Tag Archives: strain

Credibility is in the eye of the beholder

Picture1Last month I described how computational models were used as more than fables in many areas of applied science, including engineering and precision medicine [‘Models as fables’ on March 16th, 2016].  When people need to make decisions with socioeconomic and, or personal costs, based on the predictions from these models, then the models need to be credible.  Credibility is like beauty, it is in the eye of the beholder.   It is a challenging problem to convince decision-makers, who are often not expert in the technology or modelling techniques, that the predictions are reliable and accurate.  After all, a model that is reliable and accurate but in which decision-makers have no confidence is almost useless.  In my research we are interested in the credibility of computational mechanics models that are used to optimise the design of load-bearing structures, whether it is the frame of a building, the wing of an aircraft or a hip prosthesis.  We have techniques that allow us to characterise maps of strain using feature vectors [see my post entitled ‘Recognising strain‘ on October 28th, 2015] and then to compare the ‘distances’ between the vectors representing the predictions and measurements.  If the predicted map of strain  is an perfect representation of the map measured in a physical prototype, then this ‘distance’ will be zero.  Of course, this never happens because there is noise in the measured data and our models are never perfect because they contain simplifying assumptions that make the modelling viable.  The difficult question is how much difference is acceptable between the predictions and measurements .  The public expect certainty with respect to the performance of an engineering structure whereas engineers know that there is always some uncertainty – we can reduce it but that costs money.  Money for more sophisticated models, for more computational resources to execute the models, and for more and better quality measurements.

Insidious damage

bikeRecently, my son bought a carbon-fibre framed bike for his commute to work. He talked to me about it before he made the decision to go ahead because he was worried about the susceptibility of carbon-fibre to impact damage. The aircraft industry worries about barely visible impact damage (BVID) because while the damage might be barely visible on the accessible face that received the impact, within the carbon-fibre component there can be substantial life-shortening damage. I reassured my son that it is unlikely a road bike would receive impacts of sufficient energy to induce life-shortening damage, at least in ordinary use. However, such impacts are not unusual in aircraft structures which means that they have to be inspected for hidden, insidious damage. The most common method of inspection is based on ultrasound that is reflected preferentially by the damaged areas so that the shape and extent of damage can be mapped. It is difficult to predict the effect on the structural performance of the component from this morphology information so that, when damage is found, the component is usually repaired or replaced immediately. In my research group we have been exploring the use of strain measurements to locate and assess damage by comparing the strain distributions in as-manufactured and in-service components. We can measure the strain fields in components using a number of techniques including digital image correlation (see my post entitled ‘256 shades of grey’) and thermoelastic stress analysis (see my post entitled ‘Counting photons to measure stress‘). The comparison is performed using feature vectors that represent the strain fields, see my post of a few weeks ago entitled ‘Recognising strain’. The guiding principle is that if damage is present but does not change the strain field then the structural performance of the component is unchanged; however when the strain field is changed then it is easier to predict remanent life from strain data than from morphology data. We have demonstrated that these new concepts work in glass-fibre reinforced laminates and are in the process of reproducing the results in carbon-fibre composites.

Sources

Patterson, E.A., Feligiotti, M., Hack, E., 2013, On the integration of validation, quality assurance and non-destructive evaluation, J. Strain Analysis, 48(1):48-59.

Patki, A.S., Patterson, E.A., 2012, Damage assessment of fibre reinforced composites using shape descriptors, J. Strain Analysis, 47(4):244-253.

Recognizing strain

rlpoYou can step off an express train but you can’t speed up a donkey. This is paraphrased from ‘The Fly Trap’ by Fredrik Sjöberg in the context of our adoption of faster and faster technology and the associated life style. Last week we stepped briefly off the ‘express train’ and lowered our strain levels by going to a concert given by the Royal Liverpool Philharmonic Orchestra, including pieces by Dvorak, Chopin and Tchaikovsky. I am not musical at all and so I am unable to tell you much about the performances or compositions, except to say that I enjoyed the performances as did the rest of the audience to judge from the enthusiastic applause. A good deal of my enjoyment arose from the energy of the orchestra and my ability to recognise the musical themes or acoustic features in the pieces. The previous sentence was not intended as a critic’s perspective on the concert but a tenuous link…

Recognising features is one aspect of my recent research, though in strain data rather than music. Modern digital technology allows us to acquire information-rich data maps with tens of thousands of individual data values arranged in arrays or matrices, in which it can be difficult to spot patterns or features. We treat our strain data as images and use image decomposition to compress a data matrix into a feature vector. The diagram shows the process of image decomposition, in which a colour image is converted to a map of intensity in the image. The intensity values can be stored in a matrix and we can fit sets of polynomials to them by ‘tuning’ the coefficients in the polynomials. The coefficients are gathered together in a feature vector. The original data can be reconstructed from the feature vector if you know the set of polynomials used in the decomposition process, so decomposition is also a form of data compression. It is easier to recognise features in the small number of coefficients than in the original data map, which is why we use the process and why it was developed to allow computers to perform pattern recognition tasks such as facial recognition.

decompositionSources:

Wang W, Mottershead JE, Patki A, Patterson EA, Construction of shape features for the representation of full-field displacement/strain data, Applied Mechanics and Materials, 24-25:365-370, 2010.

Patki, A.S., Patterson, E.A, Decomposing strain maps using Fourier-Zernike shape descriptors, Exptl. Mech., 52(8):1137-1149, 2012.

Nabatchian A., Abdel-Raheem E., and Ahmadi M., 2008, Human face recognition using different moment invariants: a comparative review. Congress on Image and Signal Processing, 661-666.

 

Cow bladders led to modern strain measurement

 

softball figureSir David Brewster was a prolific experimentalist who published seven papers in the Philosophical Transactions of the Royal Society during 1815 and 1816. In his report dated October 22nd, 1814 that was published by the Royal Society one hundred years ago in January 1815, he described his observations on the depolarisation in more than fifty materials as diverse as sulphur and the bladder of a cow. He followed this with a series of experiments on glass sheets subject to various loads and reported his observations in the of photographic plates that show photoelastic fringe patterns which would become instantly recognisable to generations of engineers. Two hundred year later, digital technology has revolutionised photoelasticity so that it is no longer necessary to generate fringes that can be ‘seen’, as in Brewster’s experiments. Instead, digital sensors allow us to measure changes in light intensity that are undetectable to the naked eye and digital computers permit the processing of arrays of tens of thousands of measurements in less than the blink of an eye to yield maps of strain magnitude and direction in complex components. However, the principles employed in digital photoelasticity are the same as those first elucidated by Brewster and involve collecting images at multiple rotational steps of one or more of the polarising elements in a polariscope and then using Fourier analysis or matrix algebra to solve the equations describing the stress-optic law, i.e. the relationship between the applied stress and the observed change in transmitted light intensity. A polariscope is the term given to the series of polarisers and quarter-waveplates used by almost every photoelastician since Brewster to observe photoelastic fringes. One of Brewster’s other great inventions was the kaleidoscope of which there is an early example in the Science Museum in London. Recently, the concept of the kaleidoscope has been combined with a polariscope to create the poleidoscope that allows the multiple images required for digital photoelasticity to be acquired simultaneously, which is useful for dynamic applications such as in the impact example shown in the picture. These advances allow digital photoelasticity to be used not only by laboratory-based stress analysts but also in quality assurance procedures, for instance to monitor in real-time the stresses induced in float glass during production, or to investigate the residual stress in silicon wafers using infra-red light.

The picture shows a sequence of maps of photoelastic fringe order (right) showing the stress induced in an epoxy resin block when impacted by a soft ball falling under gravity (left). The maps were obtained using a precursor to the poleidoscope and a high-speed digital camera recording 4000 frames per second for the 10x10mm area shown by the white box in the schematic.

For more a little more on photoelasticity see http://www.experimentalstress.com/basic_experimental_mechanics/photoelasticity.htm

Sources:

Brewster, D., Experiments on the depolarisation of light as exhibited by various mineral, animal , and vegetable bodies, with a reference of the phenomena to the general principles of polarisation, Phil. Trans. R. Soc. Lond. 105:29-53, 1815. http://rstl.royalsocietypublishing.org/content/105/29.full.pdf+html

Brewster, D., On the communication of the structure of doubly refracting crystals to glass, muriate of soda, fluor spar, and other substances by mechanical compression and dilatation, Phil. Trans. R. Soc. Lond. 106:156-178, 1816. http://rstl.royalsocietypublishing.org/content/106/156.full.pdf+html

Ramesh, K., Kasimayan, T., Neethi Simon, B., Digital photoelasticity – a comprehensive review, J. Strain Analysis, 46(4):245-266, 2011. http://sdj.sagepub.com/content/46/4/245.abstract

www.sciencemuseum.org.uk/online_science/explore_our_collections/objects/index/smxg-3823?agent=smxg-52657

Lesniak, J.R., Zhang, S.J., Patterson, E.A., The design and evaluation of the poleidoscope: a novel digital polariscope, Experimental Mechanics, 44(2):128-135, 2004.

Hobbs, J.W., Greene, R.J., Patterson, E.A., 2003, A novel instrument for transient photoelasticity, Experimental Mechanics, 43(4):403-409, 2003.