3 research outputs found
Cellular Probabilistic Automata - A Novel Method for Uncertainty Propagation
We propose a novel density based numerical method for uncertainty propagation
under certain partial differential equation dynamics. The main idea is to
translate them into objects that we call cellular probabilistic automata and to
evolve the latter. The translation is achieved by state discretization as in
set oriented numerics and the use of the locality concept from cellular
automata theory. We develop the method at the example of initial value
uncertainties under deterministic dynamics and prove a consistency result. As
an application we discuss arsenate transportation and adsorption in drinking
water pipes and compare our results to Monte Carlo computations
Kontextsensitive Modellhierarchien für Quantifizierung der höherdimensionalen Unsicherheit
We formulate four novel context-aware algorithms based on model hierarchies aimed to enable an efficient quantification of uncertainty in complex, computationally expensive problems, such as fluid-structure interaction and plasma microinstability simulations. Our results show that our algorithms are more efficient than standard approaches and that they are able to cope with the challenges of quantifying uncertainty in higher-dimensional, complex problems.Wir formulieren vier kontextsensitive Algorithmen auf der Grundlage von Modellhierarchien um eine effiziente Quantifizierung der Unsicherheit bei komplexen, rechenintensiven Problemen zu ermöglichen, wie Fluid-Struktur-Wechselwirkungs- und Plasma-Mikroinstabilitätssimulationen. Unsere Ergebnisse zeigen, dass unsere Algorithmen effizienter als Standardansätze sind und die Herausforderungen der Quantifizierung der Unsicherheit in höherdimensionalen, komplexen Problemen bewältigen können