Publications

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Soil from an excavated test was being surveyed and fresh DU fragments removed so the soil could be returned to the excavation hole. Sandia RCTs discovered two locations where highly oxidized DU was present just below the undisturbed lake bed surface. The oxidized DU was removed for disposal as radioactive waste. Approximately one cubic foot of oxidized DU mixed with soil was removed. Line Manager, Sr. Manager and Acting Director were all notified of this event.

Power consumption of extreme-scale supercomputers has become a key performance bottleneck. Yet current practices do not leverage power management opportunities, instead running at maximum power. This is not sustainable. Future systems will need to manage power as a critical resource, directing it to where it has greatest benefit. Power capping is one mechanism for managing power budgets, however its behavior is not well understood. This paper presents an empirical evaluation of several key HPC workloads running under a power cap on a Cray XC40 system, and provides a comparison of this technique with p-state control, demonstrating the performance differences of each. These results show: 1.) Maximum performance requires ensuring the cap is not reached; 2.) Performance slowdown under a cap can be attributed to cascading delays which result in unsynchronized performance variability across nodes; and, 3.) Due to lag in reaction time, considerable time is spent operating above the set cap. This work provides a timely and much needed comparison of HPC application performance under a power cap and attempts to enable users and system administrators to understand how to best optimize application performance on power-constrained HPC systems.

The moon-forming impact and the subsequent evolution of the proto-Earth is strongly dependent on the properties of materials at the extreme conditions generated by this violent collision. We examine the high pressure behavior of MgO, one of the dominant constituents in Earth's mantle, using high-precision, plate impact shock compression experiments performed on Sandia National Laboratories' Z Machine and extensive quantum calculations using density functional theory (DFT) and quantum Monte Carlo (QMC) methods. The combined data span from ambient conditions to 1.2 TPa and 42 000 K, showing solid-solid and solid-liquid phase boundaries. Furthermore our results indicate that under impact the solid and liquid phases coexist for more than 100 GPa, pushing complete melting to pressures in excess of 600 GPa. The high pressure required for complete shock melting has implications for a broad range of planetary collision events.

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We report on the progress made to date for a Laboratory Directed Research and Development (LDRD) project aimed at diagnosing magnetic flux compression on the Z pulsed-power accelerator (0-20 MA in 100 ns). Each experiment consisted of an initially solid Be or Al liner (cylindrical tube), which was imploded using the Z accelerator's drive current (0-20 MA in 100 ns). The imploding liner compresses a 10-T axial seed field, B z ( 0 ) , supplied by an independently driven Helmholtz coil pair. Assuming perfect flux conservation, the axial field amplification should be well described by B z ( t ) = B z ( 0 ) x [ R ( 0 ) / R ( t )] 2 , where R is the liner's inner surface radius. With perfect flux conservation, B z ( t ) and dB z / dt values exceeding 10 4 T and 10 12 T/s, respectively, are expected. These large values, the diminishing liner volume, and the harsh environment on Z, make it particularly challenging to measure these fields. We report on our latest efforts to do so using three primary techniques: (1) micro B-dot probes to measure the fringe fields associated with flux compression, (2) streaked visible Zeeman absorption spectroscopy, and (3) fiber-based Faraday rotation. We also mention two new techniques that make use of the neutron diagnostics suite on Z. These techniques were not developed under this LDRD, but they could influence how we prioritize our efforts to diagnose magnetic flux compression on Z in the future. The first technique is based on the yield ratio of secondary DT to primary DD reactions. The second technique makes use of the secondary DT neutron time-of-flight energy spectra. Both of these techniques have been used successfully to infer the degree of magnetization at stagnation in fully integrated Magnetized Liner Inertial Fusion (MagLIF) experiments on Z [P. F. Schmit et al. , Phys. Rev. Lett. 113 , 155004 (2014); P. F. Knapp et al. , Phys. Plasmas, 22 , 056312 (2015)]. Finally, we present some recent developments for designing and fabricating novel micro B-dot probes to measure B z ( t ) inside of an imploding liner. In one approach, the micro B-dot loops were fabricated on a printed circuit board (PCB). The PCB was then soldered to off-the-shelf 0.020- inch-diameter semi-rigid coaxial cables, which were terminated with standard SMA connectors. These probes were recently tested using the COBRA pulsed power generator (0-1 MA in 100 ns) at Cornell University. In another approach, we are planning to use new multi-material 3D printing capabilities to fabricate novel micro B-dot packages. In the near future, we plan to 3D print these probes and then test them on the COBRA generator. With successful operation demonstrated at 1-MA, we will then make plans to use these probes on a 20-MA Z experiment.

Oxidation of exfoliated gallium selenide (GaSe) is investigated through Raman, photoluminescence, Auger, and X-ray photoelectron spectroscopies. Photoluminescence and Raman intensity reductions associated with spectral features of GaSe are shown to coincide with the emergence of signatures emanating from the by-products of the oxidation reaction, namely, Ga₂Se₃ and amorphous Se. Furthermore, photoinduced oxidation is initiated over a portion of a flake highlighting the potential for laser based patterning of two-dimensional heterostructures via selective oxidation.

We present a domain-decomposition-based pre-conditioner for the solution of partial differential equations (PDEs) that is resilient to both soft and hard faults. The algorithm is based on the following steps: first, the computational domain is split into overlapping subdomains, second, the target PDE is solved on each subdomain for sampled values of the local current boundary conditions, third, the subdomain solution samples are collected and fed into a regression step to build maps between the subdomains' boundary conditions, finally, the intersection of these maps yields the updated state at the subdomain boundaries. This reformulation allows us to recast the problem as a set of independent tasks. The implementation relies on an asynchronous server-client framework, where one or more reliable servers hold the data, while the clients ask for tasks and execute them. This framework provides resiliency to hard faults such that if a client crashes, it stops asking for work, and the servers simply distribute the work among all the other clients alive. Erroneous subdomain solves (e.g. due to soft faults) appear as corrupted data, which is either rejected if that causes a task to fail, or is seamlessly filtered out during the regression stage through a suitable noise model. Three different types of faults are modeled: hard faults modeling nodes (or clients) crashing, soft faults occurring during the communication of the tasks between server and clients, and soft faults occurring during task execution. We demonstrate the resiliency of the approach for a 2D elliptic PDE, and explore the effect of the faults at various failure rates.

Here highly conductive, solvent-resistant anionic Diels Alder polyphenylene (DAPP) membranes were synthesized with three different ionic contents and tested in an ionic liquid-based nonaqueous redox flow battery (RFB). These membranes display 3–10× increase in conductivity in propylene carbonate compared to some commercially available (aqueous) anion exchange membranes. The membrane with an ion content of 1.5 meq/g (DAPP1.5) proved too brittle for operation in a RFB, while the membrane with an ion content of 2.5 meq/g (DAPP2.5) allowed excessive movement of solvent and poor electrochemical yields (capacity fade). Despite having lower voltage efficiencies compared to DAPP2.5, the membrane with an intermediate ion content of 2.0 meq/g (DAPP2.0) exhibited higher coulombic efficiencies (96.4% vs. 89.1%) and electrochemical yields (21.6% vs. 10.9%) after 50 cycles. Crossover of the electroactive species was the primary reason for decreased electrochemical yields. Analysis of the anolyte and catholyte revealed degradation of the electroactive species and formation of a film at the membrane-solution interface. Increases in membrane resistance were attributed to mechanical and thermal aging of the membrane; no chemical change was observed. As a result, improvements in the ionic selectivity and ionic conductivity of the membrane will increase the electrochemical yield and voltage efficiency of future nonaqueous redox flow batteries.

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. We demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.

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