BMEssentia Platform / Courses / Modelling & Simulation

Course: Engineering Sciences & Systems

Modelling & Simulation

Imagine building virtual models that allow you to test and predict the behavior of complex systems, from mechanical and electrical circuits to biological processes, all without lifting a tool. This course delves into the world of modeling and simulation, a fundamental engineering skill used across industries to solve real-world problems with accuracy and efficiency. From creating mechanical and electrical models to using powerful analytical tools like Laplace transforms and state-space representations, you'll gain hands-on experience in simulating systems that mimic real-world dynamics. Each.

• Engineering Sciences & Systems
• Applied Innovation

12 chapters. Online and self-paced, in English, on the BMEssentia Platform.

What you will learn

• System Modeling Fundamentals: Understand the basics of models, simulations, and system types, enabling accurate predictions across various fields
• Mechanical and Electrical System Simulation: Learn to model mechanical systems like mass-spring-damper and electrical circuits using Kirchhoff's laws and component interactions
• Fluid and Thermal System Analysis: Model fluid flow and heat transfer, vital for HVAC, aerodynamics, and heat exchanger applications.
• Dynamic System Equations: Master state-variable and input-output equations to describe system behavior over time.
• Laplace Transform for System Analysis: Utilize Laplace transforms to solve differential equations and analyze system responses in the frequency domain.
• Frequency-Response Analysis: Apply frequency-response techniques to understand system stability and control, using Bode plots and phase/gain margins.
• Electromechanical System Modeling: Model systems that integrate electrical and mechanical components, such as motors and generators, for automation and robotics.
• State-Space Representation: Analyze complex systems using state-space methods to examine stability, controllability, and observability.
• Linearization Techniques: Approximate nonlinear systems by linearizing them around an operating point, simplifying analysis and control design.
• Applications Across Industries: Discover how modeling and simulation support innovation in automotive, aerospace, biomedical, and environmental engineering.

Modules

1. Basic Definitions and Introduction (Model, Simulation, System)
2. Modeling of Mechanical Systems
3. Modeling Electrical Systems
4. Modeling Electromechanical Systems
5. Modeling Fluid and Thermal Systems
6. Standard Models for Dynamic Systems: State-Variable Equations, State-Space Representation, Linearization
7. Standard Models for Dynamic Systems: Input-Output Equations, Transfer Functions, Block Diagrams, Standard Input Functions
8. Analytical Solution of Linear Dynamic Systems: Analytical Solutions to Linear Differential Equations, First-Order System Response, Second-Order System Response
9. Analytical Solution of Linear Dynamic Systems
10. System Analysis Using Laplace Transforms
11. Frequency-Response
12. Frequency-Response Analysis: Bode Diagrams

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