Publications

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Conventional hydrogen compressors often contribute over half of the cost of hydrogen stations, have poor reliability, and have insufficient flow rates for a mature fuel cell vehicle market. Fatigue associated with their moving parts including cracking of diaphragms and failure of seals leads to failure in conventional compressors, which is exacerbated by the repeated starts and stops expected at fueling stations. Furthermore, the conventional lubrication of these compressors with oil is generally unacceptable at fueling stations due to potential fuel contamination. MH technology offers a very good alternative to both conventional (mechanical) and newly developed (electrochemical, ionic liquid pistons) methods of hydrogen compression. Advantages of MH compression include simplicity in design and operation, absence of moving parts, compactness, safety and reliability, and the possibility to utilize waste industrial heat to power the compressor. Beyond conventional H₂ supply via pipelines or tanker trucks, another attractive scenario is the on-site generation and delivery of pure H₂ at pressure (> 875 bar) for refueling vehicles at electrolysis, wind, or solar H2 production facilities in distributed locations that are too remote or widely distributed for cost effective bulk transport. MH hydrogen compression utilizes a reversible heat-driven interaction of a hydride-forming metal alloy with hydrogen gas to form the MH phase and is a promising process for hydrogen energy applications. To deliver hydrogen continuously, each stage of the compressor must consist of multiple MH beds with synchronized hydrogenation & dehydrogenation cycles. Multistage pressurization allows achievement of greater compression ratios using reduced temperature swings compared to single stage compressors. The objectives of this project are to investigate and demonstrate on a laboratory scale a twostage MH hydrogen gas compressor with a feed pressure of >100 bar and a delivery pressure > 875 bar of high purity H₂ gas using the scheme shown in Figure 1. Progress to date includes the selection of metal hydrides for each compressor stage based on experimental characterization of their thermodynamics, kinetics, and hydrogen capacities for optimal performance with respect to energy requirements and efficiency. Additionally, final bed designs have been completed based on trade studies and all components have been ordered. The prototype two-stage compressor will be fabricated, assembled, and experimentally evaluated in FY19.

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The limiting frequency resolution of a PDV measurement is: σf = $\sqrt\frac{6 η}{fsτ^3π}$ where f_s is the sample rate, τ is the analysis time duration, and 11 is the noise fraction. Although T is a strong lever for reducing uncertainty, this parameter must be kept small to preserve time resolution. Consider a PDV measurement with sampled at 80 GS/s and analyzed in 1 ns durations. A 1% noise fraction corresponds to 0.87 MHz of frequency uncertainty, which at 1550 nm works out to 0.68 m/s. A 10% noise fraction has a limiting velocity resolution of about 7 m/s; for comparison, a VISAR system with similar response time (0.5 ns delay, 532 m/s fringe constant) would have a limiting uncertainty of 5-6 m/s. Noise fractions of 10-20% or less are desirable for measurements at this time scale.

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With the increased scale expected on future leadership-class systems, detailed information about the resource usage and performance of MPI message matching provides important insights into how to maintain application performance on next-generation systems. However, obtaining MPI message matching performance data is often not possible without significant effort. A common approach is to instrument an MPI implementation to collect relevant statistics. While this approach can provide important data, collecting matching data at runtime perturbs the application's execution, including its matching performance, and is highly dependent on the MPI library's matchlist implementation. In this paper, we introduce a trace-based simulation approach to obtain detailed MPI message matching performance data for MPI applications without perturbing their execution. Using a number of key parallel workloads and microbenchmarks, we demonstrate that this simulator approach can rapidly and accurately characterize matching behavior. Specifically, we use our simulator to collect several important statistics about the operation of the MPI posted and unexpected queues. For example, we present data about search lengths and the duration that messages spend in the queues waiting to be matched. Data gathered using this simulation-based approach have significant potential to aid hardware designers in determining resource allocation for MPI matching functions and provide application and middleware developers with insight into the scalability issues associated with MPI message matching.

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The Vanguard program informally began in January 2017 with the submission of a white paper entitled "Sandia's Vision for a 2019 Arm Testbed" to NNSA headquarters. The program proceeded in earnest in May 2017 with an announcement by Doug Wade (Director, Office of Advanced Simulation and Computing and Institutional R&D at NNSA) that Sandia National Laboratories (Sandia) would host the first Advanced Architecture Prototype platform based on the Arm architecture. In August 2017, Sandia formed a Tri-lab team chartered to develop a robust HPC software stack for Astra to support the Vanguard program goal of demonstrating the viability of Arm in supporting ASC production computing workloads. This document describes the high-level Vanguard program goals, the Vanguard-Astra project acquisition plan and procurement up to contract placement, the initial software stack environment planned for the Vanguard-Astra platform (Astra), a description of how the communities of users will utilize the platform during the transition from the open network to the classified network, and initial performance results.

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Existing models for most materials do not describe phase transformations and associated lattice dy- namics (kinetics) under extreme conditions of pressure and temperature. Dynamic x-ray diffraction (DXRD) allows material investigations in situ on an atomic scale due to the correlation between solid-state structures and their associated diffraction patterns. In this LDRD project we have devel- oped a nanosecond laser-compression and picosecond-to-nanosecond x-ray diffraction platform for dynamically-compressed material studies. A new target chamber in the Target Bay in building 983 was commissioned for the ns, kJ Z-Beamlet laser (ZBL) and the 0.1 ns, 250 J Z-Petawatt (ZPW) laser systems, which were used to create 8-16 keV plasma x-ray sources from thin metal foils. The 5 ns, 15 J Chaco laser system was converted to a high-energy laser shock driver to load material samples to GPa stresses. Since laser-to-x-ray energy conversion efficiency above 10 keV is low, we employed polycapillary x-ray lenses for a 100-fold fluence increase compared to a conventional pinhole aperture while simultaneously reducing the background significantly. Polycapillary lenses enabled diffraction measurements up to 16 keV with ZBL as well as diffraction experiments with ZPW. This x-ray diffraction platform supports experiments that are complementary to gas guns and the Z facility due to different strain rates. Ultimately, there is now a foundation to evaluate DXRD techniques and detectors in-house before transferring the technology to Z. This page intentionally left blank.

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The Vanguard program informally began in January 2017 with the submission of a white paper entitled "Sandia's Vision for a 2019 Arm Testbed" to NNSA headquarters. The program proceeded in earnest in May 2017 with an announcement by Doug Wade (Director, Office of Advanced Simulation and Computing and Institutional R&D at NNSA) that Sandia National Laboratories (Sandia) would host the first Advanced Architecture Prototype platform based on the Arm architecture. In August 2017, Sandia formed a Tri-lab team chartered to develop a robust HPC software stack for Astra to support the Vanguard program goal of demonstrating the viability of Arm in supporting ASC production computing workloads.

The 2018 NRC HEAF tests were conducted in Chalfont Pennsylvania at KEMA High Power Laboratory during the week of September 10th. These scoping tests were executed to determine the most effective measurement methodologies for future tests. The goal of Sandia’s Photometrics group was to provide high-speed quantitative and qualitative imaging of the arcing fault tests for the Nuclear Regulatory Commission. The measurement methods included visible high-speed imaging, high-speed high-dynamic range visible imaging, thermal imaging, and quantitative flow imaging. In addition, data fusion products were generated to visualize instrumentation data and imaging measurements. All imaging has been time synchronized to the start of the arcing event.