The need to optimize investments in bridge maintenance has created a demand for improved bridge management systems (BMS). Outdated practices in bridge inspection and constant advances in information technology have also contributed to this demand. The use of Digital Twins (DT), although well established in other industries, is still incipient for asset management and structural analysis of bridges. There is a great deal of research on Building Information Modelling (BIM) for bridge inspection, but its post-construction potential is still under-explored. This study presents a state-of-the-art review of the literature on asset management for bridges using digital models such as BIM and digital twins. The review was conducting using a systematic approach. Despite the rapid increase in research on DT and the amount of existing research on BIM, several gaps remain to be addressed, such as the lack of consensus about the definition of digital twins, which has led to wrongful categorisation of digital models as DT. The complex data flow and software compatibility required to develop a functional DT have hindered the exploitation of their full potential so far. The integration of BIM post-construction to BMS and existing automation technologies can also significantly improve current practices of bridge management.

Digital Twins (DT) have become a widely discussed subject, believed to have the potential to solve various problems across different industries, including Engineering & Construction (E&C). However, there is still significant misconception concerning the definition of DT and their purpose within E&C. This study dives deep into identifying DT applications within E&C and the other prominent industries, i.e., Aerospace & Aviation, Manufacturing, Energy & Utilities, Automotive, Healthcare, Smart Cities, Oil & Gas, and Retail. The main challenges to the evolution of DT practical applications are also analyzed. A combination of literature review, multi-case study analysis, and comparative analysis compose the deployed methodology. Standardization and a maturity level classification are proposed to drive progress of the adoption of DT. The distinct aspects of the different industries and their assets are evaluated to the conclusion that DT are better employed to maintenance of structures within E&C. DT have become a well-worn topic, but the abundance of complex theoretical frameworks is met with simple or inexistent practical applications. Therefore, the novelty of this study lays in its comprehensive analysis of DT applications and real-world implementations – a departure from the often-theoretical discussions surrounding DTs.

The snow galleries along the Iron Ore railway line in northern Sweden have facedproblems in recent years due to increasingly large snow loads, and several gallerieshave been damaged. These incidents motivated an evaluation of the maximumload supported by the galleries before collapse, which is presented in this study. In2021, a monitoring system was installed in one of the main frames of two snowgalleries built in the 1950s to follow up with temperature and displacements,including a trigger that sends out a warning message when a critical load isreached. A literature review on snow loads was performed, followed bycalculations on snow distribution on the galleries based on the Eurocodes andNational Swedish Standards. Finite element 2D and 3D models were created usingAxisVM to accurately assess the efforts in the structural elements. Analysis anddiscussion are complemented by observations from site visits. It was concludedthat the critical loads supported by the galleries are lower than the requirements oftoday’s standards, but since secondary construction elements were damagedbefore the main frames reached their full capacity, no major collapse has yet takenplace. The cobweb effect (load re-distribution between the neighboring elementsin a 3D structure) influenced the behavior of the galleries in the 3D analysis and thecapacity of the main frames proved to be significantly increased compared to the2D assessment.

The use of digital twin (DT) technology within the engineering and construction (E&C) industry is valuable for practical applications in asset management of structures. Functional DT in E&C, however, are still in initial stages of development. Efforts towards standardization of concepts and procedures are necessary to build on existing knowledge and drive progress further on functional DT. This paper proposes a DT of a snow gallery, part of the Iron Ore railway in northern Sweden. The gallery was instrumented with a structural health monitoring (SHM) system that feeds data in real time to the DT, which also includes a 3D model of the gallery. The proposed methodology can be replicated to different structures and scaled for larger amounts of data. The SHM data and the 3D digital model of the snow gallery are connected in a single, integrated platform that enables improved decision-making for maintenance of the gallery. To promote clarity and progress within the field, the proposed DT’s maturity level is classified in terms of autonomy, intelligence, learning, and fidelity. The snow galleries, the SHM system, and the proposed DT are all presented and discussed, following a brief review on DT, the importance of level classification, and predictive maintenance.