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Digital twins for medium span bridges – pilot project bridge Schwindegg – part 2: Asset Administration Shell The term ′digital twin′ is becoming increasingly popular in German‐speaking countries for the digital management and condition monitoring of bridges. Although standardised developments for the use of digital twins have already been initiated in industry and medicine, the first prototypes are currently being implemented in the construction industry. The digital images are typically operated in online environments that are proprietary to the project and have limited reusability. The article investigates the integration of scaling into Building Information Modelling models, which is reaching its limits due to the real‐time capability. It places existing definitions of the digital twin of the industry in the context of the construction industry. The implementation of the Isenbridge in Schwindegg as an Industry 4.0 Asset Administration Shell (AAS) is presented, building on Part 1 of this contribution. We show that an industrial, data‐driven digital twin can also be implemented technically and semantically for engineering structures. The article also presents the future challenges for evaluation and control mechanisms still to be developed for the structure. We also show a possible visualisation. The goal is to develop a syntax for the AAS' communication. [ABSTRACT FROM AUTHOR]

Image‐based acquisition and digital documentation of geometry and condition of railway bridges The continuous safety and performance of infrastructure structures is of particular importance for a modern society. The rail network becomes increasingly relevant in the context of the energy transition. Demands for resource efficiency in the construction sector will require significantly longer service lives for structures in the future. New digital maintenance strategies can make this goal achievable while reducing maintenance expenditures at the same time. This report focuses on new image‐based methods for condition assessment and digital modelling of the geometry of structures as well as damage characteristics. In particular, the permanent storage of highly accurate damage position and extent information allows the tracking of damage propagation as a basis for novel predictive maintenance strategies. Using the example of railway bridges, it is shown how high‐quality digital condition documentation is possible with the concept of digital twins. Photogrammetry is used to generate highly accurate geo‐referenced 3D building models from image data acquired by drones, for example, and AI processes are used to perform automated damage detection. The linking in a digital twin enables analyses and high‐quality documentation over the life cycle and should start with an initialization measurement on new structures. [ABSTRACT FROM AUTHOR]

Digital twin construction – process monitoring for automated control of time and cost Construction monitoring is nowadays a predominantly manual process in which construction site personnel document the processes on the construction site manually. This inefficient task results in a considerable expenditure of time and money and is highly susceptible to errors. In contrast, the rapid developments in information technology offer a wide range of possibilities, e. g. Bluetooth Low Energy (BLE) monitoring, cameras and laser scanners, to record and evaluate data in real‐time. The construction site can be mirrored by a digital twin, which stores and manages large amounts of raw data in a structured manner. Besides others, various AI‐supported processing methods are necessary to generate information and business knowledge from the raw data. The potential to enable fully automated process monitoring from this information is undeniable. Precise, automated recording of the critical features of the construction process, such as process start, process end and resources used, will form an essential foundation for optimizing the construction site in the future. This article examines the current state of the art in computer‐aided construction site monitoring. Furthermore, it presents insights gained while monitoring several construction sites. [ABSTRACT FROM AUTHOR]

Digital twins enable informed decisions through linked data Digitization in the construction industry is advancing, the topic of BIM (Building Information Modeling) is on everyone's lips, and many companies and projects are gaining their first experience with the digital working method. The processes in the life cycle of a construction facility (or use cases of digital methods) can efficiently deliver quality results when data from other sources such as schedules, documents, digital acceptance forms or from installed sensors are linked with each other. It is all about transparency and breaking down data silos. One example of this is the higher‐level management of contractually agreed customer requirements. With the help of consistently structured data models, the silos of current and future processes are overcome, thus creating end‐to‐end transparency. As a result, more data and information is available for more informed decisions and better risk management. In addition, a unified data model enables a reduction of dependencies through the software systems used – data interoperability can be better ensured in different project scenarios. This has an impact on the management of individual projects as well as comparability and control across project boundaries. To harness these added values, far from technological prerequisites, new competencies are needed to drive data‐driven ways of thinking and working among all stakeholders of a project. This can pave the way for a true digital twin in all lifecycle phases of structural assets. Efficient and informed decision‐making is a lever to meet the challenges of major changes in all areas of construction, especially also the sustainable change in transport and energy infrastructure. [ABSTRACT FROM AUTHOR]

Use cases of a digital twin bridge in operation The digital twin bridge makes an important contribution on the way to predictive life cycle management. The potentials are many, especially in the life cycle phase "operation". There, the digital twin bridge can serve as an efficient tool in terms of analyses, predictions, control and monitoring. The goal is optimized maintenance, the importance of which continues to grow in view of the current challenges for civil engineering structures. It is therefore particularly important that relevant stakeholders with their needs and requirements are involved in the conception of the digital twin bridge at an early stage. This approach is being pursued by the German Federal Highway Research Institute (BASt) in various research projects that already cover partial aspects of the digital twin and is also being continued in an ongoing project to develop an overall concept for the digital twin bridge. Possible use cases were collected and assigned to the topics of "operational processes", "maintenance planning and implementation" and "strategic life cycle management". In a workshop, the use cases were discussed and initially ranked by and with stakeholders. The results form an important basis for the elaboration of the modular overall concept of the digital twin bridge and the way into practice. [ABSTRACT FROM AUTHOR]

Structural Information Modeling – the digital transformation of building diagnostics Building diagnostics are the prerequisite for a reliable evaluation of existing structures. Often, there is a lack of specific and realistic information about the actual condition of the structure and thus the input variables for the numerical verification. In contrast to new buildings, these assumptions do not have to be estimated and covered by additional safety elements but can be reliably measured with their actual properties as well as their scatter on the existing structure. Building diagnostics offers a multitude of possibilities to realistically assess the existing structure and the condition of materials as well as structures. The digital revolution in the construction industry implies new concepts that will make it possible to use our existing structures much more efficiently and, above all, for a longer period of time. The digital twin enables the merging and linking of gigantic data of the most diverse structure and origin. This means that structural diagnostic data must also be consistently digitized, integrated into digital twins and, in combination with the other inventory and condition data, prepared for the user in an intuitive manner. This methodical approach of Structural Information Modeling forms the basis for a more realistic and reliable assessment of existing structures. [ABSTRACT FROM AUTHOR]

Digital twin for the automated production of precast concrete elements Using precast concrete elements in construction has many advantages, such as cost and planning reliability, precision, and efficiency. In most cases, the production of precast concrete elements is not fully automated. There are many manual work steps that prevent a further increase in productivity. The basis for full automation is the use of information and communication technology. A digital twin as an integrated data model is necessary for this. This paper examines how the combination of Building Information Modeling with methods from the context of Industry 4.0, which enable largely self‐organized and decentralized production, can provide the basis for the complete automation and networking of all production steps. Based on the administration shell, which implements the digital twin in Industry 4.0, a suitable description for digital twins of precast concrete modules is being developed by developing data and interaction models for industrialized production. [ABSTRACT FROM AUTHOR]