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On October 29th the workshop corresponding to the mid-term conference of BIM4EEB (Acronym of BIM Based Toolkit for Efficient rEnovation in Buildings, Horizon Project under grant agreement N. 820660 ) project was held during the Sustainable Places 2020 event. The main focus of the workshop was a general introduction of the project combined with vertical insights on the single tools that have been developed or are still in development. BIM4EEB grows from simple consideration: according to a BPIE analysis on EPC data, about 97% of building stock, currently not in A level, must be upgraded to achieve 2030 decarbonization objectives. As the biggest energy consumers, buildings consume about 40% of energy and they are responsible for 36% of CO2—they are strategic in order to reach the set of environmental goals and subjected to renovation and refurbishment during their lifecycle according to a specific schedule. Refurbishment becomes the crucial point of sustainability not only in construction but also in the environment in general for the coming years. The BIM4EEB project focuses on implementing a complete BIM (Building Information Modelling)-based toolkit to be adopted in the renovation of existing residential buildings to make the flow of information efficient, to enhance communication and data transfer decreasing intervention working time while improving building performances, quality, and comfort for inhabitants. The platform that controls all the tools developed for the best performance of renovation is BIMMS (Acronym of Building Information Modelling Management System platform), namely a management system linked to an operational and multifunctional toolkit for different AEC stakeholders, offering tools for increasing the adoption of BIM in renovation businesses based on an interoperable flow of information. During the workshop, six development tools have been explored in addition to the BIM Management System: BIM4EEB Fast Mapping of Buildings Toolkit, BIM4EEB BIMeaser tool, BIM4EEB BIM4Occupants tool, BIM4EEB Auteras tool, BIM4EEB BIMcpd tool, and BIM4EEB BIMPlanner tool

It is important to assess the effectiveness of different energy refurbishment scenarios in the early design stages of apartment buildings. This paper demonstrates the main features of a new tool BIMeaser (BIM Early Stage Energy Scenario - a product of the European Union Horizon 2020 project BIM4EEB), which supports the decision-making process in the early stage of design. The tool uses the BIM and linked data from the BIM Management System (BIMMS) for faster initialisation of the actual state, resulting in more accurate building models. The tool finds solutions in accordance with the client’s requirements while also aiming to minimize energy use and maximize the occupant’s indoor climate comfort.

Digital twins are now one of the top trends in Industry 4.0, and many companies are using them to increase their level of digitalization, and, as a result, their productivity and reliability. However, the development of digital twins is difficult, expensive, and time consuming. This article proposes a semiautomated methodology to generate digital twins for process plants by extracting process data from engineering documents using text and image processing techniques. The extracted information is used to build an intermediate graph model, which serves as a starting point for generating a model in a simulation software. The translation of a graph-based model into a simulation software environment necessitates the use of simulator-specific mapping rules. This paper describes an approach for generating a digital twin based on a steady state simulation model, using a Piping and Instrumentation Diagram (P&ID) as the main source of information. The steady state modeling paradigm is especially suitable for use cases involving retrofits for an operational process plant, also known as a brownfield plant. A methodology and toolchain is proposed, consisting of manual, semi-automated and fully automated steps. A pilot scale brownfield fiber processing plant was used as a case study to demonstrate our proposed methodology and toolchain, and to identify and address issues that may not occur in laboratory scale case studies. The article concludes with an evaluation of unresolved concerns and future research topics for the automated development of a digital twin for a brownfield process system.

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