• 한국BIM학회 논문집
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• 제12권4호
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• pp.19-31
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• 2022

With the development of 3D-based CAD (Computer Aided Design), attempts at freeform building design have expanded to small and medium-sized buildings in Korea. However, a standardized system for continuous utilization of shape data and BIM conversion process implemented with 3D-based NURBS is still immature. Without accurate review and management throughout the Freeform building project, interference between members occurs and the cost of the project increases. This is very detrimental to the project. To solve this problem, we proposed a continuous utilization process of 3D shape information based on BIM parameters. Our process includes algorithms such as Auto Split, Panel Optimization, Excel extraction based on shape information, BIM modeling through Adaptive Component, and BIM model utilization method using ID Code. The optimal cutting reference point was calculated and the optimal material specification was derived using the Panel Optimization algorithm. With the Adaptive Component design methodology, a BIM model conforming to the standard cross-section details and specifications was uniformly established. The automatic BIM conversion algorithm of shape data through Excel extraction created a BIM model without omission of data based on the optimized panel cutting reference point and cutting line. Finally, we analyzed how to use the BIM model built for automatic conversion. As a result of the analysis, in addition to the BIM utilization plan in the general construction stage such as visualization, interference review, quantity calculation, and construction simulation, an individual management plan for the unit panel was derived through ID data input. This study suggested an improvement process by linking the existing research on atypical panel optimization and the study of parameter-based BIM information management method. And it showed that it can solve the problems of existing Freeform building project.

• Spatial Information Research
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• 제20권2호
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• pp.1-11
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• 2012

기존의 건축계획 및 설계과정에서는 건축물 내 외부의 공간감을 확인하기 위해 건물모형을 제작하였으나 건물모형은 비교적 많은 제작 시간과 노력이 들며 건물의 내부 정보를 파악하기에 어려움이 따른다. 이를 보완하기 위해 기존 설계, 계획 과정과 그에 대한 가시화 방법으로써 CAD툴을 사용하여 건물 모형으로는 파악하기 어려운 건물 내부 정보를 가시화 할 수 있었지만, 건물모형에서 확인할 수 있는 부피감을 확인하기에는 부족함이 존재한다. 기본적으로 CAD는 설계에 목적을 두고 만들어진 프로그램이며 일반적인 가시화 환경인 2차원 모니터 화면상에서 3차원 건물을 보여주게 되므로 공간에 대한 인지적 몰입감을 만족시키기에는 부족하다. 본 논문에서는 BIM 형상정보 데이터를 일련의 소프트웨어로 가공하여 증강현실 컨텐츠로 변환하는 과정을 소개한다. 이는 건축계획 및 설계과정에서 형상정보가 수정될 경우 최종 가시화까지 소요되는 비용과 시간을 단축시킬 수 있다. 또한 BIM 형상정보를 증강현실기법을 이용하여 3차원 인지공간에서 가시화함으로써 3차원 건물의 내 외부 공간정보를 분석하기가 용이하다. 또한 건물의 내 외부 정보를 증강현실 환경에서 효과적으로 조작할 수 있도록 건축 요소의 제거, 슬라이스컷 등 다양한 인터랙션을 제안한다.

• 한국전산구조공학회논문집
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• 제13권1호
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• pp.115-127
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• 2000

본 논문에서는 건물 구조 통합 구조설계 시스템의 구현을 위한 설계모델인 설계 객체 모델을 제안하였다. 건물 구조에 대한 구조 설계 정보를 단계(초기구조설계, 해석, 상세설계) / 계층(시스템, 서브시스템, 콤퍼넌트)별로 분류 모델링한 후, 제시된 요구조건에 대한 세부관점별 해결방법을 고려하여 설계 객체 모델을 개발하였다. 이와 같은 방법론을 통하여 시스템 구현을 고려한 설계 객체 모델의 체계적 분석과 모델링이 가능하였다. 제시된 설계 객체 모델은 계획 설계 측면의 설계정보 표현을 통하여 효율적인 설계정보의 관리가 가능하며, 위상 설계 객체에 의한 공간상 구조부재의 인식이 용이하고, 해석 관련 설계정보를 이해하기 용이한 표현으로 관리할 수 있게 한다.

• Journal of Construction Engineering and Project Management
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• 제5권4호
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• pp.12-15
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• 2015

Size of building has a direct relationship with building cost, energy use and space maintenance cost. Therefore, minimizing building size during a project development is of paramount importance against such wastes. However, incautious reduction of building size may result in crowded space, and therefore harms the functionality despite the fact that building is supposed to satisfactorily support users' activity. A well-balanced design solution is, therefore, needed at an optimum level that minimizes building size in tandem with providing sufficient space to maintain functionality. For such design, architects and engineers need to be informed accurate and reliable space-use information. We present in this paper a conceptual framework of an agent-based space-use prediction simulation system that provides individual level space-use information over time in a building in consideration of project specific user information and activity schedules, space preference, ad beavioural rules. The information will accordingly assist architects and engineers to optimize space of the building as appropriate.

• 한국측량학회지
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• 제39권5호
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• pp.297-311
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• 2021

Around the world, there is an increasing interest in Digital Twin cities. Although geospatial data is critical for building a digital twin city, currently-established spatial data cannot be used directly for its implementation. Integration of geospatial data is vital in order to construct and simulate the virtual space. Existing studies for data integration have focused on data transformation. The conversion method is fundamental and convenient, but the information loss during this process remains a limitation. With this, standardization of the data model is an approach to solve the integration problem while hurdling conversion limitations. However, the standardization within indoor space data models is still insufficient compared to 3D building and city models. Therefore, in this study, we present a comparative analysis of data models commonly used in indoor space modeling as a basis for establishing a generic indoor space feature model. By comparing five models of IFC (Industry Foundation Classes), CityGML (City Geographic Markup Language), AIIM (ArcGIS Indoors Information Model), IMDF (Indoor Mapping Data Format), and OmniClass, we identify essential elements for modeling indoor space and the feature classes commonly included in the models. The proposed generic model can serve as a basis for developing further indoor feature models through specifying minimum required structure and feature classes.

• 대한원격탐사학회지
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• 제23권3호
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• pp.199-209
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• 2007

Traditionally, aerial images have been used as main sources for compiling topographic maps. In recent years, lidar data has been exploited as another type of mapping data. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. Lidar provides direct information about heights of object surfaces but have limitations with respect to boundary localization. Considering the characteristics of the sensors, this paper proposes an approach to extracting buildings from lidar and aerial imagery, which is based on the complementary characteristics of optical and range sensors. For detecting building regions, relationships among elevation contours are represented into directional graphs and searched for the contours corresponding to external boundaries of buildings. For generating building models, a wing model is proposed to assemble roof surface patches into a complete building model. Then, building models are projected and checked with features in aerial images. Experimental results show that the proposed approach provides an efficient and accurate way to extract building models.

• Safety and Health at Work
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• 제15권1호
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• pp.33-41
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• 2024

Background: Dust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. Methods: First, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. Results: The results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m³. The Monte Carlo model is mainly influenced by the dust concentration in the workplace of building materials enterprises and is suitable for scenarios where the dust concentration in the workplace of the building materials enterprises is relatively uniform and the average dust concentration is less than or equal to 6mg/m³. Conclusion: ART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m³; whereas, The Monte Carlo model is the best when dust concentration is homogeneous and average dust concentration is < 6 mg/m³.

• 교육시설
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• 제15권6호
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• pp.39-46
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• 2008

The main purpose of this study is to find out the strengths and weaknesses of the application of BIM to the educational facilities. All the data information is drawn from the integrated design process which links various fields such as energy simulation, structure analyzation, and etc, and it is applied to the project combined as one data set. Moreover, we analyze the possible problems of the data exchange that can happen as collaborating with various fields while working on the project, and we present its solutions and the futher studies on this matter of a project.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.73-74
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• 2023

The purpose of this study is to derive the cause of the quantity difference and present the considerations when take-off rebar quantity based on BIM model by comparing the quantity of rebar based on BIM model with 2D drawing. This research was limited to take-off the quantity of rebars in the building frame work, and after take-off the quantity of rebars by 3D modeling the 2D drawing of the target building with Revit, the quantity difference was compared with 2D-based software. Therefore, when take-off the quantity of rebars based on the BIM model, instead of take-off the existing 2D-based quantity premium proportion, according to general structural consider development length, lap splice length, covering thickness, reinforcing bars and spacing. In the future, this study is expected to contribute to improving the accuracy of BIM-based frame construction quantity take-off.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.485-492
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• 2020

Information on the energy consumption of buildings that can be obtained through conventional methods is limited. Therefore, this study aims to develop a model that can support decision making about building facility management through digital transformation technologies. Through the IoT sensor, the building's energy data and indoor air quality data are collected, and the monitored data is visualized through the ELK Stack and produced as a dashboard. In addition, the target building is photographed with a 360-degree camera and maps using a tool to create a 360-degree tour. Using such digital transformation technologies, users of buildings can obtain various information in real time without visiting buildings directly. This can lead to changes in actions or actions for building management, supporting facility management decisions, and consequently reducing building energy consumption.