Configurable Digital Twin for Multi-Aspect System Simulation
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Solution Overview
Problem
Current simulation methods for real systems are limited to modeling a single aspect of the system, failing to account for interdependencies between multiple aspects, such as electrical grids, maintenance, and financial assets, which restricts the accuracy and scope of the simulation.
Innovation Solution
A method for simulating multiple aspects of a system by creating models for each aspect, determining initial and updated data records, and iteratively updating these records based on user-selected model interactions, allowing for the exploration of dependencies and optimizing the simulation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple models simulating different aspects of a system are created and coupled together, then the comprehensiveness and accuracy of the simulation is improved, but the complexity of the simulation system increases
Solution Approach 1:
The simulation system is segmented into multiple independent aspect models (electrical grid, maintenance, energy trade, financial assets), each simulating a specific aspect separately. These segmented models are then coupled through a data exchange mechanism that shares common data records, allowing comprehensive system simulation while maintaining manageable model complexity through modular design.
2Adaptability or versatility
If the simulation covers multiple aspects of the system with interdependencies, then the global optimization capability is improved, but the computational resources and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-defining the structure of aspect models, their interrelationships, and data exchange protocols before actual simulation runs. Common data records are established in advance, and the coupling mechanisms are pre-configured, allowing the simulation to execute more efficiently by avoiding dynamic setup during runtime, thus reducing computation time while maintaining global optimization capability.
Data Source
AI summary
A method simulates aspects of a system. The method includes: (a) creating models of a system, wherein each individual model describes a specific aspect of the system, (b) determining for each model an initial first data record containing specific data used only by the model and an initial second data record containing common data used by the model and at least one other model, (c) selecting a first model and a second model, (d) determining updated first and second data records on the basis of the initial first data record for the first model and the initial second data records, and (e) determining updated first and second data records for the second model based on the initial first data record for the second model, the updated second data record for the first model and the initial second data records for all of the models except for the first model.