| dc.description.abstract | A digital twin (DT) is a computational model (or set of coupled) that evolves over time to persistently represent the critical structure, its components, system, or process. Digital twin underpins intelligent automation by supporting data-driven decision-making and enabling asset-specific analysis and system behavior. Within the context of critical infrastructure systems, the digital twins represent the flow of information among connected platforms. In the future, as many agencies turn to digital twin capabilities, they have to migrate toward continuous real-time performance models and calibrate by pairing data from real-time sensors, meters, weather, and other data. The digital twin can be used to run “what-if” scenarios, predict and prevent failures, provide early alerts of anomalies, and conduct predictive analysis. The strength of a digital twin is the interconnectivity of data and models. The main characteristics of a digital twin are: | |
