Publications

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Traditional grid models for large-scale simulations assume linear and quasi-static behavior allowing very simple models of the systems. In this paper, a scalable electric circuit simulation capability is presented that can capture a significantly higher degree of fidelity including transient dynamic behavior of the grid as well as allowing scaling to a regional and national level grid. A test case presented uses simple models, e.g. generators, transformers, transmission lines, and loads, but with the scalability feature it can be extended to include more advanced non-linear detailed models. The use of this scalable electric circuit simulator will provide the ability to conduct large-scale transient stability analysis as well as grid level planning as the grid evolves with greater degrees of penetration of renewables, power electronics, storage, distributed generation, and micro-grids. © 2011 AACC American Automatic Control Council.

Automatic feature creation is a powerful tool for identifying and reaching goals in the natural world. This paper describes in detail a biologically-inspired method of feature creation that can be applied to sensory information of any modality. The algorithm is incremental and on-line; it enforces sparseness in the features it creates; and it can form features from other features, making a hierarchical feature set. Here it demonstrates the creation of both visual and auditory features. © 2011 The authors and IOS Press. All rights reserved.

Projection of molten salt performance in thermal storage systems, whether based on sensible heat or latent heat, is highly dependent on the predictions of thermophysical properties. In the absence of experimental data, heat transfer properties rely on theoretical estimations. This work focuses on thermodynamic predictions of mixture properties for molten salts supportive of ongoing advanced heat transfer fluid research at the Sandia National Laboratories. Thus far, the candidate mixtures studied experimentally and theoretically at Sandia are made up of either ternary or quaternary nitrate and mixed nitrate/nitrite salts of various compositions. Experimentally, mixture properties such as melting points and heat of fusion are obtained by thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC). Classical thermodynamics are applied to resolve phase transitions of molten salt mixtures as well as mixture properties. The Wilson equation, developed originally for organic mixtures, is used to study phase boundaries of molten salts in this work. Molecular thermodynamics (MD), where atomistic simulation forms the basis for constructing the equation of state, are conducted where our fundamental understanding and experimental knowledge are lacking.

A key challenge in developing complete human equivalence is how to ground a synoptic theory of cognition in neural reality. Both cognitive architectures and neural models provide insight into how biological brains work, but from opposite directions. Here the authors report on initial work aimed at interpreting connectomic data in terms of algorithms. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. © 2011 The authors and IOS Press. All rights reserved.

A critical stage in microstructurally small fatigue crack growth in AA 7075-T651 is the nucleation of cracks originating in constituent particles into the matrix material. Previous work has focused on a geometric approach to modeling microstruc-turally small fatigue crack growth in which damage metrics derived from an elastic-viscoplastic constitutive model are used to predict the nucleation event [1, 2]. While a geometric approach based on classical finite elements was successful in explicitly modeling the polycrystalline grain structure, singularities at the crack tip necessitated the use of a nonlocal sampling approach to remove mesh size dependence. This study is an initial investigation of the peridynamic formulation of continuum mechanics as an alternative approach to modeling microstructurally small fatigue crack growth. Peridy-namics, a nonlocal extension of continuum mechanics, is based on an integral formulation that remains valid in the presence of material discontinuities. To capture accurately the material response at the grain scale, a crystal elastic-viscoplastic constitutive model is adapted for use in non-ordinary state-based peri-dynamics through the use of a regularized deformation gradient. The peridynamic approach is demonstrated on a baseline model consisting of a hard elastic inclusion in a single crystal. Coupling the elastic-viscoplastic material model with peridynamics successfully facilitates the modeling of plastic deformation and damage accumulation in the vicinity of the particle inclusion. Lattice orientation is shown to have a strong influence on material response. Copyright © 2011 by ASME.

The Image Composition Engine for Tiles (IceT) is a high-performance sort-last parallel rendering library. In addition to providing accelerated rendering for a standard display, IceT provides the unique ability to generate images for tiled displays. The overall resolution of the display may be several times larger than any viewport that may be rendered by a single machine. This document is an overview of the user interface to IceT.

Truncated Gaussian fields provide a flexible model for defining binary media with dispersed (as opposed to layered) inclusions. General properties of excursion sets on these truncated fields are coupled with a distance-based upscaling algorithm and approximations of point process theory to develop an estimation approach for effective conductivity in two-dimensions. Estimation of effective conductivity is derived directly from knowledge of the kernel size used to create the multiGaussian field, defined as the full-width at half maximum (FWHM), the truncation threshold and conductance values of the two modes. Therefore, instantiation of the multiGaussian field is not necessary for estimation of the effective conductance. The critical component of the effective medium approximation developed here is the mean distance between high conductivity inclusions. This mean distance is characterized as a function of the FWHM, the truncation threshold and the ratio of the two modal conductivities. Sensitivity of the resulting effective conductivity to this mean distance is examined for two levels of contrast in the two modal conductances and different FWHM sizes. Results demonstrate that the FWHM is a robust measure of mean travel distance in the background medium. The resulting effective conductivities are accurate when compared to numerical results and results obtained from effective media theory, distance-based upscaling and numerical simulation.

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The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. To meet this objective, NEAMS Waste IPSC M&S capabilities will be applied to challenging spatial domains, temporal domains, multiphysics couplings, and multiscale couplings. A strategic verification and validation (V&V) goal is to establish evidence-based metrics for the level of confidence in M&S codes and capabilities. Because it is economically impractical to apply the maximum V&V rigor to each and every M&S capability, M&S capabilities will be ranked for their impact on the performance assessments of various components of the repository systems. Those M&S capabilities with greater impact will require a greater level of confidence and a correspondingly greater investment in V&V. This report includes five major components: (1) a background summary of the NEAMS Waste IPSC to emphasize M&S challenges; (2) the conceptual foundation for verification, validation, and confidence assessment of NEAMS Waste IPSC M&S capabilities; (3) specifications for the planned verification, validation, and confidence-assessment practices; (4) specifications for the planned evidence information management system; and (5) a path forward for the incremental implementation of this V&V plan.

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Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD) project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.

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