• Journal of KIBIM
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• v.8 no.4
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• pp.23-33
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• 2018

Recently, the industry actively adopts the cutting-edge technologies of the fourth industrial revolution and uses them to enhance the productivity and service of mass-customization. The manufacturing industry is creating new processes and business models by achieving digital transformations through a lean start-up approach aimed at achieving the highest customer satisfaction with minimal resources. Although attempts are made to manufacture the building by introducing the latest technology in architecture, it is applied sporadically, not as an integrated system, in the entire phase of the architectural project. This paper analyzes the changes in the construction industry through the application of core technologies of the fourth industrial revolution. Design processes are analyzed for the digital transformation of the construction industry by case study of advanced architectural design practice. A novel design concept model 'Architectural lean startup' is proposed by combining the architectural process and the lean start up method. Through the design of the bus stop based on the architectural lean startup concept, it is confirmed that the designer repeats the 'Generate-Test-Analysis' to develop the design and generate the final result.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.143-152
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• 2012

As the Public Procurement Service announced the compulsory of BIM adaption in every public construction from 2016, the importance of BIM is increasing. Besides, automatic code checking takes significance in terms of the quality control for BIM based design. In this study, rule-sets were defined for Act on the Promotion and Guarantee of Access for the Disabled, the Aged, and Pregnant Women to Facilities and Information. Three analytic steps were suggested to shortlist the objective clauses from the entire code; the frequency analysis using project reviews for architectural code compliance, the clause analysis on quantifiability, and the analysis for model checking possibilities. The shortlisted clauses were transformed into the machine readable rule-set definition. A case study was conducted to verify the adaptiveness and consistency of rule-set definitions. In future study, it is required the methodologies of selecting objective clauses to be specified and its indicators to be quantified. Also case studies should be performed to determine the pre-conditions in modeling and to check interoperability issues and other possible errors in models.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.307-314
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• 2012

IFC-based representation method of part library for superstructure module of modular steel bridge is proposed. The library is capable of efficiently offering and exchanging part information in process of manufacture, assembly, design, and construction of modular steel bridge. Entities, representing physical part information in IFC model, are matched semantically with parts of the superstructure module for representation of part information with IFC model. Either types of matched entities are applied in order to verify the role of each part, or new types are defined as a user-defined types. In addition, assembly system has been classified and defined into 4 levels of LoD(Level of Detail) to provide appropriate part information efficiently from the part library in each step of the process. Then, new property is defined for representing the LoD information with IFC Model. Finally, IFC-based test library of modular steel bridge is generated by applying the matched entities and entity types to the actual the superstructure module of modular steel bridge.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.9-18
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• 2021

Recently, the rapid proliferation, introduction, and application of the fourth industrial revolution technology has emerged as a trend in the construction market. Building Information Model (BIM) technology is a multidimensional information system that forms the basis of the fourth industrial revolution technology. The river sector utilizing this information-based system is also being actively reviewed, for example, the current measures for maintenance. In recent years, active research and current work should be done to reflect the need for river experts to introduce BIM into the river field. In addition, the development of tools and support software for establishing various information systems is essential for the activation of facility maintenance information systems reflecting advanced technology and to establish and operate management plans. A study on the maintenance of river facilities involves using existing drawings to build a three-dimensional (3D) information model, check the damage utilizing it, and inform it, and utilize it as the data for maintenance reinforcement. This study involved determining a method to build a river facility without the existing information system and using the property maintenance information with 3D modeling to provide a more effective and highly utilized management plan to check maintenance operations and manage damages.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.393-400
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• 2015

This study proposes a method to create and combine a superstructure module by parametric modeling, in order to improve the production efficiency of information model for modular steel bridge superstructure that can be used in planning, design and construction phase. Compound classification was performed in order to derive elements to apply the parametric modeling, and according to assembly condition, the classified elements were grouped into 13 types. In addition, three assembly conditions were derived for production of stable superstructure through combination of superstructure module, which is a production unit for modular steel bridge factory. Parameter that reflects assembly condition in compound shape when producing superstructure module through parametric modeling was deducted. Superstructure module compounds were produced according to type and parameter using interface generation based on Building Information Model(BIM) software that was developed in this study. The superstructure module produced reflects information to combine into a superstructure. To verify this, information model based on Industry Foundation Classes(IFC) was built and confirmed the application in production of superstructure by identifying the reflected property information.

• Journal of KIBIM
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• v.11 no.3
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• pp.12-21
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• 2021

Existing real estate markets are monopolized because they are capital intensive and have information asymmetry. However, with the advent of the Fourth Industrial Revolution, technology is converging in various industries based on information technology (IT), and the real estate market is also developing a new field called "PropTech". According to this trend, new PropTech technologies are emerging in various real estate services sectors in Korea, but the electronic contract system, which accounts for the largest portion of the real estate industry, is still cited as a complex identification process and long processing time. Therefore, in this paper, we propose an improvement plan for the current electronic contract system through the introduction of blockchain technology, which is drawing attention with the development of PropTech, and explore the possibility of introduction by producing an experimental model of blockchain-applied electronic contract system in a programming language.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.107-118
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• 2021

Scan-to-BIM can be precisely mod eled by measuring structures with Light Detection And Ranging (LiDAR) and build ing a 3D BIM (Building Information Modeling) model based on it, but has a limitation in that it consumes a lot of manpower, time, and cost. To overcome these limitations, studies are being conducted to perform semantic segmentation of 3D point cloud data applying deep learning algorithms, but studies on how segmentation result changes depending on learning data are insufficient. In this study, a parametric study was conducted to determine how the size and track type of railroad tunnels constituting learning data affect the semantic segmentation of railroad tunnels through deep learning. As a result of the parametric study, the similar size of the tunnels used for learning and testing, the higher segmentation accuracy, and the better results when learning through a double-track tunnel than a single-line tunnel. In addition, when the training data is composed of two or more tunnels, overall accuracy (OA) and mean intersection over union (MIoU) increased by 10% to 50%, it has been confirmed that various configurations of learning data can contribute to efficient learning.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.920-927
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• 2009

Many schedule delays and cost overruns in interior construction are caused by a lack of understanding in detailed and complicated interior works. To minimize these potential impacts in interior construction, a systematic approach for project managers to detect discrepancies at early stages and take corrective action through use of visualized data is required. This systematic implementation is still challenging: monitoring is time-consuming due to the significant amount of as-built data that needs to be collected and evaluated; and current interior construction progress reports have visual limitations in providing spatial context and in representing the complexities of interior components. To overcome these issues, this research focuses on visualization and computer vision techniques representing interior construction progress with photographs. The as-planned 3D models and as-built photographs are visualized in a 3D walk-through model. Within such an environment, the as-built interior construction elements are detected through computer vision techniques to automatically extract the progress data linked with Building Information Modeling (BIM). This allows a comparison between the as-planned model and as-built elements to be used for the representation of interior construction progress by superimposing over a 3D environment. This paper presents the process of representing and detecting interior construction components and the results for an ongoing construction project. This paper discusses implementation and future potential enhancement of these techniques in construction.

• Journal of KIBIM
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• v.10 no.3
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• pp.54-62
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• 2020

There is growing consensus among planners and policymakers that brownfield remediation has positive impacts on neighborhoods in terms of housing prices, public health, and environmental quality. However, there is a limited understanding of how brownfield redevelopments spatially affect neighborhood housing turnover and stability. This paper addresses the spatial impacts of brownfield redevelopments on neighboring housing turnover in Cuyahoga County, Ohio. This study examines housing turnover before and after the remediation of brownfield sites countywide and in housing submarkets stratified by household income. Based on housing sales data between 1996 and 2007, the extended Cox Hazard model with the difference-in-difference approach is employed to clarify the causal relationships between brownfield redevelopments and neighboring housing turnover. Additionally, along with the results of the previous study examining impacts of brownfield remediation on nearby housing prices, this paper estimates the change of neighborhood stability due to brownfield redevelopments based on both attributes of housing prices and turnovers.

• Journal of KIBIM
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• v.10 no.2
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• pp.21-28
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• 2020

As the number of aging bridges increases, more studies are being conducted on developing effective and reliable methods for the assessment and maintenance of bridges. With the advancement in new sensing systems and data learning techniques through AI technology, there is growing interests in how to evaluate bridges using these advanced techniques. This paper presents a CNN(Convolution Neural Network) deep learning based technique for evaluating the damage existence and for estimating the damage location in PSC bridges using static strain data. Simulation studies were conducted to investigate the proposed method with error analysis. Damage was simulated as the reduction in the stiffness of a finite element. A data learning model was constructed by applying the CNN technique as a type of deep learning. The damage status and its location were estimated using data set built through simulation. It was assumed that the strain gauges were installed in a regular interval under the PSC bridge girders. In order to increase the accuracy in evaluating damage, the squared error between the intact and measured strains are computed and applied for training the data model. Considering the damage occurring near the supports, the results of error analysis were compared according to whether strain data near the supports were included.