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와플 형상을 가지는 프리캐스트 프리스트레스트 콘크리트 슬래브의 구조성능
허석재(Heo Seok-Jae),조승호(Cho Seung-Ho),노영숙(Roh Young-Sook),박태원(Park Tae-Won),이상현(Lee Sang-Hyun),정란(Chung Lan) 대한건축학회 2010 大韓建築學會論文集 : 構造系 Vol.26 No.1
Precast prestressed concrete provides high-quality structural elements, construction efficiency, and saving in time and overall cost of investment. Precast Prestressed Concrete had been widely used during 1990's specially those for apartment buildings. Despite of all the advantages of Precast Concrete, domestic demand was decreased due to technical difficulties for consistent quality control and maintenance problems. However precast prestressed concrete structure have become prevalent in the large parking garage and complex sales industry in recent years. The main object of this study is to investigate structural performance of Waffle Slab which was developed at our research center to improve connection problems. Experimental parameters are the number of prestressing wires and with/without truss girder on slab for flexural performance test. Also test parameter are the stirrup intervals(150㎜, 200㎜, 250㎜) and with/without truss girder for shear performance. A total of 14 full-scale specimens were manufactured and waffle slab size is 1.98m?10.80m. Increasing number of prestressing steel wire provides significant increase of the flexural strength but it causes brittle failure mode. In case of using truss girder, structural performance was improved due to increase of bond strength between waffle slab and topping concrete. Shear capacity test showed that the stirrup interval of 150㎜ specimen exhibited more brittle behavior than those of 200mm or 250㎜ specimens. Proper regulations of the number of steel wires and stirrup intervals are necessary for ensuring ductile behavior of waffle slab.
허석재 ( Heo¸ Seokjae ),정란 ( Chung¸ Lan ) 한국건축시공학회 2021 한국건축시공학회 학술발표대회 논문집 Vol.21 No.2
The development of artificial intelligence in the field of construction and construction is revitalizing. The performance and development techniques of artificial intelligence are changing rapidly, but if you look at the cases of domestic construction sites, they are using technologies from 5 to 7 years ago. It is right to follow a stable method in consideration of commercialization, but the previous AI development method requires more manpower and time to develop than the current technology. In addition, in order to actively utilize artificial intelligence technology, customized artificial intelligence is required to be applied to ever-changing changes in construction sites. it is the reality As a result, even if good AI technology is secured at the construction site, it is reluctant to introduce it because there is no advantage in terms of time and cost compared to the existing method to apply it only to some processes. Currently, an AI technique with a faster development process and accurate recognition has been developed to cope with a fluid situation, so it will be important to understand and introduce the rapidly changing AI development method.
랜드마크 완성 이후 초고층구조물에 대한 일반시민의 인식현황
허석재 ( Heo Seok Jae ),이용훈 ( Lee Yong Hun ),정란 ( Lan Chung ) 한국구조물진단유지관리공학회 2018 한국구조물진단유지관리공학회 학술발표대회 논문집 Vol.22 No.1
This study is the result of the survey on perception and anxiety of high - rise buildings in the general public. As a result of the survey, there was insufficient change in awareness before the construction of high - rise buildings such as landmarks was insufficient (before 2015). However, half of the citizens who felt uneasy that high-rise buildings were likely to collapse due to external influences were close. The anxiety was mainly due to the information of the press or the Internet. It is thought that the cause of anxiety comes from touching negative opinions about the high-rise buildings.
허석재 ( Heo¸ Seokjae ),이상현 ( Lee¸ Sanghyun ),이성원 ( Lee¸ Seungwon ),김명훈 ( Kim¸ Myunghun ),정란 ( Chung¸ Lan ) 한국건축시공학회 2021 한국건축시공학회 학술발표대회 논문집 Vol.21 No.2
The process before the model learning stage in AI R&D can be subdivided into data collection/cleansing-data purification-data labeling. After that, according to the purpose of development, it goes through a stage of verifying the model by performing learning by using the algorithm of the artificial intelligence model. Several studies describe an important part of AI research as the learning stage, and try to increase the accuracy by changing the structure and layer of the AI model. However, if the refinement and labeling process of the learning data is tailored only to the model format and is not made for the purpose of development, the desired AI model cannot be obtained. The latest research reveals that most AI research failures are the failure of the learning data rather than the structure of the AI model. analyzed.