Uncertainty Modeling for SysML v2

A team of researchers has published a paper proposing a major extension to the next-generation Systems Modeling Language (SysML v2) to formally handle uncertainty. The work, titled 'Uncertainty Modeling for SysML v2' by Man Zhang, Yunyang Li, and Tao Yue, bridges a critical gap by integrating the Object Management Group's (OMG) recently standardized Precise Semantics for Uncertainty Modeling (PSUM) framework. While SysML v2 offers improved rigor for Model-Based Systems Engineering (MBSE), it lacked native constructs for representing the inherent uncertainty in modern systems like autonomous vehicles and microservice architectures. This extension, called PSUM-SysMLv2, directly addresses that need.

The proposed extension systematically incorporates the PSUM metamodel into the SysML v2 framework, preserving its core syntax and semantics. This allows engineers to explicitly model indeterminacy sources, characterize different types of uncertainty, and analyze how uncertainty propagates through a system's design—all within a standardized modeling environment. The approach was validated across seven case studies, demonstrating its expressiveness and practical applicability. For professionals, this means complex, safety-critical systems can now be designed with built-in uncertainty analysis, potentially leading to more robust and reliable cyber-physical and autonomous systems from the earliest stages of development.