Graphical Model Variant Regions for Multi-Configuration Execution
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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.
Innovation Solution
Implementing a single model that includes a common algorithmic structure with variant regions containing alternative algorithmic substructures, where only one variant choice is active during execution, allowing for efficient representation of multiple configurations without unnecessary resource allocation.
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 updates become error-prone
Solution Approach 1:
The patent merges multiple separate models into a single unified model that contains variant regions. Each variant region can represent different system configurations, but they share common model elements and structure. This combining approach reduces the total quantity of model data stored in memory while maintaining the ability to represent multiple configurations through conditional activation of different variant choices.
Solution Approach 2:
The unified model structure serves multiple functions simultaneously: it can represent different system configurations, reduce memory usage through shared elements, and enable efficient updates across all configurations. The variant regions within the model provide multi-functionality by allowing the same model framework to adapt to various configuration scenarios without requiring separate dedicated models for each.
2Adaptability or versatility
If multiple separate models are created for different system configurations, then each configuration can be represented accurately, but updates become error-prone as they must be made to each model individually
Solution Approach 1:
By merging multiple configuration-specific models into a single unified model with variant regions, the patent ensures that updates to common model elements automatically apply across all configurations. This eliminates the error-prone process of manually updating each separate model individually, as the unified structure maintains consistency across all variant choices through centralized modification points.
3Quantity of substance
If a single model represents multiple configurations, then memory usage is reduced, but the model structure becomes more complex
Solution Approach 1:
The patent applies segmentation by dividing the unified model into distinct variant regions that can be independently managed. Each variant region represents a specific configuration option, allowing the complex model to be organized into manageable segments. This segmentation reduces the perceived complexity by providing clear structural boundaries and enabling selective activation of specific variant choices based on runtime conditions.
4Adaptability or versatility
If all variant choices are included in the model, then all configurations are represented, but processing efficiency decreases due to unnecessary resource allocation
Solution Approach 1:
The patent implements dynamic behavior by enabling runtime selection of active variant choices based on specific conditions. Instead of statically including all configuration elements in the execution path, the model dynamically activates only the relevant variant choices needed for the current operating scenario. This dynamic approach maintains adaptability across all configurations while improving computational efficiency by eliminating processing of inactive variant elements.
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.