Tag Archives: strain

From strain measurements to assessing El Niño events

Figure 11 from RSOS 201086One of the exciting aspects of leading a university research group is that you can never be quite sure where the research is going next.  We published a nice example of this unpredictability last week in Royal Society Open Science in a paper called ‘Transformation of measurement uncertainties into low-dimensional feature space‘ [1].  While the title is an accurate description of the contents, it does not give much away and certainly does not reveal that we proposed a new method for assessing the occurrence of El Niño events.  For some time we have been working with massive datasets of measurements from arrays of sensors and representing them by fitting polynomials in a process known as image decomposition [see ‘Recognising strain‘ on October 28th, 2015]. The relatively small number of coefficients from these polynomials can be collated into a feature vector which facilitates comparison with other datasets [see for example, ‘Out of the valley of death into a hype cycle‘ on February 24th, 2021].  Our recent paper provides a solution to the issue of representing the measurement uncertainty in the same space as the feature vector which is roughly what we set out to do.  We demonstrated our new method for representing the measurement uncertainty by calibrating and validating a computational model of a simple beam in bending using data from an earlier study in a EU-funded project called VANESSA [2] — so no surprises there.  However, then my co-author and PhD student, Antonis Alexiadis went looking for other interesting datasets with which to demonstrate the new method.  He found a set of spatially-varying uncertainties associated with a metamodel of soil moisture in a river basin in China [3] and global oceanographic temperature fields collected monthly over 11 years from 2002 to 2012 [4].  We used the latter set of data to develop a new technique for assessing the occurrence of El-Niño events in the Pacific Ocean.  Our technique is based on global ocean dynamics rather than on the small region in the Pacific Ocean which is usually used and has the added advantages of providing a confidence level on the assessment as well as enabling straightforward comparisons of predictions and measurements.  The comparison of predictions and measurements is a recurring theme in our current research but I did not expect it to lead into ocean dynamics.

Image is Figure 11 from [1] showing convex hulls fitted to the cloud of points representing the uncertainty intervals for the ocean temperature measurements for each month in 2002 using only the three most significant principal components . The lack of overlap between hulls can be interpreted as implying a significant difference in the temperature between months.

References:

[1] Alexiadis, A. and Ferson, S. and  Patterson, E.A., , 2021. Transformation of measurement uncertainties into low-dimensional feature vector space. Royal Society Open Science, 8(3): 201086.

[2] Lampeas G, Pasialis V, Lin X, Patterson EA. 2015.  On the validation of solid mechanics models using optical measurements and data decomposition. Simulation Modelling Practice and Theory 52, 92-107.

[3] Kang J, Jin R, Li X, Zhang Y. 2017, Block Kriging with measurement errors: a case study of the spatial prediction of soil moisture in the middle reaches of Heihe River Basin. IEEE Geoscience and Remote Sensing Letters, 14, 87-91.

[4] Gaillard F, Reynaud T, Thierry V, Kolodziejczyk N, von Schuckmann K. 2016. In situ-based reanalysis of the global ocean temperature and salinity with ISAS: variability of the heat content and steric height. J. Climate. 29, 1305-1323.

Poleidoscope (=polariscope + kaleidoscope)

A section from a photoelastic model of turbine disc with a single blade viewed in polarised light to reveal the stress distribution.Last month I wrote about the tedium of collecting data 35 years ago without digital instrumentation and how it led me to work on automation and digitalisation in experimental mechanics [see ‘35 years later and still working on a PhD thesis‘ on September 16th, 2020].  Thirty years ago, one of the leading methods for determining stresses in components was photoelasticity, which uses polarised light to generate fringe patterns in transparent components or models that correspond to the distribution of stress.  The photoelastic fringes can be analysed in a polariscope, of which the basic principles are explained in a note at the end of this post.  During my PhD, I took hundreds of black and white photographs in a polariscope using sheets of 4×5 film, which came in boxes of 25 sheets that you can still buy, and then scanned these negatives using a microdensitometer to digitise the position of the fringes.  About 15 years after my PhD, together with my collaborators, I patented the poleidoscope which is a combination of a polariscope and a kaleidoscope [US patents 6441972 & 5978087] that removes all of that tedium.  It uses the concept of the multi-faceted lens in a child’s kaleidoscope to create several polariscopes within a compound lens attached to a digital camera.  Each polariscope has different polarising elements such that photoelastic fringes are phase-shifted between the set of images generated by the multi-faceted lens.  The phase-shifted fringe patterns can be digitally processed to yield maps of stress much faster and more reliably than any other method.  Photoelastic stress analysis is no longer popular in mainstream engineering or experimental mechanics due to the simplicity and power of digital image correlation [see ‘256 shades of grey‘ on January 22nd, 2014]; however, the poleidoscope has found a market as an inspection device that provides real-time information on residual stresses in glass sheets and silicon wafers during their production.  In 2003, I took study leave for the summer to work with Jon Lesniak at Glass Photonics in Madison, Wisconsin on the commercialisation of the poleidoscope.  Subsequently, Glass Photonics have  sold more than 250 instruments worldwide.

For more information on the poleidoscope see: Lesniak JR, Zhang SJ & Patterson EA, The design and evaluation of the poleidoscope: a novel digital polariscope, Experimental Mechanics, 44(2):128-135, 2004

Note on the Basic principles of photoelasticity: At any point in a loaded component there is a stress acting in every direction. The directions in which the stresses have the maximum and minimum values for the point are known as principal directions. The corresponding stresses are known as maximum and minimum principal stresses. When polarised light enters a loaded transparent component, it is split into two beams. Both beams travel along the same path, but each vibrates along a principal direction and travels at a speed proportional to the associated principal stress. Consequently, the light emerges as two beams vibrating out of phase with one another which when combined produce an interference pattern.   The polarised light is produced by the polariser in the polariscope and the analyser performs the combination. The interference pattern is observed in the polariscope, and the fringes are contours of principal stress difference which are known as isochromatics. When plane polarised light is used black fringes known as isoclinics are superimposed on the isochromatic pattern. Isoclinics indicate points at which the principal directions are aligned to the polarising axes of the polariser and analyser.

Image: a section from a photoelastic model of turbine disc with a single blade viewed in polarised light to reveal the stress distribution.

Potential dynamic buckling in hypersonic vehicle skin

The skin of an aircraft is supported on the inside by a network, or mesh, of ribs and stringers running approximately at right angles to one another; so that the skin is effectively a series of rectangular plates supported around their edges.   In hypersonic flight, above five times the speed of sound, these rectangular plates are subject to vibration and to high temperatures that vary spatially and with time.  The combined vibratory and thermal loading causes the plates to buckle out of plane which has two possible detrimental consequences: first, it causes the formation of fatigue cracks leading to catastrophic failure; and, second, it might influence the formation of the boundary layer in the flow over the skin of the aircraft and affect the aerodynamics of the aircraft.  In my laboratory, we have built a test-rig that allows us to subject rectangular plates to random mechanical vibrations up to 1000Hz and, at the same time, to temperature distributions upto 1000K that vary in time and space.  Earlier this year, we published an article in which we showed, by experiment, that an edge-reinforced rectangular plate behaved as a dynamic system in response to thermal loading.  In other words, when a constant temperature distribution is applied, the shape of the plate varies with time until an equilibrium state is achieved.  In addition, we found that the post-buckled shape of the plate is not proportional to the energy supplied but dependent on the in-plane temperature distribution.  Probably, both of these observed behaviours are a result of differential thermal expansion of the plate and its reinforcements.

The image shows point-wise temperature and displacement measurements (centre) at the centre and edge of a reinforced plate (top) subject to a localised strip of heating over time as shown by the temperature distributions (bottom).

This is the fourth in a series of posts on recent work published by my research group.  The others are: ‘Salt increases nanoparticle diffusion‘ on April 22nd, 2020; ‘Spatio-temporal damage maps for composite materials‘ on May 6th, 2020; and, ‘Thinking out of the box leads to digital image correlation through space‘ on June 24th, 2020.

Source:

Santos Silva AC, Lambros J, Garner DM & Patterson EA, Dynamic response of a thermally stressed plate with reinforced edges, Experimental Mechanics, 60:81-92, 2020.

Condition-monitoring using infrared imaging

If you have travelled in Asia then you will probably have experienced having your health monitored by infrared cameras as you disembarked from your flight.  It has been common practice in many Asian countries since long before the COVID-19 pandemic and perhaps will become more usual elsewhere as a means of easily identifying people with symptoms of a fever that raises their body temperature.  Since, research has shown that infrared thermometers are slightly more responsive as well as quicker and easier to use than other types of skin surface thermometers [1].  In my research group, we have been using infrared cameras for many years to monitor the condition of engineering structures by evaluating the distribution of load or stress in them [see ‘Counting photons to measure stress‘ on November 18th, 2015 and  ‘Insidious damage‘ on December 2nd, 2015].  In the DIMES project, we have implemented a low-cost sensor system that integrates infrared and visible images with information about applied loads from point sensors, which allows the identification of initiation and tracking of damage in aircraft structures [2].  I reported in December 2019 [see ‘When seeing nothing is a success‘] that we were installing prototype systems in a test-bench at Empa.  Although the restrictions imposed by the pandemic have halted our tests, we were lucky to obtain data from our sensors during the propagation of damage in the section of wing at Empa before lockdown.  This is a landmark in our project and now we are preparing to install our system in test structures at Airbus once the pandemic restrictions are relaxed sufficiently.  Of course, we will also be able to use our system to monitor the health of the personnel involved in the test (see the top image of one of my research team) as well as the health of the structure being tested – the hardware is the same, it’s just the data processing that is different.

The image is a composite showing images from a visible camera (left) and processed data from infrared camera overlaid on the same visible image (right) from inside a wing box during a test at Empa with a crack extending from left to right with its tip surrounded by the red area in the right image.  Each nut in the image is about 20 mm in diameter and a constant amplitude load at 1.25 Hz was being applied causing a wing tip displacement of 80 mm +/- 15 mm.

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.

References

[1] Burnham, R.S., McKinley, R.S. and Vincent, D.D., 2006. Three types of skin-surface thermometers: a comparison of reliability, validity, and responsiveness. American journal of physical medicine & rehabilitation, 85(7), pp.553-558.

[2] Middleton, C.A., Gaio, A., Greene, R.J. and Patterson, E.A., 2019. Towards automated tracking of initiation and propagation of cracks in aluminium alloy coupons using thermoelastic stress analysis. Journal of Nondestructive Evaluation, 38(1), p.18.