Title
Towards networks of predictive twins in the Built Environment
Author
Adriaanse, A.M.
Borsboom, W.A.
Roef, R.
Publication year
2021
Abstract
The construction and infrastructure sector faces enormous challenges, such as the eve of a major replacement and renovation task for existing civil infrastructure.1 The sector is also moving towards circular construction (goal: circular by 2050) and the existing built environment must be energy-neutral by 2050.2. A widely supported view is that these challenges and the associated adaptations to the built environment can only be realised through the intensive use of advanced digital solutions.3 These make it possible to increase the productivity of the sector and to innovate much faster. But how are digital solutions really going to make a difference to these challenges? TNO sees a crucial role for predictive digital twins, or ‘predictive twins’. 4 These are predictive digital replicas of physical structures such as bridges, tunnels, homes and offices. With these twins, the future behaviour and use of structures and networks of structures can be predicted and influenced. This step towards predictive twins is crucial for proactive decision-making on structures and networks of structures based on data, learning predictive models and simulations.
Subject
Architecture and Building
Buildings and Infrastructures
2015 Urbanisation
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TNO identifier
952940
Publisher
TNO
Document type
other