Cybersecurity for internet - connected Distributed Energy Resources (DER) is essential for the safe and reliable operation of the US power system. Many facets of DER cybersecurity are currently being investigated within different standards development organizations, research communities, and industry committees to address this critical need. This report covers DER access control guidance compiled by the Access Controls Subgroup of the SunSpec/Sandia DER Cybersecurity Workgroup. The goal of the group was to create a consensus - based technical framework to minimize the risk of unauthorized access to DER systems. The subgroup set out to define a strict control environment where users are authorized to access DER monitoring and control features through three steps: (a) user is identified using a proof-of-identity, (b) the user is authenticated by a managed database, (c) and the user is authorized for a specific level of access. DER access control also provides accountability and nonrepudiation within the power system control environment that can be used for forensic analysis and attribution in the event of a cyber-attack. This paper covers foundational requirements for a DER access control environment as well as offering a collection of possible policy, model, and mechanism implementation approaches for IEEE 1547-mandated communication protocols.
Microchannel heat exchangers have seen increasing adoption in many high-pressure applications in recent decades but are subject to particulate fouling from the relatively small channel size compared to traditional designs. Typical cleaning methods require process shutdown, heat exchanger removal, cleaning, then reassembly. The objective of this project was to refine and transfer technology to enable header design improvements for Cleaning-in-Place (CIP), allowing for reduced/negligible process interruption for the cleaning process. The technology transfer was from Sandia National Laboratories (Sandia) to Vacuum Process Engineering, Inc. (VPE). This primary purpose of CIP was developed while considering channel flow uniformity and heat exchanger cost. The project phases were to 1) capture and define potential improvement options, 2) evaluate options with both simulation and experiments, and 3) transfer design knowledge to the industry partner. These efforts resulted in improved header designs from the first known focused effort in this area. The improved designs will help the entire microchannel heat exchanger field that has applications in supercritical CO2 power cycles, hydrogen (fuel cell) vehicle fueling, liquified natural gas processing, and more.
This report explores the effects of tubing size reductions on natural gas flow from representative depleted reservoir underground storage wells and fields using basic models for coupled reservoir and pipe flow. This work was motivated by interest at the U.S. Department of Transportation, Pipeline and Hazardous Materials Safety Administration, in evaluating the effects of tubing and packer as a potential safety upgrade to implement double-barrier systems to existing underground natural gas storage wells. Reservoir and well flow models were developed from widely accepted industry equations, verified against a commercial process simulator model, and validated against field data. The study utilized U.S. operator survey data to provide context and assure that modeling parameters including aver age deliverability rates for wells and fields, operating pressures, well depths, and storage capacities were all carefully considered to keep the modeling relevant to the known range of U.S. operations. The models generally found that wells and fields with inherently low deliverability were relatively insensitive to reductions in tubing diameter, primarily because the hydraulics in those cases were controlled by reservoir properties. For the high-producing wells and fields, the models found that reducing tubing diameter could produce significant reductions in deliverability, both at the field- and well-level. When put into context with occurrence data regarding average deliverability of fields and wells, it appears that most wells and most fields across the U.S. would experience deliverability reductions on the low end of what was simulated here, generally below 20%. For fields with moderate to high deliverability, reductions were generally larger, and could reach as high as 60% for the highest-producing wells and fields.
The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA’s enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.
The AG-4000 detector can identify gas phase species using molecular fingerprinting and has potential application for SARS-CoV-2 detection in near real time. As part of the development process Sandia will utilize the biological aerosol test bed deployed at the Aerosol Complex to evaluate the penetration of MS2 bacteriophage aerosol through the Ring IR system. The objective of this project is to provide experimentally derived measurements of the RingIR AG-4000 penetration efficiency, including external exhaust filter for mitigation of exhaust aerosol and operation using MS2 bacteriophage as a biological surrogate to the SARS-CoV-2 virus.
CSPlib is an open source software library for analyzing general ordinary differential equation (ODE) systems and detailed chemical kinetic ODE systems. It relies on the computational singular perturbation (CSP) method for the analysis of these systems. The software provides support for: General ODE models (gODE model class) for computing source terms and Jacobians for a generic ODE system; TChem model (ChemElemODETChem model class) for computing source term, Jacobian, other necessary chemical reaction data, as well as the rates of progress for a homogenous batch reactor using an elementary step detailed chemical kinetic reaction mechanism. This class relies on the TChem [2] library; A set of functions to compute essential elements of CSP analysis (Kernel class). This includes computations of the eigensolution of the Jacobian matrix, CSP basis vectors and co-vectors, time scales (reciprocals of the magnitudes of the Jacobian eigenvalues), mode amplitudes, CSP pointers, and the number of exhausted modes. This class relies on the Tines library; A set of functions to compute the eigensolution of the Jacobian matrix using Tines library GPU eigensolver; A set of functions to compute CSP indices (Index Class). This includes participation indices and both slow and fast importance indices.
In this study, a complete inelastic equation of state (IEOS) for solids is developed based on a superposition of thermodynamic energy potentials. The IEOS allows for a tensorial stress state by including an isochoric hyperelastic Helmholtz potential in addition to the zero-kelvin isotherm and lattice vibration energy contributions. Inelasticity is introduced through the nonlinear equations of finite strain plasticity which utilize the temperature dependent Johnson–Cook yield model. Material failure is incorporated into the model by a coupling of the damage history variable to the energy potentials. The numerical evaluation of the IEOS requires a nonlinear solution of stress, temperature and history variables associated with elastic trial states for stress and temperature. The model is implemented into the ALEGRA shock and multi-physics code and the applications presented include single element deformation paths, the Taylor anvil problem and an energetically driven thermo-mechanical problem.
Modulation doping is a commonly adopted technique to create two-dimensional (2D) electrons or holes in semiconductor heterostructures. One constraint, however, is that the intentional dopants required for modulation doping are controlled and incorporated during the growth of heterostructures. Using undoped strained germanium quantum wells as the model material system, we show, in this work, that modulation doping can be achieved post-growth of heterostructures by ion implantation and dopant-activation anneals. The carrier density is controlled ex situ by varying the ion fluence and implant energy, and an empirical calibration curve is obtained. While the mobility of the resulting 2D holes is lower than that in undoped heterostructure field-effect transistors built using the same material, the achievable carrier density is significantly higher. Potential applications of this modulation-doping technique are discussed.
In this paper, we characterize the logarithmic singularities arising in the method of moments from the Green’s function in integrals over the test domain, and we use two approaches for designing geometrically symmetric quadrature rules to integrate these singular integrands. These rules exhibit better convergence properties than quadrature rules for polynomials and, in general, lead to better accuracy with a lower number of quadrature points. In this work, we demonstrate their effectiveness for several examples encountered in both the scalar and vector potentials of the electric-field integral equation (singular, near-singular, and far interactions) as compared to the commonly employed polynomial scheme and the double Ma–Rokhlin–Wandzura (DMRW) rules, whose sample points are located asymmetrically within triangles.
Branch, Brittany A.; Frank, Geoff; Abbott, Andrew; Lacina, David; Dattelbaum, Dana M.; Neel, Christopher; Spowart, Jonathan
With the advent of additive manufacturing (AM) techniques, a new class of shockwave mitigation and structural supports has been realized through the hierarchical assembly of polymer materials. To date, there have been a limited number of studies investigating the role of structure on shockwave localization and whether AM offers a means to tailor shockwave behavior. Of particular interest is whether the mesoscopic structure can be tailored to achieve shockwave properties in one direction of impact vs the other. Here, we illustrate directional response in engineered polymer foams. In situ time-resolved x-ray phase contrast imaging at the Advanced Photon Source was used to characterize these diode-like structures. This work offers a breakthrough in materials technology for the development of protective structures that require augmentation of shock in one direction while diminishing transmission in the opposite direction.
Water flow in nanometer or sub-nanometer hydrophilic channels bears special importance in diverse fields of science and engineering. However, the nature of such water flow remains elusive. Here, we report our molecular-modeling results on water flow in a sub-nanometer clay interlayer between two montmorillonite layers. We show that a fast advective flow can be induced by evaporation at one end of the interlayer channel, that is, a large suction pressure created by evaporation (∼818 MPa) is able to drive the fast water flow through the channel (∼0.88 m/s for a 46 Å-long channel). Scaled up for the pressure gradient to a 2 μm particle, the velocity of water is estimated to be about 95 μm/s, indicating that water can quickly flow through a μm-sized clay particle within seconds. The prediction seems to be confirmed by our thermogravimetric analysis of bentonite hydration and dehydration processes, which indicates that water transport at the early stage of the dehydration is a fast advective process, followed by a slow diffusion process. The possible occurrence of a fast advective water flow in clay interlayers prompts us to reassess water transport in a broad set of natural and engineered systems such as clay swelling/shrinking, moisture transport in soils, water uptake by plants, water imbibition/release in unconventional hydrocarbon reservoirs, and cap rock integrity of supercritical CO2 storage.
Motivated by the need to simulate the effects of underwater explosion on ship structures, we develop a new cavitating acoustics formulation. The proposed approach is consistent with existing methods where the cavitation phenomenon is captured with a bilinear constitutive law. However, the new formulation is in terms of velocity potential, as opposed to the existing displacement-potential and pressure formulations. Also unique to the proposed formulation is a new generalized time-stepping procedure specific to cavitating acoustics, which has the ability to introduce numerical damping to control frothing. Numerical examples of varying complexity are presented to illustrate the effectiveness of the proposed approach and the ability to use velocity potential as a primary field variable for cavitating acoustics simulations.
Heterojunctions of semiconductors and metals are the fundamental building blocks of modern electronics. Coherent heterostructures between dissimilar materials can be achieved by composition, doping, or heteroepitaxy of chemically different elements. Here, we report the formation of coherent single-layer 1H-1T MoS2 heterostructures by mechanical exfoliation on Au(111), which are chemically homogeneous with matched lattices but show electronically distinct semiconducting (1H phase) and metallic (1T phase) character, with the formation of these heterojunctions attributed to a combination of lattice strain and charge transfer. The exfoliation approach employed is free of tape residues usually found in many exfoliation methods and yields single-layer MoS2 with millimeter (mm) size on the Au surface. Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), scanning tunneling microscopy (STM), and scanning tunneling spectroscopy (STS) have collectively been employed to elucidate the structural and electronic properties of MoS2 monolayers on Au substrates. Bubbles in the MoS2 formed by the trapping of ambient adsorbates beneath the single layer during deposition, have also been observed and characterized. Our work here provides a basis to produce two-dimensional heterostructures which represent potential candidates for future electronic devices.
Karathanassis, Ioannis K.; Hwang, Joonsik; Koukouvinis, Phoevos; Pickett, Lyle M.
A high-speed flow visualisation set-up comprising of combined diffuse backlight illumination (DBI) and schlieren imaging has been developed to illustrate the highly transient, two-phase flow arising in a real-size optical fuel injector. The different illumination nature of the two techniques, diffuse and parallel light respectively, allows for the capturing of refractive-index gradients due to the presence of both interfaces and density gradients within the orifice. Hence, the onset of cavitation and secondary-flow motion within the sac and injector hole can be concurrently visualised. Experiments were conducted utilising a diesel injector fitted with a single-hole transparent tip (ECN spray D) at injection pressures of 700–900 bar and ambient pressures in the range of 1–20 bar. High-speed DBI images obtained at 100,000 fps revealed that the orifice, due to its tapered layout, is mildly cavitating with relatively constant cavity sheets arising mainly in regions of manufacturing imperfections. Nevertheless, schlieren images obtained at the same frame rate demonstrated that a multitude of vortices with short lifetimes arise at different scales in the sac and nozzle regions during the entire duration of the injection cycle but the vortices do not necessarily result in phase change. The magnitude and exact location of coherent vortical structures have a measurable influence on the dynamics of the spray emerging downstream the injector outlet, leading to distinct differences in the variation of its cone angle depending on the injection and ambient pressures examined.
We present a new evaluation framework for implicit and explicit (IMEX) Runge-Kutta time-stepping schemes. The new framework uses a linearized nonhydrostatic system of normal modes. We utilize the framework to investigate the stability of IMEX methods and their dispersion and dissipation of gravity, Rossby, and acoustic waves. We test the new framework on a variety of IMEX schemes and use it to develop and analyze a set of second-order low-storage IMEX Runge-Kutta methods with a high Courant-Friedrichs-Lewy (CFL) number. We show that the new framework is more selective than the 2-D acoustic system previously used in the literature. Schemes that are stable for the 2-D acoustic system are not stable for the system of normal modes.
The continental shelves of the Arctic Ocean and surrounding seas contain large stocks of organic matter (OM) and methane (CH4), representing a potential ecosystem feedback to climate change not included in international climate agreements. We performed a structured expert assessment with 25 permafrost researchers to combine quantitative estimates of the stocks and sensitivity of organic carbon in the subsea permafrost domain (i.e. unglaciated portions of the continental shelves exposed during the last glacial period). Experts estimated that the subsea permafrost domain contains ~560 gigatons carbon (GtC; 170–740, 90% confidence interval) in OM and 45 GtC (10–110) in CH4. Current fluxes of CH4 and carbon dioxide (CO2) to the water column were estimated at 18 (2–34) and 38 (13–110) megatons C yr–1, respectively. Under Representative Concentration Pathway (RCP) RCP8.5, the subsea permafrost domain could release 43 Gt CO2–equivalent (CO2e) by 2100 (14–110) and 190 Gt CO2e by 2300 (45–590), with ~30% fewer emissions under RCP2.6. The range of uncertainty demonstrates a serious knowledge gap but provides initial estimates of the magnitude and timing of the subsea permafrost climate feedback.
Networked microgrids are clusters of geographically-close, islanded microgrids that can function as a single, aggregate island. This flexibility enables customer-level resilience and reliability improvements during extreme event outages and also reduces utility costs during normal grid operations. To achieve this cohesive operation, microgrid controllers and external connections (including advanced communication protocols, protocol translators, and/or internet connection) are needed. However, these advancements also increase the vulnerability landscape of networked microgrids, and significant consequences could arise during networked operation, increasing cascading impact. To address these issues, this report seeks to understand the unique components, functions, and communications within networked microgrids and what cybersecurity solutions can be implemented and what solutions need to be developed. A literature review of microgrid cybersecurity research is provided and a gap analysis of what is additionally needed for securing networked microgrids is performed. Relevant cyber hygiene and best practices to implement are provided, as well as ideas on how cybersecurity can be integrated into networked microgrid design. Lastly, future directions of networked microgrid cybersecurity R&D are provided to inform next steps.
We present a new evaluation framework for implicit and explicit (IMEX) Runge–Kutta time-stepping schemes. The new framework uses a linearized nonhydrostatic system of normal modes. We utilize the framework to investigate the stability of IMEX methods and their dispersion and dissipation of gravity, Rossby, and acoustic waves. We test the new framework on a variety of IMEX schemes and use it to develop and analyze a set of second-order low-storage IMEX Runge–Kutta methods with a high Courant–Friedrichs–Lewy (CFL) number. We show that the new framework is more selective than the 2-D acoustic system previously used in the literature. Schemes that are stable for the 2-D acoustic system are not stable for the system of normal modes.
One of the objectives of the United States (U.S.) Department of Energy's (DOE) Office of Nuclear Energy's Spent Fuel and Waste Science and Technology Campaign is to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the U.S. has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act 1982). Any repository licensed to dispose the SNF must meet requirements regarding the longterm performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration. Of particular interest is the potential behavior of SNF in dual-purpose canisters (DPCs), which are currently being used to store and transport SNF but were not designed for permanent geologic disposal. A two-phase study has been initiated to begin examining the potential consequences, with respect to longterm repository performance, of criticality events that might occur during the postclosure period in a hypothetical repository containing DPCs. Phase I, a scoping phase, consisted of developing an approach intended to be a starting point for the development of the modeling tools and techniques that may eventually be required either to exclude criticality from or to include criticality in a performance assessment (PA) as appropriate; Phase I is documented in Price et al. (2019). The Phase I approach guided the analyses and simulations done in Phase II to further the development of these modeling tools and techniques as well as the overall knowledge base. The purpose of this report is to document the results of the analyses conducted during Phase II. The remainder of Section 1 presents the background, objective, and scope of this report, as well as the relevant key assumptions used in the Phase II analyses and simulations. Subsequent sections discuss the analyses that were conducted (Section 2), the results of those analyses (Section 3), and the summary and conclusions (Section 4). This report fulfills the Spent Fuel and Waste Science and Technology Campaign deliverable M2SF-20SN010305061.
Molecular diffusion coefficients calculated using molecular dynamics (MD) simulations suffer from finite-size (i.e., finite box size and finite particle number) effects. Results from finite-sized MD simulations can be upscaled to infinite simulation size by applying a correction factor. For self-diffusion of single-component fluids, this correction has been well-studied by many researchers including Yeh and Hummer (YH); for binary fluid mixtures, a modified YH correction was recently proposed for correcting MD-predicted Maxwell-Stephan (MS) diffusion rates. Here we use both empirical and machine learning methods to identify improvements to the finite-size correction factors for both self-diffusion and MS diffusion of binary Lennard-Jones (LJ) fluid mixtures. Using artificial neural networks (ANNs), the error in the corrected LJ fluid diffusion is reduced by an order of magnitude versus existing YH corrections, and the ANN models perform well for mixtures with large dissimilarities in size and interaction energies where the YH correction proves insufficient.
Harris, Alexandra; Mcmillan, Jeremiah T.; Listyg, Ben J.; Matzen, Laura E.; Carter, Nathan T.
The Sandia Matrices are a free alternative to the Raven’s Progressive Matrices (RPMs). This study offers a psychometric review of Sandia Matrices items focused on two of the most commonly investigated issues regarding the RPMs: (a) dimensionality and (b) sex differences. Model-data fit of three alternative factor structures are compared using confirmatory multidimensional item response theory (IRT) analyses, and measurement equivalence analyses are conducted to evaluate potential sex bias. Although results are somewhat inconclusive regarding factor structure, results do not show evidence of bias or mean differences by sex. Finally, although the Sandia Matrices software can generate infinite items, editing and validating items may be infeasible for many researchers. Further, to aide implementation of the Sandia Matrices, we provide scoring materials for two brief static tests and a computer adaptive test. Implications and suggestions for future research using the Sandia Matrices are discussed.
This paper presents new measurements of species concentrations, temperature and mixture fraction in selected regions of a turbulent ethanol spray flame. The line-Raman–LIF–COsingle bondOH setup developed at the Sandia's Combustion Research Facility is utilised to probe regions of a spray flame where laser breakdown of liquid droplets is avoided and the remaining interferences can be corrected. The spray flame is stabilised on the piloted Sydney needle spray burner, where axial translation of the liquid injecting needle in the air-blast stream can transition the spray from dilute to dense. The solution to obtaining successful measurements is found to be multifaceted and includes: the appropriate selection of flame conditions; high sensitivity of the Raman detection system permitting reduced laser energies; development of a pre-processing algorithm to reject strong droplet interferences; and application of the hybrid matrix inversion method combined with wavelet denoising to account for interference corrections and noise at the very low signal levels obtained. Unique and necessary for the successful measurements reported in this paper, a pre-processing algorithm is outlined that removes data points corrupted with strong interferences from droplets. These interferences arise from a range of sources, but the most intense are due to the laser interaction with surrounding mist or liquid fragments, such that measurements near the jet centreline are corrupted and hence discarded. Reliable measurements of mixture fraction, temperature obtained from the sum of the species number densities, and species mole fractions are reported for regions in the flames sufficiently far from the centreline. The paper demonstrates the feasibility of the judicious use of Raman scattering in turbulent spray flames, the results of which will be extremely useful for validating numerical simulations.
Domestic nuclear power is facing increased financial pressures from a variety of areas and there is pressure on these utilities to reduce their cost of operation. Currently, about 20%-30% of all on-site personnel are related to physical security. The LWRS Program recognized that R&D related to physical security could play a role in providing nuclear utilities technical and staffing efficiency options to meet their physical security commitments, but utilities often lack the technical basis or the ability to create the technical basis to realize or implement these efficiencies; towards this end, the LWRS Program created the Physical Security Pathway in September 2019. The pathway performs R&D to develop methods, tools, and technologies to optimize and modernize a nuclear power facility’s security posture. The pathway will: (1) conduct research on risk-informed techniques for physical security that account for a dynamic adversary; (2) apply advanced modeling and simulation tools to better inform physical-security scenarios and reduce uncertainties in force-on-force modeling; (3) assess benefits from proposed enhancements and novel mitigation strategies and explore changes to best practices, guides, or regulation to enable modernization; and (4) enhance and provide the technical basis for stakeholders to employ new security methods, tools, and technologies.
Two methods are examined for extending the life of tritium targets for production of 14 MeV neutrons by the 3H(2H,n)4He nuclear reaction. With thick film targets the neutron production rate decreases with time due to isotope exchange of tritium in the film with implanted deuterium. In this case, the target life is maximized by operating the target at elevated temperature where the implanted deuterium mixes by thermal diffusion throughout the entire thickness of the film. The number of neutrons obtained from a target is then proportional to the initial tritium content of the film. A novel thin-film target design was also developed and tested. With these thin-film targets, the incident deuterium is implanted through the tritide into the underlying substrate material. A thin permeation barrier layer between the tritide film and substrate, reduces the rate of tritium loss from the tritide film. Good thin-film target performance was achieved using W and Fe for the barrier and substrate materials respectively. Thin-film targets were fabricated and tested and shown to produce similar number of neutrons as thick-film targets while using only a small fraction of the amount of tritium.
CTF is a thermal hydraulic subchannel code developed to predict light water reactor (LWR) core behavior. It is a version of Coolant Boiling in Rod Arrays (COBRA) developed by Oak Ridge National Laboratory (ORNL) and North Carolina State University (NCSU) and used in the Consortium for the Advanced Simulation of LWRs (CASL). In this work, the existing CTF code verification matrix is expanded, which ensures that the code is a faithful representation of the underlying mathematical model. The suite of code verification tests are mapped to the underlying conservation equations of CTF and significant gaps are addressed. As such, five new problems are incorporated: isokinetic advection, conduction, pressure drop, convection, and pipe boiling. Convergence behavior and numerical errors are quantified for each of the tests and all tests converge at the correct rate to their corresponding analytic solution. A new verification utility that generalizes the code verification process is used to incorporate these problems into the CTF automated test suite.
Vansco, Michael F.; Caravan, Rebecca L.; Pandit, Shubhrangshu; Zuraski, Kristen; Winiberg, Frank A.F.; Au, Kendrew; Bhagde, Trisha; Trongsiriwat, Nisalak; Walsh, Patrick J.; Osborn, David L.; Percival, Carl J.; Klippenstein, Stephen J.; Taatjes, Craig A.; Lester, Marsha I.
Isoprene is the most abundant non-methane hydrocarbon emitted into the Earth's atmosphere. Ozonolysis is an important atmospheric sink for isoprene, which generates reactive carbonyl oxide species (R1R2CO+O-) known as Criegee intermediates. This study focuses on characterizing the catalyzed isomerization and adduct formation pathways for the reaction between formic acid and methyl vinyl ketone oxide (MVK-oxide), a four-carbon unsaturated Criegee intermediate generated from isoprene ozonolysis. syn-MVK-oxide undergoes intramolecular 1,4 H-atom transfer to form a substituted vinyl hydroperoxide intermediate, 2-hydroperoxybuta-1,3-diene (HPBD), which subsequently decomposes to hydroxyl and vinoxylic radical products. Here, we report direct observation of HPBD generated by formic acid catalyzed isomerization of MVK-oxide under thermal conditions (298 K, 10 torr) using multiplexed photoionization mass spectrometry. The acid catalyzed isomerization of MVK-oxide proceeds by a double hydrogen-bonded interaction followed by a concerted H-atom transfer via submerged barriers to produce HPBD and regenerate formic acid. The analogous isomerization pathway catalyzed with deuterated formic acid (D2-formic acid) enables migration of a D atom to yield partially deuterated HPBD (DPBD), which is identified by its distinct mass (m/z 87) and photoionization threshold. In addition, bimolecular reaction of MVK-oxide with D2-formic acid forms a functionalized hydroperoxide adduct, which is the dominant product channel, and is compared to a previous bimolecular reaction study with normal formic acid. Complementary high-level theoretical calculations are performed to further investigate the reaction pathways and kinetics.
Accurate synthetic spectra that rely on large Line-By-Line (LBL)-databases are used in a wide range of applications such as high temperature combustion, atmospheric re-entry, planetary surveillance and laboratory plasmas. Conventionally synthetic spectra are calculated by computing a lineshape for every spectral line in the database and adding those together, which may take multiple hours for large databases. In this paper we propose a new approach for spectral synthesis based on an integral transform: the synthetic spectrum is calculated as the integral over the product of a Voigt profile and a newly proposed three-dimensional “lineshape distribution function”, which is a function of spectral position and Gaussian- & Lorentzian width coordinates. A fast discrete version of this transform based on the Fast Fourier Transform (FFT) is proposed, which improves performance compared to the conventional approach by several orders of magnitude while maintaining accuracy. Strategies that minimize the discretization error are discussed. A Python implementation of the method is compared against state-of-the-art spectral code RADIS, and is since adopted as RADIS's default synthesis method. The synthesis of a benchmark CO2 spectrum consisting of 1.8 M spectral lines and 200k spectral points took only 3.1 s using the proposed method (1011 lines × spectral points/s), a factor ~300 improvement over the state-of-the-art, with the relative improvement generally increasing for higher number of lines and/or number of spectral points. Finally, an experimental GPU-implementation of the method was also benchmarked, which demonstrated another 2~3 orders performance increase, achieving up to 5 ∙ 1014 lines × spectral points/s.
Source code is a form of human communication, albeit one where the information shared between the programmers reading and writing the code is constrained by the requirement that the code executes correctly. Programming languages are more syntactically constrained than natural languages, but they are also very expressive, allowing a great many different ways to express even very simple computations. Still, code written by developers is highly predictable, and many programming tools have taken advantage of this phenomenon, relying on language model surprisal as a guiding mechanism. Additionally, while surprisal has been validated as a measure of cognitive load in natural language, its relation to human cognitive processes in code is still poorly understood. In this paper, we explore the relationship between surprisal and programmer preference at a small granularity—do programmers prefer more predictable expressions in code? Using meaning-preserving transformations, we produce equivalent alternatives to developer-written code expressions and run a corpus study on Java and Python projects. In general, language models rate the code expressions developers choose to write as more predictable than these transformed alternatives. Then, we perform two human subject studies asking participants to choose between two equivalent snippets of Java code with different surprisal scores (one original and transformed). We find that programmers do prefer more predictable variants, and that stronger language models like the transformer align more often and more consistently with these preferences.
Two active airflow control methods are investigated to mitigate advective and particle losses from the open aperture of a falling particle receiver. Advective losses can be reduced via active airflow methods. However, in the case of once-through suction, energy lost as enthalpy of hot air due to active airflow needs to be minimized so that thermal efficiency can be maximized. In the case of forced air injection, a properly configured aerowindow can reduce advective losses substantially for calm conditions. Although some improvement is offered in windy conditions, an aerowindow in the presence of winds does not show an ability to mitigate advective losses to values achievable by an aerowindow in the absence of wind. The two active airflow methods considered in this paper both show potential for efficiency improvement, but the improvement many not be justified given the added complexity and cost of implementing an active airflow system. While active airflow methods are tractable for a 1 MWth cavity receiver with a 1 m square aperture, the scalability of these active airflow methods is questionable when considering commercial scale receivers with 10–20 m square apertures or larger.
A strategy to optimize the thermal efficiency of falling particle receivers (FPRs) in concentrating solar power applications is described in this paper. FPRs are a critical component of a falling particle system, and receiver designs with high thermal efficiencies (~90%) for particle outlet temperatures > 700°C have been targeted for next generation systems. Advective losses are one of the most significant loss mechanisms for FPRs. Hence, this optimization aims to find receiver geometries that passively minimize these losses. The optimization strategy consists of a series of simulations varying different geometric parameters on a conceptual receiver design for the Generation 3 Particle Pilot Plant (G3P3) project using simplified CFD models to model the flow. A linear polynomial surrogate model was fit to the resulting data set, and a global optimization routine was then executed on the surrogate to reveal an optimized receiver geometry that minimized advective losses. This optimized receiver geometry was then evaluated with more rigorous CFD models, revealing a thermal efficiency of 86.9% for an average particle temperature increase of 193.6°C and advective losses less than 3.5% of the total incident thermal power in quiescent conditions.
This paper captures guidelines for the design and operation of sCO2 systems for research and development applications with specific emphasis on single-pressure pumped loops for thermal-hydraulic experiments and implications toward larger sCO2 Brayton power cycles. Direct experience with R&D systems at the kilowatt (kW), 50 kW, 200 kW, and 1 megawatt thermal scale has resulted in a recommended work flow to move a design from a thermodynamic flowsheet to a set of detailed build plans that account for industrial standards, engineering analysis, and operating experience. Analyses of operational considerations including CO2 storage, filling, pressurization, inventory management, and sensitivity to pump inlet conditions were conducted and validated during shakedown and operation of a 200 kilowatt-scale sCO2 system.
Particle emissions from a high-temperature falling particle receiver with an open aperture were modeled using computational and analytical methods and compared to U.S. particle-emissions standards to assess potential pollution and health hazards. The modeling was performed subsequent to previous on-sun testing and air sampling that did not collect significant particle concentrations at discrete locations near the tower, but the impacts of wind on collection efficiency, especial for small particles less than 10 microns, were uncertain. The emissions of both large (~350 microns) and small (<10 microns) particles were modeled for a large-scale (100 MWe) particle receiver system using expected emission rates based on previous testing and meteorological conditions for Albuquerque, New Mexico. Results showed that the expected emission rates yielded particle concentrations that were significantly less than either the pollution or inhalation metrics of 12 Pg/m3 (averaged annually) and 15 mg/m3, respectively. Particle emission rates would have to increase by a factor of ~400 (~0.1 kg/s) to begin approaching the most stringent standards.
Dannemann Dugick, Fransiska K.; Stump, Brian W.; Blom, Philip S.; Marcillo, Omar E.; Hayward, Chris T.; Carmichael, Joshua D.; Arrowsmith, Stephen
Physical and deployment factors that influence infrasound signal detection and assess automatic detection performance for a regional infrasound network of arrays in the Western U.S. are explored using signatures of ground truth (GT) explosions (yields). Despite these repeated known sources, published infrasound event bulletins contain few GT events. Arrays are primarily distributed toward the south-southeast and south-southwest at distances between 84 and 458 km of the source with one array offering azimuthal resolution toward the northeast. Events occurred throughout the spring, summer, and fall of 2012 with the majority occurring during the summer months. Depending upon the array, automatic detection, which utilizes the adaptive F-detector successfully, identifies between 14% and 80% of the GT events, whereas a subsequent analyst review increases successful detection to 24%–90%. Combined background noise quantification, atmospheric propagation analyses, and comparison of spectral amplitudes determine the mechanisms that contribute to missed detections across the network. This analysis provides an estimate of detector performance across the network, as well as a qualitative assessment of conditions that impact infrasound monitoring capabilities. Finally, the mechanisms that lead to missed detections at individual arrays contribute to network-level estimates of detection capabilities and provide a basis for deployment decisions for regional infrasound arrays in areas of interest.
The impedance bandwidth of a microstrip patch antenna may be increased by additional resonances in the antenna structure. This work uses Characteristic Mode Analysis to show that a text-book coplanar parasitically coupled patch design is well described by Coupled Mode Theory. Comparisons to other multimode patch antennas also described by Coupled Mode Theory are made, and some intrinsic properties of the coplanar parasitically coupled patch geometry are noted.
Sullivan, Eduardo'; Montoya, Eduardo; Sun, Shi K.; Vasiliauskas, Jonathan G.; Kirk, Cameron; Dixon Wilkins, Malin C.; Weck, Philippe F.; Kim, Eunja; Knight, Kevin S.; Hyatt, Neil C.
The synthesis, structure, and thermal stability of the periodate double perovskites A2NaIO6 (A= Ba, Sr, Ca) were investigated in the context of potential application for the immobilization of radioiodine. A combination of X-ray diffraction and neutron diffraction, Raman spectroscopy, and DFT simulations were applied to determine accurate crystal structures of these compounds and understand their relative stability. The compounds were found to exhibit rock-salt ordering of Na and I on the perovskite B-site; Ba2NaIO6 was found to adopt the Fm-3m aristotype structure, whereas Sr2NaIO6 and Ca2NaIO6 adopt the P21/n hettotype structure, characterized by cooperative octahedral tilting. DFT simulations determined the Fm-3m and P21/n structures of Ba2NaIO6 to be energetically degenerate at room temperature, whereas diffraction and spectroscopy data evidence only the presence of the Fm-3m phase at room temperature, which may imply an incipient phase transition for this compound. The periodate double perovskites were found to exhibit remarkable thermal stability, with Ba2NaIO6 only decomposing above 1050 °C in air, which is apparently the highest recorded decomposition temperature so far recorded for any iodine bearing compound. As such, these compounds offer some potential for application in the immobilization of iodine-129, from nuclear fuel reprocessing, with an iodine incorporation rate of 25–40 wt%. The synthesis of these compounds, elaborated here, is also compatible with both current conventional and future advanced processes for iodine recovery from the dissolver off-gas.
On December 9, 2020, Sandia National Laboratories (SNL) convened a diverse set of voices from across the federal government, the United States (U.S.) military, the private sector, and national laboratories to understand current and future trends affecting our national cyber strategy, and to illuminate the role of Federally Funded Research and Development Centers (FFRDCs) in contributing to national cyber strategy objectives.
Inertial confinement fusion approaches involve the creation of high-energy-density states through compression. High gain scenarios may be enabled by the beneficial heating from fast electrons produced with an intense laser and by energy containment with a high-strength magnetic field. Here, we report experimental measurements from a configuration integrating a magnetized, imploded cylindrical plasma and intense laser-driven electrons as well as multi-stage simulations that show fast electrons transport pathways at different times during the implosion and quantify their energy deposition contribution. The experiment consisted of a CH foam cylinder, inside an external coaxial magnetic field of 5 T, that was imploded using 36 OMEGA laser beams. Two-dimensional (2D) hydrodynamic modelling predicts the CH density reaches 9.0 g cm–3, the temperature reaches 920 eV and the external B-field is amplified at maximum compression to 580 T. At pre-determined times during the compression, the intense OMEGA EP laser irradiated one end of the cylinder to accelerate relativistic electrons into the dense imploded plasma providing additional heating. The relativistic electron beam generation was simulated using a 2D particle-in-cell (PIC) code. Finally, three-dimensional hybrid-PIC simulations calculated the electron propagation and energy deposition inside the target and revealed the roles the compressed and self-generated B-fields play in transport. During a time window before the maximum compression time, the self-generated B-field on the compression front confines the injected electrons inside the target, increasing the temperature through Joule heating. For a stronger B-field seed of 20 T, the electrons are predicted to be guided into the compressed target and provide additional collisional heating.
This is the second part of a two-part contribution on modeling of the anisotropic elastic-plastic response of aluminum 7079 from an extruded tube. Part I focused on calibrating a suite of yield and hardening functions from tension test data; Part II concentrates on evaluating those calibrations. Here, a rectangular validation specimen with a blind hole was designed to provide heterogeneous strain fields that exercise the material anisotropy, while at the same time avoiding strain concentrations near sample edges where Digital Image Correlation (DIC) measurements are difficult to make. Specimens were extracted from the tube in four different orientations and tested in tension with stereo-DIC measurements on both sides of the specimen. Corresponding Finite Element Analysis (FEA) with calibrated isotropic (von Mises) and anisotropic (Yld2004-18p) yield functions were also conducted, and both global force-extension curves as well as full-field strains were compared between the experiments and simulations. Specifically, quantitative full-field strain error maps were computed using the DIC-leveling approach proposed by Lava et al. The specimens experienced small deviations from ideal boundary conditions in the experiments, which had a first-order effect on the results. Therefore, the actual experimental boundary conditions had to be applied to the FEA in order to make valid comparisons. The predicted global force-extension curves agreed well with the measurements overall, but were sensitive to the boundary conditions in the nonlinear regime and could not differentiate between the two yield functions. Interrogation of the strain fields both qualitatively and quantitatively showed that the Yld2004-18p model was clearly able to better describe the strain fields on the surface of the specimen compared to the von Mises model. These results justify the increased complexity of the calibration process required for the Yld2004-18p model in applications where capturing the strain field evolution accurately is important, but not if only the global force-extension response of the elastic–plastic region is of interest.
Monolithic integration of lattice-mismatched semiconductor materials opens up access to a wide range of bandgaps and new device functionalities. However, it is inevitably accompanied by defect formation. A thorough analysis of how these defects propagate and interact with interfaces is critical to understanding their effects on device parameters. In this study, we present a comprehensive study of dislocation networks in the GaSb/GaAs heteroepitaxial system using transmission electron microscopy (TEM). Specifically, the sample analyzed is a GaSb film grown on GaAs using dislocation–reduction strategies such as interfacial misfit array formation and introduction of a dislocation filtering layer. Using various TEM techniques, it is shown that such an analysis can reveal important information on the dislocation behavior including filtering mechanism, types of dislocation reactions, and other interactions with interfaces. A novel method that enables plan-view imaging of deeply embedded interfaces using TEM and a demonstration of independent imaging of different dislocation types are also presented. While clearly effective in characterizing dislocation behavior in GaSb/GaAs, we believe that the methods outlined in this article can be extended to study other heteroepitaxial material systems.
Accurate and timely weather predictions are critical to many aspects of society with a profound impact on our economy, general well-being, and national security. In particular, our ability to forecast severe weather systems is necessary to avoid injuries and fatalities, but also important to minimize infrastructure damage and maximize mitigation strategies. The weather community has developed a range of sophisticated numerical models that are executed at various spatial and temporal scales in an attempt to issue global, regional, and local forecasts in pseudo real time. The accuracy however depends on the time period of the forecast, the nonlinearities of the dynamics, and the target spatial resolution. Significant uncertainties plague these predictions including errors in initial conditions, material properties, data, and model approximations. To address these shortcomings, a continuous data collection occurs at an effort level that is even larger than the modeling process. It has been demonstrated that the accuracy of the predictions depends on the quality of the data and is independent to a certain extent on the sophistication of the numerical models. Data assimilation has become one of the more critical steps in the overall weather prediction business and consequently substantial improvements in the quality of the data would have transformational benefits. This paper describes the use of infrasound inversion technology, enabled through exascale computing, that could potentially achieve orders of magnitude improvement in data quality and therefore transform weather predictions with significant impact on many aspects of our society.
Sandia National Laboratories (SNL) is a multi-purpose engineering and science laboratory owned by the U.S. Department of Energy (DOE)/National Nuclear Security Administration. SNL is managed and operated by Sandia Corporation (Sandia), a wholly-owned subsidiary of Lockheed Martin Corporation. Sandia National Laboratories, New Mexico (SNL/NM) is located within the boundaries of Kirtland Air Force Base (KAFB), southeast of the City of Albuquerque in Bernalillo County, New Mexico. The Mixed Waste Landfill (MWL) is located 4 miles south of SNL/NM central facilities and 5 miles southeast of Albuquerque International Sunport, in the north-central portion of Technical Area (TA)-III. The MWL disposal area comprises 2.6 acres. During operations, the MWL accepted containerized and other low-level radioactive waste and minor amounts of mixed waste from SNL/NM research facilities and off-site DOE and U.S. Department of Defense generators from March 1959 to December 1988. More specific information regarding the MWL inventory and past disposal practices is presented in the MWL Phase 2 RCRA Facility Investigation Report (Peace et al. September 2002) and the extensive MWL Administrative Record.
In the subsurface, MgO engineered barriers are employed at the Waste Isolation Pilot Plant (WIPP), a transuranic waste repository near Carlsbad, NM. During service, the MgO will be exposed to high concentration brine environments and may form stable intermediate phases that can alter the barriers effectiveness. Here, MgO was aged in water and three different brine solutions. X-ray diffraction (XRD) and 1H nuclear magnetic resonance (NMR) analysis were performed to identify the formation of secondary phases. After aging, ~4% of the MgO was hydrated and fine-grained powders resulted in greater loss of crystallinity than hard granular grains. 1H magic angle spinning (MAS) NMR spectra resolved minor phases not visible in XRD, indicating that diverse 1H environments are present along with Mg(OH)2. Density functional theory (DFT) simulations for several proposed Mg-O-H, Mg-CI-O-H, and Na-O-H containing phases were performed to index peaks in the experimental 1H MAS NMR spectra. While proposed intermediate crystal structures exhibited overlapping 1H NMR peaks, Mg-O-H intermediates were attributed to the growth of the 1.0-0.0ppm peak while the Mg-CI-O-H structures contributed to the 2.5- 5.0ppm peak in the chloride containing brines. Overall, NMR analysis of aged MgO indicates the formation of a range of possible intermediate structures that cannot be resolved with XRD analysis alone.
Our goal was to characterize certain aspects of shaped charges. In order to determine the pressure field created by the jet and the jet velocity, I worked with and modified simulations using CTH, a code developed at Sandia. I was able to manipulate and modify certain variables in order to observe their effects and measure the pressure and velocities at different points in the simulation.
Chris Saunders and three technologists are in high demand from Sandia’s deep learning teams, and they’re kept busy by building new clusters of computer nodes for researchers who need the power of supercomputing on a smaller scale. Sandia researchers working on Laboratory Directed Research & Development (LDRD) projects, or innovative ideas for solutions on short timeframes, formulate new ideas on old themes and frequently rely on smaller cluster machines to help solve problems before introducing their code to larger HPC resources. These research teams need an agile hardware and software environment where nascent ideas can be tested and cultivated on a smaller scale.
Sandia has been developing and supporting data transfer tools for over 20 years and has the expertise to take DOE into the Extreme Scale era. In looking at Exascale and beyond (Extreme Scale Computing), data sets can be thousands of 500TBs in size, a single file can be in the 100TB range, and billions of files are expected. Huge bursts of data need to be transferred, even today. While data archiving is often not thought about, it is an integral part of the full data management path when data is generated on HPC systems. In order to move generated data to its final resting place (data archive) or to transfer between file systems, a capable data transfer tool is required.
Carnac, located at Sandia's California site, is an institutional cluster for Emulytics that provides security researchers with resources to model enterprise computer networks and evaluate how resilient they are from attacks. While multiple Emulytics cluster computers have been built at Sandia, Carnac is the first system that was developed as an institutional resource that can be shared among different groups with disparate requirements.
The Rapid Sample Insertion/Extraction System for Gamma Irradiation, otherwise known as the "rabbit" system, was a four-week long project which included many different aspects; from coding an Arduino to building PVC piping to 3-D printing the "rabbit" capsules. The "rabbit" system is a system of PVC piping that allows a quick and efficient transfer of materials into/out of one of the irradiation chambers in the Gamma Irradiation Facility (GIF) with the use of a 3-D printed "rabbit." This "rabbit" encapsulates material to be irradiated and carries it from a position outside of the irradiation chamber to the basket inside of the chamber. The main purpose of this system is to save time and provide more exact data without any delays that normally occur when a person has to enter the chamber, retrieve data, and then analyze the data. This system should take measurements and retrieve the data instantaneously. The way in which the "rabbit" is sent through the PVC piping is with an advanced bi-directional, high-throughput pneumatic system, or a shop vacuum cleaner. When the vacuum is set to blow or suck then the "rabbit" will be pulled through the PVC piping to its intended destination and will hit sensors along the sides of the tubing when it reaches the end of the piping. These sensors tell the Arduino that the "rabbit" is finished moving throughout the tubing and stops a timer. Another timer is used to see how long the "rabbit" is being irradiated so when the "rabbit" reaches the sensors in the basket in the irradiation chamber another timer is started and it ends when the sensors no longer detect the "rabbit," which means that it has begun its journey back to the starting point.
Hoekstra, Robert J.; Malone, C.M.; Montoya, D.R.; Ferencz, M.R.; Kuhl, A.L.; Wagner, J.
The review was conducted on May 8-9, 2017 at the University of Utah. Overall the review team was impressed with the work presented and found that the CCMSC had met or exceeded the Year 3 milestones. Specific details, comments, and recommendations are included in this document.
Millions of dollars and significant resources are being spent by developers of utility-scale solar photovoltaic (PV) and concentrating solar power (CSP) plants to address federal and local requirements regarding glare and avian hazards. Solar glare can occur from the glass surfaces of PV modules and from mirrors in CSP systems, which can produce safety and health risks for pilots, motorists, and residents located near these systems. In addition, concentrated solar flux at CSP plants has the potential to singe birds as they fly through regions of high solar flux. This work will develop tools to characterize and mitigate these potential hazards, which will address regulatory policies and reduce costs and efforts associated with the proposed deployment of gigawatts of solar energy systems throughout the nation. The development of standardized and publicly available tools to address these regulatory policies and ensure public and environmental safety is an appropriate role for the government.
This work is developing particle flow control and measurement methods for next-generation concentrating solar power systems employing particle-based technologies. Particle receivers are being pursued to provide substantial performance improvements through higher temperatures (>700 °C) for more efficient and cost-effective CSP systems with direct storage for electricity generation, process heating, thermochemistry, and solar fuels production. This specific work will develop technologies that enable more efficient particle receivers and scalable methods to accommodate variable irradiances during commercial on-sun operation. The development of next-generation particle-receiver systems and methods with potentially high consequences for improved performance and cost savings for CSP applications is an appropriate role for the government.
Particle receivers are being pursued to provide substantial performance improvements through higher temperatures (>700 °C) for more efficient and cost-effective concentrating solar power (CSP) systems with direct storage. However, the interface between the solar-collection and power-block subsystems - a high-temperature particle/supercritical CO2 (sCO2) heat exchanger - has not been developed. The objective of this project is to design, construct, and test a first-of-a-kind particle-to-sCO2 heat exchanger. This work will enable emerging sCO2 power cycles that have the potential to meet SunShot targets of 50% thermal-to-electric efficiency, dry cooling with 40 °C ambient temperature, and $0.06/kWh for CSP systems. The development of next-generation particle-based systems and methods with potentially high consequences for improved performance and cost savings for CSP applications is an appropriate role for the government.
After decades of R&D, quantum computers comprising more than 2 qubits are appearing. If this progress is to continue, the research community requires a capability for precise characterization (“tomography”) of these enlarged devices, which will enable benchmarking, improvement, and finally certification as mission-ready. As world leaders in characterization -- our gate set tomography (GST) method is the current state of the art – the project team is keenly aware that every existing protocol is either (1) catastrophically inefficient for more than 2 qubits, or (2) not rich enough to predict device behavior. GST scales poorly, while the popular randomized benchmarking technique only measures a single aggregated error probability. This project explored a new insight: that the combinatorial explosion plaguing standard GST could be avoided by using an ansatz of few-qubit interactions to build a complete, efficient model for multi-qubit errors. We developed this approach, prototyped it, and tested it on a cutting-edge quantum processor developed by Rigetti Quantum Computing (RQC), a US-based startup. We implemented our new models within Sandia’s PyGSTi open-source code, and tested them experimentally on the RQC device by probing crosstalk. We found two major results: first, our schema worked and is viable for further development; second, while the Rigetti device is indeed a “real” 8-qubit quantum processor, its behavior fluctuated significantly over time while we were experimenting with it and this drift made it difficult to fit our models of crosstalk to the data.
Propagation of thermal events from one damaged cell in a battery module to adjacent cells is a safety concern. A team of researchers from Sandia National Laboratories (SNL) and the National Renewable Energy Laboratory (NREL) have developed a “safety-map” to evaluate propensity for failure propagation. The model results were used to evaluate passive thermal management designs for Li-ion battery modules.
Ozkaya, Yusuf; Sariyuce, A.E.; Catalyurek, Umit V.; Pinar, Ali P.
Centrality rankings such as degree, closeness, betweenness, Katz, PageRank, etc. are commonly used to identify critical nodes in a graph. These methods are based on two assumptions that restrict their wider applicability. First, they assume the exact topology of the network is available. Secondly, they do not take into account the activity over the network and only rely on its topology. However, in many applications, the network is autonomous, vast, and distributed, and it is hard to collect the exact topology. At the same time, the underlying pairwise activity between node pairs is not uniform and node criticality strongly depends on the activity on the underlying network. In this paper, we propose active betweenness cardinality, as a new measure, where the node criticalities are based on not the static structure, but the activity of the network. We show how this metric can be computed efficiently by using only local information for a given node and how we can find the most critical nodes starting from only a few nodes. We also show how this metric can be used to monitor a network and identify failed nodes. We present experimental results to show effectiveness by demonstrating how the failed nodes can be identified by measuring active betweenness cardinality of a few nodes in the system.
The US Department of Energy (DOE) Nuclear Energy Research Initiative funded the design and construction of the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories. The start-up of the experiment facility and the execution of the experiments described here were funded by the DOE Nuclear Criticality Safety Program. The 7uPCX is designed to investigate critical systems with fuel for light water reactors in the enrichment range above 5% 235U. The 7uPCX assembly is a water-moderated and -reflected array of aluminum-clad square-pitched U(6.90%)O2 fuel rods. Other critical experiments performed in the 7uPCX assembly are documented in LEU-COMP-THERM-078, LEU-COMP-THERM-080, LEU-COMPTHERM- 096, LEU-COMP-THERM-097, and LEU-COMP-THERM-101. The twenty-seven critical experiments in this series were performed in 2020 in the SCX at the Sandia Pulsed Reactor Facility. The experiments are grouped by fuel rod pitch. Case 1 is a base case with a pitch of 0.8001 cm and no water holes in the array. Cases 2 through 6 have the same pitch as Case 1 but contain various configurations with water holes, providing slight variations in the fuel-to-water ratio. Similarly, Case 7 is a base case with a pitch of 0.854964 cm and no water holes in the array. Cases 8 through 11 have the same pitch as Case 7 but contain various configurations with water holes. Cases 12 through 15 have a pitch of 1.131512 cm and differ according to the number of water holes in the array, with Case 12 having no water holes. Cases 16 through 19 have a pitch of 1.209102 cm and differ according to number of water holes in the array, with Case 16 having no water holes. Cases 20 through 23 have a pitch of 1.6002 cm and differ according to number of water holes in the array, with Case 20 having no water holes. Cases 24 through 27 have a pitch of 1.709928 cm and differ according to number of water holes in the array, with Case 24 having no water holes. As the experiment case number increases, the fuel-to-water volume ratio decreases.
The accelerating chemical effect of ozone addition on the oxidation chemistry of methyl hexanoate [CH3(CH2)4C(= O)OCH3] was investigated over a temperature range from 460 to 940 K. Using an externally heated jet-stirred reactor at p = 700 Torr (residence time τ = 1.3 s, stoichiometry ψ = 0.5, 80% argon dilution), we explored the relevant chemical pathways by employing molecular-beam mass spectrometry with electron and single-photon ionization to trace the temperature dependencies of key intermediates, including many hydroperoxides. In the absence of ozone, reactivity is observed in the so-called low-temperature chemistry (LTC) regime between 550 and 700 K, which is governed by hydroperoxides formed from sequential O2 addition and isomerization reactions. At temperatures above 700 K, we observed the negative temperature coefficient (NTC) regime, in which the reactivity decreases with increasing temperatures, until near 800 K, where the reactivity increases again. Upon addition of ozone (1000 ppm), the overall reactivity of the system is dramatically changed due to the time scale of ozone decomposition in comparison to fuel oxidation time scales of the mixtures at different temperatures. While the LTC regime seems to be only slightly affected by the addition of ozone with respect to the identity and quantity of the observed intermediates, we observed an increased reactivity in the intermediate NTC temperature range. Furthermore, we observed experimental evidence for an additional oxidation regime in the range near 500 K, herein referred to as the extreme low-temperature chemistry (ELTC) regime. Experimental evidence and theoretical rate constant calculations indicate that this ELTC regime is likely to be initiated by H abstraction from methyl hexanoate via O atoms, which originate from thermal O3 decomposition. The theoretical calculations show that the rate constants for methyl ester initiation via abstraction by O atoms increase dramatically with the size of the methyl ester, suggesting that ELTC is likely not important for the smaller methyl esters. Experimental evidence is provided indicating that, similar to the LTC regime, the chemistry in the ELTC regime is dominated by hydroperoxide chemistry. However, mass spectra recorded at various reactor temperatures and at different photon energies provide experimental evidence of some differences in chemical species between the ELTC and the LTC temperature ranges.
Nine in ten major outages in the US have been caused by hurricanes. Long-term outage risk is a function of climate change-triggered shifts in hurricane frequency and intensity; yet projections of both remain highly uncertain. However, outage risk models do not account for the epistemic uncertainties in physics-based hurricane projections under climate change, largely due to the extreme computational complexity. Instead they use simple probabilistic assumptions to model such uncertainties. Here, we propose a transparent and efficient framework to, for the first time, bridge the physics-based hurricane projections and intricate outage risk models. We find that uncertainty in projections of the frequency of weaker storms explains over 95% of the uncertainty in outage projections; thus, reducing this uncertainty will greatly improve outage risk management. We also show that the expected annual fraction of affected customers exhibits large variances, warranting the adoption of robust resilience investment strategies and climate-informed regulatory frameworks.
This article concerns modeling unsaturated deformable porous media as an equivalent single-phase and single-force state peridynamic material through the effective force state. The balance equations of linear momentum and mass of unsaturated porous media are presented by defining relevant peridynamic states. The energy balance of unsaturated porous media is utilized to derive the effective force state for the solid skeleton that is an energy conjugate to the nonlocal deformation state of the solid, and the suction force state. Through an energy equivalence, a multiphase constitutive correspondence principle is built between classical unsaturated poromechanics and peridynamic unsaturated poromechanics. The multiphase correspondence principle provides a means to incorporate advanced constitutive models in classical unsaturated porous theory directly into unsaturated peridynamic poromechanics. Numerical simulations of localized failure in unsaturated porous media under different matric suctions are presented to demonstrate the feasibility of modeling the mechanical behavior of such three-phase materials as an equivalent single-phase peridynamic material through the effective force state concept.
Hot-electron generation has been a topic of intense research for decades for numerous applications ranging from photodetection and photochemistry to biosensing. Recently, the technique of hot-electron generation using non-radiative decay of surface plasmons excited by metallic nanoantennas, or meta-atoms, in a metasurface has attracted attention. These metasurfaces can be designed with thicknesses on the order of the hot-electron diffusion length. The plasmonic resonances of these ultrathin metasurfaces can be tailored by changing the shape and size of the meta-atoms. One of the fundamental mechanisms leading to generation of hot-electrons in such systems is optical absorption, therefore, optimization of absorption is a key step in enhancing the performance of any metasurface based hot-electron device. Here we utilized an artificial intelligence-based approach, the genetic algorithm, to optimize absorption spectra of plasmonic metasurfaces. Using genetic algorithm optimization strategies, we designed a polarization insensitive plasmonic metasurface with 90% absorption at 1550 nm that does not require an optically thick ground plane. We fabricated and optically characterized the metasurface and our experimental results agree with simulations. Finally, we present a convolutional neural network that can predict the absorption spectra of metasurfaces never seen by the network, thereby eliminating the need for computationally expensive simulations. Our results suggest a new direction for optimizing hot-electron based photodetectors and sensors.
Suri, Pranav K.; Nathaniel, James E.; Li, Nan; Baldwin, Jon K.; Wang, Yongqiang; Hattar, Khalid M.; Taheri, Mitra L.
Gold is a noble metal typically stable as a solid in a face-centered cubic (FCC) structure under ambient conditions; however, under particular circumstances aberrant allotropes have been synthesized. In this work, we document the phase transformation of 25 nm thick nanocrystalline (NC) free-standing gold thin-film via in situ ion irradiation studied using atomic-resolution transmission electron microscopy (TEM). Utilizing precession electron diffraction (PED) techniques, crystallographic orientation and the radiation-induced relative strains were measured and furthermore used to determine that a combination of surface and radiation-induced strains lead to an FCC to hexagonal close packed (HCP) crystallographic phase transformation upon a 10 dpa radiation dose of Au4+ ions. Contrary to previous studies, HCP phase in nanostructures of gold was stabilized and did not transform back to FCC due to a combination of size effects and defects imparted by damage cascades.
In this paper, two modifications are introduced for improving the accuracy, versatility, and robustness of a class of hybrid methods for radiation transport. In general, such methods are constructed by splitting the radiative flux into collided and uncollided components to which low- and high-resolution angular approximations are applied, respectively. In this work we focus on discrete ordinates discretizations of high and low order. The first modification we introduce changes the way in which the collided component is mapped into the uncollided component at the end of each time step in a simulation. The new mapping is a Nyström-type reconstruction that is applicable to arbitrary discrete ordinates quadratures, is guaranteed to preserve positivity of the solution provided that all ordinate weights are positive, is significantly more accurate than previous methods, and can be readily extended to other discretizations such as moment methods, finite element methods, and diffusion approximations. The second modification leverages integral deferred correction (IDC) to iteratively correct for the splitting error introduced by the inconsistency in angular discretization between the collided and uncollided components, in addition to improving the accuracy of the low-order temporal error that is treated by traditional IDC methods. Numerical tests in one- and two-dimensional geometries are used to demonstrate the increased accuracy and efficiency of the proposed modifications. It is found that the two techniques combined yield methods with solution accuracy and memory requirements comparable to that of monolithic discrete ordinates methods while reducing runtime by as much as a factor of between two and ten, depending on the problem.
Smectite (e.g., Montmorillonite): phyllosilicate minerals found in bentonites. Bentonites have been considered as key backfill barrier materials in deep geological nuclear waste repository concepts. Swelling/shrinking of montmorillonite (MMT) occurs with increasing/decreasing relative humidity. Our research question is, "Microscopically, how does the hydration/dehydration process occur?"
Steinberger, William M.; Ruch, Marc L.; Di Fulvio, Angela; Marleau, P.; Clarke, Shaun D.; Pozzi, Sara A.
A compact radiation imaging system capable of detecting, localizing, and characterizing special nuclear material (e.g. highly-enriched uranium, plutonium…) would be useful for national security missions involving inspection, emergency response, or war-fighters. Previously-designed radiation imaging systems have been large and bulky with significant portions of volume occupied by photomultiplier tubes (PMTs). The prototype imaging system presented here uses silicon photomultipliers (SiPMs) in place of PMTs because SiPMs are much more compact and operate at low power and voltage. The SiPMs are coupled to the ends of eight stilbene organic scintillators, which have an overall volume of 5.74 × 5.74 × 7.11 cm3. The prototype dual-particle imager’s capabilities were evaluated by performing measurements with a 252Cf source, a sphere of 4.5 kg of alpha-phase weapons-grade plutonium known as the BeRP ball, a 6 kg sphere of neptunium, and a canister of 3.4 kg of plutonium oxide (7% 240Pu and 93% 239Pu). These measurements demonstrate neutron spectroscopic capabilities, a neutron image resolution for a Watt spectrum of 9.65 ± 0.94° in the azimuthal direction and 22.59 ± 5.81° in the altitude direction, imaging of gamma rays using organic scintillators, and imaging of multiple sources in the same field of view.
Conventional electrodes and associated positioning systems for intracellular recording from single neurons in vitro and in vivo are large and bulky, which has largely limited their scalability. Further, acquiring successful intracellular recordings is very tedious, requiring a high degree of skill not readily achieved in a typical laboratory. We report here a robotic, MEMS-based intracellular recording system to overcome the above limitations associated with form factor, scalability, and highly skilled and tedious manual operations required for intracellular recordings. This system combines three distinct technologies: (1) novel microscale, glass–polysilicon penetrating electrode for intracellular recording; (2) electrothermal microactuators for precise microscale movement of each electrode; and (3) closed-loop control algorithm for autonomous positioning of electrode inside single neurons. Here we demonstrate the novel, fully integrated system of glass–polysilicon microelectrode, microscale actuators, and controller for autonomous intracellular recordings from single neurons in the abdominal ganglion of Aplysia californica (n = 5 cells). Consistent resting potentials (<−35 mV) and action potentials (>60 mV) were recorded after each successful penetration attempt with the controller and microactuated glass–polysilicon microelectrodes. The success rate of penetration and quality of intracellular recordings achieved using electrothermal microactuators were comparable to that of conventional positioning systems. Preliminary data from in vivo experiments in anesthetized rats show successful intracellular recordings. The MEMS-based system offers significant advantages: (1) reduction in overall size for potential use in behaving animals, (2) scalable approach to potentially realize multi-channel recordings, and (3) a viable method to fully automate measurement of intracellular recordings. This system will be evaluated in vivo in future rodent studies.
Through a combination of single crystal growth, experiments involving in situ deposition of surface adatoms, and complimentary modeling, we examine the electronic transport properties of lithium-decorated ZrTe5 thin films. We observe that the surface states in ZrTe5 are robust against Li adsorption. Both the surface electron density and the associated Berry phase are remarkably robust to adsorption of Li atoms. Fitting to the Hall conductivity data reveals that there exist two types of bulk carriers: those for which the carrier density is insensitive to Li adsorption, and those whose density decreases during initial Li depositions and then saturates with further Li adsorption. We propose this dependence is due to the gating effect of a Li-adsorption-generated dipole layer at the ZrTe5 surface.
Coupled poroelastic stressing and pore-pressure accumulation along pre-existing faults in deep basement contribute to recent occurrence of seismic events at subsurface energy exploration sites. Our coupled fluid-flow and geomechanical model describes the physical processes inducing seismicity corresponding to the sequential stimulation operations in Pohang, South Korea. Simulation results show that prolonged accumulation of poroelastic energy and pore pressure along a fault can nucleate seismic events larger than Mw3 even after terminating well operations. In particular the possibility of large seismic events can be increased by multiple-well operations with alternate injection and extraction that can enhance the degree of pore-pressure diffusion and subsequent stress transfer through a rigid and low-permeability rock to the fault. This study demonstrates that the proper mechanistic model and optimal well operations need to be accounted for to mitigate unexpected seismic hazards in the presence of the site-specific uncertainty such as hidden/undetected faults and stress regime.
The method of manufactured solutions (MMS) has become increasingly popular in conducting code verification studies on predictive codes, such as nuclear power system codes and computational fluid dynamic codes. The reason for the popularity of this approach is that it can be used when an analytical solution is not available. Using MMS, code developers are able to verify that their code is free of coding errors that impact the observed order of accuracy. While MMS is still an excellent tool for code verification, it does not identify coding errors that are of the same order as the numerical method. This paper presents a method that combines MMS with modified equation analysis (MEA), which calculates the local truncation error (LTE) to identify coding error up to and including the order of the numerical method. This method is referred to as modified equation analysis methd of manufactured solutions (MEAMMS). MEAMMS is then applied to a custom-built code, which solves the shallow water equations, to test the performance of the code verification method. MEAMMS is able to detect all coding errors that impact the implementation of the numerical scheme. To show how MEAMMS is different than MMS, they are both applied to the same first-order numerical method test problem with a first-order coding error. When there are first-order coding errors, only MEAMMS is able to identify them. This shows that MEAMMS is able to identify a larger set of coding errors while still being able to identify the coding errors MMS is able to identify.
Ammonothermal growth of bulk gallium nitride (GaN) crystals is considered the most suitable method to meet the demand for high quality bulk substrates for power electronics. A non-destructive evaluation of defect content in state-of-the-art ammonothermal substrates has been carried out by synchrotron X-ray topography. Using a monochromatic beam in grazing incidence geometry, high resolution X-ray topographs reveal the various dislocation types present. Ray-tracing simulations that were modified to take both surface relaxation and absorption effects into account allowed improved correlation with observed dislocation contrast so that the Burgers vectors of the dislocations could be determined. The images show the very high quality of the ammonothermal GaN substrate wafers which contain low densities of threading dislocations (TDs) but are free of basal plane dislocations (BPDs). Threading mixed dislocations (TMDs) were found to be dominant among the TDs, and the overall TD density (TDD) of a 1-inch wafer was found to be as low as 5.16 × 103 cm−2.
If quantum information processors are to fulfill their potential, the diverse errors that affect them must be understood and suppressed. But errors typically fluctuate over time, and the most widely used tools for characterizing them assume static error modes and rates. This mismatch can cause unheralded failures, misidentified error modes, and wasted experimental effort. Here, we demonstrate a spectral analysis technique for resolving time dependence in quantum processors. Our method is fast, simple, and statistically sound. It can be applied to time-series data from any quantum processor experiment. We use data from simulations and trapped-ion qubit experiments to show how our method can resolve time dependence when applied to popular characterization protocols, including randomized benchmarking, gate set tomography, and Ramsey spectroscopy. In the experiments, we detect instability and localize its source, implement drift control techniques to compensate for this instability, and then demonstrate that the instability has been suppressed.
Proceedings - 2020 IEEE 22nd International Conference on High Performance Computing and Communications, IEEE 18th International Conference on Smart City and IEEE 6th International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020
The Message Passing Interface (MPI) standard allows user-level threads to concurrently call into an MPI library. While this feature is currently rarely used, there is considerable interest from developers in adopting it in the near future. There is reason to believe that multithreaded communication may incur additional message processing overheads in terms of number of items searched during demultiplexing and amount of time spent searching because it has the potential to increase the number of messages exchanged and to introduce non-deterministic message ordering. Therefore, understanding the implications of adding multithreading to MPI applications is important for future application development.One strategy for advancing this understanding is through 'low-cost' benchmarks that emulate full communication patterns using fewer resources. For example, while a complete, 'real-world' multithreaded halo exchange requires 9 or 27 nodes, the low-cost alternative needs only two, making it deployable on systems where acquiring resources is difficult because of high utilization (e.g., busy capacity-computing systems), or impossible because the necessary resources do not exist (e.g., testbeds with too few nodes). While such benchmarks have been proposed, the reported results have been limited to a single architecture or derived indirectly through simulation, and no attempt has been made to confirm that a low-cost benchmark accurately captures features of full (non-emulated) exchanges. Moreover, benchmark code has not been made publicly available.The purpose of the study presented in this paper is to quantify how accurately the low-cost benchmark captures the matching behavior of the full, real-world benchmark. In the process, we also advocate for the feasibility and utility of the low-cost benchmark. We present a 'real-world' benchmark implementing a full multithreaded halo exchange on 9 and 27 nodes, as defined by 5-point and 9-point 2D stencils, and 7-point and 27-point 3D stencils. Likewise, we present a 'low-cost' benchmark that emulates these communication patterns using only two nodes. We then confirm, across multiple architectures, that the low-cost benchmark gives accurate estimates of both number of items searched during message processing, and time spent processing those messages. Finally, we demonstrate the utility of the low-cost benchmark by using it to profile the performance impact of state-of-The-Art Mellanox ConnectX-5 hardware support for offloaded MPI message demultiplexing. To facilitate further research on the effects of multithreaded MPI on message matching behavior, the source of our two benchmarks is to be included in the next release version of the Sandia MPI Micro-Benchmark Suite.
The amount of data produced by sensors, social and digital media, and Internet of Things (IoTs) are rapidly increasing each day. Decision makers often need to sift through a sea of Big Data to utilize information from a variety of sources in order to determine a course of action. This can be a very difficult and time-consuming task. For each data source encountered, the information can be redundant, conflicting, and/or incomplete. For near-real-time application, there is insufficient time for a human to interpret all the information from different sources. In this project, we have developed a near-real-time, data-agnostic, software architecture that is capable of using several disparate sources to autonomously generate Actionable Intelligence with a human in the loop. We demonstrated our solution through a traffic prediction exemplar problem.
A vaccine for smallpox is no longer administered to the general public, and there is no proven, safe treatment specific to poxvirus infections, leaving people susceptible to infections by smallpox and other zoonotic Orthopoxviruses such as monkeypox. Using vaccinia virus (VACV) as a model organism for other Orthopoxviruses, CRISPR–Cas9 technology was used to target three essential genes that are conserved across the genus, including A17L, E3L, and I2L. Three individual single guide RNAs (sgRNAs) were designed per gene to facilitate redundancy in rendering the genes inactive, thereby reducing the reproduction of the virus. The efficacy of the CRISPR targets was tested by transfecting human embryonic kidney (HEK293) cells with plasmids encoding both SaCas9 and an individual sgRNA. This resulted in a reduction of VACV titer by up to 93.19% per target. Following the verification of CRISPR targets, safe and targeted delivery of the VACV CRISPR antivirals was tested using adeno-associated virus (AAV) as a packaging vector for both SaCas9 and sgRNA. Similarly, AAV delivery of the CRISPR antivirals resulted in a reduction of viral titer by up to 92.97% for an individual target. Overall, we have identified highly specific CRISPR targets that significantly reduce VACV titer as well as an appropriate vector for delivering these CRISPR antiviral components to host cells in vitro.