Tag Archives: modelling

Fake facts & untrustworthy predictions

I need to confess to writing a misleading post some months ago entitled ‘In Einstein’s footprints?‘ on February 27th 2019, in which I promoted our 4th workshop on the ‘Validation of Computational Mechanics Models‘ that we held last month at Guild Hall of Carpenters [Zunfthaus zur Zimmerleuten] in Zurich.  I implied that speakers at the workshop would be stepping in Einstein’s footprints when they presented their research at the workshop, because Einstein presented a paper at the same venue in 1910.  However, as our host in Zurich revealed in his introductory remarks , the Guild Hall was gutted by fire in 2007 and so we were meeting in a fake, or replica, which was so good that most of us had not realised.  This was quite appropriate because a theme of the workshop was enhancing the credibility of computer models that are used to replicate the real-world.  We discussed the issues surrounding the trustworthiness of models in a wide range of fields including aerospace engineering, biomechanics, nuclear power and toxicology.  Many of the presentations are available on the website of the EU project MOTIVATE which organised and sponsored the workshop as part of its dissemination programme.  While we did not solve any problems, we did broaden people’s understanding of the issues associated with trustworthiness of predictions and identified the need to develop common approaches to support regulatory decisions across a range of industrial sectors – that’s probably the theme for our 5th 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 and the Swiss State Secretariat for Education, Research and Innovation under contract number 17.00064.

The opinions expressed in this blog post reflect only the author’s view and the Clean Sky 2 Joint Undertaking is not responsible for any use that may be made of the information it contains.

Image: https://www.tagesanzeiger.ch/Zunfthaus-Zur-Zimmerleuten-Wiederaufbauprojekt-steht/story/30815219

 

Same problems in a different language

I spent a lot of time on trains last week.  I left Liverpool on Tuesday evening for Bristol and spent Wednesday at Airbus in Filton discussing the implementation of the technologies being developed in the EU Clean Sky 2 projects MOTIVATE and DIMES.  On Wednesday evening I travelled to Bracknell and on Thursday gave a seminar at Syngenta on model credibility in predictive toxicology before heading home to Liverpool.  But, on Friday I was on the train again, to Manchester this time, to listen to a group of my PhD students presenting their projects to their peers in our new Centre for Doctoral Training called Growing skills for Reliable Economic Energy from Nuclear, or GREEN.  The common thread, besides the train journeys, is the Fidelity And Credibility of Testing and Simulation (FACTS).  My research group is working on how we demonstrate the fidelity of predictions from models, how we establish trust in both predictions from computational models and measurements from experiments that are often also ‘models’ of the real world.  The issues are similar whether we are considering the structural performance of aircraft [as on Wednesday], the impact of agro-chemicals [as on Thursday], or the performance of fusion energy and the impact of a geological disposal site [as on Friday] (see ‘Hierarchical modelling in engineering and biology‘ on March 14th, 2018) .  The scientific and technical communities associated with each application talk a different language, in the sense that they use different technical jargon and acronyms; and they are surprised and interested to discover that similar problems are being tackled by communities that they rarely think about or encounter.

Destruction of society as a complex system?

Sadly my vacation is finished [see ‘Relieving stress‘ on July 17th, 2019] and I have reconnected to the digital world, including the news media.  Despite the sensational headlines and plenty of rhetoric from politicians, nothing very much appears to have really changed in the world.  Yes, we have a new prime minister in the UK, who has a different agenda to the previous incumbent; however, the impact of actions by politicians on society and the economy seems rather limited unless the action represents a step change and is accompanied by appropriate resources.  In addition, the consequences of such changes are often different to those anticipated by our leaders.  Perhaps, this is because society is a global network with simple operating rules, some of which we know intuitively, and without a central control because governments exert only limited and local control.  It is well-known in the scientific community that large networks, without central control but with simple operating rules, usually exhibit self-organising and non-trivial emergent behaviour. The emergent behaviour of a complex system cannot be predicted from the behaviour of its constituent components or sub-systems, i.e., the whole is more than the sum of its parts.  The mathematical approach to describing such systems is to use non-linear dynamics with solutions lying in phase space.  Modelling complex systems is difficult and interpreting the predictions is challenging; so, it is not surprising that when the actions of government have an impact then the outcomes are often unexpected and unintended.  However, if global society can be considered as a complex system, then it would appear that its self-organising behaviour tends to blunt the effectiveness of many of the actions of government.  This seems be a fortuitous regulatory mechanism that helps maintain the status quo.   In addition, we tend to ignore phenomena whose complexity exceeds our powers of explanation, or we use over-simplified explanations [see ‘Is the world incomprehensible?‘ on March 15th, 2017 and Blind to complexity‘ on December 19th, 2018].  And, politicians are no exception to this tendency; so, they usually legislate based on simple ideology rather than rational consideration of the likely outcomes of change on the complex system we call society. And, this is probably a further regulatory mechanism.

However, all of this is evolving rapidly because a small number of tech companies have created a central control by grabbing the flow of data between us and they are using it to manipulate those simple operating rules.  This appears to be weakening the self-organising and emergent characteristics of society so that the system can be controlled more easily without the influence of its constituent parts, i.e. us.

For a more straightforward explanation listen to Carole Cadwalladr’s TED talk on ‘Facebook’s role in Brexit – and the threat to democracy‘ or if you have more time on your hands then watch the new documentary movie ‘The Great Hack‘.  My thanks to Gillian Tett in the FT last weekend who alerted me to the scale of the issue: ‘Data brokers: from poachers to gamekeepers?

 

Spatial-temporal models of protein structures

For a number of years I have been working on methods for validating computational models of structures [see ‘Model validation‘ on September 18th 2012] using the full potential of measurements made with modern techniques such as digital image correlation [see ‘256 shades of grey‘ on January 22nd 2014] and thermoelastic stress analysis [see ‘Counting photons to measure stress‘ on November 18th 2015].  Usually the focus of our interest is at the macroscale, for example the research on aircraft structures in the MOTIVATE project; however, in a new PhD project with colleagues at the National Tsing Hua University in Taiwan, we are planning to explore using our validation procedures and metrics [1] in structural biology.

The size and timescale of protein-structure thermal fluctuations are essential to the regulation of cellular functions. Measurement techniques such as x-ray crystallography and transmission electron cryomicroscopy (Cryo-EM) provide data on electron density distribution from which protein structures can be deduced using molecular dynamics models. Our aim is to develop our validation metrics to help identify, with a defined level of confidence, the most appropriate structural ensemble for a given set of electron densities. To make the problem more interesting and challenging the structure observed by x-ray crystallography is an average or equilibrium state because a folded protein is constantly in motion undergoing harmonic oscillations, each with different frequencies and amplitude [2].

The PhD project is part of the dual PhD programme of the University of Liverpool and National Tsing Hua University.  Funding is available in form of a fee waiver and contribution to living expenses for four years of study involving significant periods (perferably two years) at each university.  For more information follow this link.

References:

[1] Dvurecenska, K., Graham, S., Patelli, E. & Patterson, E.A., A probabilistic metric for the validation of computational models, Royal Society Open Society, 5:180687, 2018.

[2] Justin Chan, Hong-Rui Lin, Kazuhiro Takemura, Kai-Chun Chang, Yuan-Yu Chang, Yasumasa Joti, Akio Kitao, Lee-Wei Yang. An efficient timer and sizer of protein motions reveals the time-scales of functional dynamics in the ribosome (2018) https://www.biorxiv.org/content/early/2018/08/03/384511.

Image: A diffraction pattern and protein structure from http://xray.bmc.uu.se/xtal/