Digital twin construction for life-cycle analysis of tunnels.

Abstract

Tunnel infrastructures are located in environments with high levels of aggression towards structural elements and materials that make up the massif, and have a projected service life of about a century. Therefore, they are constructions that are connected to degradation phenomena, which are associated with fatigue resulting from service demands, chemical and physical weathering, and fortuitous situations such as accidents or seismic events. In this way, there is a loss of performance and safety over time, which can be understood by the influence of the process of reducing material properties, monitoring, identifying defects through inspection, and individual weathering characteristics on the structure. Infrastructure assets are often technologically outdated compared to other areas of engineering, but they can cause significant economic, ecological, and user harm when they collapse. Thus, constant problems in large infrastructures have made companies understand that their management is rudimentary and inadequate compared to current processes associated with the application of digital transformation tools. This research aims to develop methodologies for classification and prediction of degradation development in order to elaborate intervention projects, control, and an optimized decision-making system, generating data that connect to the latest technologies through the construction of a digital twin (DT). The concept of digital twinning attributes a reliable digitalization to the real structure through a continuous flow of information exchange that must feed constant updates of reality and virtuality. The developed methodologies will be applied in a case study on a real asset, in which we intend to understand the life cycle to maximize tunnel management processes and efficient investments, build a digital environment of the infrastructure for virtual inspections, defect mapping, and process simulations.