iNEST: an integrated digital development innovation project for the Italian Triveneto region
by Andrea Martini, Martina Teruzzi & Gianluigi Rozza
Digitalisation is a part of our everyday life. We are connected and smart. The Information and Technology sector has driven innovation in the past century, allowing development and optimisation from the industry to the life sciences.
The ultimate step of this revolution is the Digital Twin (DT), a virtual dual of its physical counterpart, the real asset. As every twin, the DT aims at achieving the closest similarity to the asset, mimicking its functioning. This affinity is to be intended in a dynamic way. First of all, the DT follows the evolution of its real counterpart through its entire lifecycle, from the design phase to the operative life. Secondly, the exchange of information between the two is continuous and should be refined in time.
The creation of a DT implies several advantages: the analysis and the design are based on simulations and not on the “build and test” concept, allowing a better validation in cases that would be unrealistic or expensive employing a real prototype. Moreover, it reduces the time to market and the overall cost, since fewer physical prototypes are built. The synchronisation between DT and real asset allows the improvement of the final quality of the product, since optimisation processes can be performed.
The phenomena we would like to simulate span over different scales and can be studied by the same governing laws in a multi-physics framework. For this reason, often the data collected are not enough to fully describe the asset, requiring a more comprehensive infrastructure which combines both simulations and data. We are going to refer to this concept as Big Model.
The Triveneto region, due to the various and rich habitats, together with its touristic and manufacturing vocation, must face several matters, which can be dealt with the DT approach. In particular, its waters are home to a rich marine ecosystem, which has to coexist with a fervent industrial business and production. The impact that one has on the other requires constant monitoring, to preserve both its integrity and its economic competitiveness. In the same way, the alpine landscape includes a prosperous biodiversity which needs to cohabit with the changing and adapting of human activities and their implications. These concepts are strictly entangled with the health and wellness of people inhabiting these areas, that passes through environment and nutrition, but at the same time is influenced by the urban architecture and design. The DT is suited for modelling these different aspects at different levels, with the ultimate goal of pursuing the interconnection of different models, or even twins.
The operational life of a Digital Twin must cope with the continuous innovation and constant integration that it aims to achieve. Its realisation requires huge computational power and a high performance computing perspective allows us to create structured, reliable models. At the same time, we think that the Reduced Order Model approach, permitting a strong reduction of computational costs, represents the way to model portability and sustainability.
In the Italian PNRR framework (Piano Nazionale di Ripresa e Resilienza), universities and research centres located in the Triveneto region put together their effort in creating an innovation ecosystem to reinforce synergy across the territory, and the digital technology as the common theme to ultimately overcome its fragmentation. We as SISSA are part of the project hosting a research spoke (with University of Trieste, Padua and OGS). In particular, the Mathematical Area with SISSA mathLab is involved in the entire process, providing the necessary support to develop the Digital Twins thanks to the expertise pursued in the last years of research. In particular, our activities will cover mathematical, numerical and data-driven modelling, Model Order Reduction, automatic learning for Digital Twins and applications of DT in industry, medicine, environmental sciences and daily life.
