Publications

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On 6/26/2015 at 1445 in 894/136, a thermal battery (approximately the size of a commercial size C cell) experienced an unexpected failure following a routine test where the battery is activated. The failure occurred while a test operator was transferring the battery from the testing primary containment box to another containment box within the same room; initial indications are that the battery package ruptured after it went into thermal runaway which led to the operator receiving bruising to the palm of the hand from the pressure of the expulsion. The operator was wearing the prescribed PPE, which was safety glasses and a high temperature glove on the hand that was holding the battery.

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Quantum Hall measurements have been performed on high-mobility GaAs/AlGaAs (p-type) and (n-type) quantum wells using a Hall/Anti-Hall bar configuration having both inner and outer edges. The potential distribution and the current flow in the bulk can be controlled by the external magnetic field or the driving current. Extreme situations occur at the Quantum Hall states where the current, driven by leads connected to the outer edge, flows exclusively in one half of the sample. In these states, the chemical potential of the inner edge aligns itself with the edge at ground potential. Accumulation and depletion of carriers takes place at the edge whose carriers flow away from the current source.

We have studied the cyclotron mobility of a Landau-quantized two-dimensional electron gas as a function of temperature (0.4 --100 K) at a fixed magnetic field (1.25 T) using terahertz time-domain spectroscopy in a sample with a low frequency mobility of μ_dc = 3.6 x 10⁶ cm² V^-1 s^-1 and a carrier concentration of ns = 2 x 10₆ cm^-2. The low temperature mobility in this sample results from both impurity scattering and acoustic deformation potential scattering, with μ$-1\atop{CR}$ ≈ (2.1 x 10⁵ cm² V^-1 s^-1)^-1 + (3.8 x 10^-8 V sK^-1 cm^-2 x T)^-1 at low temperatures. Above 50 K, the cyclotron oscillations show a strong reduction in both the oscillation amplitude and lifetime that is dominated by the contribution due to polar optical phonons. These results suggest that electron dephasing times as long as ~ 300 ps are possible even at this high lling factor (v = 6:6) in higher mobility samples (> 10⁷ cm² V^-1 s^-1) that have lower impurity concentrations and where the cyclotron mobility at this carrier concentration would be limited by acoustic deformation potential scattering.

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Relative motion at bolted connections can occur for large shock loads as the internal shear force in the bolted connection overcomes the frictional resistive force. This macroslip in a structure dissipates energy and reduces the response of the components above the bolted connection. There is a need to be able to capture macroslip behavior in a structural dynamics model. A linear model and many nonlinear models are not able to predict marcoslip effectively. The proposed method to capture macroslip is to use the multi-body dynamics code ADAMS to model joints with 3-D contact at the bolted interfaces. This model includes both static and dynamic friction. The joints are preloaded and the pinning effect when a bolt shank impacts a through hole inside diameter is captured. Substructure representations of the components are included to account for component flexibility and dynamics. This method was applied to a simplified model of an aerospace structure and validation experiments were performed to test the adequacy of the method.

The measurement of the radiation characteristics of an antenna on a near-field range requires that the antenna under test be located very close to the near-field probe. Although the direct coupling is utilized for characterizing the near field, this close proximity also presents the opportunity for significant undesired interactions (for example, reflections) to occur between the antenna and the near-field probe. When uncompensated, these additional interactions will introduce error into the measurement, increasing the uncertainty in the final gain pattern obtained through the near-field-to-far-field transformation. Quantifying this gain-uncertainty contribution requires quantifying the various additional interactions. A method incorporating spatial-frequency analysis is described which allows the dominant interaction contributions to be easily identified and quantified. In addition to identifying the additional antenna-to-probe interactions, the method also allows identification and quantification of interactions with other nearby objects within the measurement room. Because the method is a spatial-frequency method, wide-bandwidth data is not required, and it can be applied even when data is available at only a single temporal frequency. This feature ensures that the method can be applied to narrow-band antennas, where a similar time-domain analysis would not be possible.

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Major exascale computing reports indicate a number of software challenges to meet the dramatic change of system architectures in near future. While several-orders-of-magnitude increase in parallelism is the most commonly cited of those, hurdles also include performance heterogeneity of compute nodes across the system, increased imbalance between computational capacity and I/O capabilities, frequent system interrupts, and complex hardware architectures. Asynchronous task-parallel programming models show a great promise in addressing these issues, but are not yet fully understood nor developed su ciently for computational science and engineering application codes. We address these knowledge gaps through quantitative and qualitative exploration of leading candidate solutions in the context of engineering applications at Sandia. In this poster, we evaluate MiniAero code ported to three leading candidate programming models (Charm++, Legion and UINTAH) to examine the feasibility of these models that permits insertion of new programming model elements into an existing code base.

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The Database Performance Monitoring (DPM) software (copyright in processes) is being developed at Sandia National Laboratories to perform quality control analysis on time series data. The software loads time indexed databases (currently csv format), performs a series of quality control tests defined by the user, and creates reports which include summary statistics, tables, and graphics. DPM can be setup to run on an automated schedule defined by the user. For example, the software can be run once per day to analyze data collected on the previous day. HTML formatted reports can be sent via email or hosted on a website. To compare performance of several databases, summary statistics and graphics can be gathered in a dashboard view which links to detailed reporting information for each database. The software can be customized for specific applications.

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As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.

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This paper addresses work to minimize voiding and die tilt in solder attachment of a large power die, measuring 9.0 mm X 6.5 mm X 0.1 mm (0.354” x 0.256” x 0.004”), to a heat spreader. As demands for larger high power die continue, minimizing voiding and die tilt is of interest for improved die functionality, yield, manufacturability, and reliability. High-power die generate considerable heat, which is important to dissipate effectively through control of voiding under high thermal load areas of the die while maintaining a consistent bondline (minimizing die tilt). Voiding was measured using acoustic imaging and die tilt was measured using two different optical measurement systems. 80Au-20Sn solder reflow was achieved using a batch vacuum solder system with optimized fixturing. Minimizing die tilt proved to be the more difficult of the two product requirements to meet. Process development variables included tooling, weight and solder preform thickness.

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We investigate the (0001) surface of single crystal quartz with a submonolayer of Rb adsorbates. Using Rydberg atom electromagnetically induced transparency, we investigate the electric elds resulting from Rb adsorbed on the quartz surface, and measure the activation energy of the Rb adsorbates. We show that the Rb induces a negative electron affnity (NEA) on the quartz surface. The NEA surface allows for low energy electrons to bind to the surface and cancel the electric eld from the Rb adsorbates. Our results have implications for integrating Rydberg atoms into hybrid quantum systems and the fundamental study of atom-surface interactions, as well as applications for electrons bound to a 2D surface.

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Literature shows there has been extensive research and testing done in the area of wall panels and frangible materials. There is evidence from past research that shows it is possible to vent a structure that has had an accidental internal explosion [1]. The reviewed literature shows that most designs vent the entire wall panel versus a frangible material attached to the wall panel. The frangible material attachment points are important to determine the overall loading of the wall panel structure [2]. The materials used in the reviewed literature were securely attached as well as strong enough to remain intact during the pressure loading to move the entire wall panel. Since the vented wall panel was the weakest part of the overall structure, the other walls of the structure were substantially larger. The structure was usually built from concrete and large amounts of steel with dirt and sand over the top of the structure.The study will be conducted at Sandia National Laboratories located in Albuquerque New Mexico. The skeletal structural design for evaluation is a rectangular frame with a square grid pattern constructed from steel. The skeletal structure has been given to the researcher as a design requirement. The grid pattern will be evaluated strictly on plastic deformation and the loading that is applied from the frangible material. The frangible material tested will either fit into the grid or will be a veneer lightly attached to the structure frame. The frangible material may be required on both sides of the structure to adequately represent the application.

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This document describes the initial structural design for the National Rotor Testbed blade as presented during the preliminary design review at Sandia National Laboratories on October 28- 29, 2015. The document summarizes the structural and aeroelastic requirements placed on the NRT rotor for satisfactory deployment at the DOE/SNL SWiFT experimental facility to produce high-quality datasets for wind turbine model validation. The method and result of the NRT blade structural optimization is also presented within this report, along with analysis of its satisfaction of the design requirements.

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The purpose of the two projects discussed in this report is to use the cohesive zone method to evaluate fracture properties of geomaterials. Two experimental tests, the push-out test and the notched three-point bend test, were modeled computationally using finite element analysis and cohesive zone modeling to extract load and displacement information and ultimately determine failure behavior. These results are to be compared with experimental tests when they are available. The first project used the push-out test to investigate the shear bond strength at the cement- shale interface. The second project explored the effects of scaling a notched three-point bending specimen to study fracture toughness characteristics. The bond strength and fracture toughness of a material and its interfaces are important parameters to consider in subsurface applications so that zonal isolation can be achieved.

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Traditional packet-capture solutions using commodity hardware incur a large amount of overhead as packets are copied multiple times by the operating system. This overhead slows sensor systems to a point where they are unable to keep up with high bandwidth traffic, resulting in dropped packets. Incomplete packet capture files hinder network monitoring and incident response efforts. While costly commercial hardware exists to capture high bandwidth traffic, several software-based approaches exist to improve packet capture performance using commodity hardware.

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As lithium-ion battery technologies mature, the size and energy of these systems continues to increase (> 50 kWh for EVs); making safety and reliability of these high energy systems increasingly important. While most material advances for lithium-ion chemistries are directed toward improving cell performance (capacity, energy, cycle life, etc.), there are a variety of materials advancements that can be made to improve lithium-ion battery safety. Issues including energetic thermal runaway, electrolyte decomposition and flammability, anode SEI stability, and cell-level abuse tolerance continue to be critical safety concerns. This report highlights work with our collaborators to develop advanced materials to improve lithium-ion battery safety and abuse tolerance and to perform cell-level characterization of new materials.

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Except in the most extreme conditions, Synthetic aperture radar (SAR) is a remote sensing technology that can operate day or night. A SAR can provide surveillance over a long time period by making multiple passes over a wide area. For object-based intelligence it is convenient to segment and classify the SAR images into objects that identify various terrains and man-made structures that we call “static features.” In this paper we introduce a novel SAR image product that captures how different regions decorrelate at different rates. Using superpixels and their first two moments we develop a series of one-class classification algorithms using a goodness-of-fit metric. P-value fusion is used to combine the results from different classes. We also show how to combine multiple one-class classifiers to get a confidence about a classification. This can be used by downstream algorithms such as a conditional random field to enforce spatial constraints.

The dynamic stability of deep drillstrings is challenged by an inability to impart controllability with ever-changing conditions introduced by geology, depth, structural dynamic properties and operating conditions. A multi-organizational LDRD project team at Sandia National Laboratories successfully demonstrated advanced technologies for mitigating drillstring vibrations to improve the reliability of drilling systems used for construction of deep, high-value wells. Using computational modeling and dynamic substructuring techniques, the benefit of controllable actuators at discrete locations in the drillstring is determined. Prototype downhole tools were developed and evaluated in laboratory test fixtures simulating the structural dynamic response of a deep drillstring. A laboratory-based drilling applicability demonstration was conducted to demonstrate the benefit available from deployment of an autonomous, downhole tool with self-actuation capabilities in response to the dynamic response of the host drillstring. A concept is presented for a prototype drilling tool based upon the technical advances. The technology described herein is the subject of U.S. Patent Application No. 62219481, entitled "DRILLING SYSTEM VIBRATION SUPPRESSION SYSTEMS AND METHODS", filed September 16, 2015.

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Active learning methods automatically adapt data collection by selecting the most informative samples in order to accelerate machine learning. Because of this, real-world testing and comparing active learning algorithms requires collecting new datasets (adaptively), rather than simply applying algorithms to benchmark datasets, as is the norm in (passive) machine learning research. To facilitate the development, testing and deployment of active learning for real applications, we have built an open-source software system for large-scale active learning research and experimentation. The system, called NEXT, provides a unique platform for realworld, reproducible active learning research. This paper details the challenges of building the system and demonstrates its capabilities with several experiments. The results show how experimentation can help expose strengths and weaknesses of active learning algorithms, in sometimes unexpected and enlightening ways.

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The neutron scatter camera (NSC), an imaging spectrometer for fission energy neutrons, is an established and proven detector for nuclear security applications such as weak source detection of special nuclear material (SNM), arms control treaty verification, and emergency response. Relative to competing technologies such as coded aperture imaging, time-encoded imaging, neutron time projection chamber, and various thermal neutron imagers, the NSC provides excellent event-by-event directional information for signal/background discrimination, reasonable imaging resolution, and good energy resolution. Its primary drawback is very low detection efficiency due to the requirement for neutron elastic scatters in two detector cells. We will develop a singlevolume double-scatter neutron imager, in which both neutron scatters can occur in the same large active volume. If successful, the efficiency will be dramatically increased over the current NSC cell-based geometry. If the detection efficiency approaches that of e.g. coded aperture imaging, the other inherent advantages of double-scatter imaging would make it the most attractive fast neutron detector for a wide range of security applications.

Material Identification by Resonant Attenuation is a technique that measures the energy-dependent attenuation of 1-10 MeV neutrons as they pass through a sample. Elemental information is determined from the neutron absorption resonances unique to each element. With sufficient energy resolution, these resonances can be used to categorize a wide range of materials, serving as a powerful discrimination technique between explosives, contraband, and other materials. Our proposed system is unique in that it simultaneously down-scatters and time tags neutrons in scintillator detectors oriented between a d-T generator and sample. This allows not only for energy measurements without pulsed neutron beams, but for sample interrogation over a large range of relevant energies, vastly improving scan times. Our system’s core advantage is a potential breakthrough ability to provide detection discrimination of threat materials by their elemental composition (e.g. water vs. hydrogen peroxide) without opening the container. However, several technical and computational challenges associated with this technique have yet to be addressed. There are several open questions: what is the sensitivity to different materials, what scan times are necessary, what are the sources of background, how do each of these scale as the detector system is made larger, and how can the system be integrated into existing scanning technology to close current detection gaps? In order to prove the applicability of this technology, we will develop a validated model to optimize the design and characterize the uncertainties in the measurement, and then test the system in a real-world scenario. This project seeks to perform R&D and laboratory tests that demonstrate proof of concept (TRL 3) to establishing an integrated system and evaluating its performance (TRL 4) through both laboratory tests and a validated detector model. The validated model will allow us to explore our technology’s benefits to explosive detection in various applications.

The intent of the proposed work, in collaboration with University of Michigan, is to develop the algorithms that will bring the analysis from qualitative images to quantitative attributes of objects containing SNM. The first step to achieving this is to develop an indepth understanding of the intrinsic errors associated with the deconvolution and MLEM algorithms. A significant new effort will be undertaken to relate the image data to a posited three-dimensional model of geometric primitives that can be adjusted to get the best fit. In this way, parameters of the model such as sizes, shapes, and masses can be extracted for both radioactive and non-radioactive materials. This model-based algorithm will need the integrated response of a hypothesized configuration of material to be calculated many times. As such, both the MLEM and the model-based algorithm require significant increases in calculation speed in order to converge to solutions in practical amounts of time.

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This report documents the combined work of the two meetings and serves as a key part of the foundation for the A2e/HFM effort for predictive modeling of whole wind plant physics.

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This report summarizes the work performed in the prioritization of cavern access wells for remediation and monitoring at the Bayou Choctaw Strategic Petroleum Reserve site. The grading included consideration of all 15 wells at the Bayou Choctaw site, with each active well receiving a separate grade for remediation and monitoring. Numerous factors affecting well integrity were incorporated into the grading including casing survey results, cavern pressure history, results from geomechanical simulations, and site geologic factors. The factors and grading framework used here are the same as those used in developing similar well remediation and monitoring priorities at the Big Hill, Bryan Mound, and West Hackberry Strategic Petroleum Reserve Sites.

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This report concludes the LDRD entitled "Advanced SMRs using S-CO2 Power Conversion with Dry Cooling." The goal of this project was to demonstrate the feasibility of using sCO₂ as the working fluid in a dry-cooled natural circulation loop. The reason for doing this is to demonstrate that such a loop could be utilized in small modular reactors (SMRs) as a method for (a) passively removing decay heat from the reactor and (b) cooling the reactor without using the copious amounts of water needed for wet-cooled reactors. The dry-cooling aspect of this work is possible due to the working conditions of a sCO₂ Brayton power conversion cycle. The loop was designed, built, and operated over the three-year life of the LDRD project. This report outlines some of the key accomplishments and some of the future work that we are continuing to try to complete in the future. A more comprehensive report will be completed and submitted in the Fall of 2015.

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

A Moehwald HDA (HDA is a German acronym: Hydraulischer Druckanstieg: hydraulic pressure increase) injection quantity and rate measuring unit is used to investigate injection rates obtained with a fast-acting, preproduction diesel solenoid injector. Experimental parametric variations are performed to determine their impact on measured injection rate traces. A pilot-main injection strategy is investigated for various dwell times; these preproduction injectors can operate with very short dwell times with distinct pilot and main injection events. Dwell influences the main injection rate shape. A comparison between a diesel-like fuel and a gasoline-like fuel shows that injection rates are comparable for a single injection but dramatically different for multiple injections with short dwells.