Automating Physics-Based Reasoning for SysML Model Validation

2025-01-30

AI Summary

Existing SysML model verification approaches lack the capability to ensure physical correctness—particularly adherence to fundamental physical laws such as energy conservation and dynamical constraints—in electro-mechanical coupled systems. To address this, we propose the first SysML verification framework explicitly designed for multi-domain physical consistency, operating across two complementary dimensions: structural views (Block Definition Diagrams and Internal Block Diagrams) and functional views (Activity Diagrams). Our method tightly integrates formal functional semantics with cross-domain physical principles (electromagnetic, mechanical, and thermal), enabling rule-driven constraint solving and logical inference. It supports automated detection of both structural integrity and physical plausibility of functional behavior. We evaluate the framework on four real-world electromechanical systems—coffee machine, vacuum cleaner, hair dryer, and wired speaker—demonstrating its effectiveness in significantly enhancing automated, physics-aware consistency verification during early SysML-based design phases.

Technology Category

• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning
• Computer Vision: Low Level & Physics-based Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

System and software design benefits greatly from formal modeling, allowing for automated analysis and verification early in the design phase. Current methods excel at checking information flow and component interactions, ensuring consistency, and identifying dependencies within Systems Modeling Language (SysML) models. However, these approaches often lack the capability to perform physics-based reasoning about a system's behavior represented in SysML models, particularly in the electromechanical domain. This significant gap critically hinders the ability to automatically and effectively verify the correctness and consistency of the model's behavior against well-established underlying physical principles. Therefore, this paper presents an approach that leverages existing research on function representation, including formal languages, graphical representations, and reasoning algorithms, and integrates them with physics-based verification techniques. Four case studies (coffeemaker, vacuum cleaner, hairdryer, and wired speaker) are inspected to illustrate the model's practicality and effectiveness in performing physics-based reasoning on systems modeled in SysML. This automated physics-based reasoning is broken into two main categories: (i) structural, which is performed on BDD and IBD, and (ii) functional, which is then performed on activity diagrams. This work advances the field of automated reasoning by providing a framework for verifying structural and functional correctness and consistency with physical laws within SysML models.

Problem

• SysML Model Validation
• Physical Laws Compliance
• Electrical and Mechanical Rules

Innovation

• Automatic Verification
• SysML Models
• Physical Rules Compliance