Effective management and operation of buildings plays a key role in the life cycle of a building, with a significant part of the costs being represented by the use phase of the building. Facility management uses modern digital tools to manage maintenance, monitor technical equipment and automate operational processes. Digital twins, software platforms such as CAFM and BIM enable more accurate planning and more effective decision-making. Digitalization of building management and maintenance processes brings increased efficiency, data transparency and improved cooperation between all stakeholders. The introduction of digital solutions in building management and maintenance brings a number of benefits, including better control over costs, increased safety and improved user comfort. Digitalization also supports the sustainability of buildings, as it allows for more accurate monitoring of energy consumption and prevention of emergency situations through predictive maintenance. Research in this area therefore focuses on the analysis of available tools and methodologies that enable effective management of buildings in the digital era and bring new possibilities for their long-term and efficient operation.

Nowadays, building information modelling can be used by professionals to create parameterised and visualised databases of complex buildings. Specialised BIM modelling software is available which, in addition to the 3D architectural visual model, can be used to implement as a database various building materials, geometric and spatial parameters, construction costs, building physical properties, sustainability factors, etc., from the design documentation to the creation of digital twins for use in operation. From architectural, mechanical and structural engineering parameters, to acoustic characteristics and fire safety parameters, the BIM methodology serves a wide range of design disciplines.

The BIM methodology provides suitable solutions for a wide range of construction design, construction and operation activities, but it is problematic to deal with complex technical tasks that need to manage quantitative and qualitative parameters in context, such as evacuation planning, fire spread, or heat and smoke control.

In their paper, the researchers show how complex systems such as evacuation engineering can be parameterised in a complex way in BIM models. The authors describe how the technical characteristics and engineering solutions for evacuation can be implemented in BIM models in such a way that the complex system can be represented as a digital twin and preserve the fire safety characteristics required for evacuation as complex data, from structural requirements to geometric dimensions to the encoding of human behaviour.

In their research, the authors demonstrate that complex fire protection parameters can be encoded in models at higher BIM levels and prove that the use of BIM models in evacuation simulations results in a more understandable and transparent visualization compared to traditional evacuation simulations. The data content of BIM models and the visualisation of evacuation simulation as a wireframe model provides more accurate design monitoring and longer term sustainable information compared to traditional engineering solutions used today. The researchers' results suggest that the solutions to today's complex engineering problems can be improved by modelling complex fire safety features using BIM methodology.

The increasing adoption of Building Information Modeling (BIM) has accelerated the need for efficient workflows in generating Building Energy Models (BEM). However, inconsistencies in BIM modeling practices create challenges in directly utilizing BIM data for energy simulations due to variations in geometry, metadata, and spatial definitions. To address this gap, we introduce the Sustainable Analytical Model (SAM), an open-source tool developed in .NET C# that provides a flexible, semi-automated approach to transforming BIM data into energy models while minimizing manual interventions.

SAM enables various model generation methods, including 2D outlines, boundary representations (BREPs), and planar panels, ensuring compatibility with different BIM workflows. A key feature, the Adjacency Cluster system, automates spatial organization and thermal relationship definitions, significantly reducing errors compared to traditional BEM tools that require extensive manual adjustments. Additionally, SAM integrates with validated energy simulation engines such as Tas EDSL and OpenStudio (via Ladybug Tools), facilitating comprehensive energy performance analysis, load sizing, and HVAC simulations.

SAM’s modular framework and operation in Grasshopper support custom BIM workflows and enhance interoperability across platforms (Revit, Rhino etc.). This adaptability allows architects and engineers to reuse existing BIM data efficiently, reducing redundancy and improving modeling accuracy. Furthermore, SAM’s capability to support scenario-based HVAC simulations enables digital twin applications, allowing real-time analysis and optimization of both new and existing buildings.

By bridging BIM and BEM with a connected, automated workflow, SAM enhances interdisciplinary collaboration in sustainable design. The tool reduces manual workload, streamlines model conversion, and ensures consistency across various modeling approaches. Its open-source nature empowers researchers and industry professionals to extend its functionalities, fostering advancements in energy-efficient building design. This research presents SAM as an innovative solution that enhances BIM-to-BEM interoperability, reduces manual conversion challenges, and supports sustainable architecture through improved energy modeling workflows. By optimizing model accuracy, minimizing manual effort, and enhancing multi-platform compatibility, SAM offers a practical and scalable approach for architects, engineers, and sustainability consultants in the pursuit of high-performance building design.

The Central European building stock is in dire need of sustainable renovation to reduce energy consumption needs and dependency on fossil fuels for comfort heating. Although accurate thermal envelope assessment is critical for the design of energy-efficient retrofits, not only is the influence of model granularity under-explored in the Hungarian context, but previous studies show serious neglect for the incorporation of thermal bridges and related thermal anomalies by professionals. Our literature review highlights, that although actual losses are estimated to be up to 35% than initially expected due to the neglection of thermal bridging, a very small percentage of energy performance certificates are considering their effects. Our case study investigates the impact of varying levels of detail (LODs) in building information modelling (BIM) on the thermal performance analysis of a "Cube House", a common 1970s single-family home typology in Hungary. The LOD variation involves both geometrical and information-wise granularity of the models. The BIMs are authored with Archicad 28, and the IFC 4.3 model schema was used to transfer a STEP-based geometry to COMSOL Multiphysics where steady-state heat transfer was modelled for the cases. We have showed how the numerical model can be translated to a graphical calculation methodology to derive quantitative and qualitative performance metrics for a thermal envelope. We used the current Hungarian energy legislation as the baseline for comparison: we compared the regulated thermal transmittance correction factor’s (ζ=0.3) regulated value for this building geometry and assigned it to the simplest LOD1 case. The studies showed a clear impact on the usability of the level of detail in BIM models for thermal bridge assessment, and resulted in surprisingly high correction factors for both case. We have calculated the area-weighted Ud-values for both LOD2 (Ud,LOD2 = 0.387 W/m2K) and LOD3 (Ud,LOD3 = 0.327 W/m2K), and found that the corresponding correction factors are equal to the regulated ζ = 0.3 value’s 499.99% in the case of LOD2 (ζLOD2 = 1.500), and 370.13% in the LOD3’s case (ζLOD3 = 1.110). We consider our proposed geometrical interpretation especially useful for architects and façade engineers working in early stage designs, when there is still room for meaningful design iterations.

Heat insulation improves indoor comfort and reduces operational carbon emissions by minimizing heat loss in the use stage of its life cycle. Amidst the increasing energy efficiency of buildings, the importance of production, construction, and end-of-life stages causing embodied carbon emissions has started to show an upward trend. With the right selection of insulation materials and thickness, the total carbon emissions can be further reduced considering the lifetime of the building. Finding the most favourable option for insulation requires investigating the thermal insulation capacity and the impact generated throughout its production, transportation, implementation, and destruction. This study aims to identify the best possible passive refurbishment scenario in terms of insulation material and thickness for a typical residential apartment in Budapest. The optimization process is carried out using a genetic algorithm as a Python module, focusing on minimizing the whole life cycle carbon emissions. Current Energy Performance Building Directive of the European Union only addresses operational carbon, while considering the whole life cycle of building materials appears only as a recommendation. The demonstrated solution provides insights that can be applied to other cases. The method used has great potential to incorporate other passive and active refurbishment elements, such as optimizing building service engineering systems or additional components of the building envelope.

Settlement densification is a key measure against increasing land consumption. Prefabricated timber construction is ideally suited due to its structural and operational advantages. Based on a publicly available timber construction system, the LoftConcept research project developed further improvements: Parametric constructions and (semi-)automated calculation of performance indicators. Parametric components and details were modelled in Rhinoceros/Grasshopper, stored in a database (Simultan) and assigned to an architectural model either automatically by preselecting standard constructions or manually, also in Simultan. This approach enables calculations to be performed directly on the parameterized digital twin within the same software environment. The thermal transmittance (U-value) of homogeneous components is calculated in accordance with standards based on a target value. Simplified assumptions were made to calculate U-values of inhomogeneous components and regarding harmful condensate only verification-free components were used. To compute non-renewable primary energy consumption, acidification potential and total global warming potential of each component and the whole building, a mass balance was created in Simultan and aggregated with material parameters. The calculation of sound insulation descriptors at the building component level is based on partially standardized empirical models. The presented methodology integrates these calculation approaches with the framework of the EN ISO 12354, enabling the assessment of acoustic performance at building level. The procedure was validated using data from established building component databases. Modelling, component assignment, and performance calculations were validated using an example building representing a two-storey vertical extension segment.