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Lab Interactions & Education Program

Lab Interactions & Education Program. Lab Interactions that worked. Large eddy simulation of a buoyant helium plume using an unstructured hex grid with local refinement near the plume edge equivalent to 512 points azimuthally Conserved scalar is used to transport the He mixture fraction.

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Lab Interactions & Education Program

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  1. Lab Interactions & Education Program

  2. Lab Interactions that worked

  3. Large eddy simulation of a buoyant helium plume using an unstructured hex grid with local refinement near the plume edge equivalent to 512 points azimuthally Conserved scalar is used to transport the He mixture fraction

  4. Workshops - Summer 2008

  5. Labs participation in 2008 Summer workshops CTR Summer Program - July 7-August 4 • S. Domino, J. Hewson, D. Lignell (SNL) • V&V of Approximate Projection Methods • Combustion and Soot Formation UQ Workshop - July 25-26 • M. Eldred (SNL) • J. Red-Horse (SNL) • T. Wallstrom (LANL) • C. Tong (LLNL)

  6. Educational aspects • Degree granting Institute for Computational and Mathematical Engineering (ICME) • ICME impact on education and research • Interdisciplinary • Outstanding math students exposed to physics and engineering, engaged in Uncertainty Quantification • appropriate talent for out of box thinking, emphasis on programming and covering statistics, discrete math and PDEs

  7. New Courses • Hypersonics • The fundamental principals and equations related to hypersonic flight and high temperature gas dynamics, including chemical and thermal equilibrium and non-equilibrium, statistical thermodynamics, kinetic theory, transport phenomena, radiation, surface heating and scramjet engines. • Uncertainty Quantification and Probabilistic Methods. • Lectures will cover mathematical and statistical foundations of random variables and processes for uncertainty modeling. Introduction of the state-of-the-art uncertainty propagation schemes, such as advanced sampling techniques and stochastic Galerkin methods, is the major focus of this course.

  8. Pervasive Parallelism Lab • Goal: Parallel Programming environment for 2010 • Parallelism for the masses: make parallel programming accessible to the average programmer • Parallel algorithms, development environments, and runtime systems that scale to 1000s of hardware threads • Concurrent software a core component of undergraduate CS education • PPL is a combination of • Leading Stanford researchers in applications, languages, systems software and computer architecture • Leading companies in computer systems and software • Compelling vision for creating and managing pervasive parallelism

  9. Opportunities for Lab Scientists at Stanford • Advanced Graduate Classes Teaching • P. Miller (LLNL): Advanced Large Scale Programming • PhD Dissertation Reading Committees • Students will benefit from areas of long-standing expertise and real-world applications • Compete for sponsored joint research. e.g. SciDAC, AirForce

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