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Copyright of Elektronik Industrie is the property of Hüthig GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Digital twin of the road The construction and operation of road infrastructure is currently facing enormous challenges: steadily increasing traffic, climate change, necessary maintenance work, increasingly autonomous traffic etc. At the same time, the potential of technical innovations (e. g. digitization, use of sensors, Industry 4.0) is rarely used in the road system so far. In order to enable a more sustainable, safer and more efficient construction and operation of roads in the future, a digital twin for the road of the future is under development in the Collaborative Research Center/Transregio 339. [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]

Dynamic train‐bridge compatibility: the reference method as a new form of verification Newly developed rail vehicles must be investigated regarding dynamic bridge compatibility before they are placed in service on the rail network of DB Netz AG. In this context, the dynamic effect on bridges from passing trains (train‐bridge interaction) is evaluated based on dynamic calculation results in the ultimate limit state (ULS) and in the serviceability limit state (SLS) and compared with calculated (previously static) minimum capacities of the infrastructure (resistance). In this paper, a new form of verification is presented. It makes it possible to extend the existing static capacities of the bridges by existing dynamic capacities, which usually allow higher permissible vehicle speeds in the railway network. For this purpose, computational results and database‐supported expert knowledge (fusion) from short‐ and long‐term monitoring of existing vehicles and their impact on the infrastructure are used to declare the bridge stock for these existing vehicles as operationally verified. On this basis, an applicable dynamic capacity for new vehicles can be formulated. The procedure is exemplarily shown for the ICE 3 (existing vehicle) and the new development of the BR 408 series (ICE 3neo). [ABSTRACT FROM AUTHOR]

Process development and quality assurance through interconnected structures between the digital and real worlds are often reflected in digital twins. This article summarizes current trends and developments, their special features, but also the challenges of digital twins. The report includes a selection of different new and further developments, possible applications and research projects that were exhibited at ACHEMA 2022. [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]

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]

The digitalization of processes is one of the currently dominating topics and missions in both industrial production and scientific research. In biotechnology, these efforts have enormous potential to optimize existing bioprocesses or to develop new bioprocesses for upcoming challenges. In this review, the state‐of‐art of digitalization in bioprocess engineering is considered, the terms digital twin and digital shadow are characterized, and an outlook on future Lab 4.0 concepts is given. [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]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Explainable Domain‐Specific Artificial Intelligence for Bridge Engineering and Design The use of artificial intelligence (AI) is currently being discussed and evaluated across the board in research and practice in all industries. This paper first provides the necessary background knowledge on general AI and then elaborates the necessity of developing domain‐specific AI as well as explainable AI (XAI) for the calculation and design practice in civil engineering. The role of the civil engineering domain at the interface with AI in terms of data and modeling and design philosophy is discussed. The three examples of (i) computation of Kirchhoff slabs with physics‐informed neural networks, (ii) calibration of prior models for parametric bridge design from databases, and (iii) AI‐assisted conceptual design of bridges illustrate the application of domain‐specific machine and deep learning and XAI with special focus on concrete and bridge design. In particular, physics‐informed AI (piKI) represents an alternative to established numerical methods with special consideration of available simulation and experimental data and becomes explainable and comprehensible via the use of XAI. This paves the way for the use of piKI models in civil engineering as digital twins of a structure over its life cycles. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Gefaesschirurgie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Nachrichten aus der Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Technisches Messen is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Nachrichten aus der Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)