news
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision | |||
|
news [2018/05/10 17:15] potthast |
news [2018/05/10 17:15] (current) potthast |
||
|---|---|---|---|
| Line 21: | Line 21: | ||
| April 2018. | April 2018. | ||
| FROM CRACK PROPAGATION TO RANDOM GRAPHS AND THE ARCTIC SEA ICE | FROM CRACK PROPAGATION TO RANDOM GRAPHS AND THE ARCTIC SEA ICE | ||
| - | Organiser: M. Branicki (Mathematics, University of Edinburgh, UK) | + | |
| + | Organiser: M. Branicki (Mathematics, University of Edinburgh, UK)\\ | ||
| Organising committee : M. Branicki, D. Duncan (Heriot-Watt, UK), K. Law (Manchester, UK)\\ | Organising committee : M. Branicki, D. Duncan (Heriot-Watt, UK), K. Law (Manchester, UK)\\ | ||
| Location: International Centre for Mathematical Sciences, Edinburgh, UK (http://www.icms.org.uk)\\ | Location: International Centre for Mathematical Sciences, Edinburgh, UK (http://www.icms.org.uk)\\ | ||
| Line 37: | Line 38: | ||
| with random parameters, to (Lagrangian-type) data assimilation on the nodes time-dependent random | with random parameters, to (Lagrangian-type) data assimilation on the nodes time-dependent random | ||
| graphs. In the presence of model uncertainties a number of important problems need to be addressed: | graphs. In the presence of model uncertainties a number of important problems need to be addressed: | ||
| + | |||
| (i) Appropriate (stochastic) parameterisation the underlying integral operators. | (i) Appropriate (stochastic) parameterisation the underlying integral operators. | ||
| + | |||
| (ii) Choice of the necessary data-adapted discretisation for approximating time-dependent models for | (ii) Choice of the necessary data-adapted discretisation for approximating time-dependent models for | ||
| crack propagation and their capture. | crack propagation and their capture. | ||
| + | |||
| (iii) Aiding the procedures in (i)-(ii) via Bayesian data assimilation and appropriate Markov Chain | (iii) Aiding the procedures in (i)-(ii) via Bayesian data assimilation and appropriate Markov Chain | ||
| Monte Carlo (MCMC), and Multi Level Sequential Monte Carlo sampling (MLSMC). | Monte Carlo (MCMC), and Multi Level Sequential Monte Carlo sampling (MLSMC). | ||
| + | |||
| (iv) Derivation of criteria for stability, accuracy and quantification of uncertainty due to the parameterisation | (iv) Derivation of criteria for stability, accuracy and quantification of uncertainty due to the parameterisation | ||
| and/or the necessary discretisation of nonlocal problems. | and/or the necessary discretisation of nonlocal problems. | ||
news.txt · Last modified: 2018/05/10 17:15 by potthast
Page Tools
