A promising approach is the usage of formal query languages. Selection and filtering data for the user’s needs is a well-understood task in computer science, and various approaches are available. However, in an unprocessed state, these models are of limited suitability for performing engineering tasks as the amount and structure does not match the domain-specific and purpose-oriented views. The emerging models are highly structured, and instance files entail large amounts of data. To create a comprehensive description of a planned building, information from different sources must be combined, specified and regularly updated by the project’s stakeholders. The use of models enables the streamlining of workflows, and the included virtual construction increases the quality of the final product, the building. With the rising adoption of Building Information Modeling (BIM) in the AEC sector, computational models supersede traditional ways of information provision based on textual documents and two-dimensional drawings. This approach to damage information processing from the perspective of structural analysis is then validated in different case studies. The latter has the advantage that interpretation steps can be individually separated into either a structural analysis or a damage information model or a combination of both. The need for usercontrolled interpretation steps is identified and the developed prototype thus allows interaction at subsequent model stages. The common interoperability format, the Industry Foundation Class (IFC), and processes in these domains are further assessed. First, domain concepts are derived from the back-end tasks: structural analysis, damage modeling, and life-cycle assessment. Since the involved large datasets are only efficiently processed in an automated manner, the implementation of the complete workflow from damage and building data to structural analysis is targeted in this work. This approach sets two further requirements: availability of structural bridge information and a standardized storage for interoperability with subsequent analysis tools. This way, transformation to structural analysis is enabled. relating the damage artifacts to building components. However, the knowledge gain results from processing this information in a structural context, i.e. Automated imagebased inspections of the structural surface provide valuable data to extract quantitative information about deteriorations, such as crack patterns. In conjunction with the improved methods of monitoring damage and degradation processes, the interest in reliability assessment of reinforced concrete bridges is increasing in recent years.

Allplan bridge 2019