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Angelo Massafra

Dottorando

Dipartimento di Architettura

Assegnista di ricerca

Dipartimento di Architettura

Tutor didattico

Dipartimento di Architettura

Settore scientifico disciplinare: ICAR/10 ARCHITETTURA TECNICA

Temi di ricerca

Parole chiave: Built Heritage, Building Renovation, Building Management, Building Performance, Digital twins, BIM

Over the past century, a vast building stock was built in Europe. The major problem of controlling its quantity while upgrading its quality and responding to contemporary needs now emerges.
In particular, buildings managed by public administrations face daily performance and regulatory upgrades concerning safety (static-seismic and fire safety), operation (facilities, consumptions, impacts, living comfort, and logistics) and maintenance (regular maintenance and renovation). The amount of money spent annually to manage these buildings is very large due to their age, construction type, and dimension. At the same time, the impacts of building operation and maintenance on the environment can reach up to 70-90% of the overall life cycle impacts in terms of carbon emissions, energy use, and resource consumption.
A twofold issue arises for public building managers. On the one hand, they must conserve and improve the containers (i.e., the buildings, their physical characteristics, and their physical state). On the other, they need to ensure functional, environmental, and economic compatibility of the contents (i.e., users, uses and activities) according to an increasingly changing requirement framework. Nevertheless, building management practices seem unprepared to solve this complexity. Several gaps currently exist in public building management, usually due to scarce building managers’ expertise (knowledge gap), poor coordination of the multiple players usually involved in building management (coordination gap), serious financial limitations (finance gap), information unavailability or untraceability (information gap), and insufficient data visualization tools (visualization gap).
The digital transition of the Architecture, Engineering, Construction and Operation (AECO) sector proves to be a moment to seize to open new scenarios in building management. In particular, the Digital Twin (DT) paradigm could be valuable for improving building management practices. By allowing predictive building operation based on real-time measurement and evaluation of key performance indicators (KPIs), DTs can allow building managers to understand the actual performance of buildings in terms of day-to-day use (space management and facilities), consumption (energy and resources), and impact (cost, environment, and users’ well-being), supporting them in decision-making and strategic planning. Moreover, predictions based on occupancy data can help correctly allocate technical and economic resources during the actual operation of buildings, also giving reliable estimations of the costs of the different renovation measures (e.g., new uses of the buildings/areas, new occupancy levels, refurbishment alternatives) in a long-term vision (i.e. considering possible alternative use scenarios).
Within this background, the research aims at developing a new framework for including the performance dimension in digital built asset management (specifically focusing on the operation stage of existing buildings) and a service-oriented DT platform prototype for dynamically and holistically evaluating and predicting the performance of building operation. The framework will be based on the Service-oriented Five-dimension DT model, composed of five entities (the physical asset, the virtual asset, the DT data, the DT services and their connections) and four consequential capability levels (descriptive, analytical, predictive, and proactive). The platform will provide an interactive and user-friendly decision support system to building managers, helping them assess and plan building use by monitoring and benchmarking the performance of current uses and predicting, targeting, and improving future uses through some significant KPIs. The focus will be on the relationships between energy demand and occupancy conditions.
The DT will integrate static and dynamic data to be occasionally or periodically collected, and simulated, for two university buildings in Bologna (Italy) built in the Modern Age (1920-1960). Information will be structured and integrated according to a specific ontology model based on open standards (e.g., IFC). Data will be stored in Building Information Models (BIM), processed by Building Performance Simulation (BPS) tools or Machine Learning (ML) algorithms, shared with facility managers or building service providers, and acquired by sensors or IoT devices. Spatial data will be managed through topological models in Visual Programming (VP) environments to ensure bidirectional interoperability between BIM and BPS. Information models will then be federated into a centralized data environment and analyzed and visualized in a Business Intelligence (BI) platform through user-friendly interactive dashboards.

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