• Construction Engineering and Management
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• v.23 no.5
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• pp.53-60
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• 2022

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.387-388
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• 2023

PHC pile head cutting is an essential work in pile foundation construction. However, since the work has labor-intensive characteristics, there are problems such as productivity and safety. So in previous study PHC pile one-cutting head cutting automation equipment was developed to solve this problem. However, it has been investigated as a limitation that checking the cutting position of the PHC pile can be challenging in place where a rotary laser leveler cannot irradiate cutting position, as the sensing unit of the developed automated equipment utilizes an optical method. Therefore, the objective of this study is to delvelop a GNSS-based methodology for sensing the cutting position of PHC piles to overcome the limitations of the optical method and to examine its feasibility for field application. If the proposed methodology is applied to the construction site, it is expected that the convenience and productivity of the PHC pile cutting position sensing work will be improved.

• Construction Engineering and Management
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• v.24 no.3
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• pp.13-15
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• 2023

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.180-181
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• 2021

This study compared and analyzed the fluidity, compressive strength, and unit weight characteristics of mortar using bottom ash aggregates as part of a study to develop alternative aggregates

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.215-216
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• 2021

In this study, the liquidity and compressive strength characteristics of concrete mixed with self-healing capsules were analyzed as part of the study to improve the problems of cracks and maintenance of concrete structures.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.27-28
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• 2023

This study compared and analyzed the fluidity, compressive strength, and carbonation resistacne of amorphous metal fiber reinforced mortar according to the PCC mixing ratio as part of a study to improve the self-healing performance and tensile performance of concrete structures.

• Journal of Engineering Education Research
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• v.11 no.3
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• pp.70-77
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• 2008

This study investigates the level of the construction student's familiarity and interest in sustainability, their attitude toward sustainability, and the factors for bringing student's attitude toward sustainability. To accomplish the main objectives, this study employes a survey instrument created and developed by the authors. This is a descriptive and correlation study using responses from construction students at the Building Construction department at Virginia Polytechnic Institute and State University in Virginia. The results of descriptive statistics and multiple regression using SPSS version 16 present the following findings. Construction students perceive that they have a relatively high level of familiarity with sustainable construction and sustainability. Secondly, student's attitude toward sustainability is changed based on several factors such as sustainable construction courses, a professor who is interested in sustainability, their interest in the construction industry, university initiative, and the level of sustainability for student's learning facilities. Finally, the construction student's attitude toward sustainability can be improved by offering sustainable construction courses in construction programs, having professors who teach and research sustainability, and adopting sustainable initiatives at the university level such as campus recycling and various sustainable programs.

• Journal of KIBIM
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• v.11 no.4
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• pp.53-62
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• 2021

The successful implementation of Scan-to-BIM automation depends on the entire process from scanning of buildings, including indoor facilities and furniture, to generating BIM models. However, the conventional Scan-to-BIM process requires a lot of time, manpower, and cost for the manual generation of BIM models including indoor objects. To solve this problem, this study applied a Scan-to-BIM automation process using a deep learning model and parametric algorithm to an existing building, Kangwon Fire Service Academy. To improve the accuracy of the BIM model, after object data was extracted from the scan data, the data was corrected according to actual object-specific conditions. As a result, the accuracy of the BIM model created by the proposed Scan-to-BIM automation process was 91% compared to the actual area of the construction drawings. In addition, it was confirmed that the BIM objects were automatically generated for 10 object classes.

• Computational Structural Engineering
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• v.36 no.3
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• pp.17-22
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• 2023

• Magazine of RCR
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• v.17 no.4
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• pp.41-47
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• 2022