Category Archives: structures

On flatness and roughness

Photograph of aircraft carrier in heavy seas for decorative purposes onlyFlatness is a tricky term to define.  Technically, it is the deviation, or lack of deviation, from a plane. However, something that appears flat to human eye often turns out not to be at all flat when looked at closely and measured with a high resolution instrument.  It’s a bit like how the ocean might appear flat and smooth to a passenger sitting comfortably in a window seat of an aeroplane and looking down at the surface of the water below but feels like a roller-coaster to a sailor in a small yacht.  Of course, if the passenger looks at the horizon instead of down at the yacht below then they will realise the surface of the ocean is curved but this is unlikely to be apparent to the sailor who can only see the next line of waves advancing towards them.  Of course, the Earth is not flat and the waves are better described as surface roughness.  Some months ago I wrote about our struggles to build a thin flat metallic plate using additive manufacturing [see ‘If you don’t succeed, try and try again…’ on September 29th, 2021].  At the time, we were building our rectangular plates in landscape orientation and using buttresses to support them during the manufacturing process; however, when we removed the plates from the machine and detached the buttresses they deformed into a dome-shape.  I am pleased to say that our perseverance has paid off and recently we have been much more successful by building our plates orientated in portrait mode, i.e., with the short side of the rectangle horizontal, and using a more sophisticated design of buttresses.  Viewed from the right perspective our recent plates could be considered flat though in reality they deviate from a plane by less than 3% of their in-plane dimensions and also have a surface roughness of several tens of micrometres (that’s the average deviation from the surface).  The funding organisations for our research expect us to publish our results in a peer-reviewed journal that will only accept novel unpublished results so I am not going to say anything more about our flat plates.  Instead let me return to the ocean analogy and try to make you seasick by recalling an earlier career in which I was on duty on the bridge of an aircraft carrier ploughing through seas so rough, or not flat, that waves were breaking over the flight deck and the ship felt like it was still rolling and pitching when we sailed serenely into port some days later.

The current research is funded jointly by the National Science Foundation (NSF) in the USA and the Engineering and Physical Sciences Research Council (EPSRC) in the UK (see Grants on the Web).

Image from

Jigsaw puzzling without a picture

A350 XWB passes Maximum Wing Bending test

A350 XWB passes Maximum Wing Bending test

Research sometimes feels like putting together a jigsaw puzzle without the picture or being sure you have all of the pieces.  The pieces we are trying to fit together at the moment are (i) image decomposition of strain fields [see ‘Recognising strain’ on October 28th 2015] that allows fields containing millions of data values to be represented by a feature vector with only tens of elements which is useful for comparing maps or fields of predictions from a computational model with measurements made in the real-world; (ii) evaluation of the variation in measurement uncertainty over a field of view of measured displacements or strains in a large structure [see ‘Industrial uncertainty’ on December 12th 2018] which provides information about the quality of the measurements; and (iii) a probabilistic validation metric that provides a measure of how well predictions from a computational model represent measurements made in the real world [see ‘Million to one’ on November 21st 2018].  We have found some of the missing pieces of the jigsaw, for example we have established how to represent the distribution of measurement uncertainty in the feature vector domain [see ‘From strain measurements to assessing El Niño events’ on March 17th 2021] so that it can be used to assess the significance of differences between measurements and predictions represented by their feature vectors – this connects (i) and (ii) together.  Very recently we have demonstrated a generic technique for performing image decomposition of irregularly shaped fields of data or data fields with holes [see Christian et al, 2021] which extends the applicability of our method for comparing measurements and predictions to real-world objects rather than idealised shapes.  This allows (i) to be used in industrial applications but we still have to work out how to connect this to the probabilistic metric in (iii) while also incorporating spatially-varying uncertainty.  These techniques can be used in a wide range of applications, as demonstrated in our recent work on El Niño events [see Alexiadis et al, 2021], because, by treating all fields of data as images, the techniques are agnostic about the source and format of the data.  However, at the moment, our main focus is on their application to ground tests on aircraft structures as part of the Smarter Testing project in collaboration with Airbus, Centre for Modelling & Simulation, Dassault Systèmes, GOM UK Ltd, and the National Physical Laboratory with funding from the Aerospace Technology Institute.  Together we are working towards digital continuity across virtual and physical testing of aircraft structures to provide live data fusion and enable condition-led inspections, test control and validation of computational models.  We anticipate these advances will reduce time and costs for physical tests and accelerate the development of new designs of aircraft that will contribute to global sustainability targets (the aerospace industry has committed to reduce CO2 emissions to 50% of 2005 levels by 2050).  The Smarter Testing project has an ambitious goal which reveals that our pieces of the jigsaw puzzle belong to a small section of a much larger one.

For more on the Smarter Testing project see:


Alexiadis A, Ferson S, Patterson EA. Transformation of measurement uncertainties into low-dimensional feature vector space. Royal Society open science. 8(3):201086, 2021.

Christian WJ, Dean AD, Dvurecenska K, Middleton CA, Patterson EA. Comparing full-field data from structural components with complicated geometries. Royal Society open science. 8(9):210916, 2021.


Too much of a good thing?

I wrote a couple of weeks ago about ‘Our last DIMES’ meetings (on September 22nd, 2021).  They were hybrid meetings with about half the participants attending in person and the remainder on-line.  When the pandemic started we had to master the skill of conducting discussions via our laptops while sitting on our own.  Now, we are learning how to include everyone in a discussion when only half of the participants are in the physical room.  One of our first steps was to re-equip our meeting rooms with higher quality video conferencing facilities so that we can see and hear one another more clearly.  Unfortunately, our new equipment revealed the poor quality of the video clips we have produced during the DIMES project.  Nevertheless, if you have never been present during a wing-bend test or a fatigue test on a large composite panel then you might find these clips interesting (see also the video of ‘Noisy progressive failure of a composite panel’ on June 30th 2021).  We also produced an introductory video for the DIMES project which was to be first in a series of video shorts but the pandemic intervened and we have never been in the same place as our camera crew so we have not made anymore.  Maybe that’s a good thing because 500 hours of video are uploaded every minute to YouTube so you will not have time to watch our DIMES videos 😉.

For more short videos from our earlier projects see ‘Archive video footage from EU projects’ on June 5th, 2019.

The University of Liverpool is the coordinator of the DIMES project and the other partners are Empa, Dantec Dynamics GmbH and Strain Solutions LtdAirbus is the topic manager on behalf of the Clean Sky 2 Joint Undertaking.

Logos of Clean Sky 2 and EUThe 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.

Our last DIMES

Photograph of wing test in AWICThirty-three months ago (see ‘Finding DIMES‘ on February 6th, 2019) we set off at a gallop ‘to develop and demonstrate an automated measurement system that integrates a range of measurement approaches to enable damage and cracks to be detected and monitored as they originate at multi-material interfaces in an aircraft assembly’. The quotation is taken directly from the aim of the DIMES project which was originally planned and funded as a two-year research programme. Our research, in particular the demonstration element, has been slowed down by the pandemic and we resorted to two no-cost extensions, initially for three months and then for six months to achieve the project aim.   Two weeks ago, we held our final review meeting, and this week we will present our latest results in the third of a series of annual workshops hosted by Airbus, the project’s topic manager.   The DIMES system combines visual and infrared cameras with resistance strain gauges and fibre Bragg gratings to detect 1 mm cracks in metals and damage indications in composites that are only 6 mm in diameter.  We had a concept design by April 2019 (see ‘Joining the dots‘ on July 10th, 2019) and a detailed design by August 2019.  Airbus supplied us with a section of A320 wing, and we built a test-bench at Empa in Zurich in which we installed our prototype measurement system in the last quarter of 2019 (see ‘When seeing nothing is a success‘ on December 11th, 2019).  Then, the pandemic intervened and we did not finish testing until May 2021 by which time, we had also evaluated it for monitoring damage in composite A350 fuselage panels (see ‘Noisy progressive failure of a composite panel‘ on June 30th, 2021).  In parallel, we have installed our ‘DIMES system’ in ground tests on an aircraft wing at Airbus in Filton (see image) and, using a remote installation, in a cockpit at Airbus in Toulouse (see ‘Most valued player performs remote installation‘ on December 2nd, 2020), as well as an aircraft at NRC Aerospace in Ottawa (see ‘An upside to lockdown‘ on April 14th 2021).   Our innovative technology allows condition-led monitoring based on automated damage detection and enables ground tests on aircraft structures to be run 24/7 saving about 3 months on each year-long test.

The University of Liverpool is the coordinator of the DIMES project and the other partners are Empa, Dantec Dynamics GmbH and Strain Solutions Ltd.

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.