Tag: Digital Twin

  • Towards Digital Twin Driven Cultural Heritage Management: A HBIM-Based Workflow for Energy Improvement of Modern Buildings

    Towards Digital Twin Driven Cultural Heritage Management: A HBIM-Based Workflow for Energy Improvement of Modern Buildings

    Europe’s historic skyline presents a unique challenge: how do we drag buildings from the 1920s into the 2020s without losing their architectural soul?

    This research tackles the “modernization dilemma” facing asset managers who must meet strict energy-efficiency regulations while preserving the identity of listed buildings.

    The study proposes seizing the digital transition by using the Digital Twin paradigm—a virtual, data-rich mirror of a physical structure—to enable smarter conservation and more sustainable management of our urban heritage.

    The authors developed a workflow that specifically integrates Heritage Building Information Modeling (HBIM) with Building Performance Simulation (BPS) tools. Focused on Italian modern buildings constructed between the 1920s and 1960s, the methodology involves creating a virtual model based on international IFC standards to simulate various energy-improvement measures. By predicting thermal demand, computing construction costs, and analyzing benefits over the building’s entire life cycle, the researchers used a multi-criteria analysis to find the “sweet spot” where energy savings, economic costs, and financial feasibility align.

    The findings demonstrate that this data-driven approach takes the guesswork out of restoration; it provides a reliable roadmap for transforming static historic assets into dynamic, energy-efficient Digital Twins that are as functional as they are beautiful.

    Learn more about this study here: https://cris.unibo.it/handle/11585/856385


    Reference

    Massafra, A., Predari, G., Gulli, R. (2022). TOWARDS DIGITAL TWIN DRIVEN CULTURAL HERITAGE MANAGEMENT: A HBIM-BASED WORKFLOW FOR ENERGY IMPROVEMENT OF MODERN BUILDINGS. INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES, XLVI-5/W1-2022, 149-157