Publications

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This report presents the results of the sampling effort and documents all associated field activities including borehole clearing, soil sample collection, storage and transportation to the analytical laboratories, borehole backfilling and surface restoration, and storage of investigation-derived waste (IDW) for future profiling and disposal by SNL/CA waste management personnel.

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The objective of this study was to evaluate the impact of alternative ventilation configurations on airflow patterns and potential exposure risks in office spaces. Two existing conference rooms at Sandia NM were modeled using Computational Fluid Dynamics (CFD) simulations to characterize airflow patterns and potential airborne exposure risks in well-mixed and once-through (through-flow) ventilation conditions. Multiple scenarios were studied to evaluate the impact of occupancy, Plexiglass barriers, and a modified-return airflow configuration. Experimental and visualization tests were also conducted to validate the well-mixed and through-flow models and findings. The simulations demonstrated that the modified-return airflow configuration that promoted through-flow conditions reduced pathogen concentrations within the space compared to the well-mixed airflow configuration; occupancy reduction only reduced the number of exposed individuals, and Plexiglass barriers had almost no effect. The experimentally measured air speeds at nine anemometer locations generally matched the simulated airflow velocities, and a fog-purge visualization test was also consistent with simulated results of plume movement and dissipation. The visualization tests demonstrated improvements in air change rate with the modified return, which promoted through-flow conditions, versus the original well-mixed ventilation configuration. The results of this study demonstrate that minor modifications to a space that promote through-flow conditions can improve air quality and reduce pathogen concentrations. Additional airflow modeling and testing of alternative occupied space configurations are recommended to further inform room designs that mitigate airborne exposure risks for occupants.

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Borrowing from nature, neural-inspired interception algorithms were implemented onboard a vehicle. To maximize success, work was conducted in parallel within a simulated environment and on physical hardware. The intercept vehicle used only optical imaging to detect and track the target. A successful outcome is the proof-of-concept demonstration of a neural-inspired algorithm autonomously guiding a vehicle to intercept a moving target. This work tried to establish the key parameters for the intercept algorithm (sensors and vehicle) and expand the knowledge and capabilities of implementing neural-inspired algorithms in simulation and on hardware.

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This SNL document contains requested radiological survey information, as part of the documentation for the MLU shipment performed by the LANL MLU team on October 20th. The survey was performed in TA-5, on October 20th, 2021. This survey was for radiological coverage for the disassembly of two TRUPACTs, the assembly and loading of their payloads, and the reassembly of the TRUPACTs.

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It is very difficult to measure the voltage of the load on the Saturn accelerator. Time-resolved measurements such as vacuum voltmeters and V-dot monitors are impractical at best and completely change the pulsed power behavior at the load at worst. We would like to know the load voltage of the machine so that we could correctly model the radiation transport and tune our x-ray unfold methodology and circuit simulations of the accelerator. Step wedges have been used for decades as a tool to measure the end - point energies of high energy particle beams. Typically, the technique is used for multi-megavolt accelerators, but we have adapted it to Saturn's modest <2 MV end-point energy and modified the standard bremsstrahlung x-ray source to extract the electron beam without changing the physics of the load region. We found clear evidence of high energy electrons >2 MV. We also attempted to unfold an electron energy spectrum using a machine learning algorithm and while these results come with large uncertainties, they qualitatively agree with PIC simulation results.

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As the number of supported platforms for SNL software increases, so do the testing requirements. This increases the total time spent between when a developer submits code for testing, and when tests are completed. This in turn leads developers to hold off submitting code for testing, meaning that when code is ready for testing there's a lot more of it. This increases the likelihood of merge conflicts which the developer must resolve by hand -- because someone else touched the files near the lines the developer touched. Current text-based diff tools often have trouble resolving conflicts in these cases. Work in Europe and Japan has demonstrated that, using programming language aware diff tools (e.g., using the abstract syntax tree (AST) a compiler might generate) can reduce the manual labor necessary to resolve merge conflicts. These techniques can detect code blocks which have moved, as opposed than current text-based diff tools, which only detect insertions / deletions of text blocks. In this study, we evaluate one such tool, GumTree, and see how effective it is as a replacement for traditional text-based diff approaches.

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Sandia National Laboratories has tested and evaluated the performance of the following five models of low-cost infrasound sensors and sensor packages: Camas microphone, Gem Infrasound Logger, InfraBSU sensor, Raspberry Boom, and the Samsung S10 smartphone utilizing the Redvox app. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, self-noise, dynamic range, response, passband, linearity, sensitivity variation due to changes in static pressure and temperature, and sensitivity to vertical acceleration. The infrasound monitoring community has leveraged such sensors and integrated packages in novel ways; better understanding the performance of these units serves the geophysical monitoring community.

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Quantum sensing has the potential to provide ultrasensitive measurements of physical phenomenon. Unlike quantum computing, quantum sensing is available now, though in general at research laboratories. A notable commercially-available quantum sensing device is the ubiquitous Superconducting Quantum Interference Device (SQUID), which can measure faint magnetic fields such as found in the human brain. Quantum sensing is used for direct measurement of environmental phenomenon, such as electromagnetic fields and accelerations, which then are used for certain applications. For example, quantum sensing of accelerations is useful for Position, Navigation, and Timing (PNT) applications. It is not clear, however, how quantum sensing can be useful for nuclear safeguards. This report provides first a background in quantum sensing, followed by a survey of potential safeguards utilizations of quantum sensing. Several potential safeguards applications are identified and explored.

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In this project we developed and validated algorithms for privacy-preserving linear regression using a new variant of Secure Multiparty Computation (MPC) we call "Hybrid MPC" (hMPC). Our variant is intended to support low-power, unreliable networks of sensors with low-communication, fault-tolerant algorithms. In hMPC we do not share training data, even via secret sharing. Thus, agents are responsible for protecting their own local data. Only the machine learning (ML) model is protected with information-theoretic security guarantees against honest-but-curious agents. There are three primary advantages to this approach: (1) after setup, hMPC supports a communication-efficient matrix multiplication primitive, (2) organizations prevented by policy or technology from sharing any of their data can participate as agents in hMPC, and (3) large numbers of low-power agents can participate in hMPC. We have also created an open-source software library named "Cicada" to support hMPC applications with fault-tolerance. The fault-tolerance is important in our applications because the agents are vulnerable to failure or capture. We have demonstrated this capability at Sandia's Autonomy New Mexico laboratory through a simple machine-learning exercise with Raspberry Pi devices capturing and classifying images while flying on four drones.

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As noise limits the performance of quantum processors, the ability to characterize this noise and develop methods to overcome it is essential for the future of quantum computing. In this report, we develop a complete set of tools for improving quantum processor performance at the application level, including low-level physical models of quantum gates, a numerically efficient method of producing process matrices that span a wide range of model parameters, and full-channel quantum simulations. We then provide a few examples of how to use these tools to study the effects of noise on quantum circuits.

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Understanding the capture of charge carriers by colour centres in semiconductors is important for the development of novel forms of sensing and quantum information processing, but experiments typically involve ensemble measurements, often impacted by defect proximity. Here we show that confocal fluorescence microscopy and magnetic resonance can be used to induce and probe charge transport between individual nitrogen-vacancy centres in diamond at room temperature. In our experiments, a ‘source’ nitrogen vacancy undergoes optically driven cycles of ionization and recombination to produce a stream of photogenerated carriers, one of which is subsequently captured by a ‘target’ nitrogen vacancy several micrometres away. We use a spin-to-charge conversion scheme to encode the spin state of the source colour centre into the charge state of the target, which allows us to set an upper bound to carrier injection from other background defects. We attribute our observations to the action of unscreened Coulomb potentials producing giant carrier capture cross-sections, orders of magnitude greater than those measured in ensembles.

Radiographic diodes focus an intense electron beam to a small spot size to minimize the source area of energetic photons for radiographic interrogation. The self-magnetic pinch (SMP) diode has been developed as such a source and operated as a load for the RITS-6 Inductive Voltage Adder (IVA) driver. While experiments support the generally accepted conclusion that a 1:1 aspect diode (cathode diameter equals anode-cathode gap) delivers optimum SMP performance, such experiments also show that reducing the cathode diameter, while reducing spot size, also results in reduced radiation dose, by as much as 50%, and degraded shot reproducibility. Analyzation of the effective electron impingement angle on the anode converter with time made possible by a newly developed dose-rate array diagnostic indicates that fast-developing oscillations of the angle are correlated with early termination of the radiation pulse on many of the smaller-diameter SMP shots. This behavior as a function of relative cathode size persists through experiments with output voltages and currents up to 11.5 MV and 225 kA, respectively, and with spot sizes below ~ few mm. Since simulations to date have not predicted such oscillatory behavior, considerable discussion of the angle-behavior of SMP shots is made to lend credence to the inference. There is clear anecdotal evidence that DC heating of the SMP diode region leads to stabilization of this oscillatory behavior. This is the first of two papers on the performance of the SMP diode on the RITS-6 accelerator.

Archaeological data and demographic modelling suggest that the peopling of Sahul required substantial populations, occurred rapidly within a few thousand years and encompassed environments ranging from hyper-arid deserts to temperate uplands and tropical rainforests. How this migration occurred and how humans responded to the physical environments they encountered have, however, remained largely speculative. By constructing a high-resolution digital elevation model for Sahul and coupling it with fine-scale viewshed analysis of landscape prominence, least-cost pedestrian travel modelling and high-performance computing, we create over 125 billion potential migratory pathways, whereby the most parsimonious routes traversed emerge. Our analysis revealed several major pathways—superhighways—transecting the continent, that we evaluated using archaeological data. These results suggest that the earliest Australian ancestors adopted a set of fundamental rules shaped by physiological capacity, attraction to visually prominent landscape features and freshwater distribution to maximize survival, even without previous experience of the landscapes they encountered.

In preparation for testing a lithium-helium heat exchanger at Sandia, unexpected rapid failure of the mild steel lithium preheater due to liquid metal embrittlement occurred when lithium at ~400 °C flowed into the preheater then at ~200 °C. This happened before the helium system was pressurized or heating with electron beams began. The paper presents an analysis of the preheater plus a discussion of some implications for fusion.

We present a simple, near-real-time Bayesian method to infer and forecast a multiwave outbreak, and demonstrate it on the COVID-19 pandemic. The approach uses timely epidemiological data that has been widely available for COVID-19. It provides short-term forecasts of the outbreak’s evolution, which can then be used for medical resource planning. The method postulates one- and multiwave infection models, which are convolved with the incubation-period distribution to yield competing disease models. The disease models’ parameters are estimated via Markov chain Monte Carlo sampling and information-theoretic criteria are used to select between them for use in forecasting. The method is demonstrated on two- and three-wave COVID-19 outbreaks in California, New Mexico and Florida, as observed during Summer-Winter 2020. We find that the method is robust to noise, provides useful forecasts (along with uncertainty bounds) and that it reliably detected when the initial single-wave COVID-19 outbreaks transformed into successive surges as containment efforts in these states failed by the end of Spring 2020.

The stiffness of wellbore cement fracture surfaces was measured after exposing to the advective flow of nitrogen, silicone oil, and medium sweet dead crude oil for different exposure periods. The test specimens were extracted from fractured cement cylinders, where the cement fracture surfaces were exposed to the different fluids up to 15 weeks. A nanoindenter with a Berkovich indenter tip was used to measure load-indentation depth data, which was used to extract the elastic modulus (E) and nano-hardness (H) of the cement fracture surfaces. A reduction in the elastic modulus compared with an unexposed specimen were observed in all the specimens. Both elastic modulus and nano-hardness for the specimens exposed to silicone oil were lower than specimens exposed to nitrogen gas and varied with the period of exposure. The elastic modulus and nano-hardness of the specimens exposed to crude oil were the lowest with a significant decrement with the exposure period. The frequency distribution of the nanoindentation measurements shows that the volume-fraction ratio of the two types of cement hydrated nanocomposites for both the unexposed and test specimens is about 70:30%. Phase transformation beneath the indenter is observed for all of the specimens, with more obvious plastic deformation in specimens exposed to crude oil. Analytical measurements (SEM, EDS, FT-IR, and XRD) on exposed cement fracture surfaces reveal different levels of physical and chemical alteration that are consistent with the reduction in stiffness measured by nanoindentation. The study suggests that cement stiffness will decrease due to crude oil exposure, and the fracture will be sensitive to stress and pore pressure with time.

The use of bounding scenarios is a common practice that greatly simplifies the design and qualification of structures. However, this approach implicitly assumes that the quantities of interest increase monotonically with the input to the structure, which is not necessarily true for nonlinear structures. This paper surveys the literature for observations of nonmonotonic behavior of nonlinear systems and finds such observations in both the earthquake engineering and applied mechanics literature. Numerical simulations of a single degree-of-freedom mass-spring system with an elastic–plastic spring subjected to a triangular base acceleration pulse are then presented, and it is shown that the relative acceleration of this system scales nonmonotonically with the input magnitude in some cases. The equation of motion for this system is solved symbolically and an approximate expression for the relative acceleration is developed, which qualitatively agrees with the nonmonotonic behavior seen in the numerical results. The nonmonotonicity is investigated and found to be a result of dynamics excited by the discontinuous derivative of the base acceleration pulse, the magnitude of which scales nonmonotonically with the input magnitude due to the fact that the first yield of the spring occurs earlier as the input magnitude is increased. The relevance of this finding within the context of defining bounding scenarios is discussed, and it is recommended that modeling be used to perform a survey of the full range of possible inputs prior to defining bounding scenarios.

A cohesive phase-field model of ductile fracture in a finite-deformation setting is presented. The model is based on a free-energy function in which both elastic and plastic work contributions are coupled to damage. Using a strictly variational framework, the field evolution equations, damage kinetics, and flow rule are jointly derived from a scalar least-action principle. Particular emphasis is placed on the use of a rational function for the stress degradation that maintains a fixed effective strength with decreasing regularization length. The model is employed to examine crack growth in pure mode-I problems through the generation of crack growth resistance (J-R) curves. In contrast to alternative models, the current formulation gives rise to J-R curves that are insensitive to the regularization length. Numerical evidence suggests convergence of local fields with respect to diminishing regularization length as well.

This work aims to advance computational methods for projection-based reduced-order models (ROMs) of linear time-invariant (LTI) dynamical systems. For such systems, current practice relies on ROM formulations expressing the state as a rank-1 tensor (i.e., a vector), leading to computational kernels that are memory bandwidth bound and, therefore, ill-suited for scalable performance on modern architectures. This weakness can be particularly limiting when tackling many-query studies, where one needs to run a large number of simulations. This work introduces a reformulation, called rank-2 Galerkin, of the Galerkin ROM for LTI dynamical systems which converts the nature of the ROM problem from memory bandwidth to compute bound. We present the details of the formulation and its implementation, and demonstrate its utility through numerical experiments using, as a test case, the simulation of elastic seismic shear waves in an axisymmetric domain. We quantify and analyze performance and scaling results for varying numbers of threads and problem sizes. Finally, we present an end-to-end demonstration of using the rank-2 Galerkin ROM for a Monte Carlo sampling study. We show that the rank-2 Galerkin ROM is one order of magnitude more efficient than the rank-1 Galerkin ROM (the current practice) and about 970 times more efficient than the full-order model, while maintaining accuracy in both the mean and statistics of the field.

Time-resolved particle image velocimetry (TR-PIV) has become widespread in fluid dynamics. Essentially a velocity field movie, the dynamic content provides temporal as well as spatial information, in contrast to conventional PIV offering only statistical ensembles of flow quantities. From these time series arise further analyses such as accelerometry, space-time correlations, frequency spectra of turbulence including spatial variability, and derivation of pressure fields and forces. The historical development of TR-PIV is chronicled, culminating in an assessment of the current state of technology in high-repetition-rate lasers and high-speed cameras. Commercialization of pulse-burst lasers has expanded TR-PIV into more flows, including the compressible regime, and has achieved MHz rates. Particle response times and peak locking during image interrogation require attention but generally are not impediments to success. Accuracy considerations are discussed, including the risks of noise and aliasing in spectral content. Oversampled TR-PIV measurements allow use of multi-frame image interrogation methods, which improve the precision of the correlation and raise the velocity dynamic range of PIV. In combination with volumetric methods and data assimilation, a full four-dimensional description of a flow is not only achievable but becoming standardized. A survey of exemplary applications is followed by a few predictions concerning the future of TR-PIV.

A hybrid atomic-scale and continuum-modeling framework is used to study the microstructural evolution during the laser-induced shock deformation and failure (spallation) of copper microstructures. A continuum two-temperature model (TTM) is used to account for the interaction of Cu atoms with a laser in molecular dynamics (MD) simulations. The MD-TTM simulations study the effect of laser-loading conditions (laser fluence) on the microstructure (defects) evolution during various stages of shock wave propagation, reflection, and interaction in single-crystal (sc) Cu systems. In addition, the role of the microstructure is investigated by comparing the defect evolution and spall response of sc-Cu and nanocrystalline Cu systems. The defect (stacking faults and twin faults) evolution behavior in the metal at various times is further characterized using virtual in situ selected area electron diffraction and x-ray diffraction during various stages of evolution of microstructure. The simulations elucidate the uncertain relation between spall strength and strain-rate and the much stronger relation between the spall strength and the temperatures generated due to laser shock loading for the small Cu sample dimensions considered here.

In this analysis, the two material interaction models available in the MELCOR code are benchmarked for a severe accident at a BWR under representative Fukushima Daiichi boundary conditions. This part of the benchmark investigates the impact of each material interaction model on accident progression through a detailed single case analysis. It is found that the eutectics model simulation exhibits more rapid accident progression for the duration of the accident. The slower accident progression exhibited by the interactive materials model simulation, however, allows for a greater degree of core material oxidation and hydrogen generation to occur, as well as elevated core temperatures during the ex-vessel accident phase. The eutectics model simulation exhibits more significant degradation of core components during the late in-vessel accident phase – more debris forms and relocates to the lower plenum before lower head failure. The larger debris bed observed in the eutectics model simulation also reaches higher temperatures, presenting a more significant thermal challenge to the lower head until its failure. At the end of the simulated accident scenario, however, core damage is comparable between both simulations due to significant core degradation that occurs during the ex-vessel phase in the interactive materials model simulation. A key difference between the two models’ performance is the maximum temperatures that can be reached in the core and therefore the maximum ΔT between any two components. When implementing the interactive materials model, users have the option to modify the liquefaction temperature of the ZrO2-interactive and UO2-interactive materials as a way to mimic early fuel rod failure due to material interactions. Through modification of the liquefaction of high melting point materials with significant mass, users may inadvertently limit maximum core temperatures for fuel, cladding, and debris components.

Metamaterials are artificial structures that can manipulate and control sound waves in ways not possible with conventional materials. While much effort has been undertaken to widen the bandgaps produced by these materials through design of heterogeneities within unit cells, comparatively little work has considered the effect of engineering heterogeneities at the structural scale by combining different types of unit cells. In this paper, we use the relaxed micromorphic model to study wave propagation in heterogeneous metastructures composed of different unit cells. We first establish the efficacy of the relaxed micromorphic model for capturing the salient characteristics of dispersive wave propagation through comparisons with direct numerical simulations for two classes of metamaterial unit cells: namely phononic crystals and locally resonant metamaterials. We then use this model to demonstrate how spatially arranging multiple unit cells into metastructures can lead to tailored and unique properties such as spatially-dependent broadband wave attenuation, rainbow trapping, and pulse shaping. In the case of the broadband wave attenuation application, we show that by building layered metastructures from different metamaterial unit cells, we can slow down or stop wave packets in an enlarged frequency range, while letting other frequencies through. In the case of the rainbow-trapping application, we show that spatial arrangements of different unit cells can be designed to progressively slow down and eventually stop waves with different frequencies at different spatial locations. Finally, in the case of the pulse-shaping application, our results show that heterogeneous metastructures can be designed to tailor the spatial profile of a propagating wave packet. Collectively, these results show the versatility of the relaxed micromorphic model for effectively and accurately simulating wave propagation in heterogeneous metastructures, and how this model can be used to design heterogeneous metastructures with tailored wave propagation functionalities.

Performance assessment (PA) of geologic radioactive waste repositories requires three-dimensional simulation of highly nonlinear, thermo-hydro-mechanical-chemical (THMC), multiphase flow and transport processes across many kilometers and over tens to hundreds of thousands of years. Integrating the effects of a near-field geomechanical process (i.e. buffer swelling) into coupled THC simulations through reduced-order modeling, rather than through fully coupled geomechanics, can reduce the dimensionality of the problem and improve computational efficiency. In this study, PFLOTRAN simulations model a single waste package in a shale host rock repository, where re-saturation of a bentonite buffer causes the buffer to swell and exert stress on a highly fractured disturbed rock zone (DRZ). Three types of stress-dependent permeability functions (exponential, modified cubic, and Two-part Hooke's law models) are implemented to describe mechanical characteristics of the system. Our modeling study suggests that compressing fractures reduces DRZ permeability, which could influence the rate of radionuclide transport and exchange with corrosive species in host rock groundwater that could accelerate waste package degradation. Less permeable shale host rock delays buffer swelling, consequently retarding DRZ permeability reduction as well as chemical transport within the barrier system.

The mechanical behavior of Ti-6Al-4V produced by additive manufacturing processes is assessed as based on a model derived from the Kocks–Mecking relationship. A constitutive parameter cb is derived from a linear Kocks–Mecking relationship for the microstructure that is characteristic of the work hardening behavior. The formulation for cb is determined by considering the plastic strain between the strengths at the proportional limit and the plastic instability. In this way, the model accommodates the variation in work hardening behavior observed when evaluating material as produced and tested along different orientations. The modeling approach is presented and evaluated for the case of Ti-6Al-4V additively manufactured materials as tested under quasi-static uniaxial tension. It is found that different test specimen orientations, along with postbuild heat treatments, produce a change in the microstructure and plasticity behavior which can be accounted for in the corresponding change of the cb values.

Ni-Cr alloys exhibit oscillatory segregation behaviors near low index surfaces, in which the preferred segregation species changes from Ni in the first layer to Cr in the second layer. In many dilute-alloy systems, this oscillatory pattern is attributed to the elastic release of stresses in the local lattice around the segregating solute or impurity atom. These stresses are mostly thought to originate from mismatches in the atomic size of the solute and host atoms. In Ni-Cr alloys, however, an appreciable mismatch in atomic size is not present, leading to questions about the origins of the oscillatory behavior in this alloy. Using density functional theory, we have modeled the segregation of a single Cr atom in the (100) and (111) surfaces of FCC Ni, an alloy which exhibits this oscillatory behavior. Using Bader charge analysis, we show that the negative energy correlates directly with the amount of charge on the Cr atom. As Ni atoms strip valence charge from the Cr, the Cr contracts slightly in size. The greatest contraction and highest positive charge for the Cr occurs when it is in the second layer of the surface where the system exhibits the oscillating negative segregation energy. We then find that this behavior persists in other alloy systems (Ag-Nb, Cu-Cr, Pt-Nb, and Pt-V), which exhibit similar atomic radii and electronegativity differences between host and solute to Ni-Cr. These represent alloys in which the host metal exhibits an FCC ground-state structure while the solute metal exhibits a BCC ground-state structure.

This document summarizes the findings of a review of published literature regarding the potential impacts of electromagnetic pulse (EMP) and geomagnetic disturbance (GMD) phenomena on oil and gas pipeline systems. The impacts of telluric currents on pipelines and their associated cathodic protection systems has been well studied. The existing literature describes implications for corrosion protection system design and monitoring to mitigate these impacts. Effects of an EMP on pipelines is not a thoroughly explored subject. Most directly related articles only present theoretical models and approaches rather than specific analyses and in-field testing. Literature on SCADA components and EMP is similarly sparse and the existing articles show a variety of impacts to control system components that range from upset and damage to no effect. The limited research and the range of observed impacts for the research that has been published suggests the need for additional work on GMD and EMP and natural gas SCADA components.

Medical countermeasures (MCMs) based on messenger ribonucleic acid (mRNA) are promising due to their programmability, targeting precision and specificity, predictable physicochemical properties, and amenability to scalable manufacture. However, safe and effective delivery vehicles are needed, especially for targeting the lung. We developed a generalized approach to nanoparticle-mediated mRNA delivery to lung, and used it to evaluate candidate therapies. In initial studies, reporter mRNA was delivered using lipid-coated mesoporous silica nanoparticles (LC-MSNs) and lipid nanoparticles (LNPs), the latter with greater consistency. Then, mRNA encoding known protein therapies were delivered using LNPs. These formulations showed some toxicity in mice with lung damage, but those with IL-1RA, sACE2-Ig, and ANGPT1 mRNA were modestly therapeutic on balance. Our work advances the state of the art for mRNA delivery to lung, and provides a foundation for evaluating and characterizing mRNA-based lung therapies, including three that appear to be exceptionally promising.

In-situ additive manufacturing (AM) diagnostic tools (e.g., optical/infrared imaging, acoustic, etc.) already exist to correlate process anomalies to printed part defects. This current work aimed to augment existing capabilities by: 1) Incorporating in-situ imaging w/ machine learning (ML) image processing software (ORNL- developed "Peregrine") for AM process anomaly detection 2) Synchronizing multiple in-situ sensors for simultaneous analysis of AM build events 3) Correlating in-situ AM process data, generated part defects and part mechanical properties The key R&D question investigated was to determine if these new combined hardware/software tools could be used to successfully quantify defect distributions for parts build via SNL laser powder bed fusion (LPBF) machines, aiming to better understand data-driven process-structure-property- performance relationships. High resolution optical cameras and acoustic microphones were successfully integrated in two LPBF machines and linked to the Peregrine ML software. The software was successfully calibrated on both machines and used to image hundreds of layers of multiple builds to train the ML software in identifying printed part vs powder. The software's validation accuracy to identify this aspect increased from 56% to 98.8% over three builds. Lighting conditions inside the chamber were found to significantly impact ML algorithm predictions from in-situ sensors, so these were tailored to each machine's internal framework. Finally, 3D part reconstructions were successfully generated for a build from the compressed stack of layer-wise images. Resolution differences nearest and furthest from the optical camera were discussed. Future work aims to improve optical resolution, increase process anomalies identified, and integrate more sensor modalities.

A mass property calculator has been developed to compute the moment of inertia properties of an assemblage of parts that make up a system. The calculator can take input from spreadsheets or Creo mass property files or it can be interfaced with Phoenix Integration Model Center. The input must include the centroidal moments of inertia of each part with respect to its local coordinates, the location of the centroid of each part in the system coordinates and the Euler angles needed to rotate from the part coordinates to the system coordinates. The output includes the system total mass, centroid and mass moment of inertia properties. The input/output capabilities allow the calculator to interface with external optimizers. In addition to describing the calculator, this document serves as its user's manual. The up-to-date version of the calculator can be found in the Git repository https://cee-gitlab.sandia.gov/cj?ete/mass-properties-calculator.

Drilling systems that use downhole rotation must react torque either through the drill-string or near the motor to achieve effective drilling performance. Problems with drill-string loading such as buckling, friction, and twist become more severe as hole diameter decreases. Therefore, for small holes, reacting torque downhole without interfering with the application of weight-on-bit, is preferred. In this paper, we present a novel mechanism that enables effective and controllable downhole weight on bit transmission and torque reaction. This scalable design achieves its unique performance through four key features: (1) mechanical advantage based on geometry, (2) direction dependent behavior using rolling and sliding contact, (3) modular scalability by combining modules in series, and (4) torque reaction and weight on bit that are proportional to applied axial force. As a result, simple mechanical devices can be used to react large torques while allowing controlled force to be transmitted to the drill bit. We outline our design, provide theoretical predictions of performance, and validate the results using full-scale testing. The experimental results include laboratory studies as well as limited field testing using a percussive hammer. These results demonstrate effective torque reaction, axial force transmission, favorable scaling with multiple modules, and predictable performance that is proportional to applied force.

Co-deposited, immiscible alloy systems form hierarchical microstructures under specific deposition conditions that accentuate the difference in constituent element mobility. The mechanism leading to the formation of these unique hierarchical morphologies during the deposition process is difficult to identify, since the characterization of these microstructures is typically carried out post-deposition. We employ phase-field modeling to study the evolution of microstructures during deposition combined with microscopy characterization of experimentally deposited thin films to reveal the origin of the formation mechanism of hierarchical morphologies in co-deposited, immiscible alloy thin films. Our results trace this back to the significant influence of a local compositional driving force that occurs near the surface of the growing thin film. We show that local variations in the concentration of the vapor phase near the surface, resulting in nuclei (i.e., a cluster of atoms) on the film’s surface with an inhomogeneous composition, can trigger the simultaneous evolution of multiple concentration modulations across multiple length scales, leading to hierarchical morphologies. We show that locally, the concentration must be above a certain threshold value in order to generate distinct hierarchical morphologies in a single domain.

We consider a class of nonlinear control synthesis problems where the underlying mathe-matical models are not explicitly known. We propose a data-driven approach to stabilize the systems when only sample trajectories of the dynamics are accessible. Our method is built on the density-function-based stability certificate that is the dual to the Lyapunov function for dynamic systems. Unlike Lyapunov-based methods, density functions lead to a convex formulation for a joint search of the control strategy and the stability certificate. This type of convex problem can be solved efficiently using the machinery of the sum of squares (SOS). For the data-driven part, we exploit the fact that the duality results in the stability theory can be understood through the lens of Perron–Frobenius and Koopman operators. This allows us to use data-driven methods to approximate these operators and combine them with the SOS techniques to establish a convex formulation of control synthesis. The efficacy of the proposed approach is demonstrated through several examples.

Sandia National Laboratories will computationally evaluate several raceway pond design modifications for improved growth of Haematococcus pluvialis. Sandia National Laboratories will use the model to optimize design and growth conditions such as temperature, light, and CO₂ to make design and condition modification recommendations to the Requestor.

The treatment of emissions from natural gas engines is an important area of research since methane is a potent greenhouse gas. The benchmark catalysts, based on Pd, still face challenges such as water poisoning and long-term stability. Here we report an approach for catalyst synthesis that relies on the trapping of metal single atoms on the support surface, in thermally stable form, to modify the nature of further deposited metal/metal oxide. By anchoring Pt ions on a catalyst support we can tailor the morphology of the deposited phase. In particular, two-dimensional (2D) rafts of PdOx are formed, resulting in higher reaction rates and improved water tolerance during methane oxidation. The results show that modifying the support by trapping single atoms could provide an important addition to the toolkit of catalyst designers for controlling the nucleation and growth of metal and metal oxide clusters in heterogeneous catalysts. [Figure not available: see fulltext.].

Abstract not provided.

A key objective of the United States Department of Energy’s (DOE) Office of Nuclear Energy’s Spent Fuel and Waste Science and Technology Campaign is to better understand the technical basis, risks, and uncertainty associated with the safe and secure disposition of spent nuclear fuel (SNF) and high-level radioactive waste. Commercial nuclear power generation in the United States has resulted in thousands of metric tons of SNF, the disposal of which is the responsibility of the DOE (Nuclear Waste Policy Act of 1982, as amended). Any repository licensed to dispose of SNF must meet requirements regarding the long-term performance of that repository. For an evaluation of the long-term performance of the repository, one of the events that may need to be considered is the SNF achieving a critical configuration during the postclosure period. Of particular interest is the potential behavior of SNF in dual-purpose canisters (DPCs), which are currently licensed and being used to store and transport SNF but were not designed for permanent geologic disposal. A study has been initiated to examine the potential consequences, with respect to long-term repository performance, of criticality events that might occur during the postclosure period in a hypothetical repository containing DPCs. The first phase (a scoping phase) consisted of developing an approach to creating the modeling tools and techniques that may eventually be needed to either include or exclude criticality from a performance assessment (PA) as appropriate; this scoping phase is documented in Price et al. (2019a). In the second phase, that modeling approach was implemented and future work was identified, as documented in Price et al. (2019b). This report gives the results of a repository-scale PA examining the potential consequences of postclosure criticality, as well as the information, modeling tools, and techniques needed to incorporate the effects of postclosure criticality in the PA.

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

SIERRA/Aero is a compressible fluid dynamics program intended to solve a wide variety compressible fluid flows including transonic and hypersonic problems. This document describes the commands for assembling a fluid model for analysis with this module, henceforth referred to simply as Aero for brevity. Aero is an application developed using the SIERRA Toolkit (STK). The intent of STK is to provide a set of tools for handling common tasks that programmers encounter when developing a code for numerical simulation. For example, components of STK provide field allocation and management, and parallel input/output of field and mesh data. These services also allow the development of coupled mechanics analysis software for a massively parallel computing environment.

SIERRA/Aero is a compressible fluid dynamics program intended to solve a wide variety compressible fluid flows including transonic and hypersonic problems. This document describes the commands for assembling a fluid model for analysis with this module, henceforth referred to simply as Aero for brevity. Aero is an application developed using the SIERRA Toolkit (STK). The intent of STK is to provide a set of tools for handling common tasks that programmers encounter when developing a code for numerical simulation. For example, components of STK provide field allocation and management, and parallel input/output of field and mesh data. These services also allow the development of coupled mechanics analysis software for a massively parallel computing environment.

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC re environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

Presented in this document is a portion of the tests that exist in the Sierra Thermal/Fluids verification test suite. Each of these tests is run nightly with the Sierra/TF code suite and the results of the test checked under mesh refinement against the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

Polymers such as PTFE (polytetrafluorethylene or Teflon), EPDM (ethylene propylene diene monomer) rubber, FKM fluoroelastomer (Viton), Nylon 11, Nitrile butadiene (NBR) rubber, hydrogenated nitrile rubber (HNBR) and perfluoroelastomers (FF_202) are commonly employed in super critical CO₂ (sCO2) energy conversion systems. O-rings and gaskets made from these polymers face stringent performance conditions such as elevated temperatures, high pressures, pollutants, and corrosive humid environments. In FY 2019, we conducted experiments at high temperatures (100°C and 120°C) under isobaric conditions (20 MPa). Findings showed that elevated temperatures accelerated degradation of polymers in sCO2, and that certain polymer microstructures are more susceptible to degradation over others. In FY 2020, the focus was to understand the effect of sCO2 on polymers at low (10 MPa) and high pressures (40 MPa) under isothermal conditions (100°C). It was clear that the same selectivity was observed in these experiments wherein certain polymeric functionalities showed more propensity to failure over others. Fast diffusion, supported by higher pressures and long exposure times (1000 hours) at the test temperature, caused increased damage in sCO2 environments to even the most robust polymers. We also looked at polymers under compression in sCO2 at 100°C and 20 MPa pressure to imitate actual sealing performance required of these materials in sCO2 systems. Compression worsened the physical damage that resulted from chemical attack of the polymers under these test conditions. In FY 2021, the effect of cycling temperature (from 50°C to 150°C to 50°C) for polymers under a steady sCO2 pressure of 20 MPa was studied. The aim was to understand the influence of cycling temperatures of sCO2 for typical polymers under isobaric (20 MPa) conditions. Thermoplastic polymers (Nylon, and PTFE) and elastomers (EPDM, Viton, Buna N, Neoprene, FF202, and HNBR) were subjected to 20 MPa sCO2 pressure for 50 cycles and 100 cycles in separate experiments. Samples were extracted for ex-situ characterization at 50 cycles and upon the completion of 100 cycles. Each cycle constituted of 175 minutes of cycling from 50°C to 150°C. The polymer samples were examined for physical and chemical changes by Dynamic Mechanical and Thermal Analysis (DMTA), Fourier Transform Infrared (FTIR) spectroscopy, and compression set. Density and mass changes immediately after removal from test were measured for degree of swell comparisons. Optical microscopy techniques and micro computer tomography (micro CT) images were collected on select specimens. Evaluations conducted showed that exposures to super-critical CO2 environments resulted in combinations of physical and/or chemical changes. For each polymer, the dominance of cycling temperatures under sCO2 pressures, were evaluated. Attempts were made to qualitatively link the permanent sCO2 effects to polymer micro- structure, free volume, backbone substitutions, presence of polar groups, and degree of crystallinity differences. This study has established that soft polymeric materials are conducive to failure in sCO2 through mechanisms of failure that are dependent on polymer microstructure and chemistry. Polar pendant groups, large atom substitutions on the backbone are some of the factors that are influential structural factors.

Isocontours of Q-criterion with velocity visualized in the wake for two NREL 5-MW turbines operating under uniform-inflow wind speed of 8 m/s. Simulation performed with the hybrid-Nalu-Wind/AMR-Wind solver.

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, capturing the thin boundary layers, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources.

Abstract not provided.

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

We present an efficient self-consistent implementation of the Non-Equilibrium Green Function formalism, based on the Contact Block Reduction method for fast numerical efficiency, and the predictor-corrector approach, together with the Anderson mixing scheme, for the self-consistent solution of the Poisson and Schrödinger equations. Then, we apply this quantum transport framework to investigate 2D horizontal Si:P δ-layer Tunnel Junctions. We find that the potential barrier height varies with the tunnel gap width and the applied bias and that the sign of a single charge impurity in the tunnel gap plays an important role in the electrical current.

The atomic precision advanced manufacturing (APAM) enabled vertical tunneling field effect transistor (TFET) presents a new opportunity in microelectronics thanks to the use of ultra-high doping and atomically abrupt doping profiles. We present modeling and assessment of the APAM TFET using TCAD Charon simulation. First, we show, through a combination of simulation and experiment, that we can achieve good control of the gated channel on top of a phosphorus layer made using APAM, an essential part of the APAM TFET. Then, we present simulation results of a preliminary APAM TFET that predict transistor-like current-voltage response despite low device performance caused by using large geometry dimensions. Future device simulations will be needed to optimize geometry and doping to guide device design for achieving superior device performance.

CO₂-neutral ammonia production with concentrated solar technology is theoretically possible based on advanced solar thermochemical looping technology. The parametric analysis points to the re-oxidation temperature and the H₃ yield as the most influential parameters in the energy balance. The cycle time and the nitride cost are the most influential parameters on the CAPEX. The techno-economics analysis shows the potential of the plant to achieve a target price <125 $\$$/tonne.

We propose to demonstrate the feasibility of a solar thermochemical looping technology to produce and store nitrogen (N₂) from air for the subsequent production of ammonia (NH₃) via an advanced two-stage process.

Solar Thermal Ammonia Production has the potential to synthesize ammonia in a green, renewable process that can greatly reduce the carbon footprint left by the conventional Haber-Bosch reaction. Co₃Mo₃N has been identified as a potential candidate for ammonia production. It is synthesized via oxide precursor synthesis followed by nitridation under 10% H₂/N₂. The synthesis method can be extended to other candidate nitrides. The Co₃Mo₃N → Co₆Mo₆N reduction is demonstrated on TGA with rapid kinetics. The formation of NH₃ is qualitatively observed, but not quantitatively determined. The material retains crystal structure, but no secondary phases are observed in XRD. Partial re-nitridation back to CMN331 of ~35% of max nitridation is observed. Reaction parameters in TGA differ from experimental conditions in the literature. Experiments at Georgia Tech better mimic re-nitridation conditions with more sensitive, quantitative analytical techniques (GC-MS). The ASU NH₃ synthesis/re-nitridation reactor is under development and will permit experiments (reduction/re-nitridation) under precisely controlled T, pH₂.

This report includes a compilation of several slide presentations: 1) Interatomic Potentials for Materials Science and Beyond–Advances in Machine Learned Spectral Neighborhood Analysis Potentials (Wood); 2) Agile Materials Science and Advanced Manufacturing through AI/ML (de Oca Zapiain); 3) Machine Learning for DFT Calculations (Rajamanickam); 4) Structure-preserving ML discovery of a quantum-to-continuum codesign stack (Trask); and 5) IBM Overview of Accelerated Discovery Technology (Pitera)

Abstract not provided.

Laser beam directed energy deposition has become an increasingly popular advanced manufacturing technique for materials discovery as a result of the in situ alloying capability. In this study, we leverage an additive manufacturing enabled high throughput materials discovery approach to explore the composition space of a graded Wx(CoCrFeMnNi)100−x sample spanning 0 ≤ x ≤ 21 at%. In addition to microstructural and mechanical characterization, synchrotron high speed x-ray computer aided tomography was conducted on a W20(CoCrFeMnNi)80 composition to visualize melting dynamics, powder-laser interactions, and remelting effects of previously consolidated material. Results reveal the formation of the Fe7W6 intermetallic phase at W concentrations> 6 at%, despite the high configurational entropy. Unincorporated W particles also occurred at W concentrations> 10 at% accompanied by a dissolution band of Fe7W6 at the W/matrix interface and hardness values greater than 400 HV. The primary strengthening mechanism is attributed to the reinforcement of the Fe7W6 and W phases as a metal matrix composite. The in situ high speed x-ray imaging during remelting showed that an additional laser pass did not promote further mixing of the Fe7W6 or W phases suggesting that, despite the dissolution of the W into the Fe7W6 phase being thermodynamically favored, it is kinetically limited by the thickness/diffusivity of the intermetallic phase, and the rapid solidification of the laser-based process.

Simulations of several of the end-irradiated cylindrical photoelectron driven cavity experiments (also known as B-Dot cavities) that were fielded during the July 1 through 2, 2020 shot series at the National Ignition Facility are presented in this report with comparisons to experimental measurements. All cavity B-Dots fielded on the second, third, fourth, fifth and seventh shots were simulated using coupled Integrated Tiger Series (ITS) Monte Carlo transport codes and the Electromagnetic Plasmas in Realistic Environments (EMPIRE) electromagnetic particle-in-cell code.

This progress report describes work performed during FY21 at Sandia National Laboratories (SNL) to assess the localized corrosion performance of canister materials used in the interim storage of spent nuclear fuel (SNF). Of particular concern is stress corrosion cracking (SCC), by which a through-wall crack could potentially form in a canister outer wall over time intervals that are shorter than possible dry storage times. In FY21, modeling and experimental work was performed that further defined our understanding of the potential chemical and physical environment present on canister surfaces at both marine and inland sites. Research also evaluated the relationship between the environment and the rate, extent, and morphology of corrosion, as well as the corrosion processes that occur. Finally, crack growth rate testing under relevant environmental conditions was initiated.

A new method for computing anharmonic thermophysical properties for adsorbates on metal surfaces is presented. Classical Monte Carlo phase space integration is performed to calculate the partition function for the motion of a hydrogen atom on Cu(111). A minima-preserving neural network potential energy surface is used within the integration routine. Two different sampling schema for generating the training data are presented, and two different density functionals are used. The results are benchmarked against direct state counting results by using discrete variable representation. The phase space integration results are in excellent quantitative agreement with the benchmark results. Additionally, both the discrete variable representation and the phase space integration results confirm that the motion of H on Cu(111) is highly anharmonic. The results were applied to calculate the free energy of dissociative adsorption of H2 and the resulting Langmuir isotherms at 400, 800, and 1200 K in a partial pressure range of 0-1 bar. It shows that the anharmonic effects lead to significantly higher predicted surface site fractions of hydrogen.

Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials.

Understanding liquid hydrogen tank fluid dynamics is key for modeling liquid hydrogen systems. The tank is the source for nearly all liquid hydrogen systems. Accurate flow modeling out of the tank is needed to predict flows through downstream components. Tank contains liquid and gas that may not be at equilibrium. Questions to be addressed are: Does heat and mass transfer between liquid and vapor affect the flow rate? Is boiling an important consideration? For what conditions is a pressure relief valve (PRV) sufficient to relieve pressure and when is the burst disc needed?

This project explored chemical vapor deposition as a technique to synthesis cubic boron nitride (c-BN) for electronics and coating applications. Current c-BN synthesis techniques are greatly limiting due to requiring high pressure or non-equilibrium energy sources, such as ion bombardment.

For many decades, lithium metal batteries (LMBs) have been studied for their high energy density, though they suffer from high reactivity, which safety concerns such as explosions and fires. These events can occur as a result of degradation due to redox reactions and lithium morphology that evolve during cycling. Mostly, the failure is caused by the electrolyte degradation leading to the creation of a solid electrolyte interphase (SEI), which tends to induce electron leakage, lithium dendrite growth, and capacity decay. SEI formation is practically inevitable. This work investigated the minimization of degradation events by modifying different battery configurations. Modifications were made by exchanging electrolytes, electrode surfaces, and even annexing innovative components. Our goal is to achieve a configuration where Li-ion transfer is facilitated, and electron transfer is limited which would enable a longer lithium metal battery life cycle. When performing these modifications and testing their electrochemical performance, a current reduction was observed when the electrodes were spontaneously coated with preformed SEI. Herein several classes of artificial SEI layers are explored for their ability to form passivating layers through use of a redox active molecule.

Stainless steel TPBAR components undergo neutron radiation-induced segregation and dislocation loop formation. Comparison experiments with ion beams accelerate the damage, and visualize the damage process with in-situ microscopy. In-situ Au irradiation causes defect formation, but no elemental segregation.

Brittle materials, such as cement, compose major portions of built infrastructure and are vulnerable to degradation and fracture from chemo-mechanical effects. Currently, methods of modeling infrastructure do not account for the presence of a reactive environment, such as water, on the acceleration of failure. Here, we have developed methodologies and models of concrete and cement fracture that account for varying material properties, such as strength, shrinkage, and fracture toughness due to degradation or hydration. The models have been incorporated into peridynamics, non-local continuum mechanics methodology, that can model intersecting and branching brittle fracture that occurs in multicomponent brittle materials, such as concrete. Through development of new peridynamic capabilities, decalcification of cement and differential shrinkage in clay-cement composites have been evaluated, along with exemplar problems in nuclear waste cannisters and wellbores. We have developed methods to simulate multiphase phenomena in cement and cement-composite materials for energy and infrastructure applications.

Compliance with future ultra-low nitrogen oxide regulations with diesel engines requires the fastest possible heating of the exhaust aftertreatment system to its proper operating temperature upon cold starting. Late post injections are commonly integrated into catalyst-heating operating strategies. This experimental study provides insight into the complex interactions between the injection-strategy calibration and the tradeoffs between exhaust heat and pollutant emissions. Experiments are performed with certification diesel fuel and blends of diesel fuel with butylal and hexyl hexanoate. Further analyses of experimental data provide insight into fuel reactivity and oxygen content as potential enablers for improved catalyst-heating operation. A statistical design-of-experiments approach is developed to investigate a wide range of injection strategy calibrations at three different intake dilution levels. Thermodynamic and exhaust emissions measurements are taken using a new medium-duty, single-cylinder research engine. Analysis of the results provides insight into the effects of exhaust gas recirculation, oxygenated fuel blends, and fuel reactivity on exhaust heat and pollutant emissions. Late-cycle heat release is an important factor in determining exhaust temperatures. Intake dilution and fuel properties certainly affect late-cycle heat release, but the methods applied in this work are not sufficient to reproduce or explain the mechanisms by which improved fuel cetane rating promotes operation with hotter exhaust and lower pollutant emissions.

Two-step solar thermochemical cycles based on reversible reactions of SrFeO3−δand (Ba,La)0.15Sr0.85FeO3−δperovskites were considered for air separation. The cycle steps encompass (1) the thermal reduction of SrFeO3−δor (Ba,La)0.15Sr0.85FeO3−δperovskites driven by concentrated solar irradiation and (2) oxidation in air to remove O2and produce N2. Rate limiting mechanisms were examined for both reactions using a combination of isothermal and non-isothermal thermogravimetry for temperature-swings between 673 and 1373 K, heating rates of 10, 20, and 50 K min−1, and O2pressure-swings between 20% O2/Ar and 100% Ar at atmospheric pressure. Evolved O2and associated lag due to transport behavior were measured with gas chromatography and used with measured sample temperatures to predict equilibrium compositions from a compound energy formalism thermodynamic model. Measured and predicted chemical equilibrium changes in deviation from stoichiometry were compared. Rapid chemical kinetics were observed as the samples equilibrated rapidly for all conditions, indicative that heat and mass transfer were the rate limiting mechanisms. The effects of bulk diffusion (or gas diffusion through the bed or pellet) were examined using pelletized and loose powdered samples and determined to have no discernable impact.

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 (SNL/TTR) in Nevada and Sandia National Laboratories, Kaua‘i Test Facility (SNL/KTF) in Hawai‘i. Activities at SNL/TTR are conducted in support of U.S. Department of Energy weapons programs and have operated at the site since 1957. SNL/KTF 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 SNL/TTR and SNL/KTF during calendar year 2020. Environmental topics include 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.

Technologies based on water adsorption such as water harvesting from air have tremendous potential in mitigating important global crises such as water scarcity. An important challenge to the deployment of such technologies is finding optimal adsorbent materials. Given the large materials space of available adsorbents, large-scale computational screening can be extremely helpful for this task. This work explores the methods and details associated with such screening procedures and recommends best practices. We also shed light on the limitations of traditionally used and inexpensive to compute prescreening approaches involving geometric and energetic features to predict water adsorption behavior of porous materials. Such approaches can provide general trends to predict adsorption behavior but may lead to the overlook of potentially important structures due to the complex nature of water adsorption. Finally, this study offers insights for future water adsorption simulations to facilitate the development of optimal water adsorbents.

Ultradoping introduces unprecedented dopant levels into Si, which transforms its electronic behavior and enables its use as a next-generation electronic material. Commercialization of ultradoping is currently limited by gas-phase ultra-high vacuum requirements. Solvothermal chemistry is amenable to scale-up. However, an integral part of ultradoping is a direct chemical bond between dopants and Si, and solvothermal dopant-Si surface reactions are not well-developed. This work provides the first quantified demonstration of achieving ultradoping concentrations of boron (∼1e14 cm2) by using a solvothermal process. Surface characterizations indicate the catalyst cross-reacted, which led to multiple surface products and caused ambiguity in experimental confirmation of direct surface attachment. Density functional theory computations elucidate that the reaction results in direct B−Si surface bonds. This proof-of-principle work lays groundwork for emerging solvothermal ultradoping processes.

This Analysis Report (AR) documents the determination of pH correction factors for the observed pH readings. The correction factor converts the observed pH reading recorded from the brines used in geochemical studies in support of the Waste Isolation Pilot Plant (WIPP) to a corrected pH value. The data analysis in this AR falls under AP-157 Rev. 1 Analysis Plan for Determination of pH Correction Factors in Brines (Kirkes et al, 2021). Measurement of pH in some solutions can be challenging due to numerous factors such as high ionic strength, elevated or lowered temperature, complex matrix composition, etc. (Knauss et al., 1990; and Rai et al., 1995). The measured pH can be corrected by applying the correction factor, empirically obtained from a specific test solution.

We provide further details for using Lim, et al.'s marked multidimensional Hawkes processes with dissimilar decays. We first describe what makes these different from other Hawkes processes, then describe each model hyperparameter and how to initialize it informed by the input data and any prior biases. We derived tighter bounds than Lim, et al. for faster convergence of rejection sampling. The resulting hyperparameters and bounds have been helpful against both synthetic and real-world datasets.

The coupling of inter- and intramolecular vibrations plays a critical role in initiating chemistry during the shock-to-detonation transition in energetic materials. Herein, we report on the subpicosecond to subnanosecond vibrational energy transfer (VET) dynamics of the solid energetic material 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) by using broadband, ultrafast infrared transient absorption spectroscopy. Experiments reveal VET occurring on three distinct time scales: subpicosecond, 5 ps, and 200 ps. The ultrafast appearance of signal at all probed modes in the mid-infrared suggests strong anharmonic coupling of all vibrations in the solid, whereas the long-lived evolution demonstrates that VET is incomplete, and thus thermal equilibrium is not attained, even on the 100 ps time scale. Density functional theory and classical molecular dynamics simulations provide valuable insights into the experimental observations, revealing compression-insensitive time scales for the initial VET dynamics of high-frequency vibrations and drastically extended relaxation times for low-frequency phonon modes under lattice compression. Mode selectivity of the longest dynamics suggests coupling of the N-N and axial NO2stretching modes with the long-lived, excited phonon bath.

Abstract not provided.

This memo’s objective is to report a calibration of the J2 plasticity model with the Wilkins ductile failure criterion for 17-4 PH H1150 stainless steel under slow loading at room temperature. The calibration of the hardening function was based on uniaxial tension tests, while that of the failure model included data from tension tests on notched specimens, a butterfly specimen shear test, and a set of interrupted compression tests on shear hat specimens. The procedure was that described in, minus the rate and temperature dependence.

Complex organic-inorganic interfaces are important for device and sensing applications. Charge transfer doping is prevalent in such applications and can affect the interfacial energy level alignments (ELA), which are determined by many-body interactions. We develop an approximateab initiomany-body GW approach that can capture many-body interactions due to interfacial charge transfer. The approach uses significantly less resources than a regular GW calculation but gives excellent agreement with benchmark GW calculations on an F4TCNQ/graphene interface. We find that many-body interactions due to charge transfer screening result in gate-tunable F4TCNQ HOMO-LUMO gaps. We further predict the ELA of a large system of experimental interest—4,4′-bis(dimethylamino)bipyridine (DMAP-OED) on monolayer MoS2, where charge transfer screening results in an ∼1 eV reduction of the molecular HOMO-LUMO gap. Comparison with a two-dimensional electron gas model reveals the importance of explicitly considering the intraband transitions in determining the charge transfer screening in organic-inorganic interface systems.

We propose a domain decomposition method for the efficient simulation of nonlocal problems. Our approach is based on a multi-domain formulation of a nonlocal diffusion problem where the subdomains share “nonlocal” interfaces of the size of the nonlocal horizon. This system of nonlocal equations is first rewritten in terms of minimization of a nonlocal energy, then discretized with a meshfree approximation and finally solved via a Lagrange multiplier approach in a way that resembles the finite element tearing and interconnect method. Specifically, we propose a distributed projected gradient algorithm for the solution of the Lagrange multiplier system, whose unknowns determine the nonlocal interface conditions between subdomains. Several two-dimensional numerical tests on problems as large as 191 million unknowns illustrate the strong and the weak scalability of our algorithm, which outperforms the standard approach to the distributed numerical solution of the problem. Finally, this work is the first rigorous numerical study in a two-dimensional multi-domain setting for nonlocal operators with finite horizon and, as such, it is a fundamental step towards increasing the use of nonlocal models in large scale simulations.

Denoising contaminated seismic signals for later processing is a fundamental problem in seismic signals analysis. Neural network approaches have shown success denoising local signals when trained on short-time Fourier transform spectrograms. One challenge of this approach is the onerous process of hand-labeling event signals for training. By leveraging the SCALODEEP seismic event detector, we develop an automated set of techniques for labeling event data. Despite region specific challenges, training the neural network denoiser on machine curated events shows comparable performance to the neural network trained on hand curated events. We showcase our technique with two experiments, one using Utah regional data and one using regional data from the Korean peninsula.

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

Time-resolved spectroscopies using high-energy photons in the vacuum ultraviolet (VUV) to the X-ray region of the electromagnetic spectrum, have proven to be powerful probes of chemical dynamics. These high-energy photons can access valence and core orbitals of molecules and materials, providing key information on molecular and electronic structure and their time evolution. This report details the development of table-top sources of extreme ultraviolet (XUV) and VUV pulses at Sandia National Laboratories for use in studies of gas phase chemical dynamics. Femtosecond duration XUV pulses are produced using laser-driven high harmonic generation and their detected range span ~40-140 eV photon energies. These pulses are used in conjunction with ultraviolet pulses in a pump-probe scheme to study excited state dynamics of gas phase molecules. VUV pulses at 7.75 eV are generated using a four-wave-mixing scheme driven by 800 nm and 266 nm pulses in an argon-filled hollow-core fiber.

This is a simple model designed to run fast but still maintain the key physics and feedback mechanisms of a heat pipe. First, the capillary pressure is a function of the liquid working fluid volume fraction. Second, the boiling and condensation are based on the saturation temperature that is based on the heat pipe pressure. When the pressure goes up, the saturation temperature goes up and the vapor rains on the wick. When the pressure goes down, the saturation temperature goes down and the liquid in the entire wick boils. This is how the heat pipe adjusts to stay robust under different temperatures and heat fluxes.

Thermoelectric power plants often depend on multipurpose reservoirs to supply cooling water. Although reservoirs buffer natural hydrologic variability, severe droughts can deplete storage below critical thresholds, or to levels at which the effluent water temperature exceeds the environmental compliance requirement for cooling. This study explores the effects of projected climate change and drought on water storage at 30 major reservoirs in Texas. These reservoirs collectively provide cooling water for about two thirds of thermoelectric power capacity in the Electric Reliability Council of Texas (ERCOT) power grid. Multi-ensemble runoff projections generated from eleven downscaled hydroclimate simulations are mapped to key watersheds to create spatially correlated multi-reservoir inflow sequences. These data are used to drive reservoir storage simulations, which are linked to a metric of “capacity-at-risk” using critical reservoir thresholds. We find that projected impacts of climate change are mixed, with results indicating an increase in the occurrence of thermal disruption under only half of climate models. A critical threshold of 30% storage volume—applied to all reservoirs—results in disruption to about one fifth of ERCOT thermal generation during the most severe projected droughts. The study highlights an important role for detailed reservoir behavior simulations for capturing the effects of drought and climate change on thermoelectric plant performance.

Polymerization-induced phase separation enables fine control over thermoset network morphologies, yielding heterogeneous structures with domain sizes tunable over 1-100 nm. However, the controlled chain-growth polymerization techniques exclusively employed to regulate the morphology at these length scales are unsuitable for a majority of thermoset materials typically formed through step-growth mechanisms. By varying the composition of a binary curing agent mixture in a classic rubber-toughened epoxy thermoset, where the two curing agents are selected based on disparate compatibility with the rubber, we demonstrate facile tunability over morphology through a single compositional parameter. Indeed, this method yields morphologies spanning the nano-scale to the macro-scale, controlled by the relative reactivities and thermodynamic compatibility of the network components. We further demonstrate a profound connection between chain dynamics and microstructure in these materials, with the tunable morphology enabling exquisite variations in glass transition. In addition, previously unattainable control over tensile mechanical properties is realized, including atypical increase of elongation at failure while maintaining the modulus and ultimate strength.

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

Photon sources able to emit single or entangled photon pairs are key components in quantum information systems. Semiconductor quantum dots (QDs) are promising candidates due to their high efficiencies and ease of integration with other photonic or electronic components. State-of-the-art QDs, however, are limited to certain emission wavelengths and specific applications due to material choice constraints and their randomness in shape/size. This project is focused on developing a novel in-situ patterning technique to realize QDs with a broad emission range, shape/size control and the ability to emit single/entangled photons. Our approach has two key elements: (1) In-situ patterning via arsenic-induced nanovoid etching on antimonide surfaces and (2) In-filling of nanovoids to form QDs. By closely controlling the experimental conditions, it is shown that this technique can be used to realize III-V QDs in As₂- etched nanovoids on a GaSb surface. The exposure to As₂ in terms of substrate temperature, time and flux is found to have a significant impact on the process variables such as nanovoid depth, QD dimensions etc. An in-depth analysis of the etch mechanism reveals that by controlling the As₂ exposure, uniform 3-dimensional nanostructures with varying areal densities can be obtained without an in-filling step. Preliminary optical characterization of these nanostructures shows that these QDs may be relevant for realizing emitters in the telecom wavelength range.

First-of-their kind datasets from a high-speed X-ray tomography system were collected, and a novel numerical effort utilizing temporal information to reduce measurement uncertainty was shown. The experimental campaign used three high-speed X-ray imaging systems to collect data at 100 kHz of a scene containing high-velocity objects. The scene was a group of known objects propelled by a 12-gauge shotgun shell reaching speeds of hundreds of meters per second. These data represent a known volume where the individual components are known, with experimental uncertainties that can be used for reconstruction algorithm validation. The numerical effort used synthetic volumes in MATLAB to produce projections along known lines of sight to perform tomographic reconstructions. These projections and reconstructions were performed on a single object at two orientations, representing two timesteps, to increase the reconstruction accuracy.

The How To Manual supplements the User’s Manual and the Theory Manual. The goal of the How To Manual is to reduce learning time for complex end to end analyses. These documents are intended to be used together. See the User’s Manual for a complete list of the options for a solution case. All the examples are part of the Sierra/SD test suite. Each runs as is. The organization is similar to the other documents: How to run, Commands, Solution cases, Materials, Elements, Boundary conditions, and then Contact. The table of contents and index are indispensable. The Geometric Rigid Body Modes section is shared with the Users Manual.

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

Designing next generation thin films, tailor-made for specific applications, relies on the availability of robust processing-structure-property relationships. Traditional structure zone diagrams are limited to low-dimensional mappings, with machine-learning methods only recently attempting to relate multiple processing parameters to the final microstructure. Despite this progress, structure-processing relationships are unknown for processing conditions that vary during thin-film deposition, limiting the range of microstructures and properties achievable. In this project, we employed a phase-field computational model combined with a genetic algorithm (GA) to identify and design time-dependent processing protocols that achieve tailor-made microstructures. We simulate the physical vapor deposition of a binary-alloy thin film by employing a phase-field model, where deposition rates and diffusivities are controlled via the genetic algorithm. Our GA-guided protocols achieve targeted microstructures with lateral and vertical concentration modulations, as well as more complex, hierarchical microstructures previously not described in simple structure zone diagrams. Our algorithm provides insight to experimentalists looking for additional avenues to design novel thin-film microstructures.

This is an addendum to the Sierra/SolidMechanics 5.2 User's Guide that documents additional capabilities available only in alternate versions of the Sierra/SolidMechanics (Sierra/SM) code. These alternate versions are enhanced to provide capabilities that are regulated under the U.S. Department of State's International Traffic in Arms Regulations (ITAR) export control rules. The ITAR regulated codes are only distributed to entities that comply with the ITAR export control requirements. The ITAR enhancements to Sierra/SM include material models with an energy-dependent pressure response (appropriate for very large deformations and strain rates) and capabilities for blast modeling. This document is an addendum only; the standard Sierra/SolidMechanics 5.2 User's Guide should be referenced for most general descriptions of code capability and use.

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

Computational simulation is increasingly relied upon for high-consequence engineering decisions, and a foundational element to solid mechanics simulations is a credible material model. Our ultimate vision is to interlace material characterization and model calibration in a real-time feedback loop, where the current model calibration results will drive the experiment to load regimes that add the most useful information to reduce parameter uncertainty. The current work investigated one key step to this Interlaced Characterization and Calibration (ICC) paradigm, using a finite load-path tree to incorporate history/path dependency of nonlinear material models into a network of surrogate models that replace computationally-expensive finite-element analyses. Our reference simulation was an elastoplastic material point subject to biaxial deformation with a Hill anisotropic yield criterion. Training data was generated using either a space-filling or adaptive sampling method, and surrogates were built using either Gaussian process or polynomial chaos expansion methods. Surrogate error was evaluated to be on the order of 10^⁻5 and 10^⁻3 percent for the space-filling and adaptive sampling training data, respectively. Direct Bayesian inference was performed with the surrogate network and with the reference material point simulator, and results agreed to within 3 significant figures for the mean parameter values, with a reduction in computational cost over 5 orders of magnitude. These results bought down risk regarding the surrogate network and facilitated a successful FY22-24 full LDRD proposal to research and develop the complete ICC paradigm.

To date, terahertz quantum-cascade vertical-external-cavity surface-emitting lasers (QC-VECSELs) have tended to oscillate in only one or two lasing modes at a time. This is due to the fact that the interaction between all of the longitudinal external cavity modes and the QC gain material is mediated through a single metasurface resonance, whose spatial overlap changes little with frequency; this suppresses spatial-hole-burning induced multi-mode operation. In this Letter, a VECSEL external cavity is demonstrated using an output coupler based upon a high-resistivity silicon etalon, which presents a periodic reflectance spectrum that is nearly matched with the external cavity mode spectrum. As the cavity length is varied, a systematic transition between a single/double-mode lasing regime and a multi-mode lasing regime is realized due to the Vernier effect. Up to nine modes lasing simultaneously with a free-spectral-range of approximately 21 GHz is demonstrated. This result provides a path toward the multi-mode operation necessary for eventual frequency comb operation.

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and highlevel nuclear waste (HLW). A high priority for SFWST disposal R&D is disposal system modeling (DOE 2012, Table 6; Sevougian et al. 2019). The SFWST Geologic Disposal Safety Assessment (GDSA) work package is charged with developing a disposal system modeling and analysis capability for evaluating generic disposal system performance for nuclear waste in geologic media.

Thin, high-density layers of dopants in semiconductors, known as δ-layer systems, have recently attracted attention as a platform for exploration of the future quantum and classical computing when patterned in plane with atomic precision. However, there are many aspects of the conductive properties of these systems that are still unknown. Here we present an open-system quantum transport treatment to investigate the local density of electron states and the conductive properties of the δ-layer systems. A successful application of this treatment to phosphorous δ-layer in silicon both explains the origin of recently-observed shallow sub-bands and reproduces the sheet resistance values measured by different experimental groups. Further analysis reveals two main quantum-mechanical effects: 1) the existence of spatially distinct layers of free electrons with different average energies; 2) significant dependence of sheet resistance on the δ-layer thickness for a fixed sheet charge density.

Relativistic weakly collisional plasmas describe a variety of astrophysical and terrestrial plasmas, ranging from relativistic outflows from active galactic nuclei to high power microwave and magnetically insulated transmission lines. In many such systems, high fidelity kinetic models are computationally infeasible due large dynamical scales and long dynamical times. Conversely, most fluid based models such as magnetohydrodynamics (MHD) miss many relevant aspects of plasma behavior. Between these two models, two fluid methods - where the electrons and ions are evolved as separate, coupled fluids - capture many of the plasma physics of a kinetic code while remaining computational tractable for large systems.

We present a novel technique for numerically modeling relativistic magnetrons. The electrons are represented with a 5-moment relativistic fluid. Typically, the particle in cell method is used for simulated relativistic high-power microwave sources. This study considers the A6 magnetron presented by Palevsky and Bekefi [1].

C22-Gd films were deposited onto 316 stainless steel up to 2.4mm thick using three different cold spray conditions. No differences in visible coating adhesion was observed between grit-blasted and as-received 316 stainless steel substrates. All of the coatings produced had a density greater than 95% of bulk. EDS and backscattered imaging suggest that no secondary phases precipitated during coating fabrication, but potential micro-segregation of phases were likely present in the as-received material. The phase segregation was still observable in the as-deposited coatings. EDS could not resolve the differences in composition of the two phases.

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

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

A coded aperture is used to demonstrate emission spectroscopy from multiple one-dimensional measurement locations simultaneously with a single camera. The coded aperture mask has several columns of periodic apertures, each with a unique spatial frequency. Light transmitted through all mask columns is detected through an imaging spectrometer. Dispersed light from the various mask columns overlaps on the spectrometer camera but is separated using Fourier-domain filtering using the known spatial frequencies of the mask. As the coded aperture is placed at an image plane, each Fourier-filtered spectrogram comes from a unique one-dimensional measurement location. This technique represents a significant increase in the amount of spatially and spectrally resolved emission data available using a single emission spectrometer and camera at the expense of some spatial resolution due to the Fourier filtering. This instrument is particularly useful for studying transient, non-repeating events. Megahertz-rate emission spectroscopy from five one-dimensional measurement locations is demonstrated with explosive fireballs using a single camera. Optical design parameters and instrument performance characteristics are discussed.

We present a new geodesic-based method for geometry optimization in a basis set of redundant internal coordinates. Our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate manifold, which dramatically reduces the number of steps required to converge to a minimum. Our method can be implemented in any existing optimization code, requiring only implementation of derivatives of the Wilson B-matrix and the ability to numerically solve an ordinary differential equation.

The passivation of polycrystalline nickel surfaces against hydrogen uptake by oxygen is investigated experimentally with low energy ion scattering (LEIS), direct recoil spectroscopy (DRS), and thermal desorption spectroscopy (TDS). These techniques are highly sensitive to surface hydrogen, allowing the change in hydrogen adsorption in response to varying amounts of oxygen exposure to be measured. The chemical composition of a nickel surface during a mixed oxygen and hydrogen exposure was characterized with LEIS and DRS, while the uptake and activation energies of hydrogen on a nickel surface with preadsorbed oxygen were quantified with TDS. By and large, these measurements of how the oxygen and hydrogen surface coverage varied in response to oxygen exposure were found to be consistent with predictions of a simple site-blocking model. This finding suggests that, despite the complexities that arise due to polycrystallinity, the oxygen-induced passivation of a polycrystalline nickel surface against hydrogen uptake can be approximated by a simple site-blocking model.

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

Electrochemical models at different scales and varying levels of complexity have been used in the literature to study the evolution of the anode surface in lithium metal batteries. This includes continuum, mesoscale (phase-field approaches), and multiscale models. In this paper, using a motivating example of a moving boundary model in one dimension, we show how battery models need proper formulation for mass conservation, especially when simulated over multiple charge and discharge cycles. The article concludes with some thoughts on mass conservation and proper formulation for multiscale models.

This report summarizes the current actives in FY21 related to the effort by Sandia National Laboratories to identify and test coating materials for the prevention, mitigation, and repair of spent nuclear fuel dry storage canisters against potential chloride-induced stress corrosion cracking. This work follows up on the details provided in Sandia National Laboratories FY20 report on the same topic, which provided a detailed description of the specific coating properties desired for application and implementation on spent nuclear fuel canisters, as well as provided detail into several different coatings and their applicability to coat spent nuclear fuel canisters. In FY21, Sandia National Laboratories has engaged with private industry to create a Memorandum of Understanding and established a collaborative R&D program building off the analytical and laboratory capabilities at Sandia National Laboratories and the material design and synthesis capabilities of private industry. The resulting Memorandum of Understanding included four companies to date (Oxford Performance Materials, White Horse R&D, Luna Innovations, and Flora Coating) proposing six different coating technologies (polyetherketoneketone, modified polyimide/polyurea, modified phenolic resin, silane-based polyurethane hybrid with and without a Znrich primer, and a quasi-ceramic sol-gel polyurethane hybrid) to be tested, evaluated, and optimized for their potential use for this application. This report provides a detailed description of each of the coating systems proposed by the participating industry partners. It also provides a description of the planned experimental actives to be performed by Sandia National Laboratories including physical tests, electrochemical tests, and characterization methods. These analyses will be used to identify specific ways to further improve coating technologies toward their application and implementation on spent nuclear fuel canisters. In FY21, Sandia National Laboratories began baseline testing of the base metal material in according with activities of the Memorandum of Understanding. In FY22, Sandia National Laboratories will receive coated coupons from each of the participating industry partners and begin characterization, physical, and electrochemical testing following the test plan described herein.

The finite element method is a scheme to discretize the infinite number of degrees of freedom in continuum-level problems down to a finite number of degrees of freedom. This discretization is done in conjunction with methods that also reduce the field differential equations to sets of algebraic ones that can be solved by arithmetical operations. Therefore, solutions attained by finite element models are approximations to the exact solutions of the field equations.

An ordinary state-based peridynamic material model is proposed for single sheet graphene. The model is calibrated using coarse grained molecular dynamics simulations. The coarse graining method allows the dependence of bond force on bond length to be determined, including the horizon. The peridynamic model allows the horizon to be rescaled, providing a multiscale capability and allowing for substantial reductions in computational cost compared with molecular dynamics. The calibrated peridynamic model is compared to experimental data on the deflection and perforation of a graphene monolayer by an atomic force microscope probe.

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix C(x,y) of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy=0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, ρ(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. We repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. We show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

A new generation of concentrating solar power (CSP) technologies is under development to provide dispatchable renewable power generation and reduce the levelized cost of electricity (LCOE) to 6 cents/kWh by leveraging heat transfer fluids (HTFs) capable of operation at higher temperatures and coupling with higher efficiency power conversion cycles. The U.S. Department of Energy (DOE) has funded three pathways for Generation 3 CSP (Gen3CSP) technology development to leverage solid, liquid, and gaseous HTFs to transfer heat to a supercritical carbon dioxide (sCO2) Brayton cycle. This paper presents the design and off-design capabilities of a 1 MWth sCO2 test system that can provide sCO2 coolant to the primary heat exchangers (PHX) coupling the high-Temperature HTFs to the sCO2 working fluid of the power cycle. This system will demonstrate design, performance, lifetime, and operability at a scale relevant to commercial CSP. A dense-phase high-pressure canned motor pump is used to supply up to 5.3 kg/s of sCO2 flow to the primary heat exchanger at pressures up to 250 bar and temperatures up to 715 °C with ambient air as the ultimate heat sink. Key component requirements for this system are presented in this paper.

The propagation of a wave pulse due to low-speed impact on a one-dimensional, heterogeneous bar is studied. Due to the dispersive character of the medium, the pulse attenuates as it propagates. This attenuation is studied over propagation distances that are much longer than the size of the microstructure. A homogenized peridynamic material model can be calibrated to reproduce the attenuation and spreading of the wave. The calibration consists of matching the dispersion curve for the heterogeneous material near the limit of long wavelengths. It is demonstrated that the peridynamic method reproduces the attenuation of wave pulses predicted by an exact microstructural model over large propagation distances.

Virtual prototyping in engineering design rely on modern numerical models of contacting structures with accurate resolution of interface mechanics, which strongly affect the system-level stiffness and energy dissipation due to frictional losses. High-fidelity modeling within the localized interfaces is required to resolve local quantities of interest that may drive design decisions. The high-resolution finite element meshes necessary to resolve inter-component stresses tend to be computationally expensive, particularly when the analyst is interested in response time histories. The Hurty/Craig-Bampton (HCB) transformation is a widely used method in structural dynamics for reducing the interior portion of a finite element model while having the ability to retain all nonlinear contact degrees of freedom (DOF) in physical coordinates. These models may still require many DOF to adequately resolve the kinematics of the interface, leading to inadequate reduction and computational savings. This study proposes a novel interface reduction method to overcome these challenges by means of system-level characteristic constraint (SCC) modes and properly orthogonal interface modal derivatives (POIMDs) for transient dynamic analyses. Both SCC modes and POIMDs are computed using the reduced HCB mass and stiffness matrices, which can be directly computed from many commercial finite element analysis software. Comparison of time history responses to an impulse-type load in a mechanical beam assembly indicate that the interface-reduced model correlates well with the HCB truth model. Localized features like slip and contact area are well-represented in the time domain when the beam assembly is loaded with a broadband excitation. The proposed method also yields reduced-order models with greater critical timestep lengths for explicit integration schemes.

Hypertriglyceridemia (HTG) is considered within the top 5 etiologies in acute pancreatitis (AP), but the association of serum triglyceride (TG) levels with the clinical course of AP remains controversial. This study aims to examine the effect of TG levels on severity of AP. Patients were enrolled prospectively through APPRENTICE. High TG levels were defined based on the Endocrine Society Clinical Practice Guidelines. HTG was categorized as mild (serum TG levels 150–199 mg/dL), moderate (200–999 mg/dL), severe (1,000–1,999 mg/dL), and very severe (≥2,000 mg/dL). Severity of AP was based on the revised Atlanta classification criteria. Additionally, early TG levels were measured in 764 subjects and found elevated in 342 (120 with mild; 176, moderate; and 46, severe/very severe HTG). Patients with increased TG levels were younger (age ≥60, 16.7 vs. 30.3%), more likely to be male (66.1 vs. 51.2%), with more frequent alcohol use (62.8 vs. 50.7%), and diabetes mellitus (30.2 vs. 12.3%; all p ≤ 0.005). Severe AP (24.9 vs. 10.0%), ICU admission (32.5 vs. 19.7%), and mortality (5.3 vs. 1.7%; all p ≤ 0.005) were more frequently seen in patients with elevated TG levels. Based on multivariable analysis, elevated TG levels were independently associated with severe AP (p < 0.05). This large multicenter study confirms that elevated TG levels are associated with severe disease regardless of AP etiology.

Barium titanate (BTO) is a ferroelectric perovskite material used in energy storage applications because of its high dielectric constant. A previous study showed that the dielectric constant for BTO nanoparticles drastically increases to over 15,000 at a particle size of 70 nm. This result is highly contested, but its implications to energy storage motivated our investigation into the dielectric constants of BTO nanoparticles that are incorporated into a polymer matrix. We developed a novel method of using image processing techniques on transmission electron microscope images of BTO-polymer nanocomposites. Data on the positions, shapes, sizes, and orientations of BTO nanoparticles were used to build more realistic computational models that simulate the dielectric behavior of the nanocomposites. Here, we investigate the relationship between regions of enhanced electric field and the composite dielectric constant.

Ultra-low voltage drop tunnel junctions (TJs) were utilized to enable multi-active region blue light emitting diodes (LEDs) with up to three active regions in a single device. The multi-active region blue LEDs were grown monolithically by metal-organic chemical vapor deposition (MOCVD) without growth interruption. This is the first demonstration of a MOCVD grown triple-junction LED. Optimized TJ design enabled near-ideal voltage and EQE scaling close to the number of junctions. This work demonstrates that with proper TJ design, improvements in wall-plug efficiency at high output power operation are possible by cascading multiple III-nitride based LEDs.

Upon extraction/injection of a large quantity of gas from/into a subsurface system in shale gas production or carbon sequestration, the gas pressure varies remarkably, which may significantly change the wettability of porous media involved. Mechanistic understanding of such changes is critical for designing and optimizing a related subsurface engineering process. Using molecular dynamics simulations, we have calculated the contact angle of a water droplet on various solid surfaces (kerogen, pyrophyllite, calcite, gibbsite, and montmorillonite) as a function of CO2 or CH4 gas pressure up to 200 atm at a temperature of 300 K. The calculation reveals a complex behavior of surface wettability alteration by gas pressure variation depending on surface chemistry and structure, and molecular interactions of fluid molecules with surfaces. As the CO2 gas pressure increases, a partially hydrophilic kerogen surface becomes highly hydrophobic, while a calcite surface becomes more hydrophilic. Considering kerogen and calcite being the major components of a shale formation, we postulate that the wettability alteration of a solid surface induced by a gas pressure change may play an important role in fluid flows in shale gas production and geological carbon sequestration.

The quantum k-Local Hamiltonian problem is a natural generalization of classical constraint satisfaction problems (k-CSP) and is complete for QMA, a quantum analog of NP. Although the complexity of k-Local Hamiltonian problems has been well studied, only a handful of approximation results are known. For Max 2-Local Hamiltonian where each term is a rank 3 projector, a natural quantum generalization of classical Max 2-SAT, the best known approximation algorithm was the trivial random assignment, yielding a 0.75-approximation. We present the first approximation algorithm beating this bound, a classical polynomial-time 0.764-approximation. For strictly quadratic instances, which are maximally entangled instances, we provide a 0.801 approximation algorithm, and numerically demonstrate that our algorithm is likely a 0.821-approximation. We conjecture these are the hardest instances to approximate. We also give improved approximations for quantum generalizations of other related classical 2-CSPs. Finally, we exploit quantum connections to a generalization of the Grothendieck problem to obtain a classical constant-factor approximation for the physically relevant special case of strictly quadratic traceless 2-Local Hamiltonians on bipartite interaction graphs, where a inverse logarithmic approximation was the best previously known (for general interaction graphs). Our work employs recently developed techniques for analyzing classical approximations of CSPs and is intended to be accessible to both quantum information scientists and classical computer scientists.

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Seismic source modeling allows researchers both to simulate how a source that induces seismic waves interacts with the Earth to produce observed seismograms and, inversely, to infer what the time histories, sizes, and force distributions were for a seismic source given observed seismograms. In this report, we discuss improvements made in FY21 to our software as applies to both the forward and inverse seismic source modeling problems. For the forward portion of the problem, we have added the ability to use full 3-D nonlinear simulations by implementing 3-D time varying boundary conditions within Sandia’s linear seismic code Parelasti. Secondly, on the inverse source modeling side, we have developed software that allows us to invert seismic gradiometer-derived observations in conjunction with standard translational motion seismic data to infer properties of the source that may improve characterization in certain circumstances. First, we describe the basic theory behind each software enhancement and then demonstrate the software in action with some simple examples.

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The localized corrosion of laser surface melted (LSM) 316L stainless steel is investigated by a combination of potentiodynamic anodic polarization in 0.1 M HCl and microscopic investigation of the initiation and propagation of localized corrosion. The pitting potential of LSM 316L is significantly lower than the pitting potential of wrought 316L. The LSM microstructure is highly banded as a consequence of the high laser power density and high linear energy density. The bands are composed of zones of changing modes of solidification, cycling between very narrow regions of primary austenite solidification and very wide regions of primary ferrite solidification. Pits initiate in the outer edge of each band where the mode of solidification is primary austenite plane front solidification and primary austenite cellular solidification. The primary austenite regions have low chromium concentration (and possibly low molybdenum concentration), which explains their susceptibility to pitting corrosion. The ferrite is enriched in chromium, which explains the absence of pitting in the primary ferrite regions. The presence of the low chromium regions of primary austenite solidification explains the lower pitting resistance of LSM 316L relative to wrought 316L. The influence of banding on localized corrosion is applicable to other rapidly solidified processes such as additive manufacturing.

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We present a novel definition of variable-order fractional Laplacian on Rⁿ based on a natural generalization of the standard Riesz potential. Our definition holds for values of the fractional parameter spanning the entire open set (0, n/2). We then discuss some properties of the fractional Poisson’s equation involving this operator and we compute the corresponding Green’s function, for which we provide some instructive examples for specific problems.

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Sandia National Laboratories has performed testing on several Hyperion 5313A infrasound sensors in order to determine the length of time it takes for the sensors to thermally equilibrate under a variety of environmental conditions. The motivation for performing these tests is to aid in determining suitable procedures for station operators to follow when installing these sensors. The desired outcome is for the station operators to be able to determine more quickly and reliably whether the sensors are performing correctly at the time of installation.

This report summarizes work completed under the Laboratory Directed Research and Development (LDRD) project "Uncertainty Quantification of Geophysical Inversion Using Stochastic Differential Equations." Geophysical inversions often require computationally expensive algorithms to find even one solution, let alone propagating uncertainties through to the solution domain. The primary purpose of this project was to find more computationally efficient means to approximate solution uncertainty in geophysical inversions. We found multiple computationally efficient methods of propagating Earth model uncertainty into uncertainties in solutions of full waveform seismic moment tensor inversions. However, the optimum method of approximating the uncertainty in these seismic source solutions was to use the Karhunen-Love theorem with data misfit residuals. This method was orders of magnitude more computationally efficient than traditional Monte Carlo methods and yielded estimates of uncertainty that closely approximated those of Monte Carlo. We will summarize the various methods we evaluated for estimating uncertainty in seismic source inversions as well as work toward this goal in the realm of 3-D seismic tomographic inversion uncertainty.

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Microstructures and corresponding properties of compacted powders ultimately depend on the mechanical response of individual particles. In principle, computational simulations can predict the results of powder compaction processes, but the selection of appropriate models for both particle–particle interactions and particle deformations across all relevant length scales remain nontrivial tasks, especially in material systems lacking detailed mechanical property information. The work presented here addresses these issues by conducting uniaxial compressions in situ inside of a scanning electron microscope to characterize the mechanical response of individual micron-sized particles of a molecular crystal, hexanitrohexaazaisowurtzitane (CL-20). This experimental approach enabled the collection of quantitative force and displacement data alongside simultaneous imaging to capture morphology changes. The results reveal information about elastic deformation, yield, plastic deformation, creep, and fracture phenomena. Accordingly, this work demonstrates a generalizable approach for assessing the mechanical response of individual micron-sized molecular crystal particles and utilizing those responses in particle-level models. Graphic abstract: [Figure not available: see fulltext.].

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We present an experimental and numerical study of a terahertz metamaterial with a nonlinear response that is controllable via the relative structural arrangement of two stacked split ring resonator arrays. The first array is fabricated on an n-doped GaAs substrate, and the second array is fabricated vertically above the first using a polyimide spacer layer. Due to GaAs carrier dynamics, the on-resonance terahertz transmission at 0.4 THz varies in a nonlinear manner with incident terahertz power. The second resonator layer dampens this nonlinear response. In samples where the two layers are aligned, the resonance disappears, and the total nonlinear modulation of the on-resonance transmission decreases. The nonlinear modulation is restored in samples where an alignment offset is imposed between the two resonator arrays. Structurally tunable metamaterials and metasurfaces can therefore act as a design template for tunable nonlinear THz devices by controlling the coupling of confined electric fields to nonlinear phenomena in a complex material substrate or inclusion.