A Model-Based System Engineering Approach to Support System Architecting Activities in Early Aircraft Design

The aviation industry aims to reduce its environmental footprint and meet ambitious environmental targets, prompting the exploration of novel aircraft concepts and systems, such as hybrid-electric or distributed propulsion. These emerging technologies introduce complexity to aircraft system architectures, requiring innovative approaches to design, optimization, and safety assessment, particularly for system architecting. Several aspects of system architecting specification and evaluation are typically performed separately, using different people and a mix of manual and model-based processes. Connecting these activities has the potential to make the design process more efficient and effective. This thesis explores how a Model-Based Systems Engineering (MBSE) specification environment can be structured and enriched to enable a better bridge to Multidisciplinary Design Analysis and Optimization (MDAO) and Model-Based Safety Assessment (MBSA) activities. The proposed MBSE approach focuses on enhancing system specifications, particularly for unconventional system architectures, which typically feature greater variability in early design stages. Using the ARCADIA/Capella MBSE environment, a multi-level approach is proposed to structure the system architecture specification and the Property Value Management Tool (PVMT) add-on is used to facilitate the bridge to other system architecting activities. In addition, a catalogue of modeling artifacts is established to facilitate the development of various hybrid-electric system configurations. The MDAO link mechanism is demonstrated with an example from the collaborative AGILE4.0 project. Two test cases demonstrate the implementation of the approach: a hybrid-electric propulsion system and associated sub-systems for the overall approach and the landing gear braking system for the model-based Functional Hazard Analysis (FHA), as an example of an MBSA activity. Overall, this thesis helps improve the integration and collaboration between engineers working on MBSE, MDAO, and MBSA. This better integration will help to reduce the development time and risk. Therefore, the presented thesis contributes to a more efficient aircraft development process, enabling the industry to tackle the emerging needs of unconventional aircraft systems and their integration

Probabilistic Reachability Analysis for Large Scale Stochastic Hybrid Systems

This paper studies probabilistic reachability analysis for large scale stochastic hybrid systems (SHS) as a problem of rare event estimation. In literature, advanced rare event estimation theory has recently been embedded within a stochastic analysis framework, and this has led to significant novel results in rare event estimation for a diffusion process using sequential MC simulation. This paper presents this rare event estimation theory directly in terms of probabilistic reachability analysis of an SHS, and develops novel theory which allows to extend the novel results for application to a large scale SHS where a very huge number of rare discrete modes may contribute significantly to the reach probability. Essentially, the approach taken is to introduce an aggregation of the discrete modes, and to develop importance sampling relative to the rare switching between the aggregation modes. The practical working of this approach is demonstrated for the safety verification of an advanced air traffic control example

Workshop on Verification and Theorem Proving for Continuous Systems (NetCA Workshop 2005)

Oxford, UK, 26 August 200

Extending Hybrid CSP with Probability and Stochasticity

Probabilistic and stochastic behavior are omnipresent in computer controlled systems, in particular, so-called safety-critical hybrid systems, because of fundamental properties of nature, uncertain environments, or simplifications to overcome complexity. Tightly intertwining discrete, continuous and stochastic dynamics complicates modelling, analysis and verification of stochastic hybrid systems (SHSs). In the literature, this issue has been extensively investigated, but unfortunately it still remains challenging as no promising general solutions are available yet. In this paper, we give our effort by proposing a general compositional approach for modelling and verification of SHSs. First, we extend Hybrid CSP (HCSP), a very expressive and process algebra-like formal modeling language for hybrid systems, by introducing probability and stochasticity to model SHSs, which is called stochastic HCSP (SHCSP). To this end, ordinary differential equations (ODEs) are generalized by stochastic differential equations (SDEs) and non-deterministic choice is replaced by probabilistic choice. Then, we extend Hybrid Hoare Logic (HHL) to specify and reason about SHCSP processes. We demonstrate our approach by an example from real-world.Comment: The conference version of this paper is accepted by SETTA 201