Publications

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We present an optimization-level domain decomposition (DD) preconditioner for the solution of advection dominated elliptic linear-quadratic optimal control problems, which arise in many science and engineering applications. The DD preconditioner is based on a decomposition of the optimality conditions for the elliptic linear-quadratic optimal control problem into smaller subdomain optimality conditions with Dirichlet boundary conditions for the states and the adjoints on the subdomain interfaces. These subdomain optimality conditions are coupled through Robin transmission conditions for the states and the adjoints. The parameters in the Robin transmission condition depend on the advection. This decomposition leads to a Schur complement system in which the unknowns are the state and adjoint variables on the subdomain interfaces. The Schur complement operator is the sum of subdomain Schur complement operators, the application of which is shown to correspond to the solution of subdomain optimal control problems, which are essentially smaller copies of the original optimal control problem. We show that, under suitable conditions, the application of the inverse of the subdomain Schur complement operators requires the solution of a subdomain elliptic linear-quadratic optimal control problem with Robin boundary conditions for the state. Numerical tests for problems with distributed and with boundary control show that the dependence of the preconditioners on mesh size and subdomain size is comparable to its counterpart applied to a single advection dominated equation. These tests also show that the preconditioners are insensitive to the size of the control regularization parameter.

This report describes key ideas underlying the application of Quantification of Margins and Uncertainties (QMU) to nuclear weapons stockpile lifecycle decisions at Sandia National Laboratories. While QMU is a broad process and methodology for generating critical technical information to be used in stockpile management, this paper emphasizes one component, which is information produced by computational modeling and simulation. In particular, we discuss the key principles of developing QMU information in the form of Best Estimate Plus Uncertainty, the need to separate aleatory and epistemic uncertainty in QMU, and the risk-informed decision making that is best suited for decisive application of QMU. The paper is written at a high level, but provides a systematic bibliography of useful papers for the interested reader to deepen their understanding of these ideas.

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Chemically Induced Surface Evolution with Level-Sets--ChISELS--is a parallel code for modeling 2D and 3D material depositions and etches at feature scales on patterned wafers at low pressures. Designed for efficient use on a variety of computer architectures ranging from single-processor workstations to advanced massively parallel computers running MPI, ChISELS is a platform on which to build and improve upon previous feature-scale modeling tools while taking advantage of the most recent advances in load balancing and scalable solution algorithms. Evolving interfaces are represented using the level-set method and the evolution equations time integrated using a Semi-Lagrangian approach [1]. The computational meshes used are quad-trees (2D) and oct-trees (3D), constructed such that grid refinement is localized to regions near the surface interfaces. As the interface evolves, the mesh is dynamically reconstructed as needed for the grid to remain fine only around the interface. For parallel computation, a domain decomposition scheme with dynamic load balancing is used to distribute the computational work across processors. A ballistic transport model is employed to solve for the fluxes incident on each of the surface elements. Surface chemistry is computed by either coupling to the CHEMKIN software [2] or by providing user defined subroutines. This report describes the theoretical underpinnings, methods, and practical use instruction of the ChISELS 1.0 computer code.

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Using molecular dynamics simulations, a constitutive model for the chemical aging of polymer networks was developed. This model incorporates the effects on the stress from the chemical crosslinks and the physical entanglements. The independent network hypothesis has been modified to account for the stress transfer between networks due to crosslinking and scission in strained states. This model was implemented in the finite element code Adagio and validated through comparison with experiment. Stress relaxation data was used to deduce crosslinking history and the resulting history was used to predict permanent set. The permanent set predictions agree quantitatively with experiment.

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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.

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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We report on the development of an accurate first-principles computational scheme for the charge transport characteristics of molecular monolayer junctions and its application to hexanedithiolate (C6DT) devices. Starting from the Gaussian basis set density-functional calculations of a junction model in the slab geometry and corresponding two bulk electrodes, we obtain the transmission function using the matrix Green's function method and analyze the nature of transmission channels via atomic projected density of states. Within the developed formalism, by treating isolated molecules with the supercell approach, we can investigate the current-voltage characteristics of single and parallel molecular wires in a consistent manner. For the case of single C6DT molecules stretched between Au(111) electrodes, we obtain reasonable quantitative agreement of computed conductance with a recent scanning tunneling microscope experiment result. Comparing the charge transport properties of C6DT single molecules and their monolayer counterparts in the stretched and tilted geometries, we find that the effect of intermolecular coupling and molecule tilting on the charge transport characteristics is negligible in these devices. We contrast this behavior to that of the π -conjugated biphenyldithiolate devices we have previously considered and discuss the relative importance of molecular cores and molecule-electrode contacts for the charge transport in those devices. © 2006 The American Physical Society.

We will discuss a parametric study of the solution of the Wigner-Poisson equations for resonant tunneling diodes. These structures exhibit self-sustaining oscillations in certain operating regimes. We will describe the engineering consequences of our study and how it is a significant advance from some previous work, which used much coarser grids. We use LOCA and other packages in the Trilinos framework from Sandia National Laboratory to enable efficient parallelization of the solution methods and to perform bifurcation analysis of this model. We report on the parallel efficiency and scalability of our implementation. © 2006 Elsevier Ltd. All rights reserved.

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Proliferation of degrees-of-freedom has plagued discontinuous Galerkin methodology from its inception over 30 years ago. This paper develops a new computational formulation that combines the advantages of discontinuous Galerkin methods with the data structure of their continuous Galerkin counterparts. The new method uses local, element-wise problems to project a continuous finite element space into a given discontinuous space, and then applies a discontinuous Galerkin formulation. The projection leads to parameterization of the discontinuous degrees-of-freedom by their continuous counterparts and has a variational multiscale interpretation. This significantly reduces the computational burden and, at the same time, little or no degradation of the solution occurs. In fact, the new method produces improved solutions compared with the traditional discontinuous Galerkin method in some situations. © 2005 Elsevier B.V. All rights reserved.

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This document provides verification test results for normal, lognormal, and uniform distributions that are used in Sandia's Latin Hypercube Sampling (LHS) software. The purpose of this testing is to verify that the sample values being generated in LHS are distributed according to the desired distribution types. The testing of distribution correctness is done by examining summary statistics, graphical comparisons using quantile-quantile plots, and format statistical tests such as the Chisquare test, the Kolmogorov-Smirnov test, and the Anderson-Darling test. The overall results from the testing indicate that the generation of normal, lognormal, and uniform distributions in LHS is acceptable.

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We propose two new multilinear operators for expressing the matrix compositions that are needed in the Tucker and PARAFAC (CANDECOMP) decompositions. The first operator, which we call the Tucker operator, is shorthand for performing an n-mode matrix multiplication for every mode of a given tensor and can be employed to concisely express the Tucker decomposition. The second operator, which we call the Kruskal operator, is shorthand for the sum of the outer-products of the columns of N matrices and allows a divorce from a matricized representation and a very concise expression of the PARAFAC decomposition. We explore the properties of the Tucker and Kruskal operators independently of the related decompositions. Additionally, we provide a review of the matrix and tensor operations that are frequently used in the context of tensor decompositions.

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We report the implementation of an iterative scheme for calculating the Optimized Effective Potential (OEP). Given an energy functional that depends explicitly on the Kohn-Sham wave functions, and therefore, implicitly on the local effective potential appearing in the Kohn-Sham equations, a gradient-based minimization is used to find the potential that minimizes the energy. Previous work has shown how to find the gradient of such an energy with respect to the effective potential in the zero-temperature limit. We discuss a density-matrix-based derivation of the gradient that generalizes the previous results to the finite temperature regime, and we describe important optimizations used in our implementation. We have applied our OEP approach to the Hartree-Fock energy expression to perform Exact Exchange (EXX) calculations. We report our EXX results for common semiconductors and ordered phases of hydrogen at zero and finite electronic temperatures. We also discuss issues involved in the implementation of forces within the OEP/EXX approach.

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We present a series of related robust optimization models for placing sensors in municipal water networks to detect contaminants that are maliciously or accidentally injected. We formulate sensor placement problems as mixed-integer programs, for which the objective coefficients are not known with certainty. We consider a restricted absolute robustness criteria that is motivated by natural restrictions on the uncertain data, and we define three robust optimization models that differ in how the coefficients in the objective vary. Under one set of assumptions there exists a sensor placement that is optimal for all admissible realizations of the coefficients. Under other assumptions, we can apply sorting to solve each worst-case realization efficiently, or we can apply duality to integrate the worst-case outcome and have one integer program. The most difficult case is where the objective parameters are bilinear, and we prove its complexity is NP-hard even under simplifying assumptions. We consider a relaxation that provides an approximation, giving an overall guarantee of near-optimality when used with branch-and-bound search. We present preliminary computational experiments that illustrate the computational complexity of solving these robust formulations on sensor placement applications.

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A new multi-scale, stabilized method for Q1/P0 finite element computations of Lagrangian shock hydrodynamics is presented. Instabilities (of hourglass type) are controlled by a stabilizing operator derived using the variational multi-scale analysis paradigm. The resulting stabilizing term takes the form of a pressure correction. With respect to currently implemented hourglass control approaches, the novelty of the method resides in its residual-based character. The stabilizing residual has a definite physical meaning, since it embeds a discrete form of the Clausius-Duhem inequality. Effectively, the proposed stabilization samples and acts to counter the production of entropy due to numerical instabilities. The proposed technique is applicable to materials with no shear strength, for which there exists a caloric equation of state. The stabilization operator is incorporated into a mid-point, predictor/multi-corrector time integration algorithm, which conserves mass, momentum and total energy. Encouraging numerical results in the context of compressible gas dynamics confirm the potential of the method.

Verdict is a collection of subroutines for evaluating the geometric qualities of triangles, quadrilaterals, tetrahedra, and hexahedra using a variety of metrics. A metric is a real number assigned to one of these shapes depending on its particular vertex coordinates. These metrics are used to evaluate the input to finite element, finite volume, boundary element, and other types of solvers that approximate the solution to partial differential equations defined over regions of space. The geometric qualities of these regions is usually strongly tied to the accuracy these solvers are able to obtain in their approximations. The subroutines are written in C++ and have a simple C interface. Each metric may be evaluated individually or in combination. When multiple metrics are evaluated at once, they share common calculations to lower the cost of the evaluation.

Germanium telluride undergoes rapid transition between polycrystalline and amorphous states under either optical or electrical excitation. While the crystalline phases are predicted to be semiconductors, polycrystalline germanium telluride always exhibits p -type metallic conductivity. We present a study of the electronic structure and formation energies of the vacancy and antisite defects in both known crystalline phases. We show that these intrinsic defects determine the nature of free-carrier transport in crystalline germanium telluride. Germanium vacancies require roughly one-third the energy of the other three defects to form, making this by far the most favorable intrinsic defect. While the tellurium antisite and vacancy induce gap states, the germanium counterparts do not. A simple counting argument, reinforced by integration over the density of states, predicts that the germanium vacancy leads to empty states at the top of the valence band, thus giving a complete explanation of the observed p -type metallic conduction.

Over 300 Asian life scientists were surveyed to provide insight into work with infectious agents. This report provides the reader with a more complete understanding of the current practices employed to study infectious agents by laboratories located in Asian countries--segmented by level of biotechnology sophistication. The respondents have a variety of research objectives and study over 60 different pathogens and toxins. Many of the respondents indicated that their work was hampered by lack of adequate resources and the difficulty of accessing critical resources. The survey results also demonstrate that there appears to be better awareness of laboratory biosafety issues compared to laboratory biosecurity. Perhaps not surprisingly, many of these researchers work with pathogens and toxins under less stringent laboratory biosafety and biosecurity conditions than would be typical for laboratories in the West.

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This report evaluates a newly-available, high-definition, video camera coupled with a zoom optical system for microscopic imaging of micro-electro-mechanical systems. We did this work to support configuration of three document-camera-like stations as part of an installation in a new Microsystems building at Sandia National Laboratories. The video display walls to be installed as part of these three presentation and training stations are of extraordinary resolution and quality. The new availability of a reasonably-priced, cinema-quality, high-definition video camera offers the prospect of filling these displays with full-motion imaging of Sandia's microscopic products at a quality substantially beyond the quality of typical video microscopes. Simple and robust operation of the microscope stations will allow the extraordinary-quality imaging to contribute to Sandia's day-to-day research and training operations. This report illustrates the disappointing image quality from a camera/lens system comprised of a Sony HDC-X310 high-definition video camera coupled to a Navitar Zoom 6000 lens. We determined that this Sony camera is capable of substantially more image quality than the Navitar optic can deliver. We identified an optical doubler lens from Navitar as the component of their optical system that accounts for a substantial part of the image quality problem. While work continues to incrementally improve performance of the Navitar system, we are also evaluating optical systems from other vendors to couple to this Sony camera.

This paper summarizes the results of a theoretical and experimental program at Sandia National Laboratories aimed at identifying and modeling key physical features of rocks and rock-like materials at the laboratory scale over a broad range of strain rates. The mathematical development of a constitutive model is discussed and model predictions versus experimental data are given for a suite of laboratory tests. Concurrent pore collapse and cracking at the microscale are seen as competitive micromechanisms that give rise to the well-known macroscale phenomenon of a transition from volumetric compaction to dilatation under quasistatic triaxial compression. For high-rate loading, this competition between pore collapse and microcracking also seems to account for recently identified differences in strain-rate sensitivity between uniaxial-strain 'plate slap' data compared to uniaxial-stress Kolsky bar data. A description is given of how this work supports ongoing efforts to develop a predictive capability in simulating deformation and failure of natural geological materials, including those that contain structural features such as joints and other spatial heterogeneities.

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This SAND report provides the technical progress through April 2005 of the Sandia-led project, "Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to Hierarchical Modeling," funded by the DOE Office of Science Genomics:GTL Program. Understanding, predicting, and perhaps manipulating carbon fixation in the oceans has long been a major focus of biological oceanography and has more recently been of interest to a broader audience of scientists and policy makers. It is clear that the oceanic sinks and sources of CO2 are important terms in the global environmental response to anthropogenic atmospheric inputs of CO2 and that oceanic microorganisms play a key role in this response. However, the relationship between this global phenomenon and the biochemical mechanisms of carbon fixation in these microorganisms is poorly understood. In this project, we will investigate the carbon sequestration behavior of Synechococcus Sp., an abundant marine cyanobacteria known to be important to environmental responses to carbon dioxide levels, through experimental and computational methods. This project is a combined experimental and computational effort with emphasis on developing and applying new computational tools and methods. Our experimental effort will provide the biology and data to drive the computational efforts and include significant investment in developing new experimental methods for uncovering protein partners, characterizing protein complexes, identifying new binding domains. We will also develop and apply new data measurement and statistical methods for analyzing microarray experiments. Computational tools will be essential to our efforts to discover and characterize the function of the molecular machines of Synechococcus. To this end, molecular simulation methods will be coupled with knowledge discovery from diverse biological data sets for high-throughput discovery and characterization of protein-protein complexes. In addition, we will develop a set of novel capabilities for inference of regulatory pathways in microbial genomes across multiple sources of information through the integration of computational and experimental technologies. These capabilities will be applied to Synechococcus regulatory pathways to characterize their interaction map and identify component proteins in these - 4 -pathways. We will also investigate methods for combining experimental and computational results with visualization and natural language tools to accelerate discovery of regulatory pathways. The ultimate goal of this effort is develop and apply new experimental and computational methods needed to generate a new level of understanding of how the Synechococcus genome affects carbon fixation at the global scale. Anticipated experimental and computational methods will provide ever-increasing insight about the individual elements and steps in the carbon fixation process, however relating an organism's genome to its cellular response in the presence of varying environments will require systems biology approaches. Thus a primary goal for this effort is to integrate the genomic data generated from experiments and lower level simulations with data from the existing body of literature into a whole cell model. We plan to accomplish this by developing and applying a set of tools for capturing the carbon fixation behavior of complex of Synechococcus at different levels of resolution. Finally, the explosion of data being produced by high-throughput experiments requires data analysis and models which are more computationally complex, more heterogeneous, and require coupling to ever increasing amounts of experimentally obtained data in varying formats. These challenges are unprecedented in high performance scientific computing and necessitate the development of a companion computational infrastructure to support this effort. More information about this project can be found at www.genomes-to-life.org Acknowledgment We want to gratefully acknowledge the contributions of: Grant Heffelfinger1*, Anthony Martino2, Brian Palenik6, Andrey Gorin3, Ying Xu10,3, Mark Daniel Rintoul1, Al Geist3, Matthew Ennis1, with Pratul Agrawal3, Hashim Al-Hashimi8, Andrea Belgrano12, Mike Brown1, Xin Chen9, Paul Crozier1, PguongAn Dam10, Jean-Loup Faulon2, Damian Gessler12, David Haaland1, Victor Havin4, C.F. Huang5, Tao Jiang9, Howland Jones1, David Jung3, Katherine Kang14, Michael Langston15, Shawn Martin1, Shawn Means1, Vijaya Natarajan4, Roy Nielson5, Frank Olken4, Victor Olman10, Ian Paulsen14, Steve Plimpton1, Andreas Reichsteiner5, Nagiza Samatova3, Arie Shoshani4, Michael Sinclair1, Alex Slepoy1, Shawn Stevens8, Charlie Strauss5, Zhengchang Su10, Ed Thomas1, Jerilyn Timlin1, WimVermaas13, Xiufeng Wan11, HongWei Wu10, Dong Xu11, Grover Yip8, Erik Zuiderweg8 *Author to whom correspondence should be addressed (gsheffe@sandia.gov) 1. Sandia National Laboratories, Albuquerque, NM 2. Sandia National Laboratories, Livermore, CA 3. Oak Ridge National Laboratory, Oak Ridge, TN 4. Lawrence Berkeley National Laboratory, Berkeley, CA 5. Los Alamos National Laboratory, Los Alamos, NM 6. University of California, San Diego 7. University of Illinois, Urbana/Champaign 8. University of Michigan, Ann Arbor 9. University of California, Riverside 10. University of Georgia, Athens 11. University of Missouri, Columbia 12. National Center for Genome Resources, Santa Fe, NM 13. Arizona State University 14. The Institute for Genomic Research 15. University of Tennessee 5 Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL8500.

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Given the logic density of modern FPGAs, it is feasible to use FPGAs for floating-point applications. However, it is important that any floating-point units that are used be highly optimized. This paper introduces an open source library of highly optimized floating-point units for Xilinx FPGAs. The units are fully IEEE compliant and achieve approximately 230 MHz operation frequency for double-precision add and multiply in a Xilinx Virtex-2-Pro FPGA (-7 speed grade). This speed is achieved with a 10 stage adder pipeline and a 12 stage multiplier pipeline. The area requirement is 571 slices for the adder and 905 slices for the multiplier.

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PyTrilinos provides python access to selected Trilinos packages: emerging from early stages, portability, completeness; parallelism; rapid prototyping; application development; unit testing; and numeric compatibility (migrating to NumPy). PyTrilinos complements and supplements the SciPy package.

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The Independent Network Model (INM) has proven to be a useful tool for understanding the development of permanent set in strained elastomers. Our previous work showed the applicability of the INM to our simulations of polymer systems crosslinking in strained states. This study looks at the INM applied to theoretical models incorporating entanglement effects, including Flory's constrained junction model and more recent tube models. The effect of entanglements has been treated as a separate network formed at gelation, with additional curing treated as traditional phantom contributions. Theoretical predictions are compared with large-scale molecular dynamics simulations.

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The global, synchronous nature of some collective operations implies that they will become the bottleneck when scaling to hundreds of thousands of nodes. One approach improves collective performance using a programmable network interface to directly implement collectives. While these implementations improve micro-benchmark performance, accelerating applications will require deeper understanding of application behaviour. We describe several characteristics of applications that impact collective communication performance. We analyse network resource usage data to guide the design of collective offload engines and their associated programming interfaces. In particular, we provide an analysis of the potential benefit of non-blocking collective communication operations for MPI. © 2006 Inderscience Enterprises Ltd.

This report presents a initial validation strategy for specific SNL pulsed power program applications of the ALEGRA-HEDP radiation-magnetohydrodynamics computer code. The strategy is written to be (1) broadened and deepened with future evolution of particular specifications given in this version; (2) broadly applicable to computational capabilities other than ALEGRA-HEDP directed at the same pulsed power applications. The content and applicability of the document are highly constrained by the R&D thrust of the SNL pulsed power program. This means that the strategy has significant gaps, indicative of the flexibility required to respond to an ongoing experimental program that is heavily engaged in phenomena discovery.

Constitutive models for chemically reacting networks are formulated based on a generalization of the independent network hypothesis. These models account for the coupling between chemical reaction and strain histories, and have been tested by comparison with microscopic molecular dynamics simulations. An essential feature of these models is the introduction of stress transfer functions that describe the interdependence between crosslinks formed and broken at various strains. Efforts are underway to implement these constitutive models into the finite element code Adagio. Preliminary results are shown that illustrate the effects of changing crosslinking and scission rates and history.

Chemical/Biological/Radiological (CBR) contamination events pose a considerable threat to our nation's infrastructure, especially in large internal facilities, external flows, and water distribution systems. Because physical security can only be enforced to a limited degree, deployment of early warning systems is being considered. However to achieve reliable and efficient functionality, several complex questions must be answered: (1) where should sensors be placed, (2) how can sparse sensor information be efficiently used to determine the location of the original intrusion, (3) what are the model and data uncertainties, (4) how should these uncertainties be handled, and (5) how can our algorithms and forward simulations be sufficiently improved to achieve real time performance? This report presents the results of a three year algorithmic and application development to support the identification, mitigation, and risk assessment of CBR contamination events. The main thrust of this investigation was to develop (1) computationally efficient algorithms for strategically placing sensors, (2) identification process of contamination events by using sparse observations, (3) characterization of uncertainty through developing accurate demands forecasts and through investigating uncertain simulation model parameters, (4) risk assessment capabilities, and (5) reduced order modeling methods. The development effort was focused on water distribution systems, large internal facilities, and outdoor areas.

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We demonstrate use of a Jacobian-Free Newton-Krylov solver to enable strong thermal coupling at the interface between a solid body and an external compressible fluid. Our method requires only information typically used in loose coupling based on successive substitution and is implemented within a multi-physics framework. We present results for two external flows over thermally conducting solid bodies obtained using both loose and strong coupling strategies. Performance of the two strategies is compared to elucidate both advantages and caveats associated with strong coupling.

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This paper presents automated expert modeling for automated student evaluation, or AEMASE (pronounced "amaze"). This technique grades students by comparing their actions to a model of expert behavior. The expert model is constructed with machine learning techniques, avoiding the costly and time-consuming process of manual knowledge elicitation and expert system implementation. A brief summary of after action review (AAR) and intelligent tutoring systems (ITS) provides background for a prototype AAR application with a learning expert model. A validation experiment confirms that the prototype accurately grades student behavior on a tactical aircraft maneuver application. Finally, several topics for further research are proposed. © Springer-Verlag Berlin Heidelberg 2006.

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Many problems in science and engineering require the solution of a long sequence of slowly changing linear systems. We propose and analyze two methods that significantly reduce the total number of matrix-vector products required to solve all systems. We consider the general case where both the matrix and right-hand side change, and we make no assumptions regarding the change in the right-hand sides. Furthermore, we consider general nonsingular matrices, and we do not assume that all matrices are pairwise close or that the sequence of matrices converges to a particular matrix. Our methods work well under these general assumptions, and hence form a significant advancement with respect to related work in this area. We can reduce the cost of solving subsequent systems in the sequence by recycling selected subspaces generated for previous systems. We consider two approaches that allow for the continuous improvement of the recycled subspace at low cost. We consider both Hermitian and non-Hermitian problems, and we analyze our algorithms both theoretically and numerically to illustrate the effects of subspace recycling. We also demonstrate the effectiveness of our algorithms for a range of applications from computational mechanics, materials science, and computational physics. © 2006 Society for Industrial and Applied Mathematics.

We discuss computing first derivatives for models based on elements, such as large-scale finite-element PDE discretizations, implemented in the C++ programming language. We use a hybrid technique of automatic differentiation (AD) and manual assembly, with local element-level derivatives computed via AD and manually summed into the global derivative. C++ templating and operator overloading work well for both forward- and reverse-mode derivative computations. We found that AD derivative computations compared favorably in time to finite differencing for a scalable finite-element discretization of a convection-diffusion problem in two dimensions. © Springer-Verlag Berlin Heidelberg 2006.

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Surfpack is a general-purpose software library of multidimensional function approximation methods for applications such as data visualization, data mining, sensitivity analysis, uncertainty quantification, and numerical optimization. Surfpack is primarily intended for use on sparse, irregularly-spaced, n-dimensional data sets where classical function approximation methods are not applicable. Surfpack is under development at Sandia National Laboratories, with a public release of Surfpack version 1.0 in August 2006. This paper provides an overview of Surfpack's function approximation methods along with some of its software design attributes. In addition, this paper provides some simple examples to illustrate the utility of Surfpack for data trend analysis, data visualization, and optimization. Copyright © 2006 by the American Institute of Aeronautics and Astronautics, Inc.

In evaluating new high-speed network interfaces, the usual metrics of latency and bandwidth are commonly measured and reported. There are numerous other message passing characteristics that can have a dramatic effect on application performance that should be analyzed when evaluating a new interconnect. One such metric is overhead, which dictates the networks ability to allow the application to perform non-message passing work while a transfer is taking place. A method for measuring overhead, and hence calculating application availability, is presented. Results for several next-generation network interfaces are also presented. © Springer-Verlag Berlin Heidelberg 2006.

This report summarizes the results of an effort to establish a framework for assigning and communicating technology readiness levels (TRLs) for the modeling and simulation (ModSim) capabilities at Sandia National Laboratories. This effort was undertaken as a special assignment for the Weapon Simulation and Computing (WSC) program office led by Art Hale, and lasted from January to September 2006. This report summarizes the results, conclusions, and recommendations, and is intended to help guide the program office in their decisions about the future direction of this work. The work was broken out into several distinct phases, starting with establishing the scope and definition of the assignment. These are characterized in a set of key assertions provided in the body of this report. Fundamentally, the assignment involved establishing an intellectual framework for TRL assignments to Sandia's modeling and simulation capabilities, including the development and testing of a process to conduct the assignments. To that end, we proposed a methodology for both assigning and understanding the TRLs, and outlined some of the restrictions that need to be placed on this process and the expected use of the result. One of the first assumptions we overturned was the notion of a ''static'' TRL--rather we concluded that problem context was essential in any TRL assignment, and that leads to dynamic results (i.e., a ModSim tool's readiness level depends on how it is used, and by whom). While we leveraged the classic TRL results from NASA, DoD, and Sandia's NW program, we came up with a substantially revised version of the TRL definitions, maintaining consistency with the classic level definitions and the Predictive Capability Maturity Model (PCMM) approach. In fact, we substantially leveraged the foundation the PCMM team provided, and augmented that as needed. Given the modeling and simulation TRL definitions and our proposed assignment methodology, we conducted four ''field trials'' to examine how this would work in practice. The results varied substantially, but did indicate that establishing the capability dependencies and making the TRL assignments was manageable and not particularly time consuming. The key differences arose in perceptions of how this information might be used, and what value it would have (opinions ranged from negative to positive value). The use cases and field trial results are included in this report. Taken together, the results suggest that we can make reasonably reliable TRL assignments, but that using those without the context of the information that led to those results (i.e., examining the measures suggested by the PCMM table, and extended for ModSim TRL purposes) produces an oversimplified result--that is, you cannot really boil things down to just a scalar value without losing critical information.

The physics of ballistic penetration mechanics is of great interest in penetrator and counter-measure design. The phenomenology associated with these events can be quite complex and a significant number of studies have been conducted ranging from purely experimental to 'engineering' models based on empirical and/or analytical descriptions to fully-coupled penetrator/target, thermo-mechanical numerical simulations. Until recently, however, there appears to be a paucity of numerical studies considering 'non-ideal' impacts [1]. The goal of this work is to demonstrate the SHISM algorithm implemented in the ALEGRA Multi-Material ALE (Arbitrary Lagrangian Eulerian) code [13]. The SHISM algorithm models the three-dimensional continuum solid mechanics response of the target and penetrator in a fully coupled manner. This capability allows for the study of 'non-ideal' impacts (e.g. pitch, yaw and/or obliquity of the target/penetrator pair). In this work predictions using the SHISM algorithm are compared to previously published experimental results for selected ideal and non-ideal impacts of metal penetrator-target pairs. These results show good agreement between predicted and measured maximum depth-of-penetration, DOP, for ogive-nose penetrators with striking velocities in the 0.5 to 1.5 km/s range. Ideal impact simulations demonstrate convergence in predicted DOP for the velocity range considered. A theory is advanced to explain disagreement between predicted and measured DOP at higher striking velocities. This theory postulates uncertainties in angle-of-attack for the observed discrepancies. It is noted that material models and associated parameters used here, were unmodified from those in the literature. Hence, no tuning of models was performed to match experimental data. Copyright © 2005 by ASME.

Kevlar materials make excellent body armor due to their fabric-like flexibility and ultra-high tensile strength. Carbon composites are made up from many layers of carbon AS-4 material impregnated with epoxy. Fiber orientation is bidirectional, orientated at 0° and 90°. They also have ultra-high tensile strength but can be made into relatively hard armor pieces. Once many layers are cut and assembled they can be ergonomicically shaped in a mold during the heated curing process. Kevlar and carbon composites can be used together to produce light and effective body armor. This paper will focus on computer analysis and laboratory testing of a Kevlar/carbon composite cross-section proposed for body armor development. The carbon composite is inserted between layers of Kevlar. The computer analysis was performed with a Lagrangian transversely Isotropic material model for both the Kevlar and Carbon Composite. The computer code employed is AUTODYN. Both the computer analysis and laboratory testing utilized different fragments sizes of hardened steel impacting on the armor cross-section. The steel fragments are right-circular cylinders. Laboratory testing was undertaken by firing various sizes of hardened steel fragments at square test coupons of Kevlar layers and heat cured carbon composites. The V50 velocity for the various fragment sizes was determined from the testing. This V50 data can be used to compare the body armor design with other previously designed armor systems. AUTODYN [1] computer simulations of the fragment impacts were compared to the experimental results and used to evaluate and guide the overall design process. This paper will include the detailed transversely isotropic computer simulations of the Kevlar/carbon composite cross-section as well as the experimental results and a comparison between the two. Conclusions will be drawn about the design process and the validity of current computer modeling methods for Kevlar and carbon composites. Copyright © 2005 by ASME.

Processing-in-Memory (PIM) technology encompasses a range of research leveraging a tight coupling of memory and processing. The most unique features of the technology are extremely wide paths to memory, extremely low memory latency, and wide functional units. Many PIM researchers are also exploring extremely fine-grained multi-threading capabilities. This paper explores a mechanism for leveraging these features of PIM technology to enhance commodity architectures in a seemingly mundane way: accelerating MPI. Modern network interfaces leverage simple processors to offload portions of the MPI semantics, particularly the management of posted receive and unexpected message queues. Without adding cost or increasing clock frequency, using PIMs in the network interface can enhance performance. The results are a significant decrease in latency and increase in small message bandwidth, particularly when long queues are present.

The critical Rayleigh number Racr of the Hopf bifurcation that signals the limit of steady flows in a differentially heated 8:1:1 cavity is computed. The two-dimensional analog of this problem was the subject of a comprehensive set of benchmark calculations that included the estimation of Racr [1]. In this work we begin to answer the question of whether the 2D results carry over into 3D models. For the case of the 2D model being extruded for a depth of 1, and no-slip/no-penetration and adiabatic boundary conditions placed at these walls, the steady flow and destabilizing eigenvectors qualitatively match those from the 2D model. A mesh resolution study extending to a 20-million unknown model shows that the presence of these walls delays the first critical Rayleigh number from 3.06 × 105 to 5.13 × 105. © 2005 Elsevier Ltd.

This paper is about making reversible logic a reality for supercomputing. Reversible logic offers a way to exceed certain basic limits on the performance of computers, yet a powerful case will have to be made to justify its substantial development expense. This paper explores the limits of current, irreversible logic for supercomputers, thus forming a threshold above which reversible logic is the only solution. Problems above this threshold are discussed, with the science and mitigation of global warming being discussed in detail. To further develop the idea of using reversible logic in supercomputing, a design for a 1 Zettaflops supercomputer as required for addressing global climate warming is presented. However, to create such a design requires deviations from the mainstream of both the software for climate simulation and research directions of reversible logic. These deviations provide direction on how to make reversible logic practical. Copyright 2005 ACM.

Latency and bandwidth are usually considered to be the dominant factor in parallel application performance; however, recent studies have indicated that support for independent progress in MPI can also have a significant impact on application performance. This paper leverages the Cplant system at Sandia National Labs to compare a faster, vendor provided MPI library without independent progress to an internally developed MPI library that sacrifices some performance to provide independent progress. The results are surprising. Although some applications see significant negative impacts from the reduced network performance, others are more sensitive to the presence of independent progress. © 2005 IEEE.

Advances in FPGA technology have led to dramatic improvements in double precision floating-point performance. Modern FPGAs boast several GigaFLOPs of raw computing power. Unfortunately, this computing power is distributed across 30 floating-point units with over 10 cycles of latency each. The user must find two orders of magnitude more parallelism than is typically exploited in a single microprocessor; thus, it is not clear that the computational power of FPGAs can be exploited across a wide range of algorithms. This paper explores three implementation alternatives for the Fast Fourier Transform (FFT) on FPGAs. The algorithms are compared in terms of sustained performance and memory requirements for various FFT sizes and FPGA sizes. The results indicate that FPGAs are competitive with microprocessors in terms of performance and that the "correct" FFT implementation varies based on the size of the transform and the size of the FPGA. © 2005 IEEE.

This paper provides an overview of several approaches to formulating and solving optimization under uncertainty (OUU) engineering design problems. In addition, the topic of high-performance computing and OUU is addressed, with a discussion of the coarse- and fine-grained parallel computing opportunities in the various OUU problem formulations. The OUU approaches covered here are: sampling-based OUU, surrogate model-based OUU, analytic reliability-based OUU (also known as reliability-based design optimization), polynomial chaos-based OUU, and stochastic perturbation-based OUU.

There have been many papers proposing the use of logarithmic numbers (LNS) as an alternative to floating point because of simpler multiplication, division and exponentiation computations [1,4-9,13]. However, this advantage comes at the cost of complicated, inexact addition and subtraction, as well as the need to convert between the formats. In this work, we created a parameterized LNS library of computational units and compared them to an existing floating point library. Specifically, we considered multiplication, division, addition, subtraction, and format conversion to determine when one format should be used over the other and when it is advantageous to change formats during a calculation. © 2005 IEEE.

We investigate the accuracy of chemical transport in network models for small geometric configurations. Network model have successfully simulated the general operations of large water distribution systems. However, some of the simplifying assumptions associated with the implementation may cause inaccuracies if chemicals need to be carefully characterized at a high level of detail. In particular, we are interested in precise transport behavior so that inversion and control problems can be applied to water distribution networks. As an initial phase, Navier Stokes combined with a convection-diffusion formulation was used to characterize the mixing behavior at a pipe intersection in two dimensions. Our numerical models predict only on the order of 12-14 % of the chemical to be mixed with the other inlet pipe. Laboratory results show similar behavior and suggest that even if our numerical model is able to resolve turbulence, it may not improve the mixing behavior. This conclusion may not be appropriate however for other sets of operating conditions, and therefore we have started to develop a 3D implementation. Preliminary results for duct geometry are presented. © copyright ASCE 2005.

We performed molecular dynamics simulations of beta-amyloid (A{beta}) protein and A{beta} fragment(31-42) in bulk water and near hydrated lipids to study the mechanism of neurotoxicity associated with the aggregation of the protein. We constructed full atomistic models using Cerius2 and ran simulations using LAMMPS. MD simulations with different conformations and positions of the protein fragment were performed. Thermodynamic properties were compared with previous literature and the results were analyzed. Longer simulations and data analyses based on the free energy profiles along the distance between the protein and the interface are ongoing.

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