1887

Abstract

Summary

Western cities manage their buried utilities through a large number of distinctive owners. This current fragmentation of the utility sector, and the poor registration of utility locations in the past has created an underground puzzle containing data pieces with different formats, accuracies, and completeness. We argue that virtual technologies address this problem but require that basic modelling conditions be fulfilled first. To structure this discussion, we use literature on Building Information Modelling (BIM) technologies in construction. BIM supports construction management tasks through the use of object-based parametric design models. This enables 3D and 4D design reviews as well as multi-stakeholder scheduling and planning. Furthermore, BIM integration with geospatial data enables the on-site use of construction data for facility management. Based on the experiences from our lab, we explain that the utility sector should train engineers in 3D utility mapping, and develop 3D/4D underground data models for design, scheduling, and maintenance. Such 3D models consequently integrate with other geospatial data to support risk analysis, construction site decision making, and on-site Virtual Reality applications. Our lab currently works on these needs together with industry. It seeks collaboration with other partners that also contribute to BIM for buried infrastructure.

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/content/papers/10.3997/2214-4609.201902540
2019-09-08
2021-04-21
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References

  1. Azhar, S., Nadeem, A., Mok, J., & Leung, B.
    (2008). Building Information Modeling (BIM): A new paradigm for visual interactive modeling and simulation for construction projects. In Proc., First International Conference on Construction in Developing Countries (Vol. 1, pp. 435–46).
    [Google Scholar]
  2. Ding, L., Zhou, Y., & Akinci, B.
    (2014). Building Information Modeling (BIM) application framework: The process of expanding from 3D to computable nD.Automation in construction, 46, 82–93.
    [Google Scholar]
  3. Döner, F., Thompson, R., Stoter, J., Lemmen, C., Ploeger, H., van Oosterom, P., & Zlatanova, S.
    (2010). 4D cadastres: First analysis of legal, organizational, and technical impact—With a case study on utility networks.Land Use Policy, 27(4), 1068–1081.
    [Google Scholar]
  4. Eastman, C., Teicholz, P., Sacks, R., & Liston, K.
    (2011). BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors.John Wiley & Sons.
    [Google Scholar]
  5. ter Huurne, R. B. A.
    (2019). Modelling utilities by developing a domain ontology (PDEng dissertation). Enschede: University of Twente.
    [Google Scholar]
  6. Messner, J., Anumba, C., Dubler, C., Goodman, S., Kasprzak, C., Kreider, R., Leicht, R., Saluja, C., Nizic, N.
    BIM Project Execution Planning Guide - Version 2.0, The Pennsylvania State University, University Park, PA, USA, 2011.
    [Google Scholar]
  7. Metje, N., Atkins, P., Brennan, M., Chapman, D., Lim, H., Machell, J., … & Rogers, C.
    (2007). Mapping the Underworld–State-of-the-art review.Tunnelling and underground space technology, 22(5–6), 568–586.
    [Google Scholar]
  8. olde Scholtenhuis, L. L., Hartmann, T., & Dorée, A. G.
    (2016). Testing the Value of 4D Visualizations for Enhancing Mindfulness in Utility Reconstruction Works.Journal of Construction Engineering and Management, 142(7), 04016015.
    [Google Scholar]
  9. olde Scholtenhuis, L. L., den Duijn, X., & Zlatanova, S.
    (2018). Representing geographical uncertainties of utility location data in 3D.Automation in construction, 96, 483–493.
    [Google Scholar]
  10. Park, J., Kim, B., Kim, C., & Kim, H.
    (2011). 3D/4D CAD applicability for life-cycle facility management.Journal of computing in civil engineering, 25(2), 129–138.
    [Google Scholar]
  11. Racz, P., van Buiten, M., & Doree, A. G.
    (2016). To dig or not to dig: how to determine the number and location of test trenches. In H. J. P.Timmermans (Ed.), Proceedings of the 13th international conference on design & decision support systems in architecture and urban planning, 27–28 June 2016, Eindhoven, The Netherlands (pp. 1–16).
    [Google Scholar]
  12. Talmaki, S., Dong, S., Kamat, V.
    Geospatial databases and augmented reality visualization for improving safety in urban excavation operations Proc., Construction Research Congress2010, ASCE, Reston, VA (2010), pp. 91–101
    [Google Scholar]
  13. Vahdatikhaki, F., & Hammad, A.
    (2015). Risk-based look-ahead workspace generation for earthwork equipment using near real-time simulation.Automation in Construction, 58, 207–220.
    [Google Scholar]
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