Abstract The statistically sound treatment of modelled uncertainties in simulations comes with significant additional computational costs. Since a deterministic model can already be arbitrarily complex, running statistics for general problems may soon become infeasible unless some kind of model reduction is involved.
Abstract Within the last couple of months, the COVID-19 epidemic has determined our public and private life with travel restrictions, lockdown, social distancing, working from home, hygiene rules etc. The daily news informed about reproduction rates and the numbers of current confirmed COVID-19 cases.
By analysing the Kronecker index of the difference-algebraic equations, that represent commonly and successfully used time stepping schemes for the Navier-Stokes equations, we show that those time-integration schemes factually remove strangeness. The …
POD is a common and popular approach for order reduction of nonlinear models. Recently, we have extended the standard POD formulation such that the temporal dimension can be reduced by the same principles. In this talk, we illustrate how the …