Tag Archives: thinking-out-of-box

Thinking out of the box leads to digital image correlation through space

This is the third in a short series of posts on recent engineering research published by my research group.  Actually, two have already been published: ‘Salt increases nanoparticle diffusion‘ on April 22nd, 2020; and ‘Spatio-temporal damage maps for composite materials‘ on May 6th, 2020 and then I got distracted.  This third one arose from the same project as the time-damage maps which was sponsored by the United States Air Force.  The time-damage maps allow us to explore the evolution of failure in complex materials; however, we already know that damage tends to initiate from imperfections or flaws in the microstructure in the material.  New continuous fibre reinforced composite (CFRC) materials based on ceramics are very sensitive to defects or anomalies in their microstructure, such as misalignment of fibres.  However, they are capable of withstanding temperatures in excess of 1500 degrees Centigrade, which offers the opportunity to use them in jet engines or nuclear power plants to help generate energy more efficiently.  Therefore, it is worthwhile investigating effective methods of inspecting their microstructure which we can do either destructively by repetitively polishing away the surface of a sample and viewing it in a microscope, or non-destructively using x-ray tomography.  In both cases, the result is hundreds of ‘images’ containing millions of data values from which it is challenging to extract useful information.  In our work, we have used a little lateral thinking, to show how digital image correlation, usually used to track deformation of structures using multiple images collected over time [see ‘256 shades of grey‘ on January 22nd, 2014] , can be used to track fibres through the multiple images of the layers of the microstructure.  The result is the sort of ‘stick’ diagram in the image showing the orientation of fibres through the sample.  We have demonstrated that our new algorithm was more reliable and 30 times faster than its nearest rival.

The image shows, at the top, a typical stack of images from the microscope of a ceramic matrix composite; and, at the bottom, a plot of 3d profiles of the fibres tracked using the DIC-based method with the fibres orientated nominally at ±45° from the sectioning (x-y) plane shown in red and green colours.


Amjad K, Christian WJR, Dvurecenska K, Chapman MG, Uchic MD, Przybyla CP & Patterson EA, Computationally efficient method of tracking fibres in composite materials using digital image correlation, Composites Part A, 129:105683, 2020.


When will you be replaced by a computer?

I have written before about extending our minds by using external computing power in our mobile phones [see ‘Science fiction becomes virtual reality‘ on October 12th, 2016; and ‘Thinking out of the skull‘ on March 18th, 2015]; but, how about replacing our brain with a computer?  That’s the potential of artificial intelligence (AI); not literally replacing our brain, but at least taking over jobs that are traditionally believed to require our brain-power.  For instance, in a recent test, an AI lawyer found 95% of the loopholes in a non-disclosure agreement in 22 seconds while a group of human lawyers found only 88% in 90 minutes, according to Philip Delves Broughton in the FT last weekend.

If this sounds scary, then consider for a moment the computing power involved.  Lots of researchers are interested in simulating the brain and it has been estimated that the computing power required is around hundred peta FLOPS (FLoating point Operations Per Second), which conveniently, is equivalent to the world’s most powerful computers.  At the time of writing the world’s most powerful computer was ‘Summit‘ at the US Oak Ridge National Laboratory, which is capable of 200 petaFLOPS.  However, simulating the brain is not the same as reproducing its intelligence; and petaFLOPS are not a good measure of intelligence because while ‘Summit’ can multiply many strings of numbers together per second, it would take you and me many minutes to multiply two strings of numbers together giving us a rating of one hundredth of a FLOP or less.

So, raw computing power does not appear to equate to intelligence, instead intelligence seems to be related to our ability to network our neurons together in massive assemblies that flicker across our brain interacting with other assemblies [see ‘Digital hive mind‘ on November 30th, 2016]. We have about 100 billion neurons compared with the ‘Summit’ computer’s 9,216 CPUs (Central Processing Unit) and 27,648 GPUs (Graphic Processing Units); so, it seems unlikely that it will be able to come close to our ability to be creative or to handle unpredictable situations even accounting for the multiple cores in the CPUs.  In addition, it requires a power input of 13MW or a couple of very large wind turbines, compared to 80W for the base metabolic rate of a human of which the brain accounts for about 20%; so, its operating costs render it an uneconomic substitute for the human brain in activities that require intelligence.  Hence, while computers and robots are taking over many types of jobs, it seems likely that a core group of jobs involving creativity, unpredictability and emotional intelligence will remain for humans for the foreseeable future.


Max Tegmark, Life 3.0 – being human in the age of artificial intelligence, Penguin Books, 2018.

Philip Delves Broughton, Doom looms over the valley, FT Weekend, 16 November/17 November 2019.

Engelfriet, Arnoud, Creating an Artificial Intelligence for NDA Evaluation (September 22, 2017). Available at SSRN: https://ssrn.com/abstract=3039353 or http://dx.doi.org/10.2139/ssrn.3039353

See also NDA Lynn at https://www.ndalynn.com/

Thinking out-of-the-skull

bustLast year after the relaxation of our annual vacation, I wrote about the benefits of ‘Mind wandering‘ [see my post on September 3rd, 2014].  Our brains work in two modes known as central executive mode, for those tasks requiring focussed attention, and mind-wandering mode that involves day-dreaming and surfing from one idea to another leading to the emergence of new ideas.  We tend to feel tired and stressed when we try to switch between the two modes repeatedly.  At the moment, I struggle to set aside time for mind-wandering and indeed writing a weekly blog can induce a headache!

Perhaps this is because our brains are of finite size; and sometimes it feels as if we have reached their limitations.  I wrote about our attention capacity in my post entitled ‘Silence is golden‘ on January 14th, 2014.  More recently, Antonio Macaro and Julian Baggini have written that ‘savants who remember everything often understand very little’.  Probably this is because if you fill your brain with information there is less capacity for processing ideas to create understanding.  I would like to think that maintaining space for understanding is why I can’t remember anything whereas in fact it is probably just the impact of growing old!  However, Macaro and Baggini also suggest that we should use our smart phones and tablet computers as mental prosthetics to extend the capacity of our brains.  In other words, we should let these mental prostheses handle all of the routine processing of information associated with central executive mode tasks and keep the mental processes in our skulls for the creative thinking associated with mind-wandering.

Traditionally, engineers have followed Leonardo di Vinci‘s example by writing and drawing in a series of notebooks;  perhaps in the hope of emulating his creativity but also to extend the capacity of our minds by recording and ordering thoughts.  However, the processing capacity of modern devices creates the opportunity to go even further.  So that thinking out-of-the-skull could lead to more thinking out-of-the-box!

Source: Macaro, A. & Baggini, J., ‘Do we need props?’ in Financial Times magazine, January 10/11, 2015.

Photo credit: Tom