Populating MBSE Models from MDAO Analysis

Aiello, Ombeline; Kandel, David Sanchez Del Rio; Chaudemar, Jean-Charles; Poitou, Olivier; Saqui-Sannes, Pierre de

doi:10.1109/isse51541.2021.9582519

Cited by 8 publications

(10 citation statements)

References 19 publications

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“…The output of the design steps is the architecture of blocks, where each block is described internally by the state machine. The method proposed in [14] cuts off the direct connection between the analysis and design steps. This work has made modifications to it [14], as shown in figure 1.…”

Section: Icmsoa-2023 Journal Of Physics: Conference Series 2755 (2024...mentioning

confidence: 99%

“…The method proposed in [14] cuts off the direct connection between the analysis and design steps. This work has made modifications to it [14], as shown in figure 1. On the MBSE side, the incomplete parameters defined by the requirements and structure are transferred to the MDAO tool through simulation calculation and analysis steps.…”

Section: Icmsoa-2023 Journal Of Physics: Conference Series 2755 (2024...mentioning

confidence: 99%

“…In [13], Wolny S et al conducted a survey and analysis of SysML papers on the joint use of MBSE and MDAO in the early development stage over the past 13 years and found that SysML and SysML tools were extensively combined with other MBSE tools and methods, but very few MDAO solutions being implemented in MBSE system models. Thereby, Aïello O et al [14] discuss the coupling problem between MBSE and MDAO. The MBSE part relies on SysML and Time Automata, while the MDAO part is developed based on Open MDAO.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

Qi,

Luo,

Zhao

et al. 2024

J. Phys.: Conf. Ser.

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The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

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Section: Icmsoa-2023 Journal Of Physics: Conference Series 2755 (2024...mentioning

confidence: 99%

Section: Icmsoa-2023 Journal Of Physics: Conference Series 2755 (2024...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

Qi,

Luo,

Zhao

et al. 2024

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…Reuse of models is not addressed, and the MDAO problem remains a black box for the system engineer. A further work [51] focuses on the refinement of requirements in MBSE by linking them to MDAO. For this purpose, tool interfaces between TTool, OpenMDAO, and UPPAAL-SMC are implemented.…”

Section: Related Workmentioning

confidence: 99%

Optimization Workflows for Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO)

et al. 2022

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Developing modern products involves numerous domains (controlling, production, engineering, etc.) and disciplines (mechanics, electronics, software, etc.). The products have become increasingly complex while their time to market has decreased. These challenges can be overcome by Model-Based Systems Engineering (MBSE), where all development data (requirements, architecture, etc.) is stored and linked in a system model. In an MBSE system model, product requirements at the system level can lead to numerous technical variants with conflicting objectives at the parameter level. To determine the best technical variants or tradeoffs, Multidisciplinary Analysis and Optimization (MDAO) is already being used today. Linking MBSE and MDAO allows for mutually beneficial synergies to be expected that have not yet been fully exploited. In this paper, a new approach to link MBSE and MDAO is proposed. The novelty compared to existing approaches is the reuse of existing MBSE system model data. Models developed during upstream design and test activities already linked to the MBSE system model were integrated into an MDAO problem. Benefits are reduced initial and reconfiguration efforts and the resolution of the MDAO black-box behavior. For the first time, the MDAO problem was modeled as a workflow using activity diagrams in the MBSE system model. For a given system architecture, this workflow finds the design variable values that allow for the best tradeoff of objectives. The structure and behavior of the workflow were formally described in the MBSE system model with SysML. The presented approach for linking MBSE and MDAO is demonstrated using an example of an electric coolant pump.

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“…The RTS pattern presented in this paper could be easily instantiated on different real time systems, such as electrically assisted bicycles, drones exploring buildings [16], and drones exploring high-voltage lines [17].…”

Section: Design Stepmentioning

confidence: 99%

Mind Maps Upstream SysML v2 Diagrams

Saqui-Sannes

Vingerhoeds

Damouche

et al. 2022

2022 IEEE International Systems Conference (SysCon)

Self Cite

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Over the past two decades, the promoters of Model Based Systems Engineering (MBSE) have encouraged systems engineers to transition from document-centric approaches to model-based ones. Literacy of systems engineers in reading, sharing and elaborating models has therefore become an issue. Whatever the modeling language, elaboration of models is a highly complex intellectual process and SysML is no exception. Feedback from industry practitioners and MBSE lecturers suggests that developers of SysML models often stumble on the same problem: thinking about the system before modeling it in SysML. The authors of this paper propose to ease that elaboration process by using mind maps. With their graphic form and rather flexible way of organizing ideas, mind maps turn out to be a good candidate to help thinking about the system. Unlike approaches that directly switch from mind maps to SysML diagrams dedicated to one specific system, this paper introduces an intermediate step: mind maps first enable elaboration of diagrams patterns. The latter may in turn be instantiated on one or several systems. Without loss of generality, the proposed approach is step-wise illustrated on real-time systems monitored by software controllers. Patterns are proposed to cover need expression, requirement capture, use case driven analysis and design.

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Populating MBSE Models from MDAO Analysis

Cited by 8 publications

References 19 publications

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

Optimization Workflows for Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO)

Mind Maps Upstream SysML v2 Diagrams

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