PDES focuses on models that can accurately and effectively simulate California’s large-scale electric grid.

# Topic: *Computational Science*

Based on a discretization and time-stepping algorithm, these equations include a local order parameter, a quaternion representation of local orientation, and species composition.

This scalable first-principles MD algorithm with O(N) complexity and controllable accuracy is capable of simulating systems that were previously impossible with such accuracy.

High-resolution finite volume methods are being developed for solving problems in complex phase space geometries, motivated by kinetic models of fusion plasmas.

LLNL’s version of Qbox, a first-principles molecular dynamics code, will let researchers accurately calculate bigger systems on supercomputers.

The Earth System Grid Federation is a web-based tool set that powers most global climate change research.

Researchers are testing and enhancing a neutral particle transport code and its algorithm to ensure that they successfully scale to larger and more complex computing systems.

Testbed Environment for Space Situational Awareness software helps to track satellites and space debris and prevent collisions.

Livermore researchers are enhancing HARVEY, an open-source parallel fluid dynamics application designed to model blood flow in patient-specific geometries.

These methods for solving hyperbolic wave propagation problems allow for complex geometries, realistic boundary and interface conditions, and arbitrary heterogeneous material properties.

A new algorithm for use with first-principles molecular dynamics codes enables the number of atoms simulated to be proportional to the number of processors available.

This genome sequencing technology helps accelerate the comparison of genetic fragments with reference genomes and improve the accuracy of the results as compared to previous technologies.

BLAST is a high-order finite element hydrodynamics research code that improves the accuracy of simulations and provides a path to extreme parallel computing and exascale architectures.

Brian Gunney became fascinated with the field of computational fluid dynamics because he thought it could be critical in solving many problems he considered unsolvable.

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