Category Archives: everyday engineering examples

Pareto principle in train travel

The moral of this story is don’t travel with me.  Last week, I wrote about my train being delayed by someone pulling the emergency handle before we got to the end of the platform in Liverpool [see ‘Stopped in Lime Street’ on June 26th, 2019].  Four days later, I was once again on a late afternoon train to London waiting for it to leave Lime Street station.  This time we didn’t even get started before the train manager announced that a road vehicle had hit a bridge between Crewe and Liverpool; and, so we were being held in Liverpool for an unknown period of time.  I sent a message to my family telling them about the delay and one, an engineer, replied that I was ‘hitting the low frequency failure modes on the service quality pareto’.  The Pareto principle is also known as the 80/20 principle.  I first encountered it when I was working at the University of Sheffield and the Vice-Chancellor,  Professor Gareth Roberts, used it to describe the distribution of research output in academic departments, i.e., 80% of research was produced by 20% of the professors.  In service maintenance, it is assumed that 80% of service interruptions are caused by 20% of the possible failure modes.  Hence, if you can address the correct 20% of failure modes then you will prevent 80% of the service interruptions, which is an efficient use of your resources.  The remaining, unaddressed failure modes are likely to occur infrequently and, hence, can be described as low frequency modes; including passengers pulling emergency handles or people driving vehicles into bridges.

How do you drive into a bridge and block the main railway lines between London and the north-west of England?  Perhaps the driver was using their smart phone which was not smart enough to warn them of the impending collision with the bridge.  So, there’s a new product for someone to develop: a smartphone app that connects to dashboard camera in your vehicle and warns you of impending collisions, or better still just drives the vehicle for you.  Yes, I know some vehicles come with all of this installed but not everyone is driving the latest model; so, a retro-fit system should sell well and protect train passengers from unexpected delays caused by road vehicles damaging rail infrastructure.

By the way, the 14:47 to London magically became the 15:47 to London and left on time!

Christmas diamonds

If you enjoyed a holiday dinner lit by candles then you might be interested to know that the majority of the light from the candle does not come from the combustion of the candle wax in the flame, but from the unburnt soot glowing in the intense heat of the flame.  The combustion process generates the heat and the blue colour in the centre of the flame. However, due to the lack of sufficient oxygen, the combustion of the candle wax is incomplete  and this produces particles of unburnt carbon.  The unburnt carbon forms soot or graphite, but also more exotic structures of carbon atoms, such as nano-diamonds.  The average candle has been estimated to produce about 1.5 million nano-diamonds per seconds, or maybe 10 billion nano-diamonds per Christmas dinner! Unfortunately, they are too small to see otherwise they would add a lot of sparkles to festive occasions.

The picture is an infrared image of a 1cm diameter candle.  About 2cm of the candle height extends from the bottom of the picture and the visible flame is about 2cm high.

Source:

Helen Czerski, Storm in a Teacup: The Physics of Everyday Life, London: Penguin Random House, 2016.

 

Blended learning environments

This is the last in the series of posts on Creating A Learning Environment (CALE).  The series has been based on a workshop given periodically by Pat Campbell [of Campbell-Kibler Associates] and me in the UK and USA, except for the last one on ‘Learning problem-solving skills’ on October 24th, 2018 which was derived on talks I gave to students and staff in Liverpool.  In all of these posts, the focus has been on traditional forms of learning environments; however, almost everything that I have described can be transferred to a virtual learning environment, which is what I have done in the two MOOCs [see ‘Engaging learners on-line’ on May 25th, 2016 and ‘Slowing down time to think (about strain energy)’ on March 8th, 2017].

You can illustrate a much wider range of Everyday Engineering Examples on video than is viable in a lecture theatre.  So, for instance, I used my shower to engage the learners and to introduce a little statistical thermodynamics and explain how we can consider the average behaviour of a myriad of atoms.  However, it is not possible to progress through 5Es [see ‘Engage, Explore, Explain, Elaborate and Evaluate’ on August 1st, 2018] in a single step of a MOOC; so, instead I used a step (or sometimes two steps) of the MOOC to address each ‘E’ and cycled around the 5Es about twice per week.  This approach provides an effective structure for the MOOC which appears to have been a significant factor in achieving higher completion rates than in most MOOCs.

In the MOOC, I extended the Everyday Engineering Example concept into experiments set as homework assignments using kitchen equipment.  For instance, in one lab students were asked to measure the efficiency of their kettle.  In another innovation, we developed Clear Screen Technology to allow me to talk to the audience while solving a worked example.  In the photo below, I am calculating the Gibbs energy in the tank of a compressed air powered car in the final week of the MOOC [where we began to transition to more sophisticated examples].

Last academic year, I blended the MOOC on thermodynamics with my traditional first year module by removing half the lectures, the laboratory classes and worked example classes from the module.  They were replaced by the video shorts, homework labs and Clear Screen Technology worked examples respectively from the MOOC.  The results were positive with an increased attendence at lectures and an improved performance in the examination; although some students did not like and did not engage with the on-line material.

Photographs are stills from the MOOC ‘Energy: Thermodynamics in Everyday Life’.

CALE #10 [Creating A Learning Environment: a series of posts based on a workshop given periodically by Pat Campbell and Eann Patterson in the USA supported by NSF and the UK supported by HEA] – although this post is based on recent experience in developing and delivering a MOOC integrated with traditional learning environments.

Learning problem-solving skills

Inukshuk: meaning ‘in the likeness of a human’ in the Inuit language. A traditional symbol meaning ‘someone was here’ or ‘you are on the right path’.

One definition of engineering given in the Oxford English Dictionary is ‘the action of working artfully to bring something about’.  This action usually requires creative problem-solving which is a common skill possessed by all engineers regardless of their field of specialisation.  In many universities, students acquire this skill though solving example problems set by their instructors and supported by example classes and, or tutorials.

In my lectures, I solve example problems in class using a pen and paper combined with a visualiser and then give the students a set of problems to solve themselves.  The answers but not the solutions are provided; so that students know when they have arrived at the correct answer but not how to get there.  Students find this difficult and complain because I am putting the emphasis on their learning of problem-solving skills which requires considerable effort by them.  There are no short-cuts – it’s a process of deep-learning [see ‘Deep long-term learning’ on April 18th, 2018].

Research shows that students tend to jump into algebraic manipulation of equations whereas experts experiment to find the best approach to solving a problem.  The transition from student to skilled problem-solver requires students to become comfortable with the slow and uncertain process of creating representations of the problem and exploring the possible approaches to the solution [Martin & Schwartz, 2014].  And, it takes extensive practice to develop these problem-solving skills [Martin & Schwartz, 2009].  For instance, it is challenging to persuade students to sketch a representation of the problem that they are trying to solve [see ‘Meta-representational competence’ on May 13th, 2015].  Working in small groups with a tutor or a peer-mentor is an effective way of supporting students in acquiring these skills.  However, it is important to ensure that the students are engaged in the problem-solving so that the tutor acts as consultant or a guide who is not directly involved in solving the problem but can give students confidence that they are on the right path.

[Footnote: a visualiser is the modern equivalent of an OverHead Projector (OHP) which instead of projecting optically uses a digital camera and projector.  It’s probably deserves to be on the Mindset List since it is one of those differences between a professor’s experience as a student and our students’ experience [see ‘Engineering idiom’ on September 12th, 2018]].

References:

Martin L & Schwartz DL, A pragmatic perspective on visual representation and creative thinking, Visual Studies, 29(1):80-93, 2014.

Martin L & Schwartz DL, Prospective adaptation in the use of external representations, Cognition and Instruction, 27(4):370-400, 2009.

 

CALE #9 [Creating A Learning Environment: a series of posts based on a workshop given periodically by Pat Campbell and Eann Patterson in the USA supported by NSF and the UK supported by HEA] – although this post is based on an introduction to tutorials given to new students and staff at the University of Liverpool in 2015 & 2016.

Photo: ILANAAQ_Whistler by NordicLondon (CC BY-NC 2.0) https://www.flickr.com/photos/25408600@N00/189300958/