Tacit knowledge is traditionally defined as knowledge that is not explicit or that is difficult to express or transfer from someone else. This description of what it is not makes the definition itself tacit knowledge which is not very helpful. Management guides resolve this by giving examples, such as aesthetic sense, or innovation and leadership skills which are elusive skills that are hard to explain [see ‘Innovation out of chaos‘ on June 29th 2016 and ‘Clueless on leadership style‘ on June 14th, 2017]. In engineering, there are a series of skills that are hard to explain or teach, including creative problem-solving [see ‘Learning problem-solving skills‘ on October 24th, 2018], artful design [see ‘Skilled in ingenuity‘ on August 19th, 2015] and elegant modelling [see ‘Credibility is in the eye of the beholder‘ on April 20th, 2016]. In a university course we attempt to lay the foundations for this tacit engineering knowledge; however, much of it is gained in work through experience and becomes regarded by organisations as part of their intellectual assets – the core of their competitiveness and source of their sustainable technology advantage. In our work on integrated nuclear digital environments, from which digital twins can be spawned, we would like to capture both explicit and tacit knowledge about complex systems throughout their life cycle which will extend beyond the working lives of their designers, builders and operators. One of the potential advantages of digital twins is as a knowledge management system by duplicating the life of the physical system and thus allowing its safer and cheaper operation in the long-term as well as its eventual decommissioning. However, besides the very nature of tacit knowledge that makes its capture difficult, we are finding that its perceived value as an intellectual asset renders stakeholders reluctant to discuss it with us; never mind consider how it might be preserved as part of a digital twin. Research has shown that tacit knowledge sharing is influenced by environmental factors including national culture, leadership characteristics and social networks [Cai et al, 2020]. I suspect that all of these factors were present in the heyday of the UK civil nuclear power industry when it worked together to construct advanced and complex systems; however, it has not built a power station since 1995 and, at the moment, new power stations are cancelled more often than built, which has almost certainly depressed all of these factors. So, perhaps we should not be surprised by the difficulties encountered in establishing an integrated nuclear digital environment despite its importance for the future of the industry.
Digital twins are a combination of computational models and real-world data describing the form, function and condition of a system [see ‘Can you trust your digital twin?‘ on November 23rd 2016]. They are beginning to transform design processes for complex systems in a number of industries. We have been working on a proof-of-concept study for a digital reactor in fission energy based on the Integrated Nuclear Digital Environment (INDE) . The research has been conducted by the Virtual Engineering Centre (VEC) at the University of Liverpool together with partners from industry and national laboratories with funding from the UK Government for nuclear innovation. In parallel, I having been working with a colleague at the University of Manchester and partners at the Culham Centre for Fusion Energy on the form of a digital environment for fusion energy taking account of the higher order of complexity, the scale of resources, the integration of novel technologies, and the likely diversity and distribution of organisations involved in designing, building and operating a fusion powerplant. We have had positive interactions with the regulatory authorities during the digital fission reactor project and the culture of enabling-regulation  offers an opportunity for a new paradigm in the regulation of fusion powerplants. Hence, we propose in a new PhD project to investigate the potential provided by the integration of digital twins with the regulatory environment to enable innovation in the design of fusion powerplants.
The PhD project is fully-funded for UK and EU citizens as part of a Centre for Doctoral Training and will involve a year of specialist training followed by three years of research. For more information following this link.
Digital everything is trendy at the moment. I am as guilty as everyone else: my research group is using digital cameras to monitor the displacement and deformation of structural components using a technique called digital image correlation (see my post on 256 Shades of grey on January 22nd, 2014) . Some years ago, in a similar vein, I pioneered a technique known as ‘digital photoelasticity’ (se my post on ‘Cow bladders lead to strain measurement‘ on January 7th, 2015.. But, what do we mean by ‘digital’? Originally it meant related to, resembling or operated by a digit or finger. However, electronic engineers will refer us to A-to-D and D-to-A converters that transform analogue signals into digital signals and vice versa. In this sense, digital means ‘expressed in discrete numerical form’ as opposed to analogue which means something that can vary continuously . Digital signals are ubiquitous because computers can handle digital information easily. Computers could be described as very, very large series of switches that can be either on or off, which allows numbers to be represented in binary. The world’s second largest computer, Tianhe-2, which I visited in Guangzhou a couple of years ago, has about 12.4 petabytes (about 1016 bytes) of memory which compares to 100 billion (1012) neurons an average human brain. There’s lots of tasks at which the world’s largest computers are excellent but none of them can drive a car, ride a bicycle, tutor a group of engineering students and write a blog post on the limits of digital technology all in a few hours. Ok, we could connect specialized computers together wirelessly under the command of one supercomputer but that’s incomparable to the 1.4 kilograms of brain cells in an engineering professor’s skull doing all of this without being reprogrammed or requiring significant cooling.
So, what’s our brain got that the world latest computer hasn’t? Well, it appears to be analogue and not digital. Our consciousness appears to arise from assemblies of millions of neurons firing in synchrony and because each neuron can fire at an infinite number of levels, then our conscious thoughts can take on a multiplicity of forms that a digital computer can never hope to emulate because its finite number of switches have only two positions each: on and off.
I suspect that the future is not digital but analogue; we just don’t know how to get there, yet. We need to stop counting with our digits and start thinking with our brains.