Repository logo
 

Structural Performance Monitoring Using a Dynamic Data-Driven BIM Environment

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Delgado, Juan Manuel Davila 
Butler, Liam J 
Elshafie, Mohammed ZEB 
Middleton, Campbell R 

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.

Description

Keywords

4005 Civil Engineering, 40 Engineering

Journal Title

JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Conference Name

Journal ISSN

0887-3801
1943-5487

Volume Title

32

Publisher

American Society of Civil Engineers (ASCE)
Sponsorship
Engineering and Physical Sciences Research Council (EP/L010917/1)
Engineering and Physical Sciences Research Council (EP/N021614/1)