For more information about this meeting, contact Hope Shaffer, Chun Liu.
|Title:||Uncertainty quantification and geophysical hazard mapping|
|Seminar:||Computational and Applied Mathematics Colloquium|
|Speaker:||Elaine Spiller, Marquette University (Host: J Conway)|
|PDE models of granular flows are invaluable tools for developing probabilistic hazards maps for volcanic landslides, but they are far from perfect. First, any probabilistic hazard map is conditioned on assumptions about the aleatoric uncertainty -- how mother nature rolls the dice -- and is hence tied to the choice of probability distributions describing various scenarios (e.g. initial and/or boundary conditions). Thus new data, differing expert opinion, or emergent scenarios may suggest that the original assumptions were invalid and thus the hazard map made under those assumptions is not terribly useful. Epistemic uncertainty -- uncertainty due to a lack of model refinement -- arises through assumptions made in physical models, numerical approximation, and imperfect statistical models. In the context of geophysical hazard mapping, we propose a surrogate-based methodology which efficiently assesses the impact of various uncertainties enabling a quick yet methodical comparison of the effects of uncertainty and error on computer model output.|
Room Reservation Information
|Date:||12 / 01 / 2014|
|Time:||02:30pm - 03:30pm|