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School of Engineering and Informatics (for staff and students)

Mechanical Dynamics (518H3)

Mechanical Dynamics

Module 518H3

Module details for 2025/26.

15 credits

FHEQ Level 7 (Masters)

Module Outline

State space modelling of dynamic systems; self-excited vibration and instability; various non-linear phenomena; applications of the Finite-Element Method in dynamics; the Rayleigh-Ritz method; linear model reduction techniques; MDOF models of linear damping; the effect of damping on natural frequencies and mode shapes; forced vibration of general linear MDOF systems: time and frequency domain analysis, solution via DFT; review of probability theory and the normal distribution; introduction to stochastic processes, correlation functions, and power spectral densities; random vibration analysis of linear dynamic systems; international standards on machine vibration levels.

The syllabus is covered by the the following AHEP4 learning outcomes: M1, M2, M3, M4, M17

Library

Clough R W and Penzien J, 1993. Dynamics of Structures, McGraw-Hill, 2nd ed.
Newland D E, 1994. Mechanical Vibrations Analysis and Computation, Longman.
Rao I S S, 1995. Mechanical Vibrations, Addison Wesley.
Brogan W L, 1991 . Modern Control Theory Prentice Hall, 517-521.
Panovko Y G and Gubanova I I, 1965. Stability and Oscillations of Elastic Systems, Consultants Bureau.
Harris C M (Ed in Chief), 1996. The Shock and Vibration Digest, McGraw-Hill.
Inman D J 2001 Prentice Hall, Engineering Vibration, 2nd Edition
Close M C, Frederick D H, Newell JC, 2002, Wiley, Modelling and analysis of Dynamic Systems, 3rd Edition

Module learning outcomes

Systematically understand key aspects of the mathematical and mechanical science principles which form the basis for the analysis of mechanical dynamics

Comprehensively understand the techniques and methods used in the analysis of dynamics of structures to study: modal properties, forced response (harmonic and transient), self-excited vibrations, parametrically excited vibrations

Demonstrate critical awareness of the importance of the appropriate modelling and demonstrate knowledge and comprehensive understanding of model reduction techniques and state space modelling .

Act independently in critical decision making on the choice of modelling approaches and methods for the analysis of complex problems

TypeTimingWeighting
Unseen ExaminationSemester 1 Assessment80.00%
Coursework20.00%
Coursework components. Weighted as shown below.
ReportT1 Week 11 100.00%
Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

TermMethodDurationWeek pattern
Autumn SemesterLecture3 hours11111111111

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Yevgen Petrov

Assess convenor
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The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.

School of Engineering and Informatics (for staff and students)

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