Graphical Language Model Parameter Propagation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional graphical language environments lack the ability to handle multiple system parameters within a single model, requiring systems with varying parameters to be split into multiple models, which hinders the simulation and evaluation of changes across different regions.
Innovation Solution
A graphical language model that allows multiple parameterization functions to be associated with selected nodes, enabling changes in one parameterization function to propagate across all associated nodes within a domain, allowing for a single integrated model to handle systems with multiple environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single graphical language model is used to represent a system with varying parameters across different regions, then the model can maintain system-wide coherence and enable evaluation of changes across regions, but traditional graphical languages cannot accommodate multiple parameterization functions within a single model
Solution Approach 1:
The model is segmented into multiple domains, where each domain can have its own parameterization function. This allows different regions of the system to be associated with different parameters while maintaining a unified model structure. The segmentation enables the model to handle complex systems with varying parameters across different operational regions without requiring multiple separate models.
Solution Approach 2:
Different parameterization functions are applied to different domains within the model, allowing each region to have locally appropriate parameters. This local quality approach enables the model to represent systems where different parts operate under different conditions (e.g., steady-state vs. dynamic regions) while maintaining system-wide coherence and enabling cross-region evaluation.
2Reliability
If systems with multiple parameters are split into multiple separate models, then each model can use the proper external parameters for its region, but the ability to track and evaluate effects of parameter changes across different systems is lost
Solution Approach 1:
Multiple domains that would traditionally require separate models are merged into a single graphical language model. This unified model structure allows parameter changes in one domain to be propagated and evaluated across other domains, maintaining cross-system evaluation capability while ensuring each domain uses its appropriate parameterization function.
Solution Approach 2:
The graphical language model is extended to serve multiple functions by supporting multiple parameterization functions within a single model. This universal model can handle both steady-state and dynamic systems, as well as systems with varying parameters across different regions, eliminating the need for multiple specialized models while preserving parameter propagation accuracy.
3Productivity
If traditional graphical languages propagate parameters globally across all nodes, then parameter changes can be easily propagated throughout the system, but parameters cannot be restricted to specific regions where they should apply
Solution Approach 1:
The model is divided into distinct domains that serve as boundaries for parameter propagation. Each domain can have its own parameterization function, and parameters are propagated efficiently within each domain while being restricted from affecting other domains. This segmentation maintains propagation efficiency within regions while providing control over which regions are affected by parameter changes.
Data Source
AI summary
The present invention provides systems and methods for providing two or more parameterization functions which are associated with a single graphical language environment. Such an arrangement allows for modeling of complex models with interaction across multiple domains. In the present invention, the graphical language environment include components, represented by nodes, that have multiple parameterization functions associated with them, yet operate within a single graphical language environment. A change in one parameterization function associated with one or more nodes is propagated across all associated nodes within the domain.