Automated Simulation Model Coupling via NLP Variable Ranking
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Solution Overview
Problem
Existing methods for connecting distinct simulation models require significant manual intervention, such as merging code or developing ad-hoc couplers, which are inefficient and lack automation in linking variables across disparate models.
Innovation Solution
A distributed computing system that extracts and ranks variable descriptions using natural language processing to determine similarities, allowing for automated linking of variables between simulation models based on confidence levels, thereby facilitating the coupling of distinct simulation models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual methods (merging code or developing ad-hoc couplers) are used to connect simulation models, then model connectivity is achieved, but the process requires significant manual intervention and is inefficient
Solution Approach 1:
The system enables self-service by automatically extracting variable descriptions from simulation models, ranking them using natural language processing, and linking variables without requiring manual code merging or ad-hoc coupler development. The automated ranking system with confidence levels performs the linking task independently, eliminating the need for manual intervention in variable connection.
2Ease of operation
If manual code merging is performed to connect models, then variable linking is achieved, but the complexity of the process increases
Solution Approach 1:
The patent replaces the mechanical process of manual code merging and ad-hoc coupler development with an automated natural language processing system. Instead of manually manipulating code and data structures, the system uses NLP to extract, rank, and link variables automatically, significantly simplifying the operation while reducing process complexity.
3Adaptability or versatility
If ad-hoc couplers are developed for each model coupling, then model-specific requirements are met, but the effort and time required increases significantly
Solution Approach 1:
The system provides a universal solution that can handle different model coupling scenarios through a single automated platform. The natural language processing and ranking system is model-agnostic, capable of extracting and linking variables from any simulation model without requiring custom ad-hoc couplers for each specific coupling case, thereby maintaining adaptability while dramatically improving productivity.
Data Source
AI summary
A distributed computer system includes a distributed processor, a distributed memory, and a simulation engine (SE). The SE includes a simulation I/O coupler that links a first variable of a first simulation model I/O data structure to a second variable of a second simulation model I/O data structure. The SE includes a natural language processing system that extracts a first variable description associated with the first variable, determines similar character strings to the first variable description from an information corpus, and ranks the determined character strings based upon similarity to the first variable description. The SE links the first variable to the second variable if the rank of an equal character string to the second variable description is greater than a rank threshold. The SE may augment the simulation model I/O data structures by writing a value of the first variable to a value of the second variable, or visa versa.