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BIM Geometry Cache Structure for Data Streaming with Large Volume

대용량 BIM 형상 데이터 스트리밍을 위한 캐쉬 구조

  • Kang, Tae-Wook (Korea Institute of Civil Engineering and Building Technology)
  • Received : 2017.07.20
  • Accepted : 2017.09.15
  • Published : 2017.09.30

Abstract

The purpose of this study is to propose a cache structure for processing large-volume building information modeling (BIM) geometry data,whereit is difficult to allocate physical memory. As the number of BIM orders has increased in the public sector, it is becoming more common to visualize and calculate large-volume BIM geometry data. Design and review collaboration can require a lot of time to download large-volume BIM data through the network. If the BIM data exceeds the physical free-memory limit, visualization and geometry computation cannot be possible. In order to utilize large amounts of BIM data on insufficient physical memory or a low-bandwidth network, it is advantageous to cache only the data necessary for BIM geometry rendering and calculation time. Thisstudy proposes acache structure for efficiently rendering and calculating large-volume BIM geometry data where it is difficult to allocate enough physical memory.

본 연구의 목적은 물리적 메모리 할당이 어려운 대용량 BIM(Building Information Modeling) 형상 데이터를 처리하기 위한 캐쉬(cache) 구조를 제안한다. 조달청 등 공공기관에서 BIM 발주가 많아짐에 따라 대용량 BIM 형상 데이터를 가시화하고, 계산해야 하는 경우가 많아지고 있다. 규모가 크고 복합적인 시설물의 경우, 렌더링 및 계산해야하는 형상 수가 많아 사용자가 BIM 모델을 검토하고, 단면을 확인하는 데 어려움을 겪는 경우가 있다. 예를 들어, 설계, 검토 협업 시, 대용량 BIM 데이터를 네트워크를 통해 전달받아야 할 경우, 다운로드에 많은 시간이 걸릴 수 있고, 물리적 여유 메모리 한계를 넘어가면, 에러로 가시화나 형상정보 추출이 불가능할 수도 있다. 물리적 메모리가 부족하거나 대역폭이 적은 네트워크 상에서 대용량 BIM 데이터를 활용하기 위해서는, BIM 형상 렌더링 및 계산 시점에 필요한 데이터만 메모리로 캐쉬(cache) 처리하는 것이 유리하다. 이 연구는 물리적 메모리 할당이 어려운 대용량 BIM 형상 데이터를 효과적으로 렌더링하고 계산하기 위한 BIM 형상 캐쉬 구조를 제안한다.

Keywords

References

  1. T. W. Kang, C. H. Hong, "A Study on the Lightweight BIM Shape Format(LBSF) Structure Development to Represent the Large Volume BIM Geometry Objects based on GIS as the Viewpoint of the Building Facility Management", Korea Spatial Information Society, vol. 21, no. 3, pp. 79-87, 2013. DOI: https://doi.org/10.12672/ksis.2013.21.3.079
  2. G. I. Du, C. J. H, E. D. Kim, J. M. Lee, "Extracting Building Element Geometry from BIM/IFC Physical Files, Computational Structural Engineering Institutes of Korea", vol. 22, no. 2, pp. 163-172, 2009.
  3. J. H. Jung, S. A. Kim, "Study on the Lightweighting & Automation of Data Exchange by Semantic-Filtering Method in the BIM-based Collaborative Design Process In the initial step of BIM based architectural design process, workloads are increased & the decision making process becomes more complex than those of the convent", Architectural Institute of Korea, vol. 30, pp. 71-78, 2014. DOI: https://doi.org/10.5659/JAIK_PD.2014.30.10.71
  4. J. Y. Na, C. H. Hong, A Study on the Weight Lightening Algorithm of 3-Dimensional Large Object based on Spatial Data LOD, Korea Spatial Information Society, vol. 21, no. 6, pp. 1-9, 2013. DOI: http://dx.doi.org/10.12672/ksis.2013.21.6.001
  5. Redmond, A., Hore, A., Alshawi, M., & West, R, Exploring how information exchanges can be enhanced through Cloud BIM. Automation in construction, 24, pp. 175-183, 2012. DOI: https://doi.org/10.1016/j.autcon.2012.02.003
  6. Nopachinda, S., Ergan, S. Challenges in Converting Building Information Models into Virtual Worlds for FM Operations and User Studies in the Built Environment.
  7. Jianping, Z., Zhang Yang, Z. X. Methodology of 3D geometric modeling and model conversion of IFC-based BIM. Journal of Information Technology in Civil Engineering and Architecture, vol. 1, no. 1, pp. 40-50, 2009.