Two for one

2 Replies

I wrote this short annual report in anticipation of being on vacation this week. However, as my editor commented, it is ‘a bit of a non-blog’ and so I have written a second post for today that will be published a few minutes later.

The painting in the thumbnail is by Peter Curran and shows a view of Liverpool’s Anglican Cathedral that is almost the same as the view from the seat at which I usually sit to write this blog. The blog is read world-wide as shown by the distribution of visitors to the blog during 2018 in the temperature map in the graphic below. The weekly readership dropped by 60% at the beginning of April 2018 after I deleted my Facebook page and cut the link between Facebook and this blog (see ‘Some changes to Realize Engineering‘ on March 28th, 2018). However, I am pleased say that the visitor numbers have recovered; and last month’s visitor numbers were only 4% lower than the corresponding month in 2017. So many thanks to those readers that stayed with me, or found the blog again without using Facebook. While, I enjoy writing ‘to make life more fruitful’ to quote Sylvain Tesson (see ‘Thinking more clearly by writing weekly‘), it is also encouraging to know that people are reading the blog.

For those of you that enjoy reading it as much as I enjoy writing, there have been more than 330 posts since the first one in July 2012 – that’s a huge archive for you to browse, if you have nothing else to do. Happy New Year!

Sylvain Tesson, Consolations of the forest: alone in a cabin in the middle Taiga, London: Penguin Books, 2014.

Christmas diamonds

Blind to complexity

1 Reply

When faced with complexity, we tend to seek order and simplicity. Most of us respond negatively to the uncertainty associated with complex systems and their apparent unpredictability. Complex systems can be characterised as large networks operating using simple rules but without central control which results in self-organising behaviour and non-trivial emergent behaviour. Emergent behaviour is the behaviour of the system that is not apparent or expected from the behaviour of its constituent parts [see ‘Emergent properties‘ on September 16th, 2015].

The philosopher, William Wimsatt observed that we tend to ignore phenomena whose complexity exceeds our predictive capability and our detection apparatus. This is problematic because we try to over-simplify our descriptions of complex systems. Occam’s razor is often mis-interpreted to mean that simple explanations are better ones, whereas in reality ‘everything should be made as simple as possible, but not simpler’, (which is often attributed to Einstein). This implies that our explanation and any mathematical model of a complex system, such as the nervous system in the image, will need to be complex. In mathematical terms, this will probably mean a non-linear dynamic model with a solution in the form of a phase portrait. ‘Non-linear’ because the response of the system not proportional to the stimulus inducing the response; ‘dynamic’ because the system changes with time; and a ‘phase portrait’ because the system can exist in many states, some stable and some unstable, dependent on its prior history; so, for instance for a pendulum, its phase portrait is a plot of all of its possible positions and velocities.

If all this sounds too hard, then you see why people shy away from using complex models to describe a complex system even when it is obvious that the system is complex and extremely unlikely to be adequately described by a linear model, such as for the nervous system in the image.

In other words, if we can’t see it and its too hard to think about it, then we pretend it’s not happening!

The thumbnail shows an image of a fruit-fly’s nervous system taken by Albert Cardona from HHMI Janelia Research Campus. The image won a Wellcome Image Award in 2015.

William C. Wimsatt, Randomness and perceived randomness in evolutionary biology, Synthese, 43(2):287-329, 1980.

For more on this topic see: ‘Is the world comprehensible?‘ on March 15th, 2017.

Industrial uncertainty

4 Replies

Last month I spent almost a week in Zurich. It is one of our favourite European cities [see ‘A reflection of existentialism‘ on December 20th, 2017]; however, on this occasion there was no time for sight-seeing because I was there for the mid-term meeting of the MOTIVATE project and to conduct some tests and demonstrations in the laboratories of our host, EMPA, the Swiss Federal Laboratories for Materials Science and Technology. Two of our project partners, Dantec Dynamics GmbH based in Ulm, Germany, and the Athena Research Centre in Patras, Greece, have developed methods for quantifying the uncertainty present in measurements of deformation made in an industrial environment using digital image correlation (DIC) [see ‘256 shades of grey‘ on January 22, 2014]. Digital image correlation is a technique in which we usually apply a random speckle pattern to the object which allows us to track the movement of the object surface over time by searching for the new position of the speckles in the photographs of the object. If we use a pair of cameras in a stereoscopic arrangement, then we can measure in-plane and out-of-plane displacements. Digital image correlation is a well-established measurement technique that has become ubiquitous in mechanics laboratories. In previous EU projects, we have developed technology for quantifying uncertainty in in-plane [SPOTS project] and out-of-plane [ADVISE project] measurements in a laboratory environment. However, when you take the digital image correlation equipment into an industrial environment, for instance an aircraft hangar to make measurements during a full-scale test, then additional sources of uncertainty and error appear. The new technology demonstrated last month allows these additional uncertainties to be quantified. As part of the MOTIVATE project, we will be involved in a full-scale test on a large section of an Airbus aircraft next year and so, we will be able to utilise the new technology for the first time.

The photograph shows preparations for the demonstrations in EMPA’s laboratories. In the foreground is a stereoscopic digital image correlation system with which we are about to make measurements of deformation of a section of aircraft skin, supplied by Airbus, which has a speckle pattern on its surface and is about to be loaded in compression by the large servo-hydraulic test machine.

References:

From SPOTS project:

Patterson EA, Hack E, Brailly P, Burguete RL, Saleem Q, Seibert T, Tomlinson RA & Whelan M, Calibration and evaluation of optical systems for full-field strain measurement, Optics and Lasers in Engineering, 45(5):550-564, 2007.

Whelan MP, Albrecht D, Hack E & Patterson EA, Calibration of a speckle interferometry full-field strain measurement system, Strain, 44(2):180-190, 2008.

From ADVISE project:

Hack E, Lin X, Patterson EA & Sebastian CM, A reference material for establishing uncertainties in full-field displacement measurements, Measurement Science and Technology, 26:075004, 2015.