A fiber optics enriched Digital Twin for assessment of reinforced concrete structures
Paper i proceeding, 2021

This paper presents the results of SensIT, an ongoing research initiative at Chalmers University of Technology aimed at developing a digital twin concept to improve the asset management strategies of reinforced concrete infrastructure. The developed concept relies on data collected from distributed optical fiber sensors (DOFS), which are then analysed to extract relevant features, such as deflections and crack widths, that can be used as indicators of the structural performance. Thereafter, intuitive contour plots are generated to deliver critical information about the element's structural condition in a clear and straightforward manner. Last, both raw and analysed data are integrated into a collaborative web application where information can be readily accessed, and results can be visualized directly onto a 3D model of the element. The concept has been tested on a large-scale reinforced concrete beam subjected to flexural loading in laboratory conditions.

Distributed optical fiber sensing

Assessment

Digital twin

Crack monitoring

Rayleigh backscattering

Performance indicators

Reinforced concrete

Författare

Carlos Gil Berrocal

Chalmers, Arkitektur och samhällsbyggnadsteknik, Konstruktionsteknik

Ignasi Fernandez

Chalmers, Arkitektur och samhällsbyggnadsteknik, Konstruktionsteknik

Rasmus Rempling

Chalmers, Arkitektur och samhällsbyggnadsteknik, Konstruktionsteknik

IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs

382-390

IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs
Ghent, Virtual, Belgium,

SensIT – Sensorstyrd molnbaserad förvaltningsstrategi av infrastruktur

WSP Sverige, 2018-07-01 -- 2020-08-31.

Microsoft Research, 2018-07-01 -- 2020-08-31.

Trafikverket (2018/27871), 2018-07-01 -- 2020-08-31.

NCC AB, 2018-07-01 -- 2020-08-31.

Thomas Concrete Group, 2018-07-01 -- 2020-08-31.

Ämneskategorier

Annan data- och informationsvetenskap

Systemvetenskap

Datavetenskap (datalogi)

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Senast uppdaterat

2021-11-27