Models can easily become so complex that they are impenetrable, unexaminable, and virtually unalterable. — Donella Meadows (1980) "The unavoidable a priori" in: Randers J. ed., Elements of the system dynamics method. p. 27. In our last post, we introduced the unsteady non-linear advection-diffusion-reaction equation in strong form, $$ \mathcal{…
No good ending can be expected in the absence of the right beginning. — I Ching Before we can make our predictions better, we need to be able to make predictions in the first place. For physical systems, this means we need a mathematical model of how the system works. Once…
Over the next few weeks, Cory Frontin and I are releasing a series of posts giving an overview of the mathematics that underpin output based adaption: Introducing the Strong and Weak Forms Galerkin Methods Adjoint Fundamentals Error Estimation Metric Based Meshing Putting it All Together: MOESS The idea is to…
Oh, short answer, "yes" with an "if." Long answer, "no" with a "but." -- Reverend Lovejoy, "Hurricane Neddy" When I explain my research to friends and family, they often ask me whether output adaptivity is some kind of machine learning.…
