Publications

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Instrumented indentation has yielded mixed results when used to measure surface residual stresses in metal films. Relative to metals, many glasses and ceramics have a low modulus-to-yield strength (E/sy) ratio. The advantage of this characteristic for measuring residual stress using instrumented indentation is demonstrated by a series of comparative spherical and conical tip finite element simulations. Two cases are considered: (i) a material with E/s{sub y} = 24-similar to glass and (ii) a material with E/s{sub y} = 120-similar to metal films. In both cases, compressive residual stress shifts the simulated load-displacement response toward increasing hardness, irrespective of tip geometry. This shift is shown to be entirely due to pile up for the ''metal'' case, but primarily due to the direct influence of the residual stress for the ''glass'' case. Hardness changes and load-displacement curve shifts are explained by using the spherical cavity model. Supporting experimental results on stressed glasses are provided.

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The development and calibration to experimental data of a nonlinear stochastic dynamics model for a Micro-Electro-Mechanical System (MEMS) inertial switch is discussed. The MEMS switch is modeled as a classical vibro-impact dynamic system: a single degree-of-freedom oscillator subject to impact with a single rigid barrier. An applied load, modeled as a stationary Gaussian stochastic process with prescribed power spectral density (PSD), excites the device and causes repetitive impacts with the barrier. A subset of the model parameters are described as correlated random variables to represent the significant unit-to-unit variability observed during testing of a collection of the switches. Experimental measurements from linear modal and nonlinear transient tests on multiple nominally-identical units are used to calibrate the probabilistic model. The calibrated model for the MEMS inertial switch is then used for probabilistic design studies, where the metric of performance is the amount of time the switch remains closed when subject to the applied stochastic load. © 2006 Elsevier B.V. All rights reserved.

Computational fluid dynamics (CFD) codes are increasingly being used in the liquefied natural gas (LNG) industry to predict natural gas dispersion distances. This paper addresses several issues regarding the use of CFD for LNG dispersion such as specification of the domain, grid, boundary and initial conditions. A description of the k-ε model is presented, along with modifications required for atmospheric flows. Validation issues pertaining to the experimental data from the Burro, Coyote, and Falcon series of LNG dispersion experiments are also discussed. A description of the atmosphere is provided as well as discussion on the inclusion of the Coriolis force to model very large LNG spills. © 2006 Elsevier B.V. All rights reserved.

Non-equilibrium sorption of contaminants in ground water systems is examined from the perspective of sorption rate estimation. A previously developed Markov transition probability model for solute transport is used in conjunction with a new conditional probability-based model of the sorption and desorption rates based on breakthrough curve data. Two models for prediction of spatially varying sorption and desorption rates along a one-dimensional streamline are developed. These models are a Markov model that utilizes conditional probabilities to determine the rates and an ensemble Kalman filter (EKF) applied to the conditional probability method. Both approaches rely on a previously developed Markov-model of mass transfer, and both models assimilate the observed concentration data into the rate estimation at each observation time. Initial values of the rates are perturbed from the true values to form ensembles of rates and the ability of both estimation approaches to recover the true rates is examined over three different sets of perturbations. The models accurately estimate the rates when the mean of the perturbations are zero, the unbiased case. Finally, for the cases containing some bias, addition of the ensemble Kalman filter is shown to improve accuracy of the rate estimation by as much as an order of magnitude.

Simultaneous imaging of multiple cellular components is of tremendous importance in the study of complex biological systems, but the inability to use probes with similar emission spectra and the time consuming nature of collecting images on a confocal microscope are prohibitive. Hyperspectral imaging technology, originally developed for remote sensing applications, has been adapted to measure multiple genes in complex biological tissues. A spectral imaging microscope was used to acquire overlapping fluorescence emissions from specific mRNAs in brain tissue by scanning the samples using a single fluorescence excitation wavelength. The underlying component spectra obtained from the samples are then separated into their respective spectral signatures using multivariate analyses, enabling the simultaneous quantitative measurement of multiple genes either at regional or cellular levels. © 2006 Elsevier B.V. All rights reserved.

Axial symmetry in x-ray radiation of wire-array z pinches is important for the creation of dynamic hohlraums used to compress inertial-confinement-fusion capsules. We present the first evidence that this symmetry is directly correlated with the magnitude of the negative radial electric field along the wire surface. This field (in turn) is inferred to control the initial energy deposition into the wire cores, as well as any current shorting to the return conductor. © 2007 The American Physical Society.

A 1 km square regular grid system created on the Universal Transverse Mercator zone 54 projected coordinate system is used to work with volcanism related data for Sengan region. The following geologic variables were determined as the most important for identifying volcanism: geothermal gradient, groundwater temperature, heat discharge, groundwater pH value, presence of volcanic rocks and presence of hydrothermal alteration. Data available for each of these important geologic variables were used to perform directional variogram modeling and kriging to estimate geologic variable vectors at each of the 23949 centers of the chosen 1 km cell grid system. Cluster analysis was performed on the 23949 complete variable vectors to classify each center of 1 km cell into one of five different statistically homogeneous groups with respect to potential volcanism spanning from lowest possible volcanism to highest possible volcanism with increasing group number. A discriminant analysis incorporating Bayes' theorem was performed to construct maps showing the probability of group membership for each of the volcanism groups. The said maps showed good comparisons with the recorded locations of volcanism within the Sengan region. No volcanic data were found to exist in the group 1 region. The high probability areas within group 1 have the chance of being the no volcanism region. Entropy of classification is calculated to assess the uncertainty of the allocation process of each 1 km cell center location based on the calculated probabilities. The recorded volcanism data are also plotted on the entropy map to examine the uncertainty level of the estimations at the locations where volcanism exists. The volcanic data cell locations that are in the high volcanism regions (groups 4 and 5) showed relatively low mapping estimation uncertainty. On the other hand, the volcanic data cell locations that are in the low volcanism region (group 2) showed relatively high mapping estimation uncertainty. The volcanic data cell locations that are in the medium volcanism region (group 3) showed relatively moderate mapping estimation uncertainty. Areas of high uncertainty provide locations where additional site characterization resources can be spent most effectively. The new data collected can be added to the existing database to perform future regionalized mapping and reduce the uncertainty level of the existing estimations. © Springer Science+Business Media B.V. 2006.

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A novel hyperspectral fluorescence microscope for high-resolution 3D optical sectioning of cells and other structures has been designed, constructed, and used to investigate a number of different problems. We have significantly extended new multivariate curve resolution (MCR) data analysis methods to deconvolve the hyperspectral image data and to rapidly extract quantitative 3D concentration distribution maps of all emitting species. The imaging system has many advantages over current confocal imaging systems including simultaneous monitoring of numerous highly overlapped fluorophores, immunity to autofluorescence or impurity fluorescence, enhanced sensitivity, and dramatically improved accuracy, reliability, and dynamic range. Efficient data compression in the spectral dimension has allowed personal computers to perform quantitative analysis of hyperspectral images of large size without loss of image quality. We have also developed and tested software to perform analysis of time resolved hyperspectral images using trilinear multivariate analysis methods. The new imaging system is an enabling technology for numerous applications including (1) 3D composition mapping analysis of multicomponent processes occurring during host-pathogen interactions, (2) monitoring microfluidic processes, (3) imaging of molecular motors and (4) understanding photosynthetic processes in wild type and mutant Synechocystis cyanobacteria.

This report describes a Cooperative Research and Development Agreement (CRADA) between Salt River Project Agricultural Improvement and Power District (SRP) and Sandia National Laboratories to jointly develop advanced methods of controlling distributed energy resources (DERs) that may be located within SRP distribution systems. The controls must provide a standardized interface to allow plug-and-play capability and should allow utilities to take advantage of advanced capabilities of DERs to provide a value beyond offsetting load power. To do this, Sandia and SRP field-tested the IEC 61850-7-420 DER object model (OM) in a grid environment, with the goal of validating whether the model is robust enough to be used in common utility applications. The diesel generator OM tested was successfully used to accomplish basic genset control and monitoring. However, as presently constituted it does not enable plug-and-play functionality. Suggestions are made of aspects of the standard that need further development and testing. These problems are far from insurmountable and do not imply anything fundamentally unsound or unworkable in the standard.

This report describes efforts by the Performance Modeling and Analysis Team to investigate performance characteristics of Sandia's engineering and scientific applications on the ASC capability and advanced architecture supercomputers, and Sandia's capacity Linux clusters. Efforts to model various aspects of these computers are also discussed. The goals of these efforts are to quantify and compare Sandia's supercomputer and cluster performance characteristics; to reveal strengths and weaknesses in such systems; and to predict performance characteristics of, and provide guidelines for, future acquisitions and follow-on systems. Described herein are the results obtained from running benchmarks and applications to extract performance characteristics and comparisons, as well as modeling efforts, obtained during the time period 2004-2006. The format of the report, with hypertext links to numerous additional documents, purposefully minimizes the document size needed to disseminate the extensive results from our research.

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