This report provides guidance on how to adjust temperature measurements from mineral-insulated, metal-sheathed (MIMS) thermocouples (TCs) mounted on metal plates to correct for slow transient response. This information is needed so that more accurate transient temperature measurements can be made. These more accurate temperature measurements are of benefit for both qualification of hardware and as data sets for model validation. The approach was to use a relatively simple first order adjustment to the MIMS TC reading, as compared to a more accurate metal plate temperature measurement. MIMS TCs are used to improve reliability. Results from four data sets were analyzed to determine the time constraint; an overall average of 5.0 s was obtained.
This project aims to provide experimental support, including support for validation and parameterization, for mechanical failure modeling work as part of DOE's Computer Aided Engineering for Electric-Drive Vehicle Batteries (CAEBAT) program. This work involves mechanical deformation testing on both charged and discharged cells, including abusive mechanical testing leading to battery failure. The mechanical data generated is provided to the modeling teams to provide empirical parameterization as well as validation for newly developed models. Testing fully charged cells and packs (abusive battery testing) also allows for a better understanding of what conditions are most likely to lead to a potentially hazardous thermal runaway event.
This document summarily provides brief descriptions of the MELCOR code enhancement made between code revision number 9496 and 11932. Revision 9496 represents the last official code release; therefore, the modeling features described within this document are provided to assist users that update to the newest official MELCOR code release, 11932. Along with the newly updated MELCOR Users' Guide and Reference Manual, users will be aware and able to assess the new capabilities for their modeling and analysis applications.
A series of Magnetized Liner Inertial Fusion (MagLIF) experiments have been conducted in order to investigate the mix introduced from various target surfaces during the laser preheat stage. The material mixing was measured spectroscopically for a variety of preheat protocols by employing mid-atomic number surface coatings applied to different regions of the MagLIF target. The data show that the material from the top cushion region of the target can be mixed into the fuel during preheat. For some preheat protocols, our experiments show that the laser-entrance-hole (LEH) foil used to contain the fuel can be transported into the fuel a significant fraction of the stagnation length and degrade the target performance. Preheat protocols using pulse shapes of a few-ns duration result in the observable LEH foil mix both with and without phase-plate beam smoothing. In order to reduce this material mixing, a new capability was developed to allow for a low energy (∼20 J) laser pre-pulse to be delivered early in time (-20 ns) before the main laser pulse (∼1.5 kJ). In experiments, this preheat protocol showed no indications of the LEH foil mix. The experimental results are broadly in agreement with pre-shot two-dimensional HYDRA simulations that helped motivate the development of the early pre-pulse capability.
We seek scalable benchmarks for entity resolution problems. Solutions to these problems range from trivial approaches such as string sorting to sophisticated methods such as statistical relational learning. The theoretical and practical complexity of these approaches varies widely, so one of the primary purposes of a benchmark will be to quantify the trade-off between solution quality and runtime. We are motivated by the ubiquitous nature of entity resolution as a fundamental problem faced by any organization that ingests large amounts of noisy text data. A benchmark is typically a rigid specification that provides an objective measure usable for ranking implementations of an algorithm. For example the Top500 and HPCG500 bench- marks rank supercomputers based on their performance of dense and sparse linear algebra problems (respectively). These two benchmarks require participants to report FLOPS counts attainable on various machines. Our purpose is slightly different. Whereas the supercomputing benchmarks mentioned above hold algorithms constant and aim to rank machines, we are primarily interested in ranking algorithms. As mentioned above, entity resolution problems can be approached in completely different ways. We believe that users of our benchmarks must decide what sort of procedure to run before comparing implementations and architectures. Eventually, we also wish to provide a mechanism for ranking machines while holding algorithmic approach constant . Our primary contributions are parallel algorithms for computing solution quality mea- sures per entity. We find in some real datasets that many entities are quite easy to resolve while others are difficult, with a heavy skew toward the former case. Therefore, measures such as global confusion matrices, F measures, etc. do not meet our benchmarking needs. We design methods for computing solution quality at the granularity of a single entity in order to know when proposed solutions do well in difficult situations (perhaps justifying extra computational), or struggling in easy situations. We report on progress toward a viable benchmark for comparing entity resolution algo- rithms. Our work is incomplete, but we have designed and prototyped several algorithms to help evalute the solution quality of competing approaches to these problems. We envision a benchmark in which the objective measure is a ratio of solution quality to runtime.
Jooya, H.Z.; Mckay, K.S.; Kim, E.; Weck, Philippe F.; Pappas, D.P.; Da HiteDa; Sadeghpour, H.R.
The variation of the work function upon carbon adsorption on the reconstructed Au(110) surface is measured experimentally and compared to density functional calculations. The adsorption dynamics is simulated with ab-initio molecular dynamics techniques. The contribution of various energetically available adsorption sites on the deposition process is analyzed, and the work function behavior with carbon coverage is explained by the resultant electron charge density distributions.
Additive manufacturing (AM) has enabled the creation of a near infinite set of functionally graded materials (FGMs). One limitation on the manufacturability and usefulness of these materials is the presence of undesirable phases along the gradient path. For example, such phases may increase brittleness, diminish corrosion resistance, or severely compromise the printability of the part altogether. In the current work, a design methodology is proposed to plan an FGM gradient path for any number of elements that avoids undesirable phases at a range of temperatures. Gradient paths can also be optimized for a cost function. A case study is shown to demonstrate the effectiveness of the methodology in the Fe-Ni-Cr system. Paths were successfully planned from 316 L Stainless Steel (316 L SS) to pure Cr that either minimize path length or maximize separation from undesirable phases. Examinations on the stochastic variability, parameter dependency, and computational efficiency of the method are also presented. Several avenues of future research are proposed that could improve the manufacturability, utility, and performance of FGMs through gradient path design.
This study examines channeling, multiple scattering, and neutralization/re-ionization of ions scattered along the stepped Al(332) plane. Our experimental approach involves probing the surface with 1–2 keV He+ and Ne+ beams, and then systematically mapping the scattered ion fluxes over a large solid angle. This provides comprehensive ion channeling information over all directions, rather than along a few low-index azimuths, as is common practice in ion scattering spectroscopy. We first probe the surface with 2 keV He+ at near-normal incidence, and then map the backscattered particle flux (both ions and neutrals) via time of flight (TOF) spectrometry. The features contained in these maps can be correlated with axial and inter-planar channeling effects, and are reproduced well via binary collision simulations. Sensitivity to the stepped surface topography is heightened considerably for oblique ion incidence in the forward-scattering direction. In this geometry, we used 2 keV Ne+ to probe the surface and mapped the corresponding scattered fluxes of both single and multiply-charged ions. In both cases, the scattering intensity depends strongly on the precise trajectory taken along the surface, and is particularly sensitive to how extensively the incident ions interact with the step edges. We interpret the information contained in these maps by considering several mechanisms for charge transfer and double ion production. The formation of Ne++ appears to be correlated with a previously observed inelastic mechanism that occurs when the collision apsis, Rmin, is less than 0.65 Å. This contributes to an energy loss of 48 ± 8 eV for Ne+ undergoing single scattering; the Rmin threshold for this inelastic step coincides with the emergence of a distinct Ne++ peak. Using the information gained from the maps, we propose methods for extending this approach to chemisorbed layers.
Semi-coherent cube-on-cube miscible U–Zr interfaces were studied using molecular dynamics simulations. The misfit accommodation of such semi-coherent phase boundaries was characterized by a two-dimensional dislocation network model utilizing a combination of theoretical predictions and analysis of the atomic system. The dislocation networks were discussed for various stacking orientation of the adjoining phases in terms of the composition of the dislocation sets, the partitioning between edge and screw components and the associated residual elastic fields. These analyses showed that the patterning of the network of dislocations forming these phase boundaries results from the competition between a structurally-driven process (i.e., function of the lattice misfit) and a chemically-driven process (i.e., due to the miscibility between U and Zr).
Dewers, Thomas D.; Eppes, M.C.; Hancock, G.S.; Chen, X.; Arey, J.; Kiessling, S.; Moser, F.; Tannu, N.
Bedrock fracture is a key element of rock erosion and subsequent surface processes. Here, we test the hypothesis that rock's susceptibility to subcritical cracking, a specific type of fracturing, significantly drives and limits rock erosion. We measured 10Be-derived erosion rates, compressive strength, and crack characteristics on 20 outcrops of different rock units (quartzite, granite, and two metasandstones) in the northern Blue Ridge Mountains of Virginia (USA). We also measured the subcritical cracking index (n), Charles's law velocity constant (A), and fracture toughness (KIC) of samples from four of the same outcrops, representative of each rock type. Erosion rates range from 1.16 ± 0.67 to 32.3 ± 7.8 m/m.y. We find strong correlations- across the four rock units-between average erosion rates and the three subcritical cracking parameters (R2 > 0.85, p < 0.05), but not compressive strength (R2 = 0.6; p > 0.1). We also find a correlative relationship between n and outcrop fracture length (R2 = 0.91; p < 0.05). The latter correlation is consistent with that of published model predictions, further indicating a mechanistic link between subcritical cracking and rock erosion. We infer that subcritical cracking parameters closely tie to erosion rates, because subcritical cracking is the dominant process of mechanical weathering, leading to positive feedbacks relating subcritical cracking rates, crack length, porosity, and water accessibility. These data are the first that directly test and support the hypothesis that subcritical cracking can set the pace of long-term rock erosion.
The Magnetized Liner Inertial Fusion concept (MagLIF) [Slutz et al., Phys. Plasmas 17, 056303 (2010)] is being studied on the Z facility at Sandia National Laboratories. Neutron yields greater than 1012 have been achieved with a drive current in the range of 17-18 MA and pure deuterium fuel [Gomez et al., Phys. Rev. Lett. 113, 155003 (2014)]. We show that 2D simulated yields are about twice the best yields obtained on Z and that a likely cause of this difference is the mix of material into the fuel. Mitigation strategies are presented. Previous numerical studies indicate that much larger yields (10-1000 MJ) should be possible with pulsed power machines producing larger drive currents (45-60 MA) than can be produced by the Z machine [Slutz et al., Phys. Plasmas 23, 022702 (2016)]. To test the accuracy of these 2D simulations, we present modifications to MagLIF experiments using the existing Z facility, for which 2D simulations predict a 100-fold enhancement of MagLIF fusion yields and considerable increases in burn temperatures. Experimental verification of these predictions would increase the credibility of predictions at higher drive currents.
Recent research and development in exploiting quantum phenomenon have solidified the creation of large-scale quantum computers as a reality. These machines will have the ability to solve intractable problems defined on conventional computers. This has a significant impact on current cryptographic systems. A viable quantum computer will require an increase in symmetric key sizes and the replacement of asymmetric cryptographic schemes. Specifically, new constructs for public key cryptosystems must be established in order to continue to ensure the security that digital signatures and key exchange protocols provide. Understanding the post-quantum landscape is critical to applying Sandia-developed capabilities to post-quantum cyber areas. Developing a cohort of experts in this challenging and volatile space has enabled our ability to adapt to the new challenges in various customer mission areas.
A mercury-based sphygmomanometer was used in the New Mexico Tech Medical clinic because a patient had consistently high blood pressure measurements when a mercury-free sphygmomanometer was used. The mercury-based unit was chosen to verify the mercury-free measurements. When the nurse began pumping up the cuff, mercury leaked from the bottom of the machine. Prior to that use, the sphygmomanometer functioned correctly, and inspection showed no visible cracks. Knowing that mercury (Hg) was hazardous to patients, that it vaporized at room temperature, and that the clinic had no windows, the nurse moved the sphygmomanometer from the clinic to a nearby biohazard room. In addition, the nurse taped the door gaps on the outside of the biohazard room to limit exposure. The biohazard room was vented to the outside, but that fact was not commonly known by the incident response team. The floor between the clinic and biohazard room was carpeted, resulting in Hg contamination of the carpet as well as the clinic and the biohazard room.
A compelling narrative has taken hold as quantum computing explodes into the commercial sector: Quantum computing in 2018 is like classical computing in 1965. In 1965 Gordon Moore wrote his famous paper about integrated circuits, saying: "At present, [minimum cost] is reached when 50 components are used per circuit. But... the complexity for minimum component costs has increased at a rate of roughly a factor of two per year... by 1975, the number of components per integrated circuit for minimum cost will be 65,000." This narrative is both appealing (we want to believe that quantum computing will follow the incredibly successful path of classical computing!) and plausible (2018 saw IBM, Intel, and Google announce 50-qubit integrated chips). But it is also deeply misleading. Here is an alternative: Quantum computing in 2018 is like classical computing in 1938. In 1938, John Atanasoff and Clifford Berry built the very first electronic digital computer. It had no program, and was not Turing-complete. Vacuum tubes — the standard "bit" for 20 years — were still 5 years in the future. ENIAC and the achievement of "computational supremacy" (over hand calculation) wouldn't arrive for 8 years, despite the accelerative effect of WWII. Integrated circuits and the information age were more than 20 years away. Neither of these analogies is perfect. Quantum computing technology is more like 1938, while the level of funding and excitement suggest 1965 (or later!). But the point of the cautionary analogy to 1938 is simple: Quantum computing in 2018 is a research field. It is far too early to establish metrics or benchmarks for performance. The best role for neutral organizations like IEEE is to encourage and shape research into metrics and benchmarks, so as to be ready when they become necessary. This white paper presents the evidence and reasoning for this claim. We explain what it means to say that quantum computing is a "research field", and why metrics and benchmarks for quantum processors also constitute a research field. We discuss the potential for harmful consequences of prematurely establishing standards or frameworks. We conclude by suggesting specific actions that IEEE or similar organizations can take to accelerate the development of good metrics and benchmarks for quantum computing.
This report presents a specification for the Portals 4 network programming interface. Portals 4 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4 is well suited to massively parallel processing and embedded systems. Portals 4 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4 is targeted to the next generation of machines employing advanced network interface architectures that support enhanced offload capabilities.
De Supinski, Bronis R.; Scogland, Thomas R.W.; Duran, Alejandro; Klemm, Michael; Mateo, Sergi; Olivier, Stephen L.; Terboven, Christian; Mattson, Timothy G.
This paper presents an overview of the past, present and future of the OpenMP application programming interface (API). While the API originally specified a small set of directives that guided shared memory fork-join parallelization of loops and program sections, OpenMP now provides a richer set of directives that capture a wide range of parallelization strategies that are not strictly limited to shared memory. As we look toward the future of OpenMP, we immediately see further evolution of the support for that range of parallelization strategies and the addition of direct support for debugging and performance analysis tools. Looking beyond the next major release of the specification of the OpenMP API, we expect the specification eventually to include support for more parallelization strategies and to embrace closer integration into its Fortran, C and, in particular, C++ base languages, which will likely require the API to adopt additional programming abstractions.
Decalcification of cement in solutions of carbonated brine is important to a host of engineering applications, especially in subsurface service environments where cementitious materials are frequently utilized as engineered barriers for wellbore seals, as well as shaft and drift seals and waste forms for nuclear waste disposal. Analysis of leaching simulations and experiments shows that, depending on solution compositions (dissolved CO2 concentration, pH, Ca ion concentration), calcite precipitation occurring during leaching of cement in contact with carbonated brine can have a significant impact on cement reactivity, in some instances leading to complete arrest of reactivity via calcium carbonate “pore-clogging”. We present modeling and experimental results that examine the range of solution conditions that can lead to pore-clogging. Analysis of the results shows that distinct regimes of leaching behavior, based on pH and pCO2, can be used to form a framework to better understand the occurrence of pore-clogging.
This report details the activity of the project, "High Resolution Modeling and Measurements in the Arctic" spanning Fiscal Years 2016 - 2018 supported by the Sandia National Laboratories Laboratory Directed Research and Development (LDRD) program. The project's primary goal was to test the hypothesis that global climate model bias of low boundary layer clouds lacking liquid water in the Arctic could be improved by increasing horizontal resolution in the model. As model resolution is constrained by computational resources, four different model types were explored and compared to test the project's primary theory. Given the Arctic is a data-sparse region lacking robust data sets of liquid water in clouds, this project also obtained in situ measurements of low clouds with sensors on a tethered balloon system to constrain and compare with the models. Although other model biases remained, the liquid water path generally increased with resolution, supporting the original hypothesis.
We present a measurement cell that allows simultaneous measurement of second harmonic generation (SHG) and streaming potential (SP) at mineral-water interfaces with flat specimen that are suitable for non-linear optical (NLO) studies. The set-up directly yields SHG data for the interface of interest and can also be used to obtain information concerning the influence of flow on NLO signals from that interface. The streaming potential is at present measured against a reference substrate (PTFE). The properties of this inert reference can be independently determined for the same conditions. With the new cell, for the first time the SHG signal and the SP for flat surfaces have been simultaneously measured on the same surface. This can in turn be used to unambiguously relate the two observations for identical solution composition. The SHG test of the cell with a fluorite sample confirmed previously observed differences in NLO signal under flow vs. no flow conditions in sum frequency generation (SFG) investigations. As a second test surface, an inert (“hydrophobic”) OTS covered sapphire-c electrolyte interface was studied to verify the zeta-potential measurements with the new cell. For this system we obtained combined zeta-potential/SHG data in the vicinity of the point of zero charge, which were found to be proportional to each other as expected. Furthermore, on the accessible time scales of the SHG measurements no effects of flow, flow velocity and stopped flow occurred on the interfacial water structure. This insensitivity to flow for the inert surface was corroborated by concomitant molecular dynamics simulations. Finally, the set-up was used for simultaneous measurements of the two properties as a function of pH in automated titrations with an oxidic surface. Different polarization combinations obtained in two separate titrations, yielded clearly different SHG data, while under identical conditions zeta-potentials were exactly reproduced. The polarization combination that is characteristic for dipoles perpendicular to the surface scaled with the zeta-potentials over the pH-range studied, while the other did not. The work provides an advanced approach for investigating liquid/surface interactions which play a major role in our environment. The set-up can be upgraded for SFG studies, which will allow more detailed studies on the chemistry and the water structure at a given interface, but also the combined study of specific adsorption including kinetics in combination with electrokinetics. Such investigations are crucial for the basic understanding of many environmental processes from aquatic to atmospheric systems.
Radioisotopes such as Cs-137 and Co-60 are utilized in various medical, industrial, and research applications. This radiological material can be a theft or sabotage target, which necessitates a certain level of security to adequately protect it. The presented work will explore the necessity of an international security standard for devices used in clinical settings that contain high activity radiological material and the facilities that contain these devices. This standard intends to complement existing safety standards; however, it serves a very different purpose: to reduce the threat of radiological theft and sabotage while taking into full consideration the effect on the patient, user safety, and patient workflow with the aim to minimize the unwanted effects of the security measures. The proposed standard will complement existing International Atomic Energy Agency (IAEA) guidance, published in the IAEA Nuclear Security Series. While those documents primarily focus on the state, competent authorities, and regulatory agencies, the proposed industry standard will involve device manufacturers, source producers, and medical staff.
The propagation and decay of waves in a nonlocal, one-dimensional, viscoelastic medium is analyzed. Waves emanating from a source with constant amplitude applied at one end of a semi-infinite bar decay exponentially with distance from the source. A method for computing the attenuation coefficient explicitly as a function of material properties and source frequency is presented. The results are compared with direct numerical simulations. The relationship between the attenuation coefficient and the group velocity is investigated. It is shown that in the limit of long waves (or small peridynamic horizon), Stokes' law of sound attenuation is recovered.
In recent years, an increasing number of memory and spintronic devices have been developed exploiting the combination of ferromagnetic (FM) and anti-ferromagnetic (aFM) materials. Consequently, magnetic imaging based on continuous-wave (CW) ultraviolet (UV) (λ = 266nm and longer wavelength) photoemission electron microscopy (PEEM) is gaining considerable attention due to the possibility of determining magnetizations for FM and aFM materials with 10 nm lateral resolution at video rate image acquisition. This PEEM-based approach exploits the polarization-dependent photoemission yield, which is subject to the polarization vector and the FM or aFM magnetization direction. Because of this unique attribute, magnetic imaging using PEEM when coupled to a laser with multiple illumination geometries allows for characterizing in-plane and out-of-plane magnetizations. This concept, however, has not been tested using a deep-UV laser (λ = 213nm), which has a much broader application space than the longer wavelength excitation used in previous reports. The purpose of this project in FY17 was to show the proof-of-concept of magnetic circular dichroism (MCD)-PEEM imaging using a λ = 210nm pulsed laser. Our results demonstrated the feasibility of in-plane and out-of-plane magnetic imaging with the limitations in the lateral resolution, data acquisition time, and signal-to-noise ratio anticipated for using a pulsed laser of moderate power. The project goal for FY18 is to construct the automated polarization-controlled data acquisition, and to establish the new lab facility in anticipation of acquiring a state-of-the-art high-power 213nm CW laser, planned to be installed in FY19. We successfully demonstrate the former by measuring dielectric stacks with polarization-dependent photoemission yield. Extrapolating from our result, we conclude that the capability of PEEM-based magnetic imaging using a CW deep UV laser could be a potential game-changer for scientific investigations and technological developments of magnetic materials and spintronic devices. In addition, polarization controlled PEEM imaging shows the potential for ellipsometry imaging of embedded nanomaterials exploiting their subtle differences in optical constants with respect to their surrounding dielectrics.
The goal of the DOE OE ESS Safety Roadmap is to foster confidence in the safety and reliability of energy storage systems (ESSs). Three interrelated objectives support the realization of that goal: research, codes and standards, and communication/coordination. The objective focused on codes and standards is as follows: To apply research and development (R&D) to support efforts that are focused on ensuring that codes and standards are available to enable the safe implementation of ESSs in a comprehensive, non-discriminatory and science-based manner. The following activities support that objective and realization of the goal: a. Review and assess codes and standards that affect the design, installation, and operation of ESSs. b. Identify gaps in knowledge that require research and analysis that can serve as a basis for criteria in those codes and standards. c. Identify areas in codes and standards that potentially need revision or enhancement and can benefit from activities conducted under R&D. d. Develop input for new or revisions to existing codes and standards through individual stakeholders, facilitated task forces, or through laboratory staff supporting these efforts. The purpose of this special briefing paper is to support the above objective by providing information about current and upcoming efforts being conducted by U.S. standards and model code developing organizations, specifically code changes associated with the 2018 Group A International Codes (I-Codes) of the International Code Council (ICC) that are relevant to ESSs.
This study investigates the static and dynamic mechanical performance of conformal negative stiffness honeycomb structures. Negative stiffness honeycombs are capable of elastically absorbing a static or dynamic mechanical load at a predefined force threshold and returning to their initial configuration after the load is released. Most negative stiffness honeycombs rely on mechanical loading that is orthogonal to the base of the structure. In this study, a more three-dimensional design is presented that allows the honeycomb to conform to complex surfaces and protect against impacts from multiple directions. The conformal designs are additively manufactured in nylon and stainless steel and subjected to quasi-static mechanical loading and dynamic mechanical impact tests that demonstrate their impact protection capabilities.
Overall objectives of the project are: Develop a science & engineering basis for the release, ignition, and combustion behavior of hydrogen across its range of use (including high pressure and cryogenic); and, Facilitate the assessment of the safety (risk) of hydrogen systems and enable use of that information for revising regulations, codes, and standards (RCS), and permitting hydrogen fueling stations.
Shale is characterized by the predominant presence of nanometer-scale (1-100 nm) pores. The behavior of fluids in those pores directly controls shale gas storage and release in shale matrix and ultimately the wellbore production in unconventional reservoirs. Recently, it has been recognized that a fluid confined in nanopores can behave dramatically differently from the corresponding bulk phase due to nanopore confinement (Wang, 2014). CO2 and H20, either preexisting or introduced, are two major components that coexist with shale gas (predominately CH4) during hydrofracturing and gas extraction. Note that liquid or supercritical CO2 has been suggested as an alternative fluid for subsurface fracturing such that CO2 enhanced gas recovery can also serve as a CO2 sequestration process. Limited data indicate that CO2 may preferentially adsorb in nanopores (particularly those in kerogen) and therefore displace CH4 in shale. Similarly, the presence of water moisture seems able to displace or trap CH4 in shale matrix. Therefore, fundamental understanding of CH4-0O2-H20 behavior and their interactions in shale nanopores is of great importance for gas production and the related CO2 sequestration. This project focuses on the systematic study of CH4-CO2-H20 interactions in shale nanopores under high-pressure and high temperature reservoir conditions. The proposed work will help to develop new stimulation strategies to enable efficient resource recovery from fewer and less environmentally impactful wells.
The U.S. Department of Energy Office of Spent Fuel Waste Disposition (SFWD) established in fiscal year 2010 (FY10) the Spent Fuel Waste Science & Technology (SFWST) Program (formerly the Used Fuel Disposition Campaign - UFDC) program to conduct the research and development (R&D) activities related to storage, transportation and disposal of used nuclear fuel and high level nuclear waste. The Mission of the SFWST is: To identify alternatives and conduct scientific research and technology development to enable storage, transportation and disposal of used nuclear fuel and wastes generated by existing and future nuclear fuel cycles. The work package of Crystalline Disposal R&D directly supports the following SFWST objectives: Develop a fundamental understanding of disposal system performance in a range of environments for potential wastes that could arise from future nuclear fuel cycle alternatives through theory, simulation, testing, and experimentation. ; Develop a computational modeling capability for the performance of storage and disposal options for a range of fuel cycle alternatives, evolving from generic models to more robust models of performance assessment. The objective of the Crystalline Disposal R&D control account is to advance our understanding of long-term disposal of used fuel in crystalline rocks and to develop necessary experimental and computational capabilities to evaluate various disposal concepts in such media. Significant progress has been made in FY18 in both experimental and modeling arenas in evaluation of used fuel disposal in crystalline rocks, especially in model demonstration using field data. The work covers a wide range of research topics identified in the R&D plan. The major accomplishments are summarized.
The Large-N array of the Source Physics Experiment (SPE) consisted, in part, of 496 vertical component geophones that recorded the seismic wave field produced by the SPE-5 buried chemical explosion. Preliminary observations of the data showed a large degree of azimuthally dependent seismic scattering, particularly for post-P wave arrivals, hindering surface wave analysis. We document and quantify the azimuthal dependence of the wave field scattering in order to guide future coherent wave field processing methods. Specifically, we form three linear arrays, with different nominal source-receiver azimuths, by extracting a subset of the Large-N stations. For each linear array, we evaluate wave field coherence as a function of frequency and inter-station distance. For P waves, we observe that there is a strong azimuthal dependence of wave coherence, with the highest degree of scattering occurring in a northwest/southeast propagation direction. This suggests that there are structural elements beneath the Large-N array that affect the direct source to receiver body wave ray path. We also observe that the scattering of the post-P energy displays a coherence that is dependent on both frequency and azimuthal direction. This energy is preferentially coherent in the southwest-to-northeast propagation direction, consistent with the strike of the steeply dipping fault (Boundary fault) adjacent to the northeast side of the Large-N array, but only at low frequencies (<10 Hz). At higher frequencies, the azimuthally dependent wave coherence diminishes, suggesting that the scattering of high frequency portion of the post-P wave field is independent of the large-scale geologic structure at this site.
Neutron and gamma radiation spectra and dose rates were measured in and around the Ion Beam Laboratory, Building 720, at Sandia/NM. Measurements were made to support the testing of an enhanced target yielding 14 MeV neutrons from the deuterium-tritium (D-T) fusion reaction. The target room has thick concrete walls but an unshielded ceiling. Neutron and gamma radiation in and around the facility appear to be the result of skyshine. Estimates of neutron/gamma dose rates (per 10 9 source neutrons/s) at six (6) monitoring locations were made. Results indicated the need for enhanced radiological controls due to increased neutron production rates.
With the recent successful attempts against the digital control systems of critical infrastructures, there is a need to develop new defense strategies that recognize two important realities, 1) state- sponsored attackers can rely on a number of techniques including espionage, social engineering, and brute force techniques, etc. to gain access to the raw data used to control system behavior, 2) attackers can falsify operational data in manners that do not trigger conventional outlier/anomaly detection techniques in order to go undetected, which is referred to as false data injection attacks. Therefore, there is a strong need to explore another class of defense measures, referred to as physical process defense, serving as a new line of defense in the event existing defenses relying on information protection measures are breached. This physical process defenses utilize the physics and engineering models of the system to build unique signatures for genuine system behavior. If successful, the signatures would be able to detect attacks that falsify the operational data and render them harmless before they can inflict physical damage on the system. This report is focused on exploring the feasibility of physical process defenses for nuclear reactors, and their associated functional requirements to maximize their resiliency against state-sponsored, or equivalent, attackers.
NM Institute of Mining and Technology, NM Tech, reached out to Sandia National Laboratories to perform a causal analysis resulting in lessons learned for a mercury spill on campus earlier in the academic year. That causal analysis meeting was held on October 30, 2018 on the NM Tech campus and this report is a result of interviews and information gathered prior to, during, and after that meeting.
Primrose, Michael S.; Toulouse, Jean; Randall, Clive; Bock, Jonathan
Reduced strontium barium niobate, SrxBa1 − xNb2O6 (SBN), is a potential candidate for oxide thermoelectrics. In order to understand the effects of oxygen reduction on the structure and properties of SBN, room temperature Raman spectra of reduced and unreduced crystals with composition x = 0.61 (SBN61) have been measured, fitted, and compared, for incident light polarized successively along the crystallographic a- and c-axes. Unexpectedly, the low wavenumber spectra (<200 cm−1) of reduced SBN are found to display much better resolved and intense peaks than those of unreduced SBN, suggestive of a more ordered and compact lattice arrangement in reduced SBN. Shape changes of certain peaks and the disappearance or appearance of other peaks (30 cm−1/1000 cm−1) are also observed as a result of reduction. Comparison of the experimental spectra and fits of the unreduced and reduced crystals are suggestive of a redistribution of the remaining oxygen anions, structural rearrangements, and the development of supergrowth or intergrowth structures in reduced SBN. The reduced spectra are found to be very similar to the published spectra of other complex oxides such as the H-form of niobium oxide, H-Nb2O5, or TiNb2O7, which are made up of a regular layered arrangement of blocks of corner-sharing and edge-sharing oxygen octahedra. These structural changes may play an important role in the enhanced electrical conductivity of reduced SBN perpendicular to the layers.
Nuclear weapons alteration (ALT) and life extension programs (LEP) are of primary interest to the mission of Sandia National Laboratories. These programs continue to require experimental exploration and computational simulation of ductile failure scenarios to address qualification. Therefore, we invest in generating understanding about ductile failure as demonstrated though experimental procedures and computational simulation of engineering environments. In particular, we study an approach to ductile failure that incorporates the notion of phase-field fracture into our models of inelasticity appropriate for structural alloys. This report covers the formulations of the constitutive model and fracture models used within the phase-field approach and provides some numerical examples highlighting features and the state of the capability.
Fe‐Ni‐Cr stainless‐steels are important structural materials because of their superior strength and corrosion resistance. Atomistic studies of mechanical properties of stainless‐steels, however, have been limited by the lack of high‐fidelity interatomic potentials. Here using density functional theory as a guide, we have developed a new Fe‐Ni‐Cr embedded atom method potential. We demonstrate that our potential enables stable molecular dynamics simulations of stainless‐steel alloys at high temperatures, accurately reproduces the stacking fault energy—known to strongly influence the mode of plastic deformation (e.g., twinning vs. dislocation glide vs. cross‐slip)—of these alloys over a range of compositions, and gives reasonable elastic constants, energies, and volumes for various compositions. The latter are pertinent for determining short‐range order and solute strengthening effects. Our results suggest that our potential is suitable for studying mechanical properties of austenitic and ferritic stainless‐steels which have vast implementation in the scientific and industrial communities. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
Linear dimensionality reduction (DR) techniques have been applied with great success in the domain of hyperspectral image (HSI) classification. However, these methods do not take advantage of supervisory information. Instead, they act as a wholly unsupervised, disjoint portion of the classification pipeline, discarding valuable information that could improve classification accuracy. We propose Supervised Non-negative Matrix Factorization (SNMF) to remedy this problem. By learning an NMF representation of the data jointly with a multi-class classifier, we are able to improve classification accuracy in real world problems. Experimental results on a widely used dataset show state of the art performance while maintaining full linearity of the entire DR pipeline.
The progress of nanoparticle (NP)-based drug delivery has been hindered by an inability to establish structure-activity relationships in vivo. Here, using stable, monosized, radiolabeled, mesoporous silica nanoparticles (MSNs), we apply an integrated SPECT/CT imaging and mathematical modeling approach to understand the combined effects of MSN size, surface chemistry and routes of administration on biodistribution and clearance kinetics in healthy rats. We show that increased particle size from ~32- to ~142-nm results in a monotonic decrease in systemic bioavailability, irrespective of route of administration, with corresponding accumulation in liver and spleen. Cationic MSNs with surface exposed amines (PEI) have reduced circulation, compared to MSNs of identical size and charge but with shielded amines (QA), due to rapid sequestration into liver and spleen. However, QA show greater total excretion than PEI and their size-matched neutral counterparts (TMS). Overall, we provide important predictive functional correlations to support the rational design of nanomedicines.
We demonstrate an all-semiconductor coupled-cavity VCSEL designed to achieve narrow linewidth at 850 nm. A resonant AlGaAs cavity of thickness 1,937 nm (8 wavelengths) is situated below the 3-quantum-well active region and results in an effective coupled-cavity length of 36 wavelengths.
We present simulations of the force-extension curves of strong polyelectrolytes with varying intrinsic stiffness as well as specifically treating hyaluronic acid, a polyelectrolyte of intermediate stiffness. Whereas fully flexible polyelectrolytes show a high-force regime where extension increases nearly logarithmically with force, we find that the addition of even a small amount of stiffness alters the short-range structure and removes this logarithmic elastic regime. This further confirms that the logarithmic regime is a consequence of the short-ranged "wrinkles" in the flexible chain. As the stiffness increases, the force-extension curves tend toward and reach the wormlike chain behavior. Using the screened Coulomb potential and a simple bead-spring model, the simulations are able to reproduce the hyaluronic acid experimental force-extension curves for salt concentrations ranging from 1 to 500 mM. Furthermore, the simulation data can be scaled to a universal curve like the experimental data. The scaling analysis is consistent with the interpretation that, in the low-salt limit, the hyaluronic acid chain stiffness scales with salt with an exponent of -0.7, rather than either of the two main theoretical predictions of -0.5 and -1. Furthermore, given the conditions of the simulation, we conclude that this exponent value is not due to counterion condensation effects, as had previously been suggested.
We demonstrate a top-down fabrication strategy for creating a III-nitride hole array photonic crystal (PhC) with embedded quantum wells (QWs). Our photoelectrochemical (PEC) etching technique is highly bandgap selective, permitting the removal of QWs with well-defined indium (In) concentration. Room-temperature micro-photoluminescence (μ-PL) measurements confirm the removal of one multiple quantum well (MQW) while preserving a QW of differing In concentration. Moreover, PhC cavity resonances, wholly unobservable before, are present following PEC etching. Our results indicate an interesting route for creating III-nitride membranes with tailorable emission wavelengths. Our top-down fabrication approach offers exciting opportunities for III-nitride based light emitters.
Soft magnetic materials are key to the efficient operation of the next generation of power electronics and electrical machines (motors and generators). Many new materials have been introduced since Michael Faraday's discovery of magnetic induction, when iron was the only option. However, as wide bandgap semiconductor devices become more common in both power electronics and motor controllers, there is an urgent need to further improve soft magnetic materials.These improvements will be necessary to realize the full potential in efficiency, size, weight, and power of high-frequency power electronics and high-rotational speed electrical machines. Here we provide an introduction to the field of soft magnetic materials and their implementation in power electronics and electrical machines. Additionally, we review the most promising choices available today and describe emerging approaches to create even better soft magnetic materials.
Lane, J.M.D.; Leung, Kevin; Thompson, Aidan P.; Cuneo, Michael E.
Quantitative understanding and control of water and impurity desorption from steel surfaces are crucial for high-voltage, pulsed power, vacuum technology, catalysis, and environmental applications. We apply a suite of modeling techniques, ranging from electronic density functional theory, to classical molecular dynamics (MD) and grand canonical Monte Carlo (GCMC) methods to study the thermodynamics and kinetics of fast water desorption from different surfaces of hematite Fe2O3 and Cr2O3. Water binding energies on chromium oxide are found to be higher than iron oxide at zero temperature. MD simulations are conducted on Fe2O3 surfaces using thermodynamically consistent initial water inventory deduced with GCMC. The resulting time- and temperature-dependent desorption profiles on the Fe2O3 surfaces show multi-water cooperative behavior which cannot be deduced from zero temperature predictions, but which are in reasonable agreement with simple Temkin isotherm model estimates if finite temperature effects are incorporated into the Temkin binding energy parameter. Qualitatively different desorption behaviors associated with the and facets are discussed.
Feynman's ratchet is a microscopic machine in contact with two heat reservoirs, at temperatures TA and TB, that was proposed by Richard Feynman to illustrate the second law of thermodynamics. In equilibrium (TA = TB), thermal fluctuations prevent the ratchet from generating directed motion. When the ratchet is maintained away from equilibrium by a temperature difference (TA≠TB), it can operate as a heat engine, rectifying thermal fluctuations to perform work. While it has attracted much interest, the operation of Feynman's ratchet as a heat engine has not been realized experimentally, due to technical challenges. In this work, we realize Feynman's ratchet with a colloidal particle in a one dimensional optical trap in contact with two heat reservoirs: one is the surrounding water, while the effect of the other reservoir is generated by a novel feedback mechanism, using the Metropolis algorithm to impose detailed balance. We verify that the system does not produce work when TA = TB, and that it becomes a microscopic heat engine when TA≠TB. We analyze work, heat and entropy production as functions of the temperature difference and external load. As a result, our experimental realization of Feynman's ratchet and the Metropolis algorithm can also be used to study the thermodynamics of feedback control and information processing, the working mechanism of molecular motors, and controllable particle transportation.
Molecular dynamics simulations are carried out to characterize irradiation effects in TiO2 rutile, for wide ranges of temperatures (300-900 K) and primary knock-on atom (PKA) energies (1-10 keV). The number of residual defects decreases with increased temperature and decreased PKA energy, but is independent of PKA type. In the ballistic phase, more oxygen than titanium defects are produced, however, the primary residual defects are titanium vacancies and interstitials. Defect clustering depends on the PKA energy, temperature, and defect production. For some 10 keV PKAs, the largest cluster of vacancies at the peak of the ballistic phase and after annealing has up to ≈1200 and 100 vacancies, respectively. For the 10 keV PKAs at 300 K, the energy storage, primarily in residual Ti vacancies and interstitials, is estimated at 140-310 eV. It decreases with increased temperature to as little as 5-180 eV at 900 K. Selected area electron diffraction patterns and radial distribution functions confirm that although localized amorphous regions form during the ballistic phase, TiO2 regains full crystallinity after annealing.
Risk assessment plays a vital role in protecting our nation's critical infrastructure. Traditionally, such assessments have been conducted as a singular activity confined to the boarders of a particular asset or utility with little external sharing of information. In contrast other domains, e.g., disaster preparedness, cyber security, food-borne hazards, have demonstrated the benefits of sharing data, experiences and lessons learned in assessing and managing risk. Here we explore the concept of a Shared Risk Framework (SRF) in the context of critical infrastructure assessments. In this exploration, key elements of an SRF are introduced and initial instantiations demonstrated by way of three water utility assessments. Results from these three demonstrations were then combined with results from four other risk assessments developed using a different risk assessment application by a different set of analysts. Through this comparison we were able to explore potential challenges and benefits from implementation of a SRF. Challenges included both the capacity and interest of local utilities to conduct a shared risk assessment; particularly, wide scale adoption of any SRF will require a clear demonstration that such an effort supports the basic mission of the utility, adds benefit to the utility, and protects utility data from unintended access or misuse. In terms of benefits, anonymous sharing of results among utilities could provide the added benefits of recognizing and correcting bias; identifying ‘unknown, unknowns’; assisting self-assessment and benchmarking for the local utility; and providing a basis for treating shared assets and/or threats across multiple utilities.
Jones, Benjamin M.; Baughman, Carson A.; Buzard, Richard M.; Arp, Christopher D.; Grosse, Guido; Bull, Diana L.; Gunther, Frank; Nitze, Ingmar; Urban, Frank; Kasper, Jeremy L.; Frederick, Jennifer M.; Thomas, Matthew; Jones, Craig; Mota, Alejandro; Dallimore, Scott; Tweedie, Craig; Maio, Christopher; Mann, Daniel H.; Richmond, Bruce; Gibbs, Ann; Xiao, Ming; Sachs, Torsten; Iwahana, Go; Kanevskiy, Mikhail; Romanovsky, Vladimir E.
Eroding permafrost coasts are likely indicators and integrators of changes in the Arctic System as they are susceptible to the combined effects of declining sea ice extent, increases in open water duration, more frequent and impactful storms, sea-level rise, and warming permafrost. However, few observation sites in the Arctic have yet to link decadal-scale erosion rates with changing environmental conditions due to temporal data gaps. This study increases the temporal fidelity of coastal permafrost bluff observations using near-annual high spatial resolution (<1 m) satellite imagery acquired between 2008-2017 for a 9 km segment of coastline at Drew Point, Beaufort Sea coast, Alaska. Our results show that mean annual erosion for the 2007-2016 decade was 17.2 m yr-1, which is 2.5 times faster than historic rates, indicating that bluff erosion at this site is likely responding to changes in the Arctic System. In spite of a sustained increase in decadal-scale mean annual erosion rates, mean open water season erosion varied from 6.7 m yr-1 in 2010 to more than 22.0 m yr-1 in 2007, 2012, and 2016. This variability provided a range of coastal responses through which we explored the different roles of potential environmental drivers. The lack of significant correlations between mean open water season erosion and the environmental variables compiled in this study indicates that we may not be adequately capturing the environmental forcing factors, that the system is conditioned by long-term transient effects or extreme weather events rather than annual variability, or that other not yet considered factors may be responsible for the increased erosion occurring at Drew Point. Our results highlight an increase in erosion at Drew Point in the 21st century as well as the complexities associated with unraveling the factors responsible for changing coastal permafrost bluffs in the Arctic.
A thorough code verification effort has been performed on a reduced order, finite element model for one-dimensional (1D) fluid flow convectively coupled with a three-dimensional (3D) solid, referred to as the “advective bar” model. The purpose of this effort was to provide confidence in the proper implementation of this model within the sierra/aria thermal response code at Sandia National Laboratories. Furthermore the method of manufactured solutions (MMS) is applied so that the order of convergence in error norms for successively refined meshes and timesteps is investigated. Potential pitfalls that can lead to a premature evaluation of the model's implementation are described for this verification approach when applied to this unique model. Through observation of the expected order of convergence, these verification tests provide evidence of proper implementation of the model within the codebase.
Branda, Steven B.; Franco, Magdalena; D'Haeseleer, Patrik M.; Liou, Megan J.; Haider, Yasmeen; Segelke, Brent W.; El-Etr, Sahar H.
Burkholderia pseudomallei and B. mallei are the causative agents of melioidosis and glanders, respectively, and are often fatal to humans and animals. Owing to the high fatality rate, potential for spread by aerosolization, and the lack of efficacious therapeutics, B. pseudomallei and B. mallei are considered biothreat agents of concern. In this study, we investigate the proteome of Burkholderia thailandensis, a closely related surrogate for the two more virulent Burkholderia species, during infection of host cells, and compare to that of B. thailandensis in culture. Studying the proteome of Burkholderia spp. during infection is expected to reveal molecular mechanisms of intracellular survival and host immune evasion; but proteomic profiling of Burkholderia during host infection is challenging. Proteomic analyses of host-associated bacteria are typically hindered by the overwhelming host protein content recovered from infected cultures. To address this problem, we have applied bio-orthogonal noncanonical amino acid tagging (BONCAT) to B. thailandensis, enabling the enrichment of newly expressed bacterial proteins from virtually any growth condition, including host cell infection. In this study, we show that B. thailandensis proteins were selectively labeled and efficiently enriched from infected host cells using BONCAT. We also demonstrate that this method can be used to label bacteria in situ by fluorescent tagging. Finally, we present a global proteomic profile of B. thailandensis as it infects host cells and a list of proteins that are differentially regulated in infection conditions as compared to bacterial monoculture. Among the identified proteins are quorum sensing regulated genes as well as homologs to previously identified virulence factors. This method provides a powerful tool to study the molecular processes during Burkholderia infection, a much-needed addition to the Burkholderia molecular toolbox.
Understanding of the potential to injection‐induced seismicity along faults requires the response of fault zone system to spatiotemporal perturbations in pore pressure and stress. In this study, three‐dimensional (3‐D) model system consisting of the caprock, reservoir, and basement is intersected by vertical strike‐slip faults. We examine the full poroelastic behavior of the formation and perform the mechanical analysis along each fault zone using the Coulomb stress change. The magnitude, rate, and location of potential earthquakes are predicted using the spatial distribution of stresses and pore pressure over time. Rapid diffusion of pore pressure into conductive faults initiates failure, but the majority of induced seismicity occurs at deep fault zones due to poroelastic stabilization near the injection interval. Less permeable faults can be destabilized by either delayed pore pressure diffusion or poroelastic stressing. A two‐dimensional (2‐D) horizontal model, representing the interface between the reservoir and the basement, limits diffusion of pore pressure and deformation of the formation in the vertical direction that may overestimate or underestimate the potential of earthquakes along the fault. Our numerical results suggest that the 3‐D modeling of faulting system including poroelastic coupling can reduce the uncertainty in the seismic hazard prediction by considering the hydraulic and mechanical interaction between faults and bounding formations.
We report a fluid flow in a nanochannel highly depends on the wettability of the channel surface to the fluid. The permeability of the nanochannel is usually very low, largely due to the adhesion of fluid at the solid interfaces. Using molecular dynamics (MD) simulations, we demonstrate that the flow of water in a nanochannel with rough hydrophilic surfaces can be significantly enhanced by the presence of a thin layer of supercritical carbon dioxide (scCO2) at the water–solid interfaces. The thin scCO2 layer acts like an atomistic lubricant that transforms a hydrophilic interface into a super-hydrophobic one and triggers a transition from a stick- to- a slip boundary condition for a nanoscale flow. Here, this work provides an atomistic insight into multicomponent interactions in nanochannels and illustrates that such interactions can be manipulated, if needed, to increase the throughput and energy efficiency of nanofluidic systems.
A fully resolved kinetic model (particle-in-cell and direct simulation Monte Carlo for particle/photon collisions) of a near atmospheric pressure ionization wave is presented here. Fully resolving the required numerical spatial (sub-μm) and temporal scales (tens of fs) for atmospheric pressure discharges in three-dimensions is still a challenging task on modern super computers. To keep the overall problem tractable, the total number of elements are reduced by only simulating a 10° wedge rather than a full 360° geometry. The ionization wave is generated in a needle-plane configuration with a gap size of 250 μm and a background of nitrogen and helium gas. A voltage of 1500 V is applied to the anode and an initial electron and ion density of 109 cm-3 is seeded in a region near the anode electrode tip and extending towards the cathode. As these initial electrons are swept away, photoionization and photoemission create new electrons and allow the ionization front to propagate towards the cathode. Results from the 90% N2, 10% He discharge indicate that photoionization has minimal impact on plasma formation processes and cathode photoemission is the dominant mechanism for new electrons. In the 90% He, 10% N2 discharge case, however, photoionization likely has an impact as the observed locations of photoionization occur far enough away from the ionization front to allow for sufficient avalanche processes that contribute to the propagation of the ionization wave. Additionally, the electron energy distribution functions in the 90% He, 10% N2 case indicate that there is less energy loss to the low lying molecular N2 electronic states as well as the vibrational and rotational modes. This leads to higher electron energies and faster plasma development times of ∼0.4 ns for the 90% He, 10% N2 case, and ∼1.5 ns for the 90% N2, 10% He case. In addition to analysis of the ionization wave results, the overall challenges associated with simulations near atmospheric pressure discharges in three-dimensions are discussed, including the limitations of the 10° wedge that produces, at least qualitatively, minimal 3D effects.
In this work, we show that a strong upper bound on the objective of the alternating current optimal power flow (ACOPF) problem can significantly improve the effectiveness of optimization-based bounds tightening (OBBT) on a number of relaxations. We additionally compare the performance of relaxations of the ACOPF problem, including the rectangular form without reference bus constraints, the rectangular form with reference bus constraints, and the polar form. We find that relaxations of the rectangular form significantly strengthen existing relaxations if reference bus constraints are included. Overall, relaxations of the polar form perform the best. However, neither the rectangular nor the polar form dominates the other. In conclusion, with these strategies, we are able to reduce the optimality gap to less than 0.1% on all but 5 NESTA test cases with up to 300 buses by performing OBBT alone.
A previous study analyzed the convergence of probability densities for forward and inverse problems when a sequence of approximate maps between model inputs and outputs converges in L∞. Our report generalizes the analysis to cases where the approximate maps converge in LP for any 1 ≤ p < ∞. In particular, under the assumption that the approximate maps converge in LP, the convergence of probability density functions solving either forward or inverse problems is proven in V where the value of 1 ≤ q < ∞ may even be greater than p in certain cases. This greatly expands the applicability of the previous results to commonly used methods for approximating models (such as polynomial chaos expansions) that only guarantee LP convergence for some 1 ≤ p < ∞. Severalnumerical examples are also included along with numerical diagnostics of solutions and verification of assumptions made in the analysis.
The chemical and physical processes involved in the shock-to-detonation transition of energetic solids are not fully understood due to difficulties in probing the fast dynamics involved in initiation. Here, we employ shock interferometry experiments with sub-20-ps time resolution to study highly textured (110) pentaerythritol tetranitrate (PETN) thin films during the early stages of shock compression using ultrafast laser-driven shock wave methods. We observe evidence of rapid exothermic chemical reactions in the PETN thin films for interface particle velocities above ∼1.05 km/s as indicated by shock velocities and pressures well above the unreacted Hugoniot. The time scale of our experiment suggests that exothermic reactions begin less than 50 ps behind the shock front for these high-density PETN thin films. Thermochemical calculations for partially reacted Hugoniots also support this interpretation. The experimentally observed time scale of reactivity could be used to narrow possible initiation mechanisms.
Detection of low intensity light down to a few photons requires photodetectors with high gain. A new photodetector is reported based on C60-sensitized aligned carbon nanotube (CNT) transistors with an extremely high responsivity of 108 A W−1 (gain > 108) in the ultraviolet and visible range, and 720 A W−1 (gain = 940) in the infrared range. In contrast to most sensitized phototransistors that operate on the photogating effect, the new photodetector operates on the modulation of the electrons scattering in the CNTs, leading to negative photoconductivity. Comparison with similar photodetectors using random CNT networks shows the benefit of using aligned CNTs. At room temperature, the aligned CNT photodetectors are demonstrated to detect a few tens of photons per CNT.
We study two inexact methods for solutions of random eigenvalue problems in the context of spectral stochastic finite elements. In particular, given a parameter-dependent, symmetric matrix operator, the methods solve for eigenvalues and eigenvectors represented using polynomial chaos expansions. Both methods are based on the stochastic Galerkin formulation of the eigenvalue problem and they exploit its Kronecker-product structure. The first method is an inexact variant of the stochastic inverse subspace iteration [B. Sousedfk, H. C. Elman, SIAM/ASA Journal on Uncertainty Quantification 4(1), pp. 163-189, 2016]. The second method is based on an inexact variant of Newton iteration. In both cases, the problems are formulated so that the associated stochastic Galerkin matrices are symmetric, and the corresponding linear problems are solved using preconditioned Krylov subspace methods with several novel hierarchical preconditioners. The accuracy of the methods is compared with that of Monte Carlo and stochastic collocation, and the effectiveness of the methods is illustrated by numerical experiments.
The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.
This study describes the implementation of a tool to estimate latencies and data dropouts in communication networks transferring synchrophasor data defined by the C37.118 standard. The tool assigns a time tag to synchrophasor packets at the time it receives them according to a global positioning system clock and with this information is able to determine the time those packets took to reach the tool. The tool is able to connect simultaneously to multiple phasor measurement units (PMUs) sending packets at different reporting rates with different transport protocols such as user datagram protocol or transmission control protocol. The tool is capable of redistributing every packet it receives to a different device while recording the exact time this information is re-sent into the network. The results of measuring delays from a PMU using this tool are presented and compared with those of a conventional network analyzer. The results show that the tool presented in this paper measures delays more accurately and precisely than the conventional network analyzer.
Typical lithium-ion battery electrodes are porous composites comprised of active material, conductive additives, and polymeric binder, with liquid electrolyte filling the pores. The mesoscale morphology of these constituent phases has a significant impact on both electrochemical reactions and transport across the electrode, which can ultimately limit macroscale battery performance. We reconstruct published X-ray computed tomography (XCT) data from a NMC333 cathode to study mesoscale electrode behavior on an as-manufactured electrode geometry. We present and compare two distinct models that computationally generate a composite binder domain (CBD) phase that represents both the polymeric binder and conductive additives. We compare the effect of the resulting CBD morphologies on electrochemically active area, pore phase tortuosity, and effective electrical conductivity. Both dense and nanoporous CBD are considered, and we observe that acknowledging CBD nanoporosity significantly increases effective electrical conductivity by up to an order of magnitude. Properties are compared to published measurements as well as to approximate values often used in homogenized battery-scale models. All reconstructions exhibit less than 20% of the standard electrochemically active area approximation. Order of magnitude discrepancies are observed between two popular transport simulation numerical schemes (finite element method and finite volume method), highlighting the importance of careful numerical verification.
Here, a general formulation of silicon damage metrics and associated energy-dependent response functions relevant to the radiation effects community is provided. Using this formulation, a rigorous quantitative treatment of the energy-dependent uncertainty contributors is performed. This resulted in the generation of a covariance matrix for the displacement kerma, the NRT-based damage energy, and the 1-MeV(Si) equivalent damage function. Lastly, when a careful methodology is used to apply a reference 1-MeV damage value, the systematic uncertainty in the fast fission region is seen to be removed and the uncertainty for integral metrics in broad-based fission-based neutron fields is demonstrated to be significantly reduced.
This work proposes a method for model reduction of finite-volume models that guarantees the resulting reduced-order model is conservative, thereby preserving the structure intrinsic to finite-volume discretizations. The proposed reduced-order models associate with optimization problems characterized by a minimum-residual objective function and nonlinear equality constraints that explicitly enforce conservation over subdomains. Conservative Galerkin projection arises from formulating this optimization problem at the time-continuous level, while conservative least-squares Petrov–Galerkin (LSPG) projection associates with a time-discrete formulation. We equip these approaches with hyper-reduction techniques in the case of nonlinear flux and source terms, and also provide approaches for handling infeasibility. In addition, we perform analyses that include deriving conditions under which conservative Galerkin and conservative LSPG are equivalent, as well as deriving a posteriori error bounds. Numerical experiments performed on a parameterized quasi-1D Euler equation demonstrate the ability of the proposed method to ensure not only global conservation, but also significantly lower state-space errors than nonconservative reduced-order models such as standard Galerkin and LSPG projection.
Author, No; Shaner, Eric A.; Harris, Charles T.; Lewis, Rupert
We measure the charge sensitivity, Se, of a single electron transistor (SET) in the presence of strong (Vrf ~ e/Cg) spurious radio frequency (rf) signals at frequencies up to 50 MHz, where Cg is the gate capacitance. Although Se appears to degrade when exposed to Vrf, we find that broadening of conduction peaks is largely due to the measurement technique and show that Se is maintained even with strong Vrf present. We show cancellation of a known Vrf signal at 1 MHz, demonstrating that a stable bias point in the presence of rf signals is possible.
Bisht, Gautam; Riley, William J.; Hammond, Glenn E.; Lorenzetti, David M.
Improving global-scale model representations of near-surface soil moisture and groundwater hydrology is important for accurately simulating terrestrial processes and predicting climate change effects on water resources. Most existing land surface models, including the default E3SM Land Model (ELMv0), which we modify here, routinely employ different formulations for water transport in the vadose and phreatic zones. Clark et al. (2015) identified a variably saturated Richards equation flow model as an important capability for improving simulation of coupled soil moisture and shallow groundwater dynamics. In this work, we developed the Variably Saturated Flow Model (VSFM) in ELMv1 to unify the treatment of soil hydrologic processes in the unsaturated and saturated zones. VSFM was tested on three benchmark problems and results were evaluated against observations and an existing benchmark model (PFLOTRAN). The ELMv1-VSFM's subsurface drainage parameter, fd, was calibrated to match an observationally constrained and spatially explicit global water table depth (WTD) product. Optimal spatially explicit fd values were obtained for 79% of global 1.9° × 2.5° grid cells, while the remaining 21% of global grid cells had predicted WTD deeper than the observationally constrained estimate. Comparison with predictions using the default fd value demonstrated that calibration significantly improved predictions, primarily by allowing much deeper WTDs. Model evaluation using the International Land Model Benchmarking package (ILAMB) showed that improvements in WTD predictions did not degrade model skill for any other metrics. We evaluated the computational performance of the VSFM model and found that the model is about 30% more expensive than the default ELMv0 with an optimal processor layout. The modular software design of VSFM not only provides flexibility to configure the model for a range of problem setups but also allows for building the model independently of the ELM code, thus enabling straightforward testing of the model's physics against other models.
Amplification of the transverse scattered component of stimulated Brillouin scattering (SBS) can contribute to optical damage in the large aperture optics of multi-kJ lasers. Because increased laser bandwidth from optical phase modulation (PM) can suppress SBS, high energy laser amplifiers are injected with PM light. Phase modulation distributes the single-frequency spectrum of a master oscillator laser among individual PM sidebands, so a sufficiently high modulation index β can maintain the fluence for all spectral components below the SBS threshold. To avoid injection of single frequency light in the event of a PM failure, a high-speed PM failsafe system (PMFS) must be employed. Because PM is easily converted to AM, essentially all PM failsafes detect AM, with the one described here employing a novel configuration where optical heterodyne detection converts PM to AM, followed by passive AM power detection. Although the PMFS is currently configured for continuous monitoring, it can also detect PM for pulse durations ≥2 ns and could be modified to accommodate shorter pulses. This PMFS was deployed on the Z-Beamlet Laser (ZBL) at Sandia National Laboratories, as required by an energy upgrade to support programs at Sandia’s Z Facility such as magnetized liner inertial fusion. Depending on the origin of a PM failure, the PMFS responds in as little as 7 ns. In the event of an instantaneous failure during initiation of a laser shot, this response time translates to a 30–50 ns margin of safety by blocking a pulse from leaving ZBL’s regenerative amplifier, which prevents injection of single frequency light into the main amplification chain. In conclusion, the performance of the PMFS, without the need for operator interaction, conforms to the principles of engineered safety.
Deep neural networks (DNN) now outperform competing methods in many academic and industrial domains. These high-capacity universal function approximators have recently been leveraged by deep reinforcement learning (RL) algorithms to obtain impressive results for many control and decision making problems. During the past three years, research toward pruning, quantization, and compression of DNNs has reduced the mathematical, and therefore time and energy, requirements of DNN-based inference. For example, DNN optimization techniques have been developed which reduce storage requirements of VGG-16 from 552MB to 11.3MB, while maintaining the full-model accuracy for image classification. Building from DNN optimization results, the computer architecture community is taking increasing interest in exploring DNN hardware accelerator designs. Based on recent deep RL performance, we expect hardware designers to begin considering architectures appropriate for accelerating these algorithms too. However, it is currently unknown how, when, or if the 'noise' introduced by DNN optimization techniques will degrade deep RL performance. This work measures these impacts, using standard OpenAI Gym benchmarks. Our results show that mathematically optimized RL policies can perform equally to full-precision RL, while requiring substantially less computation. We also observe that different optimizations are better suited than others for different problem domains. By beginning to understand the impacts of mathematical optimizations on RL policy performance, this work serves as a starting point toward the development of low power or high performance deep RL accelerators.
Controlling polymer viscosity and flow is key to their many applications through strength and processability. The topology of the polymer i.e., linear, stars, and branched, affects the macroscopic flow characteristics of melts, where introducing one branch is sufficient to increase the viscosity significantly. While a number of studies have probed the effects of polymer topology on their rheology, the molecular understanding that underlies the macroscopic behavior remains an open question. The current study uses molecular dynamics simulations to resolve the effects of topology of polymer melts on chain mobility and viscosity in the comb regime using polyethylene as a model system. A coarse-grained model where four methylene groups constitute one bead is used, and the results are transposed to the atomistic level. We find that while the number of branches only slightly affects the chain mobility and viscosity, their length strongly impacts their behavior. The results are discussed in terms of interplay between the relaxation of the branches and reptation of the backbone where the topology of the polymer affects the tube dimensions.
Self-assembly of colloidal nanocrystals (NCs) into ordered superlattices (SLs) and supercrystals (SCs) enables new artificial NC solids for nanoelectronic and nanophotonic applications, which requires critical control of nucleation and growth conditions. Herein large SCs of PbS NCs up to ∼100 μm size were synthesized by two controlled self-assembly methods from NC solutions. Both translational symmetry and orientational ordering of the nanocrystals in the SCs were readily tuned by excess oleic acid ligands and antisolvents. Slow evaporation and the counterdiffusion method of solvents resulted in the formation of single SCs with two different SLs from the same PbS NCs: a face-centered cubic SL with weak yet complex orientational order or a body-centered cubic SL with strong and uniform particle orientation, respectively. The translational ordering was mainly determined by the effective shape of the NCs while the difference in orientational order was a result of the balance between ligand-ligand attraction and rotational entropy. The ease of the growth of large SC solids could lead to diverse NC systems and facilitate essential investigation of nanoparticle interactions and coupling based nanoelectronic and nanophotonic properties.
Recently, we have introduced a new generation of effective core potentials (ECPs) designed for accurate correlated calculations but equally useful for a broad variety of approaches. The guiding principle has been the isospectrality of all-electron and ECP Hamiltonians for a subset of valence many-body states using correlated, nearly-exact calculations. Here we present such ECPs for the 3d transition series Sc to Zn with Ne-core, i.e., with semi-core 3s and 3p electrons in the valence space. Besides genuine many-body accuracy, the operators are simple, being represented by a few gaussians per symmetry channel with resulting potentials that are bounded everywhere. The transferability is checked on selected molecular systems over a range of geometries. The ECPs show a high overall accuracy with valence spectral discrepancies typically ≈0.01-0.02 eV or better. They also reproduce binding curves of hydride and oxide molecules typically within 0.02-0.03 eV deviations over the full non-dissociation range of interatomic distances.
The U.S. Strategic Petroleum Reserve (SPR) stores crude oil in underground storage caverns that have been solution mined from salt domes. Salt falls from the sides or top of a cavern pose a potential threat to cavern and well integrity and to operational readiness. Underground storage caverns require a suspended casing, or hanging string, to extend into the bottom part of the cavern for brine injection in order to remove oil from the top of the cavern; salt falls can break hanging strings, leaving the cavern inaccessible until a well workover is performed to replace or extend the string. Detecting salt falls is difficult, as string breaks may not occur and surface pressure signals are similar to operationally induced signals. SONAR based detection is possible, but SONAR surveys are expensive and conducted infrequently. Historical records from the SPR were examined to look for possible correlations to geographic or operational causes. A library of salt fall and operational signals was developed and three case studies are presented.
Holes in germanium-rich heterostructures provide a compelling alternative for achieving spin based qubits compared to traditional approaches such as electrons in silicon. In this project, we addressed the question of whether holes in Ge/SiGe quantum wells can be confined into laterally defined quantum dots and made into qubits. Through this effort, we successfully fabricated and operated single-metal-layer quantum dot devices in Ge/SiGe in multiple devices. For single quantum dots, we measured the capacitances of the quantum dot to the surface electrodes and find that they reasonably compare to expected values based on the electrode dimensions, suggested that we have formed a lithographic quantum dot. We also compare the results to detailed self-consistent calculations of the expected potential. Finally, we demonstrate, for the first time, a double quantum dot in the Ge/SiGe material system.
In late July 2018, the Energy Storage (ES) Safety Collaborative sent a survey to their stakeholders. The survey was designed to gather input and data to "support the timely deployment of safe energy storage technologies." The survey would also help to inform decisions related to enhancing ES efforts while "streamlining opportunities for collaboration amongst all relevant stakeholders." A total of 17 questions were included in the survey: 13 multiple choice questions and 4 open response questions. A total of 51 responses were collected and presented here are some of the high-level takeaways.
A new approach for solving the electron transport equation in the upper atmosphere is derived. The problem is a very stiff boundary value problem, and to obtain an accurate numerical solution, matrix factorizations are used to decouple the fast and slow modes. A stable finite difference method is applied to each mode. This solver is applied to a simplified problem for which an exact solution exists using various versions of the boundary conditions that might arise in a natural auroral display. The numerical and exact solutions are found to agree with each other, verifying the method.
This study explores a Bayesian calibration framework for the RAMPAGE alloy potential model for Cu-Ni and Cu-Zr systems, respectively. In RAMPAGE potentials, it is proposed that once calibrated potentials for individual elements are available, the inter-species interactions can be described by fitting a Morse potential for pair interactions with three parameters, while densities for the embedding function can be scaled by two parameters from the elemental densities. Global sensitivity analysis tools were employed to understand the impact each parameter has on the MD simulation results. A transitional Markov Chain Monte Carlo algorithm was used to generate samples from the multimodal posterior distribution consistent with the discrepancy between MD simulation results and DFT data. For the Cu-Ni system the posterior predictive tests indicate that the fitted interatomic potential model agrees well with the DFT data, justifying the basic RAMPAGE assumptions. For the Cu-Zr system, where the phase diagram suggests more complicated atomic interactions than in the case of Cu-Ni, the RAMPAGE potential captured only a subset of the DFT data. The resulting posterior distribution for the 5 model parameters exhibited several modes, with each mode corresponding to specific simulation data and a suboptimal agreement with the DFT results.
In this report, we present preliminary research into nonparametric clustering methods for multi-source imagery data and quantifying the performance of these models. In many domain areas, data sets do not necessarily follow well-defined and well-known probability distributions, such as the normal, gamma, and exponential. This is especially true when combining data from multiple sources describing a common set of objects (which we call multimodal analysis), where the data in each source can follow different distributions and need to be analyzed in conjunction with one another. This necessitates nonparametric density estimation methods, which allow the data to better dictate the distribution of the data. One prominent example of multimodal analysis is multimodal image analysis, when we analyze multiple images taken using different radar systems of the same scene of interest. We develop uncertainty analysis methods, which are inherent in the use of probabilistic models but often not taken advance of, to assess the performance of probabilistic clustering methods used for analyzing multimodal images. This added information helps assess model performance and how much trust decision-makers should have in the obtained analysis results. The developed methods illustrate some ways in which uncertainty can inform decisions that arise when designing and using machine learning models.
Scope and Objectives: Kokkos Support provides cyber resources and conducts training events for current and prospective Kokkos users; In person training events are organized in various venues providing both generic Kokkos tutorials with lectures and exercises, as well as hands-on work on users applications.
Sparse matrix-matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix-matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, KKSPGEMM, to choose the right algorithm and data structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.
A framework is presented for multi-material compliance minimization in the context of continuum based topology optimization. We adopt the common approach of finding an optimal shape by solving a series of explicit convex (linear) approximations to the volume constrained compliance minimization problem. The dual objective associated with the linearized subproblems is a separable function of the Lagrange multipliers and thus, the update of each design variable is dependent only on the Lagrange multiplier of its associated volume constraint. By tailoring the ZPR design variable update scheme to the continuum setting, each volume constraint is updated independently. This formulation leads to a setting in which sufficiently general volume/mass constraints can be specified, i.e., each volume/mass constraint can control either all or a subset of the candidate materials and can control either the entire domain (global constraints) or a sub-region of the domain (local constraints). Material interpolation schemes are investigated and coupled with the presented approach. The key ideas presented herein are demonstrated through representative examples in 2D and 3D.
The increasing interest in gasification and oxy-fuel combustion of biomass has heightened the need for a detailed understanding of char gasification in industrially relevant environments (i.e., high temperature and high-heating rate). Despite innumerable studies previously conducted on gasification of biomass, very few have focused on such conditions. Consequently, in this study the high-temperature gasification behaviors of biomass-derived chars were investigated using non-intrusive techniques. Two biomass chars produced at a heating rate of approximately 104 K/s were subjected to two gasification environments and one oxidation environment in an entrained flow reactor equipped with an optical particle-sizing pyrometer. A coal char produced from a common U.S. low sulfur subbituminous coal was also studied for comparison. Both char and surrounding gas temperatures were precisely measured along the centerline of the furnace. Despite differences in the physical and chemical properties of the biomass chars, they exhibited rather similar reaction temperatures under all investigated conditions. On the other hand, a slightly lower particle temperature was observed in the case of coal char gasification, suggesting a higher gasification reactivity for the coal char. A comprehensive numerical model was applied to aid the understanding of the conversion of the investigated chars under gasification atmospheres. In addition, a sensitivity analysis was performed on the influence of four parameters (gas temperature, char diameter, char density, and steam concentration) on the carbon conversion rate. The results demonstrate that the gas temperature is the most important single variable influencing the gasification rate.
Most of the commonly used seismic discrimination approaches are designed for teleseismic and regional data. To monitor for the smallest events, some of these discriminants have been adapted for local distances (<200 km), with mixed level of success. We take advantage of the variety of seismic sources, including nontraditionally studied anthropogenic sources and the existence of a dense regional seismic network in the Utah region to evaluate amplitude ratio seismic discrimination at local distances. First, we explored phase-amplitude Pg-to-Sg ratios for multiple frequency bands to classify events in a dataset that comprises populations of single-shot surface explosions, shallow and deep ripple-fired mining blasts, mininginduced events (MIEs), and tectonic earthquakes. We achieved a success rate of about 59%-83%. Then, for the same dataset, we combined the Pg-to-Sg phase-amplitude ratios with Sg-to-Rg spectral amplitude ratios in a multivariate quadratic discriminant function (QDF) approach. For two-category pairwise classification, seven of ten population pairs show misclassification rates of about 20% or less, with five pairs showing rates of about 10% or less. The approach performs best for the pair involving the populations of single-shot explosions and MIEs. By combining both Pg-to-Sg and Rg-to-Sg ratios in the multivariate QDFs, we are able to achieve an average improvement of about 4%-14% in misclassification rates compared with Pg-to-Sg ratios alone. When all five event populations are considered simultaneously, as expected, the potential for misclassification increases, and our QDF approach using both Pg-to-Sg and Rg-to-Sg ratios achieves an average success rate of about 74% compared with the rate of about 86% for two-category pairwise classification.
In a uniform superconductor, electrons form Cooper pairs that pick up the same quantum mechanical phase for their bosonic wavefunctions. This spontaneously breaks the gauge symmetry of electromagnetism. In 1962 Josephson predicted, and it was subsequently observed, that Cooper pairs can quantum mechanically tunnel between two weakly coupled superconductors that have a phase difference Φ. The resulting supercurrent is a 2π periodic function of the phase difference Φ across the junction. This is the celebrated Josephson effect. More recently, a fractional Josephson effect related to the presence of Majorana bound states — Majoranas — has been predicted for topological superconductors. This fractional Josephson effect has a characteristic 4π periodic current–phase relation. Now, writing in Nature Materials, Chuan Li and colleagues report experiments that utilize nanoscale phase-sensitive junction technology to induce superconductivity in a fine-tuned Dirac semimetal Bi0.97Sb0.03 and discover a significant contribution of 4π periodic supercurrent in Nb–Bi0.97Sb0.03–Nb Josephson junctions under radiofrequency irradiation.
We demonstrate ultra-low power cryogenic high electron mobility transistor (HEMT) amplifiers for measurement of quantum devices. The low power consumption (few uWs) allows the amplifier to be located near the device, at the coldest cryostat stage (typically less than 100 mK). Such placement minimizes parasitic capacitance and reduces the impact of environmental noise (e.g. triboelectric noise in cabling), allowing for improvements in measurement gain, bandwidth and noise. We use custom high electron mobility transistors (HEMTs) in GaAs/A1GaAs heterostructures. These HEMTs are known to have excellent performance specifically at mK temperatures, with electron mobilities that can exceed 106 cm2 /Vs, allowing for large gain with low power consumption. Low temperature measurements of custom HEMT amplifiers at T = 4 K show a current sensitivity of 50 pA at 1 MHz bandwidth for 5 mW power dissipation, which is an improvement upon performance of amplifiers using off-the-shelf HEMTs.
X-ray diffraction measurements to characterize phase transitions of dynamically compressed high-Z matter at Mbar pressures require both sufficient photon energy and fluence to create data with high fidelity in a single shot. Large-scale laser systems can be used to generate x-ray sources above 10 keV utilizing line radiation of mid-Z elements. However, the laser-to-x-ray energy conversion efficiency at these energies is low, and thermal x-rays or hot electrons result in unwanted background. We employ polycapillary x-ray lenses in powder x-ray diffraction measurements using solid target x-ray emission from either the Z-Beamlet long-pulse or the Z-Petawatt (ZPW) short-pulse laser systems at Sandia National Laboratories. Polycapillary lenses allow for a 100-fold fluence increase compared to a conventional pinhole aperture while simultaneously reducing the background significantly. This enables diffraction measurements up to 16 keV at the few-photon signal level as well as diffraction experiments with ZPW at full intensity.
We propose a functional integral framework for the derivation of hierarchies of Landau-Lifshitz-Bloch (LLB) equations that describe the flow toward equilibrium of the first and second moments of the magnetization. The short-scale description is defined by the stochastic Landau-Lifshitz-Gilbert equation, under both Markovian or non-Markovian noise, and takes into account interaction terms that are of practical relevance. Depending on the interactions, different hierarchies on the moments are obtained in the corresponding LLB equations. Two closure Ansätze are discussed and tested by numerical methods that are adapted to the symmetries of the problem. Our formalism provides a rigorous bridge between the atomistic spin dynamics simulations at short scales and micromagnetic descriptions at larger scales.
Our goal was to develop an integrated platform for electrical control of SiV defects in diamond. The understanding and techniques we discover for electrical control have direct relevance for scalable color center based devices. More fundamentally, they can serve as a basis for developing diamond light sources and exploring color center transitions previously understood as inaccessible. While we did not meet all these goals we did develop a unique set of capabilities that allowed Sandia to distinct itself both internally and through continuing external collaborations.
Physically unclonable functions are physical entities or devices that generate unique, unpredictable responses to inputs. They are important in many security applications, including encryption, authentication, anti-counterfeiting, etc. Physical unclonable functions are based on the unavoidable randomness in the manufacturing processes and are impossible to duplicate, even by the original manufacturer. In this project, we studied the feasibility of using hardened SmCo nanomagnets as the physical implementation of physically unclonable functions. Hardened SmCo nano-magnets were fabricated through a lift-off process as well as an etch-back process. The magnetization of these nano-magnets was mapped out as a function of shapes, dimensions, and processing conditions, using magnetic force microscopy. A systematic, uncontrolled bias in the polarity was identified. Attempts to mitigate this bias were made but were unsuccessful. Nevertheless, we found in the process that blanket SmCo films themselves may serve as the desired physically unclonable functions.
Fundamental investigations of non-equilibrium gas-liquid interfaces at elevated pressure will require knowledge of gas-phase boundary conditions affecting the interface structure. To assess the feasibility of applying one-dimensional imaging of spontaneous Raman scattering to resolve species and temperature gradients in the gas-phase boundary layer above a fluoroketone liquid surface, spectra of fluoroketone (1,1,1,2,2,4,5,5,5-nonafluoro-4-(trifluoromethyl)-3-pentanone) vapor in a carrier gas (N2 or CO2) are reported over the temperature range 300 K to 700 K. The measured Raman spectra show no detectable broadband interference from laser-induced fluorescence. Features of the fluoroketone Raman spectrum overlap the CO2 spectrum, such that crosstalk corrections will be necessary for quantitative concentration measurements of CO2 in mixtures. High-resolution Raman spectra in this overlap region, acquired over the same temperature range, will enable future development of temperature dependent spectral libraries for fluoroketone.
Sandia National Laboratories (SNL) is investigating photovoltaic (PV) cell configurations, integrating them with the battery-operated Remotely Monitored Sealing Array (RMSA), and testing and evaluating performance for enhanced battery life under various environmental conditions at the K-Area Material Storage (KAMS) facility at the Savannah River Site (SRS). Unattended safeguards equipment (e.g. seals) incorporates many low-power electronic circuits, which are often powered by expensive and environmentally toxic lithium batteries. These batteries must periodically be replaced, adding a radiological hazard for both safeguards inspectors and operators. An extended field test of these prototype PV energy harvesting (EH) RMSAs at an operational nuclear facility will give additional data and allow for an analysis of this technology in a variety of realistic conditions, which will be documented in a final report. RMSAs are used for this testing, but SNL envisions energy harvesting technology may be applicable to other safeguards equipment.
This report summarizes the work performed under the Sandia LDRD project "Eyes on the Ground: Visual Verification for On-Site Inspection." The goal of the project was to develop methods and tools to assist an IAEA inspector in assessing visual and other information encountered during an inspection. Effective IAEA inspections are key to verifying states' compliance with nuclear non-proliferation treaties. In the course of this work we developed a taxonomy of candidate inspector assistance tasks, selected key tasks to focus on, identified hardware and software solution approaches, and made progress in implementing them. In particular, we demonstrated the use of multiple types of 3-d scanning technology applied to simulated inspection environments, and implemented a preliminary prototype of a novel inspector assistance tool. This report summarizes the project's major accomplishments, and gathers the abstracts and references for the publication and reports that were prepared as part of this work. We then describe work in progress that is not yet ready for publication. Approved for public release; further dissemination unlimited.
Trusting simulation output is crucial for Sandia's mission objectives. We rely on these simulations to perform our high-consequence mission tasks given our treaty obligations. Other science and modelling needs, while they may not be high-consequence, still require the strongest levels of trust to enable using the result as the foundation for both practical applications and future research. To this end, the computing community has developed work- flow and provenance systems to aid in both automating simulation and modelling execution, but to also aid in determining exactly how was some output created so that conclusions can be drawn from the data. Current approaches for workflows and provenance systems are all at the user level and have little to no system level support making them fragile, difficult to use, and incomplete solutions. The introduction of container technology is a first step towards encapsulating and tracking artifacts used in creating data and resulting insights, but their current implementation is focused solely on making it easy to deploy an application in an isolated "sandbox" and maintaining a strictly read-only mode to avoid any potential changes to the application. All storage activities are still using the system-level shared storage. This project was an initial exploration into extending the container concept to also include storage and to use writable containers, auto generated by the system, as a way to link the contained data back to the simulation and input deck used to create it.
This report summarizes the work performed under the Sandia LDRD project "Adverse Event Prediction Using Graph-Augmented Temporal Analysis." The goal of the project was to develop a method for analyzing multiple time-series data streams to identify precursors providing advance warning of the potential occurrence of events of interest. The proposed approach combined temporal analysis of each data stream with reasoning about relationships between data streams using a geospatial-temporal semantic graph. This class of problems is relevant to several important topics of national interest. In the course of this work we developed new temporal analysis techniques, including temporal analysis using Markov Chain Monte Carlo techniques, temporal shift algorithms to refine forecasts, and a version of Ripley's K-function extended to support temporal precursor identification. This report summarizes the project's major accomplishments, and gathers the abstracts and references for the publication sub-missions and reports that were prepared as part of this work. We then describe work in progress that is not yet ready for publication.