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Human uses of Energy with Professional Skills - PHY00019C

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  • Department: Physics
  • Module co-ordinator: Prof. Roddy Vann
  • Credit value: 20 credits
  • Credit level: C
  • Academic year of delivery: 2019-20
    • See module specification for other years: 2018-19

Related modules

Pre-requisite modules

  • None

Co-requisite modules

  • None

Prohibited combinations


Module will run

Occurrence Teaching cycle
A Autumn Term 2019-20 to Summer Term 2019-20

Module aims

The aim of the professional skills element of this module is to develop the core competencies and knowledge required of any physicist, including a general introduction to the subject, basic IT skills, report writing, use of information resources, experimental techniques, problem solving and computer programming. This will be achieved through a mix of activities, including laboratories, workshops, lectures, programming classes and small group teaching. The knowledge and skills learnt will be further developed in later years.

The “human uses of energy” component of the module aims to give an appreciation of the energy “budget” typical of the world today, in terms of both energy demand (for an appropriate standard of living) and also energy supply. This will enable students to apply basic physics principles to understand the options for energy production (at least partially in the context of carbon emission reduction) and to understand the ways in which energy is used. Working on these topics will develop fundamental physics skills in problem solving, including simplifying problems to render them tractable and making quantitative approximations.

Module learning outcomes

  • Solve a range of problems in various topics surrounding energy usage and supply, applying skills including approximation and simplification, and presenting solutions in ways that are readily comprehensible
  • Discuss the need for energy, a reduced dependence on carbon fuels, and the benefits and/or drawbacks of various production methods, including economic considerations
  • Calculate and/or estimate the energy consumption associated with different activities such as transport and heating.
  • Calculate and/or estimate the (potential) capacity for energy production & storage from various methods, including (but not limited to) wind turbines, hydroelectric and nuclear fusion
  • Understand the thermodynamics of heat pumps and heat engines
  • Make simple estimates of the cost of electricity from different energy sources

Module content

Professional Skills Syllabus

Induction Activities (weeks 1 and 2, term 1):

Introduction to communication skills, study skills, career planning, personal development planning (3 hour lecture). Library: tour of the JB Morrell library (1 hour) and information retrieval exercises. A basic introduction to IT (web, e-mail, etc) and use of Office applications for scientific presentation (3 hours of computer sessions).

Statistics (weeks 4-7, term 1):

Five lectures on basic concepts in probability and statistics, with weekly coursework problems. Covers the notion of probability and binomial, Poisson, and normal probability distributions.

Introduction to Experimental Laboratory

(weeks 2-3, term 1): Three short workshops on experimental measurement techniques, plotting scientific data, and recording data and analysing errors.

(weeks 4-5, term 1): A core experiment to be presented in a formal report (see First Year Laboratory Handbook for full details).

Scientific report writing (week 6, term 1): An introduction to writing scientific reports (1-hour workshop).

Problem solving skills (fortnightly, term 1): Small group discussions with your supervisor, to help develop “thinking-like-a-physicist” skills such as order of magnitude estimations, dimensional analysis, applying differential equations, and curve sketching and interpretation (5 x 1-hour tutorials).

Introductory Python Programming (term 2)

Aims: This course introduces problem solving using computers, using Python as the programming language. The most difficult aspect of programming is designing a step-by-step recipe (algorithm) to solve a given problem. This kind of logical problem solving is a useful skill which is highly valued in research and in the commercial world, and which all physicists should learn through practice. Once an algorithm has been designed, it must be implemented in a programming language, which for this course is Python. Python is a modern language which is freely available for Windows, Linux/Unix and Mac OS with extensive documentation, tutorials and extensions available online. It is easy to learn but very powerful, and is increasingly being used commercially and in scientific research. Students will learn how to create programs in the Python language to solve physics problems and then visualise the results in 2D and 3D. The emphasis is on problem solving, and teaching skills which students can then apply to other areas of their study.

Syllabus

  • Problem solving strategies and algorithm development

  • Computer programming fundamentals and Python

  • Looping with for..in and while loops

  • Control using if, elif and else

  • Getting input from the user, and printing results

  • Debugging and testing methods

  • Python's module system and importing libraries

  • Defining functions and using built-in mathematical functions

  • Using Visual Python to produce animations of mechanics simulations

Mini-conference (weeks 8-10, Term 3)

Students will choose a topic in physics and prepare a short presentation for an informal “mini-conference” in week 10. The emphasis is on enjoyment of physics and relaxed discussion of topics of interest, including subjects that will be explored in greater depth in year 2. Prior to the presentation in week 10, guidance and help will be given on presentation skills and discussion of subject and content.

Human Uses of Energy syllabus (refer also to lecture summary)

  • The need for energy – how much and to whom

  • Vehicle transport

  • Wind power

  • Domestic energy usage

  • Thermodynamics of heat engines & heat pumps

  • Fluctuations in demand and supply

  • Combined heat & power (CHP)

  • Nuclear fusion

  • Health impact & safety

Lecture Notes

Lectures are intended to highlight and explore the key concepts of each topic. Reading of the textbook and other sources will be required for a complete understanding of the course. Lectures will be a blend of delivery and discussion and students are expected to actively participate.

Students will need to make their own lecture notes in addition to those supplied by the lecturer. Lectures will be recorded to allow students to capture all points discussed and additional supporting material will be made available via the VLE.

Assessment

Task Length % of module mark
Essay/coursework
Induction and laboratory activities		 N/A 5
Essay/coursework
Laboratory reports		 N/A 10
Essay/coursework
Marking of lab books		 N/A 5
Essay/coursework
Physics Practice Questions		 N/A 7
Essay/coursework
Python: assignments		 N/A 20
Essay/coursework
Statistics		 N/A 10
University - closed examination
Human uses of Energy		 1.5 hours 43

Special assessment rules

None

Additional assessment information

Assessment

The Python course will be assessed by weekly short multiple-choice tests (10%), followed by five weekly programming assignments of increasing difficulty (first two assignments 15% each, following three assignments 20% each). Programming assignments will be assessed on the quality of source code. (NB. percentages stated in this paragraph are percentages of the total Python course mark, not the total Professional Skills module mark.)

The energy and environment element of the module will be assessed through a combination of Physics Practice Questions and a 1.5 hour examination.

Reassessment

Task Length % of module mark
Essay/coursework
Induction and laboratory activities		 N/A 5
Essay/coursework
Laboratory reports		 N/A 10
Essay/coursework
Marking of lab books		 N/A 5
Essay/coursework
Python: assignments		 N/A 20
University - closed examination
Human uses of Energy		 1.5 hours 43

Module feedback

PPQs within 7 days deadline. Python programming assignments will be returned with comments and suggestions for improvement. Mark for the laboratory note book received from the demonstrator at the end of a completed experiment and receive report back along with a mark sheet that provides a mark and a set of comments/suggestions for each section of the report.

Indicative reading

Practical Physics by G L Squires (Cambridge University Press) ***

Python Programming: An Introduction to Computer Science by John Zelle **

“Sustainable Energy without the hot air” ( also available as a free e-book at http://www.withouthotair.com/ ) by David MacKay

“Energy science : principles, technologies, and impacts” by Andrews & Jelley

“Elementary Climate Physics” by F.W.Taylor


The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.