Digital Twin Experiment Selection for Hardware Change Prediction
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Solution Overview
Problem
Existing systems face challenges in predicting the impact of hardware modifications on system performance due to high computational and financial costs of extensive simulations, leading to inefficient resource allocation and potential undesired system behavior.
Innovation Solution
A method utilizing a digital twin model to simulate potential system modifications, employing an orthogonal matrix to limit simulations and analyze variance, thereby selecting significant modifications efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive simulations are performed to predict hardware modification impact, then prediction accuracy is improved, but computational cost and time increase significantly
Solution Approach 1:
The patent creates a digital twin model that copies the physical hardware system, allowing simulations to be performed on the virtual model rather than actual hardware. This enables extensive simulations to be conducted efficiently, improving prediction accuracy while reducing computational time and physical resource consumption.
Solution Approach 2:
The system performs preliminary simulations on the digital twin model before implementing actual hardware modifications. By analyzing potential impacts in advance through the simulated environment, the system identifies significant modifications without needing to test every possible change through extensive real-world experimentation.
2Measurement precision
If extensive simulations are performed to predict hardware modification impact, then prediction accuracy is improved, but financial cost increases
Solution Approach 1:
By creating a virtual digital twin copy of the hardware system, the patent enables simulations to run on software rather than requiring physical hardware resources for each simulation. This significantly reduces financial costs associated with extensive simulations while maintaining prediction accuracy through comprehensive virtual experimentation.
3Adaptability or versatility
If all possible hardware modifications are simulated, then comprehensive analysis is achieved, but system complexity increases
Solution Approach 1:
The patent segments the hardware system into modular components within the digital twin model, allowing simulations to focus on specific components or subsystems. This enables comprehensive analysis of all possible modifications through the modular structure while managing system complexity by analyzing individual segments rather than the entire system at once.
Solution Approach 2:
The system performs simulations on the digital twin model, which is a partial representation of the physical system. This partial action approach allows comprehensive analysis of modification impacts through the virtual model without requiring the full complexity of simulating every possible hardware configuration in the physical system.
Data Source
AI summary
Methods and systems for managing systems are disclosed. To manage the systems, potential changes to the system may be simulated. The numbers and types of changes to be simulated may be selected to reduce computational expense while maintaining coverage to evaluate impacts of different types of changes on operation of the system. Once selected, a digital twin model may be used to simulate potential operation of the system as modified by the potential changes. The resulting simulation results may be analyzed to identify significance of different potential changes to the system.