• Journal of KIBIM
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• v.11 no.3
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• pp.67-74
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• 2021

An IFC file is dependent on the IFC schema. Because of this relationship, most IFC-using software reads and interprets the IFC File by employing an early binding method, which uses a standard IFC schema. In the case of most open sources, early binding methods using standard IFC schema have a problem that they cannot express extra information of IFC File out of extended IFC schema. Also, in the case of previous studies, they suggested schema extension, such as adding attribute information to the schema, rather than the interpretation of IFC File. This study research on method of extracting shape and attribute information was conducted by analyzing the IFC File produced through the Port schema, which is an extended IFC schema. Three objects were created using the reference relationship between the Port schema definition and the IFC entity, and, at the end, the three objects were combined into one object. It has been confirmed that the shape and property data were express properly while delivering the combined object to the viewer. The process is possible because of the method of matching IFC schema and IFC File, which is dependent on IFC schema but not early binding method. However, this method has some drawbacks, such that contemporaneously generated many objects consume many memory spaces. Future research to investigate that issue further is needed.

• Korean Journal of Computational Design and Engineering
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• v.10 no.2
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• pp.121-132
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• 2005

There have been several efforts for the investigation of the formal development team which was formed in the IAI to develop a common 2D standard specification between ISO/STEP and IAI/IFC since 2002. As a result, a drafting model has been included in the IFC2.x2 model. However, to be used actively in the construction practice for construction drawing exchange, the IFC model should be extended to the paper space for multiple views, drawing output, and delivery of drawings. Therefore, in this paper, the methodology of relating STEP and IFC has been investigated and schema extension of paper space(drawing sheet, presentation view, view pipeline), complex entity(leader), and dimension(associative) have been achieved. The resulting, IFC model will enable a basic harmonization with KOSDIC. SCADEC, and STEP-CDS by retaining the current IFC architecture. In addition, IT systems for the construction industry can be beneficial from the developed data model.

• Journal of KIBIM
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• v.14 no.2
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• pp.35-49
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• 2024

IFC, a neutral standard data model for BIM, ensures data interoperability across BIM applications but struggles with adapting to diverse construction standards across countries and regions. In practice, the standard IFC schema does not include the entity and attribute information necessary for reviewing Korean Construction Standards. To overcome this, this study developed an extended IFC schema that incorporates design and construction standards data specifically for bridge. The extended IFC schema defines entities for representing types of bridges, structures, and elements, and Psets for containing relevant standards information. This schema is customized to be compatible with both Korean Design Standards (KDS) and Korean Construction Specifications (KCS). Additionally, based on the extended IFC schema, a specialized extension module was developed, capable of embedding design and construction standards data by element within IFC Physical File. Through this module, the necessary design and construction standards were inserted into specific elements.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1198-1199
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• 2012

국내에서는 수량산출정보의 전자적인 교환, 납품 등의 활용을 위한 자료구조 및 파일포맷 등을 규격화 하여 디지털 수량산출정보 교환표준을 개발하였다. 국외에서는 IFC 국제표준을 통해 BIM 발주시 데이터 납품 포맷으로 IFC를 활용하고 있으며 건축분야를 중심으로 공사비 정보의 표준 개발이 이루어 지고 있다. 이에 본 논문에서는 디지털 수량산출정보 교환표준의 Type 및 Element와 IFC 국제표준의 공사비 정보 Entity를 비교분석하여 국내 토목분야 실정에 부합하는 공사비 분야 정보모델 표준개발의 기반자료로 활용하고자 한다.

• 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 Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1195-1203
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• 2014

Since IFC (Industry Foundation Classes) 4 is based on the representation of 3D elements for an architecture project, and does not define standardized shapes for civil projects such as roads, bridges, and tunnels etc, it has limitations in securing interoperability for exchanging a shape information model for the civil projects. Besides, since road facilities have a linear reference, which is modeled along the center alignment, it is difficult the designers to create a standardized 3D road model. The aim of this study is to configure structure elements and their attribute for a road in the perspective of 3D design for developing a shape information model for the road. To solve these issues, this study analyzes the design documents, which consist of a road design handbook, guide, specifications and standards, and then extract shape elements and their attributes of road structures. Such shape elements are defined as an entity item and we review a hierarchical structure of a road shape defined by a virtual road model. The detailed elements and their attributes can be utilized as a 3D shape information model for constructing BIM (Building Information Modeling) environment for Infrastructures. Besides, it is expected that the suggested items will be utilized as a base data for extending to IFC for a road subdividing the detailed shapes, types and attributes for road projects.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.78-88
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• 2017

With the growing use of BIM in the AEC industry, various new applications are being developed to meet these specific needs. Such developments have increased the importance of Industry Foundation Classes, which is the international standard for sharing BIM data and thus ensuring interoperability. However, mapping individual BIM objects to IFC entities is still a manual task, and is a main cause for errors or omissions during data transfers. This research focused on addressing this issue by applying novelty detection, which is a technique for detecting anomalies in data. By training the algorithm to learn the geometry of IFC entities, misclassifications (i.e., outliers) can be detected automatically. Two IFC classes (ifcWall, ifcDoor) were trained using objects from three BIM models. The results showed that the algorithm was able to correctly identify 141 of 160 outliers. Novelty detection is thus suggested as a competent solution to resolve the mapping issue, mainly due to its ability to create multiple inlier boundaries and ex ante training of element geometry.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.277-288
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• 2021

Building information modeling (BIM) element to industry foundation classes (IFC) entity mappings need to be checked to ensure the semantic integrity of BIM models. Existing studies have demonstrated that machine learning algorithms trained on geometric features are able to classify BIM elements, thereby enabling the checking of these mappings. However, reliance on geometry is limited, especially for elements with similar geometric features. This study investigated the employment of relational data between elements, with the assumption that such additions provide higher classification performance. Neural structured learning, a novel approach for combining structured graph data as features to machine learning input, was used to realize the experiment. Results demonstrated that a significant improvement was attained when trained and tested on eight BIM element types with their relational semantics explicitly represented.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.301-312
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• 2017

Quality evaluation and control represent increasingly important concerns for construction quality management. There is an evident need for a standard data model to be used as the basis for computer-aided quality management. This study focuses on how to realize evaluation of construction quality based on BIM and database technology. In this paper, the reinforced concrete main structure is taken as an example, and the BP neural network evaluation model is established by inquiring current construction quality acceptance specification and evaluation standard. Furthermore, IFC standard is extended to integrate quality evaluation information and realize the mapping of evaluation information in BIM model, contributing to the visualization and transfer sharing of evaluation information. Furthermore, the conceptual entity model is designed to build quality evaluation database, and this paper select MySQL workbench system to achieve the establishment of the database. This study is organized to realize the requirement of visualization and data integration on construction quality evaluation which makes it more effective, convenient, intuitive, easy to find quality problems and provide more comprehensive and reliable data for the quality management of construction enterprises and official construction administratiors.

• Journal of KIBIM
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• v.11 no.3
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• pp.22-33
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• 2021

In order to maximize the use of BIM, all data related to individual elements in the model must be correctly assigned, and it is essential to check whether it corresponds to the IFC entity classification. However, as the BIM modeling process is performed by a large number of participants, it is difficult to achieve complete integrity. To solve this problem, studies on semantic integrity verification are being conducted to examine whether elements are correctly classified or IFC mapped in the BIM model by applying an artificial intelligence algorithm to the 2D image of each element. Existing studies had a limitation in that they could not correctly classify some elements even though the geometrical differences in the images were clear. This was found to be due to the fact that the geometrical characteristics were not properly reflected in the learning process because the range of the region to be learned in the image was not clearly defined. In this study, the CRF-RNN-based semantic segmentation was applied to increase the clarity of element region within each image, and then applied to the MVCNN algorithm to improve the classification performance. As a result of applying semantic segmentation in the MVCNN learning process to 889 data composed of a total of 8 BIM element types, the classification accuracy was found to be 0.92, which is improved by 0.06 compared to the conventional MVCNN.