Please read our student and staff community guidance on Covid-19
Skip to main content Skip to navigation

Adaptive probabilistic meshless methods for evolutionary systems

Supervisors: Tim Sullivan (Mathematics and Engineering), James Kermode (Engineering),
Jon Cockayne (Alan Turing Institute)

This project will develop and implement a new class of numerical solvers for evolving systems such as interacting fluid-structure flows. To cope with extreme strain rates and large deformations these new solvers will be adaptive and meshless, and they will also implicitly represent their own solution uncertainty, thus enabling optimal design and uncertainty quantification. This exciting project brings together aspects of continuum mechanics, numerical methods for partial differential equations, and statistical machine learning.

Adaptive probabilistic meshless methods for evolutionary systems