A SysML v2 Metamodel for -Ilities: Application to a Digital Twin Complex System
TL;DR
This article focuses on using SysML v2 to model reusable parameterized templates for nonfunctional requirements, referred to as -ilities, to address how they can be treated with the same rigor as functional requirements and mapped directly and explicitly from the requirements engineering phase within digital engineering and MBSE environments.
Abstract
Multidisciplinary knowledge and exchange of information are two of the most important aspects of complex system design within digital engineering and model-based systems engineering (MBSE) environments. The next generation of systems modeling language, SysML v2, developed by the Object Management Group, improves the implementation and maturation of model-based approaches. This article focuses on using SysML v2 to model reusable parameterized templates for nonfunctional requirements, referred to as -ilities, to address how they can be treated with the same rigor as functional requirements and mapped directly and explicitly from the requirements engineering phase within digital engineering and MBSE environments. The selected set of -ilities are safety, human system integration, and cybersecurity. The rationale for this selection is based on past studies that have documented the need to evaluate safety risks that involve humans in the loop and cybersecurity considerations. The metamodel design uses SysML v2 syntax to compile general characteristics for -ilities, with an application to a digital twin complex system architecture model to demonstrate an instantiation within Digital Engineering and MBSE environments. The resulting metamodel is composed of SysML v2 parameterized requirements constructs, notations for analysis and verification, and relationships that can be generalized to other -ilities with implementation steps aligned with ISO/IEC/IEEE 29148, the standard for systems and software requirements engineering. These contributions lower the barrier of adoption for SysMLv2, support the standard and consistent modeling within the MBSE domain, and advance multidisciplinary analysis.