Maplesoft Solutions for Model-Based Systems Engineering Projects

How Maplesoft products are being used as critical components within MBSE system design processes.

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The Role of Multidomain Dynamic Models for Functional Verification in Model-Based Systems Engineering.

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As engineering organizations adopt Model-based Systems Engineering (MBSE) methodologies, Maplesoft's technologies are being increasingly used to bridge the gap between the architectural systems model and the analytical tasks throughout the rest of the system design process.

Maplesoft products simplify the creation of system architecture and requirements, as well as providing critical support in the early analytical stages.

Creation, maintenance, and validation of requirements and systems models

Computation and management of executable requirements

Functional verification through system-level synthesis

Creation, maintenance, and validation of requirements and systems models

In the world of Model Based Systems Engineering, specialized tools help define high-level system requirements that are used throughout the design chain. Most engineers don't have the training needed to use these complex tools, but their input into system requirements remains vital. With customization by the Maplesoft Engineering Solutions team to meet your specific needs, MapleMBSE makes collaboration on requirements accessible to all stakeholders, providing streamlined interfaces for each task in your MBSE project. By giving more engineers an easy connection to MBSE tools, you can work faster, reduce errors, and ensure a system-wide collaboration on your next project.

With its intuitive, Excel®-based interface, you can perform tasks more quickly and accurately in MapleMBSE than in other MBSE tools.

MBSE executable requirements can be imported into Maple

Executable Requirements can be imported, computed and documented in Maple

Computation and Management of Executable Requirements

Very often, the MBSE model will include many quantitative requirements that are defined as mathematical expressions. However, it won't be until these expressions have been combined and executed that a likely conflict will arise.

Maple provides a powerful, rigorous environment for importing these requirements from the architectural model, combining the related expressions together and computing the results. Not only that, since all the expressions are handled as equations, analysts are freed from the constraint of deciding which variables are dependent and independent so early in the process. This allows them to perform trade-off studies on any of the parameters and relationships to resolve design conflicts. Moreover, it is done in a live technical document environment that allows analysts to document their work with the mathematical expressions at a level of quality that would be expected in a technical publication or design manual.

Functional Verification through System-level Synthesis

A powerful benefit of MBSE is that once the system architecture has been defined, it is relatively easy step to create a physics-based model in MapleSim that matches the structure of the architectural model. The subsystems and components that make up the system can be populated with the necessary mathematical information to define their dynamic behavior. In this way, engineering analysts can create a virtual prototype, or “functional mockup”, of the system to verify against the design requirements in the architectural model. Doing this very early in the process often highlights issues in the design that can be addressed quickly. This has been proven to reduce the risk of failure - and associated delays and costs - later in the process.

Verification of the design requires the functional mockup to be tested through numerous simulated duty cycles, requiring many compliance tests per simulation. This task is considerably eased through the use of Process Integration tools such as ModelCenter from Phoenix Integration. With its MBSE Analysis Pack, ModelCenter can be used to integrate the MapleSim functional mockup with SysML architectural models, automate the many requirement-compliance tests and report any non-compliances. This can then be carried through the entire design and development process, adding further details from other analyses, such as FEA and CFD studies, to enhance the accuracy of the functional mockup. This increases confidence in the design and significantly reduces the risk of late-stage design changes that add unbudgeted delays and costs to the project.