Invention Reference Number
Digital Twin (DT) represents an essential technology in which an operations model of a physical system uses real-time data to predict, monitor, and improve the physical system's operations. One of the primary objectives of a DT is to inform the physical system of measures to take in response to one or multiple intervening events that change the physical system's state. The capability to perform various real-time scenario assessments in readiness for such events is an effective use of simulations as DTs, and here, scalable performance-efficient simulation cloning methods become relevant. However, continuous evaluations of simulation clones, each representing a unique cascade of intervening events, are highly challenging due to the constraints of finite memory and an extensive exploration space. Here a novel simulation cloning-based method to continuously evaluate a tree of simulation clones formed speculatively based on probabilistic what-if scenarios under finite resource constraints to realize a DT is presented with an example scenario demonstration of its utility for the power grid, transportation systems, communication system, etc. Currently, the usage of machine learning models and simulation models as DT is popular. There exists no parallel to the DT that is realized using tree of simulation clone.
