Publications

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This report describes the results of a seven day effort to assist subject matter experts address a problem related to COVID-19. In the course of this effort, we analyzed the 29K documents provided as part of the White House's call to action. This involved applying a variety of natural language processing techniques and compression-based analytics in combination with visualization techniques and assessment with subject matter experts to pursue answers to a specific question. In this paper, we will describe the algorithms, the software, the study performed, and availability of the software developed during the effort.

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Purpose: To remind personnel of potential power strip electrical hazards at the office and home Before you reach for that power strip, read this! This Lessons Learned Snapshot highlights the very real potential for electrical contact with power strip usage. It happens more often than you might think! But there are ways to reduce this potential.

For my internship project, I chose to evaluate the training program for the Sandia National Laboratories (SNL) Recorded Information Management (RIM) Program. The purpose of the evaluation was to identify: Where the current training meets federal and corporate requirements and if not, what gaps exist; If the training is accessible in a consistent location; If the training contains a consistent message about the responsibility of managing documents; If the training is organized by records management subject areas.

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The research presented in this paper is to be a contribution to a larger research project. The project was designed to test the safety standards of Sandia National Laboratories' ACRR. The MCNP model of the ACRR core is being used to simulate the environment. To test the safety standards, the dimensions and density of the fuel in the core were varied randomly. Each rod had its own dimension and density assigned to it randomly. Ten different cases of the ACRR core were randomly created. The different cases were studied using 640-group neutron fluxes. The fluxes were compared to see how the variations affected the system.

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In response to anticipated resource shortfalls related to the treatment and testing of COVID-19, many communities are planning to build additional facilities to increase capacity. These facilities include field hospitals, testing centers, mobile manufacturing units, and distribution centers. In many cases, these facilities are intended to be temporary and are designed to meet an immediate need. When deciding where to place new facilities many factors need to be considered, including the feasibility of potential locations, existing resource availability, anticipated demand, and accessibility between patients and the new facility. In this project, a facility location optimization model was developed to integrate these key pieces of information to help decision makers identify the best place, or places, to build a facility to meet anticipated resource demands. The facility location optimization model uses the location of existing resources and the anticipated resource demand at each location to minimize the distance a patient must travel to get to the resource they need. The optimization formulation is presented below. The model was designed to operate at the county scale, where patients are grouped per county. This assumption can be modified to integrate other scales or include individual patients.

Genome editing technologies, particularly those based on zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and CRISPR (clustered regularly interspaced short palindromic repeat DNA sequences)/Cas9 are rapidly progressing into clinical trials. Most clinical use of CRISPR to date has focused on ex vivo gene editing of cells followed by their re-introduction back into the patient. The ex vivo editing approach is highly effective for many disease states, including cancers and sickle cell disease, but ideally genome editing would also be applied to diseases which require cell modification in vivo. However, in vivo use of CRISPR technologies can be confounded by problems such as off-target editing, inefficient or off-target delivery, and stimulation of counterproductive immune responses. Current research addressing these issues may provide new opportunities for use of CRISPR in the clinical space. In this review, we examine the current status and scientific basis of clinical trials featuring ZFNs, TALENs, and CRISPR-based genome editing, the known limitations of CRISPR use in humans, and the rapidly developing CRISPR engineering space that should lay the groundwork for further translation to clinical application.

The influence of ozone addition on the low-temperature oxidation of dimethyl ether (DME) was investigated experimentally in an atmospheric-pressure jet-stirred reactor, over the temperature range of 400–800 K. Detailed speciation information was obtained by employing synchrotron vacuum ultraviolet photoionization mass spectrometry. Experimental results revealed that the ozone addition had a positive influence on the production of the highly reactive intermediates. Moreover, the low-temperature reactivity of DME was significantly enhanced, which resulted in the broadening of the temperature window of fuel consumption and intermediates formation at lower temperatures. Therefore, novel experimental data of the low temperature regime (400–500 K) could be obtained. The data set of this special temperature regime yielded insights into the DME low-temperature kinetics, which were further supported with modeling analysis based on two existing DME models (Metcalfe et al., 2013; Wang et al., 2015) combined with an ozone sub-mechanism (Zhao et al., 2016). The analysis showed that temperature-sensitive reactions such as the second oxygen channel could be nearly “frozen” at this low temperature (T < 440 K). Furthermore, the production of some intermediates was found to be strongly governed by reaction pairs, such as CH3OCH2 + O2 = CH3OCH2O2 and CH3OCH2 + O2 = 2CH2O + OH for the CH2O formation. This finding could be useful for examining branching ratios in both models, and the analysis suggested the further modification of the branching ratios for the oxygen addition to CH3OCH2O2 pathways and the CH3OCH2O2 self-reactions were required. Finally, the influences of the O3 addition in the sensitive reactions of the fuel initial low-temperature oxidation were investigated in this work. It was interesting to note that O3 addition could change the dominating reactions in the initial low-temperature oxidation, by the addition of some O3-related pathways with relatively high sensitivity.

Perfluorooctanoic acid, PFOA, is one of the many concerning pollutants in our atmosphere; it is highly resistant to environmental degradation processes, which enables it to accumulate biologically. With direct routes of this chemical to the environment decreasing, as a consequence of the industrial phase out of PFOA, it has become more important to accurately model the effects of indirect production routes, such as environmental degradation of precursors; e.g., fluorotelomer alcohols (FTOHs). The study reported here investigates the chemistry, physical loss and transport of PFOA and its precursors, FTOHs, throughout the troposphere using a 3D global chemical transport model, STOCHEM-CRI. Moreover, this investigation includes an important loss process of PFOA in the atmosphere via the addition of the stabilised Criegee intermediates, hereby referred to as the "Criegee Field. " Whilst reaction with Criegee intermediates is a significant atmospheric loss process of PFOA, it does not result in its permanent removal from the atmosphere. The atmospheric fate of the resultant hydroperoxide product from the reaction of PFOA and Criegee intermediates resulted in a ≈0.04 Gg year-1 increase in the production flux of PFOA. Furthermore, the physical loss of the hydroperoxide product from the atmosphere (i.e., deposition), whilst decreasing the atmospheric concentration, is also likely to result in the reformation of PFOA in environmental aqueous phases, such as clouds, precipitation, oceans and lakes. As such, removal facilitated by the "Criegee Field" is likely to simply result in the acceleration of PFOA transfer to the surface (with an expected decrease in PFOA atmospheric lifetime of ≈10 h, on average from ca. ≈80 h without Criegee loss to 70 h with Criegee loss).

Complex metal hydrides provide high-density hydrogen storage, which is essential for vehicular applications. However, the practical application of these materials is limited by thermodynamic and kinetic barriers present during the dehydrogenation and rehydrogenation processes as new phases form inside parent phases. An improved understanding of the mixed-phase mesostructures and their interfaces will assist in improving cyclability. In this work, the phase evolution during hydrogenation of lithium nitride and dehydrogenation of lithium amide with lithium hydride is probed with scanning transmission X-ray microscopy at the nitrogen K edge. With this technique, core–shell structures are observed in particles of both partially hydrogenated Li3N and partially dehydrogenated LiNH2 + 2LiH. To generate these structures, the rate-limiting step must shift from internal hydrogen diffusion during hydrogenation to the formation of hydrogen gas at the surface during desorption.

The Microgrid Design Toolkit (MDT) supports decision analysis for new ("greenfield") microgrid designs as well as microgrids with existing infrastructure. The current version of MDT includes two main capabilities. The first capability, the Microgrid Sizing Capability (MSC), is used to determine the size and composition of a new, grid connected microgrid in the early stages of the design process. MSC is focused on developing a microgrid that is economically viable when connected to the grid. The second capability is focused on designing a microgrid for operation in islanded mode. This second capability relies on two models: the Technology Management Optimization (TMO) model and Performance Reliability Model (PRM).

Sandia National Laboratories is part of the government test and evaluation team for the Defense Advanced Research Projects Agency Collection and Monitoring via Planning for Active Situational Scenarios program. The program is designed to better understand competition in the area between peace and conventional conflict when adversary actions are subtle and difficult to detect. For the purposes of test and evaluation, Sandia conducted a range of activities for the program: creation of the Grey Zone Test Range; design of the data stream for a user experiment conducted with U.S. Indo-Pacific Command; design, implementation, and execution of the formal evaluation; and analysis and summary of the evaluation results. This report details Sandia's activities and provides additional information on the Grey Zone Test Range urban simulation environment developed to evaluate the performer technologies.

Telecommuting at Sandia and within the Federal workforce has been optional for years. With the COVID-19 crisis, social distancing makes this a necessity that may be with us for some weeks and even months to come. All of us - whether new to telecommuting or an experienced remote worker - are challenged with how to efficiently and effectively adapt to this new work environment, while maintaining work-life balance to adequately care for ourselves and loved ones.

This Sandia National Laboratories, New Mexico Environmental Restoration Operations (ER) Consolidated Quarterly Report (ER Quarterly Report) fulfills all quarterly reporting requirements set forth in the Compliance Order on Consent. Table I-1 lists the six sites remaining in the corrective action process.

Fatigue crack growth rates (FCGR) of multiple X100 pipeline steel welds and heat affected zones were measured in high-pressure hydrogen gas to investigate their behavior compared to lower strength pipeline welds. A total of five high strength welds and two heat affected zones (HAZ) were examined all of which were fabricated using the same X100 base material. Different welding wires and techniques were used to fabricate the welds to provide a variety of end products to evaluate susceptibility to fatigue in high pressure hydrogen gas. Residual stresses were measured for each weld and HAZ using the slitting method and the effect of residual stress on the stress intensity factor, Kres, was determined. Using Kres, the fatigue crack growth rate curves were corrected to remove the effects of residual stress by examining the influence of Kres on stress ratio, R. Comparisons were then made between the high strength welds, which were corrected for residual stress, and lower strength welds from the literature. It was found that the higher strength welds and heat affected zones exhibited comparable fatigue crack growth rates to lower strength welds, as the FCGR data of the high strength welds overlaid the lower strength welds. This suggests that despite distinct differences in strength and microstructure between the different welds, hydrogen-assisted fatigue crack growth susceptibility is similar. A comparison was made between the Kres measured in extracted coupons and residual stress estimates provided in relevant welded pipe assessment standards such as API 579-1/ASME FFS-1. It was found the residual stress values in the test coupons extracted from welded pipe were significantly lower than those expected in the intact welded pipes and highlights the importance in quantifying and removing coupon residual stresses when fatigue crack growth rates are measured and including expected weld joint residual stress when making structural assessments.

Abstract: The development of high-speed volumetric laser-induced fluorescence measurements of formaldehyde (CH 2O -LIF) using a pulse-burst laser operated at a repetition rate of 100kHz is presented. A novel laser scanning system employing an acousto-optic deflector (AOD) enables quasi-4D CH 2O -LIF imaging at a scan frequency of 10kHz. The diagnostic capability of time-resolved volumetric imaging is demonstrated in a partially premixed DME/air lifted turbulent jet flame near the flame base. Simultaneous imaging of laser beam profiles is performed to account for the laser pulse energy fluctuation and laser sheet inhomogeneity. With the accurate registration of laser sheet positions, the volumetric reconstruction of CH 2O -LIF signals is performed within a detection volume of 17.3×11.9×2.3mm3 with an average out-of-plane spatial resolution of 250μm. A surface detection algorithm with adaptive thresholding is used to determine the global maximum intensity gradient by calculating gradient percentiles. The flame topology characteristics are investigated by evaluating the 3D curvatures of CH 2O surfaces. Curvatures calculated using 2D data systematically underestimate the full 3D curvature due to the lack of out-of-plane information. The inner surfaces near the turbulent fuel jet exhibit higher probabilities of large mean curvature than the outer surfaces. The saddle and cylindrical structures are dominant on both the inner and outer surfaces and the elliptic structures occur with lower probability. The results suggest that the damping of turbulent fluctuations by the temperature increase through the CH 2O region reduces the curvature, but the local structure topology remains self-similar. Graphic abstract: [Figure not available: see fulltext.].

Data assimilation techniques are investigated for integrating high-speed high-resolution experimental data into large-eddy simulations. To this end, an ensemble Kalman filter is employed to assimilate velocity measurements of a turbulent jet at a Reynolds number of 13,500 into simulations. The goal of the current work is to examine the behavior of the assimilation algorithm for state estimation of turbulent flows that are of relevance to engineering applications. This is accomplished by investigating the impact that localization, measurement uncertainties, assimilation frequency, data sparsity and ensemble size have on the estimated state vector. For the flow configuration and computational setup considered in this study an optimal value of the localization radius is identified, which minimizes the error between experimental data and state vector. The impact of experimental uncertainties on the state estimation is demonstrated to provide solution bounds on the assimilation algorithm. It is found that increasing the number of ensembles has a positive impact on the state estimation. In comparison, decreasing the assimilation frequency or reducing the experimental data available for assimilation is found to have a negative impact on the state estimation. These findings demonstrate the viability of assimilating measurements into numerical simulations to improve state estimates, to support parameter evaluations and to guide model assessments.

Ultrafast x-ray imagers developed at Sandia National Laboratories are a transformative diagnostic tool in inertial confinement fusion and high energy density physics experiments. The nanosecond time scales on which these devices operate are a regime with little precedent, and applicable characterization procedures are still developing. This paper presents pulsed x-ray characterization of the Icarus imager under a variety of illumination levels and timing modes. Results are presented for linearity of response, absolute sensitivity, variation of response with gate width, and image quality.

The stability of neutron absorber composite materials at hydrothermal conditions was tested in a series of two-week experiments to mimic spent nuclear fuel disposal. Coupons, composed of boron carbide (B4C) sintered with and encased in aluminum, were increasingly altered in experiments at 150, 230, and 300 °C and pressures of 150 bar. Alteration of aluminum to boehmite (γ-AlO(OH)) and hydrogen gas generation occurred over the range of investigated temperatures, but is most significant at 300 °C. The formation of boron-bearing mineral phases was not detected; however, aqueous boron was present in the reaction fluids.

By engineering atomic geometries composed of nearly 1000 atomic segments embedded in micro-resonators, we observe Bragg resonances induced by the atomic lattice at the telecommunication wavelength. The geometrical arrangement of erbium atoms into a lattice inside a silicon nitride (SiN) microring resonator reduces the scattering loss at a wavelength commensurate with the lattice. We confirm dependency of light emission to the atomic positions and lattice spacing and also observe Fano interference between resonant modes in the system.

Turbulent mixing in pilot-scale cultivation systems influences the productivity of photoautotrophic cultures. We studied turbulent mixing by applying particle image velocimetry and acoustic doppler velocimetry to pilot-scale, flat-panel photobioreactor, and open-channel raceway. Mixing energy inputs were varied from 0.1 to 2.1 W·m−3. The experimental results were used to quantify turbulence and to validate computational fluid dynamics models, from which Lagrangian representations of the fluid motion in these reactors were derived. The results of this investigation demonstrated that differences in mixing energy input do not significantly impact the structure of turbulence and the light/dark cycling frequencies experienced by photoautotrophic cells within the reactors. The experimental and computational results of our research demonstrated that well-mixed conditions exist in pilot-scale, flat-panel photobioreactors and open-channel raceways, even for relatively low mixing energy inputs.

Two different cell constructions are currently being investigated for the LFP/Graphite system. These cells have undergone continuous cycling until the target of 1000 cycles was reached.

Electric-field-induced second-harmonic generation, or E-FISH, has received renewed interest as a nonintrusive tool for probing electric fields in gas discharges and plasmas using ultrashort laser pulses. An important contribution of this work lies in establishing that the E-FISH method works effectively in the nanosecond regime, yielding field sensitivities of about a kV/cm at atmospheric pressure from a 16 ns pulse. This is expected to broaden its applicability within the plasma community, given the wider access to conventional nanosecond laser sources. A Pockels-cell-based pulse-slicing scheme, which may be readily integrated with such nanosecond laser systems, is shown to be a complementary and cost-effective option for improving the time resolution of the electric field measurement. Using this scheme, a time resolution of ∼3 ns is achieved, without any detriment to the signal sensitivity. This could prove invaluable for nonequilibrium plasma applications, where time resolution of a few nanoseconds or less is often critical. Finally, we take advantage of the field vector sensitivity of the E-FISH signal to demonstrate simultaneous measurements of both the horizontal and vertical components of the electric field.

This report details the test setup, process, and results for radiated susceptibility testing of multicrystalline silicon photovoltaic (PV) modules as part of the EMP-Resilient Electric Grid Grand Challenge Laboratory Directed Research and Development (LDRD) project at Sandia National Laboratories. Testing was conducted over October 10-17, 2019, where 8 photovoltaic modules were exposed to E1 transient pulses with peak field levels up to 100 kV/m. Modules were terminated in a resistive load representing connected components. State of health testing conducted via I-V curve tracing of the photovoltaic modules showed no observable loss of device function due to large electric field transients. Differential mode currents were measured on the order of 10's of amps for up to a microsecond following the radiated field pulse. Common mode currents took the form of a damped sinusoid with a maximum peak of 10's to 100's of amps with a resonance near 60 MHz.

Climate change and its impacts on average temperature, water supply, agriculture, coastal flooding, biodiversity, social and economic stability, human migration, and overall global stability is one of the leading threats emerging for humanity, and is likely to increase as a threat for decades to come. This report represents a snapshot of climate change data, information, and understanding, as of 2018, and can serve as a kind of benchmark for changes going forward in time. This report covers temperature change and heat effects, atmospheric and ocean circulation, freshwater supply changes, sea level rise and flooding, extreme climate events, oceanic deoxygenation, land degredation, social and economic changes, migration, and food. Data and information on all these issues represent a compelling body of knowledge supporting the scientific hypothesis describing climate change, and an important mile marker in our effort to track the unfolding nature of the problem. A slide presentation that summarizes the content of this report is in Appendix A and can serve as an executive summary for the report.

The IEC 61853 PV module energy rating standard requires measuring module power (and hence efficiency) over a matrix of irradiance and temperature conditions. These matrix points represent nearly the full range of operating conditions encountered in the field in all but the most extreme locations, and create an opportunity to develop alternative approaches to existing modelssuch as the single-diode models and the Sandia Array Performance Modelfor calculating system performance. This report begins by discussing the bilinear interpolation and extrapolation method from IEC 61853-3, and then describes four existing model-based methods that could be used with matrix measurements. Then a new model is developed and all options are compared according to seven objective criteria using the matrix measurements of four PV modules of different technologies. The results show that the new model is an excellent candidate for launching power matrix-based PV system simulations.

Space rendezvous and proximity operations are increasing in numbers, enabling inspections, diagnostics, and maintenance of on-orbit systems. Because collision, loss of control, and unintended damage can impact the system under examination -- and at the extreme, cause system break-up and space debris -- the safety practices for rendezvous and proximity operations can have significant implications for national security. This study examines the applicability of the Always/Never surety framework, which was developed for United States nuclear weapons, as a model safety basis for unmanned space proximity operations. This unclassified framework has understandable safety approaches and principles and focuses on a system being always safenever unsafe. The authors consider that the adapting the framework might present a means for standardization across government and commerce, encouraging a consistent approach and a set of clarifying safety principles and applications for rendezvous and proximity operations. The framework also offers a consistent taxonomy, presents safety and reliability requirements organized by four environment categories, defines accident or abnormal conditions, contributes a strategy for identifying hostile and tactical environments, and enables decision-making for determining if conditions are safe for proximity space operations.

This report examines the sensitivity of salt cavern Mechanical Integrity Tests (MIT) to uncertainties in key test parameters. MIT's are used by cavern operators to detect and quantify leak rates in access wells in underground salt storage caverns and involve a suite of measured and assumed parameters that have a direct impact on the sensitivity of the testing to detect actual leaks from the cavern storage system. Determining the sensitivity of the testing to these different parameters provides a basis for understanding the results from, and informing the design criteria for, this type of testing. Without fully understanding the sensitivity of the test to the testing parameters, it is possible that the test results may not accurately reflect the integrity of the cavern system; an actual leak may be missed, or an intact system may be interpreted as leaking. This report reviews the main parameters included in MITs and examines how selected changes in their values can impact test results. The deviations used in the sensitivity analyses were designed to be within the ranges believed to be similar to those which may be encountered during testing. The results show that small, plausible fluctuations in some of the parameters measured values can have a significant impact on the testing results. Of the parameters studied here, the sensitivity analyses showed the order of importance to be (from highest to lowest): nitrogen-oil interface depth measurement, well bore temperature, well head pressure, and finally the internal geometry of the testing interval.

Milestone Description: Enhance Nalu-Wind's actuator disc model through hardening, documenting, stress-testing, verifying, and validating. Existing workflows will be improved by reducing the data output stream, and by making the analysis capabilities more modular and generally better. These model capabilities are needed by other A2e areas, namely Wake Dynamics, AWAKEN, and VV&UQ.

The international export of handheld spectroscopy detectors by the National Nuclear Security Administration (NNSA) to partner states will provide state regulatory authorities and nuclear material owners a way to improve accountancy for accidental gains of nuclear material, including the provision of reports to the IAEA, in order to meet their safeguards agreements. International Atomic Energy Agency (IAEA) safeguards agreements for non-nuclear weapons states requires accountancy for all nuclear material. As defined in Article XX of the IAEA statute, nuclear material includes source materials: "uranium containing the mixture of isotopes occurring in nature," and special fissionable material: "plutonium-239; uranium-233; uranium enriched in the isotopes 235 or 233". For IAEA Member States to meet their requirements under comprehensive safeguards agreements (CSA), safeguards are to be applied on "all source or special fissionable material," which "includes all nuclear material subject to IAEA safeguards". Therefore, accidental gains and losses of nuclear material must be reported to the IAEA. An accidental gain occurs when a state unexpectedly adds nuclear material to their inventory by various means such as seizing smuggled material or the discovery of legacy items previously unaccounted for. The material type and quantity must be added to the State's inventory by updating domestic records and then communicated to the IAEA.

The availability of repair garage infrastructure for hydrogen fuel cell vehicles is becoming increasingly important for future industry growth. Ventilation requirements for hydrogen fuel cell vehicles can affect both retrofitted and purpose-built repair garages and the costs associated with these requirements can be significant. A hazard and operability study (HAZOP) was performed to identify key risk-significant scenarios related to hydrogen vehicles in a repair garage. Detailed simulations and modeling were performed using appropriate computational tools to estimate the location, behavior, and severity of hydrogen release based on key HAZOP scenarios. This work compares current fire code requirements to an alternate ventilation strategy to further reduce potentially hazardous conditions. Overall, the amount of flammable mass of hydrogen at any one time in the simulation is low compared to the total mass of hydrogen released, due to the low flow rate of a low pressure release. It is shown that position, direction, and velocity of ventilation have a significant impact on the amount of instantaneous flammable mass in the domain.

Continuing previous efforts to investigate and develop the Unclassified Radioisotope Algorithm, the goal of the FY19-FY20 effort was to develop a prototype detector system which uses the algorithm to confirm warhead attributes related to the presence of either weapons grade plutonium (WGPu) or highly enriched uranium (HEU). The final deliverable is a prototype attribute measurement system built with common, commercially available gamma radiation detector components, capable of confirming the presence of specific, complex radioactive sources of interest, without the collection and storage of gamma energy spectra. This is accomplished by processing each gamma pulse as it is received, applying weight values based on the energy and incrementing or decrementing scalar counters which can be compared with expected values to determine if the measured source is consistent with WGPu or HEU. This report documents the design of the prototype system as well as the development of the algorithm and performance testing results. While the previously conceptualized, simple algorithm resulted in a prohibitive amount of false positives, the goal for a simple attribute measurement system capable of verifying Ba-133 and Ra-226 (weapons grade plutonium and highly enriched uranium surrogate testing sources) at over 95% accuracy with sub 5% false positive rate was demonstrated.

There are numerous vehicles which utilize alternative fuels, or fuels that differ from typical hydrocarbons such as gasoline and diesel, throughout the world. Alternative vehicles include those running on the combustion of natural gas and propane as well as electrical drive vehicles utilizing batteries or hydrogen as energy storage. Because the number of alternative fuels vehicles is expected to increase significantly, it is important to analyze the hazards and risks involved with these new technologies with respect to the regulations related to specific transport infrastructure, such as bridges and tunnels. This report focuses on hazards presented by hydrogen fuel cell electric vehicles that are different from traditional fuels. There are numerous scientific research and analysis publications on hydrogen hazards in tunnel scenarios; however, compiling the data to make conclusions can be a difficult process for tunnel owners and authorities having jurisdiction over tunnels. This report provides a summary of the available literature characterizing hazards presented by hydrogen fuel cell electric vehicles, including light-duty, medium and heavy-duty, as well as buses. Research characterizing both worst-case and credible scenarios, as well as risk-based analysis, is summarized. Gaps in the research are identified to guide future research efforts to provide a complete analysis of the hazards and recommendations for the safe use of hydrogen fuel cell electric vehicles in tunnels.

The incorporation of uranium, plutonium and technetium in the negative thermal expansion (NTE) α-Zr(WO4)2 has been investigated within the framework of density functional theory (DFT). It is found that the vacancy formation energies of the charged vacancies are overall larger than that of its counterpart neutral Frenkel defects and Schottky defects. DFT calculations suggest that U and Pu substitutions for the Zr site are preferred in α-Zr(WO4)2. In case of Tc substitution, both Tc(IV) for the Zr site and Tc(VII) for the W site are considered under oxygen-poor and oxygen-rich conditions, while Tc(VII) substitution can be improved significantly by including Y2O3 (charge compensation).

The U.S. Nuclear Regulatory Commission (NRC) has interacted with vendors pursuing the commercialization of micro-reactors (i.e., reactors capable of producing about 1 MW(th) to 20 MW(th) of energy from nuclear fission). It is envisioned that micro-reactors could be assembled and fueled in a factory and shipped to a site. Many of the sites are expected to be remote locations requiring off-grid power or in some cases military bases. The objective of this effort is to explore the technical issues and the approach required to reach a finding of "reasonable assurance of public health and safety" for this new and different class of reactors. The analysis performed here leverages available micro-reactor design and testing data available from national laboratory experience as well as commercial design information to explore technical issues. Some factors considered include source term, accidents that would need to be analyzed, and the extent of the probabilistic risk assessment (PRA). The technical evaluation was performed within the framework of the Licensing Modernization Project (LMP) to identify licensing basis events, classification of structures, systems and components, and defense-in-depth needed to provide regulatory certainty. With this framework and technical evaluation in mind, the scope and content of a micro-reactor licensing application is discussed.

Under its Grid Modernization Initiative, the U.S. Department of Energy (DOE), in collaboration with energy industry stakeholders developed a multi-year research plan to support modernizing the electric grid. One of the foundational projects for accelerating modernization efforts is information and communications technology interoperability. A key element of this project has been the development of a methodology for engaging ecosystems related to grid integration to create roadmaps that advance the ease of integration of related smart technology. This document is the product of activities undertaken in 2017 through 2019. It provides a Cybersecurity Plan describing the technology to be adopted in the project with details as per the GMLC Call document.

A new commercial design of BAM friction tester that utilizes a programmable servo motor was tested in comparison to the traditional cam-driven model. Displacement and velocity profiles were analyzed for both designs; significant differences were found between the two designs, most notable of which is that the traditional cam-driven unit has plate velocities that can be 50–75 % greater than those seen on the servo-driven model. Five energetic materials were also tested on each machine, including PETN, RDX, HMX, CL-20, and HNAB. Results from the servo-driven model generally showed slightly less sensitivity when compared to the cam driven model, though the magnitude of the difference is not significant enough to require modification of safe handling procedures for the materials tested.

This report presents a novel fault detection, characterization, and fault current control algorithm for a standalone solar-photovoltaic (PV) based dc microgrids. The protection scheme is based on the current derivative algorithm. The overcurrent and current directional/differential comparison based protection schemes are incorporated for the dc microgrid fault characterization. For a low impedance fault, the fault current is controlled based on the current/voltage thresholds and current direction. Generally, the droop method is used to control the power-sharing between the converters by controlling the reference voltage. In this article, an adaptive droop scheme is also proposed to control the fault current by calculating a virtual resistance R droop , and to control the converter output reference voltage. For a high impedance fault, differential comparison method is used to characterize the fault. These algorithms effectively control the converter pulsewidth and reduce the flow of source current from a particular converter, which helps to increase the fault clearing time. Additionally, a trip signal is sent to the corresponding dc circuit breaker (DCCB), to isolate the faulted converter, feeder or a dc bus. The dc microgrid protection design procedure is detailed, and the performance of the proposed method is verified by simulation analysis.

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which is focused on developing high-fidelity and high-resolution Modeling and Simulation (M&S) tools for modeling of Light Water Reactors (LWRs). This hub, Consortium for Advanced Simulation of LWRs (CASL), has developed an LWR simulation tool called Virtual Environment for Reactor Applications (VERA). The multi-physics capability of VERA is achieved through the coupling of single-physics codes, including BISON, CTF, MPACT, and MAMBA. BISON is a fuel performance code which models the thermo-mechanical behavior of nuclear fuel using high performance M&S. It is capable of modeling traditional LWR fuel rods, fuel plates, and TRi-structural ISOtropic (TRISO) fuel particles. It can employ three-dimensional Cartesian, two-dimensional axisymmetric cylindrical, or one-dimensional radial spherical geometry. It includes empirical models for a large variety of fuel physics: temperature- and burnup-dependent thermal properties, fuel swelling and densification, fission gas production, cladding creep, fracture, cladding plasticity, and gap/plenum models. This document details a series of code verification test problems that are used to test BISON. These problems add confidence that the BISON code is a faithful representation of its underlying mathematical model. The suite of verification tests are mapped to the underlying conservation equations solved by the code: heat conduction, mechanics, and species conservation. Twenty-two problems are added for the heat conduction solution, two for the mechanics solution, and none for species conservation. Method of Manufactured Solutions (MMS) capability is demonstrated with three problems, and temperature drops across the fuel gap are tested.

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which is focused on developing high-fidelity and high-resolution modeling and simulation (M&S) tools for modeling of light water reactors (LWRs). This hub, the Consortium for Advanced Simulation of LWRs (CASL), has developed an LWR simulation tool called the Virtual Environment for Reactor Applications (VERA). The multi-physics capability of VERA is achieved through the coupling of single-physics codes, including CTF (the CASL version of Coolant Boiling in Rod Arrays— Three Field (COBRA-TF)), Michigan Parallel Characteristics Transport (MPACT), BISON, and Materials Performance and Optimization (MPO) Advanced Model for Boron Analysis (MAMBA). As part of its M&S efforts, CASL has identified various challenge problems, including Crud Induced Power Shift (CIPS), Crud-Induced Localized Corrosion (CILC), Pellet-Cladding Interaction (PCI), and Departure from Nucleate Boiling (DNB). This work addresses CASL milestone L2:VVI.P19.03, which focuses on uncertainty quantification of crud, which is relevant to both CIPS and CILC. This is achieved through an analysis and separate effects validation of the thermal hydraulic phenomenon known as subcooled boiling. As part of this work, various sources of experimental data are examined and compared to different options for empirical modeling of subcooled boiling. Through this analysis, a complete understanding of the underlying models and their implementation details are understood. A subset of these data are incorporated into a separate effects validation study of CTF. The Westinghouse Advanced Loop Tester (WALT) and Rohsenow experiments are modeled, and it is shown that the newly-implemented Gorenflo correlation is more accurate than the existing Chen and Thom correlations.

The selection of austenitic stainless steels for hydrogen service is challenging since there are few intrinsic metrics that relate alloy composition to hydrogen degradation. One such metric, explored here, is intrinsic stacking fault energy. Stacking fault energy has an influence on the character and structure of dislocations and on the formation of secondary crystalline phases created during mechanical deformation in austenitic alloys. In this work, a data-driven model for the intrinsic stacking fault energy of common austenitic stainless steel alloys is applied to compare the relative degradation of tensile performance in the presence of hydrogen. A transition in the tensile reduction of area of both 300-series and manganese stabilized stainless steels is observed at a calculated stacking fault energy of approximately 43 mJ m^-2, below which pronounced hydrogen degradation on tensile ductility is observed. The model is also applied to suggest alloying strategies for low nickel austenitic stainless steels for hydrogen service. Lastly, through this investigation, we find that calculated intrinsic stacking fault energy is a high-throughput screening metric that enables the ranking of the performance of a diverse range of austenitic stainless steel compositions, as well as the identification of new alloys, with regard to hydrogen compatibility.

This paper is focused on the aspects of limiting in residual distribution (RD) schemes for high-order finite element approximations to advection problems. Both continuous and discontinuous Galerkin methods are considered in this work. Discrete maximum principles are enforced using algebraic manipulations of element contributions to the global nonlinear system. The required modifications can be carried out without calculating the element matrices and assembling their global counterparts. The components of element vectors associated with the standard Galerkin discretization are manipulated directly using localized subcell weights to achieve optimal accuracy. Low-order nonlinear RD schemes of this kind were originally developed to calculate local extremum diminishing predictors for flux-corrected transport (FCT) algorithms. In the present paper, we incorporate limiters directly into the residual distribution procedure, which makes it applicable to stationary problems and leads to well-posed nonlinear discrete problems. To circumvent the second-order accuracy barrier, the correction factors of monolithic limiting approaches and FCT schemes are adjusted using smoothness sensors based on second derivatives. The convergence behavior of presented methods is illustrated by numerical studies for two-dimensional test problems.

Terahertz semiconductor quantum-cascade lasers (QCLs) are widely implemented with metallic cavities that support low-loss plasmonic optical modes at long wavelengths. However, resonant optical modes in such cavities suffer from poor radiative characteristics due to their subwavelength transverse dimensions. Consequently, single-mode terahertz QCLs with metallic cavities and large (> 100 mW) output power have only been realized in the surface-emitting configuration that affords a large radiating surface. Here, we demonstrate a method to enhance radiative outcoupling from such plasmonic lasers for high-power emission in the edge-emitting (end-fire or longitudinal) direction. Single-sided plasmon waves propagating in vacuum are resonantly excited in surrounding medium of metallic cavities with the QCL semiconductor medium. The vacuum guided plasmon waves with a large wavefront phase-lock multiple metallic cavities longitudinally, which leads to intense radiation in multiple directions, including that in the longitudinal direction in a narrow single-lobed beam. The multicavity array radiates predominantly in a single spectral mode. A peak-power output of 260 mW and a slope efficiency of 303 mW/A are measured for the end-fire beam from a 3.3 THz QCL operating at 54 K in a Stirling cooler. Single-mode operation and lithographic tuning across a bandwidth of ∼ 150 GHz are demonstrated.

This is an addendum to the Sierra/SolidMechanics 4.56 User's Guide that documents additional capabilities available only in alternate versions of the Sierra/SolidMechanics (Sierra/SM) code. These alternate versions are enhanced to provide capabilities that are regulated under the U.S. Department of State's International Traffic in Arms Regulations (ITAR) export control rules. The ITAR regulated codes are only distributed to entities that comply with the ITAR export control requirements. The ITAR enhancements to Sierra/SM include material models with an energy-dependent pressure response (appropriate for very large deformations and strain rates) and capabilities for blast modeling. This document is an addendum only; the standard Sierra/SolidMechanics 4.56 User's Guide should be referenced for most general descriptions of code capability and use.

This user's guide documents capabilities in Sierra/SolidMechanics which remain "in-development" and thus are not tested and hardened to the standards of capabilities listed in Sierra/SM 4.56 User's Guide. Capabilities documented herein are available in Sierra/SM for experimental use only until their official release. These capabilities include, but are not limited to, novel discretization approaches such as peridynamics and the reproducing kernel particle method (RKPM), numerical fracture and failure modeling aids such as the extended finite element method (XFEM) and J-integral, explicit time step control techniques, dynamic mesh rebalancing, as well as a variety of new material models and finite element formulations.

This document describes how to build a 5-gore, 5.8 m diameter heliotrope solar hot air balloon. This is a fairly straightforward process, but it is painstaking. When making the balloons, make sure not to wear anything that can snag the material (badges, etc). Sharp objects or corners should not be present. When laying out, folding, and cutting gores, it is best to wear socks instead of shoes. Tape should never be pulled off of a balloon. If it accidentally touches the balloon material, it should be left in place or cut free. Also, when adding tape (either intentionally or not), no sticky parts should be left. Sticky parts should either be cut free or taped over. Otherwise, the sticky part will grab the balloon envelope and tear it. You are building a 20 ft sphere out of material thinner than a grocery bag — the best guidance is just to use common sense.

The study of infrasound (acoustic) and gravity waves sources and propagation in the atmosphere of a planet gives us precious insight on atmosphere dynamics, climate, and even internal structure. The implementation of modern pressure sensors with high rate sampling on stratospheric balloons is improving their study. We analyzed the data from the National Aeronautics and Space Administration Ultra Long Duration Balloon mission (16 May to 30 June 2016). Here, we focus on the balloon's transit of the Andes Mountains. We detected gravity waves that are associated to troposphere convective activity and mountain waves. An increase of the horizontal wavelengths from 50 to 70 km with increasing distance to the mountains is favoring the presence of mountain waves. We also report on the detection of infrasounds generated by the mountains in the 0.01–0.1 Hz range with a pressure amplitude increase by a factor 2 relative background signal. Besides, we characterized the decrease of microbaroms power when the balloon was flying away from the ocean coast. These observations suggest, in a way similar to microseisms for seismometers, that microbaroms are the main background noise sources recorded in the stratosphere even far from the ocean sources. Finally, we observed a broadband signal above the Andes, between 0.45 and 2 Hz, probably associated with a thunderstorm. The diversity of geophysical phenomena captured in less than a day of observation stresses the interest of high rate pressure sensors on board long-duration balloon missions.

We present a theoretical model that predicts the peak strength of polycrystalline metals based on the activation energy (or stress) required to cause deformation via amorphization. Building on extensive earlier work, this model is based purely on materials properties, requires no adjustable parameters, and is shown to accurately predict the strength of four exemplar metals (fcc, bcc, and hcp, and an alloy). This framework reveals new routes for design of more complex high-strength materials systems, such as compositionally complex alloys, multiphase systems, nonmetals, and composite structures.

Terahertz (THz) technology has shown promise for several applications, but limitations in sources and detectors have prevented broader adoption. Existing THz detectors are rigid, planar, and fabricated using complex technology, making it difficult to integrate into systems. Here we demonstrate THz detectors fabricated by inkjet printing on submicrometer thick, ultraflexible substrates. By developing p- and n-type carbon nanotube inks, we achieve optically thick p–n junction and p-type devices, enabling antenna-free pixels for THz imaging. By further designing and folding the printed devices, we realize origami-inspired architectures with improved performance over single devices, achieving a noise-equivalent power of 12 nW/Hz1/2 at room temperature with no voltage bias. Our approach opens avenues for nonplanar, foldable, deployable, insertable, and retractable THz detectors for applications in nondestructive inspection.

Abstract not provided.

Presented in this document are the theoretical aspects of capabilities contained in the Sierra/SM code. This manuscript serves as an ideal starting point for understanding the theoretical foundations of the code. For a comprehensive study of these capabilities, the reader is encouraged to explore the many references to scientific articles and textbooks contained in this manual. It is important to point out that some capabilities are still in development and may not be presented in this document. Further updates to this manuscript will be made as these capabilities come closer to production level.

Slow slip events (SSEs) accommodate a significant proportion of tectonic plate motion at subduction zones, yet little is known about the faults that actually host them. The shallow depth (<2 km) of well-documented SSEs at the Hikurangi subduction zone offshore New Zealand offers a unique opportunity to link geophysical imaging of the subduction zone with direct access to incoming material that represents the megathrust fault rocks hosting slow slip. Two recent International Ocean Discovery Program Expeditions sampled this incoming material before it is entrained immediately down-dip along the shallow plate interface. Drilling results, tied to regional seismic reflection images, reveal heterogeneous lithologies with highly variable physical properties entering the SSE source region. These observations suggest that SSEs and associated slow earthquake phenomena are promoted by lithological, mechanical, and frictional heterogeneity within the fault zone, enhanced by geometric complexity associated with subduction of rough crust.

Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high-fidelity, validated models used in modal, vibration, static and shock analysis of weapons systems. This document provides a user's guide to the input for Sierra/SD. Details of input specifications for the different solution types, output options, element types and parameters are included. The appendices contain detailed examples, and instructions for running the software on parallel platforms.

Numerical weather and climate prediction rates as one of the scientific applications whose accuracy improvements greatly depend on the growth of the available computing power. As the number of cores in top computing facilities pushes into the millions, increasing average frequency of hardware and software failures forces users to review their algorithms and systems in order to protect simulations from breakdown. This report surveys approaches for fault-tolerance in numerical algorithms and system resilience in parallel simulations from the perspective of numerical weather and climate prediction systems. A selection of existing strategies is analyzed, featuring interpolation-restart and compressed checkpointing for the numerics, in-memory checkpointing, user-level failure mitigation-based and backup-based methods for the systems. Numerical examples showcase the performance of the techniques in addressing faults, with particular emphasis on iterative solvers for linear systems, a staple of atmospheric fluid flow solvers. The potential impact of these strategies is discussed in relation to current development of numerical weather prediction algorithms and systems towards the exascale. Trade-offs between performance, efficiency and effectiveness of resiliency strategies are analyzed and some recommendations outlined for future developments.

Siera/SolidMechanics (Sierra / SM) is a Lagrangian, three-dimensional code for finite element analysis of solids and structures. It provides capabilities for explicit dynamic, implicit quasistatic and dynamic analyses. The explicit dynamics capabilities allow for the efficient and robust solution of models with extensive contact subjected to large, suddenly applied loads. For implicit problems, Sierra / SM uses a multi-level iterative solver, which enables it to effectively solve problems with large deformations, nonlinear material behavior, and contact. Sierra / SM has a versatile library of continuum and structural elements, and a large library of material models. The code is written for parallel computing environments enabling scalable solutions of extremely large problems for both implicit and explicit analyses. It is built on the SIERRA Framework, which facilitates coupling with other SIERRA mechanics codes . This document describes the functionality and input syntax for Sierra/SM.

Planck’s law predicts the distribution of radiation energy, color and intensity, emitted from a hot object at thermal equilibrium. The Law also sets the upper limit of radiation intensity, the blackbody limit. Recent experiments reveal that micro-structured tungsten can exhibit significant deviation from the blackbody spectrum. However, whether thermal radiation with weak non-equilibrium pumping can exceed the blackbody limit in the far field remains un-answered experimentally. Here, we compare thermal radiation from a micro-cavity/tungsten photonic crystal (W-PC) and a blackbody, which are both measured from the same sample and also in-situ. We show that thermal radiation can exceed the blackbody limit by >8 times at λ=1.7 μm resonant wavelength in the far-field. Our observation is consistent with a recent calculation by Wang and John performed for a 2D W-PC filament. This finding is attributed to non-equilibrium excitation of localized surface plasmon resonances coupled to nonlinear oscillators and the propagation of the electromagnetic waves through non-linear Bloch waves of the W-PC structure. This discovery could help create super-intense narrow band thermal light sources and even an infrared emitter with a laser-like input-output characteristic.

The attachment of dopant precursor molecules to depassivated areas of hydrogen-terminated silicon templated with a scanning tunneling microscope (STM) has been used to create electronic devices with sub-nanometer precision, typically for quantum physics demonstrations, and to dope silicon past the solid-solubility limit, with potential applications in microelectronics and plasmonics. However, this process, which we call atomic precision advanced manufacturing (APAM), currently lacks the throughput required to develop sophisticated applications because there is no proven scalable hydrogen lithography pathway. Here, we demonstrate and characterize an APAM device workflow where STM lithography has been replaced with photolithography. An ultraviolet laser is shown to locally heat silicon controllably above the temperature required for hydrogen depassivation. STM images indicate a narrow range of laser energy density where hydrogen has been depassivated, and the surface remains well-ordered. A model for photothermal heating of silicon predicts a local temperature which is consistent with atomic-scale STM images of the photo-patterned regions. Finally, a simple device made by exposing photo-depassivated silicon to phosphine is found to have a carrier density and mobility similar to that produced by similar devices patterned by STM.

Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional finite element analysis code for solids and structures subjected to extensive contact and large deformations, encompassing explicit and implicit dynamic as well as quasistatic loading regimes. This document supplements the primary Sierra/SM 4.56 User’s Guide, describing capabilities specific to Goodyear analysis use cases, including additional implicit solver options, material models, finite element formulations, and contact settings.

Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high fidelity, validated models used in modal, vibration, static and shock analysis of structural systems. This manual describes the theory behind many of the constructs in Sierra/SD. For a more detailed description of how to use Sierra/SD, we refer the reader to Sierra/SD, User's Notes. Many of the constructs in Sierra/SD are pulled directly from published material. Where possible, these materials are referenced herein. However, certain functions in Sierra/SD are specific to our implementation. We try to be far more complete in those areas. The theory manual was developed from several sources including general notes, a programmer notes manual, the user's notes and of course the material in the open literature.

This document presents tests from the Sierra Structural Mechanics verification test suite. Each of these tests is run nightly with the Sierra/SD code suite and the results of the test checked versus the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the Sierra/SD code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.

We report on the experimental observation of a decreased self-injection threshold by using laser pulses with circular polarization in laser wakefield acceleration experiments in a nonpreformed plasma, compared to the usually employed linear polarization. A significantly higher electron beam charge was also observed for circular polarization compared to linear polarization over a wide range of parameters. Theoretical analysis and quasi-3D particle-in-cell simulations reveal that the self-injection and hence the laser wakefield acceleration is polarization dependent and indicate a different injection mechanism for circularly polarized laser pulses, originating from larger momentum gain by electrons during above threshold ionization. This enables electrons to meet the trapping condition more easily, and the resulting higher plasma temperature was confirmed via spectroscopy of the XUV plasma emission.

Moderate-temperature thermal sources (100° to 400°C) that radiate waste heat are often the by-product of mechanical work, chemical or nuclear reactions, or information processing. We demonstrate conversion of thermal radiation into electrical power using a bipolar grating-coupled complementary metal-oxide-silicon (CMOS) tunnel diode. A two-step photon-assisted tunneling charge pumping mechanism results in separation of charge carriers in pn-junction wells leading to a large open-circuit voltage developed across a load. Electrical power generation from a broadband blackbody thermal source has been experimentally demonstrated with converted power densities of 27 to 61 microwatts per square centimeter for thermal sources between 250° and 400°C. Scalable, efficient conversion of radiated waste heat into electrical power can be used to reduce energy consumption or to power electronics and sensors.

We report on the experimental observation of a decreased self-injection threshold by using laser pulses with circular polarization in laser wakefield acceleration experiments in a nonpreformed plasma, compared to the usually employed linear polarization. A significantly higher electron beam charge was also observed for circular polarization compared to linear polarization over a wide range of parameters. Theoretical analysis and quasi-3D particle-in-cell simulations reveal that the self-injection and hence the laser wakefield acceleration is polarization dependent and indicate a different injection mechanism for circularly polarized laser pulses, originating from larger momentum gain by electrons during above threshold ionization. This enables electrons to meet the trapping condition more easily, and the resulting higher plasma temperature was confirmed via spectroscopy of the XUV plasma emission.

Low-salinity waterflooding (LSWF) has proven to improve oil recovery in carbonate formations through rock wettability alteration, although the underlying mechanism remains elusive. Multivalent ionic exchange and calcite dissolution have usually been investigated using geochemical analysis in secondary coreflooding. In this work, coreflooding, in tertiary mode, coupled with a surface reactivity analysis approach was employed to investigate the interplay of wettability alteration mechanisms such as mineral dissolution, electrostatic bond attraction, and the effect of pH at in situ conditions. Improved oil recovery (IOR) in tertiary mode observed by coreflooding in Indiana limestone rocks showed an ionic strength dependence, that is, reducing brine ionic strength resulted in an increase in oil recovery. Coreflooding results showed that the seawater and low-salinity brines deprived of Mg2+ ions resulted in the lowest IOR in tertiary mode, indicating the significance of Mg2+ on IOR in limestone rocks. Similar results were observed through the contact angle measurement showing the limestone rock wettability state dependence on ionic strength and the effect of Mg2+ ions. Surface reactivity analysis showed an increase in solution pH, Ca2+ and Mg2+ ions concentration in the effluent solution from the coreflooding in tertiary mode using low salinity brines (about 40 and 20% increase in the effluent composition for Ca2+ and Mg2+, respectively). These changes in solution composition were used to calculate the in situ oil-brine and rock-brine zeta potential using a validated surface complexation model, showing the changes of zeta potential as brine is injected into limestone rocks. The results show that using seawater-like brine in tertiary mode resulted in no mineral dissolution or ionic exchange. However, improved oil recovery (IOR) using such seawater-like brine was due to wettability alteration caused by reduced electrostatic bond attraction associated with Mg2+ ions [from 2.6 × 10-13 (mol/m2)2 for formation water salinity to 1.5 × 10-13 (mol/m2)2 for seawater salinity]. Using low-salinity brines in tertiary mode improved oil recovery by mineral dissolution, resulting in oil desorption and an increase in solution pH. The increase in solution pH also resulted in reduced electrostatic bond attraction which lead to rock wettability alteration using low-salinity brines.

Detailed speciation of electrolytes as a function of chemical system and concentration provides the foundation for understanding bulk transport as well as possible decomposition mechanisms. In particular, multivalent electrolytes have shown a strong coupling between anodic stability and solvation structure. Furthermore, solvents that are found to exhibit reasonable stability against alkaline-earth metals generally exhibit low permittivity, which typically increases the complexity of the electrolyte species. To improve our understanding of ionic population and associated transport in these important classes of electrolytes, the speciation of Mg(TFSI)2 in monoglyme and diglyme systems is studied via a multiscale thermodynamic model using first-principles calculations for ion association and molecular dynamics simulations for dielectric properties. The results are then compared to Raman and dielectric relaxation spectroscopies, which independently confirm the modeling insights. We find that the significant presence of free ions in the low-permittivity glymes in the concentration range from 0.02 to 0.6 M is well-explained by the low-permittivity redissociation hypothesis. Here, salt speciation is largely dictated by long-range electrostatics, which includes permittivity increases due to polar contact ion pairs. The present results suggest that other low-permittivity multivalent electrolytes may also reach high conductivities as a result of redissociation.

Molten Salt Reactors (MSRs) have seen a resurgence of interest in the past decade around the world. Support for these activities is provided from both national and private sources. The largest difference from the 2011 GIF MSR PR&PP evaluation consequently is the transition from evaluating academic systems focused on exploring the technical potential of MSRs to those of companies and countries focusing on near-term deployment. A wide variety of designs currently exist ranging from solid to liquid-fueled designs, with salt processing on-site or off-site, and a variety of fuel choices. As such, the proliferation resistance and physical protection aspects will have significantly more variation depending on reactor design than the other advanced reactors. The rapid introduction and evolution of innovative MSR designs inevitably means that technology specific details of overview reports, such as this one, become rapidly outdated. Consequently, this report focuses on essential features required for any MSR rather than specific design aspects.

The behavior of commercially available potential obscurants for cobalt-60 (⁶⁰Co) wet-source storage industrial irradiator facilities (IRFs) were further evaluated for corrosive behavior of Nordion C-188 pencil stubs and obscurant properties under radiation exposure (⁶⁰Co). The potential obscurants studied included: titania aqueous dispersions (TAD - water soluble white paint), Chlorazol Black (CBOD - Chlorazol Black organic dye), powdered milk (COW - calcium obscurant in water), diatomaceous earth (DEA - diatomaceous earth additive), and rhodamine 6G (R6G). For corrosion efforts, stubs from an inert C-188 pencil-source rod were soaked in obscurant solutions and visually inspected. For radiation stability, obscurant samples were exposed to ⁶⁰Co radiation sources at 207 rad/s. The results from these studies reveal: the obscurants had no impact on the surrogate samples and may assist in terms of corrosion resistance; materials that did not rely on organic compounds to provide obscurance performed the best, as the organic compounds decomposed too rapidly in the high radiation environment, whereas the materials survived.

Deep learning has been successfully applied to the segmentation of 3D Computed Tomography (CT) scans. Establishing the credibility of these segmentations requires uncertainty quantification (UQ) to identify untrustworthy predictions. Recent UQ architectures include Monte Carlo dropout networks (MCDNs), which approximate deep Gaussian processes, and Bayesian neural networks (BNNs), which learn the distribution of the weight space. BNNs are advantageous over MCDNs for UQ but are thought to be computationally infeasible in high dimension, and neither architecture has produced interpretable geometric uncertainty maps. We propose a novel 3D Bayesian convolutional neural network (BCNN), the first deep learning method which generates statistically credible geometric uncertainty maps and scales for application to 3D data. We present experimental results on CT scans of graphite electrodes and laser-welded metals and show that our BCNN outperforms an MCDN in recent uncertainty metrics. The geometric uncertainty maps generated by our BCNN capture distributions of sigmoid values that are interpretable as confidence intervals, critical for applications that rely on deep learning for high-consequence decisions.

Data scans were performed on a Zeiss Xradia 520 Versa operated by departments 1851 (Philip Noell) and 1819 (James Griego). Sample 1, 2, and 3 Catheters were scanned with a 30 um pixel (low-resolution) to get an overall view of the part. (This does not include the entire height of the catheter assembly.) The following slides show the Z, Y, and X slice plane at a specific cross-hair location. We can perform a higher resolution scan down to —0.7 um pixel size including a limited field of view of ~700 um wide. Slide 5 has some requests for the customer for further scan locations. These catheters were provided to us by Simon Dunham of Weill Cornell Medical College.

The Mobile Radiation Detection and Identification System (MRDIS) is a large mobile scanner that inspects containers in transit from cargo ships for radiological materials. The MRDIS platform operates as a two-part system with one MRDIS using a plastic Polyvinyl Toleune (synthetic polymer) for primary detection and another MRDIS that uses spectroscopic detectors for secondary isotopic identification. MRDIS can operate either independently or as part of a team, depending on the needs of the port. MRDIS is controlled by a human operator, who searches the computer monitor for any traces of radiological materials when the containers pass through the center of the system. Each MRDIS can also feed data into a central system or collect data on its own for additional material analysis. The system integrates radiation detection, radioisotope identification, an optical character recognition system, occupancy/speed sensors, wireless communications, and data processing capabilities to discern what specific radiological materials are of particular interest. In addition, Sandia engineers created a detailed set of requirements for subsequent models, allowing for faster implementation of additional detection systems.

We report isotopic shifts and hyperfine structures of selected U transitions employing tunable spectroscopy viz: laser-induced fluorescence and laser absorption spectroscopy of laser ablation plumes. The plasmas were produced during ns laser ablation on a natural U metal target which contains 0.73% ²³⁵U. Our results show that isotopic shifts between ²³⁸U and ²³⁵U are entangled with hyperfine structures of ²³⁵U. Measurements obtained using laser-induced fluorescence are affected by the high absorbance of ²³⁸U. Time-resolved laser absorption spectroscopy is carried out for evaluating the optical absorption and estimating the hyperfine constants.

A number of applications in basic science and technology would benefit from high-fidelity photon-number-resolving photodetectors. While some recent experimental progress has been made in this direction, the requirements for true photon number resolution are stringent, and no design currently exists that achieves this goal. Here we employ techniques from fundamental quantum optics to demonstrate that detectors composed of subwavelength elements interacting collectively with the photon field can achieve high-performance photon number resolution. We propose a new design that simultaneously achieves photon number resolution, high efficiency, low jitter, low dark counts, and high count rate. We discuss specific systems that satisfy the design requirements, pointing to the important role of nanoscale device elements.

Multi-shaker vibration testing is gaining interest from structural dynamics test engineers as it can provide a much more accurate match to complicated field vibration responses than traditional single-axis shaker tests. However, the force capabilities of the small modal shakers typically used in multi-shaker vibration tests has limited the achievable response levels. To date, most multi-shaker vibration tests have been performed using a variety of standard, commercially-available control systems. While these control systems are adequate for a wide range of multiple-input/multiple-output tests, their control algorithms have not been tailored for the specific problem of multi-shaker vibration tests: efficiently coordinating the various shakers to work together to achieve a desired response. Here, a new input estimation algorithm is developed and demonstrated using simulations and actual test data. This algorithm, dubbed shape-constrained input estimation, is shown to effectively coordinate multiple shakers using a set of constraint vectors based on the deflection shapes of the test structure. This is accomplished by using the singular vector shapes of the system frequency response matrix, which allows the constraint vectors to automatically change as a function of frequency. Simulation and test results indicate a significant reduction in the input forces required to achieve a desired response. Finally, the results indicate that shape-constrained input estimation is an effective method to achieve higher response levels from limited shaker forces which will enable higher level multi-shaker vibration tests to be performed.

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAME advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAME library in application, this effort seeks to document and verify the various models in the LAME library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

Presented in this document are tests that exist in the Sierra/SolidMechanics example problem suite, which is a subset of the Sierra/SM regression and performance test suite. These examples showcase common and advanced code capabilities. A wide variety of other regression and verification tests exist in the Sierra/SM test suite that are not included in this manual.

Recent dynamic compression experiments [M. D. Knudson et al., Science 348, 1455 (2015); P. M. Celliers et al., Science 361, 677 (2018)] have observed the insulator-metal transition in dense liquid deuterium, but with an approximately 95-GPa difference in the quoted pressures for the transition at comparable estimated temperatures. It was claimed in the latter of these two papers that a very large latent heat effect on the temperature was overlooked in the first, requiring correction of those temperatures downward by a factor of 2, thereby putting both experiments on the same theoretical phase boundary and reconciling the pressure discrepancy. We have performed extensive path-integral molecular dynamics calculations with density functional theory to directly calculate the isentropic temperature drop due to latent heat in the insulator-metal transition for dense liquid deuterium and show that this large temperature drop is not consistent with the underlying thermodynamics.

The quality of a sonar array's localization capabilities, often expressed as directivity, is limited by the sonar's aperture, that is, the length of the sonar array. Previous attempts to improve directivity, without increasing array size, have been moderately successful. Wave scattering within a nontraditional array, such as an array fabricated from a non-homogeneous material, could provide additional information to the localization calculations and improve array directivity without increasing the size of the array. An investigation of array directivity improvement through wave scattering is performed. This paper modifies existing localization and directivity calculations to consider the scattered waves and uses the derived equations to explain why previous proposed scattering was incapable of increasing directivity. Finally, a scattering relationship capable of enhancing array localization without increasing array size is proposed, and the directivity improvement claims are verified with beamform plot comparisons and directivity index calculations.

Light hydrocarbons (C1–C3) are used as basic energy feedstocks and as commodity organic compounds for the production of many industrially necessary chemicals. Due to the nature of the raw materials and production processes, light hydrocarbons are generated as mixtures, but the high-purity single-component products are of vital importance to the petrochemical industry. Consequently, the separation of these C1–C3 products is a crucial industrial procedure that comprises a significant share of the total global energy consumption per year. As a complement to traditional separation methods (distillation, partial hydrogenation, etc.), adsorptive separations using porous solids have received widespread attention due to their lower energy costs and higher efficiency. Extensive research has been devoted to the use of porous materials such as zeolites and metal-organic frameworks (MOFs) as solid adsorbents for these key separations, owing to the high porosity, tunable pore structures, and unsaturated metal sites present in these materials. Recently, porous organic framework (POF) materials composed of organic building blocks linked by covalent bonds have also shown excellent properties in light hydrocarbon adsorption and separation, sparking interest in the use of these materials as adsorbents in separation processes. This Minireview summarizes the recent advances in the use of POFs for light hydrocarbon separations, including the separation of mixtures of methane/ethane, methane/propane, ethylene/ethane, acetylene/ethylene, and propylene/propane, while highlighting the relationships between the structural features of these materials and their separation performances. Finally, the difficulties, challenges, and opportunities associated with leveraging POFs for light hydrocarbon separations are discussed to conclude the review.

Nuclear spins are highly coherent quantum objects. In large ensembles, their control and detection via magnetic resonance is widely exploited, for example, in chemistry, medicine, materials science and mining. Nuclear spins also featured in early proposals for solid-state quantum computers1 and demonstrations of quantum search2 and factoring3 algorithms. Scaling up such concepts requires controlling individual nuclei, which can be detected when coupled to an electron4–6. However, the need to address the nuclei via oscillating magnetic fields complicates their integration in multi-spin nanoscale devices, because the field cannot be localized or screened. Control via electric fields would resolve this problem, but previous methods7–9 relied on transducing electric signals into magnetic fields via the electron–nuclear hyperfine interaction, which severely affects nuclear coherence. Here we demonstrate the coherent quantum control of a single 123Sb (spin-7/2) nucleus using localized electric fields produced within a silicon nanoelectronic device. The method exploits an idea proposed in 196110 but not previously realized experimentally with a single nucleus. Our results are quantitatively supported by a microscopic theoretical model that reveals how the purely electrical modulation of the nuclear electric quadrupole interaction results in coherent nuclear spin transitions that are uniquely addressable owing to lattice strain. The spin dephasing time, 0.1 seconds, is orders of magnitude longer than those obtained by methods that require a coupled electron spin to achieve electrical driving. These results show that high-spin quadrupolar nuclei could be deployed as chaotic models, strain sensors and hybrid spin-mechanical quantum systems using all-electrical controls. Integrating electrically controllable nuclei with quantum dots11,12 could pave the way to scalable, nuclear- and electron-spin-based quantum computers in silicon that operate without the need for oscillating magnetic fields.

Societal verification-the use of data produced by the public to support confirmation that a state is in compliance with its nonproliferation or arms control obligations-is a concept as old as nonproliferation and arms control proposals themselves. With the tremendous growth in access to the Internet, and its accompanying public generation of and access to data, the concept of societal verification has undergone a recent resurgence in popularity. This chapter explores societal verification through two mechanisms of collecting and analyzing societallyproduced data: mobilization and observation. It describes current applications and research in each area before providing an overview of challenges and considerations that must be addressed in order to bring societally-produced data into an official verification regime. The chapter concludes by emphasizing that the role of societal verification, if any, in nonproliferation and arms control will supplement rather than supplant traditional verification means.

This paper demonstrates a monolithic surface acoustic wave amplifier fabricated by state-of-the-art heterogenous integration of a III-V InGaAs-based epitaxial material stack and LiNbO3. We compare amplification of Raleigh-SAW and leaky-SAW modes on a on Y-cut, X-propagating delay line amplifier. Due to the superior properties of the materials employed, we observe a net terminal gain of 3dB for an LSAW overtone mode This platform enables further advances in active and non-reciprocal piezoelectric acoustic devices.

The "how to" document is designed to help walk the analyst through difficult aspects of software usage. It should supplement both the User's manual and the Theory document, by providing examples and detailed discussion that reduce learning time for complex set ups. These documents are intended to be used together. We will not formally list all parameters for an input here — see the User's manual for this. All the examples in the "How To" document are part of the Sierra/SD test suite, and each will run with no modification. The nature of this document casts together a number of rather unrelated procedures. Grouping them is difficult. Please try to use the table of contents and the index as a guide in finding the analyses of interest.

The study of Venus' evolution is inexorably linked with studying its interior properties, which can be investigated by performing seismic studies on the planet. However, seismology on Venus has long eluded planetary scientists due to technological challenges presented by high surface temperature and pressure, which limit lifetimes of surface-based instrumentation. In this white paper, we present two complementary techniques for performing seismology on Venus by measuring the low-frequency acoustic signature (infrasound) produced by seismic activity through coupling between the solid planet and the atmosphere. These techniques may be implemented with technology available today, without the use of high-temperature electronics.

The prevalence of flammable carbon-based composite airframe materials and their use in high-temperature nuclear weapon re-entry systems requires analysts to address the abnormal thermal environment hazards associated with composite material fires. These fires tend to burn very differently than conventional fuel fires, usually burning less intensely, but much longer. This could lead to challenges in understanding margins in classic safety themes. The technical challenges in modeling the phenomena associated with these new types of fires are considerable, but new models have been developed. Their predictions have been compared with well-documented measurements of a vertical porous burner fire, known as a "wall fire" (a "wall-fire" validation simulation is reflected in the figures below). These measurements were conducted at FMGlobal, a mutual insurance company with a strong fire risk management program, as part of an ongoing collaboration between Sandia and FMGlobal. To date, the "wall-fire" scenario has been set up and initial model assessments with grid refinement studies have been conducted focusing on mesh resolutions suitable for full weapon system simulations. This work will continue with further verification and validation tasks assessing the predictions of the new model. Future work will address specific aspects of the wall models that are lacking in their predictive ability.

With the elimination of underground nuclear testing and declining defense budgets, science-based stockpile stewardship requires increased reliance on high performance modeling and simulation of weapon systems. Today's weapon systems are comprised of various electrical components and systems. As a result, there is a need for tools that will allow the use of massively parallel modeling and simulation techniques on high performance computers in existing and future weapons' electrical systems models. The Xyce Parallel Electronic Simulator is a SPICE (Simulation Program with Integrated Circuit Emphasis)- compatible circuit simulator designed to run on large-scale parallel computing platforms, though it can also execute efficiently on a variety of architectures including single processor workstations. As a mature platform for large-scale parallel circuit simulation, Xyce supports standard capabilities available in commercial simulators, in addition to various devices and models specific to Sandia's needs. Specifically, Xyce aids in the design and verification of electrical and electronic circuits and systems prior to weapons' manufacturing and deployment.

Very recently, we introduced a set of correlation consistent effective core potentials (ccECPs) constructed within full many-body approaches. By employing significantly more accurate correlated approaches, we were able to reach a new level of accuracy for the resulting effective core Hamiltonians. We also strived for simplicity of use and easy transferability into a variety of electronic structure methods in quantum chemistry and condensed matter physics. Here, as a reference for future use, we present exact or nearly exact total energy calculations for these ccECPs. The calculations cover H-Kr elements and are based on the state-of-the-art configuration interaction (CI), coupled-cluster (CC), and quantum Monte Carlo (QMC) calculations with systematically eliminated/improved errors. In particular, we carry out full CI/CCSD(T)/CCSDT(Q) calculations with cc-pVnZ with up to n = 6 basis sets and we estimate the complete basis set limits. Using combinations of these approaches, we achieved an accuracy of ≈1-10 mHa for K-Zn atoms and ≈0.1-0.3 mHa for all other elements - within about 1% or better of the ccECP total correlation energies. We also estimate the corresponding kinetic energies within the feasible limit of full CI calculations. In order to provide data for QMC calculations, we include fixed-node diffusion Monte Carlo energies for each element that give quantitative insights into the fixed-node biases for single-reference trial wave functions. The results offer a clear benchmark for future high-accuracy calculations in a broad variety of correlated wave function methods such as CI and CC as well is in stochastic approaches such as real space sampling QMC.

Permeability of salt formations is controlled by the equilibrium between the salt-brine and salt-salt interfaces described by the dihedral angle, which can change with the composition of the intergranular brine. Here, classical molecular dynamics (MD) simulations were used to investigate the structure and properties of the salt-brine interface to provide insight into the stability of salt systems. Mixed NaCl-KCl brines were investigated to explore differences in ion size on the surface energy and interface structure. Nonlinearity was noted in the salt-brine surface energy with increasing KCl concentration, and the addition of 10% KCl increased surface energies by 2-3 times (5.0 M systems). Size differences in Na+ and K+ ions altered the packing of dissolved ions and water molecules at the interface, impacting the surface energy. Additionally, ions at the interface had lower numbers of coordinating water molecules than those in the bulk and increased hydration for ions in systems with 100% NaCl or 100% KCl brines. Ultimately, small changes in brine composition away from pure NaCl altered the structure of the salt-brine interface, impacting the dihedral angle and the predicted equilibrium permeability of salt formations.

Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly parallel sparse solvers are essential for continuing advances in high-fidelity, multi-physics and multi-scale simulations, especially as we target exascale platforms. This paper describes the challenges, strategies and progress of the US Department of Energy Exascale Computing project towards providing sparse solvers for exascale computing platforms. We address the demands of systems with thousands of high-performance node devices where exposing concurrency, hiding latency and creating alternative algorithms become essential. The efforts described here are works in progress, highlighting current success and upcoming challenges. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.

QSCOUT is the Quantum Scientific Computing Open User Testbed, a trapped-ion quantum computer testbed realized at Sandia National Laboratories on behalf of the Department of Energy's Office of Science and its Advanced Scientific Computing Research (ASCR) program.

Abstract not provided.

Abstract not provided.

Feedstock variability that originates from biomass production and field conditions propagates through the value chain, posing a significant challenge to the emerging biorefinery industry. Variability in feedstock properties impacts feeding, handling, equipment operations, and conversion performance. Feedstock quality attributes, and their variations, are often overlooked in assessing feedstock value and utilization for conversion to fuels, chemicals, and products. This study developed and employed a multiscale analytical characterization approach coupled with data analytic methods to better understand the sources and distribution of feedstock quality variability through evaluation of 24 corn stover bales collected in 4 counties of Iowa. In total, 216 core samples were generated by sampling nine positions on each bale using a reliable bale coring process. The samples were characterized for a broad suite of physicochemical properties ranging across field and bale, macro, micro, and molecular scales. Results demonstrated that feedstock quality attributes can vary at all spatial scales and that multiple sources of variability must be considered in order to establish and manage biomass quality for conversion processes.

The Rydberg blockade mechanism is now routinely considered for entangling qubits encoded in clock states of neutral atoms. Challenges towards implementing entangling gates with high fidelity include errors due to thermal motion of atoms, laser amplitude inhomogeneities, and imperfect Rydberg blockade. We show that adiabatic rapid passage by Rydberg dressing provides a mechanism for implementing two-qubit entangling gates by accumulating phases that are robust to these imperfections. We find that the typical error in implementing a two-qubit gate, such as the controlled phase gate, is dominated by errors in the single-atom light shift, and that this can be easily corrected using adiabatic dressing interleaved with a simple spin echo sequence. This results in a two-qubit Mølmer-Sørensen gate. A gate fidelity ∼0.995 is achievable with modest experimental parameters and a path to higher fidelities is possible for Rydberg states in atoms with a stronger blockade, longer lifetimes, and larger Rabi frequencies.

A novel modeling framework that simultaneously improves accuracy, predictability, and computational efficiency is presented. It embraces the benefits of three modeling techniques integrated together for the first time: surrogate modeling, parameter inference, and data assimilation. The use of polynomial chaos expansion (PCE) surrogates significantly decreases computational time. Parameter inference allows for model faster convergence, reduced uncertainty, and superior accuracy of simulated results. Ensemble Kalman filters assimilate errors that occur during forecasting. To examine the applicability and effectiveness of the integrated framework, we developed 18 approaches according to how surrogate models are constructed, what type of parameter distributions are used as model inputs, and whether model parameters are updated during the data assimilation procedure. We conclude that (1) PCE must be built over various forcing and flow conditions, and in contrast to previous studies, it does not need to be rebuilt at each time step; (2) model parameter specification that relies on constrained, posterior information of parameters (so-called Selected specification) can significantly improve forecasting performance and reduce uncertainty bounds compared to Random specification using prior information of parameters; and (3) no substantial differences in results exist between single and dual ensemble Kalman filters, but the latter better simulates flood peaks. The use of PCE effectively compensates for the computational load added by the parameter inference and data assimilation (up to ~80 times faster). Therefore, the presented approach contributes to a shift in modeling paradigm arguing that complex, high-fidelity hydrologic and hydraulic models should be increasingly adopted for real-time and ensemble flood forecasting.

Representations are developed and illustrated for the distribution of link property values at the time of link failure in the presence of aleatory uncertainty in link properties. The following topics are considered: (i) defining properties for weak links and strong links, (ii) cumulative distribution functions (CDFs) for link failure time, (iii) integral-based derivation of CDFs for link property at time of link failure, (iv) sampling-based approximation of CDFs for link property at time of link failure, (v) verification of integral-based and sampling-based determinations of CDFs for link property at time of link failure, (vi) distributions of link properties conditional on time of link failure, and (vii) equivalence of two different integral-based derivations of CDFs for link property at time of link failure.

This numerical study compares thewave field generated by the spectral wave action balance code, SNL-SWAN, to the linear-wave boundary-element method (BEM) code, WAMIT. The objective of this study is to assess the performance of SNL-SWAN for modeling wave field effects produced by individual wave energy converters (WECs) and wave farms comprising multiple WECs by comparing results from SNL-SWAN with those produced by the BEM codeWAMIT. BEM codes better model the physics of wave-body interactions and thus simulate a more accurate near-field wave field than spectral codes. In SNL-SWAN, the wave field's energy extraction is modeled parametrically based on the WEC's power curve. The comparison between SNL-SWAN andWAMIT is made over a range of incident wave conditions, including short-, medium-, and long-wavelength waves with various amounts of directional spreading, and for three WEC archetypes: a point absorber (PA), a pitching flap (PF) terminator, and a hinged raft (HR) attenuator. Individual WECs and wave farms of five WECs in various configuration were studied with qualitative comparisons made of wave height and spectra at specific locations, and quantitative comparisons of the wave fields over circular arcs around the WECs as a function of radial distance. Results from this numerical study demonstrate that in the near-field, the difference between SNL-SWAN andWAMIT is relatively large (between 20% and 50%), but in the far-field from the array the differences are minimal (between 1% and 5%). The resultant wave field generated by the two different numerical approaches is highly dependent on parameters such as: directional wave spreading, wave reflection or scattering, and the WEC's power curve.

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems involving multiple time-dependent failure modes are developed. The following topics are described: (i) defining properties for WLs and SLs, (ii) background on cumulative distribution functions (CDFs) for link failure time, link property value at link failure, and time at which LOAS occurs, (iii) CDFs for failure time margins defined by (time at which SL system fails) − (time at which WL system fails), (iv) CDFs for SL system property values at LOAS, (v) CDFs for WL/SL property value margins defined by (property value at which SL system fails) − (property value at which WL system fails), and (vi) CDFs for SL property value margins defined by (property value of failing SL at time of SL system failure) − (property value of this SL at time of WL system failure). Included in this presentation is a demonstration of a verification strategy based on defining and approximating the indicated margin results with (i) procedures based on formal integral representations and associated quadrature approximations and (ii) procedures based on algorithms for sampling-based approximations.

Nearly all model-reduction techniques project the governing equations onto a linear subspace of the original state space. Such subspaces are typically computed using methods such as balanced truncation, rational interpolation, the reduced-basis method, and (balanced) proper orthogonal decomposition (POD). Unfortunately, restricting the state to evolve in a linear subspace imposes a fundamental limitation to the accuracy of the resulting reduced-order model (ROM). In particular, linear-subspace ROMs can be expected to produce low-dimensional models with high accuracy only if the problem admits a fast decaying Kolmogorov n-width (e.g., diffusion-dominated problems). Unfortunately, many problems of interest exhibit a slowly decaying Kolmogorov n-width (e.g., advection-dominated problems). To address this, we propose a novel framework for projecting dynamical systems onto nonlinear manifolds using minimum-residual formulations at the time-continuous and time-discrete levels; the former leads to manifold Galerkin projection, while the latter leads to manifold least-squares Petrov–Galerkin (LSPG) projection. We perform analyses that provide insight into the relationship between these proposed approaches and classical linear-subspace reduced-order models; we also derive a posteriori discrete-time error bounds for the proposed approaches. In addition, we propose a computationally practical approach for computing the nonlinear manifold, which is based on convolutional autoencoders from deep learning. Finally, we demonstrate the ability of the method to significantly outperform even the optimal linear-subspace ROM on benchmark advection-dominated problems, thereby demonstrating the method's ability to overcome the intrinsic n-width limitations of linear subspaces.

High resolution electron backscatter diffraction (HREBSD), an SEM-based diffraction technique, may be used to measure the lattice distortion of a crystalline material and to infer the geometrically necessary dislocation content. Uncertainty in the image correlation process used to compare diffraction patterns leads to an uneven distribution of measurement noise in terms of the lattice distortion, which results in erroneous identification of dislocation type and density. This work presents a method of reducing noise in HREBSD dislocation measurements by removing the effect of the most problematic components of the measured distortion. The method is then validated by comparing with TEM analysis of dislocation pile-ups near a twin boundary in austenitic stainless steel and with ECCI analysis near a nano-indentation on a tantalum oligocrystal. The HREBSD dislocation microscopy technique is able to resolve individual dislocations visible in TEM and ECCI and correctly identify their Burgers vectors.

Validated models of melt cast explosives exposed to accidental fires are essential for safety analysis. In the current work, we provide several experiments that can be used to develop and validate cookoff models of melt cast explosives such as Comp-B3 composed of 60:40 wt% RDX:TNT. We present several vented and sealed experiments from 2.5 mg to 4.2 kg of Comp-B3 in several configurations. We measured pressure, spatial temperature, and ignition time. Some experiments included borescope images obtained during both vented and sealed decomposition. We observed the TNT melt, the suspension of RDX particles in the melt, bubble formation caused by RDX decomposition, and bubble-induced mixing of the suspension. The RDX suspension did not completely dissolve, even as temperatures approached ignition. Our results contrast with published measurements of RDX solubility in hot TNT that suggest RDX would be completely dissolved at these high temperatures. These different observations are attributed to sample purity. We did not observe significant movement of the two-phase mixture until decomposition gases formed bubbles. Bubble generation was inhibited in our sealed experiments and suppressed mixing.

Comparison between an open divertor and a more-closed divertor in DIII-D demonstrates detachment up to 40% lower pedestal density (n e, ped) in the closed divertor due to a combination of decreased fueling of the pedestal and increased dissipation in the scrape off layer (SOL) in the closed divertor, both resulting from increased neutral trapping in the divertor. Predicting whether the relationship between divertor closure and detachment will hold for an opaque SOL, in which the contribution of ionizing neutrals to fueling the pedestal is lessened, requires separating out different mechanisms contributing to the density difference at detachment. A series of experiments on DIII-D characterizes matched discharges using various divertor configurations to isolate the effects of divertor closure. These experiments show detachment up to 25% lower n e, sep in the closed divertor than in the open divertor, supported by simulations showing increased neutral trapping, and hence, increased dissipation, in the closed divertor. A difference in n e, ped / n e, sep is also seen: for matched n e, sep, the closed divertor has up to 20% lower n e, ped, consistent with modeling showing a smaller ionization fraction inside the separatrix in this case. Understanding how these pieces fit together will help in the development of predictive models of pedestal density and detached divertors compatible with a high performance core.

We report experimental results on relativistic electron beam (REB) transport in a set of cold and shock-heated carbon samples using the high-intensity kilojoule-class OMEGA EP laser. The REB energy distribution and transport were diagnosed using an electron spectrometer and X-ray fluorescence measurements from a Cu tracer buried at the rear side of the samples. The measured rear REB density shows brighter and narrower signals when the targets were shock-heated. Hybrid PIC simulations using advanced resistivity models in the target warm-dense-matter (WDM) conditions confirm this observation. We show that the resistivity response of the media, which governs the self-generated resistive fields, is of paramount importance to understand and correctly predict the REB transport.

The precise patterning of front-side mesas, backside vias, and selective removal of ternary alloys are all needed for power device fabrication in the various wide bandgap (AlGaN/GaN, SiC) and ultrawide bandgap (high Al-content alloys, boron nitride, Ga2O3, diamond) semiconductor technologies. The plasma etching conditions used are generally ion-assisted because of the strong bond strengths in these materials, and this creates challenges for the choice of masks in order to have sufficient selectivity over the semiconductor and to avoid mask erosion and micromasking issues. It can also be challenging to achieve practical etch rates without creating excessive damage in the patterned surface. The authors review the optimum choices for plasma chemistries for each of the semiconductors and acknowledge the pioneering work of John Coburn, who first delineated the ion-assisted etch mechanism.

KinBot is a Python code that automatically characterizes kinetically important stationary points on reactive potential energy surfaces and arranges the results into a form that lends itself easily to master equation calculations. This version of KinBot tackles C, H, O and S atom containing species and unimolecular (isomerization or dissociation) reactions. KinBot iteratively changes the geometry of the reactant to obtain initial guesses for reactive saddle points defined by KinBot's reaction types, which are then optimized by a third-party quantum chemistry package. KinBot verifies the connectivity of the saddle points with the reactant and identifies the products through intrinsic reaction coordinate calculations. New calculations can be automatically spawned from the products to obtain complete potential energy surfaces. The utilities of KinBot include conformer searches, projected frequency and hindered rotor calculations, and the automatic determination of the rotational symmetry numbers. Input files for popular RRKM master equation codes are automatically built, enabling an automated workflow all the way to the calculation of pressure and temperature dependent rate coefficients. Four examples are included. (i) [1,3]-sigmatropic H-migration reactions of unsaturated hydrocarbons and oxygenates are calculated to assess the relative importance of suprafacial and antrafacial reactions. (ii) Saddle points on three products of gamma-valerolactone thermal decomposition are studied and compared to literature potential energy surfaces. (iii) The previously published propene+OH reaction is reproduced to show the capability of building an entire potential energy surface. (iv) All species up to C4 in the Aramco Mech 2.0 are subjected to a KinBot search. Program summary: Program title: KinBot Program files doi: http://dx.doi.org/10.17632/hsh6dvv2zj.1 Licensing provisions: BSD 3-Clause Programming language: Python Supplementary material: 1. A static version of the source code (KinBot.tar), 2. The manual for the static version (KinBot_Manual.pdf) 3. Geometries and energies of the stationary points on the potential energy surface of the sigmatropic reaction search (sigmatropic_H_shift.out) 4. Geometries and energies of the stationary points on the potential energy surface of the propene+ OH central and terminal addition reaction (propene+oh central addition.out, propene+oh terminal addition.out) 5. Geometries and energies of the stationary points on the potential energy surface of gamma valerolactone, 4-pentenoic acid and 3-pentenoic acid (GVL energies and geometries.out, 4PA energies and geometries.out, 3PA energies and geometries.out) 6. Example runs including all input and output files for a one-well search for propanol radical, full PES search for the n-pentyl radical, a search for all homolytic scission in propanol, and the reaction searches for GVL (output.zip) 7. Results of symmetry calculations for a literature benchmark dataset (Symmetry_correct.pdf, Symmetry_wrong.pdf) Nature of problem: Automatic discovery of unimolecular reaction pathways (isomerization and dissociation) for molecules and radicals relevant in gas-phase combustion and atmospheric chemistry, including oxidation and pyrolytic processes for structures including carbon, oxygen, sulfur and hydrogen atoms. The reactants, products, and transition states are characterized using a suite of tools coupled to electronic structure codes, and the results are provided in a format that lends itself easily to calculating rate coefficients based on statistical rate theories with other external codes. Solution method: Reaction pathways are identified using heuristic searches starting from a reactant by iteratively altering its geometry toward a good guess for a transition state for reactions with barriers. The transition state is identified as a first-order saddle point on the potential energy surface, which is located using local optimization methods of third-party quantum chemistry codes. We use intrinsic reaction coordinate calculations to verify the direct connectivity of the saddle point to the reactant and to identify the product species. Conformational searches, hindered rotor potentials, frequency calculations, and high-level optimizations yield the necessary data for RRKM master equation calculations. Additional comments including restrictions and unusual features: KinBot is designed to run on Unix clusters, and is written in Python, compatible with versions 2.7 and 3. It communicates with a PBS or SLURM workload manager to submit quantum chemistry calculations to third-party software. It makes use of a modified fork of ASE for the input writing, calling and output parsing of the quantum chemistry software which has been tested with Gaussian (G09RevD.01). OpenBabel (2.4.1) and RDKit (2018.09.01) are used to convert smiles to internal species representations and for species comparison and results visualization. The output of KinBot can be visualized with the PESViewer script, and graph structures are drawn using NetworkX. The master equation solvers MESS or MESMER are needed to calculate rate coefficients at the end of a given run. This version of KinBot can handle H, C, S, and O atom-containing molecules, and searches for isomerization and dissociation pathways.

The fractional Laplacian in Rd, which we write as (−Δ)α/2 with α∈(0,2), has multiple equivalent characterizations. Moreover, in bounded domains, boundary conditions must be incorporated in these characterizations in mathematically distinct ways, and there is currently no consensus in the literature as to which definition of the fractional Laplacian in bounded domains is most appropriate for a given application. The Riesz (or integral) definition, for example, admits a nonlocal boundary condition, where the value of a function must be prescribed on the entire exterior of the domain in order to compute its fractional Laplacian. In contrast, the spectral definition requires only the standard local boundary condition. These differences, among others, lead us to ask the question: “What is the fractional Laplacian?” Beginning from first principles, we compare several commonly used definitions of the fractional Laplacian theoretically, through their stochastic interpretations as well as their analytical properties. Then, we present quantitative comparisons using a sample of state-of-the-art methods. We discuss recent advances on nonzero boundary conditions and present new methods to discretize such boundary value problems: radial basis function collocation (for the Riesz fractional Laplacian) and nonharmonic lifting (for the spectral fractional Laplacian). In our numerical studies, we aim to compare different definitions on bounded domains using a collection of benchmark problems. We consider the fractional Poisson equation with both zero and nonzero boundary conditions, where the fractional Laplacian is defined according to the Riesz definition, the spectral definition, the directional definition, and the horizon-based nonlocal definition. We verify the accuracy of the numerical methods used in the approximations for each operator, and we focus on identifying differences in the boundary behaviors of solutions to equations posed with these different definitions. Through our efforts, we aim to further engage the research community in open problems and assist practitioners in identifying the most appropriate definition and computational approach to use for their mathematical models in addressing anomalous transport in diverse applications.

Low-frequency sound ≤20 Hz, known as infrasound, is generated by a variety of natural and anthropogenic sources. Following an event, infrasonic waves travel through a dynamic atmosphere that can change on the order of minutes. This makes infrasound event classification a difficult problem, as waveforms from the same source type can look drastically different. Event classification usually requires ground-truth information from seismic or other methods. This is time consuming, inefficient, and does not allow for classification if the event locates somewhere other than a known source, the location accuracy is poor, or ground truth from seismic data is lacking. Here,we compare the performance of the state of the art for infrasound event classification, support vector machine (SVM) to the performance of a convolutional neural network (CNN), a method that has been proven in tangential fields such as seismology. For a 2-class catalog of only volcanic activity and earthquake events, the fourfold average SVM classification accuracy is 75%, whereas it is 74% when using a CNN. Classification accuracies from the 4-class catalog consisting of the most common infrasound events detected at the global scale are 55% and 56% for the SVM and CNN architectures, respectively. These results demonstrate that using a CNN does not increase performance for infrasound event classification. This suggests that SVM should be the preferred classification method, as it is a simpler and more trustworthy architecture and can be tied to the physical properties of the waveforms. The SVM and CNN algorithms described in this article are not yet generalizable to other infrasound event catalogs. We anticipate this study to be a starting point for development of large and comprehensive, systematically labeled, infrasound event catalogs, as such catalogs will be necessary to provide an increase in the value of deep learning on event classification.

Causality in an engineered system pertains to how a system output changes due to a controlled change or intervention on the system or system environment. Engineered systems designs reflect a causal theory regarding how a system will work, and predicting the reliability of such systems typically requires knowledge of this underlying causal structure. The aim of this work is to introduce causal modeling tools that inform reliability predictions based on biased data sources. We present a novel application of the popular structural causal modeling (SCM) framework to reliability estimation in an engineering application, illustrating how this framework can inform whether reliability is estimable and how to estimate reliability given a set of data and assumptions about the subject matter and data generating mechanism. When data are insufficient for estimation, sensitivity studies based on problem-specific knowledge can inform how much reliability estimates can change due to biases in the data and what information should be collected next to provide the most additional information. We apply the approach to a pedagogical example related to a real, but proprietary, engineering application, considering how two types of biases in data can influence a reliability calculation.

The Lorentz-like effective medium resonance (LEMR) exhibited by the longitudinal effective permittivity of semiconductor hyperbolic metamaterials (SHMs) has been known for some time. However, direct observation of this resonance proved to be difficult. Herein, we experimentally demonstrate its existence by strongly coupling SHMs to plasmonic metasurfaces. We consider four strong coupling implementations of SHMs that exhibit different LEMR absorption profiles (both in frequency and in strength) to validate our approach.

Material fragmentation after a hypervelocity impact is important to predictive electro-optical and infrared (EO/IR) modeling. Successful comparisons with data require that hot, submicron fragments are generated in such impacts; however, experimental data has so far been unable to produce fragments of this scale. The purpose of this work was to investigate how modeling assumptions of macro-scale, bulk materials might influence the generation of debris in hypervelocity impacts and ultimately the predicted EO/IR signatures of these debris clouds. Sphere-on-plate impact simulations simplified the comparison of different modeling approaches. In one set of simulations, materials were modeled with the traditional, bulk approach. Those results were compared to simulations run with the mesoscale material grain structure explicitly modeled. This study focused on the comparison of two parameters that are tied directly to the EO/IR signature: strain rate at failure (a proxy for debris fragment size) and material temperature. Interfaces between grains, here due to void insertion, resulted in the most notable change in both the strain rate at failure and material temperature. Shock reflections from grain-void interfaces induced higher strain rates and material temperatures, and it is expected that similar effects may be produced from inclusions or dislocations in real materials. Thus, interfaces within a material may play an important role in producing smaller hot debris fragments that support the EO/IR predictive models of hypervelocity impacts.

Origami offers a distinct approach for designing and engineering new material structures and properties. The folding and stacking of atomically thin van der Waals (vdW) materials, for example, can lead to intriguing new physical properties including bandgap tuning, Van Hove singularity, and superconductivity. On the other hand, achieving well-controlled folding of vdW materials with high spatial precision has been extremely challenging and difficult to scale toward large areas. Here, a deterministic technique is reported to fold vdW materials at a defined position and direction using microfluidic forces. Electron beam lithography (EBL) is utilized to define the folding area, which allows precise control of the folding geometry, direction, and position beyond 100 nm resolution. Using this technique, single-atomic-layer vdW materials or their heterostructures can be folded without the need for any external supporting layers in the final folded structure. In addition, arrays of patterns can be folded across a large area using this technique and electronic devices that can reconfigure device functionalities through folding are also demonstrated. Such scalable formation of folded vdW material structures with high precision can lead to the creation of new atomic-scale materials and superlattices as well as opening the door to realizing foldable and reconfigurable electronics.

Scattering due to interface-roughness (IR) and longitudinal-optical (LO) phonons are primary transport mechanisms in terahertz quantum-cascade lasers (QCLs). By choosing GaAs/Al0.10Ga0.90As heterostructures with short-barriers, the effect of IR scattering is mitigated, leading to low operating current-densities. A series of resonant-phonon terahertz QCLs developed over time, achieving some of the lowest threshold and peak current-densities among published terahertz QCLs with maximum operating temperatures above 100 K. The best result is obtained for a three-well 3.1 THz QCL with threshold and peak current-densities of 134 A/cm2 and 208 A/cm2 respectively at 53 K, and a maximum lasing temperature of 135 K. Another three-well QCL designed for broadband bidirectional operation achieved lasing in a combined frequency range of 3.1-3.7 THz operating under both positive and negative polarities, with an operating current-density range of 167-322 A/cm2 at 53 K and maximum lasing temperature of 141 K or 121 K depending on the polarity of the applied bias. By showing results from QCLs developed over a period of time, here we show conclusively that short-barrier terahertz QCLs are effective in achieving low current-density operation at the cost of a reduction in peak temperature performance.

Research results for AlGaN-channel transistors are reviewed as they have progressed from low Al-content and long-channel devices to Al-rich and short-channel RF devices. Figure of merit (FOM) analysis shows encouraging comparisons relative to today's state-of-the-art GaN devices for high Al-content and elevated temperatures. Critical electric field (EC), which fuels the AlGaN transistor FOM for high Al-composition, is not measured directly, but average gate-drain electric field at breakdown is substantially better in multiple reported AlGaN-channel devices compared to GaN. Challenges for AlGaN include the constraints arising from relatively low room temperature mobility dominated by ternary alloy scattering and the difficulty of making low-resistivity Ohmic contacts to high Al-content materials. Nevertheless, considerable progress has been made recently in the formation of low-resistivity Ohmic contacts to Al-rich AlGaN by using reverse compositional grading in the semiconductor, whereby a contact to a lower-Al alloy (or even to GaN) is made. Specific contact resistivity (ρc) approaching ρc ∼2 × 10-6ωcm2 to AlGaN devices with 70% Al-content in the channel has been reported. Along with scaling of the channel length and tailoring of the threshold voltage, this has enabled a dramatic increase in the current density, which has now reached 0.6 A/mm. Excellent ION/IOFF current ratios have been reported for Schottky-gated structures, in some cases exceeding 109. Encouraging RF performance in Al-rich transistors has been reported as well, with fT and fmax demonstrated in the tens of gigahertz range for devices with less than 150 nm gates. Al-rich transistors have also shown lesser current degradation over temperature than GaN in extreme high-temperature environments up to 500 °C, while maintaining ION/IOFF ratios of ∼106 at 500 °C. Finally, enhancement-mode devices along with initial reliability and radiation results have been reported for Al-rich AlGaN transistors. The Al-rich transistors promise to be a very broad and exciting field with much more progress expected in the coming years as this technology matures.

Light coupling with patterned subwavelength hole arrays induces enhanced transmission supported by the strong surface plasmon mode. In this work, a nanostructured plasmonic framework with vertically built-in nanohole arrays at deep-subwavelength scale (6 nm) is demonstrated using a two-step fabrication method. The nanohole arrays are formed first by the growth of a high-quality two-phase (i.e., Au–TiN) vertically aligned nanocomposite template, followed by selective wet-etching of the metal (Au). Such a plasmonic nanohole film owns high epitaxial quality with large surface coverage and the structure can be tailored as either fully etched or half-way etched nanoholes via careful control of the etching process. The chemically inert and plasmonic TiN plays a role in maintaining sharp hole boundary and preventing lattice distortion. Optical properties such as enhanced transmittance and anisotropic dielectric function in the visible regime are demonstrated. Numerical simulation suggests an extended surface plasmon mode and strong field enhancement at the hole edges. Two demonstrations, including the enhanced and modulated photoluminescence by surface coupling with 2D perovskite nanoplates and the refractive index sensing by infiltrating immersion liquids, suggest the great potential of such plasmonic nanohole array for reusable surface plasmon-enhanced sensing applications.

This paper reports on a near-zero power inertial wakeup sensor system supporting digital weighting of inputs and with protection against false positives due to mechanical shocks. This improves upon existing work by combining the selectivity and sensitivity (Q-amplification) of resonant MEMS sensors with the flexibility of digital signal processing while consuming below 10 nW. The target application is unattended sensors for perimeter sensing and machinery health monitoring where extended battery life afforded by the low power consumption eliminates the need for power cables. For machinery health monitoring, the signals of interest are stationary but may contain spurious mechanical shocks.

Recent work in metal additive manufacturing (AM) suggests that mechanical properties may vary with feature size; however, these studies do not provide a statistically robust description of this phenomenon, nor do they provide a clear causal mechanism. Because of the huge design freedom afforded by 3D printing, AM parts typically contain a range of feature sizes, with particular interest in smaller features, so the size effect must be well understood in order to make informed design decisions. This work investigates the effect of feature size on the stochastic mechanical performance of laser powder bed fusion tensile specimens. A high-throughput tensile testing method was used to characterize the effect of specimen size on strength, elastic modulus and elongation in a statistically meaningful way. The effective yield strength, ultimate tensile strength and modulus decreased strongly with decreasing specimen size: all three properties were reduced by nearly a factor of two as feature dimensions were scaled down from 6.25 mm to 0.4 mm. Hardness and microstructural observations indicate that this size dependence was not due to an intrinsic change in material properties, but instead the effects of surface roughness on the geometry of the specimens. Finite element analysis using explicit representations of surface topography shows the critical role surface features play in creating stress concentrations that trigger deformation and subsequent fracture. The experimental and finite element results provide the tools needed to make corrections in the design process to more accurately predict the performance of AM components.

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Practical applications of nanocrystalline metallic thin films are often limited by instabilities. In addition to grain growth, the thin film itself can become unstable and collapse into islands through solid-state dewetting. Selective alloying can improve nanocrystalline stability, but the impact of this approach on dewetting is not clear. In this study, two alloys that exhibit nanocrystalline thermal stability as ball milled powders are evaluated as thin films. While both alloys demonstrated dewetting behavior following annealing, the severity decreased in more dilute compositions. Ultimately, a balance may be struck between nanocrystalline stability and thin film structural stability by tuning dopant concentration.

Nanocrystalline metals are promising radiation tolerant materials due to their large interfacial volume fraction, but irradiation-induced grain growth can eventually degrade any improvement in radiation tolerance. Therefore, methods to limit grain growth and simultaneously improve the radiation tolerance of nanocrystalline metals are needed. Amorphous intergranular films are unique grain boundary structures that are predicted to have improved sink efficiencies due to their increased thickness and amorphous structure, while also improving grain size stability. In this study, ball milled nanocrystalline Cu-Zr alloys are heat treated to either have only ordered grain boundaries or to contain amorphous intergranular films distributed within the grain boundary network, and are then subjected to in situ transmission electron microscopy irradiation and ex situ irradiation. Differences in defect density and grain growth due to grain boundary complexion type are then investigated. When amorphous intergranular films are incorporated within the material, fewer and smaller defect clusters are observed while grain growth is also limited, leading to nanocrystalline alloys with improved radiation tolerance.

The effect of hydrogen (H) on the deformation behavior of Monel K-500 in various isothermal heat treatment conditions (non-aged, under-aged, peak-aged, and over-aged) was assessed via uniaxial mechanical testing. H-charged and non-charged specimens were strained to failure to facilitate a comparison of ductility, fracture surface morphology, strength, and work hardening behavior. For all examined heat treatment conditions, H charging leads to a significant reduction in ductility, which is accompanied by a consistent change in fracture surface morphology from ductile microvoid coalescence to brittle intergranular fracture. While H charging led to a systematic enhancement in the yield strength of all heat treatments, the three age-hardened conditions exhibited a more than 2-fold increase relative to the non-aged heat treatment. This suggests that H modifies the dislocation–precipitate interactions, which also manifest themselves through changes in work hardening metrics related to the dislocation storage and recovery rates. In particular, the H-charged peak-aged specimen exhibited a significant increase in initial hardening (dislocation storage) rate relative to the H-charged under-aged specimen. Transmission electron microscopy of these samples revealed the onset of widespread dislocation looping in the H-charged peak-aged sample, in addition to the planar slip bands characteristic of the non-charged condition. This result suggests that hydrogen induces the particle shearing-to-looping transition at smaller particle sizes. Possible mechanistic explanations for this observed behavior are presented.

Machine learning (ML), including deep learning (DL), has become increasingly popular in the last few years due to its continually outstanding performance. In this context, we apply machine learning techniques to "learn" the microstructure using both supervised and unsupervised DL techniques. In particular, we focus (1) on the localization problem bridging (micro)structure (localized) property using supervised DL and (2) on the microstructure reconstruction problem in latent space using unsupervised DL. The goal of supervised and semi-supervised DL is to replace crystal plasticity finite element model (CPFEM) that maps from (micro)structure (localized) property, and implicitly the (micro)structure (homogenized) property relationships, while the goal of unsupervised DL is (1) to represent high-dimensional microstructure images in a non-linear low-dimensional manifold, and (2) to discover a way to interpolate microstructures via latent space associating with latent microstructure variables. At the heart of this report is the applications of several common DL architectures, including convolutional neural networks (CNN), autoencoder (AE), and generative adversarial network (GAN), to multiple microstructure datasets, and the quest of neural architecture search for optimal DL architectures.

This scenario was drafted for inclusion in a revision of Federal Radiological Monitoring and Assessment Center (FRMAC) Assessment Manual, Volume 2 - Pre-Assessed Default Scenarios. The contents of this scenario were reviewed and approved by the FRMAC Assessment Working Group in March 2020. The scenario is being issued separately from the full volume ahead of the Mars 2020 launch. The full volume will be published in the future once all scenarios are complete.

The SPARC team has completed much of the workflow development needed for the coupled and uncoupled analyses needed to support our flight test validation work. The SPARC team has continued to make progress on development activities to support unsteady, full reentry vehicle aero analysis, which have focused on turbulence modeling, uniform mesh refinement, in-situ visualization (with the Paraview/Catalyst team), and performance analysis. The SPARC team is making solid progress towards our Q4 goal of demonstrating an improved Wall Modeled Large Eddy Simulation (WMLES) capability for standard geometries using high-order finite difference, discontinuous Galerkin, and low-dissipation finite volume methods. The SPARC team has met the minimum completion criteria for parts of the L1, including documenting performance and scaling of SPARC on Trinity, Sierra and Astra, and performing runs for the flight test validation case.

Advances in FinFET design and fabrication enable manufacturing of denser, more compact integrated circuits (ICs) with substantially reduced leakage while shortening the channel-lengths. The same stress-induced leakage and breakdown degradation mechanisms that affect planar transistors also impact FinFET devices. Reliability concerns such as Bias Temperature Instability (BTI), Time Dependent Dielectric Breakdown (TDDB), and Hot Carrier Injection (HCI) become very important with changes to transistor geometry and fin sidewall crystal orientation. Recent testing has shown that FinFETs respond differently to radiation (radiation effects such as total ionizing dose) when compared to planar transistors. These reliability and radiation effects issues become very important when changing transistor geometry and scaling FinFETs towards smaller feature sizes (22-nm, 16-nm, 14- nm, 10-nm, and smaller critical dimensions). The comparable 2019 state of the art transistor densities in current high-volume manufacturing silicon-based foundries is 7-nm (ISMC, Samsung) and 10-nm (Intel) [www.anandtech.com,fuse.wikichip.org]. Released products include supporting components for the cellphone and commercial microprocessor markets respectively. Extensive development in the foundry industry is driving to a 5-nm technology node in late 2020.

Sandia National Laboratories has experienced a number of electrical events in recent years. A careful examination of data shows that for the third year in a row, two of the three most frequently categorized Occurrence Reporting and Processing System (ORPS)-reportable event types were unexpected or unintended personal contact with a hazardous energy source and a failure to follow a prescribed hazardous energy control process, as defined in the occurrence reporting criteria of DOE Order 232.2A, Occurrence Reporting and Processing of Operations Information, 2D(1) and 2D(2). Sandia policy CA001.2, Identify and Manage Issues, requires an extent-of-condition review for any high-level reportable occurrence, and the analysts were tasked to perform this EOC in light of high-level reportable occurrence NA-SS-SNL-1000-2019- 0007, Contact with Electrical Energy During Marx Capacitor Troubleshooting. This extent of condition not only evaluated the 10 reportable electrical occurrences for Fiscal Year 2019, but also looked at 11 other related events: those involving control of hazardous energy and electrical events associated with less than hazardous energy.1 This Extent-of-Condition report makes several observations, conclusions, and recommendations for improvement.

The Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department (NMED) issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015) to the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA) and its Management and Operating (M&O) contractor. The current M&O contractor is National Technology & Engineering Solutions of Sandia, LLC (NTESS). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for calendar year (CY) 2019, as required by the Permit.

A table showing sampling results from 2019 is provided.

This lessons learned snapshot covers the topic of traffic safety around the Sandia campus.

Hydrogen Fueling Infrastructure Research and Station Technology (H2FIRST) is a project initiated by the DOE in 2015 and executed by Sandia National Laboratories and the National Renewable Energy Laboratory to address R&D barriers to the deployment of hydrogen fueling infrastructure. One key barrier to the deployment of fueling stations is the land area they require (i.e. "footprint"). Space is particularly a constraint in dense urban areas where hydrogen demand is high but space for fueling stations is limited. This work presents current fire code requirements that inform station footprint, then identifies and quantifies opportunities to reduce footprint without altering the safety profile of fueling stations. Opportunities analyzed include potential new methods of hydrogen delivery, as well as alternative placements of station technologies (i.e. rooftop/underground fuel storage). As interest in heavy-duty fueling stations and other markets for hydrogen grows, this study can inform techniques to reduce the footprint of heavy-duty stations as well. This work characterizes generic designs for stations with a capacity of 600 kg/day hydrogen dispensed and 4 dispenser hoses. Three base case designs (delivered gas, delivered liquid, and on-site electrolysis production) have been modified in 5 different ways to study the impacts of recently released fire code changes, colocation with gasoline refueling, alternate delivery assumptions, underground storage of hydrogen, and rooftop storage of hydrogen, resulting in a total of 32 different station designs. The footprints of the base case stations range from 13,000 to 21,000 ft² . A significant focus of this study is the NFPA 2 requirements, especially the prescribed setback distances for bulk gaseous or liquid hydrogen storage. While the prescribed distances are large in some cases, these setback distances are found to have a nuanced impact on station lot size; considerations of the delivery truck path, traffic flow, parking, and convenience store location are also important. Station designs that utilize underground and rooftop storage can reduce footprint but may not be practical or economical. For example, burying hydrogen storage tanks underground can reduce footprint, but the cost savings they enable depend on the cost of burial and the cost land. Siting and economic analysis of station lot sizes illustrate the benefit of smaller station footprints in the flexibility and cost savings they can provide. This study can be used as a reference that provides examples of the key design differences that fueling stations can incorporate, the approximate sizes of generic station lots, and considerations that might be unique to particular designs.

This February 2020 monthly report is intended to communicate the status of North Slope ARM facilities managed by Sandia National Labs.

Data is shown for z3308 z3309 photoionized Fe spectra and z3147 satire SS spectrum collected for Ryan Childers (Univ. of Nevada, Reno).

This manual describes the installation and use of the XyCe^TM XDM Net list Translator. XDM simplifies the translation of netlists generated by commercial circuit simulator tools into Xyce-compatible netlists. XDM currently supports translation from PSpice and HSPICE netlists into Xyce^TM netlists.

The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.1.0 offers intrusive and non-intrusive methods for propagating input uncertainties through computational models, tools for sensitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters from experimental data. This manual discusses the download and installation process for UQTk, provides pointers to the UQ methods used in the toolkit, and describes some of the examples provided with the toolkit.

Several sparse-sample uncertainty quantification (UQ) methods are compared for conservative but not overly conservative estimation of small tail probabilities involving responses that lay beyond specified thresholds in the tails of probability distributions. Sixteen very differently shaped distributions (or probability density functions, PDFs) and tail probability magnitudes ranging from 10^-5 to 10^-1 are considered in order for the study to be relevant to a wide range of risk analysis and quantification of margins and uncertainty (QMU) problems. The emphasis of the study is on limited data regimes ranging from N = 2 to 20 samples, reflective of most experimental and some expensive computational situations. Relatively simple sparse-sample UQ methods tested for this regime involve statistical tolerance interval "Equivalent Normal and related "Ensemble of Normals" and "Superdistribution (SD) approaches. (The independently derived SD is effectively equivalent to the Bayesian posterior predictive distribution given the assumptions of the derivation.) The performance of the methods was generally improved for N ≥ 5 samples with a generalized Jackknife resampling technique, which determines a tail probability estimate by averaging estimates from smaller sub-samples. Several quantitative metrics for method conservatism and accuracy of tail probability estimation are used to assess and rank the methods' performance over many random trials for each test PDF and probability magnitude. A variant of Bootstrap resampling was also tried, but did not significantly improve tail probability estimates in most cases. Detailed results are presented from over 100-million tests over the above factors that provide useful granular information on which methods or combination of methods perform best in various areas of the factor space.

The traditional design approach for product development is to develop a design based on customer requirements and technical knowledge, build the product according to the detail requirements provided, and then test the product to validate that it works as intended. The team typically starts by identifying a single design approach and spends their time validating a single design during testing. Design teams often encounter issues in the course of development with performance, manufacturability, interfaces and more. To compensate for test failures, teams often build in time into the schedule for additional design loopbacks. Further, when the loopbacks lead to change, the late changes are costly and risky, causing the team to focuses on "fixing the bare minimum" to meet cost and schedule expectations.

Sandia National Laboratories has tested and evaluated a new digitizer, the Centaur, manufactured by Nanometrics, Inc. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as power, sensitivity, self-noise, dynamic range, system noise, modified noise power ration, relative transfer function, analog bandwidth, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Centaur provides six channels of 24 bit digitization, three of which may be transmitted utilizing CD1.1 protocol.

Sandia National Laboratories has tested and evaluated a new digitizer, the Q330M+, manufactured by Quanterra, a division of Kinemetrics Inc. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as sensitivity, input impedance, power consumption, self noise, dynamic range, system noise, relative transfer function, analog bandwidth, modified noise power ratio, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Q330M+ provides six channels of 24 bit digitization, all of which may be transmitted utilizing CD1.1 protocol, at multiple sample rates.

Sandia National Laboratories has tested and evaluated a new digitizer, the Affinity, manufactured by Guralp Systems. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as sensitivity, power, self-noise, dynamic range, system noise, relative transfer function, modified noise power ratio, analog bandwidth, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Affinity provides eight, rather the typical six, channels of 24 bit high sample rate digitization, all of which may be transmitted utilizing the CD1.1 protocol, at multiple sample rates.

Transitional Markov Chain Monte Carlo (TMCMC) is a variant of a class of Markov Chain Monte Carlo algorithms known as tempering-based methods. In this report, the implementation of TMCMC in the Uncertainty Quantification Toolkit is investigated through the sampling of high-dimensional distributions, multi-modal distributions, and nonlinear manifolds. Furthermore, the Bayesian model evidence estimates obtained from TMCMC are tested on problems with known analytical solutions and shown to provide consistent results.

With the elimination of underground nuclear testing and declining defense budgets, science-based stockpile stewardship requires increased reliance on high performance modeling and simulation of weapon systems. Today's weapon systems are comprised of various electrical components and systems. As a result, there is a need for tools that will allow the use of massively parallel modeling and simulation techniques on high performance computers in existing and future weapons' electrical systems models. The Xyce Parallel Electronic Simulator is a SPICE (Simulation Program with Integrated Circuit Emphasis)- compatible circuit simulator designed to run on large-scale parallel computing platforms, though it can also execute efficiently on a variety of architectures including single processor workstations. As a mature platform for large-scale parallel circuit simulation, Xyce supports standard capabilities available in commercial simulators, in addition to various devices and models specific to Sandia's needs. Specifically, Xyce aids in the design and verification of electrical and electronic circuits and systems prior to weapons' manufacturing and deployment.

The Chemical Waste Landfill (CWL) at Sandia National Laboratories/New Mexico (SNL/NM) is a remediated hazardous waste landfill that underwent closure in accordance with Title 20, Chapter 4, Part 1 of the New Mexico Administrative Code (20.4.1.600 NMAC), incorporating Title 40, Code of Federal Regulations (CFR), Part 265, (40 CFR § 265) Subpart G, and the CWL Final Closure Plan (SNL/NM December 1992 and subsequent revisions). The CWL Post- Closure Care Permit (PCCP) (NMED October 2009), which became effective June 2, 2011 (Kieling June 2011) and as modified, defines all post-closure requirements. This ninth CWL Annual Post-Closure Care Report documents all activities and results as required by the PCCP Attachment 1, Section 1.12.

The Hawthorne Nevada, deep direct-use geothermal study is a two-year effort funded by the U.S. Department of Energy to determine the techno-economic feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the public facilities of the city of Hawthorne and Mineral County. The approach links a production side analysis (PSA) and a demand side analysis (DSA) into a whole-system analysis (WSA) to provide an integrated assessment of the resource and the probability of delivering economically viable direct-use energy to Hawthorne. Hawthorne, Nevada is in the western part of the Basin and Range province and has been the focus of geothermal investigations for over 40 years. Over the last 15 years, several studies completed by the U.S. Navy Geothermal Program Office (GPO) in conjunction with industry professionals quantified the existence of several low temperature geothermal prospects, the most promising of which is called Prospect A. The promise of Prospect A is based on drilling and flow testing that produced ~100 °C water at flow rates of up to 31 l/s (500 gallons per minute). Measured productivity indexes range from 40-85 l/s/MPa, suggesting a warm and productive heat source. Despite the promise of the resource, uncertainties in its spatial extent and long-term sustainability mean that techno-economic analyses must include probabilities of the sustainability of the resource under different operating scenarios. Here, the PSA is conducted by integrating a wide range of disparate data to estimate lognormal P90, P50, and P10 resource capacities. These capacities are used as input to a thermal-hydrologic (T-H) model to estimate thermal drawdown for each capacity estimate for several different DSA scenarios. Using a systems-based approach, the WSA links the dynamic T-H simulations of the PSA/DSA combinations with the techno-economic model GEOPHIRES to account for both the temporal dynamics and uncertainties in the system to produce probabilistic distributions of several performance metrics including the levelized cost of heat (LCOH) and the return on investment (ROI). This report is the final delivery for the project and documents the study's activities and results.

Supercritical CO₂ Brayton cycle systems (sCO₂) offer potential benefits over traditional steam plants. The changing economics of the electricity sector favors solar photovoltaic (PV), wind, and natural gas combined cycle (NGCC). Ultimately, the ability of sCO₂ systems to compete depends on the economics and ability to offer additional benefits to the market, such as the ability for dry cooling and their compact size. Updated results show that the projected LCOE for Brayton systems in the 100 to 300 MWe size range are between ${$}$44.8 and ${$}$56.1/MWh (4.48 and 5.61 cents/kWh). This report presents screening tools for assessing the potential market size and concludes that while at these LCOE estimates sCO₂ systems can compete directly against NGCC, there are many hurdles to commercialization, including the need to demonstrate long-term operations at low-cost and ability to quickly ramp for integration with intermittent resources. Additional customer discovery is necessary to fully understand the ability of this technology to solve customer problems that other technologies cannot.

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Sandia National Laboratories has tested and evaluated three digitizers, the Affinity, manufactured by Guralp Systems, the Centaur, manufactured by Nanometrics, and the Q330M+, manufactured by Quanterra, a division of Kinemetrics. These digitizers are used to record sensor output for seismic and infrasound monitoring applications. The purpose of this document is to highlight various results and observations collected during comprehensive evaluations conducted on each unit.

With our previous research, it was found that surface asperities or roughness must be present to create periodic surface structures upon laser exposure. In particular, an initial rough surface morphology (such as that found with a machined surface) provides multiple sites for light scattering, which underlies the formation of periodic ripple morphologies. Light scattering from a random surface creates patterns of periodic structures (with complex orientations) that could be used as intrinsic markings for tagging materials and equipment. Despite these initial findings, the fundamental mechanisms that give rise to periodic surface structures and their characteristic shapes were not identified in prior research.

Presented in this document is a small portion of the tests that exist in the Sierra / SolidMechanics (Sierra / SM) verication test suite. Most of these tests are run nightly with the Sierra / SM code suite, and the results of the test are checked versus the correct analytical result. For each of the tests presented in this document, the test setup, a description of the analytic solution, and comparison of the Sierra / SM code results to the analytic solution is provided. Mesh convergence is also checked on a nightly basis for several of these tests. This document can be used to conrm that a given code capability is veried or referenced as a compilation of example problems. Additional example problems are provided in the Sierra / SM Example Problems Manual. Note, many other verication tests exist in the Sierra / SM test suite, but have not yet been included in this manual.

This report reviews a hierarchy of formal mathematical models for describing plasma phenomena. Starting with the Boltzmann equation, a sequence of approximations and modeling assumptions can be made that progressively reduce to the equations for magnetohydrodynamics. Understanding the assumptions behind each of these models and their mathematical form is essential to appropriate use of each level of the hierarchy. A sequence of moment models of the Boltzmann equation are presented, then focused into a generalized three-fluid model for neutral species, electrons, and ions. This model is then further reduced to a two-fluid model, for which Braginskii described a useful closure. Further reduction of the two-fluid model yields a Generalized Ohm's Law model, which provides a connection to magnetohydrodynamic approaches. A verification approach based on linear plasma waves is presented alongside the model hierarchy, which is intended as an initial and necessary but not sufficient step for verification of plasma models within this hierarchy.

This report provides a summary of notes for building and running the Sandia Computational Engine for Particle Transport for Radiation Effects (SCEPTRE) code. SCEPTRE is a general purpose C++ code for solving the Boltzmann transport equation in serial or parallel using unstructured spatial finite elements, multigroup energy treatment, and a variety of angular treatments including discrete ordinates and spherical harmonics. Either the first-order form of the Boltzmann equation or one of the second-order forms may be solved. SCEPTRE requires a small number of open-source Third Party Libraries (TPL) to be available, and example scripts for building these TPL's are provided. The TPL's needed by SCEPTRE are Trilinos, boost, and netcdf. SCEPTRE uses an autoconf build system, and a sample configure script is provided. Running the SCEPTRE code requires that the user provide a spatial finite-elements mesh in Exodus format and a cross section library in a format that will be described. SCEPTRE uses an xml-based input, and several examples will be provided.

The eddy current approximation to Maxwell's equation often omits terms associated with magnetization, removing permanent magnets from the domain of validity of the approximation. We show that adding these terms back into the eddy current approximation is relatively straightforward, and demonstrate this on using a simple material constitutive model.

The Gulf Nuclear Energy Infrastructure Institute (GNEII) at Khalifa University of Science and Technology was created as a regional institute offering education, research and technical services to support nuclear energy safety, security and safeguards (3S) objectives. A mixed methods approach—using the (1) Course Evaluation, (2) GNEH Alumni Survey, (3) Capstone Project and, (4) GNEII-Related Literature data sets—was used to evaluate the effect of implementing this multidisciplinary `3S' educational program and the broader impact of the associated `3S' multidisciplinary institute on nuclear energy human resource development. Data sets (1), (2) and (3) illustrate how well GNEII implemented this novel 3S curriculum and resulted in successful knowledge transfer. Data sets (2), (3) and (4) illustrate how well GNEII's impact has positively influenced professional workplace behaviors and the institute's broader reputation to support responsible nuclear energy program education. Furthermore, GNEII demonstrates one option for successfully providing a multidisciplinary, 3S curriculum to support broader nuclear infrastructure and human resource development aims.

Inspired by the in-memory computing architectures of biological systems, neuromorphic computing using crossbar arrays of artificial synapses based on non-volatile memory (NVM) devices with variable conductances has emerged as a new paradigm to enable massively parallel and ultra-low power computing hardware for data centric applications. Although inference has been demonstrated successfully using crossbars based on a variety of NMV technologies, efficient learning and scaling to large arrays (>10⁶ elements) remains a challenge due to the synaptic elements' non-ideal electrical characteristics which degrades ANN accuracy. A further challenge is that in the conductive state memristors draw large currents >μA resulting in significant voltage drops in the interconnect wires and increased probability of failure in scaled arrays. We suggest the organic polymer redox transistor (RT) is an alternate approach that could solve many of these challenges, enabling both inference and parallel outer product updates, as recently demonstrated by Fuller et al. An RT consists of redox-active channel and gate electrodes in contact with a liquid or solid electrolyte. lon insertion through the electrolyte controls the channel electronic conductivity, while electron transfer through an external circuit maintains overall charge neutrality. Unlike a rechargeable battery, in the RT the voltage built-up across the electrolyte is kept to a minimum (typically <100 mV) by using the same material for the gate and channel. Elimination of the voltage offset simplifies integration of the RT into programmable arrays by enabling the use of various selectors. RTs based on inorganic and organic materials have been recently demonstrated with conductance tuning occurring at potentials of just a few mV and hundreds to thousands of linearly and symmetrically programmable conductance states, enabling near ideal accuracy in neural network simulations. Introduced in the 1980's, redox transistors with metallic gate electrodes and organic channel materials, also known as organic electrochemical transistors (OECTs), have been explored for a variety of applications such as chem- and bio-sensing, neural interfaces, and low cost printed circuits. A typical channel material for OECTs is the conducting polymer poly(3,4-ethylenedioxythiophene) doped with poly(styrene sulfonate) (PEDOT:PSS). PEDOT is a p-type semiconducting polymer with mobile positively charged polarons that hop chain-to-chain.

Coupled fluid-flow and geomechanical analysis of caprock integrity has gained a lot of attention among scientists and researchers investigating the long-term performance of geologic carbon storage systems. Reactivation of pre-existing fractures within the caprock or re-opening of faults can create permeable pathways which can influence the seal integrity. Stability of the caprock during and after injection of super-critical CO₂, and the impact of pre-existing fractures in the presence or absence of one or multiple faults have been investigated in this study. The impact of the wellbore orientation and the injection rate are among other key factors in understanding the structural trapping mechanisms within such geological formations. In this study, we numerically investigated the impact of each of these factors. This study revealed the interplay between joints and faults and how different leakage pathways are formed and under which scenario they play a dominant role in terms of CO₂ leakage. Finally, this study also highlights the role of one versus multiple faults in the domain and the importance of the fault hydrological property in forming leakage pathway.

With the adoption of Distributed Energy Resource (DER) interoperability standards, common communication protocols are now being deployed between power system operators and DER devices. In 2018, a revision to the US interconnection and interoperability standard, Institute of Electrical and Electronics Engineers (IEEE) Std. 1547, required DER equipment to have an IEEE 2030.5, IEEE 1815, or SunSpec Modbus communication exchange interface. This change supports the future transition to secure connection and exchange of information between the DER equipment and implementing parties, such as grid operators. Adoption of standardized communication protocols and associated information models is a critical step toward interoperability between power system operators and DER, such as photovoltaic (PV) and energy storage systems. However, security requirements for these standardized communication protocols are not comprehensive, resulting in non-standard and vendor-specific implementation that may leave DER equipment susceptible to cyberattacks. This paper examines the data-in-flight security requirements for standardized DER communication protocols, per IEEE 1547-2018 revision, as it relates to device authentication, key management, and encryption. The state of the art for these security features is also explored, addressing their impact on communication and performance of low-cost single board computers, which are typical of DER devices. In conclusion, a recommendation is provided to adopt a common set of communication requirements, which are intended to achieve interoperability and implement data security over DER network pathways, while ensuring reliable, secure, and real-time information delivery.

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