SysML Models, part of Model Based System Engineering (MBSE) are more than just diagrams. They provide a mechanism for testing and experimentation. Connecting elements of the model, directly to a corresponding real-world entity (device, processes) leads to the digital twin. Data monitored on the actual entity (possible with IoT (Internet of Things) devices) can be fed into the digital twin, leading to a more realistic and testable model.
Requirements incorporated into the model, instead of being captured in various external documents, can be validated within the model as well.
This 2-day Hands-On Simulation and Automated Testing course provides the knowledge to build more robust models. In addition to requirements validation, attendees will also add more applicable data types, connect external programming scripts, and incorporate modeling elements from other tools.
The course case study builds upon the model built in course 3682, Model Based System Engineering with SysML. The model will be connected to a digital twin. Attendees will be able to validate requirement expectations by simulating actual environmental conditions.
Simulation and Automated Testing Course Delivery Methods
Simulation and Automated Testing Course Information
In this course, you will learn how to:
- Generate results of the theoretical situations by using a digital twin.
- Create domain-specific data types to build a more robust model.
- <> to capture equations and formulas.
- Use parametric diagrams to link structural and behavioral diagrams.
- Leverage existing models generated via external modeling tools.
- Use opaque behaviors to run code blocks of various languages.
- <> blocks via <> and <> blocks and subsequent simulations.
Training Prerequisites
You should have a fundamental understanding of systems engineering.
It is suggested that attendees have knowledge at the level of course 3682, Model Based System Engineering with SysML.
Simulation and Automated Testing Course Outline
- Describe the benefits of building a digital twin
- Review the principles and pillars of MBSE
- Leverage symbols and diagrams to capture the appropriate level of a system’s model
- Walk through diagrams in simulation mode
- Cross-reference requirements with structures, behaviors, and parametrics
- Use constraints to capture formulas for reuse
- Add specific types for additional model integrity
- Connecting structure to behavior with parametric diagrams
- Use binding parameters to achieve the connections
- See the results of equations by running a simulation
- Add external modeling elements via other tools
- Use OpenModelica to model an equation
- Visualize functionality in Simulink
- Generate part of the model in a programming language for reusability
- Add opaque behaviors to an activity diagram to execute code directly
- Add an opaque behavior to call an external Python script
- Add constraints to the model to validate it is executing requirement specifications
- Testing the digital twin to see if it behaves correctly in extreme conditions
- Extract documentation from the model to share with other stakeholders
