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Uncertainty Modeling for SysML v2

Man Zhang, Yunyang Li, Tao Yue

TL;DR

A systematic extension of SysML v2 that incorporates the PSUM metamodel into its modeling framework, which enables explicit specification of indeterminacy sources, structured characterization of uncertainties, and consistent propagation of uncertainty within system models, while preserving conformance with SysML v2 syntax and semantics.

Abstract

Uncertainty is inherent in modern engineered systems, including cyber-physical systems, autonomous systems, and large-scale software-intensive infrastructures (such as microservice-based systems) operating in dynamic and partially observable environments. The recent publication of Precise Semantics for Uncertainty Modeling (PSUM) by the Object Management Group represents the first standardized specification for uncertainty modeling within the Model-Based Systems Engineering (MBSE) community, providing formally defined semantics for representing and reasoning about uncertainty in models. In parallel, the second version of Systems Modeling Language (SysML v2) was released as the next-generation systems modeling language, offering improved semantic rigor and reusability, yet lacking native constructs aligned with PSUM for first-class uncertainty representation. This paper proposes a systematic extension of SysML v2 that incorporates the PSUM metamodel into its modeling framework. The extension enables explicit specification of indeterminacy sources, structured characterization of uncertainties, and consistent propagation of uncertainty within system models, while preserving conformance with SysML v2 syntax and semantics. We validate the approach through seven case studies. Results demonstrate that the proposed extension (PSUM-SysMLv2) is expressive and applicable for uncertainty-aware MBSE, and potentially enables uncertainty and uncertainty propagation analyses.

Uncertainty Modeling for SysML v2

TL;DR

A systematic extension of SysML v2 that incorporates the PSUM metamodel into its modeling framework, which enables explicit specification of indeterminacy sources, structured characterization of uncertainties, and consistent propagation of uncertainty within system models, while preserving conformance with SysML v2 syntax and semantics.

Abstract

Uncertainty is inherent in modern engineered systems, including cyber-physical systems, autonomous systems, and large-scale software-intensive infrastructures (such as microservice-based systems) operating in dynamic and partially observable environments. The recent publication of Precise Semantics for Uncertainty Modeling (PSUM) by the Object Management Group represents the first standardized specification for uncertainty modeling within the Model-Based Systems Engineering (MBSE) community, providing formally defined semantics for representing and reasoning about uncertainty in models. In parallel, the second version of Systems Modeling Language (SysML v2) was released as the next-generation systems modeling language, offering improved semantic rigor and reusability, yet lacking native constructs aligned with PSUM for first-class uncertainty representation. This paper proposes a systematic extension of SysML v2 that incorporates the PSUM metamodel into its modeling framework. The extension enables explicit specification of indeterminacy sources, structured characterization of uncertainties, and consistent propagation of uncertainty within system models, while preserving conformance with SysML v2 syntax and semantics. We validate the approach through seven case studies. Results demonstrate that the proposed extension (PSUM-SysMLv2) is expressive and applicable for uncertainty-aware MBSE, and potentially enables uncertainty and uncertainty propagation analyses.
Paper Structure (27 sections, 6 figures, 5 tables)

This paper contains 27 sections, 6 figures, 5 tables.

Figures (6)

  • Figure 1: The belief profile of PSUM-SysMLv2. The classes in grey are stereotypes while those in white are either KerML or SysML v2 metaclasses.
  • Figure 2: The PSUM-SysMLv2 uncertainty profile. The classes in grey are stereotypes while those in white are SysML v2 metaclasses
  • Figure 3: Model snippet illustrating additional uncertain transitions in MF
  • Figure 4: Model snippet illustrating indeterminacy sources in MF
  • Figure 5: Model snippet illustrating uncertainty-to-uncertainty propagation in AF
  • ...and 1 more figures

Theorems & Definitions (12)

  • Example 1
  • Example 2
  • Example 3
  • Definition 1
  • Definition 2
  • Example 4
  • Definition 3
  • Definition 4
  • Definition 5
  • Definition 6
  • ...and 2 more