Monthly Archives: January 2014

Setting standards

cenLast week I wrote about digital image correlation as a method for measuring surface strain and displacement fields.  The simplicity and modest cost of the equipment required combined with the quality and quantity of the results is revolutionizing the field of experimental mechanics.  It also has the potential to do the same in computational mechanics by enabling more comprehensive validation of models and thus enhancing the credibility and confidence in engineering simulations.  I have written and lectured on this topic many times, see for instance my post of September 17th, 2012 entitled ‘Model credibility’ or

At the moment, I am chair of a CEN workshop WS71 that is developing a precursor to a standard on validation of computational solid mechanics models.  To inform our deliberations, we have organised an Inter-Laboratory Study (ILS) to allow people to try out the proposed validation protocol and give us feedback.   If you would like to have a go then download the information pack.  You don’t need to do any experiments or modelling, just try the validation procedure with some of the data sets provided.  The more engineers that participate in the ILS then the better that the final CEN document is likely to be; so if you know someone who might be interested then forward this blog to them or just send them the link.

Displacement field measured using image correlation for metal wedge indenting a rubber block

Displacement field measured using digital image correlation for a metal wedge indenting a rubber block


EU FP7 project VANESSA:

For information on the data field shown to the right see:

256 shades of grey

bonnet panelEngineers are increasingly using digital photographs with 256 shades of grey to measure displacement of structural components.  The technique is known as Digital Image Correlation and is the most common way to measure the deformation of engineering structures and components in a laboratory, and increasingly in the field.  DIC provides maps of the displacement of the component surface from which the strain field can be calculated and which in turn allows engineers to assess the behaviour and likely failure modes of the component.  DIC is beginning to revolutionise the way in which we validate computational mechanics models.

DIC involves capturing ‘before’ and ‘after’ images of the component surface while load is applied.  If the surface has a random pattern, which is often created by spray-painting black speckles onto a white background, then it is possible to track the movement of the pattern as the surface moves and deforms.  The images are usually recorded as intensity maps defined by 256 shades of grey or grey levels from white through to black.  A mathematical signature is assigned to facets or sub-images of the intensity map in the ‘before’ image and a correlation algorithm uses the signature to recognise the facet in the ‘after’ image.  The positions of the centre of the facet in the ‘before’ and ‘after’ images indicates the displacement of the corresponding area of the component surface.  Two cameras can be used to provide stereoscopic vision and information on displacements in all directions.

The picture shows a car bonnet or hood panel in a test frame in a laboratory prior to an impact test with a random speckle pattern on the surface to allow DIC to be performed using high-speed cameras. For more details see: Burguete et al , 2013, J. Strain Analysis, doi:10.1177/0309324713498074 at

For detailed explanations of DIC try the monograph by Professor Mike Sutton and his colleagues [] or the chapter on DIC in Optical Methods for Solid Mechanics by Pramod Rastogi and Erwin Hack [].

For some applications see the special issue on DIC of the Journal of Strain Analysis for Engineering Design [].

Silence is golden

118-1804_IMGThe digital age has led to us being overwhelmed with sources of information and entertainment.  It is unfashionable to suggest that it might be unproductive to take advantage of multiple data streams to interact with the virtual world, listen to your favourite music and study simultaneously.

However in 1973, Kahneman proposed that the amount of attention that an individual can deploy at any time is limited.  It is known as the ‘capacity model of attention’ and is based on the assumptions that attention can be freely allocated to activities based on their arousal level and that your total attention is finite.  The model has been used to explain research findings on the effect of background television on cognitive performance.  While recent research has demonstrated that students read and study better in silence; though if they must listen to music then certain types are better than others, for instance light classical music has a less deleterious effect than hip hop music – maybe because it has a lower arousal level.

So multi-tasking is not conducive to high quality output or efficient working.  Many people have arrived at this conclusion by the time they graduate from University or have spent a few years in a mentally demanding job.  However, it is an uphill task to convince young people that they would perform better and finish tasks faster without the distractions made readily available by the digital age.

Or that is safer not to cross the road while listening to music and texting your friends!


For many references to the research literature see Chou, P. M-T., Attention drainage effect: how background music effects concentration in Taiwanese college students, Journal of Scholarship of Teaching & Learning, 10(1):36-46, 2010.

Kahneman, D., Attention and effect, Englewood Cliffs, NJ: Prentice Hall, 1973.

Hot particles

diffraction pattern from nanoparticlesHave you ever wondered why people visiting the site of the Fukushima nuclear accident are only dressed up in coveralls and masks?  In my post on December 18th entitled ‘Hiding in the Basement’, I explained that gamma radiation requires a sheet of lead to stop it so the coveralls are clearly not protecting Fukushima visitors against radiation.

Our bodies cope with low levels of radiation everyday because we absorb about 0.024 Sieverts per year from the natural environment and the same amount is absorbed during a full-body scan in hospital.  One Sievert is equivalent to 1 Joule absorbed per kilogram of body mass. If you hold a tennis ball as high above your head as you can reach and let it fall to the ground, then the ball hits the ground with about 1 Joule of kinetic energy.  Your heart uses about 1 Joule of energy per beat.

The estimated maximum dose received by residents living close to Fukushima was 0.068 Sieverts or about three annual doses.  The visitors’ coveralls and mask are protecting them from ‘hot’ particles that are often produced during a nuclear accident. ‘Hot’ particles can be inhaled or ingested and continue to emit radiation when inside the body thus delivering a large concentrated dose to a relatively small number of surrounding cells, which are disrupted and destroyed by the high-levels of energy.  ‘Hot’ particles are small pieces of radioactive material and vary in size from tens of nanometres to a few millimetres, so that they don’t have high penetrating power and can be detected using a Geiger counter.