Publications

This project has progressed several physics models in the EMPIRE plasma simulation code to achieve higher fidelity simulations of high-current diode operation in pulsed-power accelerators. In this report, we present details for the following major work products: (1) a set of verification problems covering all key processes involved in gap closure physics has been designed; this suite has facilitated feature vetting and overall model maturation, (2) a new EMPIRE exemplar has been developed: the Radiographic Integrated Test Stand 6 (RITS-6) diode, and (3) An exemplar for the Saturn accelerator exemplar was enabled by the models matured under this work to self-consistently simulate further into the diode pulse than previously possible (bipolar flow regime). These developments have lead to the highest confidence EMPIRE power flow predictions of the Saturn accelerator to date. Additionally, three modeling approaches for simulating electrode plasmas have been investigated. We report on these results and provide recommendations.

An interferometric radioimager provides real-time, high-fidelity radioimaging of high voltage breakdown (HVB) both internal and external to electrical components at sub-nanosecond and sub-millimeter resolution and has an ability to resolve multiple/spatially-extensive HVB simultaneously. Therefore, radioimaging can be used to screen for early life weakness/failure and enable non-destructive screening of defective electrical components. In particular, radioimaging can detect precursors to catastrophic HVB, allowing for early detection of weakness in critical electrical components. Radioimaging can also be used to track HVB and pinpoint defects in electrical components real time, including transformers, capacitors, cables, switches, and microelectronics.

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

Conceptually, single-ion polymer electrolytes (SIPE) with the anion bound to the polymer could solve major issues in Li-ion batteries, but their conductivity is too low. Experimentally, weakly interacting anionic groups have the best conductivity. To provide a theoretical basis for this result, density functional theory calculations of the optimized geometries and energies are performed for charged ligands used in SIPE. Comparison is made to neutral ligands found in dual-ion conductors, which demonstrate higher conductivity. Further, the free energy differences between adding and subtracting a ligand are small enough for the neutral ligands to have the conductivity seen experimentally. However, charged ligands have large barriers, implying that lithium transport will coincide with the slow polymer diffusion, as observed in experiments. Overall, SIPE will require additional solvent to achieve a sufficiently high conductivity. Additionally, the binding of mono- and bidentate geometries varies, providing a simple and clear reason that polarizable force fields are required for detailed interactions.

Despite their many advantages, covalent organic frameworks (COFs) built from three-dimensional monomers are synthetically difficult to functionalize. Herein, we provide a new synthetic approach to the functionalization of a three-dimensional covalent organic framework (COF-300) by using a series of solid-state linkage transformations. By reducing the imine linkages of the framework to amine linkages, we produced a more hydrolytically stable material and liberated a nucleophilic amino group, poised for further functionalization. We then treated the amine-linked COF with diverse electrophiles to generate a library of functionalized materials, which we tested for their ability to adsorb perfluoroalkyl substances (PFAS) from water. The framework functionalized with dimethylammonium groups, COF-300-dimethyl, adsorbed more than 250 mg of perfluorooctanoic acid (PFOA) per 1 g of COF, which represents an approximately 14,500-fold improvement over that of COF-300 and underscores the importance of electrostatic interactions to PFAS adsorption performance. In conclusion, this work provides a conceptually new approach to the design and synthesis of functional three-dimensional COFs.

Sandia’s contribution to the FY23/Q4 GNG milestone was met: Demonstrate one composite hydride material with experimental data showing reversibility (50 cycles) and volumetric capacity ≥ 350 bar compressed gas.

Methyl-ethyl-substituted Criegee intermediate (MECI) is a four-carbon carbonyl oxide that is formed in the ozonolysis of some asymmetric alkenes. MECI is structurally similar to the isoprene-derived methyl vinyl ketone oxide (MVK-oxide) but lacks resonance stabilization, making it a promising candidate to help us unravel the effects of size, structure, and resonance stabilization that influence the reactivity of atmospherically important, highly functionalized Criegee intermediates. We present experimental and theoretical results from the first bimolecular study of MECI in its reaction with SO2, a reaction that shows significant sensitivity to the Criegee intermediate structure. Using multiplexed photoionization mass spectrometry, we obtain a rate coefficient of (1.3 ± 0.3) × 10-10 cm3 s-1 (95% confidence limits, 298 K, 10 Torr) and demonstrate the formation of SO3 under our experimental conditions. Through high-level theory, we explore the effect of Criegee intermediate structure on the minimum energy pathways for their reactions with SO2 and obtain modified Arrhenius fits to our predictions for the reaction of both syn and anti conformers of MECI with SO2 (ksyn = 4.42 × 1011 T-7.80exp(−1401/T) cm3 s-1 and kanti = 1.26 × 1011 T-7.55exp(−1397/T) cm3 s-1). Our experimental and theoretical rate coefficients (which are in reasonable agreement at 298 K) show that the reaction of MECI with SO2 is significantly faster than MVK-oxide + SO2, demonstrating the substantial effect of resonance stabilization on Criegee intermediate reactivity.

Recently developed techniques for assembling moiré heterostructures have enabled unprecedented control of the interlayer interactions within the heterostructure, allowing for the realization of strongly correlated electronic states. The experimentally realized states, to date, include a variety of topological states, superconductivity, and strange metal behavior. However, the phenomenology varies significantly from sample to sample. Here we will present microscopy techniques for further characterization of both the progenitor exfoliated materials and the composite moiré heterostructure. The application of these techniques has allowed for an unprecidented degree of characterization in ambient conditions. Additionally we will explore the use of resistively detected electron spin resonance (ESR) as a novel probe for spin order in moirés. While our results do not show clearly dispersive features that would unambiguously evince spin excitations within the sample, the technique is still promising.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. (2) A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models. (3) Device models that are specifically tailored to meet Sandia’s needs, including some radiation-aware devices (for Sandia users only). (4) Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase — a message passing parallel implementation — which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.

Single particle levitation methods are a powerful subset of aerosol instrumentation that allow a wide range of particle properties and processes to be explored. One of the most common forms of single particle levitation uses electric fields and is generally referred to as an electrodynamic balance (EDB). There are many different kinds of EDB's that have been designed with different applications in mind, and a corresponding array of analytical tools have been developed to characterize particles held in these traps. In this tutorial, we review the design and development of the EDB and discuss a range of analytical methods, including electrostatic analysis, light scattering, spectroscopy, and imaging, that allow for measurements of hygroscopic growth, volatility, surface tension and viscosity, diffusion, and phase and morphology. We go on to review recent advanced analytical methods using mass spectrometry to probe particle composition. This review is intended to provide readers with the basic knowledge to set up an EDB platform, design measurement protocols based on the available analytical tools, and run experiments to probe the fundamental properties of aerosol particles relevant to their role in the atmosphere, impacts on clouds and climate, effects on air quality, role in health and disease, and applications in industrial processes.

Abstract not provided.

Infrasound observations have grown increasingly important for the monitoring of earthquakes. While large earthquakes generate infrasound that can be detected thousands of kilometers away, there are few near-field observations of infrasound generated by low-magnitude events. We describe preliminary results of the West Texas Acoustic Experiment, during which infrasound sensors collected continuous data in the Permian Basin for a six-month period spanning January—June 2023. During this time, more than 1000 earthquakes with magnitudes between 1.2 and 4.2 occurred within 50 km of the network. We used spectral analysis, array processing, and manual inspection of waveforms to evaluate arrivals of infrasound signals following 84 events with magnitudes between 2.5 and 4.2. Here, we describe eight such events and the infrasound signals associated with each. We find detections of seismic-to-acoustic infrasound signals associated with seven events. We also find strong evidence of a laterally-propagating, purely acoustic wave generated by an M2.9 earthquake.

This paper is concerned with goal-oriented a posteriori error estimation for nonlinear functionals in the context of nonlinear variational problems solved with continuous Galerkin finite element discretizations. A two-level, or discrete, adjoint-based approach for error estimation is considered. The traditional method to derive an error estimate in this context requires linearizing both the nonlinear variational form and the nonlinear functional of interest which introduces linearization errors into the error estimate. In this paper, we investigate these linearization errors. In particular, we develop a novel discrete goal-oriented error estimate that accounts for traditionally neglected nonlinear terms at the expense of greater computational cost. We demonstrate how this error estimate can be used to drive mesh adaptivity. We show that accounting for linearization errors in the error estimate can improve its effectivity for several nonlinear model problems and quantities of interest. We also demonstrate that an adaptive strategy based on the newly proposed estimate can lead to more accurate approximations of the nonlinear functional with fewer degrees of freedom when compared to uniform refinement and traditional adjoint-based approaches.

Peat fires are a major contributor to greenhouse gas emissions. The estimates of these emissions currently contain major uncertainties, due to the difficulty of determining the mass of peat burned in a fire. To address these uncertainties, we develop a computational physics-based peat smoldering model, which will be leveraged for high-fidelity quantitative estimates of peat fire emissions relevant to climate change. We present the verification of the 2-D axisymmetric model, a first step towards developing a full 3-D model. Verification includes the solution verification against a literature model for the 0-D smoldering case and verification of the heat transfer problem in 1-D and 2-D. Also presented is the effect of reaction mechanism on the smoldering model, for which we found a relatively simple three-step reaction mechanism is able to capture key behavior. These verification results provide the foundation for moving forward with validation against experimental data of the 2-D model.

This report captures the results of development and testing of a integral downhole motor and percussive hammer used for drilling in near-surface hard rock formations. The work was funded through the DOE Office of Technology Transitions Technology Commercialization Fund. It was a collaboration between Sandia National Labs and The Charles Machine Works (aka Ditch Witch). In the collaboration, Sandia developed a pneumatic motor derived from an indexing tool used in other drilling applications, and Ditch Witch developed the bearing pack tied to the output shaft of the motor as well as the angled beacon housing used for directional control.

Neural networks are becoming the cornerstone for national security prediction tasks. However, designing them requires significant research and trial/error, as they have many hyperparameters, including their computation graph (“architecture”). Neural architecture search (NAS) employs secondary optimizers to search for architectures maximizing objectives like accuracy. Evolutionary algorithms (EAs) are the most used class of optimizer for NAS. However, existing Python libraries for writing EAs limit the complexity of experiments a user can design. In this project, we built ARENA, a Python framework that encodes complex, hyper-realistic EAs. ARENA collects detailed information as it runs and is flexible enough to encode non-EA search algorithms. We tested ARENA on 4 toy optimization problems by encoding 3 search algorithms for each—random search, an EA, and simulated annealing. We also designed an EA that performs NAS on the MNIST dataset. Our experiments suggest the potential for immediate mission impact through solving lab-wide optimization problems.

We present methods to estimate parameters for models for the incidence angle modifier for simulating irradiance on a photovoltaic array. The incidence angle modifier quantifies the fraction of direct irradiance that is reflected away at the array’s face, as a function of the direct irradiance’s angle of incidence. Parameters can be estimated from data and the fitting method can be used to convert between models. We show that the model conversion procedure results in models that produce similar annual insolation on a fixed plane.

Mechanical metamaterials are artificial materials with unique global properties due to the structural geometry and material composition of their unit cell. Typically, mechanical metamaterial unit cells are designed such that, when tessellated, they exhibit unique mechanical properties such as zero or negative Poisson's ratio and negative stiffness. Beyond these applications, mechanical metamaterials can be used to achieve tailorable nonlinear deformation responses. Computational methods such as gradient-based topology optimization (TO) and size/shape optimization (SSO) can be implemented to design these metamaterials. However, both methods can lead to suboptimal solutions or a lack of generalizability. Therefore, this research used deep reinforcement learning (DRL), a subset of deep machine learning that teaches an agent to complete tasks through interactive experiences, to design mechanical metamaterials with specific nonlinear deformation responses in compression or tension. The agent learned to design the unit cells by sequentially adding material to a discrete design domain and being rewarded for achieving the desired deformation response. After training, the agent successfully designed unit cells to exhibit desired deformation responses not experienced during training. This work shows the potential of DRL as a high-level design tool for a wide array of engineering applications.

The Daedalus ultrafast x-ray imager is the latest generation in Sandia’s hybrid CMOS detector family. With three frames along an identical line of sight, 1 ns minimum integration time, a higher full well than Icarus, and added features, Daedalus brings exciting new capabilities to diagnostic applications in inertial confinement fusion and high energy density science. In this work, we present measurements of time response, dynamic range, spatial uniformity, pixel cross-talk, and absolute x-ray sensitivity using pulsed optical and x-ray sources. We report a measured 1.5 Me− full well, pixel sensitivity at 9.58 × 10−7 V/e−, and an estimate of spatial uniformity at ∼5% across the sensor array.

The U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system administered by the U.S. Department of Energy. SPR injected a total of over 230 MMB of raw water into 48 caverns as part of oil sales in CY22. Leaching effects were monitored in these caverns to understand how the sales operations may impact the long-term integrity of the caverns. The leaching effects were modeled here using the Sandia Solution Mining Code, SANSMIC. The modeling results indicate that leaching-induced features do not raise concern for the majority of the caverns. In addition to 12 caverns identified in previous leaching reports, seven caverns have been identified for further monitoring based on the results of this report. Twenty-two caverns had pre- and post-leach sonars that were compared with SANSMIC results. Overall, SANSMIC was able to capture the leaching well.

Ion diffusion in atmospheric pressure plasmas is examined and particular attention is paid to the fact that ion-ion interactions can be influenced by strong Coulomb coupling. Three regimes are identified. At low ionization fractions ( x i ≲ 10 − 6 ), standard weakly correlated ion-neutral interactions set the diffusion rate. At moderate ionization fractions ( 10 − 6 ≲ x i ≲ 10 − 2 ) there is a transition from ion-neutral to ion-ion collisions setting the diffusion rate. In this regime, the effect of strong Coulomb coupling in ion-ion collisions is accounted for by applying the mean force kinetic theory. Since both ion-neutral and ion-ion interactions contribute a comparable amount to the total diffusion rate, models (such as particle-in-cell or fluid) must account for both contributions. At high ionization fractions ( x i ≳ 10 − 2 ), strongly correlated ion-ion collisions dominate and the plasma is heated substantially by a disorder-induced heating (DIH) process associated with strong correlations. The temperature increase due to DIH strongly influences the ion diffusion rate. This effect becomes even more important, and occurs at lower ionization fractions, as the pressure increases above atmospheric pressure. In addition to ion diffusion, DIH affects the neutral gas temperature, therefore influencing the neutral diffusion rate. Model predictions are tested using molecular dynamics simulations, which included a Monte Carlo collision routine to simulate the effect of ion-neutral collisions at the lowest ionization fractions. The model and simulations show good agreement over a broad range of ionization fractions. The results provide a model for ion diffusion, on a wide range of ionization fractions and pressures, solely considering the elastic contribution to the diffusion coefficient—as an illustration of how strong Coulomb coupling influences diffusion processes in general.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Uncertainty in severe accident evolution and outcome is driven by event bifurcations that represent distinctive challenges to defensive layers and tend to promote the emergence of discrete classes of core damage and accident risk. This discrete set of "attractor" states arise from the complex networks of competing physical phenomena and conditional event cascades occurring as the overall system degrades – a process that yields increasing degrees of freedom and accident progression pathways. Characterization of these event spaces has proven elusive to more traditional data interrogation methods, but proves tractable by application of more advanced data collection and machine learning approaches. Through application of these approaches we demonstrate a conceptual framework that enables real-time/robust, risk-informed decision-making support to improve accident mitigation and encourage “graceful exits” during low probability, extreme events limiting accident consequences. In this analysis, we simulated over 8,000 short-term station blackout (STSBO) accidents with the state-of-the-art integral severe accident code, MELCOR, and demonstrate the potential for ML approaches to predict simulation outcomes. We chose to pair ML tools with interpretable and mechanistic event trees for the considered STSBO accident space to predict the likelihood of future event paths along the tree. In addition to the current state of the system, we use information from recent trajectories of temperature, pressure, and other physical features, combining both the current state and past trajectories to forecast future event paths. Finally, we simulate the random injection of variable amounts of water to quantify the efficacy of available actions at reducing risks along the many branches in the event tree. We identify scenarios and windows of opportunity to mitigate risk as well as scenarios in which such actions are unlikely to alter the accident end-state.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Aquaculture systems require careful consideration of location, which determines water conditions, pollution impacts, and hazardous conditions. Mobility may be able to address these factors while also supporting the targeting of renewable energy sources such as wind, wave, and solar power throughout the year. In this paper, a purpose-built mobile aquaculture ship is identified and modeled with a combination of renewable energy harvesting capabilities as a case study with the objective of assessing the potential benefits of targeting high renewable energy potentials to power aquaculture operations. A route optimization algorithm is created and tuned to simulate the mobility of the aquaculture platform and cost-basis comparisons are made to a stationary system. The small spatial variability in renewable energy potential when combining multiple resources significantly limits the benefits of a mobile, renewable-targeting aquaculture system. On the other hand, the consistent energy harvest from a blend of renewable energy types (13 kW installed wind capacity, 661 m2 installed solar, and 1 m characteristic width wave-energy converter) suggests that the potential benefits of a mobile platform for offshore aquaculture (mitigation of environmental and social concerns, any potential positive impact on yields, hazard avoidance, etc.) can likely be pursued without significant increases in energy harvester costs.

Abstract not provided.

Moving target defenses (MTDs) are widely used as an active defense strategy for thwarting cyberattacks on cyber-physical systems by increasing diversity of software and network paths. Recently, machine Learning (ML) and deep Learning (DL) models have been demonstrated to defeat some of the cyber defenses by learning attack detection patterns and defense strategies. It raises concerns about the susceptibility of MTD to ML and DL methods. In this article, we analyze the effectiveness of ML and DL models when it comes to deciphering MTD methods and ultimately evade MTD-based protections in real-time systems. Specifically, we consider a MTD algorithm that periodically randomizes address assignments within the MIL-STD-1553 protocol - a military standard serial data bus. Two ML and DL-based tasks are performed on MIL-STD-1553 protocol to measure the effectiveness of the learning models in deciphering the MTD algorithm: 1) determining whether there is an address assignments change i.e., whether the given system employs a MTD protocol and if it does 2) predicting the future address assignments. The supervised learning models (random forest and k-nearest neighbors) effectively detected the address assignment changes and classified whether the given system is equipped with a specified MTD protocol. On the other hand, the unsupervised learning model (K-means) was significantly less effective. The DL model (long short-term memory) was able to predict the future addresses with varied effectiveness based on MTD algorithm's settings.

Mechanical metamaterials are regularly implemented in engineering applications due to their unique properties derived from their structural geometry and material composition. This study incorporates deep reinforcement learning, a subset of machine learning that teaches an agent to complete a task through interactive experiences, into mechanical metamaterial design. The approach creates a design environment for the reinforcement learning agent to iteratively construct metamaterials with tailorable deformation and hysteretic characteristics. Validation involved producing metamaterials with a thermoplastic polyurethane (TPU) base material that exhibited the deformation response of expanded thermoplastic polyurethane (E-TPU) while maximizing or minimizing hysteresis in cyclic compression. This alignment confirmed the feasibility of tailoring deformation and energy manipulation using mechanical metamaterials. The agent's generalizability was tested by tasking it to create various metamaterials with distinct loading deformation responses and specific hysteresis goals in a simulated setting. The agent consistently delivered metamaterials that met loading curve criteria and demonstrated favorable energy return. This work demonstrates the potential of deep reinforcement learning as a rapid and effective tool for designing mechanical metamaterials with customizable traits. It ushers in the possibility of on-demand metamaterial design solutions, opening avenues across industries like footwear, wearables, and medical equipment.

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and −3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.

Abstract not provided.

Marine aerosol injections are a key component in further understanding of both the potentials of deliberate injection for marine cloud brightening (MCB), a potential climate intervention (CI) strategy, and key aerosol-cloud interaction behaviors that currently form the largest uncertainty in global climate model (GCM) predictions of our climate. Since the rate of spread of aerosols in a marine environment directly translates to the effectiveness and ability of aerosol injections in impacting cloud radiative forcing, it is crucial to understand the spatial and temporal extent of injected-aerosol effects following direct injection into marine environments. The ubiquity of ship-injected aerosol tracks from satellite imagery renders observational validation of new parameterizations possible in 2D, however, 3D compatible data is more scarce, and necessary for the development of subgrid scale parameterizations of aerosol-cloud interactions in GCMs. This report introduces two novel parameterizations of atmospheric aerosol injection behavior suitable for both 3D (GCM-compatible) and 2D (observation-related) modeling. Their applicability is highlighted using a wealth of different observational data: small and larger scale salt-aerosol injection experiments conducted at SNL, 3D large eddy simulations of ship-injected aerosol tracks and 2D satellite images of ship tracks. The power of experimental data in enhancing knowledge of aerosol-cloud interactions is in particular emphasized by studying key aerosol microphysical and optical properties as observed through their mixing in cloud-like environments.

The Ghareb Formation is a shallowly buried porous chalk in southern Israel that is being considered as a host rock for a geologic nuclear waste repository. Setup and operation of a repository will induce significant mechanical, hydrological and chemical perturbations in the Ghareb. Developing a secure repository requires careful characterization of the rock behavior to different loads. To characterize hydromechanical behavior of the Ghareb, several short- and long-term deformation experiments were conducted. Hydrostatic loading tests were conducted both dry and water-saturated, using different setups to measure elastic properties, time-dependent behavior, and permeability. A set of triaxial tests were conducted to measure the elastic properties and rock strength under differential loading at dry and water-saturated conditions. The hydrostatic tests showed the Ghareb began to deform inelastically around 12–15 MPa, a relatively low effective pressure. Long-term permeability measurements demonstrated that permeability declined with increasing effective pressure and was permanently reduced by ~ 1 order of magnitude after unloading pressure. Triaxial tests showed that water saturation significantly degrades the rock properties of the Ghareb, indicating water-weakening is a significant risk during repository operation. Time-dependent deformation is observed during hold periods of both the hydrostatic and triaxial tests, with deformation being primarily visco-plastic. The rate of deformation and permeability loss is strongly controlled by the effective pressure as well. Additionally, during holds of both hydrostatic and triaxial tests, it is observed that when water-saturated, radial strain surpassed axial strain when above effective pressures of 13–20 MPa. Thus, deformation anisotropy may occur in situ during operations even if the stress conditions are hydrostatic when above this pressure range.

Abstract not provided.

Five alternative design configurations for a heavy-duty hydrogen refueling truck stop are detailed in this work. Each of the station concepts provides fast, 5-minute, 50 kg fills of up to 4 vehicles simultaneously, with a station capacity of 4200 kg/day. Two on-site production stations using PEM electrolysis are considered: one with off-peak production of the daily capacity; and one with on-demand production of hydrogen during vehicle refueling. Three delivered liquid hydrogen station concepts are considered: one with the same, high-pressure cascade storage system for dispensing as the electrolysis supplied stations, with low-pressure vaporization of the liquid hydrogen and pressurization via a compressor; and two with on-demand pressurization: one by low-pressure vaporization and compressors; and one with a cryogenic pump and high-pressure vaporization. Design, economic, and operational considerations for each of the components needed in these station concepts is provided. Of all the station concepts, the delivered liquid station with a low-pressure vaporizer and a cascade dispensing system has the lowest capital costs and equipment footprint, but the second highest operating costs primarily due to high costs for liquid hydrogen delivery. The lowest operating cost station is that with on-site production via PEM electrolysis at off-peak hours with a cascade delivery system. The low-pressure buffer storage system and electrolyzers have a large footprint and considerable capital costs, but could result in a low total cost of ownership, depending on the design timeline. The liquid hydrogen station with a cryo-pump has moderate capital costs, the lowest operating costs of the three delivered hydrogen stations, and the same small equipment footprint as the delivered liquid, cascade dispensing system. As cryogenic pumping technology improves and the capital costs for these pumps decreases, this station concept will become even more favorable. Three-dimensional renderings of the five station concepts provide station designers with a starting point for the development of heavy-duty refueling stations.

American Vacuum Society National Conference presentation on ferroelectric hafnium oxide

Directed energy deposition (DED) is an attractive additive manufacturing (AM) process for large structural components. The rapid solidification and layer-by-layer process associated with DED results in non-ideal microstructures, such as large grains with strong crystallographic textures. These non-ideal microstructures can lead to severe anisotropy in the mechanical properties. Despite these challenges, DED has been identified as a potential solution for the manufacturing of near net shape Ti-6Al-4V preforms, replacing lost casting and forging capabilities. Two popular wire-based directed energy deposition (W-DED) processes were considered for the manufacturing of Ti-6Al-4V with assessments on their respective metallurgical and mechanical properties, as compared to a conventionally processed material. The two W-DED processes explored were wire arc additive manufacturing (WAAM) and electron beam additive manufacturing (EBAM). High throughput inspection and tensile testing procedures were utilized to generate statistically relevant data sets related to each process and sample orientation. The 2 AM technologies produced material with remarkably different microstructures and mechanical properties. Results revealed key differences in strength and ductility for the two disparate processes which were found to be related to differences in the metallurgical properties.

Sandia National Laboratories (SNL) was contracted by the United States Department of Energy Environmental Management (DOE-EM), Los Alamos Field Office to perform mechanical and thermal scoping calculations as part of a study seeking to understand the ignitability risk of the Remediated Nitrate Salts (RNS) waste drums during transportation from the Waste Control Specialists (WCS) facility to Waste Isolation Pilot Plant (WIPP) and permanent disposal of the waste at WIPP. The scoping thermal simulations described in this report pertain to thermal calculations performed with a packaging system consisting of one Standard Waste Box (SWB) loaded with drums placed inside a Standard Large Box 2 (SLB2). During transportation, the SLB2 is inside Transuranic Package Transporter Model III (TRUPACT-III), which provides the third layer of the packaging. Once at the WIPP, it is assumed the SLB2 is extracted from the TRUPACT-III and maintained above ground, and then subsequently placed underground for permanent disposal. In these proposed configurations, the space between the SLB2 and the SWB is always filled by a layer of insulation consisting of air-filled glass microbubbles except for the bottom which rests directly on the SLB2. The thermal scoping calculations described in this report specifically address whether the introduction of external heat inputs, combined with the contributions from the internally generated radiolytic decay heat and chemical reactions, lead to an unstable thermal state during the time of its movement and placement in the permanent disposal location. The external heat inputs are of two forms: 1) ambient thermal irradiation (e.g., solar and ambient storage/disposal temperatures) and 2) accident-induced fire. Three scoping calculation scenarios were derived as representative, conservative scenarios: 1A) TRUPACT-III transient transportation, 1B) SLB2 48-hour outdoor storage with solar radiation, and 2) fully-engulfing fire during SLB2 handling or emplacement following a steady-state analysis in a 38 °C environment. All the simulated scenarios are conservative relative to the operational conditions expected for handling the waste package during transportation and placement in the WIPP underground disposal unit. The predictions obtained from simulating the three exposure scenarios revealed that adding the SLB2 and the air-filled glass microbubbles to the transport and storage/disposal configurations provides additional thermal protection of the drums beyond what the SWB provides alone, both during long-term above ground insolation and underground during a fire accident. Under the current transportation/storage/disposal concepts, the degree of protection provided by the packaging concept is sufficient to prevent the waste from being ignitable. The simulation results demonstrate that there is adequate margin to safely transport and place the RNS waste from WCS to the WIPP under the current operational concept.

Fast and reliable estimation of engineered fracture geometries is a key factor in controlling undesirable fractures and enhancing stimulation design. Measuring the surface deformation gradient (tilt) for engineered fractures in shallow depths (<1000 m) has been proven a reliable source of data to infer fracture geometry, thanks to the impressive resolution of tiltmeter units (in the order of nano-radians). However, solving the inverse problem requires reliable and fast forward models. In this study, we present a fast and reliable machine-learned surrogate model to estimate the ground surface tilt induced by pressurised fractures. The proposed surrogate model, based on Conditional Generative Adversarial Networks (cGAN), receives a fracture aperture map in XY and XZ planes as input and predicts the corresponding surface tilts (in X and Y directions). The surrogate model with Wasserstein loss and gradient penalty has been trained using 11,000 samples and tested for a range of input parameters such as depth, dip angles, elastic properties, fluid pressures and fracture shapes. The testing results show excellent performance of the surrogate model compared with the forward finite element model for both single and multiple pressurised fractures, while running hundreds to potentially thousands of times faster.

The research described here was performed as part of the DOE SciDAC project Coupling Approaches for Next Generation Architectures (CANGA). A framework was developed for the derivation of novel algorithms for the multirate time integration of two-component systems coupled across an interface between spatial domains. The multirate aspect means that different time steps are allowed by each component integrator. The framework provides a way to construct multirate integrators with desirable properties related to stability, accuracy and preservation of system invariants. This report describes the framework and summarizes the major results, examples and research products.

Abstract not provided.

Abstract not provided.

Ultimately, our experiment measures two quantities on an aluminum bar: motion (which modeling must predict) and temperature (which sets thermal boundary conditions). For motion, stereo DIC is a technique to use imaging data to provide displacements relative to a reference image down to 1/100th of a pixel. We use a calibrated infrared imaging method for accurate temperature measurements. We will be capturing simultaneous data and then registering temperature data in space to the same coordinate system as the displacement data. While we will later show that our experiments are repeatable, indicating that separate experiments for motion and temperature would provide similar data, the simultaneous and registered data removes test to test variability as a source of uncertainty for model calibration and reduces the number of time-consuming tests that must be performed.

Abstract not provided.

As a follow-up to our previous report on quantum sensing for safeguards, here we delve deeper into quantum-enhanced imaging & spectroscopy and address their relevance to international safeguards. Much of the approaches rely on entangled photons, a quantum phenomenon not possible with classical physics, although just correlated photons will work for some applications, such as ghost imaging. We provide a comprehensive survey of quantum approaches, including multiple entangled photon ghost imaging and spectroscopy techniques. Entangled photons for noise reduction are also described, as well as Non-Line-Of-Sight imaging, compressive techniques, and squeezed light. Of particular interest is the generation of entangled photons with large wavelength separation, such as infrared/visible entangled photon pairs. Such entangled pairs would allow interaction with objects in the IR, such as in the molecular “fingerprint” wavelength region, while the recording device captures the visible photons, thus leveraging the high efficiency and lower cost of visible detectors. Unfortunately, entangled x-ray photons are not practical, which would have been useful for safeguards to interrogate shielded materials. Entangled gamma rays are even further beyond reason. We provide our assessment for application of quantum-enhanced imaging & spectroscopy for international safeguards, including suggested improvements to existing IAEA instruments and destructive assay measurements that are done at IAEA lab facilities.

Abstract not provided.

A near net shape coating is desired to be applied to the outer surface of a capped cylinder (“cake pan”) type substrate using thermal spray technology. A capped cylinder geometry is more complex than simple coupon-level substrate substrates (e.g., flat panels, cylinders) and thus requires a more complex toolpath to deposit a uniform coating. This report documents a practical theoretical approach to calculating relative torch-to-substrate speeds for coating the cylindrical, corner, and cap region of a rotating capped cylinder based on fundamental thermal spray toolpath principles. A preliminary experimental test deposited a thermal spray coating onto a mock substrate using toolpath speeds calculated by the theoretical approach proposed. The mock substrate was metallographically inspected to assess coating uniformity across the cylindrical, corner, and cap region. Inspection of the mock substrate revealed qualitatively uniform coating microstructure and thickness where theoretically predicted, demonstrating the viability of the proposed toolpath method and associated calculations. Pathways forward to optimizing coating uniformity at the cap center are proposed as near term suggested future work.

Large, pulsed power and high voltage systems often employ a stack of insulators to separate a vacuum section away from water or oil sections. The size of this insulator stack often drives overall costs and feasibility of these systems. An electric breakdown along the insulator surface is a primary failure mechanism and is especially impactful if it occurs while power is still being delivered downstream. This report describes a set of experimental and modeling investigations into the cause of these breakdowns, especially focusing on the much less well-understood anode-initiated breakdowns that occur during early parts of power delivery. Additionally, new diagnostics for assessing relevant material properties and behavior of insulators are described. These results describe breakdown behavior and evolution at new temporal and spatial fidelities and provide hypotheses and some answers as to how these breakdowns can occur. This new understanding of the roles of different physics phenomena guide modifications and trade-offs in generating newer insulator stack designs that are smaller and/or have higher electrical stress thresholds.

Full-field, multi-measurand diagnostics provide rich validation data necessary to improve the product life cycle time of nuclear safety components. Thermophosphor digital image correlation (TP+DIC) is a method of simultaneously measuring strain and temperature fields using patterned phosphor coatings deposited with aerosol deposition (AD). While TP+DIC produces a functional diagnostic, the coating’s reproducibility and the effect of the patterned features on the inferred temperature remains uncharacterized. This NSR&D project provided the opportunity to study two areas: 1) the tunability and repeatability of aerosol deposition and 2) the robustness of aerosol deposition phosphor on deforming substrates. The first area explores the process-property relationship of parameters elucidating the significance of each on the coating. The second area explores the relationship between the features’ characteristics (namely thickness) and the phosphor emission and inferred temperature. Together, the results will lead to the improved accuracy and functionality of TP+DIC for qualification testing of nuclear safety components.

Physical Chemistry Chemical Physics

Abstract not provided.

This special memorial issue pays tribute to James (Jim) A. Miller, a giant of combustion science who died in 2021, with a celebration of his enormous influence on the field. We were touched by the responses we received after we sent out the invitations for it. Jim inspired several generations of scientists, who viewed him as a mentor, a father figure, and a friend. Together with Nils Hansen and Peter Glarborg, we have written a detailed account on his life and work. Furthermore, it appeared in this journal shortly after his death; and so here we focus on the scientific areas he had interest in and influence on, and how they relate to the 34 papers in this issue. The topics of these papers span a variety of Jim's interests including nitrogen chemistry, polycyclic aromatic hydrocarbon (PAH) chemistry, oxidation chemistry, energy transfer, prompt dissociations, and codes to facilitate combustion chemistry simulations.

The objective of this project was to evaluate material- and chemical-based solutions for hydrogen storage in rail applications as an alternative to high-pressure hydrogen gas and liquid hydrogen. Three use cases were assessed: yard switchers, long-haul locomotives, and tenders. Four storage options were considered: metal hydrides, nanoporous sorbents, liquid organic hydrogen carriers, and ammonia, using 700 bar compressed hydrogen as a benchmark. The results suggest that metal hydrides, currently the most mature of these options, have the highest potential. Storage in tenders is the most likely use case to be successful, with long-haul locomotives the least likely due to the required storage capacities and weight and volume constraints. Overall, the results are relevant for high-impact regions, such as the South Coast Air Quality Management District, for which an economical vehicular hydrogen storage system with minimal impact on cargo capacity could accelerate adoption of fuel cell electric locomotives. The results obtained here will contribute to the development of technical storage targets for rail applications that can guide future research. Moreover, the knowledge generated by this project will assist in development of material-based storage for stationary applications such as microgrids and backup power for data centers.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The Clifford spectrum is a form of joint spectrum for noncommuting matrices. This theory has been applied in photonics, condensed matter and string theory. In applications, the Clifford spectrum can be efficiently approximated using numerical methods, but this only is possible in low dimensional example. In this paper we examine the higher-dimensional spheres that can arise from theoretical examples. We also describe a constructive method to generate five real symmetric almost commuting matrices that have a K-theoretical obstruction to being close to commuting matrices. For this, we look to matrix models of topological electric circuits.

Commercial generation of energy by nuclear power plants in the United States (U.S.) has produced thousands of metric tons of spent nuclear fuel (SNF), the disposal of which is the responsibility of the U.S. Department of Energy (DOE). Utilities typically utilize the practice of storing this SNF in dual-purpose canisters (DPCs). DPCs were designed, licensed, and loaded to meet Nuclear Regulatory Commission (NRC) requirements that preclude the possibility of a criticality event during SNF storage and transport, but were not designed or loaded to preclude the possibility of a criticality event during the regulated post-closure period following disposal, which could be up to 1,000,000 years (Price, 2019). There are several options being investigated that could facilitate the disposal of SNF stored in DPCs in a geologic repository (Hardin et al., 2015; SNL 2020b; SNL 2021b). These include: (1) repackage the SNF into canisters that are designed to prevent criticality during the regulated post-closure period following disposal, but with an increased disposal cost estimated at approximately $\$$20B in United States dollars (USD) (Freeze et al., 2019); (2) analysis of the probability and consequences of criticality from the direct disposal of DPCs during a 1,000,000-year post-closure period in several geologic disposal media (Price, 2019); and (3) filling the void space of a DPC with a material before its disposal that significantly limits the potential for criticality over the post-closure regulatory period. This report further investigates the third option, filling DPC already containing SNF with a material to limit the potential for criticality over the post-closure regulatory period.

Here, a line list for the N second positive system, $B^3Π_g—C^3Π_u$, has been compiled using the PGOPHER spectral simulation software. The line list extends the number of vibrational states of the $B^3Π_g$ up to v=29 and a maximum rotational state of J=150 for simulation temperatures up to 7000 K. New electronic–vibrational transition moments were calculated using refined potential energy curves and a transition dipole moment with the DUO software. Comparisons to experimental data and the SPECAIR software have been used to validate the new line list. The results are available in ASCII ExoMol .state and .trans files and as a PGOPHER input file for use in spectral analysis.

Opacity-on-NIF has obtained opacity data under conditions similar to those achieved by the entirely different Opacity-on-Z platform. From low- and high-Z elements at different anchor points, rigorously compare the opacity data between the laboratories and to multiple opacity theory models. Compare and assess the data acquisition and processing methods for obtaining opacities and for measuring/inferring sample conditions. Explain, or develop hypotheses for, any discrepancies. Map progress to the National Opacity Strategy and define future directions.

We report a spontaneous and hierarchical self-assembly mechanism of carbon dots prepared from citric acid and urea into nanowire structures with large aspect ratios (>50). Scattering-type scanning near-field optical microscopy (s-SNOM) with broadly tunable mid-IR excitation was used to interrogate details of the self-assembly process by generating nanoscopic chemical maps of local wire morphology and composition. s-SNOM images capture the evolution of wire formation and the complex interplay between different chemical constituents directing assembly over the nano- to microscopic length scales. We propose that residual citrate promotes tautomerization of melamine surface functionalities to produce supramolecular shape synthons comprised of melamine-cyanurate adducts capable of forming long-range and highly directional hydrogen-bonding networks. This intrinsic, heterogeneity-driven self-assembly mechanism reflects synergistic combinations of high chemical specificity and long-range cooperativity that may be harnessed to reproducibly fabricate functional structures on arbitrary surfaces.

Nonlocal models allow for the description of phenomena which cannot be captured by classical partial differential equations. The availability of efficient solvers is one of the main concerns for the use of nonlocal models in real world engineering applications. Here, we present a domain decomposition solver that is inspired by substructuring methods for classical local equations. In numerical experiments involving finite element discretizations of scalar and vectorial nonlocal equations of integrable and fractional type, we observe improvements in solution time of up to 14.6x compared to commonly used solver strategies.

The basic building block of a distributed-memory cluster or supercomputer is a node. Each node includes a host, which is a processor (xPU) + memory hierarchy. The host can communicate with other hosts via its NIC (network interface controller). A network connects the nodes. The nodes may be arranged in some topology, which determines the network’s carrying capacity and cost.

The heat generated by high-level radioactive waste can pose numerical and physical challenges to subsurface flow and transport simulators if the liquid water content in a region near the waste package approaches residual saturation due to evaporation. Here, residual saturation is the fraction of the pore space occupied by liquid water when the hydraulic connectivity through a porous medium is lost, preventing the flow of liquid water. While conventional capillary pressure models represent residual saturation using asymptotically large values of capillary pressure, here, residual saturation is effectively modeled as a tortuosity effect alone. Treating the residual fluid as primarily dead-end pores and adsorbed films, relative permeability is independent of capillary pressure below residual saturation. To test this approach, PFLOTRAN is then used to simulate thermal-hydrological conditions resulting from direct disposal of a dual-purpose canister in unsaturated alluvium using both conventional asymptotic and revised, smooth models. Importantly, while the two models have comparable results over 100 000 years, the number of flow steps required is reduced by approximately 94%.

The finite element method (FEM) is widely used to simulate a variety of physics phenomena. Approaches that integrate FEM with neural networks (NNs) are typically leveraged as an alternative to conducting expensive FEM simulations in order to reduce the computational cost without significantly sacrificing accuracy. However, these methods can produce biased predictions that deviate from those obtained with FEM, since these hybrid FEM-NN approaches rely on approximations trained using physically relevant quantities. In this work, an uncertainty estimation framework is introduced that leverages ensembles of Bayesian neural networks to produce diverse sets of predictions using a hybrid FEM-NN approach that approximates internal forces on a deforming solid body. The uncertainty estimator developed herein reliably infers upper bounds of bias/variance in the predictions for a wide range of interpolation and extrapolation cases using a three-element FEM-NN model of a bar undergoing plastic deformation. This proposed framework offers a powerful tool for assessing the reliability of physics-based surrogate models by establishing uncertainty estimates for predictions spanning a wide range of possible load cases.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the. U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at the Sandia National Laboratories Kaua'i Test Facility in Hawai'i. Activities at the site are conducted in support of U.S. Department of Energy weapons programs., and the site has operated as a rocket preparation launching and tracking facility since 1962. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report summarizes the environmental protection, restoration, and monitoring programs in place at Sandia National Laboratories, Kaua'i Test Facility, during calendar year 2022. Environmental topics include cultural resource management, chemical management, air quality, meteorology, ecology, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, wastewater discharge, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting and has been approved for public distribution.

Auto-magnetizing (AutoMag) liners are cylindrical tubes that employ helical current flow to produce strong internal axial magnetic fields prior to radial implosion on ~100 ns timescales. AutoMag liners have demonstrated strong uncompressed axial magnetic field production (>100 T) and remarkable implosion uniformity during experiments on the 20 MA Z accelerator. However, both axial field production and implosion morphology require further optimization to support the use of AutoMag targets in magnetized liner inertial fusion (MagLIF) experiments. Data from experiments studying the initiation and evolution of dielectric flashover in AutoMag targets on the Mykonos accelerator have enabled the advancement of magnetohydrodynamic (MHD) modeling protocols used to simulate AutoMag liner implosions. Implementing these protocols using ALEGRA has improved the comparison of simulations to radiographic data. Specifically, both the liner in-flight aspect ratio and the observed width of the encapsulant-filled helical gaps during implosion in ALEGRA simulations agree more closely with radiography data compared to previous GORGON simulations. Although simulations fail to precisely reproduce the measured internal axial magnetic field production, improved agreement with radiography data inspired the evaluation of potential design improvements with newly developed modeling protocols. Three-dimensional MHD simulation studies focused on improving AutoMag target designs, specifically seeking to optimize the axial magnetic field production and enhance the cylindrical implosion uniformity for MagLIF. Importantly, by eliminating the driver current prepulse and reducing the initial inter-helix gap widths in AutoMag liners, simulations indicate that the optimal 30–50 T range of precompressed axial magnetic field for MagLIF on Z can be accomplished concurrently with improved cylindrical implosion uniformity.

The assembly of ultra-complex structures from simple building units remains a long-term challenge in chemistry. Using small molecular building blocks (MBBs) in a mixed-ligand approach permitted the assembly of unprecedented metal-organic frameworks (MOFs), M-kum-MOF-1 (M = Y, Tb), exhibiting extra-large mesoporous cavities with small access windows. The ultra-complex cage of M-kum-MOF-1 consists of 240 vertices bridged by 432 edges, leading to a 194 faces-containing tile. This tile exhibits more faces than in any periodic structures (zeolites, MOFs, metal-organic polyhedra [MOPs], etc.) known to date. M-kum-MOF-1 not only possess zeolitic features (anionic framework), but they also contain an underlying wse zeolitic topology, which is observed for the first time.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, California. Activities at this multiprogram engineering and science laboratory support the nuclear weapons stockpile program, energy and environmental research, homeland security, micro- and nanotechnologies, and basic science and engineering research. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report provides a summary of environmental monitoring information and compliance activities that occurred at Sandia National Laboratories, California during calendar year 2022 unless noted otherwise. General site and environmental program information is also included. This report was prepared in accordance with DOE O 231.1B, Environment, Safety and Health Reporting.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, New Mexico. Activities at the site support research and development programs with a wide variety of national security missions, resulting in technologies for nonproliferation, homeland security, energy and infrastructure, and defense systems and assessments. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report summarizes the environmental protection and monitoring programs in place at Sandia National Laboratories, New Mexico, during calendar year 2022. Environmental topics include cultural resource management, chemical management, air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting, and has been approved for public distribution.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the. U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, Tonopah Test Range. Activities at the site are conducted in support of U.S. Department of Energy weapons programs and have operated at the site since 1957. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding file environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report summarizes the environmental protection, restoration, and monitoring programs in place at Sandia National Laboratories, Tonopah Test Range during calendar year 2022. Environmental topics include cultural resource management, chemical management, air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, wastewater discharge, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE 0 231.IB, Admin Change 1, Environment, Safety and Health Reporting and has been approved for public distribution.

The interactions of carboxylate anions with water and cations are important for a wide variety of systems, both biological and synthetic. Here, in order to gain insight on properties of the local complexes, we apply density functional theory, to treat the complex electrostatic interactions, and investigate mixtures with varied numbers of carboxylate anions (acetate) and waters binding to monovalent cations, Li⁺, Na⁺ and K⁺. The optimal structure with overall lowest free energy contains two acetates and two waters such that the cation is four-fold coordinated, similar to structures found earlier for pure water or pure carboxylate ligands. More generally, the complexes with two acetates have the lowest free energy. In transitioning from the overall optimal state, exchanging an acetate for water has a lower free energy barrier than exchanging water for an acetate. In most cases, the carboxylates are monodentate and in the first solvation shell. As water is added to the system, hydrogen bonding between waters and carboxylate O atoms further stabilizes monodentate structures. These structures, which have strong electrostatic interactions that involve hydrogen bonds of varying strength, are significantly polarized, with ChelpG partial charges that vary substantially as the bonding geometry varies. Overall, these results emphasize the increasing importance of water as a component of binding sites as the number of ligands increases, thus affecting the preferential solvation of specific metal ions and clarifying Hofmeister effects. Finally, structural analysis correlated with free energy analysis supports the idea that binding to more than the preferred number of carboxylates under architectural constraints are a key to ion transport.

There is a common need in the advancement of optical diagnostic techniques to increase the dimensionality of measurements. For example, point measurements could be improved to multi-point, line, planar, volumetric, or time-resolved volumetric measurements. In this work, a unique optical element is presented to enable multidimensional measurements, namely, an array of glass wedges. A light source is passed through the wedges, and different portions of the illumination are refracted by different amounts depending on the glass wedge angle. Subsequent optics can be used to focus the light to multiple points, lines, or planes. Basic characterization of a glasswedge array is presented. Additionalwedge-array configurations are discussed, including the use of a periodic intensity mask for multi-planar measurements via structured illumination. The utility of this optical element is briefly demonstrated in (a) multi-planar flame particulate measurements, (b) multi-point femtosecond-laser electronic excitation tagging for flow velocimetry, and (c) multi-line nitric oxide molecular tagging velocimetry in a hypersonic shock-tunnel. One significant advantage of this optical component is its compatibility with highenergy laser sources, which may be a limiting factor with other beam-splitting or beam-forming elements such as some diffractive optics. Additionally, an array of glass wedges is simple and easily customizable compared to other methods for forming multiple closely spaced illumination patterns. Suggestions for further development and applications are discussed.

This milestone work baselines electromagnetic particle-in-cell capability of the EMPIRE plasma simulation code to model key processes germane to the physics of electrode plasmas arising in magnetically-insulated transmission lines operating at or near 20 MA. This evaluation is done so through the provision of benchmark verification problems designed to exercise the individual and combined physics models on a small-scale surrogate geometry for the final-feed-to-load region of the Z accelerator under representative operating conditions. In this report, we overview our test designs, and present a portfolio of simulation results along with performance assessments which altogether establish state-of-the-art. In particular, two main verification categories are covered this report: (1) Z-relevant desorption physics (Temkin isotherm), and (2) two approaches to simulate electrode plasma creation and dynamics (automatic creation versus self-consistent creation through direct simulation Monte Carlo collisions).

The natural assemblage of a symbiotic bacterial microbiome (bacteriome) with microalgae in marine ecosystems is now being investigated as a means to increase algal productivity for industry. When algae are grown in open pond settings, biological contamination causes an estimated 30% loss of the algal crop. Therefore, new crop protection strategies that do not disrupt the native algal bacteriome are needed to produce reliable, high-yield algal biomass. Bacteriophages offer an unexplored solution to treat bacterial pathogenicity in algal cultures because they can eliminate a single species without affecting the bacteriome. To address this, we identified a highly virulent pathogen of the microalga Nannochloropsis gaditana, the bacterium Bacillus safensis, and demonstrated rescue of the microalgae from the pathogen using phage. 16S rRNA amplicon sequencing showed that phage treatment did not alter the composition of the bacteriome. It is widely suspected that the algal bacteriome could play a protective role against bacterial pathogens. To test this, we compared the susceptibility of a bacteriome-attenuated N. gaditana culture challenged with B. safensis to a N. gaditana culture carrying a growth-promoting bacteriome. We showed that the loss of the bacteriome increased the susceptibility of N. gaditana to the pathogen. Transplanting the microalgal bacteriome to the bacteriome-attenuated culture reconstituted the protective effect of the bacteriome. Finally, the success of phage treatment was dependent on the presence of beneficial bacteriome. This study introduces two synergistic countermeasures against bacterial pathogenicity in algal cultures and a tractable model for studying interactions between microalgae, phages, pathogens, and the algae microbiome.

The Python-Cubit^® enhancement code base is intended to be used as an extension to already existing Cubit^® functionality. It provides the user with a number of functionalities that are either currently outside the realm of the python functions which Cubit^® supplies internally (such as vector math), or that are comprised of commonly used combinations of already existing python functionalities (such as removing a full round from a slot cut). The foreseen style of use for many of these scripts is to utilize volume names and geometric data such as surface area, surface type, etc. as a way to filter out geometries, and provide a powerful id-less method. These filters combined with a number of already existing python functionalities such as the set() operator and zip() function can be used to operate on many geometries at a single time without a need for the user to manually select them or use their ids. Please refer to the example given in the documents examples section for a demonstration of the work flow.

The dislocation core structure has a significant role in determining the dominant slip plane and the magnitude of the Peierls stress for a dislocation. An important challenge when studying dislocation cores is to determine the stable and metastable core morphologies, and then relate these structures to the dynamics of the dislocations. ere this study introduces a method for identifying core structures that are metastable at zero temperature. Application of this method to $\langle$a$\rangle$-type screw dislocations in α-Ti (as described using an empirical potential) reveals a multitude of (meta)stable nonplanar cores. Molecular dynamics studies show how the competing metastable core structures determine the properties of the dislocations at temperature and under a range of non-Schmid stresses.

There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. This work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow.

A series of MD and DFT simulations were performed to investigate hydrogen self-clustering and retention in tungsten. Using a newly develop machine learned interatomic potential, spontaneous formation of hydrogen platelets was observed after implanting low-energy hydrogen into tungsten at high fluxes and temperatures. The platelets formed along low miller index orientations and neighboring tetrahedral and octahedral sites and could grow to over 50 atoms in size. High temperatures above 600 K and high hydrogen concentrations were needed to observe significant platelet formation. A critical platelet size of six hydrogen atoms was needed for long term stability. Platelets smaller than this were found to be thermally unstable within a few nanoseconds. To verify these observations, characteristic platelets from the MD simulations were simulated using large-scale DFT. DFT corroborated the MD results in that large platelets were also found to be dynamically stable for five or more hydrogen atoms. The LDOS from the DFT simulated platelets indicated that hydrogen atoms, particularly at the periphery of the platelet, were found to be at least as stable as hydrogen atoms in bulk tungsten. In addition, electrons were found to be localized around hydrogen atoms in the platelet itself and that hydrogen atoms up to 4.2 Å away within the platelet were found to share charge suggesting that the hydrogen atoms are interacting across longer distances than previously suggested. These results reveal a self-clustering mechanisms for hydrogen within tungsten in the absence of radiation induced or microstructural defects that could be a precursor to blistering and potentially explain the experimentally observed high hydrogen retention particularly in the near surface region.

The Xyce™ Parallel Electronic Simulator has been written to support the simulation needs of Sandia National Laboratories’ electrical designers. Xyce™ is a SPICE-compatible simulator with the ability to solve extremely large circuit problems on large-scale parallel computing platforms, but also includes support for most popular parallel and serial computers.

This work presents a spectral micromechanical formulation for obtaining the full-field and homogenized response of elastic micropolar composites. The algorithm relies on a coupled set of convolution integral equations for the micropolar strains, where periodic Green’s operators associated with a linear homogeneous reference medium are convolved with functions of the Cauchy and couple stress fields that encode the material’s heterogeneity, as well as any potential material nonlinearity. Such convolution integral equations take an algebraic form in the reciprocal Fourier space that can be solved iteratively. In this vein, the fast Fourier transform (FFT) algorithm is leveraged to accelerate the numerical solution, resulting in a mesh-free formulation in which the periodic unit cell representing the heterogeneous material can be discretized by a regular grid of pixels in two dimensions (or voxels in three dimensions). For verification, the numerical solutions obtained with the micropolar FFT solver are compared with analytical solutions for a matrix with a dilute circular inclusion subjected to plane strain loading. The developed computational framework is then used to study length-scale effects and effective (micropolar) moduli of composites with various topological configurations.

The Z accelerator at Sandia National Laboratories conducts z-pinch experiments at 26 MA in support of DOE missions in stockpile stewardship, dynamic materials, fusion, and other basic sciences. Increasing the current delivered to the z-pinch would extend our reach in each of these disciplines. To achieve increases in current and accelerator efficiency, a fraction of Z’s shots are set aside for research into transmission-line power flow. These shots, with supporting simulations and theory, are incorporated into this Advanced Diagnostics milestone report. The efficiency of Z is reduced as some portion of the total current is shunted across the transmission-line gaps prior to the load. This is referred to as “current loss”. Electrode plasmas have long been implicated in this process, so the bulk of dedicated power-flow experiments are designed to measure the plasma environment. The experimental analyses are enhanced by simulations conducted using realistic hardware and Z voltage pulses. In the same way that diagnostics are continually being improved for sensitivity and resolution, the modeling capability is continually being improved to provide faster and more realistic simulations. The specifics of the experimental hardware, diagnostics, simulations, and algorithm developments are provided in this report. The combined analysis of simulation and data confirms that electrode plasmas have the most detrimental impact on current delivery. Experiments over the last three years have tested the theoretical current-loss mechanisms of enhanced ion current, plasma gap closure, and Hall-related current. These mechanisms are not mutually exclusive and may be coincident in the final feed as well as in upstream transmission lines. The final-feed geometries tested here, however, observe lower-density plasmas without dominant ion currents which is consistent with a Hall-related current. The picture of plasma formation and transport formed from experiment and simulation is informing hardware designs being fielded on Z now and being proposed for the Next-Generation Pulsed Power (NGPP) facility. In this picture, the strong magnetic fields that heat the electrodes above particle emission thresholds also confine the charged particles near the surface. Some portion of the plasmas thus formed is transported into the transmission-line gap under the force of the electric field, with aid from plasma instabilities. The gap plasmas are then transported towards the load by a cross-field drift, where they accumulate and contribute to a likely Hall-related cross-gap current. The achievements in experimental execution, model validation, and physical analysis presented in this report set the stage for continued progress in power flow and load diagnostics on Z. The planned shot schedule for Z and Mykonos will provide data for extrapolation to higher current to ensure the predicted performance and efficiency of a NGPP facility.

A third-generation chloride salt tank system was designed for a 1 MWth pilot-scale system to be investigated at the National Solar Thermal Test Facility (NSTTF) in Albuquerque, NM, USA. This prototype Gen 3, concentrating solar power (CSP) system was designed to facilitate a minimum of 6 hrs. of thermal energy storage (TES) with operational nominal temperatures of 500°C and 720°C for a cold and hot tank respectively. For this investigation, the researchers developed steady and transient computational fluid mechanics (CFD) circulation models to assess thermal-fluid behavior within the tanks, and their respective interactions with environmental heat transfer. The models developed for this novel CSP system design included unique chloride molten salt thermodynamic properties and correlations. The results of this investigation suggest thermal gradients for the steady flow model less 1oC with overall circulation velocities as high as approximately 2.1 m/s. Higher steady flow rates of salt passing into and out of the tanks resulted in smaller thermal gradients than the slower flow rates as the molten salt mixes better (an increase of around 120% in the heat transfer coefficient) at the higher velocities associated with the higher flow rate. The port spacing of 3.85 m was found to have a highly uniform temperature distribution. For the unsteady model, nitrogen flow was found to become appreciably steady after approximately 10 minutes, and resultant molten salt flow was found to increase slowly as the overall salt level rose.

This paper summarizes findings from a small, mixed-method research study examining industry perspectives on the potential for new forms of automation to invigorate the concentrating solar power (CSP) industry. In Fall 2021, the Solar Energy Technologies Office (SETO) of the United States Department of Energy (DOE) funded Sandia National Laboratories to elicit industry stakeholder perspectives on the potential role of automated systems in CSP operations. We interviewed eleven CSP professionals from five countries, using a combination of structured and open comment response modes. Respondents indicated a preference for automated systems that support heliostat manufacturing and installation, calibration, and responsiveness to shifting weather conditions. This pilot study demonstrates the importance of engaging industry stakeholders in discussions of technology research and development, to promote adoptable, useful innovation.

The United Sates Department of Energy (DOE) Generation 3 Concentrated Solar Power (CSP) program is interested in higher efficiency power systems at lower costs, potentially with systems utilizing chloride molten salts. Ternary chloride molten salts are corrosive and need to be held at high temperatures to achieve higher power system efficiencies. However, materials and cost of manufacturing of such a facility can be very expensive, particularly using exotic materials that are not always readily available. Materials that can withstand the harsh corrosive and thermal-mechanical environments of high-temperature molten salt systems (>700 ℃) are needed. High temperature systems offer greater thermodynamic efficiency but must also make cost efficient use of corrosion-resistant alloys. To ensure reliable high-performance operation for molten salt power plant designs confidence in materials compatibility with CSP Gen 3 halide salts must be established. This paper will present an analysis of Inconel 625 as an alternative to the costly Haynes 230 at 760℃ for 500 hours. Both metals were tested in an unaltered state as well as a homogenous weld. Each sample was weighed pre- and post-test, with a final composition analysis using Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray Spectroscopy (EDS). Preliminary findings suggest that Haynes 230 outperformed Inconel 625, but more research at longer durations, 1,000 hours will be required for full reliable assessment.

Falling particle receivers are a promising receiver design to couple with particle-based concentrating solar power to help meet future levelized cost of electricity targets in next generation systems. The thermal performance of receivers is critical to the economics of the overall system, and accurate models of particle receivers are necessary to predict the performance in all conditions. A model validation study was performed using falling particle receiver data recently collected at the National Solar Thermal Test Facility at Sandia National Laboratories. The particle outlet temperature, the thermal efficiency of the receiver, and the wind speed and direction around the receiver were measured in 26 steady-state experiments and compared to a corresponding receiver model. The results of this study showed improved agreement with the experimental data over past validation efforts but did not fully meet all predefined validation metrics. Future model improvements were identified to continue to strengthen the modeling capabilities.

The Sandia National Laboratories (SNL) National Solar Thermal Test Facility (NSTTF) conducted efficacy testing on a shut-off isolation valve for use with molten ternary chloride salt. A ball valve was tested under controlled N2 ullage gas pressure and connected with flanged fittings that featured a spiral-wound gasket. The valve assembly consisted of boronized nickel coated SS316 components, with design features that greatly reduce the cost of overall valve assembly. Testing results showed that the valve did not leak, and post-test analysis demonstrated that the ball, seat, packing, and body all survived both the heat loads and the relative corrosive environment. Spiral-wound gaskets for flanged connections used in the system also functioned nominally, with no leaks or signs of failures during post-test analysis. However, testing was ultimately forced to rapidly stop after testing between 500-530°C as the actuator used on the valve failed in the heat, preventing the valve from sealing in the closed position. In addition, salt plugs and salt vapor plating also prevented the test from continuing.

The need for reliable, cost-effective, utility scale energy storage that is universally applicable across different regions is becoming evident with the global transition towards non-polluting renewable energy resources. The operations and management of these energy storage technologies introduces a unique challenge that is inherently different from the conventional energy storage in the form of fossil fuel. The investigation into the business model, value proposition and economic viability of a utility scale thermal energy storage was part of a program sponsored by the United States Department of Energy, called Energy I-Corps. During this program, the project team reached out to a series of industry stakeholders to conduct interviews on the topic of thermal energy storage for utility scale power generation. Specific focus was placed on the business model based on the market needs in the context of the power grid in the United States. The utilization and re-use of infrastructure at existing thermo-electric power plants yielded the most viable business model for the implementation of the form of thermal energy storage discussed here.

This paper summarizes findings from a small, mixed-method research study examining industry perspectives on the potential for new forms of automation to invigorate the concentrating solar power (CSP) industry. In Fall 2021, the Solar Energy Technologies Office (SETO) of the United States Department of Energy (DOE) funded Sandia National Laboratories to elicit industry stakeholder perspectives on the potential role of automated systems in CSP operations. We interviewed eleven CSP professionals from five countries, using a combination of structured and open comment response modes. Respondents indicated a preference for automated systems that support heliostat manufacturing and installation, calibration, and responsiveness to shifting weather conditions. This pilot study demonstrates the importance of engaging industry stakeholders in discussions of technology research and development, to promote adoptable, useful innovation.

In this study, deformations inflicted in diamond could help design stronger materials.

Here, we develop a Stockmayer fluid model that accounts for the dielectric responses of polar solvents (water, MeOH, EtOH, acetone, 1-propanol, DMSO, and DMF) and NaCl solutions. These solvent molecules are represented by Lennard-Jones (LJ) spheres with permanent dipole moments and the ions by charged LJ spheres. The simulated dielectric constants of these liquids are comparable to experimental values, including the substantial decrease in the dielectric constant of water upon the addition of NaCl. Moreover, the simulations predict an increase in the dielectric constant when considering the influence of ion translations in addition to the orientation of permanent dipoles.

Sandia National Laboratories and the Institut de Radioprotection et de Sûreté Nucléaire have collaborated on the design and execution of a set of critical experiments that explore the effects of molybdenum in water-moderated fuel-rod arrays. The molybdenum was included as sleeves on some of the fuel rods in the critical experiment fuel arrays. Approach-to-critical experiments were performed on five configurations of fuel and molybdenum sleeves using the 7uPCX fuel in core hardware that set the triangular fuel rod pitch at 15.494 mm. The experiments are evaluated as benchmark critical experiments for the 2023 edition of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook as LEU-COMP-THERM-111.

NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.

The Integrated Tiger Series (ITS) generates a database containing energy deposition data. This data, when stored on an Exodus file, is not typically suitable for analysis within Sierra Mechanics for finite element analysis. The its2sierra tool maps data from the ITS database to the Sierra database. This document provides information on the usage of its2sierra.