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Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

Laity, George R.; Robinson, Allen C.; Cuneo, M.E.; Alam, Mary K.; Beckwith, Kristian B.; Bennett, Nichelle L.; Bettencourt, Matthew T.; Bond, Stephen D.; Cochrane, Kyle C.; Criscenti, Louise C.; Cyr, Eric C.; De Zetter, Karen J.; Drake, Richard R.; Evstatiev, Evstati G.; Fierro, Andrew S.; Gardiner, Thomas A.; Glines, Forrest W.; Goeke, Ronald S.; Hamlin, Nathaniel D.; Hooper, Russell H.; Koski, Jason K.; Lane, James M.; Larson, Steven R.; Leung, Kevin L.; McGregor, Duncan A.; Miller, Philip R.; Miller, Sean M.; Ossareh, Susan J.; Phillips, Edward G.; Simpson, Sean S.; Sirajuddin, David S.; Smith, Thomas M.; Swan, Matthew S.; Thompson, Aidan P.; Tranchida, Julien G.; Bortz-Johnson, Asa J.; Welch, Dale R.; Russell, Alex M.; Watson, Eric D.; Rose, David V.; McBride, Ryan D.

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

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Probing off-Hugoniot states in Ta, Cu, and Al to 1000 GPa compression with magnetically driven liner implosions

Journal of Applied Physics

Lemke, Raymond W.; Dolan, Daniel H.; Dalton, D.G.; Brown, Justin L.; Tomlinson, K.; Robertson, G.R.; Knudson, Marcus D.; Harding, Eric H.; Mattsson, A.E.; Carpenter, John H.; Drake, Richard R.; Cochrane, Kyle C.; Blue, B.E.; Robinson, Allen C.; Mattsson, Thomas M.

We report on a new technique for obtaining off-Hugoniot pressure vs. density data for solid metals compressed to extreme pressure by a magnetically driven liner implosion on the Z-machine (Z) at Sandia National Laboratories. In our experiments, the liner comprises inner and outer metal tubes. The inner tube is composed of a sample material (e.g., Ta and Cu) whose compressed state is to be inferred. The outer tube is composed of Al and serves as the current carrying cathode. Another aluminum liner at much larger radius serves as the anode. A shaped current pulse quasi-isentropically compresses the sample as it implodes. The iterative method used to infer pressure vs. density requires two velocity measurements. Photonic Doppler velocimetry probes measure the implosion velocity of the free (inner) surface of the sample material and the explosion velocity of the anode free (outer) surface. These two velocities are used in conjunction with magnetohydrodynamic simulation and mathematical optimization to obtain the current driving the liner implosion, and to infer pressure and density in the sample through maximum compression. This new equation of state calibration technique is illustrated using a simulated experiment with a Cu sample. Monte Carlo uncertainty quantification of synthetic data establishes convergence criteria for experiments. Results are presented from experiments with Al/Ta, Al/Cu, and Al liners. Symmetric liner implosion with quasi-isentropic compression to peak pressure ∼1000 GPa is achieved in all cases. These experiments exhibit unexpectedly softer behavior above 200 GPa, which we conjecture is related to differences in the actual and modeled properties of aluminum.

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Parallel scaling analysis for explicit solid dynamics in ALEGRA

Niederhaus, John H.; Drake, Richard R.; Luchini, Christopher B.

Weak scaling studies were performed for the explicit solid dynamics component of the ALEGRA code on two Cray supercomputer platforms during the period 2012-2015, involving a production-oriented hypervelocity impact problem. Results from these studies are presented, with analysis of the performance, scaling, and throughput of the code on these machines. The analysis demonstrates logarithmic scaling of the average CPU time per cycle up to core counts on the order of 10,000. At higher core counts, variable performance is observed, with significant upward excursions in compute time from the logarithmic trend. However, for core counts less than 10,000, the results show a 3 × improvement in simulation throughput, and a 2 × improvement in logarithmic scaling. This improvement is linked to improved memory performance on the Cray platforms, and to significant improvements made over this period to the data layout used by ALEGRA.

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ALEGRA Update: Modernization and Resilience Progress

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.

Fundamental issues in the representation and propagation of uncertain equation of state information in shock hydrodynamics

Computers and Fluids

Robinson, Allen C.; Berry, Robert D.; Carpenter, John H.; Debusschere, Bert D.; Drake, Richard R.; Mattsson, A.E.; Rider, William J.

Uncertainty quantification (UQ) deals with providing reasonable estimates of the uncertainties associated with an engineering model and propagating them to final engineering quantities of interest. We present a conceptual UQ framework for the case of shock hydrodynamics with Euler's equations where the uncertainties are assumed to lie principally in the equation of state (EOS). In this paper we consider experimental data as providing both data and an estimate of data uncertainty. We propose a specific Bayesian inference approach for characterizing EOS uncertainty in thermodynamic phase space. We show how this approach provides a natural and efficient methodology for transferring data uncertainty to engineering outputs through an EOS representation that understands and deals consistently with parameter correlations as sensed in the data.Historically, complex multiphase EOSs have been built utilizing tables as the delivery mechanism in order to amortize the cost of creation of the tables over many subsequent continuum scale runs. Once UQ enters into the picture, however, the proper operational paradigm for multiphase tables become much less clear. Using a simple single-phase Mie-Grüneisen model we experiment with several approaches and demonstrate how uncertainty can be represented. We also show how the quality of the tabular representation is of key importance. As a first step, we demonstrate a particular tabular approach for the Mie-Grüneisen model which when extended to multiphase tables should have value for designing a UQ-enabled shock hydrodynamic modeling approach that is not only theoretically sound but also robust, useful, and acceptable to the modeling community. We also propose an approach to separate data uncertainty from modeling error in the EOS. © 2012 Elsevier Ltd.

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A smoothed two-and three-dimensional interface reconstruction method

Computing and Visualization in Science

Mosso, Stewart; Garasi, Christopher J.; Drake, Richard R.

The Patterned Interface Reconstruction algorithm reduces the discontinuity between material interfaces in neighboring computational elements. This smoothing improves the accuracy of the reconstruction for smooth bodies. The method can be used in two- and three-dimensional Cartesian and unstructured meshes. Planar interfaces will be returned for planar volume fraction distributions. The algorithm is second-order accurate for smooth volume fraction distributions. © 2008 Springer-Verlag.

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Pamgen, a library for parallel generation of simple finite element meshes

Hensinger, David M.; Drake, Richard R.; Foucar, James G.

Generating finite-element meshes is a serious bottleneck for large parallel simulations. When mesh generation is limited to serial machines and element counts approach a billion, this bottleneck becomes a roadblock. Pamgen is a parallel mesh generation library that allows on-the-fly scalable generation of hexahedral and quadrilateral finite element meshes for several simple geometries. It has been used to generate more that 1.1 billion elements on 17,576 processors. Pamgen generates an unstructured finite element mesh on each processor at the start of a simulation. The mesh is specified by commands passed to the library as a 'C'-programming language string. The resulting mesh geometry, topology, and communication information can then be queried through an API. pamgen allows specification of boundary condition application regions using sidesets (element faces) and nodesets (collections of nodes). It supports several simple geometry types. It has multiple alternatives for mesh grading. It has several alternatives for the initial domain decomposition. Pamgen makes it easy to change details of the finite element mesh and is very useful for performance studies and scoping calculations.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) software quality plan part 2 mappings for the ASC software quality engineering practices, version 2.0

Boucheron, Edward A.; Sturtevant, Judy E.; Drake, Richard R.; Edwards, Harold C.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Minana, Molly A.; Pavlakos, Constantine P.; Schofield, Joseph R.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR001.3.2 and CPR001.3.6 and to a Department of Energy document, ''ASCI Software Quality Engineering: Goals, Principles, and Guidelines''. This document also identifies ASC management and software project teams' responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) software quality plan. Part 1: ASC software quality engineering practices, Version 2.0

Drake, Richard R.; Sturtevant, Judy E.; Boucheron, Edward A.; Edwards, Harold C.; Minana, Molly A.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Pavlakos, Constantine P.; Schofield, Joseph R.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR 1.3.2 and 1.3.6 and to a Department of Energy document, ASCI Software Quality Engineering: Goals, Principles, and Guidelines. This document also identifies ASC management and software project teams responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals.

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ALEGRA : version 4.6

Wong, Michael K.; Brunner, Thomas A.; Garasi, Christopher J.; Haill, Thomas A.; Mehlhorn, Thomas A.; Drake, Richard R.; Hensinger, David M.; Robbins, Joshua R.; Robinson, Allen C.; Summers, Randall M.; Voth, Thomas E.

ALEGRA is an arbitrary Lagrangian-Eulerian multi-material finite element code used for modeling solid dynamics problems involving large distortion and shock propagation. This document describes the basic user input language and instructions for using the software.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan. Part 2, Mappings for the ASC software quality engineering practices. Version 1.0

Boucheron, Edward A.; Schofield, Joseph R.; Drake, Richard R.; Minana, Molly A.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Pavlakos, Constantine P.; Sturtevant, Judy E.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR 1.3.2 and 1.3.6 and to a Department of Energy document, 'ASCI Software Quality Engineering: Goals, Principles, and Guidelines'. This document also identifies ASC management and software project teams responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) software quality plan. Part 1 : ASC software quality engineering practices version 1.0

Boucheron, Edward A.; Schofield, Joseph R.; Drake, Richard R.; Edwards, Harold C.; Minana, Molly A.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Pavlakos, Constantine P.; Sturtevant, Judy E.

The purpose of the Sandia National Laboratories (SNL) Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. Quality is defined in DOE/AL Quality Criteria (QC-1) as conformance to customer requirements and expectations. This quality plan defines the ASC program software quality practices and provides mappings of these practices to the SNL Corporate Process Requirements (CPR 1.3.2 and CPR 1.3.6) and the Department of Energy (DOE) document, ASCI Software Quality Engineering: Goals, Principles, and Guidelines (GP&G). This quality plan identifies ASC management and software project teams' responsibilities for cost-effective software engineering quality practices. The SNL ASC Software Quality Plan establishes the signatories commitment to improving software products by applying cost-effective software engineering quality practices. This document explains the project teams opportunities for tailoring and implementing the practices; enumerates the practices that compose the development of SNL ASC's software products; and includes a sample assessment checklist that was developed based upon the practices in this document.

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An Exploration in Implementing Fault Tolerance in Scientific Simulation Application Software

Drake, Richard R.; Drake, Richard R.; Summers, Randall M.

The ability for scientific simulation software to detect and recover from errors and failures of supporting hardware and software layers is becoming more important due to the pressure to shift from large, specialized multi-million dollar ASCI computing platforms to smaller, less expensive interconnected machines consisting of off-the-shelf hardware. As evidenced by the CPlant{trademark} experiences, fault tolerance can be necessary even on such a homogeneous system and may also prove useful in the next generation of ASCI platforms. This report describes a research effort intended to study, implement, and test the feasibility of various fault tolerance mechanisms controlled at the simulation code level. Errors and failures would be detected by underlying software layers, communicated to the application through a convenient interface, and then handled by the simulation code itself. Targeted faults included corrupt communication messages, processor node dropouts, and unacceptable slowdown of service from processing nodes. Recovery techniques such as re-sending communication messages and dynamic reallocation of failing processor nodes were considered. However, most fault tolerance mechanisms rely on underlying software layers which were discovered to be lacking to such a degree that mechanisms at the application level could not be implemented. This research effort has been postponed and shifted to these supporting layers.

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ALEGRA: User Input and Physics Descriptions Version 4.2

Boucheron, Edward A.; Haill, Thomas A.; Peery, James S.; Petney, Sharon P.; Robbins, Joshua R.; Robinson, Allen C.; Summers, Randall M.; Voth, Thomas E.; Wong, Michael K.; Brown, Kevin H.; Budge, Kent G.; Burns, Shawn P.; Carroll, Daniel E.; Carroll, Susan K.; Christon, Mark A.; Drake, Richard R.; Garasi, Christopher J.

ALEGRA is an arbitrary Lagrangian-Eulerian finite element code that emphasizes large distortion and shock propagation. This document describes the user input language for the code.

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45 Results
45 Results