• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.4
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• pp.13-20
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• 2012

The recent advances in digital technology allow the use of BIM for integratively managing various information pertaining to an architectural structure. This can be the suitable tool for effectively utilizing the various requests of both the users and the administrators from the planning phase. In particular, planning and constructing a school facility can be challenging because it is an important learning facility where the students are required follow a set schedule. Accommodating to the various needs and requests of the users and the other related parties in the progress can be very difficult. Therefore, in order to use the BIM with the basis of data to manage the lifetime of the school facility, it is necessary to develop the specialized BIM process customized to the school facilities. Using this as the base, the BIM process specifically for school facilities should be phased in, applied, and expanded. The objective of this study is to define the scope of application and to plan for the efficient utilization of the BIM process specialized for school facilities, when conducting the project from planning phase to design development phase through the series of processes. Unlike the presently used enhancement of the visible minute details of the models, the methods to enhance the quality of information contained inside the model will be proposed. Also, the user will participate in the school facility construction. The realistic BIM application is aimed through the research for the processes for building models that will be utilized for construction and management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.129-137
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• 2016

BIM libraries for architectural projects have been developed and distributed. However, they do not define physical and logical quality control methods for individual library objects, so there are some difficulties in securing reliability of 3D library models converted from 2D drawings. Because the BIM library contents can be built by participating material and member-fabrication companies, after making individual BIM library objects, a certification process through separate quality verification is very important when delivering as-built BIM libraries. Since the BIM library should have generality for usage, it is necessary to secure the quality of BIM library objects according to consistent verification standards. Therefore, this study suggests a quality verification method for certifying a BIM library object from physical and data perspectives by comparing existing 2D drawings in the BIM libraries built based on standardized 2D drawings from MOLIT. This method could be widely used for quality verification in delivering BIM libraries by companies in the construction sector and operated with rule set data for quality verification of as-built BIM models.

• 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.

• Journal of KIBIM
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• v.8 no.1
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• pp.56-62
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• 2018

There exists no precedented case of quantity take-off, using parametric modeling, from BIM-based irregular structures. Civil 3D provides earthwork quantity take-off based on surface modeling. Generally, designers should enter data into the specification additionally after extracting quantity estimation from earthwork modeling design. The objective of this report is to suggest the method from quantity take-off to specification of BIM-based earthwork quantities. We intend to investigate earthwork take-off method by Civil3D and explain why parametric information extraction is required for quantity estimation and specification and how information of earthwork quantity based on solid and surface modeling is connected to open quantity take-off module. It is highly expected that this suggestion would be the practical methodology of earthwork quantity take-off and specification in the field of civil engineering.

• Journal of KIBIM
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• v.11 no.3
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• pp.55-66
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• 2021

Recently, Building Information Modeling(BIM) has become a hot topic in the construction industry such as quantity calculation, interference check, process management, and construction cost management. It is also trying to convert the existing 2D design to 3D design and introduce the BIM in various fields, thus, many new deliverable are being presented but there are many issues due to the lack of standard guides on the preparation and delivery criteria for such new deliverable and how to utilize performance data. Therefore, In order to develop the electronic delivery process, we analyzed the process related to the delivery of BIM digital models presented in domestic and international BIM guidelines and the delivery of products from the Korea National Railway. The analysis focused on the list of achievements, delivery process, quality review standards, and the utilization code system of the Korea National Railway through BIM guidelines and the National Railroad Service's business procedures. Based on these analysis results, it presents a plan to construct an functional module of electronic delivery.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.752-759
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• 2022

The instantiation of spaces as a discrete entity allows users to utilize BIM models in a wide range of analyses. However, in practice, their utility has been limited as spaces are erroneously entered due to human error and often omitted entirely. Recent studies attempted to automate space allocation using artificial intelligence approaches. However, there has been limited success as most studies focused solely on the use of geometric features to distinguish spaces. In this study, in addition to geometric features, semantic relations between spaces and elements were modeled and used to improve space classification in BIM models. Graph Convolutional Networks (GCN), a deep learning algorithm specifically tailored for learning in graphs, was deployed to classify spaces via a similarity graph that represents the relationships between spaces and their surrounding elements. Results confirmed that accuracy (ACC) was +0.08 higher than the baseline model in which only geometric information was used. Most notably, GCN was able to correctly distinguish spaces with no apparent difference in geometry by discriminating the specific elements that were provided by the similarity graph.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.792-799
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• 2022

Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial reality of a project site can offer crucial information to stakeholders for construction progress monitoring, error checking, and building maintenance purposes. Geometric methods for automatically converting raw scan data into BIM models (Scan-to-BIM) often fail to make use of higher-level semantic information in the data. Whereas, semantic segmentation methods only output labels at the point level without creating object level models that is necessary for BIM. To address these issues, this research proposes a hybrid semantic-geometric approach for clutter-resistant floorplan generation from laser-scanned building point clouds. The input point clouds are first pre-processed by normalizing the coordinate system and removing outliers. Then, a semantic segmentation network based on PointNet++ is used to label each point as ceiling, floor, wall, door, stair, and clutter. The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation. A region-growing segmentation algorithm paired with geometric reasoning rules is applied to group the points together into individual building elements. Finally, a 2-fold Random Sample Consensus (RANSAC) algorithm is applied to parameterize the building elements into 2D lines which are used to create the output floorplan. The proposed method is evaluated using the metrics of precision, recall, Intersection-over-Union (IOU), Betti error, and warping error.

• KIEAE Journal
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• v.15 no.5
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• pp.95-105
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• 2015

Purpose: This paper presents a framework development for BIM (Building Information Modeling)-based OOPM (Object-Oriented Physical Modeling) for Building Thermal Simulation. The framework facilitates decision-making in the design process by integrating two object-oriented modeling approaches (BIM and OOPM) and efficiently providing object-based thermal simulation results into the BIM environment. Method: The framework consists of a system interface between BIM and OOPM-based building energy modeling (BEM) and the visualization of simulation results for building designers. The interface enables a BIM models to be translated into OOPM-based BEM automatically and the thermal simulation from the created BEM model immediately. The visualization module enables the simulation results to be presented in BIM for building designers to comprehend the relationships between design decisions and the building performances. For the framework implementation, we utilized the Modelica Buildings Library developed by the Lawrence Berkeley National Laboratory as a thermal simulation solver. We also conducted an experiment to validate the framework simulation results and demonstrate our framework. Result: This paper demonstrates a new methodology to integrate BIM and OOPM-based BEM for building thermal simulation, which enables an automatic translation BIM into OOPM-based BEM with high efficiency and accuracy.

• Journal of KIBIM
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• v.10 no.2
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• pp.1-11
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• 2020

BIM(Building Information Modeling) is a salient technology for influential innovation in the construction industry. The patent network analysis is useful for suggesting the direction of technology development and exploring the research and development field. Therefore, the purpose of this study is to analyze the BIM technology structure and core technologies according to the convergence of BIM technology and market expansion. In this study, social network analysis was conducted by establishing a co-classification IPC network for the United States BIM patent. In particular, the characteristics of the major technical areas in the BIM technology network were identified through centrality analysis. G06F017/00, digital computing or data processing method, is a core technology field in the BIM network. Arrangements, apparatus or systems for transmission of digital information, H04L029/00 is an influential technology across the network. B25J009/00 for program controlled manipulators is an intermediary technology field and G06T019/00, manipulating 3D models or images for computer graphics, is an important field for technological development competitiveness.

• Journal of KIBIM
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• v.12 no.2
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• pp.12-25
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• 2022

To increase the usability of Building Information Modeling (BIM) in construction projects, it is critical to ensure the interoperability of data between heterogeneous BIM software. The Industry Foundation Classes (IFC), an international ISO format, has been established for this purpose, but due to its structural complexity, geometric information and properties are not always transmitted correctly. Recently, deep learning approaches have been used to learn the shapes of the BIM elements and thereby verify the mapping between BIM elements and IFC entities. These models performed well for elements with distinct shapes but were limited when their shapes were highly similar. This study proposed a method to improve the performance of the element type classification by using an Ensemble model that leverages not only shapes characteristics but also the relational information between individual BIM elements. The accuracy of the Ensemble model, which merges MVCNN and MLP, was improved 0.03 compared to the existing deep learning model that only learned shape information.