• Journal of KIBIM
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• v.5 no.4
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• pp.53-62
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• 2015

Korea has been at the forefront of green growth initiatives. In 2008, the government declared the new vision toward 'low-carbon society and green growth'. The government subsidies and Feed-in Tariff (FIT) increased domestic usage of solar power by supplying photovoltaic housing and photovoltaic generation systems. Since 2000, solar power industry has been the world's fastest growing source with the annual growth rate of 52.5%. Especially, BIPV(Building Integrated Photovoltaic) systems are capturing a growing portion of the renewable energy market due to several reasons. BIPV consists of photovoltaic cells and modules integrated into the building envelope such as a roof or facades. By avoiding the cost of conventional materials, the incremental cost of photovoltaics is reduced and its life-cycle cost is improved. When it comes to atypical building, numerous problems occur because PV modules are flat, stationary, and have its orientation determined by building surface. However, previous studies mainly focused on improving installations of solar PV technologies on ground and rooftop photovoltaic array and developing prediction model to estimate the amount of produced electricity. Consequently, this paper discusses the problem during a planning and design stage of BIPV systems and suggests the method to select optimal design of the systems by applying the national strategy and economic policies. Furthermore, the paper aims to develop BIM tool based on the engineering knowledge from experts in order for non-specialists to design photovoltaic generation systems easily.

• Journal of Construction Engineering and Project Management
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• v.8 no.4
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• pp.1-24
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• 2018

In the last decade, the use of Building Information Modeling (BIM) as a new technology has been applied with traditional Computer-aided design implementations in an increasing number of architecture, engineering, and construction projects and applications. Its employment alongside construction management, can be a valuable tool in helping move these activities and projects forward in a more efficient and time-effective manner. The traditional stakeholders, i.e., Owner, A/E and the Contractor are involved in this BIM system that is used in almost every activity of construction projects, such as design, cost estimate and scheduling. This article extracts major features of the application of BIM from perspective of participating BIM components, along with the different phrases, and applies to them a logistic analysis using a fuzzy performance tree, quantifying these phrases to judge the effectiveness of the BIM techniques employed. That is to say, these fuzzy performance trees with fuzzy logic concepts can properly translate the linguistic rating into numeric expressions, and are thus employed in evaluating the influence of BIM applications as a mathematical process. The rotational fuzzy models are used to represent the membership functions of the performance values and their corresponding weights. Illustrations of the use of this fuzzy BIM performance tree are presented in the study for the uninitiated users. The results of these processes are an evaluation of BIM project performance as highly positive. The quantification of the performance ratings for the individual factors is a significant contributor to this assessment, capable of parsing vernacular language into numerical data for a more accurate and precise use in performance analysis. It is hoped that fuzzy performance trees and fuzzy set analysis can be used as a tool for the quality and risk analysis for other construction techniques in the future. Baldwin's rotational models are used to represent the membership functions of the fuzzy sets. Three scenarios are presented using fuzzy MEAN, AND and OR gates from the lowest to intermediate levels of the tree, and fuzzy SUM gate to relate the intermediate level to the top component of the tree, i.e., BIM application final performance. The use of fuzzy MEAN for lower levels and fuzzy SUM gates to reach the top level suggests the most realistic and accurate results. The methodology (fuzzy performance tree) described in this paper is appropriate to implement in today's construction industry when limited objective data is presented and it is heavily relied on experts' subjective judgment.

• Korean Journal of Construction Engineering and Management
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• v.15 no.2
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• pp.53-61
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• 2014

Previous studies reveal the need for a tool to cost estimation of building design in early design stages. This paper proposes an internal finishes cost model tool to address this need. The tool allows users to evaluate the functionality, economics and quality of finishes concurrently with high-rise building design. Lack of information in the early stages of the project enables a relatively accurate estimates of work to raise up. Measurements are automatically extracted from simple design information and profile driven estimates are revised in real-time. The data model uses a flexible unit rate system that can easily be extended to other estimate dimensions such as mix-use building surcharge rate estimation. The approach illustrated in this paper is applicable to BIM tool conceptual estimation that support for massing purposes other than the one chosen for this study.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.24-32
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• 2012

Reinforced Concrete is the most dominant structure type for buildings in South Korea. Reinforced Concrete is one of materials having the most cost and quantity at construction projects. It is important to manage concrete quantity so that the total project cost is not affected due to underestimate or overestimate of its quantity. Generally the concrete quantity is taken-off based on the volume of the space inside forms without subtracting volumes of rebar embedded, which cannot be considered to make quite accurate results. Resource waste and extra cost due to over or under estimate of quantity occur since they cannot estimate accurate quantity at practices. Therefore, the objective of this paper is to analyze the effect of the volume for rebars embedded in reinforced concrete members. By comparing the quantity based on the existing method with the one from BIM data, it was found that about 1~2% of quantity discrepancy was observed while the typical concrete waste rate is 1 % at the current practice.

• Korean Journal of Construction Engineering and Management
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• v.14 no.6
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• pp.14-21
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• 2013

While a detailed cost estimation utilizes the comprehensive quantity information obtained from a complete drawing and specification, an approximate cost estimation heavily relies on the subjective decisions. This phenomenon is because the approximate estimation is usually conducted in early stage of the construction phase where the drawing and specification are not available. This study developed a roadway construction cost estimation system which enables users to estimate the approximated cost of the project in early stage. The system identifies the variation of the construction costs due to the road route change using a cased based reasoning(CBR) method. Overall the system is expected to improves the accuracy and effectiveness of the estimation process, because it would provide users with increased accessability and consistent results in early stage of the project which leaded to the increased work transparency.

• Spatial Information Research
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• v.18 no.3
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• pp.13-22
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• 2010

Due to the frequent gales and typhoons by anomaly climates and its subsequent loss of life and property, the importance of the research estimating wind load is being emphasized when structure is designed. It is necessary to measure geographical information exactly to estimate topographic factor of wind speed because the increase of topographic factor of wind speed means the increase of wind velocity and the increase of wind velocity has an influence on wind load proportionate to a square. Therefore, the accurate and reasonable estimation method of topographic factor of wind speed is presented in this study using ArchiCAD, an architectural BIM(Building Information Modeling) software. When the structure subjected to wind load is designed, reasonability and economic performance of design will be more improved by using the proposed method.

• Journal of KIBIM
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• v.13 no.2
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• pp.29-36
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• 2023

This study explores the potential of utilizing video-based data analysis and machine learning techniques to estimate the number of occupants within a building. The research methodology involves developing a sophisticated counting system capable of detecting and tracking individuals' entry and exit patterns. The proposed method demonstrates promising results in various scenarios; however, it also identifies the need for improvements in camera performance and external environmental conditions, such as lighting. The study emphasizes the significance of incorporating machine learning in architectural and urban planning applications, offering valuable insights for the field. In conclusion, the research calls for further investigation to address the limitations and enhance the system's accuracy, ultimately contributing to the development of a more robust and reliable solution for building occupancy estimation.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.433-436
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• 2013

This study suggests IFC-based bridge information modeling methods and its application model in BIM environment. Data model extension for bridge structure was achieved using user-defined property sets based on IFC framework. First, identification information was added. Bridge members are identified through physical and spatial semantic information added as property sets. Instances for semantic information were assigned according to standardized rules. Second, CO2 related factors were added for application information model. It can play a role to calculate and manage the quantity of CO2 emission. Third, properties for temporary structure to estimate and manage the construction cost were added. Finally, we investigated proposed methods through implementing the application information model of bridges.

• Journal of the Korea Institute of Building Construction
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• v.10 no.6
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• pp.49-60
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• 2010

Cost Estimating allows each entity in a construction project to plan, distribute, and control its required construction cost for the project. However, existing 2D design based estimating has problems, such as inaccuracy and inefficiency caused by missing, duplicated, or erroneous calculations. In this situation, current estimations for school facilities have more difficulties in forecasting construction costs due to an inadequate work breakdown structure for BOQ (Bill of Quantity) and insufficient guidelines for Basis of Estimate. In this study, therefore, an effort was made to increase the efficiency of estimating for school facilities by applying a 3D modeling based BIM tool to quantity and cost estimates. In addition, this study suggested a reasonable work breakdown structure for BOQ that was appropriate when 3D modeling was applied, and verified it through a case study. The authors tried to provide a BIM-based estimating method for school facilities to obtain greater accuracy and efficiency by having more information in an earlier stage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.320-330
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• 2020

Fire is difficult to achieve good performance in image detection using deep learning because of its high irregularity. In particular, there is little data on fire detection in underground utility facilities, which have poor light conditions and many objects similar to fire. These make fire detection challenging and cause low performance of deep learning models. Therefore, this study proposed a fire detection model using deep learning and estimated the performance of the model. The proposed model was designed using a combination of a basic convolutional neural network, Inception block of GoogleNet, and Skip connection of ResNet to optimize the deep learning model for fire detection under underground utility facilities. In addition, a training technique for the model was proposed. To examine the effectiveness of the method, the trained model was applied to fire images, which included fire and non-fire (which can be misunderstood as a fire) objects under the underground facilities or similar conditions, and results were analyzed. Metrics, such as precision and recall from deep learning models of other studies, were compared with those of the proposed model to estimate the model performance qualitatively. The results showed that the proposed model has high precision and recall for fire detection under low light intensity and both low erroneous and missing detection capabilities for things similar to fire.