Category Archives: Engineering

Commoditisation of civil nuclear power

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Logo for BBC Inside ScienceA colleague and I published a paper last month that we hope will bring about a paradigm shift in the nuclear power industry. I was interviewed on BBC Radio 4’s Inside Science on the day following its publication – its the first time one of my scientific papers has made that big a splash in the media!  You can listen to the programme on BBC Sounds at https://www.bbc.co.uk/sounds/play/m001zdwv.

In the paper we describe a blueprint for the factory-production of sealed micro-power units with a digitally-enabled, holistic assurance framework.  Currently, several designs of micro-reactors are progressing to the prototype stage with hazards contained on-site.  The integration of these approaches enables a transformation of the regulatory regime to type or series approval at the factory, similar to the aerospace industry, and supported by digital tools such as block chains to provide transparent quality assurance within the supply chain.  The transformation of the regulatory regime and the shift to ‘flow’ production in a factory would remove the financial risk from the power plant to the factory thereby enabling nuclear power to become a realistic competitor for intermittent green energy sources, such as wind and solar, both in terms of financial and ecological costs.  The output from three production lines could replace the current electricity generating capacity from fossil fuels in the UK over approximately 15 years thus making a significant contribution to achieving net zero greenhouse gas emissions.  We propose a design philosophy for the micro-power units that will allow them to go unnoticed in an urban environment or even become an iconic product that signals a community’s commitment to responsible stewardship of the Earth’s resources.  Our blueprint represents a revolutionary change for the nuclear power industry that would likely lead to the commoditisation of nuclear power whereas the status quo probably leads to extinction.

The paper is published with open access (its free) at Patterson EA & Taylor RJ, 2024, The commoditisation of civil nuclear power, Royal Society Open Science, 11:240021.

Extra on digital twins

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After five months of posting monthly, I cannot resist the temptation to slip in an extra one.  Mainly because I want to let you know about the Pint of Science Festival taking place next week.  In Liverpool we have organised a series of three evenings at the Philharmonic pub on Hope Street featuring talks by engineers from the School of Engineering and the Institute for Digital Engineering and Autonomous Systems (IDEAS) at the University of Liverpool.  I am planning to talk about digital twins – what they are, how we can use them, what they might become and whether we are already part of a digital world.  If you enjoyed reading my posts on ‘Digital twins that thrive in the real world’, ‘Dressing up your digital twin’, and ‘Are we in a simulation?’ then come and discuss digital twins with me in person.  My talk is part of a programme on Digital with Everything on May 15th.  On May 13th and 14th we have programmes on Engineering in Nature and Science of Vision, Colliders and Crashes, respectively.  I hope you can come and join us in the real-world.

Highest mountain, deepest lake, smallest church and biggest liar

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Last month we took a short vacation in the Lake District and stayed in Wasdale whose tag-line is highest mountain, deepest lake.  The mountain is Scafell Pike, the highest mountain in England at 978 m, which we never saw because the clouds never lifted high enough to reveal it.  The lake is Wast Water, the deepest lake in England at 74 m, which rose slowly during our week due to the almost continuous rain falling on the surrounding hills.  But that’s typical Lake District weather because the area protrudes to the west of England so it is the first landfall for rainstorms moving east after they have replenished with water over the Irish Sea.  We spent our time reading in our cottage and venturing out to walk in lowlands when the lake was a calm presence, occasionally reflecting the surrounding mountains but more often dark reflecting the low clouds.  We were not tempted to test its temperature but I would expect it to have been around 4 °C because this is the temperature of the water in the depths of all deep lakes all year around.  Hence, in winter the surface layers of water will usually be colder than 4 °C and in summer warmer than 4 °C reflecting the air temperature, so in spring when we visited it would probably have been around 4 °C.  Water expands when it freezes which is possible on the surface of bodies of water where it can expand into the air; however, at depths in deep lakes the pressure prevents the expansion required for the freezing process and equilibrium between opposing processes occurs at about 4 °C.  Thus, the water at the bottom of all deep lakes remains at 4 °C all year with a gradient of increasing temperatures towards the surface in summer and of decreasing temperatures in winter.

Wasdale also claims the smallest church, St Olaf’s and the biggest liar, Will Ritson (1808-1890) who was a landlord of the Wastwater Hotel.  He won the annual world’s biggest liar competition by saying, when it was his turn, that he was withdrawing from the competition because having heard the other competitors he could not tell a bigger lie.

Image: Wast Water with clouds sitting on Great Gable at the east end of the lake.

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.