ANALYTICAL MECHANICS AND MODELLING - 2022/3
Module code: PHY2073
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice during the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
The module provides a coherent development of the methods of analytical classical mechanics and their applications for students at FHEQ 5 level. The module develops both the necessary formal background and provides practical experience and examples of several applications that enable the derivation of the equations of motion for a more diverse set of physical systems. The module incorporates an existing computational modelling experience that will support the taught material through the numerical implementation and study of a particular physical system.
FAUX David (Physics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 5
JACs code: F300
Module cap (Maximum number of students): N/A
Overall student workload
Workshop Hours: 22
Independent Learning Hours: 95
Lecture Hours: 22
Tutorial Hours: 11
Prerequisites / Co-requisites
Indicative content includes:
- Introduction and review: Vector nature of Newton’s Laws, the motions of sytems of interacting particles, conservation laws, Energy and the Minimum Energy Principle, degrees of freedom and constraints, Principle of Virtual Work and D’Alembert’s Principle (with their applications to simple mechanical systems).
- Lagrangian Mechanics: Generalised co-ordinates, velocities and forces, and the derivation of Lagrange’s equation. Applications of the Lagrange equation to projectile motion, pendula, motion and orbital properties in a central potential, motion in a rotating frame and rotational motion, oscillatory systems and normal modes analysis.
- Hamiltonian Mechanics: Generalised momenta, derivation of Hamilton’s equations of motion. Revisit of several of the applications in the Hamiltonian formulation.
|Assessment type||Unit of assessment||Weighting|
|Coursework||COMPUTATIONAL MODELLING PROJECT (INTERIM REPORT)||8|
|Coursework||COMPUTATIONAL MODELLING PROJECT (FINAL REPORT)||22|
|Examination||End of semester Examination - 2 hours||70|
The assessment strategy is designed to provide students with the opportunity to demonstrate:
Familiarity and understanding, via unseen problems, of the content of the course materials and the ability to apply these in a new and unrehearsed situation. To apply computational methods and expertise taught in other courses to develop a methodology and computer code to solve and analyse a physical dynamical system of their choosing, with emphasis on the accuracy and the physical results of the model constructed.
Thus, the summative assessment for this module consists of:
· Closed book examination of duration 2.0hrs comprising a section A of compulsory questions and a section B in which students answer 2 questions from 3 (70%)
· Computational modelling project (30%), comprising an assessed interim report (8%) and an assessed final report (22%).
Formative feedback on the lecture-based material will be provided weekly through tutorials.
Weekly interactive meetings take place in the computational laboratories with feedback on methods and the science. Tutorial support and feedback on progress on examples sheets will be provided as part of the timetable.
- review the vector-based mechanics of Newton and disuss the role of conservation laws
- provide a coherent development, via the Minimum Energy, Virtual Work and D'Alembert Principles, of the physical basis and application of the Lagrangian and Hamiltonian formulations of classical dynamical systems and their solution.
- by the use of examples and selected applications, develop a familarity and a working knowledge of the appropriate choice of generalised coordinates and of constructing the Lagrangian and Hamitonian equations of motion for e.g. linear and rotational motion.
- via the computational modelling component of the module, give a practical experience of the numerical implementation and the solution of a chosen dynamical system.
|1||State, derive and use the Minimum Energy, Virtual Work and D'Alembert Principles to solve introductory problems in classical mechanics||KCT|
|2||State Lagrange's and Hamilton’s equations of motion (K). Be able to choose a suitable of generalised coordinates and construct the Lagrangian and Hamiltonian for a range of dynamical systems, and so derive the relevant equations of motion||KCT|
|3||Code, solve and study a computational model of a chosen dynamical system||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
Support the practical, problem solving and computational applications of the methods by the provision of a coherent series of lectures that develop the physical basis and derive the formal methods that underpin the (differential) equations of motion of Lagrange and Hamilton.
The learning and teaching methods include:
Lectures and tutorial periods to introduce the mathematical and formal methods and to practice the application of these methods to model systems in a supported tutorial environment.
Computational laboratory sessions for the conduct of an individual project that is designed to reinforce to major concepts of the lecture course.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: PHY2073
Programmes this module appears in
|Physics with Quantum Technologies BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Physics with Quantum Technologies MPhys||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Physics MPhys||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Physics BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.