• Title/Summary/Keyword: 빅데이터 프로젝트

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Recent Research Trends Analysis of Building Information Modeling using WordCloud through Comparison of Korean and International Journals (워드클라우드를 이용한 국내·외 BIM 연구 동향 분석)

  • Seo, Min-Goo;Lee, Ung-Kyun
    • Journal of the Korea Institute of Building Construction
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    • v.19 no.1
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    • pp.95-103
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    • 2019
  • Introduction and use of Building Information Modeling(BIM) in construction projects have increased steadily over the past few years. However, the level of domestic BIM utilization is still tenuous compared to the international scene. Therefore, this study aims to present the possible directions for BIM research through an analysis of research literatures in Korea as well as in foreign countries. Papers on BIM were collected for this study from Korea and foreign countries for the field of architecture, and analyses and comparisons were performed by year and field. Further, the research patterns were analyzed using WordCloud, which is one of the popular big data techniques. From the analysis, it is found that the design field still constitutes the largest component of research, but the construction field is actively developing as well. In addition, it is realized that domestic BIM research continues to grow on collaboration and environment-friendly methodologies since 2012; it is also demonstrated that foreign BIM research has undergone changes in research trends every year including recently, and is progressing actively. Therefore, this study concludes that it is necessary to actively conduct research in the field of Industry Foundation Class(IFC) in the future. The results of this study can further be used as reference data for conducting BIM studies in Korea in the future.

Flow field simulation and structural optimization design of cyclone separator based on Fluent (플루언트(Fluent) 기반의 사이클론 분리기의 유동장 시뮬레이션 및 구조 최적화 설계)

  • Gu Haiqin;Byung-Won Min
    • Journal of Internet of Things and Convergence
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    • v.10 no.5
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    • pp.73-85
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    • 2024
  • In recent years, China has been committed to promoting energy-saving and emission-reduction measures across various industries. In the steel production process, wet dust removal technology is widely adopted. However, the existing dust removal equipment, particularly the cyclone separator, suffers from insufficient dewatering efficiency, leading to a "rain" phenomenon during waste gas emission, which in turn causes secondary environmental pollution. The design of the guide vane wheel is crucial for enhancing the dewatering efficiency of the cyclone separator. Therefore, this study, based on fluid mechanics and flow field analysis theories, utilizes the FLUENT software to simulate and analyze the blade angle and flow area of the guide vane wheel. By combining the flow field analysis and simulation results with the specific parameters of the equipment, the structure of the cyclone separator's guide vanes was optimized and applied to actual production. Practice has proven that the optimized cyclone separator significantly improved dewatering efficiency and effectively reduced the rain phenomenon around the chimney, thereby enhancing environmental quality. The research of this project is conducive to the later application of artificial intelligence, the Internet of Things, big data, cloud computing, and other technologies in the 5G+ smart steel factory of the steel industry. It lays the foundation for using digital twin technology to carry out 3D modeling of the plant area, in order to facilitate the reappearance and simulation of the entire production process.