Category Archives: Engineering

Creating an evolving learning environment

A couple of weeks ago, I wrote about marking examinations and my tendency to focus on the students that I had failed to teach rather than those who excelled in their knowledge of problem-solving with the laws of thermodynamics [see my post ‘Depressed by exams‘ on January 31st, 2018].  One correspondent suggested that I shouldn’t beat myself up because ‘to teach is to show, to learn is to acquire‘; and that I had not failed to show but that some of my students had failed to acquire.  However, Adams and Felder have stated that the ‘educational role of faculty is not to impart knowledge; but to design learning environments that support knowledge acquisition‘.  My despondency arises from my apparent inability to create a learning environment that supports and encourages knowledge acquisition for all of my students.  People arrive in my class with a variety of formative experiences and different ways of learning, which makes it challenging to generate a learning environment that is effective for everyone.   It’s an on-going challenge due to the ever-widening cultural gap between students and their professors, which is large enough to have warranted at least one anthropological study (see My Freshman Year by Rebekah Nathan). So, my focus on the weaker exam scripts has a positive outcome because it causes me to think about evolving the learning environment.

Sources:

Adams RS, Felder RM, Reframing professional development: A systems approach to preparing engineering educators to educate tomorrow’s engineers. J. Engineering Education, 97(3):230-240, 2008.

Nathan R, My freshman year: what a professor learned by becoming a student, Cornell University Press, Ithaca, New York, 2005

Depressed by exams

I am not feeling very creative this week, because I am in middle of marking examination scripts; so, this post is going to be short.  I have 20 days to grade at least 1100 questions and award a maximum of 28,400 marks – that’s a lot of decisions for my neurons to handle without being asked to find new ways to network and generate original thoughts for this blog [see my post on ‘Digital hive mind‘ on November 30th, 2016].

It is a depressing task discovering how little I have managed to teach students about thermodynamics, or maybe I should say, how little they have learned.  However, I suspect these feelings are a consequence of the asymmetry of my brain, which has many more sites capable of attributing blame and only one for assigning praise [see my post entitled ‘Happenstance, not engineering‘ on November 9th, 2016].  So, I tend to focus on the performance of the students at the lower end of the spectrum rather than the stars who spot the elegant solutions to the exam problems.

Sources:

Ngo L, Kelly M, Coutlee CG, Carter RM , Sinnott-Armstrong W & Huettel SA, Two distinct moral mechanisms for ascribing and denying intentionality, Scientific Reports, 5:17390, 2015.

Bruek H, Human brains are wired to blame rather than to praise, Fortune, December 4th 2015.

Formula Ocean

I have had intermittent interactions with motorsport during my engineering career, principally with Formula 1, Formula SAE and Formula Student teams.  The design, construction and competition involved in Formula Student generates tremendous enthusiasm amongst a section of the student community and enormously increases their employability.  As a Department Chair at Michigan State University, I was a proud and enthusiastic sponsor of the MSU Formula SAE team.  However, I find it increasingly difficult to support an activity that is associated with profligate expenditure of energy and resources – this is not the impression of engineering that should be portrayed to our current and future students.  Engineering is about so much more than making a vehicle go around a track as fast as possible.  See my posts on ‘Re-engineering Engineering‘ on August 30th, 2017, ‘Engineering is all about ingenuity‘ on September 14th, 2016 or ‘Life takes engineering‘ on April 22nd, 2015.

There are many other challenges that could taken up by student teams, in competition if that encourages participation, which would benefit human-kind and the planet.  A current hot topic in the UK media is the pollution of oceans by waste plastic [see for example BBC report]; so, engineering undergraduates could be challenged to design, construct and operate an autonomous marine vehicle that collects and processes plastic waste.  It could be powered from the embedded energy in the waste plastic collected in the ocean.  It would need to navigate to avoid collisions with other vessels, coastal features and wildlife, and to locate and identify the waste.  These represent technological changes in chemical, control, electronic, materials and mechanical engineering – and probably some other fields as well.  I have shared this concept with colleagues in Liverpool and there is some enthusiasm for it; maybe some competition from other universities is all that’s needed to get Formula Ocean started.  The machine with the largest positive net impact on the environment wins!

 

Slow moving nanoparticles

Random track of a nanoparticle superimposed on its image generated in the microscope using a pin-hole and narrowband filter.

A couple of weeks ago I bragged about research from my group being included in a press release from the Royal Society [see post entitled ‘Press Release!‘ on November 15th, 2017].  I hate to be boring but it’s happened again.  Some research that we have been performing with the European Union’s Joint Research Centre in Ispra [see my post entitled ‘Toxic nanoparticles‘ on November 13th, 2013] has been published this morning by the Royal Society Open Science.

Our experimental measurements of the free motion of small nanoparticles in a fluid have shown that they move slower than expected.  At low concentrations, unexpectedly large groups of molecules in the form of nanoparticles up to 150-300nm in diameter behave more like an individual molecule than a particle.  Our experiments support predictions from computer simulations by other researchers, which suggest that at low concentrations the motion of small nanoparticles in a fluid might be dominated by van der Waals forces rather the thermal motion of the surrounding molecules.  At the nanoscale there is still much that we do not understand and so these findings will have potential implications for predicting nanoparticle transport, for instance in drug delivery [e.g., via the nasal passage to the central nervous system], and for understanding enhanced heat transfer in nanofluids, which is important in designing systems such as cooling for electronics, solar collectors and nuclear reactors.

Our article’s title is ‘Transition from fractional to classical Stokes-Einstein behaviour in simple fluids‘ which does not reveal much unless you are familiar with the behaviour of particles and molecules.  So, here’s a quick explanation: Robert Brown gave his name to the motion of particles suspended in a fluid after reporting the random motion or diffusion of pollen particles in water in 1828.  In 1906, Einstein postulated that the motion of a suspended particle is generated by the thermal motion of the surrounding fluid molecules.  While Stokes law relates the drag force on the particle to its size and fluid viscosity.  Hence, the Brownian motion of a particle can be described by the combined Stokes-Einstein relationship.  However, at the molecular scale, the motion of individual molecules in a fluid is dominated by van der Waals forces, which results in the size of the molecule being unimportant and the diffusion of the molecule being inversely proportional to a fractional power of the fluid viscosity; hence the term fractional Stokes-Einstein behaviour.  Nanoparticles that approach the size of large molecules are not visible in an optical microscope and so we have tracked them using a special technique based on imaging their shadow [see my post ‘Seeing the invisible‘ on October 29th, 2014].

Source:

Coglitore D, Edwardson SP, Macko P, Patterson EA, Whelan MP, Transition from fractional to classical Stokes-Einstein behaviour in simple fluids, Royal Society Open Science, 4:170507, 2017. doi: