TY - JOUR
T1 - Digital Twins for civil engineering
T2 - 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2021
AU - Gunner, S.
AU - Voyagaki, E.
AU - Gavriel, G.
AU - Carhart, N.
AU - MacDonald, J.
AU - Tryfonas, T.
AU - Taylor, C.
AU - Pregnolato, M.
N1 - Funding Information:
This work was supported by the Engineering and Physical Sciences Research Council (ESPRC) LWEC (Living With Environmental Change) Fellowship (EP/R00742X/2); UK Collaboratorium for Research in Infrastructure & Cities (UKCRIC): Urban Observatories (EP/P016782/1);UKCRIC City Observatory Research platfOrm for iNnovation and Analytics (CORONA) (EP/R013411/1). The authors gratefully acknowledge: CSBT, Trish, AMP, COWI
Funding Information:
ACKNOWLEDGMENTS This work was supported by the Engineering and Physical Sciences Research Council (ESPRC) LWEC (Living With Environmental Change) Fellowship (EP/R00742X/2); UK Collaboratorium for Research in Infrastructure & Cities (UKCRIC): Urban Observatories (EP/P016782/1);UKCRIC City Observatory Research platfOrm for iNnovation and Analytics (CORONA) (EP/R013411/1). The authors gratefully acknowledge: CSBT, Trish, AMP, COWI
Publisher Copyright:
© 2021 International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII. All rights reserved.
PY - 2021
Y1 - 2021
N2 - Society is dependent on aging infrastructure, which usually operates outside its expected life. Replacing this infrastructure is often an unviable option due to its cost and disruption. A structure's operational life might be extended if the features of its aging are better understood, enabling preventive maintenance to compensate. Digital Twins (the continuous comparison between sensor measurements and a mathematical model) are one way of enabling this sort of data-driven decision making. However, despite the possibilities for this technology, its take up amongst industry has been slow, in part because infrastructure managers are unsure of how the technology will support them. This work develops a methodological framework to enhance this uptake in the field of systems engineering and the system development life cycle, using the developed knowledge to inform how an operational Digital Twin should be created. The requirements capture is the most important part of any system design development process. We present a Digital Twin development method, grounded firmly in a thorough requirements capture, and illustrate how those requirements inform many of the later design decisions. We then present our method through a case study of the Clifton Suspension Bridge, UK. Our method provides a series of actionable steps, the completion of which will facilitate the creation of a Digital Twin able to support operational decisions. By fulfilling the requirements of infrastructure managers, we hope to encourage the uptake of the technology.
AB - Society is dependent on aging infrastructure, which usually operates outside its expected life. Replacing this infrastructure is often an unviable option due to its cost and disruption. A structure's operational life might be extended if the features of its aging are better understood, enabling preventive maintenance to compensate. Digital Twins (the continuous comparison between sensor measurements and a mathematical model) are one way of enabling this sort of data-driven decision making. However, despite the possibilities for this technology, its take up amongst industry has been slow, in part because infrastructure managers are unsure of how the technology will support them. This work develops a methodological framework to enhance this uptake in the field of systems engineering and the system development life cycle, using the developed knowledge to inform how an operational Digital Twin should be created. The requirements capture is the most important part of any system design development process. We present a Digital Twin development method, grounded firmly in a thorough requirements capture, and illustrate how those requirements inform many of the later design decisions. We then present our method through a case study of the Clifton Suspension Bridge, UK. Our method provides a series of actionable steps, the completion of which will facilitate the creation of a Digital Twin able to support operational decisions. By fulfilling the requirements of infrastructure managers, we hope to encourage the uptake of the technology.
KW - Bridge Management
KW - Decision Support
KW - Digital Twin
KW - Finite Element Model
KW - Resilience
KW - Structural Health Monitoring
UR - http://www.scopus.com/inward/record.url?scp=85128350948&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85128350948
SN - 2564-3738
VL - 2021-June
SP - 1561
EP - 1566
JO - International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII
JF - International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII
Y2 - 30 June 2021 through 2 July 2021
ER -