternative routes and cross-sections of a highway project. Real case studies are used to demonstrate and validate the benefits of the proposed approach. Through the two-stage cost estimation system, users are able to hold a timely prospect to presume the final cost within the budge such that feasibility study as well as budget allocation decisions are made on effectively and competitively.
Korean Journal of Computational Design and Engineering
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v.20
no.2
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pp.182-192
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2015
In recent years, numerous studies have attempted to extract quantity data by using Building Information Modeling (BIM). In terms of open-BIM based quantity take-off at the early design stage, only few studies were conducted in the field of cost engineering. A lack of compatibility of open BIM for information exchange is postulated as the cause. The Industry Foundation Classes (IFC) extension model has been developed to accommodate the interoperability with quantity take-off software. Improvement of open BIM for quantity take-off needs exchange requirements and model guidelines. For this purpose, the quantity data of IFC models were analyzed using BIM analysis tools. This paper also provides a proposal of requirements on open BIM based quantity take-off at the early design stage. Further this study have been develop the interface system for open BIM based quantity take-off requirements with the results on this study.
The purpose of this paper is two-fold: 1) A novel algorithm in order to extract lane-related information from road images is presented; 2) Design specifications of an image processing onboard unit capable of extracting lanerelated information in real-time is also presented. Obtaining precise information from road images requires many features due to the effects of noise that eventually leads to long processing time. By exploiting a FPGA and DSP, we solve the problem of real-time processing. Due to the fact that image processing of road images relies largely on edge features, the FPGA is adopted in the hardware design. The schematic configuration of the FPGA is optimized in order to perform 3 $\times$ 3 Sobel edge extraction. The DSP carries out high-level image processing of recognition, decision, estimation, etc. The proposed algorithm uses edge features to define an Edge Distribution Function (EDF), which is a histogram of edge magnitude with respect to the edge orientation angle. The EDF enables the edge-related information and lane-related to be connected. The performance of the proposed system is verified through the extraction of lane-related information. The experimental results show the robustness of the proposed algorithm and a processing speed of more than 25 frames per second, which is considered quite successful.
Korean Journal of Construction Engineering and Management
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v.21
no.6
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pp.113-124
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2020
Social movements to improve the performance of buildings through remodeling of aging apartment houses are being captured. To this end, the remodeling construction cost analysis, structural analysis, and political institutional review have been conducted to suggest ways to activate the remodeling. However, although the method of analyzing construction cost for remodeling apartment houses is currently being proposed for research purposes, there are limitations in practical application possibilities. Specifically, In order to be used practically, it is applicable to cases that have already been completed or in progress, but cases that will occur in the future are also used for construction cost analysis, so the sustainability of the analysis method is lacking. For the purpose of this, we would like to suggest an automated estimating method. For the sustainability of construction cost estimates, Deep-Learning was introduced in the estimating procedure. Specifically, a method for automatically finding the relationship between design elements, work types, and cost increase factors that can occur in apartment remodeling was presented. In addition, Monte Carlo Simulation was included in the estimation procedure to compensate for the lack of uncertainty, which is the inherent limitation of the Deep Learning-based estimation. In order to present higher accuracy as cases are accumulated, a method of calculating higher accuracy by comparing the estimate result with the existing accumulated data was also suggested. In order to validate the sustainability of the automated estimates proposed in this study, 13 cases of learning procedures and an additional 2 cases of cumulative procedures were performed. As a result, a new construction cost estimating procedure was automatically presented that reflects the characteristics of the two additional projects. In this study, the method of estimate estimate was used using 15 cases, If the cases are accumulated and reflected, the effect of this study is expected to increase.
Korean Journal of Construction Engineering and Management
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v.13
no.3
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pp.99-108
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2012
The rough design information is only available from BIM(Building Information Model) based schematic design. So, it is difficult to obtain sufficient information for generating BOQ. Like 2D design, there are some problems that the results are depend on what the choice of cost estimator. However, the most research of BIM based cost estimation are focus on quantity takeoff, the consideration of work item for generating BOQ is insufficient. Therefore, this paper present automatic inference process of work items in a BOQ using ontology. The proposed process and ontology is validated through applying tiling construction. If the proposed process is utilized, it is expected the basis of developing generation method for consistent BOQ by resolving intervention of cost estimator's arbitrary decision.
Many activities associated with the construction and habitation of buildings are connected with issues affecting the environment such as global warming, climate change, and consumption of valuable natural resources such as fossil fuels. To minimize negative impacts on the environment, the building industry worldwide has implemented green building practices in many countries. One of the main green strategies is to reduce greenhouse gas emissions caused by residential structures because they are most substantially connected with global warming and climate change. To determine the actual quantity of green house gas emissions caused by the construction and use of a building, it is important to analyze total greenhouse gas emissions over the life cycle of buildings including construction, operation & maintenance(O&M) and demolition stages. Many studies suggest methods to calculate greenhouse gas emissions at the construction stage, but the literature addressing greenhouse gas emissions at the O & M stage is limited. A year-long study was conducted utilizing the deterioration method to calculate greenhouse gas emissions at the O & M stage of building life for condominium types of buildings in South Korea. Through this research, it is possible to analyze greenhouse gas emissions of buildings at the O & M stage, the longest span of the life cycle, and eventually help to calculate total greenhouse gas emissions over the life cycle of the building.
Journal of The Korean Digital Architecture Interior Association
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v.10
no.3
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pp.19-28
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2010
The construction projects are recently having changes in their magnitude and complexity. Therefore, the amount of information created and managed by participants over project phases is enormous and this may cause difficulties in consistent and integrated data management. Because of the change in construction projects, there is a need to apply more logical and systematic ways to deal integrated data management. For the solution to this, BIM(Building Information Modeling), a new paradigm for integrated management of the information over project life-cycle, has been seriously considered. Also, the Korean Public Procurement Service announced that project over 50 billion Korean Won should introduce BIM into procurement starting from 2012. However, the studies and development have lack on studies of applying BIM and managing the data made using BIM in pre-design and maintenance stage. In pre-design stage, the concept of schematic design model is made to support for making major decisions concerning the size, shape and cost of the project. To decide the cost for the building in this stage by making use of BIM, estimating the amount of building materials used for constructing should be preceded. In this study, the pre-design BIM is explained to gain a better understanding of its process, since this paper focused on space programming stage. Finally, the paper suggests the concept process of estimating the amount of materials in building interior finishing from selecting the type for the elements of each space made to support the client for making decisions in space programming stage based on pre-design BIM.
Spatial data integration using multiple geo-based data sets has been regarded as one of the primary GIS application issues. As for this issue, several integration schemes have been developed as the perspectives of mathematical geology or geo-mathematics. However, research-based approaches for statistical/quantitative assessments between integrated layer and input layers are not fully considered yet. Related to this niche point, in this study, spatial data integration using multiple geoscientific data sets by known integration algorithms was primarily performed. For spatial integration by using raster-based GIS functionality, geological, geochemical, geophysical data sets, DEM-driven data sets and remotely sensed imagery data sets from the Ogdong area were utilized for geological thematic mapping related by mineral potential mapping. In addition, statistical/quantitative information extraction with respective to relationships among used data sets and/or between each data set and integrated layer was carried out, with the scope of multiple data fusion and schematic statistical assessment methodology. As for the spatial integration scheme, certainty factor (CF) estimation and principal component analysis (PCA) were applied. However, this study was not aimed at direct comparison of both methodologies; whereas, for the statistical/quantitative assessment between integrated layer and input layers, some statistical methodologies based on contingency table were focused. Especially, for the bias reduction, jackknife technique was also applied in PCA-based spatial integration. Through the statistic analyses with respect to the integration information in this case study, new information for relationships of integrated layer and input layers was extracted. In addition, influence effects of input data sets with respect to integrated layer were assessed. This kind of approach provides a decision-making information in the viewpoint of GIS and is also exploratory data analysis in conjunction with GIS and geoscientific application, especially handing spatial integration or data fusion with complex variable data sets.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.17
no.4
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pp.225-242
/
2012
This is the first attempt to produce simultaneous surface current field from satellite altimeter data for the entire East Sea and to provide surface current information to users with formal description. It is possible to estimate surface geostrophic current field in near real-time because satellite altimeters and coastal tide gauges supply sea level data for the whole East Sea. Strength and location of the major currents and meso-scale eddies can be identified from the estimated surface geostrophic current field. The mean locations of major surface currents were explicated relative to topographic, ocean-surface and undersea features with schematic representation of surface circulation. In order to demonstrate the practical use of this surface current information, exemplary descriptions of annual, seasonal and monthly mean surface geostrophic current distributions were presented. In order to objectively classify surface circulation patterns in the East Sea, empirical orthogonal function (EOF) analysis was performed on the estimated 16-year (1993-2008) surface current data. The first mode was associated with intensification or weakening of the East Korea Warm Current (EKWC) flowing northward along the east coast of Korea and of the anti-cyclonic circulation southwest of Yamato Basin. The second mode was associated with meandering paths of the EKWC in the southern East Sea with wavelength of 300 km. The first and second modes had inter-annual variations. The East Sea surface circulation was classified as inertial boundary current pattern, Tsushima Warm Current pattern, meandering pattern, and Offshore Branch pattern by the time coefficient of the first two EOF modes.
PARK, JU-EUN;KIM, SOO-YUN;CHOI, BYOUNG-JU;BYUN, DO-SEONG
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.24
no.2
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pp.208-225
/
2019
To understand the mean surface circulation and surface currents in the East Sea, trajectories of surface drifters passed through the East Sea from 1991 to 2017 were analyzed. By analyzing the surface drifter trajectory data, the main paths of surface ocean currents were grouped and the variation in each main current path was investigated. The East Korea Warm Current (EKWC) heading northward separates from the coast at $36{\sim}38^{\circ}N$ and flows to the northeast until $131^{\circ}E$. In the middle (from $131^{\circ}E$ to $137^{\circ}E$) of the East Sea, the average latitude of the currents flowing eastward ranges from 36 to $40^{\circ}N$ and the currents meander with large amplitude. When the average latitude of the surface drifter paths was in the north (south) of $37.5^{\circ}N$, the meandering amplitude was about 50 (100) km. The most frequent route of surface drifters in the middle of the East Sea was the path along $37.5-38.5^{\circ}N$. The surface drifters, which were deployed off the coast of Vladivostok in the north of the East Sea, moved to the southwest along the coast and were separated from the coast to flow southeastward along the cyclonic circulation around the Japan Basin. And, then, the drifters moved to the east along $39-40^{\circ}N$. The mean surface current vector and mean speed were calculated in each lattice with $0.25^{\circ}$ grid spacing using the velocity data of surface drifters which passed through each lattice. The current variance ellipses were calculated with $0.5^{\circ}$ grid spacing. Because the path of the EKWC changes every year in the western part of the Ulleung Basin and the current paths in the Yamato Basin keep changing with many eddies, the current variance ellipses are relatively large in these region. We present a schematic map of the East Sea surface current based on the surface drifter data. The significance of this study is that the surface ocean circulation of the East Sea, which has been mainly studied by numerical model simulations and the sea surface height data obtained from satellite altimeters, was analyzed based on in-situ Lagrangian observational current data.
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