Publications

Siefert, Christopher S.; Hu, Jonathan J.; Fisher, Travis C.; Domino, Stefan P.

Abstract not provided.

Siefert, Christopher S.; Kelley, Brian K.

This is the user guide for the Matlab interface in MUELU.

Kramer, Richard M.; Siefert, Christopher S.; Voth, Thomas E.

Abstract not provided.

Siefert, Christopher S.; Tuminaro, Raymond S.; Becker, Gauthier B.; Sun, Huafei S.; Yin, Jichao Y.; Huang, Hao H.

Abstract not provided.

Niederhaus, John H.; Siefert, Christopher S.; Petney, Sharon P.

Abstract not provided.

Hu, Jonathan J.; Siefert, Christopher S.; Atzberger, Paul J.; Plunkett, Pat P.

Abstract not provided.

Siefert, Christopher S.; Kramer, Richard M.; Bochev, Pavel B.; Voth, Thomas E.

Abstract not provided.

Parallel Processing Letters

Lin, Paul L.; Bettencourt, Matthew T.; Domino, Stefan P.; Fisher, Travis C.; Hoemmen, Mark F.; Hu, Jonathan J.; Phipps, Eric T.; Prokopenko, Andrey V.; Rajamanickam, Sivasankaran R.; Siefert, Christopher S.; Kennon, Stephen

Trilinos is an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. While Trilinos was originally designed for scalable solutions of large problems, the fidelity needed by many simulations is significantly greater than what one could have envisioned two decades ago. When problem sizes exceed a billion elements even scalable applications and solver stacks require a complete revision. The second-generation Trilinos employs C++ templates in order to solve arbitrarily large problems. We present a case study of the integration of Trilinos with a low Mach fluids engineering application (SIERRA low Mach module/Nalu). Through the use of improved algorithms and better software engineering practices, we demonstrate good weak scaling for up to a nine billion element large eddy simulation (LES) problem on unstructured meshes with a 27 billion row matrix on 524,288 cores of an IBM Blue Gene/Q platform.

Perego, Mauro P.; Kim, Kyungjoo K.; Maxey, M.M.; Pan, Wei P.; Parks, Michael L.; Trask, N.T.; Siefert, Christopher S.

Abstract not provided.

Journal of Computational Physics

Plunkett, Pat; Hu, Jonathan J.; Siefert, Christopher S.; Atzberger, Paul J.

We develop stochastic mixed finite element methods for spatially adaptive simulations of fluid-structure interactions when subject to thermal fluctuations. To account for thermal fluctuations, we introduce a discrete fluctuation-dissipation balance condition to develop compatible stochastic driving fields for our discretization. We perform analysis that shows our condition is sufficient to ensure results consistent with statistical mechanics. We show the Gibbs-Boltzmann distribution is invariant under the stochastic dynamics of the semi-discretization. To generate efficiently the required stochastic driving fields, we develop a Gibbs sampler based on iterative methods and multigrid to generate fields with O(N) computational complexity. Our stochastic methods provide an alternative to uniform discretizations on periodic domains that rely on Fast Fourier Transforms. To demonstrate in practice our stochastic computational methods, we investigate within channel geometries having internal obstacles and no-slip walls how the mobility/diffusivity of particles depends on location. Our methods extend the applicability of fluctuating hydrodynamic approaches by allowing for spatially adaptive resolution of the mechanics and for domains that have complex geometries relevant in many applications. © 2014 Elsevier Inc.

Fisher, Travis C.; Siefert, Christopher S.; Hoemmen, Mark F.; Prokopenko, Andrey P.

Abstract not provided.

Hu, Jonathan J.; Prokopenko, Andrey V.; Wiesner, Tobias A.; Siefert, Christopher S.; Tuminaro, Raymond S.

This is the official user guide for the M UE L U multigrid library in Trilinos version 11.12. This guide provides an overview of M UE L U , its capabilities, and instructions for new users who want to start using M UE L U with a minimum of effort. Detailed information is given on how to drive M UE L U through its XML interface. Links to more advanced use cases are given. This guide gives information on how to achieve good parallel performance, as well as how to introduce new algorithms. Finally, readers will find a comprehensive listing of available M UE L U options. Any options not documented in this manual should be considered strictly experimental.

Siefert, Christopher S.; Bochev, Pavel B.; Kramer, Richard M.; Voth, Thomas E.

Abstract not provided.

Kramer, Richard M.; Siefert, Christopher S.; Voth, Thomas E.

Abstract not provided.

Siefert, Christopher S.; Bochev, Pavel B.; Kramer, Richard M.; Voth, Thomas E.; Cox, James C.

Surface effects are critical to the accurate simulation of electromagnetics (EM) as current tends to concentrate near material surfaces. Sandia EM applications, which include exploding bridge wires for detonator design, electromagnetic launch of flyer plates for material testing and gun design, lightning blast-through for weapon safety, electromagnetic armor, and magnetic flux compression generators, all require accurate resolution of surface effects. These applications operate in a large deformation regime, where body-fitted meshes are impractical and multimaterial elements are the only feasible option. State-of-the-art methods use various mixture models to approximate the multi-physics of these elements. The empirical nature of these models can significantly compromise the accuracy of the simulation in this very important surface region. We propose to substantially improve the predictive capability of electromagnetic simulations by removing the need for empirical mixture models at material surfaces. We do this by developing an eXtended Finite Element Method (XFEM) and an associated Conformal Decomposition Finite Element Method (CDFEM) which satisfy the physically required compatibility conditions at material interfaces. We demonstrate the effectiveness of these methods for diffusion and diffusion-like problems on node, edge and face elements in 2D and 3D. We also present preliminary work on h -hierarchical elements and remap algorithms.

Siefert, Christopher S.; Kramer, Richard M.

Abstract not provided.

Lin, Paul L.; Siefert, Christopher S.; Cyr, Eric C.; Bettencourt, Matthew T.; Domino, Stefan P.; Fisher, Travis C.; Hoemmen, Mark F.; Hu, Jonathan J.; Phipps, Eric T.; Prokopenko, Andrey V.; Rajamanickam, Sivasankaran R.

Abstract not provided.

Siefert, Christopher S.

Abstract not provided.

Lin, Paul L.; Rajamanickam, Sivasankaran R.; Siefert, Christopher S.; Bettencourt, Matthew T.; Cyr, Eric C.; Domino, Stefan P.; Fisher, Travis C.; Hoemmen, Mark F.; Hu, Jonathan J.; Phipps, Eric T.; Prokopenko, Andrey V.

Abstract not provided.

Robinson, Allen C.; Petney, Sharon P.; Drake, Richard R.; Weirs, Vincent G.; Adams, Brian M.; Vigil, Dena V.; Carpenter, John H.; Garasi, Christopher J.; Wong, Michael K.; Robbins, Joshua R.; Siefert, Christopher S.; Strack, Otto E.; Wills, Ann E.; Trucano, Timothy G.; Bochev, Pavel B.; Summers, Randall M.; Stewart, James R.; Ober, Curtis C.; Rider, William J.; Haill, Thomas A.; Lemke, Raymond W.; Cochrane, Kyle C.; Desjarlais, Michael P.; Love, Edward L.; Voth, Thomas E.; Mosso, Stewart J.; Niederhaus, John H.

Abstract not provided.

Tuminaro, Raymond S.; Hu, Jonathan J.; Prokopenko, Andrey V.; Siefert, Christopher S.; Tsuji, Paul H.; Boman, Erik G.; Cyr, Eric C.; Lin, Paul L.; Shadid, John N.

Abstract not provided.

Siefert, Christopher S.; Bochev, Pavel B.; Voth, Thomas E.; Kramer, Richard M.

Abstract not provided.

Siefert, Christopher S.; Kramer, Richard M.; Voth, Thomas E.; Bochev, Pavel B.

Abstract not provided.

Computer Methods in Applied Mechanics and Engineering

Kramer, Richard M.; Bochev, Pavel B.; Siefert, Christopher S.; Voth, Thomas E.

Abstract not provided.

Tuminaro, Raymond S.; Boman, Erik G.; Hu, Jonathan J.; Prokopenko, Andrey V.; Siefert, Christopher S.; Tsuji, Paul H.

Abstract not provided.