MEC452: Advanced Dynamics

Vibrations in real structures are rarely linear or even sinusoidal. This is the module where you will become confident in handling the maths and physics that govern random and nonlinear structural dynamics.

Dr. Nikolaos Dervilis, Module Lead

Module Description

In this module we will explore how linear/nonlinear structures vibrate and how we can model them in order to understand and optimise their complex behaviour both analytically and numerically. We will uncover the behaviour of theoretical nonlinear models and we will explore and evaluate the fascinating world of advanced dynamics, random vibration, nonlinear systems and chaos through lectures and dedicated reading. We link advanced engineering with concepts from physics and maths that are of core importance in the new era of engineering, considering structures from light aerospace structures to offshore wind turbines and space shuttles. Furthermore, we will discover the world of Hamiltonian mechanics by capturing its fundamental physics. The learning will be supported by dedicated tutorial sessions. 

Key Concepts & Assumed Knowledge

Students are expected to have some knowledge of structural vibrations.

Teaching Methods

• Lectures

• Tutorials

• Independent Study

Assessment Methods

• 100% Exam: Here students will be asked to derive and solve the equations of motion of complex systems as well as evaluate their knowledge in real engineering scenarios using critical thinking and combining knowledge to overcome advanced vibration scenario.

Module Aims

• Allow students to explore the use of advanced mathematical and statistical models to capture the behaviour of vibrating structures/systems -both linear and nonlinear, -subject to harmonic and random vibration, in order to contribute to the robust and safe design of structures under complex conditions.

• Support students in developing the necessary analytical, numerical and statistical tools in order to investigate nonlinear systems and chaos. We will also touch on how things like artificial intelligence and machine learning tools can be utilised nowadays in order to simplify our analysis for complex structural behaviours.

• Develop students so they are able to optimise and connect mathematical models with experimental analysis and explore how we can analyse and update structures/systems in operation.

• Challenge students to apply their existing foundational understanding of (mechanical) engineering to a greater range and depth suitable for a research or industrial environment.