Category Archives: Engineering

When seeing nothing is a success

In November I went to Zurich twice: once for the workshop that I wrote about last week [see ‘Fake facts and untrustworthy predictions’ on December 4th, 2019]; and, a second time for a progress meeting of the DIMES project [see ‘Finding DIMES’ on February 6th, 2019].  The progress meeting went well.  The project is on schedule and within budget. So, everyone is happy and you are wondering why I am writing about it.  It was what our team was doing around the progress meeting that was exciting.  A few months ago, Airbus delivered a section of an A320 wing to the labs of EMPA who are our project partner in Switzerland, and the team at EMPA has been rigging the wing section for a simple bending test so that we can use it to test the integrated measurement system which we are developing in the DIMES project [see ‘Joining the dots’ on July 10th, 2019].  Before and after the meeting, partners from EMPA, Dantec Dynamics GmbH, Strain Solutions Ltd and my group at the University of Liverpool were installing our prototype systems to monitor the condition of the wing when we apply bending loads to it.  There is some pre-existing damage in the wing that we hope will propagate during the test allowing us to track it with our prototype systems using visible and infra-red spectrum cameras as well as electrical and optical sensors.  The data that we collect during the test will allow us to develop our data processing algorithms and, if necessary, refine the system design.  The final stage of the DIMES project will involve installing a series of our systems in a complete wing undergoing a structural test in the new Airbus Wing Integration Centre (AWIC) in Filton, near Bristol in the UK.  The schedule is ambitious because we will need to install the sensors for our systems in the wing in the first quarter of next year, probably before we have finished all of the tests in EMPA.  However, the test in Bristol probably will not start until the middle of 2020, by which time we will have refined our algorithm for data processing and be ready for the deluge of data that we are likely to receive from the test at Airbus.  The difference between the two wing tests besides the level of maturity of our measurement system, is that no damage should be detected in the wing at Airbus whereas there will be detectable damage in the wing section in EMPA.  So, a positive result will be a success at EMPA but a negative result, i.e. no damage detected, will be a success at Airbus.

The DIMES project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 820951.


The opinions expressed in this blog post reflect only the author’s view and the Clean Sky 2 Joint Undertaking is not responsible for any use that may be made of the information it contains.

Fake facts & untrustworthy predictions

I need to confess to writing a misleading post some months ago entitled ‘In Einstein’s footprints?‘ on February 27th 2019, in which I promoted our 4th workshop on the ‘Validation of Computational Mechanics Models‘ that we held last month at Guild Hall of Carpenters [Zunfthaus zur Zimmerleuten] in Zurich.  I implied that speakers at the workshop would be stepping in Einstein’s footprints when they presented their research at the workshop, because Einstein presented a paper at the same venue in 1910.  However, as our host in Zurich revealed in his introductory remarks , the Guild Hall was gutted by fire in 2007 and so we were meeting in a fake, or replica, which was so good that most of us had not realised.  This was quite appropriate because a theme of the workshop was enhancing the credibility of computer models that are used to replicate the real-world.  We discussed the issues surrounding the trustworthiness of models in a wide range of fields including aerospace engineering, biomechanics, nuclear power and toxicology.  Many of the presentations are available on the website of the EU project MOTIVATE which organised and sponsored the workshop as part of its dissemination programme.  While we did not solve any problems, we did broaden people’s understanding of the issues associated with trustworthiness of predictions and identified the need to develop common approaches to support regulatory decisions across a range of industrial sectors – that’s probably the theme for our 5th workshop!

The MOTIVATE project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 754660 and the Swiss State Secretariat for Education, Research and Innovation under contract number 17.00064.

The opinions expressed in this blog post reflect only the author’s view and the Clean Sky 2 Joint Undertaking is not responsible for any use that may be made of the information it contains.



Citizens of the world

Last week in Liverpool, we hosted a series of symposia for participants in a dual PhD programme involving the University of Liverpool and National Tsing Hua University, in Taiwan, that has been operating for nearly a decade.  On the first day, we brought together about dozen staff from each university, who had not met before, and asked them to present overviews of their research and explore possible collaborations using as a theme: UN Sustainable Development Goal No.11: Sustainable Cities and Communities.  The expertise of the group included biology, computer science, chemistry, economics, engineering, materials science and physics; so, we had wide-ranging discussions.  On the second and third day, we connected a classroom on each campus using a video conferencing system and the two dozen PhD students in the dual programme presented updates on their research from whichever campus they are currently resident.  Each student has a supervisor in each university and divides their time between the two universities exploiting the expertise and facilities in the two institutions.

The range of topics covered in the student presentations was probably even wider than on the first day; extending from deep neural networks, through nuclear reactor technology, battery design and three-dimensional cell culturing to policy impacts on households.  One student spoke about the beauty of mathematical equations she is working on that describe the propagation of waves in lattice structures; while, another told us about his investigation of the causes of declining fertility rates across the world.  Data from the UN DESA Population Division show that live births per woman in the Americas & Europe have already fallen below the 2.1 required to sustain the population, while it is projected to fall below this level in south-east Asia within the next five years and in the world by 2060.  This made me think that perhaps the Gaia principle, proposed by James Lovelock, is operating and that human population is self-regulating as it interacts with constraints imposed by the Earth though perhaps not in a fashion originally envisaged.


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: or

See also NDA Lynn at