Graphical Program Variant Regions for Multi-Configuration Modeling
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Solution Overview
Problem
Current modeling environments require creating multiple separate models for different system configurations, leading to inefficient use of computer memory and error-prone updates, as changes need to be made to each model individually, which is time-consuming and prone to errors.
Innovation Solution
Implementing a single model that can represent multiple configurations using variant regions with active and inactive algorithmic substructures, where only one variant choice is executed at a time, and variant conditions are propagated to optimize resource usage and simplify model construction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple separate models are created for different system configurations, then each configuration can be represented accurately, but computer memory usage increases and model updates become error-prone and time-consuming
Solution Approach 1:
The patent merges multiple separate configuration models into a single unified model by introducing variant regions that can contain multiple algorithmic substructures representing different configurations. These variant regions are consolidated within one model file, eliminating the need for separate model files for each configuration and thereby reducing memory usage while maintaining the ability to represent multiple system configurations.
Solution Approach 2:
The unified model structure serves multiple functions simultaneously: it can represent different system configurations through variant regions, maintain a single source of truth for all configurations, and enable efficient memory usage. The model can dynamically switch between different algorithmic substructures based on the active configuration, providing multi-functionality within a single model framework.
2Adaptability or versatility
If multiple separate models are created for different system configurations, then each configuration can be represented accurately, but model updates become error-prone and time-consuming as changes need to be made to each model individually
Solution Approach 1:
By consolidating multiple configuration models into a single unified model with variant regions, the patent enables centralized update management. When a configuration needs to be updated, the change is made in one location within the unified model rather than propagating changes across multiple separate model files, significantly reducing update time and eliminating the risk of inconsistencies between models.
Solution Approach 2:
The unified model structure allows a single update operation to affect all configurations that share common elements. Common algorithmic substructures defined once in the unified model can be automatically applied across multiple configurations, reducing the time required to maintain consistency across different system configurations.
3Quantity of substance
If a single model represents multiple configurations using variant regions, then memory usage is reduced, but the model structure becomes more complex
Solution Approach 1:
The patent manages model structure complexity by segmenting the unified model into distinct variant regions, each containing specific algorithmic substructures for different configurations. This segmentation allows the complex model to be organized into manageable, independently manageable sections that can be selectively activated or deactivated based on the current configuration, making the complexity controllable and navigable.
Solution Approach 2:
The model structure employs dynamic characteristics where variant regions and algorithmic substructures can be selectively activated or deactivated based on the current configuration context. This dynamic approach allows the model to present a simplified structure for the active configuration while maintaining the capability to represent multiple configurations, effectively managing complexity through conditional visibility and activation rather than permanent structural complexity.
4Reliability
If variant conditions are propagated automatically, then errors are reduced and accuracy improves, but processing overhead increases
Solution Approach 1:
The patent implements preliminary action by pre-defining variant conditions and algorithmic substructures within the unified model before execution. The variant conditions are established in advance, allowing the model to quickly determine which configurations are applicable without performing complex real-time analysis. This preliminary setup reduces the processing overhead during actual model execution while maintaining high accuracy through systematic condition propagation.
Data Source
AI summary
Systems and methods provide, as part of an executable graphical model, a region for providing variants that includes one or more computational choices defining alternative execution implementations of the region. Conditions assigned to the one or more computational choices indicate which of the computational choices is active. The conditions specify logical expressions of variables that evaluate to True or False. For a given simulation of the executable graphical model, all of the logical expressions may evaluate to False, such that none of the computational choices are active. All of the computational choices of the executable graphical model may be removed for the given simulation.