# Reshaping the Digital Twin Construct with Levels of Digital Twinning (LoDT)
## 3 Digital Twinning throughout the Life Cycle of Physical Assets
### Uses and Life Cycle Phases of Physical Assets
#### 3.1.3 Use  
During use, the asset undergoes a continuous cycle of operation and maintenance, which typically has a longer duration than all previous phases, especially for civil infrastructures. In addition to the various opportunities identified during the planning, design, and construction phases, the use phase places extra emphasis on the dimension of time. This is because the asset's condition gradually deteriorates over time as it strives to maintain the desired performance levels. Hence, monitoring actions concerning both asset performance and condition (or risk of failure) become crucial in the overarching goal of extracting maximum value from it.  
Sensors can be installed or be already embedded in some assets, allowing for preventative decision making and quicker response times. Reducing response times is essential for enhancing the resilience of infrastructure assets, a key objective of sustainable development [6]. For example, in the study by [PERSON] et al. [56], a combination of BIM methodology and the Internet of Things is proposed to monitor the operational state of 100 jet turbines in a road tunnel. This system can anticipate potential failures and optimise maintenance activities through rule-based inference. These opportunities pave the way for a shift from a preventive or condition-based maintenance approach to a predictive one, wherein asset interventions are adjusted based on real-time performance data. This leads to increased resource efficiency (human, financial, and material), which is key to assuring environmental, social, and economic sustainability [6].  
It is worth noting that there are also opportunities for sensor application involving external data acquisition means. In the operation of complex systems such as train operations, maximising the number of trains in circulation while adhering to demand and safety constraints is crucial. Satellite data, used to track the instant positioning of trains (via the GSM-R communication system), can reduce distances between trains, and consequently increase system capacity with ensured safety. In another example, satellite data (e.g., InSAR, i.e., Interferometric Synthetic Aperture Radar) is employed to monitor displacements in geotechnical structures and potentially detect early signs of instability [57]. Such solutions can present significant opportunities in addressing the barrier of high implementation costs identified by the industry, often cited in the literature [13; 58]. Other technological tools, such as drones (UAVs), can be customised for specific uses, such as inspecting hard-to-reach locations (e.g., bridge piers and bridge decks) or large areas (e.g., vegetation near railway catenary). Besides improving data acquisition efficiency, these tools also reduce safety risks associated with such activities. Data acquisition using current technologies can also expand existing knowledge about asset behaviour (e.g., degradation models), potentially leading to more optimised life cycle management.  
At certain times during the use phase, interventions may be required on the asset to restore the expected performance and mitigate risk levels. In such cases, having an adequate asset register and complete information (such as records of previous interventions, suppliers, costs, etc.) contributes to the quality and efficiency of the work to be carried out.  
Opportunities also arise from automating construction processes based on the current condition of assets. One such case study is the RoboShot@FRC project [59], in which a robot shoots fibre-reinforced concrete into the voids found in tunnel walls (detected in the point cloud), and based on the structural reinforcement design specifications (e.g., concrete layer thickness), it automatically adjusts the amount of concrete to be shot along the tunnel surface. This solution optimises material consumption (with positive economic and environmental impacts) while reducing execution errors, time, and safety risks.