Category Archives: MyResearch

Opportunities lost in knowledge management using digital technology

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Decorative imageRegular readers of this blog will know that I occasionally feature publications from my research group.  The most recent was ‘Predicting release rates of hydrogen from stainless steel’ on September 13th, 2023 and before that ‘Label-free real-tracking of individual bacterium’ on January 25th 2023 and ‘A thermal emissions-based real-time monitoring system for in situ detection of cracks’ in ‘Seeing small changes is a big achievement’ on October 26th 2023.  The subject of these publications might seem a long way apart but they are linked by my interest in trying to measure events in the real-world and use the data to develop and validate high-fidelity digital models.  Recently, I have stretched my research interests still further through supervising a clutch of PhD students with a relatively new collaborator working in the social sciences.  Two of the students have had their first papers published by the ASME (American Society of Mechanical Engineers) and the IEEE (Institute of Electrical and Electronics Engineers).  Their papers are not directly connected but they both explore the use of published information to gain new insights on a topic.  In the first one [1], we have explored the similarities and differences between safety cases for three nuclear reactors: a pair of research reactors – one fission and one fusion reactor; and a commercial fission reactor.  We have developed a graphical representation of the safety features in the reactors and their relationships to the fundamental safety principles set out by the nuclear regulators. This has allowed us to gain a better understanding of the hazard profiles of fission and fusion reactors that could be used to create the safety case for a commercial fusion reactor.  Fundamentally, this paper is about exploiting existing knowledge and looking at it in a new way to gain fresh insights, which we did manually rather than automating the process using digital technology.  In the second paper [2], we have explored the extent to which digital technologies are being used to create, collate and curate knowledge during and beyond the life-cycle of an engineering product.  We found that these processes were happening but generally not in a holistic manner.  Consequently, opportunities were being lost through not deploying digital technology in knowledge management to undertake multiple roles simultaneously, e.g., acting as repositories, transactive memory systems (group-level knowledge sharing), communication spaces, boundary objects (contact points between multiple disciplines, systems or worlds) and non-human actors.  There are significant challenges, as well as competitive advantages and organisational value to be gained, in deploying digital technology in holistic approaches to knowledge management.  However, despite the rapid advances in machine learning and artificial intelligence [see ‘Update on position of AI on hype curve: it cannot dream’ on July 26th 2023] that will certainly accelerate and enhance knowledge management in a digital environment, a human is still required to realise the value of the knowledge and use it creatively.

References

  1. Nguyen, T., Patterson, E.A., Taylor, R.J., Tseng, Y.S. and Waldon, C., 2023. Comparative maps of safety features for fission and fusion reactors. Journal of Nuclear Engineering and Radiation Science, pp.1-24
  2. Yao, Y., Patterson, E.A. and Taylor, R.J., 2023. The Influence of Digital Technologies on Knowledge Management in Engineering: A Systematic Literature Review. IEEE Transactions on Knowledge and Data Engineering.

Work, rest and play in Smallville

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Decorative imageI am comfortable with the lack of certainty about us not being in a simulation [see ‘Are we in a simulation?‘ on September 28, 2022].  However, I know that some of you would prefer not to consider this possibility.  Unfortunately, recently published research has likely increased the probability that we are in a simulation because the researchers set up a simulation of a community of human-like agents called Smallville [Park et al, 2023].  The generative agents fuse large language models used in artificial intelligence with computational, interactive agents who eat, sleep, work and play just like humans and coalesce into social groups.  The simulation was created as a research tool for studying human interactions and emergent social behaviour which completely concurs with the argument for us already being part of a simulation created to study social behaviour.  Smallville only had 25 virtual inhabitants but the speed of advances in artificial intelligence and computational tools perhaps implies that a simulation of billions of agents (people) is not as far in the future as we once thought thus making it more credible that we are in a simulation.  The emergent social behaviour observed in Smallville suggests that our society is essentially a self-organising complex system that cannot be micro-managed from the centre.

Sources:

Oliver Roeder, Keeping up with the ChatGPT neighbours, FT Weekend, August 26/27 2023.

Camilla Cavendish, Charities could lead new age of community spirit, FT Weekend, August 26/27 2023.

Park JS, O’Brien JC, Cai CJ, Morris MR, Liang P, Bernstein MS. Generative agents: Interactive simulacra of human behavior. arXiv preprint arXiv:2304.03442. 2023.

Image: Ceramic tile by Pablo Picasso in museum in Port de Sóller Railway Station, Mallorca.

 

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.

Conflicted about cost-benefit analysis of international conferences

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Decorative image of an aircraftLast week I wrote about my stimulating experience of attending a conference in Orlando, Florida and presenting our recent research to the experimental mechanics community for the first time in four years.  Whilst there, I was conscious of the ecological footprint of my trip – the venue was making extensive use of single use plastics on a scale that surprised me.  However, my trans-Atlantic flight had an order of magnitude larger impact.  It is difficult to find a reliable estimate of the carbon emissions for a return flight between the UK and Florida but 1,267 kg CO2 from the Guardian newspaper website lies between a lower bound estimate of 856 kg CO2 from iata.org and and an upper bound of 2,200 kg CO2 from myclimate.org.  This is equivalent to about one-sixth of my annual domestic carbon footprint of 9,000 kg CO2 using the calculator on the World Wildlife Fund website.  The UK average footprint is 9,300 kg CO2/capita and the global average is 6,300 kg CO2/capita.  The question is whether it is justifiable to generate additional emissions to attend a research conference?  The prime motivation of the research that I presented is to support the development of aircraft which are lighter with less embedded carbon and use less energy while also having a longer useful life.  Ultimately, supporting the aviation industry to achieve its target of zero-net emissions by 2050.  The carbon emissions of the global aviation industry in 2021 were 720 Mt CO2 [see IEA report]; hence, if my research contributes towards one hundredth of a percent reduction in these emissions then this would be 72,000 kg CO2/year.  It seems reasonable to cause a tenth of this annual saving each year (7,200 kg CO2/year) for the next ten years in order to deliver the required technology, i.e., committing one year’s savings to achieve an annual saving in perpetuity.  The problem is that I do not have a reliable estimate of the carbon footprint of my research activities.  I supervised an MSc student a couple of years ago who conducted a carbon audit of the School of Engineering and estimated the carbon emissions due to research alone to be 61,531 kg CO2 excluding heating, lighting and travel.  My group might be responsible for 10% of these emissions, i.e., about 6000 kg CO2; hence, adding about 1,200 kg CO2 to interact with other researchers at a conference seems reasonable and within a budget of 7,200 kg CO2. However, it is difficult to find reliable data to use in estimating carbon emissions for these activities and so perhaps the key conclusion is that we need more and better carbon audits to allow more informed decision-making.  In the meantime, perhaps attendence at an international conference once every four years is sufficient.

Image: Tayeb Mezahdia