Digital Twin Calibration via Asynchronous Queue Processing
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Solution Overview
Problem
The challenge of creating digital twins at scale is hindered by the exponential increase in computing resources and costs associated with high-complexity simulation models, necessitating a resource-efficient method for calibrating multiple digital twin models simultaneously.
Innovation Solution
A system and method utilizing a message queue paradigm to efficiently deploy and manage calibration engines and simulation clusters, enabling asynchronous processing and reducing resource usage, by enqueuing and dequeuing requests and results through calibration and simulation queues, allowing for concurrent model simulations and dynamic resource allocation on a cloud platform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-complexity simulation models are used to create high-fidelity digital twins, then the accuracy and detail of the digital twin is improved, but the computing resources and costs increase exponentially
Solution Approach 1:
The patent divides the digital twin creation process into separate modules: a calibration engine that handles parameter optimization and a simulation cluster that executes models. This segmentation allows independent scaling of each component, enabling high-fidelity twins without proportionally increasing overall computational cost.
Solution Approach 2:
The system dynamically allocates computing resources based on the complexity of each digital twin project. The calibration engine and simulation cluster can be deployed, scaled, or terminated according to actual needs, transforming static resource allocation into a dynamic process that optimizes the fidelity-cost tradeoff.
2Productivity
If multiple digital twin models are calibrated simultaneously, then the productivity is improved, but the computing resources required increase exponentially
Solution Approach 1:
The patent merges multiple calibration requests into a single calibration engine that processes them concurrently. Multiple simulation clusters can be deployed to handle different digital twin models simultaneously, combining computational efforts to achieve high productivity without exponential resource increases.
Solution Approach 2:
The calibration engine acts as an intermediary between the calibration requests queue and the simulation clusters. It manages the workflow, coordinates resource allocation, and optimizes the calibration process, enabling efficient batch processing of multiple digital twins.
3Use of energy by stationary object
If calibration requests are processed sequentially, then the resource usage is reduced, but the processing time increases
Solution Approach 1:
The patent implements continuous processing through an asynchronous queue system where calibration requests are continuously received, processed, and completed. The calibration engine and simulation clusters operate continuously without idle time, maintaining useful action throughout the processing cycle to minimize total time while managing resources efficiently.
Solution Approach 2:
The system performs preliminary actions by pre-processing calibration requests and preparing simulation parameters before actual model execution. This allows the calibration engine to optimize settings in advance and the simulation clusters to execute models more efficiently, reducing overall processing time.
Data Source
AI summary
Described are methods and systems for calibrating simulation models to generate digital twins for physical entities. In some embodiments, a method includes receiving a plurality of datasets for a plurality of corresponding physical entities. A calibration request is enqueued to a calibration requests queue for each received dataset and includes information indicating a dataset and a corresponding physical entity. A plurality of calibration engines and a plurality of corresponding simulation clusters for generating a plurality of calibration results for a plurality of calibration requests dequeued from the calibration requests queue can be deployed. Each calibration result is enqueued to a calibration results queue as the plurality of calibration engines generates the calibration result and a plurality of calibration results dequeued from the calibration results queue in association with the plurality of corresponding physical entities can be stored as information used to generate a plurality of corresponding digital twins.