This thesis deals with asset management of structures through Building Information Modelling (BIM) and Digital Twins.

Background: Current inspection and management processes for civil structures are time-consuming and can even be inaccurate. There is an increasingly high potential to improve these processes through recent advances in technology. Digital Twins offer a common platform to these technologies, so they can interact and be used to their optimal performance. Other industries have significantly advanced in the development of Digital Twins, however, in the construction industry there are still many gaps and room for improvement.

Aim and objectives: The main aim of this project was to investigate the status of Digital Twins in the construction industry and propose a methodology for a Digital Twin for asset management of structures. The three immediate objectives sought are (i) Perform a literature review to establish the current practice with digital twins, in both construction and other industries, and what are the gaps for asset management of structures; (ii) Participate in a pilot experimental program that yields data to a potential digital twin prototype; and (iii) Define a methodology for a digital twin for asset management of structures which fills the identified gaps.

Methods of investigation: A literature review was performed and served as basis for the development of a methodology for a digital twin. A pilot experimental program was defined and performed, and its results were used for BIM and Finite Element (FE) models. A webapp was also created using Autodesk Forge and Java programming language, andthe BIM model was uploaded into it.

Results: The literature review provided insight into the maturity level of digital twins, as well as on bridge inspection, maintenance and monitoring, BIM, facility and asset management, and Bridge Management Systems (BMS). A methodology to achieve a digital twin for asset management was proposed, and the conducted experimental program yielded data results to be used in future research.

Conclusion: There has been significant progress in technology to improve structural assessment and analysis, however, their full potential is still under-explored. A digital twin created in a common data environment can provide a platform for these technologies to improve efficiency of current practices. Nonetheless, the construction industry is still significantly behind other industries such as aerospace and automotive.