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Structural performance monitoring using a dynamic data-driven BIM environment

Davila Delgado, J. M.; Butler, L.J.; Brilakis, I.; Elshafie, M.Z.E.B; Middleton, C.R.

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Authors

Manuel Davila Delgado Manuel.Daviladelgado@uwe.ac.uk
Associate Professor - AR/VR Development with Artificial Intelligence

L.J. Butler

I. Brilakis

M.Z.E.B Elshafie

C.R. Middleton



Abstract

Structural health monitoring data has not been fully leveraged to support asset management due to a lack of effective integration with other datasets. A Building Information Modelling (BIM) approach is presented to leverage structural monitoring data in a dynamic manner. The approach allows for the automatic generation of parametric BIM models of structural monitoring systems that include time-series sensor data; and it enables data-driven and dynamic visualisation in an interactive 3D environment. The approach supports dynamic visualisation of key structural performance parameters, allows for the seamless updating and long-term management of data, and facilitates data exchange by generating Industry Foundation Classes (IFC) compliant models. A newly-constructed bridge near Stafford, UK, with an integrated fibre-optic sensor based monitoring system was used to test the capabilities of the developed approach. The case study demonstrated how the developed approach facilitates more intuitive data interpretation, provides a user-friendly interface to communicate with various stakeholders, allows for the identification of malfunctioning sensors thus contributing to the assessment of monitoring system durability, and forms the basis for a powerful data-driven asset management tool. In addition, this project highlights the potential benefits of investing in the development of data-driven and dynamic BIM environments.

Citation

Davila Delgado, J. M., Butler, L., Brilakis, I., Elshafie, M., & Middleton, C. (2018). Structural performance monitoring using a dynamic data-driven BIM environment. Journal of Computing in Civil Engineering, 32(3), https://doi.org/10.1061/%28ASCE%29CP.1943-5487.0000749

Journal Article Type Article
Acceptance Date Oct 3, 2017
Online Publication Date Feb 9, 2018
Publication Date May 1, 2018
Deposit Date Feb 15, 2019
Publicly Available Date Mar 28, 2024
Journal Journal of Computing in Civil Engineering
Print ISSN 0887-3801
Publisher American Society of Civil Engineers
Peer Reviewed Peer Reviewed
Volume 32
Issue 3
DOI https://doi.org/10.1061/%28ASCE%29CP.1943-5487.0000749
Public URL https://uwe-repository.worktribe.com/output/868639
Publisher URL https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000749
Related Public URLs https://www.repository.cam.ac.uk/handle/1810/276220
Additional Information Additional Information : This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000749

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