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              <p>Cyber-physical systems (CPS) often involve vague or qualitative requirements such as comfort or energy efficiency, which are difficult to verify using the crisp Boolean logic traditionally employed in Systems Modeling Language v2 (SysML v2). This paper introduces an approach for modeling and verifying fuzzy requirements directly within SysML v2 without modifying its metamodel or relying on external tools. Fuzzy semantics are encoded using native constructs such as calculation definitions, requirements, and constraints, with satisfaction degrees computed via trapezoidal membership functions and evaluated using the native expression evaluation mechanism provided by the modeling environment. We illustrate the effectiveness and feasibility of our expression-based fuzzy verification approach using a smart building Heating, Ventilation, and Air Conditioning (HVAC) system example and clearly show how the modeling is achieved in standard SysML v2 notation. Furthermore, to extend verification capability under variability and uncertainty, we introduce a complementary external transformation of expression-based model elements into Python scripts to perform scenario-based evaluation. A batch-based exploration method is then presented to systematically analyze fuzzy requirement satisfaction under different runtime conditions, offering insights into system robustness and design-space analysis.</p>
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