Category Archives: Thermodynamics

Isolated systems in nature?

Is a coconut an isolated thermodynamic system?  This is a question that I have been thinking about this week.  A coconut appears to be impermeable to matter since its milk does not leak out and it might be insulated against heat transfer because its husk is used for insulation in some building products.  If you are wondering why I am pondering such matters, then it is because, once again, I am teaching thermodynamics to our first year students (see ‘Pluralistic Ignorance‘ on May 1st, 2019).  It is a class of more than 200 students and I am using a blended learning environment (post on 14th November 2018) that combines lectures with the units of the massive open online course (MOOC) that I developed some years ago (see ‘Engaging learners on-line‘ on May 25th, 2016).  However, before devotees of MOOCs get excited, I should add that the online course is neither massive nor open because we have restricted it to our university students.  In my first lecture, I talked about the concept of defining the system of interest for thermodynamic analysis by drawing boundaries (see ‘Drawing boundaries‘ on December 19th, 2012).  The choice of the system boundary has a strong influence on the answers we will obtain and the simplicity of the analysis we will need to perform.  For instance, drawing the system boundary around an electric car makes it appear carbon neutral and very efficient but including the fossil fuel power station that provides the electricity reveals substantial carbon emissions and significant reductions in efficiency.  I also talked about different types of system, for example: open systems across whose boundaries both matter and energy can move; closed systems that do not allow matter to flow across their boundaries but allow energy transfers; and, isolated systems that do not permit energy or matter to transfer across their boundaries.  It is difficult to identify closed systems in nature (see ‘Revisiting closed systems in nature‘ on October 5th, 2016); and so, once again I asked the students to suggest candidates but then I started to think about examples of isolated systems.  I suspect that completely isolated systems do not exist; however, some systems can be approximated to the concept and considering them to be so, simplifies their analysis.  However, I am happy to be corrected if anyone can think of one!

Image: https://www.flickr.com/photos/yimhafiz/4031507140 CC BY 2.0

Thought leadership in fusion engineering

The harnessing of fusion energy has become something of a holy grail – sought after by many without much apparent progress.  It is the energy process that ‘powers’ the stars and if we could reproduce it on earth in a controlled environment then it would offer almost unlimited energy with very low environmental costs.  However, understanding the science is an enormous challenge and the engineering task to design, build and operate a fusion-fuelled power station is even greater.  The engineering difficulties originate from the combination of two factors: the emergent behaviour present in the complex system and that it has never been done before.  Engineering has achieved lots of firsts but usually through incremental development; however, with fusion energy it would appear that it will only work when all of the required conditions are present.  In other words, incremental development is not viable and we need everything ready before flicking the switch.  Not surprisingly, engineers are cautious about flicking switches when they are not sure what will happen.  Yet, the potential benefits of getting it right are huge; so, we would really like to do it.  Hence, the holy grail status: much sought after and offering infinite abundance.

Last week I joined the search, or at least offered guidance to those searching, by publishing an article in Royal Society Open Science on ‘An integrated digital framework for the design, build and operation of fusion power plants‘.  Working with colleagues at the Culham Centre for Fusion Energy, Richard Taylor and I have taken our earlier work on an integrated nuclear digital environment for the nuclear energy using fission [see ‘Enabling or disruptive technology for nuclear engineering?‘ on january 28th, 2015] and combined it with the hierarchical pyramid of testing and simulation used in the aerospace industry [see ‘Hierarchical modelling in engineering and biology‘ on March 14th, 2018] to create a framework that can be used to guide the exploration of large design domains using computational models within a distributed and collaborative community of engineers and scientists.  We hope it will shorten development times, reduce design and build costs, and improve credibility, operability, reliability and safety.  It is a long list of potential benefits for a relatively simple idea in a relatively short paper (only 12 pages).  Follow the link to find out more – it is an open access paper, so it’s free.

References

Patterson EA, Taylor RJ & Bankhead M, A framework for an integrated nuclear digital environment, Progress in Nuclear Energy, 87:97-103, 2016.

Patterson EA, Purdie S, Taylor RJ & Waldon C, An integrated digital framework for the design, build and operation of fusion power plants, Royal Society Open Science, 6(10):181847, 2019.

Meta-knowledge: knowledge about knowledge

As engineers, we like to draw simple diagrams of the systems that we are attempting to analyse because most of us are pictorial problem-solvers and recording the key elements of a problem in a sketch helps us to identify the important issues and select an appropriate solution procedure [see ‘Meta-representational competence’ on May 13th, 2015].  Of course, these simple representations can be misleading if we omit parameters or features that dominate the behaviour of the system; so, there is considerable skill in idealising a system so that the analysis is tractable, i.e. can be solved.  Students find it especially difficult to acquire these skills [see ‘Learning problem-solving skills‘ on October 24th, 2018] and many appear to avoid drawing a meaningful sketch even when examinations marks are allocated to it [see ‘Depressed by exams‘ on January 31st, 2018].  Of course, in thermodynamics it is complicated by the entropy of the system being reduced when we omit parameters in order to idealise the system; because with fewer parameters to describe the system there are fewer microstates in which the system can exist and, hence according to Boltzmann, the entropy will be lower [see ‘Entropy on the brain‘ on November 29th, 2017].  Perhaps this is the inverse of realising that we understand less as we know more.  In other words, as our knowledge grows it reveals to us that there is more to know and understand than we can ever hope to comprehend [see ‘Expanding universe‘ on February 7th, 2018]. Is that the second law of thermodynamics at work again, creating more disorder to counter the small amount of order achieved in your brain?

Image: Sketch made during an example class

Pluralistic ignorance

This semester I am teaching an introductory course in Thermodynamics to undergraduate students using a blended learning approach [see ‘Blended learning environments‘ on November 14th, 2018].  The blend includes formal lectures, example classes, homework assignments, assessed coursework questions and an on-line course, which I delivered as a MOOC a couple of years ago [see ‘Engaging learners on-line‘ on May 25th, 2016].  It is not unusual in a large class, nearly two hundred students this year, that no one asks questions during the lecture; although, at the end of each lecture and example class, a small group of students with questions always forms.  The on-line course has extensive opportunities for asking questions and discussing issues with the instructor and fellow learners.  These opportunities  were used heavily when the course was offered as a MOOC  with 6600 comments posted or 1 every 7.7 minutes!  However, this year the undergraduates have not made any on-line comments and it was a similar situation last year.  Is this a case of pluralistic ignorance?  The term was coined by psychologists Daniel Katz and Floyd Henry Allport in 1931 to describe students who pretend to understand everything explained in class and don’t ask any questions because they believe everyone else in the class has understood everything and they don’t want to damage their reputation with their peers.  Perhaps we have all done it and been very grateful when someone has asked the question that we wanted to ask but did not dare.  Would be it ethical to pretend to be a student and post questions on-line that I know from the MOOC they are likely to want to ask?

Sources:

Patterson EA, Using everyday engineering examples to engage learners on a massive open online course, IJ Mechanical Engineering Education, in press.

Katz D & Allport FH, Students’ attitude, Syracuse, NY: Craftsmann, 1931.

Origgi G, Reputation: what it is and why it matters, Princeton, NJ: Princeton University Press, 2018.

Image: Author speaking at National Tsing Hua University, Taiwan