Numerical PDEs/High-Order Discretization Modeling
We’re developing next-generation numerical methods to enable more accurate and efficient simulations of physical phenomena such as wave propagation, turbulent incompressible and high-speed reacting flows, shock hydrodynamics, fluid–structure interactions, and kinetic simulation. Our application-driven research is focused on designing, analyzing, and implementing new high-order finite difference, finite volume, and finite element discretization algorithms, with an emphasis on increased robustness, parallel scalability, and better utilization of modern computer architectures. View content related to Numerical PDEs/High-Order Discretization Modeling.
Podcast: Optimizing Math Libraries to Prepare Applications for Exascale Computing
CEED’s Impact on Exascale Computing Project Efforts Is Wide-Ranging
Center for Applied Scientific Computing (CASC) Newsletter, Volume 4
Sidney Fernbach Postdoctoral Fellowship Awarded to Will Pazner
LLNL has named Will Pazner as Computation’s third Sidney Fernbach Postdoctoral Fellow in the Computing Sciences.
Leading a Revolution in Design
Accelerating Simulation Software with Graphics Processing Units
Livermore scientists are redesigning simulation software to leverage the capabilities of next-generation exascale computing.
Center for Applied Scientific Computing
CASC conducts world-class scientific research and development on problems critical to national security.
High-Order Multi-Material Finite Element Simulation
High-order multi-material finite element simulation of cylindrical inertial confinement fusion (ICF) implosion.
High-Order Finite Volume Methods
High-resolution finite volume methods are being developed for solving problems in complex phase space geometries, motivated by kinetic models of fusion plasmas. Techniques being investigated include conservative, high-order methods based on the method-of-lines for hyperbolic problems, as well as coupling to implicit solvers for fields equations. Mapped multiblock grids enable alignment of the grid coordinate directions to accommodate strong anisotropy. The algorithms developed will be broadly applicable to systems of equations with conservative formulations in mapped geometries.
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