Topic: Computational Science

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

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

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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.

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

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

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

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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.

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

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

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

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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.

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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.

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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.

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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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