PROJECTS
PDES
PDES focuses on models that can accurately and effectively simulate California’s large-scale electric grid.
Legacy
Phase-Field Modeling
Livermore researchers have developed an algorithm for the numerical solution of a phase-field model of microstructure evolution in polycrystalline materials. The system of equations includes a…
Legacy
First-Principles Molecular Dynamics
LLNL researchers are developing a truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems of sizes that were…
NEWS
DOE funds 13 new HPC4EI projects
The Department of Energy announced awards of $3.7 million for 13 new High Performance Computing for Energy Innovation (HPC4EI) projects, including a collaboration involving LLNL targeted at improving CO2 conversion.
New heavy vehicle design increases fuel efficiency, cuts carbon emissions
LLNL engineers have demonstrated that aerodynamically integrated vehicle shapes decrease body-axis drag in a crosswind, creating large negative front pressures that effectively “pull” the vehicle forward against the wind, much like a sailboat.
Virtual LLNL-UC Merced Data Science Challenge tackles asteroid detection though machine learning
Meeting virtually three times per week, 22 UC Merced students engaged with LLNL mentors and peers to address a real-world challenge problem, using machine learning to identify potentially hazardous asteroids that could pose an existential threat to humanity.