If it moves we can model it: Teaching Engineering Dynamics using Computational Thinking
Time & Place
Thu, 28 Mar 2019 12:00:00 NZDT in E14 (Lecture Theatre), Engineering CORE
In this presentation, it will be demonstrated how MATLAB supports the teaching of Engineering dynamics. The proposed workflow incorporates tasks involving both symbolic and numeric computing – a natural combination that leads to deeper learning engagements with students.
A collection of case studies from Mechanical and Mechatronic engineering will be presented, including:
- Modelling an autonomous 4 wheel vehicle controlled by a computer vision algorithm.
- A demo packet developed for the Droid Racing Challenge student competition
- Modelling a 2-dof nonplanar robotic manipulator
- Modelling a quadcopter balancing and inverted pendulum
- Modelling a solenoid.
In this session, it will be demonstrated how the following deeper learning attributes are encouraged with students:
- Complex problems can be broken down into a series of smaller problems.
- A problem-solving narration consists of signposting an engineering principle, followed immediately by its implementation – keeping these 2 components together encourages a deep learning mindset.
- Curiosity can be fostered, leading to students wanting to “create” and “do”
- If the engineering principles are understood, then utilise technology to overcome large and tedious computations.
- Immediately and easily, solve (numerically) the derived equations.
All are welcome!
Bradley Horton is a member of the Academic Customer Success team at MathWorks, helping faculty members better utilize MATLAB and Simulink for education and research. Bradley has supported and consulted for clients on projects in process control engineering, power systems simulation, military operations research, and earthquake impact modelling. Before joining MathWorks, Brad spent 5 years as a systems engineer with the Defence Science & Technology Organisation (DSTO) working as an operations research analyst. Bradley holds a B.Eng. in Mechanical engineering and a B.Sc. in Applied mathematics.