Category Archives: structures

More on fairy lights and volume decomposition (with ice cream included)

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Explanation in textLast June, I wrote about representing five-dimensional data using a three-dimensional stack of transparent cubes containing fairy lights whose brightness varied with time and also using feature vectors in which the data are compressed into a relatively short string of numbers [see ‘Fairy lights and decomposing multi-dimensional datasets’ on June 14th, 2023].  After many iterations, we have finally had an article published describing our method of orthogonally decomposing multi-dimensional data arrays using Chebyshev polynomials.  In this context, orthogonal means that components of the resultant feature vector are statistically independent of one another.  The decomposition process consists of fitting a particular form of polynomials, or equations, to the data by varying the coefficients in the polynomials.  The values of the coefficients become the components of the feature vector.  This is what we do when we fit a straight line of the form y=mx+c to set of values of x and y and the coefficients are m and c which can be used to compare data from different sources, instead of the datasets themselves.  For example, x and y might be the daily sales of ice cream and the daily average temperature with different datasets relating to different locations.  Of course, it is much harder for data that is non-linear and varying with w, x, y and z, such as the intensity of light in the stack of transparent cubes with fairy lights inside.  In our article, we did not use fairy lights or icecream sales, instead we compared the measurements and predictions in two case studies: the internal stresses in a simple composite specimen and the time-varying surface displacements of a vibrating panel.

The image shows the normalised out-of-plane displacements as the colour as a function of time in the z-direction for the surface of a panel represented by the xy-plane.

Source:

Amjad KH, Christian WJ, Dvurecenska KS, Mollenhauer D, Przybyla CP, Patterson EA. Quantitative Comparisons of Volumetric Datasets from Experiments and Computational Models. IEEE Access. 11: 123401-123417, 2023.

Predicting release rates of hydrogen from stainless steel

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Decorative photograph showing electrolysis cellThe influence of hydrogen on the structural integrity of nuclear power plant, where water molecules in the coolant circuit can be split by electrolysis or radiolysis to produce hydrogen, has been a concern to engineers for decades.  However, plans for a hydrogen economy and commercial fusion reactors, in which plasma-facing structural components will likely be exposed to hydrogen, has accelerated interest in understanding the complex interactions of hydrogen with metals, especially in the presence of irradiation.  A key step in advancing our understanding of these interactions is the measurement and prediction of the uptake and release of hydrogen by key structural materials.  We have recently published a study in Scientific Reports in which we developed a method for predicting the amount hydrogen in a steel under test conditions.  We used a sample of stainless steel as an electrode (cathode) in an electrolysis cell that split water molecules producing hydrogen atoms that were attracted to the steel. After loading the steel with hydrogen in the cell, we measured the rate of release of the hydrogen from the steel over two minutes by monitoring the drop in current in the cell, using a technique called potentiostatic discharge.  We used our measurements to calibrate a model of hydrogen release rate, based on Fick’s second law of diffusion, which relates the rate of hydrogen motion (diffusion) to the surface area perpendicular to the motion and the concentration gradient in the direction of motion.  Finally, we used our calibrated model to predict the release rate of hydrogen over 24 hours and checked our predictions using a second measurement based on the hydrogen released when the steel was melted.  So, now we have a method of predicting the amount of hydrogen in a steel remaining in a sample many hours after exposure during electrolysis without destroying the test sample.  This will allow us to perform better defined tests on the influence of hydrogen on the performance of stainless steel in the extreme environments of fission and fusion reactors.

Source:

Weihrauch M, Patel M, Patterson EA. Measurements and predictions of diffusible hydrogen escape and absorption in cathodically charged 316LN austenitic stainless steel. Scientific Reports. 13(1):10545, 2023.

Image:

Figure 2a from Weihrauch et al , 2023 showing electrolysis cell setup for potentiostatic discharge experiments.

Taking an aircraft’s temperature as a health check

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The title of this post is the title of a talk that I will deliver during the Pint of Science Festival in Liverpool later this month.  At last year’s festival I spoke about the very small: Revealing the invisible: real-time motion of virus particles [see ‘Fancy a pint of science‘ on April 27th, 2022].  This year I am moving up the size scale and from biomedical engineering to aerospace engineering to talk about condition monitoring in aircraft structures based on our recent research in the INSTRUCTIVE [see ‘INSTRUCTIVE final reckoning‘ on January 9th 2019] and DIMES [see ‘Our last DIMES‘ on September 22, 2021] projects.  I am going describe how we have reduced the size and cost of infrared instrumentation for monitoring damage propagation in aircraft structures while at the same time increasing the resolution so that we can detect 1 mm increments in crack growth in metals and 6 mm diameter indications of damage in composite materials.  If you want to learn more how we did it and fancy a pint of science, then join us in Liverpool later this month for part of the world’s largest festival of public science.  This year we have a programme of engineering talks on Hope Street in Frederiks on May 22nd and in the Philharmonic Dining Rooms on May 23rd where I be the second speaker.

The University of Liverpool was the coordinator of the DIMES project and the other partners were Empa, Dantec Dynamics GmbH and Strain Solutions Ltd.  Strain Solutions Limited was the coordinator of the INSTRUCTIVE project in which the other participant was the University of Liverpool.  Airbus was the project manager for both projects.

The DIMES and INSTRUCTIVE projects  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 and 6968777 respectively.

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.

Structural damage assessment using infrared detectors in fusion environments

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Schematic representation of plasma flux in a fusion reactorAbout six months ago, I described the success of my research group in detecting the early stages of the development of damage in structural components using small, cheap devices based on infrared measurements [see ‘Seeing small changes is a big achievement‘ on October 26th, 2022] after it had been reported in the Proceedings of the Royal Society.  The research was motivated by the needs of the aerospace industry and largely supported via the European Union’s Horizon 2020 research and innovation programme.  We are planning to extend the research to allow our technology to be used for diagnostics in future fusion power plants.  Plasma facing components in these powerplants will experience significant structural and functional degradation in service due to the extreme condition in the reactor.  Our aim is to develop systems based on our infrared monitoring technology that can identify and track material degradation without the need for plant shutdown thereby enabling unplanned maintenance to be undertaken at the earliest sign of component failure.  We are collaborating with the UKAEA and are looking to recruit a PhD student to work on the project supported by the GREEN CDT and Eurofusion.  If you are interested or know someone who might be interested then please follow this link for more information.

Reference:

Amjad, K., Lambert, C.A., Middleton, C.A., Greene, R.J., Patterson, E.A., 2022, A thermal emissions-based real-time monitoring system for in situ detection of cracks, Proc. R. Soc. A., 478: 20210796.