The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-5/W1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-5/W1-2022, 149–157, 2022
https://doi.org/10.5194/isprs-archives-XLVI-5-W1-2022-149-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-5/W1-2022, 149–157, 2022
https://doi.org/10.5194/isprs-archives-XLVI-5-W1-2022-149-2022

  03 Feb 2022

03 Feb 2022

TOWARDS DIGITAL TWIN DRIVEN CULTURAL HERITAGE MANAGEMENT: A HBIM-BASED WORKFLOW FOR ENERGY IMPROVEMENT OF MODERN BUILDINGS

A. Massafra, G. Predari, and R. Gulli A. Massafra et al.
  • Department of Architecture, University of Bologna, Bologna, Italy

Keywords: Cultural heritage, Energy improvement, Digital Twins (DT), Heritage Building Information Modeling (HBIM), Building Energy Modeling (BEM), Building Performance Simulation (BPS), International Foundation Classes (IFC), Multi-criteria analysis

Abstract. Europe has numerous historic buildings that need to become more energy-efficient, which need permanent maintenance and refurbishment to fulfill sustainability and use requirements. Asset owners and asset managers need to adopt new strategies to protect listed buildings while optimizing costs and benefits during their life cycle. In this sense, the digital transition proves to be a moment to seize for opening new scenarios. The Digital Twin paradigm promises to be valuable for enabling the sustainable knowledge, conservation, restoration, and management of built assets and solving the dilemma about protecting the architectural identity of these buildings while adapting them to the functional and performance requirements dictated by the regulatory framework. This study proposes a workflow that integrates Heritage Building Information Modeling (HBIM) and Building Performance Simulation (BPS) tools for data-driving the energy improvement of Italian listed modern buildings built between the 1920s and 1960s. After acquiring information about the building, the HBIM model and the Building Energy Model (BEM) are realized based on the International Foundation Classes (IFC) standard. Energy intervention measures are defined, construction costs are computed, and benefits during the intervention life cycle are predicted in thermal demand. Finally, an expeditious multi-criteria analysis allows for comparing different intervention combinations and indicating the optimal solution for the energy improvement of the building concerning energy, economic, and financial issues. These outcomes represent the first step towards realizing a dynamic, accessible, and sharable Digital Twin.