The MFEM software library provides high-order mathematical algorithms for large-scale scientific simulations. An October workshop brought together MFEM’s global user and developer community for the first time.
An LLNL mathematician and collaborators have developed a machine learning–based technique capable of automatically deriving a mathematical model for the motion of binary black holes from raw gravitational wave data.
In a project with U.S. Steel, LLNL computational physicists built models of the hot-rolling process to run on LLNL’s HPC platforms. The models track the steel from reheat-furnace dropout through the subsequent steps of rolling, cooling on the runout table, coiling and, finally, post-rolling cooling.