Large building stocks’ management, conservation, and renovation processes must consider a complex requirement framework. On the one hand, asset managers have to maintain and improve the physical characteristics of buildings constantly; on the other hand, they need to allow their compatibility with the functional, environmental, and economic issues that change over time. Deep knowledge of built assets is the fundamental premise for their sustainable development. This knowledge needs to be well structured, made usable through shared languages, exchanged between multiple actors and between various life cycle phases, for various uses and in an interoperable manner. In recent years, the digital transition introduced new paradigms to open new scenarios in building information management. However, the accessibility to building data for non-digital experts still represents a barrier to the digital revolution of the sector. This paper defines and tests a method for data acquisition, structuring, sharing, and visualizing on a selected listed building belonging to the University of Bologna. Based on the service-oriented five-dimensional digital twin model proposed by the literature in the manufacturing field, the method consists of four main steps; these are the development of an ontological data model, the realization of information templates, the collection and elaboration of building information, and the design of a data visualization environment. Prototypes of visualization dashboards, designed to support administrators in building energy management, are provided. They allow the handlers to monitor energy consumption over time and compare different intervention strategies for the energy improvement of the building in terms of life cycle costs, showing that not the most expensive intervention solution is the cheapest during the intervention lifetime.

Strumenti e modelli per la gestione digitale del patrimonio costruito

A. Massafra
Writing – Original Draft Preparation
;
R. Gulli
Writing – Review & Editing
2022

Abstract

Large building stocks’ management, conservation, and renovation processes must consider a complex requirement framework. On the one hand, asset managers have to maintain and improve the physical characteristics of buildings constantly; on the other hand, they need to allow their compatibility with the functional, environmental, and economic issues that change over time. Deep knowledge of built assets is the fundamental premise for their sustainable development. This knowledge needs to be well structured, made usable through shared languages, exchanged between multiple actors and between various life cycle phases, for various uses and in an interoperable manner. In recent years, the digital transition introduced new paradigms to open new scenarios in building information management. However, the accessibility to building data for non-digital experts still represents a barrier to the digital revolution of the sector. This paper defines and tests a method for data acquisition, structuring, sharing, and visualizing on a selected listed building belonging to the University of Bologna. Based on the service-oriented five-dimensional digital twin model proposed by the literature in the manufacturing field, the method consists of four main steps; these are the development of an ontological data model, the realization of information templates, the collection and elaboration of building information, and the design of a data visualization environment. Prototypes of visualization dashboards, designed to support administrators in building energy management, are provided. They allow the handlers to monitor energy consumption over time and compare different intervention strategies for the energy improvement of the building in terms of life cycle costs, showing that not the most expensive intervention solution is the cheapest during the intervention lifetime.
Memoria e Innovazione
1241
1260
A. Massafra, R. Gulli
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/895032
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact