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news [2018/05/10 17:15] potthast |
news [2018/05/10 17:15] (current) potthast |
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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, | + | |
+ | Organiser: M. Branicki (Mathematics, | ||
Organising committee : M. Branicki, D. Duncan (Heriot-Watt, | Organising committee : M. Branicki, D. Duncan (Heriot-Watt, | ||
Location: International Centre for Mathematical Sciences, Edinburgh, UK (http:// | Location: International Centre for Mathematical Sciences, Edinburgh, UK (http:// | ||
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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: | ||
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(i) Appropriate (stochastic) parameterisation the underlying integral operators. | (i) Appropriate (stochastic) parameterisation the underlying integral operators. | ||
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(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. | ||
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(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). | ||
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(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. |