Research lectures, seminars and events
The events listed in this area are research seminars, workshops and lectures hosted by Durham University departments and research institutes. If you are not a member of the University, but wish to enquire about attending one of the events please contact the organiser or host department.
|October 2019||December 2019|
Events for 27 November 2019
* These postgraduate seminars are hosted by CdT, but welcome presentations and attendance from all members of the postgraduate community.
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Long Chen: Topological evolution and the equivalent unstirring problem in resistive magnetic relaxation
Complex magnetic fields in plasmas may eventually relax to a simple state even if the resistivity is small. Nevertheless, what predicts the end state remains unclear. Using 3D magnetohydrodynamic (MHD) models, we find that there are two stages of topological evolution. The first is a fast reconnection phase constrained by the topological degree. The next is a slow phase dominated by diffusion and shows rearrangement and reconnection of discrete flux tubes. The end state always has two flux tubes with opposite twists, just as predicted by E. N. Parker.
Meanwhile, we find the topological change can also be studied in 2D effective models at a low computational cost. Interestingly, the structural change in the reduced model during the first stage is similar to the reverse process of fluid mixing. The overall reduction in complexity is consistent with an optimal unstirred state.
Contact Christopher Prior for more information about this event.
Nigel Aston: ‘Thomas Townson and high church continuities and connections in eighteenth century England’
Jonathan Owen: A Bayesian statistical approach to decision support for petroleum reservoir well control optimisation
Complex mathematical computer models are used across many scientific disciplines and industry to improve the understanding of the behaviour of physical systems and increasingly to aid decision makers. Major limitations to the use of computer simulators include their complex structure; high-dimensional parameter spaces and large number of unknown model parameters; which is further compounded by their long evaluation times. Decision support, commonly misrepresented as an optimisation task, often requires a large number of model evaluations rendering traditional optimisation methods intractable whilst simultaneously failing to incorporate uncertainty. Consequently, they may yield non-robust decisions.
I will present an iterative decision support strategy which imitates the history matching procedure aiming to identify a robust class of decisions. Bayes linear emulators provide fast, statistical approximations to computer models, yielding predictions for as yet unevaluated parameter settings, along with a corresponding quantification of uncertainty. Appropriate structured uncertainties are accurately quantified and incorporated to link the sophisticated computer model and the actual system in order to obtain robust decisions for the real world problem.
In the petroleum industry, TNO devised a field development optimisation challenge under uncertainty providing an ensemble of 50 fictitious oil reservoir models generated using a stochastic geology model. This challenge exhibits many of the common issues associated with computer experimentation. I will demonstrate the robust decision support strategy applied to the TNO challenge for a greatly reduced computational cost versus ensemble optimisers. This includes the construction of a targeted Bayesian design as well as methods of identifying subsets of models as representatives for the entire ensemble.
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Prof. Melinda J. Duer: Heavy mice and light things: using solid-state NMR spectroscopy to understand biological tissues in health and disease
Very Revd Dr Sarah Rowland Jones LVO OBE: Anglican Communion Office Seminar. An Anglican praxis for public engagement in troubling times- with lessons from Desmond Tutu
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