Advanced MBSE: Simulation and Automated Testing Course

Course Outline

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.

Advanced MBSE: Simulation and Automated Testing Course Benefits

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

Chapter 1 Fundamentals of Model Based Systems Engineering

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

Chapter 2 Data Types and Parameters

Cross-reference requirements with structures, behaviors, and parametrics
Use constraints to capture formulas for reuse
Add specific types for additional model integrity

Chapter 3 Deploying Parametric Diagrams

Connecting structure to behavior with parametric diagrams
Use binding parameters to achieve the connections
See the results of equations by running a simulation

Chapter 4 Incorporating Add-Ons

Add external modeling elements via other tools
Use OpenModelica to model an equation
Visualize functionality in Simulink

Chapter 5 Writing Scripts

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

Chapter 6 Requirements Testing, Validation, and Reporting

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