Siyuan Ji

Charles Lewis, Amal Elsokary, Siyuan Ji

Model-Based Systems Engineering (MBSE) is widely treated as the backbone of digital engineering, with languages such as the Systems Modeling Language (SysML) providing the means to capture system structure, behaviour, and verification intent. Yet once verification moves to hardware, the system model is routinely left behind. Domain-specific simulation environments, model transformations, and bespoke tool integrations take over, and the model that began as the authoritative reference drifts out of sync with the implementation it was meant to govern. This paper introduces the SysML Hardware Interface Architecture (SHIA), which keeps an executable SysML model directly inside the verification loop, exchanging messages with physical hardware without intermediate transformation chains, co-simulation platforms, or broker-mediated plugins. SHIA is realised through a SysML side server, written in embedded C++ within IBM Rhapsody, and a hardware side server running on a Raspberry Pi, together establishing a bidirectional link between the digital model and the physical system. A logic gate case study demonstrates the approach end-to-end, from hardware model construction and prototype assembly to test harness design, behavioural statechart control, and staged verification of each component before integration. The integrated system exchanged messages correctly in both directions, and Karnaugh map comparison between the SysML-generated and hardware-generated outputs showed zero discrepancy. The result shows that, when paired with a suitable interface, SysML need not remain a static description that informs downstream tools; it can serve as the executable layer through which hardware behaviour is stimulated, observed, and verified. The work demonstrates a route to model-governed verification and a shorter digital thread between system architecture and the hardware that realises it.

Siyuan Ji

AI tools are being deployed over MBSE models today, and those models were not designed for this kind of consumption. The problem is not simply that tools hallucinate: well-prompted frontier models produce competent, useful output over a conformant SysML model, but the reasoning they produce is drawn from training rather than retrieved from the model itself, and different tools over the same model produce different results with nothing in the record to adjudicate between them. The model, in other words, is functioning as a prompt rather than as a knowledge base. Attaching better tools to the same model does not resolve this. The model and the methodology that governs its construction need to be designed together for AI participation, treating the model as a machine-queryable knowledge substrate rather than a structured artefact for human navigation, and that co-design has not yet happened in any systematic way. This paper works through a concrete workflow scenario to show what that gap looks like in practice, proposes three principles that jointly characterise what model and methodology must achieve together, and closes with a call to the community to begin this work before the architectural decisions about AI integration settle without the methodological foundation they require.

Matthew Harrison, John Carlin, Chengyuan Liu et al.

This paper presents a framework to bridge the gap between subjective stakeholder context and formal system architecture. This is achieved using Soft Systems Methodology (SSM) and Systems Modelling Language version 2 (SysML v2). The methodology utilises the precision of Kernel Modelling Language (KerML) and the alignment of SysML v2 with ISO 42010 to define a reference architecture for the mapping of SSM outputs to SysML v2 concepts such as stakeholders and concerns. Application of the framework is demonstrated through the use of a case study, highlighting the traceable path from stakeholder context to system architecture. The structured mapping and increased semantic precision of SysML v2 are anticipated to reduce the risk of misinterpretation compared to less formal approaches, though empirical validation across diverse stakeholder contexts remains as future work. The primary identified trade-off is the increased barrier to entry associated with SysML v2's textual notation.

Charles E. Dickerson, Michael K. Wilkinson, Eugenie Hunsicker et al.

Architecture Definition, which is central to system design, is one of the two most used technical processes in the practice of model-based systems engineering. In this paper a fundamental approach to architecture definition is presented and demonstrated. The success of its application to engineering problems depends on a precise but practical definition of the term architecture. In the standard for Architecture Description, ISO/IEC/IEEE 42010:2011, a definition was adopted that has been subsumed into later standards. In 2018 the working group JTC1/SC7/WG42 on System Architecture began a review of the adopted definition, holding sessions late in the year. This paper extends and complements a position paper submitted during the meetings; in which Tarski model theory and ISO/IEC 24707:2018 (logic-based languages) were used to better understand relationships between system models and concepts related to architecture. Independent from the working group, it now contributes intuitive fundamental definitions of the terms architecture and system that are used to specify a mathematically based technical process for architecture definition. The engineering utility and benefits to complex system design are demonstrated in a diesel engine emissions reduction case study.

Michael K. Wilkinson, Charles E. Dickerson, Siyuan Ji

The current ISO standards pertaining to the Concepts of System and Architecture express succinct definitions of these two key terms that lend themselves to practical application and can be understood through elementary mathematical foundations. The current work of the ISO/IEC Working Group 42 is seeking to refine and elaborate the existing standards. This position paper revisits the fundamental concepts underlying both of these key terms and offers an approach to: (i) refine and exemplify the term 'fundamental concepts' in the current ISO definition of Architecture, (ii) exploit existing standards for the term 'concept', and (iii) introduce a new concept, Architectural Structure, that can serve to unify the current terminology at a fundamental level. Precise elementary examples are used in to conceptualise the approach offered.

Mole Li, Alan Grigg, Charles Dickerson et al.

Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a Product Line Systems Engineering process is proposed. Specifically, the process extends research in the System Orthogonal Variability Model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of the process in the reduction of variation points, it is further applied to case studies in different engineering domains at different levels of complexity. Subject to system model availability, reduction of 14% to 40% in the number of variation points are demonstrated in the case studies.

Charles Dickerson, Rosmira Roslan, Siyuan Ji

Fault analysis and resolution of faults should be part of any end-to-end system development process. This paper is concerned with developing a formal transformation method that maps control flows modeled in UML Activities to semantically equivalent Fault Trees. The transformation method developed features the use of propositional calculus and probability theory. Fault Propagation Chains are introduced to facilitate the transformation method. An overarching metamodel comprised of transformations between models is developed and is applied to an understood Traffic Management System of Systems problem to demonstrate the approach. In this way, the relational structure of the system behavior model is reflected in the structure of the Fault Tree. The paper concludes with a discussion of limitations of the transformation method and proposes approaches to extend it to object flows, State Machines and functional allocations.