Active Materials & Manufacturing Engineering

Risk Assuring Future Structure Critical Systems: Combining 21st Century Science with Engineering Intuition - Renewal

In plain English

AI plain-English summary

Every time you sit in a new chair, you rely on gut instinct, not science, to decide it won’t collapse. This fellowship aims to replace that kind of empirical guesswork with rigorous predictive modelling for critical structures where failure is catastrophic—think fusion reactors or aerospace power systems. The problem is a gap between two worlds. Materials science can simulate how atoms behave under stress, giving a best estimate of performance. But engineering needs to account for real-world variability: tiny defects, manufacturing flaws, and damage over time. Currently, engineers rely on past experience and safety margins, not on the science that could predict future failure. This project builds a bridge between atomistic models and the bounding estimates that engineers actually use. If successful, the research could transform how we assure safety in high-integrity systems—from aircraft engines to nuclear reactors—where we have no centuries of trial-and-error to fall back on. It would give regulators, manufacturers, and the public a science-based trust in structures that have never been built before, rather than relying on empirical knowledge that only tells us what happened last time.

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As you read this you are probably sitting down. When you sat down, were you concerned that the chair would fail? You likely did not even consider it as you may have sat in this same chair hundreds, if not thousands of times before. You used your empirical knowledge that this chair is safe for you to sit in. What if this was a new chair to you? If the chair was brand new, you would take comfort in the fact that the chair has been manufactured to a standard and been subject to some level of quality control. If the chair belongs to an organisation then you would expect that organisation to take responsibility if the chair failed and would have been replaced if reported by another user. Failure of the chair will, very rarely, be due to a poor design. The chair will be able to withstand any expected loads assuming that it has been manufactured correctly; however, the material that it is made from will be inherently variable and contain defects that are not always apparent at the point of a manufacturing inspection. The degree of that material variability may be slight and the defect sizing understood, but making sure that the design takes account of this variability through life (especially when the chair is mistreated) is often not considered. To some extent we are all materials engineers when we make a judgement that the chair appears to be 'sturdy' before we sit down, but we do this based on our empirical knowledge and not on the science that is available to us. Are you sure the next time you sit in the chair it won't fail? Your empirical knowledge only informs you of what happened last time not what 'will' happen in the future. The application of materials science knowledge will inform the future performance. Bridging the gap between the atomistic world of materials science that defines the best estimate of mechanical performance and the bounding estimates required in materials engineering that takes account of the variability and defects is key to improving trust in applying materials science to engineering structures. Assurance is about the trust that we place that the quality system has not failed. The chair may have been subject to a level of quality control before it left the factory, at this stage we need to have trust in the manufacturer. If the chair belongs to an individual or organisation, we trust that as responsible owners, that they would replace the chair if broken and that they have systems in place to check if the chair is broken before someone sits on it. This fellowship is about developing a similar level of trust for future high integrity or critical applications. We cannot use empirical knowledge, i.e. we don't have thousands of years of experience with building fusion reactors or producing high integrity power transmission systems for aerospace applications, so we must use science. Developing a similar level of trust in the predictive modelling capability in the application of materials science to these complex and high value systems, to the empirical knowledge we all have of our usual chair is key to unlocking the public trust in the safe performance of future critical systems.

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Researchers

Catrin Davies (Co-Investigator)Daniel James Cogswell (Principal Investigator)Ed Pickering (Co-Investigator)

Related Research

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Risk Assuring Future Structure Critical Systems: Combining 21st Century Science with Engineering Intuition
Geometric Mechanics of Solids: new analysis of modern engineering materials
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Reducing risk through uncertainty quantification for past, present and future generations of nuclear power plants
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Original classification

Fellowship

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