Tag Archives: computational mechanics

On the trustworthiness of multi-physics models

I stayed in Sheffield city centre a few weeks ago and walked past the standard measures in the photograph on my way to speak at a workshop.  In the past, when the cutlery and tool-making industry in Sheffield was focussed around small workshops, or little mesters, as they were known, these standards would have been used to check the tools being manufactured.  A few hundred years later, the range of standards in existence has extended far beyond the weights and measures where it started, and now includes standards for processes and artefacts as well as for measurements.  The process of validating computational models of engineering infrastructure is moving slowly towards establishing an internationally recognised standard [see two of my earliest posts: ‘Model validation‘ on September 18th, 2012 and ‘Setting standards‘ on January 29th, 2014].  We have guidelines that recommend approaches for different parts of the validation process [see ‘Setting standards‘ on January 29th, 2014]; however, many types of computational model present significant challenges when establishing their reliability [see ‘Spatial-temporal models of protein structures‘ on March 27th, 2019].  Under the auspices of the MOTIVATE project, we are gathering experts in Zurich on November 5th, 2019 to discuss the challenges of validating multi-physics models, establishing credibility and the future use of data from experiments.  It is the fourth in a series of workshops held previously in Shanghai, London and Munich.  For more information and to register follow this link. Come and join our discussions in one of my favourite cities where we will be following ‘In Einstein’s footprints‘ [posted on February 27th, 2019].

The MOTIVATE project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 754660.

In Einstein’s footprints?

Grand Hall of the Guild of Carpenters, Zurich

During the past week, I have been working with members of my research group on a series of papers for a conference in the USA that a small group of us will be attending in the summer.  Dissemination is an important step in the research process; there is no point in doing the research if we lock the results away in a desk drawer and forget about them.  Nowadays, the funding organisations that support our research expect to see a plan of dissemination as part of our proposals for research; and hence, we have an obligation to present our results to the scientific community as well as to communicate them more widely, for instance through this blog.

That’s all fine; but nevertheless, I don’t find most conferences a worthwhile experience.  Often, there are too many uncoordinated sessions running in parallel that contain presentations describing tiny steps forward in knowledge and understanding which fail to compel your attention [see ‘Compelling presentations‘ on March 21st, 2018].  Of course, they can provide an opportunity to network, especially for those researchers in the early stages of their careers; but, in my experience, they are rarely the location for serious intellectual discussion or debate.  This is more likely to happen in small workshops focussed on a ‘hot-topic’ and with a carefully selected eclectic mix of speakers interspersed with chaired discussion sessions.

I have been involved in organising a number of such workshops in Glasgow, London, Munich and Shanghai over the last decade.  The next one will be in Zurich in November 2019 in Guild Hall of Carpenters (Zunfthaus zur Zimmerleuten) where Einstein lectured in November 1910 to the Zurich Physical Society ‘On Boltzmann’s principle and some of its direct consequences‘.  Our subject will be different: ‘Validation of Computational Mechanics Models’; but we hope that the debate on credible models, multi-physics simulations and surviving with experimental data will be as lively as in 1910.  If you would like to contribute then download the pdf from this link; and if you just like to attend the one-day workshop then we will be announcing registration soon and there is no charge!

We have published the outcomes from some of our previous workshops:

Advances in Validation of Computational Mechanics Models (from the 2014 workshop in Munich), Journal of Strain Analysis, vol. 51, no.1, 2016

Strain Measurement in Extreme Environments (from the 2012 workshop in Glasgow), Journal of Strain Analysis, vol. 49, no. 4, 2014.

Validation of Computational Solid Mechanics Models (from the 2011 workshop in Shanghai), Journal of Strain Analysis, vol. 48, no.1, 2013.

The workshop is supported by the MOTIVATE project and further details are available at http://www.engineeringvalidation.org/4th-workshop

The MOTIVATE project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 754660.

Can you trust your digital twin?

Author's digital twin?

Author’s digital twin?

There is about a 3% probability that you have a twin. About 32 in 1000 people are one of a pair of twins.  At the moment an even smaller number of us have a digital twin but this is the direction in which computational biomedicine is moving along with other fields.  For instance, soon all aircraft will have digital twins and most new nuclear power plants.  Digital twins are computational representations of individual members of a population, or fleet, in the case of aircraft and power plants.  For an engineering system, its computer-aided design (CAD) is the beginning of its twin, to which information is added from the quality assurance inspections before it leaves the factory and from non-destructive inspections during routine maintenance, as well as data acquired during service operations from health monitoring.  The result is an integrated model and database, which describes the condition and history of the system from conception to the present, that can be used to predict its response to anticipated changes in its environment, its remaining useful life or the impact of proposed modifications to its form and function. It is more challenging to create digital twins of ourselves because we don’t have original design drawings or direct access to the onboard health monitoring system but this is being worked on. However, digital twins are only useful if people believe in the behaviour or performance that they predict and are prepared to make decisions based on the predictions, in other words if the digital twins possess credibility.  Credibility appears to be like beauty because it is in eye of the beholder.  Most modellers believe that their models are both beautiful and credible, after all they are their ‘babies’, but unfortunately modellers are not usually the decision-makers who often have a different frame of reference and set of values.  In my group, one current line of research is to provide metrics and language that will assist in conveying confidence in the reliability of a digital twin to non-expert decision-makers and another is to create methodologies for evaluating the evidence prior to making a decision.  The approach is different depending on the extent to which the underlying models are principled, i.e. based on the laws of science, and can be tested using observations from the real world.  In practice, even with principled, testable models, a digital twin will never be an identical twin and hence there will always be some uncertainty so that decisions remain a matter of judgement based on a sound understanding of the best available evidence – so you are always likely to need advice from a friendly engineer   🙂

Sources:

De Lange, C., 2014, Meet your unborn child – before it’s conceived, New Scientist, 12 April 2014, p.8.

Glaessgen, E.H., & Stargel, D.S., 2012, The digital twin paradigm for future NASA and US Air Force vehicles, Proc 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, AIAA paper 2012-2018, NF1676L-13293.

Patterson E.A., Feligiotti, M. & Hack, E., 2013, On the integration of validation, quality assurance and non-destructive evaluation, J. Strain Analysis, 48(1):48-59.

Patterson, E.A., Taylor, R.J. & Bankhead, M., 2016, A framework for an integrated nuclear digital environment, Progress in Nuclear Energy, 87:97-103.

Patterson EA & Whelan MP, 2016, A framework to establish credibility of computational models in biology, Progress in Biophysics & Molecular Biology, doi: 10.1016/j.pbiomolbio.2016.08.007.

Tuegel, E.J., 2012, The airframe digital twin: some challenges to realization, Proc 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference.