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.
The purpose of this Seedling project is to couple a marine renewable energy (MRE) dynamics simulation software with the soil-foundation models in the OC6 Phase II project [Bergua et al., 2021] and evaluate the software’s performance. This is a first step to accurately evaluating soil-foundation impacts on other types of MRE, like wave or current energy converters (WECs, CECs). OC6 Phase II compares offshore wind turbine (OWT) simulations using several different soil-foundation models to identify and fill key gaps in soil-foundation analyses. WEC-Sim was chosen to model the OC6 Phase II offshore wind turbine and various load cases because of its adaptability, accuracy of hydrodynamic loads, and ability to apply an arbitrary wind loading. Of the four methods used in OC6, the apparent fixity soil-foundation method was coupled with WEC-Sim. Technical challenges with flexible hydrodynamic bodies, added mass and external function libraries inhibited the ability to compare the WEC-Sim results to other OC6 participants. These challenges required that the WEC-Sim model of the OC6 OWT use a combination of rigid and flexible bodies to ensure a numerically stable solution. The rigid monopile creates a more stiff system and causes smaller amplitude motion under hydrodynamic loading and higher dominant frequency of motion under wind loading. These discrepancies are expected based on the increased stiffness of the WEC-Sim case.
Rapid molecular-weight growth of hydrocarbons occurs in flames, in industrial synthesis, and potentially in cold astrochemical environments. A variety of high- and low-temperature chemical mechanisms have been proposed and confirmed, but more facile pathways may be needed to explain observations. We provide laboratory confirmation in a controlled pyrolysis environment of a recently proposed mechanism, radical–radical chain reactions of resonance-stabilized species. The recombination reaction of phenyl (c-C6H5) and benzyl (c-C6H5CH2) radicals produces both diphenylmethane and diphenylmethyl radicals, the concentration of the latter increasing with rising temperature. A second phenyl addition to the product radical forms both triphenylmethane and triphenylmethyl radicals, confirming the propagation of radical–radical chain reactions under the experimental conditions of high temperature (1100–1600 K) and low pressure (ca. 3 kPa). Similar chain reactions may contribute to particle growth in flames, the interstellar medium, and industrial reactors.
We report the details of an infrared, laser absorption diagnostic capable of quantifying aluminum monoxide temperature and column density at 100 kHz repetition rate. This novel technique employs a near infrared MEMS-VCSEL to measure rotationally resolved optical absorption spectra of aluminum monoxide $A^2\Pi_i$ - $X^2\Sigma^+$ from approximately 7400 –7900 cm-1. Temperatures and column densities are extracted from model regressions to provide temporally resolved thermochemical information on aluminum oxidation reactions. The measurement capability is demonstrated by performing 100 kHz measurement in the plume of an exploding bridgewire with measured temperatures of 3450–3100 K and column densities of 1– 11 x 1016cm -2. To the authors knowledge, this is the first use of the AlO $A^2\Pi_i$ - $X^2\Sigma^+$ transition to characterize aluminum combustion environments. Details regarding signal extraction and calibration of MEMS-VCSEL spectra are also included. Although unsuccessful, efforts to extract kinetic temperature and column density from simultaneously measured, atomic aluminum 2P3/2,1/2-2S1/2 transitions at 7618 cm-1 and 7602 cm-1 are also described.
Li metal anodes are enticing for batteries due to high theoretical charge storage capacity, but commercialization is plagued by dendritic Li growth and short circuits when cycled at high currents. Applied pressure has been suggested to improve morphology, and therefore performance. We hypothesized that increasing pressure would suppress dendritic growth at high currents. To test this hypothesis, here, we extensively use cryogenic scanning electron microscopy to show that varying the applied pressure from 0.01 to 1 MPa has little impact on Li morphology after one deposition. We show that pressure improves Li density and preserves Li inventory after 50 cycles. However, contrary to our hypothesis, pressure exacerbates dendritic growth through the separator, promoting short circuits. Therefore, we suspect Li inventory is better preserved in cells cycled at high pressure only because the shorts carry a larger portion of the current, with less being carried by electrochemical reactions that slowly consume Li inventory.
The canonical beam splitter - a fundamental building block of quantum optical systems - is a reciprocal element. It operates on forward- and backward-propagating modes in the same way, regardless of direction. The concept of nonreciprocal quantum photonic operations, by contrast, could be used to transform quantum states in a momentum- and direction-selective fashion. Here we demonstrate the basis for such a nonreciprocal transformation in the frequency domain through intermodal Bragg scattering four-wave mixing (BSFWM). Since the total number of idler and signal photons is conserved, the process can preserve coherence of quantum optical states, functioning as a nonreciprocal frequency beam splitter. We explore the origin of this nonreciprocity and find that the phase-matching requirements of intermodal BSFWM produce an enormous asymmetry (76×) in the conversion bandwidths for forward and backward configurations, yielding ∼25 dB of nonreciprocal contrast over several hundred GHz. We also outline how the demonstrated efficiencies (∼10-4) may be scaled to near-unity values with readily accessible powers and pumping configurations for applications in integrated quantum photonics.
Natural and anthropogenic events may create low frequency sound waves, or infrasound, that can travel for vast distances in planetary atmospheres. They permit the remote monitoring of geophysical activity over local to global scales. Most studies have utilized ground-based recorders, but it is possible to deploy acoustic sensors to altitudes of over 50 km. Such elevated platforms can capture sounds that their surface analogs cannot access. High altitude balloons and low altitude aerostats are filling this observation gap, but key environments remain out of reach of both of these. Recent work by den Ouden, Smets et al. (2021) addressed this with a new instrumentation platform—a large seabird flying just above the ocean's surface. Their work demonstrates that, infrasound sensing using heavier-than-air platforms in windy environments is possible, which has implications both terrestrially (e.g., extending sensor networks over the oceans) and extraterrestrially (proposed or planned missions to Venus and Titan).
Motivation: Crucial aspect of mechanical design is joining methodology of parts. Ability to analyze joint and fasteners in system for structural integrity is fundamental. Different modeling representations of fasteners include spring, beam, and solid elements. Various methods compared for linear system to decide method appropriate for design study. New method for modeling fastener joint is explored from full system perspective. Analysis results match well with published experimental data for new method.
Wang, Qian; Guillaume, Joseph; Jakeman, John D.; Yang, Tao; Iwanaga, Takuya; Croke, Barry; Jakeman, Tony
Despite widespread use of factor fixing in environmental modeling, its effect on model predictions has received little attention and is instead commonly presumed to be negligible. We propose a proof-of-concept adaptive method for systematically investigating the impact of factor fixing. The method uses Global Sensitivity Analysis methods to identify groups of sensitive parameters, then quantifies which groups can be safely fixed at nominal values without exceeding a maximum acceptable error, demonstrated using the 21-dimensional Sobol’ G-function. Furthermore, three error measures are considered for quantities of interest, namely Relative Mean Absolute Error, Pearson Product-Moment Correlation and Relative Variance. Results demonstrate that factor fixing may cause large errors in the model results unexpectedly, when preliminary analysis suggests otherwise, and that the default value selected affects the number of factors to fix. To improve the applicability and methodological development of factor fixing, a new research agenda encompassing five opportunities is discussed for further attention.
This report documents the analysis conducted by Sandia National Laboratories on the effect of various alterations to published methodologies to calculate Derived Response Levels for Environmental Protection Agency Drinking Water Protective Action Guides. Specifically, this study sought to assess and provide recommendations on calculation of the Derived Response Level accounting for decay during the consumption period, assess the impact of decay on laboratory Minimal Detectable Concentration in water samples as compared to the Derived Response Level, make a recommendation on the calculation of Derived Response Level consistent with existing Public Protection Methods, and make a recommendation on the use of six age groups versus eight age groups based on available dose coefficients for calculation of the Derived Response Level. The authors analyzed these various factors using nominal radionuclide mixes from four scenarios and compared calculation of the Derived Response Level accounting for decay and no decay and then compared those results to the laboratory Minimal Detectable Concentrations. The authors concluded that decay should be included in the calculation of the Derived Response Level, existing Public Protection Methods should be employed to calculate the Derived Response Level, six age groups should be used versus eight, and the use of both decay and Public Protection Methods result in little to no concern for water samples meeting the Minimum Detectable Concentration requirements. The results of this study may be used in further developing and implementing a method for the Environmental Protection Agency Water Derived Response Level calculation in the Federal Radiological Monitoring and Assessment Center Assessment Manual.
We present a minimally invasive method for forward propagation of material property uncertainty to full-field quantities of interest in solid dynamics. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known a priori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the evolution equations based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the driving term of the evolution equations. The implementation is model independent, storage and communication efficient, and straightforward. We demonstrate its efficiency, accuracy, scaling with dimension of the parameter space, and convergence in distribution with two problems: a quasi-one-dimensional bar impact, and a two material notched plate impact. For the bar impact problem, we provide an analytical solution to PDF of the solution fields for method validation. With the notched plate problem, we also demonstrate good parallel efficiency and scaling of the method.
Wong, Man H.; Bierwagen, Oliver; Kaplar, Robert K.; Umezawa, Hitoshi
Ultrawide-bandgap (UWBG) semiconductor technology is presently going through a renaissance exemplified by advances in material-level understanding, extensions of known concepts to new materials, novel device concepts, and new applications. This focus issue presents a timely selection of papers spanning the current state of the art in UWBG materials and applications, including both experimental results and theoretical developments. It covers broad research subtopics on UWBG bulk crystals and substrate technologies, UWBG defect science and doping, UWBG epitaxy, UWBG electronic and optoelectronic properties, and UWBG power devices and emitters. In this overview article, we consolidate the fundamentals and background of key UWBG semiconductors including aluminum gallium nitride alloys (AlxGa1–xN), boron nitride (BN), diamond, β-phase gallium oxide (β-Ga2O3), and a number of other UWBG binary and ternary oxides. Graphical Abstract: [Figure not available: see fulltext.]
The construction of deep geological repositories (DGR) in salt formations requires penetrating through naturally sealing geosphere layers. While the emplaced nuclear waste is primarily protected by the containment-providing rock zone (CRZ), technical barriers are required, for example during handling. For closure geotechnical barriers seal the repository along the accesses against water or solutions from outside and the possible emission paths for radionuclides contained inside. As these barriers must ensure maintenance-free function on a long-term basis, they typically comprise a set of specialized elements with diversified functions that may be used redundantly. The effects of the individual elements are coordinated so that they are collectively referred to as the Engineered Barrier System (EBS).
A stable solid electrolyte interphase (SEI) layer is key to high performing lithium ion and lithium metal batteries for metrics such as calendar and cycle life. The SEI must be mechanically robust to withstand large volumetric changes in anode materials such as lithium and silicon, so understanding the mechanical properties and behavior of the SEI is essential for the rational design of artificial SEI and anode form factors. The mechanical properties and mechanical failure of the SEI are challenging to study, because the SEI is thin at only ∼10-200 nm thick and is air sensitive. Furthermore, the SEI changes as a function of electrode material, electrolyte and additives, temperature, potential, and formation protocols. A variety of in situ and ex situ techniques have been used to study the mechanics of the SEI on a variety of lithium ion battery anode candidates; however, there has not been a succinct review of the findings thus far. Because of the difficulty of isolating the true SEI and its mechanical properties, there have been a limited number of studies that can fully de-convolute the SEI from the anode it forms on. A review of past research will be helpful for culminating current knowledge and helping to inspire new innovations to better quantify and understand the mechanical behavior of the SEI. This review will summarize the different experimental and theoretical techniques used to study the mechanics of SEI on common lithium battery anodes and their strengths and weaknesses.
Targeting host factors for anti-viral development offers several potential advantages over traditional countermeasures that include broad-spectrum activity and prevention of resistance. Characterization of host factors in animal models provides strong evidence of their involvement in disease pathogenesis, but the feasibility of performing high-throughput in vivo analyses on lists of genes is problematic. To begin addressing the challenges of screening candidate host factors in vivo, we combined advances in CRISPR-Cas9 genome editing with an immunocompromised mouse model used to study highly pathogenic viruses. Transgenic mice harboring a constitutively expressed Cas9 allele (Cas9tg/tg) with or without knockout of type I interferon receptors served to optimize in vivo delivery of CRISPR single-guide RNA (sgRNA) using Invivofectamine 3.0, a simple and easy-to-use lipid nanoparticle reagent. Invivofectamine 3.0-mediated liver-specific editing to remove activity of the critical Ebola virus host factor Niemann-Pick disease type C1 in an average of 74% of liver cells protected immunocompromised Cas9tg/tg mice from lethal surrogate Ebola virus infection. We envision that immunocompromised Cas9tg/tg mice combined with straightforward sgRNA in vivo delivery will enable efficient host factor loss-of-function screening in the liver and other organs to rapidly study their effects on viral pathogenesis and help initiate development of broad-spectrum, host-directed therapies against emerging pathogens.
This report documents the feasibility phase of the Critical Experiment Design (CED) conducted as part of integral experiment request (IER) 523. The purpose of IER-523 is to explore the effects of using 35 weight percent enriched uranium dioxide-beryllium oxide (UO2-BeO) material on critical configurations using the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories (Sandia). Preliminary experiment design concepts, neutronic analysis results, and proposed paths for continuing the CED process are presented.
Understanding how atoms interact with hot dense matter is essential for astrophysical and laboratory plasmas. Interactions in high-density plasmas broaden spectral lines, providing a rare window into interactions that govern, for example, radiation transport in stars. However, up to now, spectral line-shape theories employed at least one of three common approximations: second-order Taylor treatment of broadening operator, dipole-only interactions between atom and plasma, and classical treatment of perturbing electrons. In this Letter, we remove all three approximations simultaneously for the first time and test the importance for two applications: neutral hydrogen and highly ionized magnesium and oxygen. We found 15%-50% change in the spectral line widths, which are sufficient to impact applications including white-dwarf mass determination, stellar-opacity research, and laboratory plasma diagnostics.
The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.
We report progress on a task to model transformers in ALEGRA using the “Transient Magnetics” option. We specifically evaluate limits of the approach resolving individual coil wires. There are practical limits to the number of turns in a coil that can be numerically modeled, but calculated inductance can be scaled to the correct number of turns in a simple way. Our testing essentially confirmed this “turns scaling” hypothesis. We developed a conceptual transformer design, representative of practical designs of interest, and that focused our analysis. That design includes three coils wrapped around a rectangular ferromagnetic core. The secondary and tertiary coils have multiple layers. The tertiary has three layers of 13 turns each; the secondary has five layers of 44 turns; the primary has one layer of 20 turns. We validated the turns scaling of inductance for simple (one-layer) coils in air (no core) by comparison to available independent calculations for simple rectangular coils. These comparisons quantified the errors versus reduced number of turns modeled. For more than 3 turns, the errors are <5%. The magnetic field solver failed to converge (within 5000 iterations) for >10 turns. Including the core introduced some complications. It was necessary to capture the core surfaces in thin grid sheaths to minimize errors in computed magnetic energy. We do not yet have quantitative benchmarks with which to compare, but calculated results are qualitatively reasonable.
Point defects in SiC are an attractive platform for quantum information and sensing applications because they provide relatively long spin coherence times, optical spin initialization, and spin-dependent fluorescence readout in a fabrication-friendly semiconductor. The ability to precisely place these defects at the optimal location in a host material with nano-scale accuracy is desirable for integration of these quantum systems with traditional electronic and photonic structures. Here, we demonstrate the precise spatial patterning of arrays of silicon vacancy (VSi) emitters in an epitaxial 4H-SiC (0001) layer through mask-less focused ion beam implantation of Li+. We characterize these arrays with high-resolution scanning confocal fluorescence microscopy on the Si-face, observing sharp emission lines primarily coming from the V1 ′ zero-phonon line (ZPL). The implantation dose is varied over 3 orders of magnitude, leading to VSi densities from a few per implantation spot to thousands per spot, with a linear dependence between ZPL emission and implantation dose. Optically-detected magnetic resonance (ODMR) is also performed, confirming the presence of V2 VSi. Our investigation reveals scalable and reproducible defect generation.
Middleton, Bobby M.; Reyes, Gustavo A.; Harrison, Thomas J.; Burli, Pralhad; Foss, Andrew; Huning, Alexander; Yadav, Vaibhav; Drennen, Thomas
Advanced Reactor and Small Modular Reactor (AR/SMR) designs have the potential to provide clean, reliable baseload energy. Ensuring the capability to deploy these reactors in an economically viable fashion is of interest to industry. A large portion of the expected operating costs of AR/SMRs involves the security of the plant. Security by Design (SeBD) is the practice of including features in the design and construction of the site, with the intent to decrease the operating costs related to security. Quantifying the increase or decrease in the overall lifetime cost to the plant as a result of SeBD is of paramount importance in understanding the disadvantages and benefits of such activities. The National Nuclear Security Administration’s (NNSA) Office of International Nuclear Security (INS) is funding the development of a methodology whereby the capital expenses and operating expenses, as well as the physical security effectiveness, of SeBD can be quantified for AR/SMRs. This report is an interim report on the progress of the work performed by Sandia National Laboratories (SNL), Idaho National Laboratory, and Oak Ridge National Laboratory (ORNL). It is the second annual report on this work.
We report on the characterization of heating rates and photoinduced electric charging on a microfabricated surface ion trap with integrated waveguides. Microfabricated surface ion traps have received considerable attention as a quantum information platform due to their scalability and manufacturability. Here, we characterize the delivery of 435-nm light through waveguides and diffractive couplers to a single ytterbium ion in a compact trap. We measure an axial heating rate at room temperature of 0.78±0.05 q/ms and see no increase due to the presence of the waveguide. Furthermore, the electric field due to charging of the exposed dielectric outcoupler settles under normal operation after an initial shift. The frequency instability after settling is measured to be 0.9 kHz.
This report summarizes the guidance provided to Sustainable Engineering to help them learn about equation-oriented optimization and the Sandia-developed software packages Pyomo and IDAESPSE. This was a short 10-week project (October 2021 – December 2021) and the goal was to help the company learn about the IDAES framework and how it could be used for their future projects. The company submitted an SBIR proposal related to developing a green ammonia process model with IDAES and if that proposal is successful this NMSBA project could lead to future collaboration opportunities.
Combining plasmonic and magnetic properties, namely magneto-plasmonic coupling, inspires great research interest and the search for magneto-plasmonic nanostructure becomes considerably critical. Here we designed a nanopillar-in-matrix structure with core–shell alloyed nanopillars for both BaTiO3 (BTO)-Au0.5Co0.5 (AuCo) and BTO-Au0.25Cu0.25Co0.25Ni0.25 (AuCuCoNi) hybrid systems, i.e., ferromagnetic alloy cores (e.g., Co or CoNi) with plasmonic shells (e.g., Au or Au/Cu). These core–shell alloy nanopillars are uniformly embedded into a dielectric BTO matrix to form a vertically aligned nanocomposite (VAN) structure. Both hybrid systems present excellent epitaxial quality and interesting multi-functionality, e.g., high magnetic anisotropy, magneto-optical coupling response, tailorable plasmonic resonance wavelength, tunable hyperbolic properties and strong optical anisotropy. These alloyed nanopillars-in-matrix designs provide enormous potential for complex hybrid material designs with multi-functionality and demonstrate strong interface enabled magneto-plasmonic coupling along with plasmonic and magnetic performance.
We report on experimental measurements of how an externally imposed magnetic field affects plasma heating by kJ-class, nanosecond laser pulses. The experiments reported here took place in gas cells analogous to magnetized liner inertial fusion targets. We observed significant changes in laser propagation and energy deposition scale lengths when a 12T external magnetic field was imposed in the gas cell. We find evidence that the axial magnetic field reduces radial electron thermal transport, narrows the width of the heated plasma, and increases the axial plasma length. Reduced thermal conductivity increases radial thermal gradients. This enhances radial hydrodynamic expansion and subsequent thermal self-focusing. Our experiments and supporting 3D simulations in helium demonstrate that magnetization leads to higher thermal gradients, higher peak temperatures, more rapid blast wave development, and beam focusing with an applied field of 12T.
Diffraction techniques can powerfully and nondestructively probe materials while maintaining high resolution in both space and time. Unfortunately, these characterizations have been limited and sometimes even erroneous due to the difficulty of decoding the desired material information from features of the diffractograms. Currently, these features are identified non-comprehensively via human intuition, so the resulting models can only predict a subset of the available structural information. In the present work we show (i) how to compute machine-identified features that fully summarize a diffractogram and (ii) how to employ machine learning to reliably connect these features to an expanded set of structural statistics. To exemplify this framework, we assessed virtual electron diffractograms generated from atomistic simulations of irradiated copper. When based on machine-identified features rather than human-identified features, our machine-learning model not only predicted one-point statistics (i.e. density) but also a two-point statistic (i.e. spatial distribution) of the defect population. Hence, this work demonstrates that machine-learning models that input machine-identified features significantly advance the state of the art for accurately and robustly decoding diffractograms.
Daly, Luke; Lee, Martin R.; Hallis, Lydia J.; Ishii, Hope A.; Bradley, John P.; Bland, Phillip A.; Saxey, David W.; Fougerouse, Denis; Rickard, William D.A.; Forman, Lucy V.; Timms, Nicholas E.; Jourdan, Fred; Reddy, Steven M.; Salge, Tobias; Zakaria; Quadir, Zakaria; Christou, Evangelos; Cox, Morgan A.; Aguiar, Jeffrey A.; Hattar, Khalid M.; Monterrosa, Anthony; Keller, Lindsay P.; Christoffersen, Roy; Dukes, Catherine A.; Loeffler, Mark J.; Thompson, Michelle S.
The isotopic composition of water in Earth’s oceans is challenging to recreate using a plausible mixture of known extraterrestrial sources such as asteroids—an additional isotopically light reservoir is required. The Sun’s solar wind could provide an answer to balance Earth’s water budget. We used atom probe tomography to directly observe an average ~1 mol% enrichment in water and hydroxyls in the solar-wind-irradiated rim of an olivine grain from the S-type asteroid Itokawa. We also experimentally confirm that H+ irradiation of silicate mineral surfaces produces water molecules. These results suggest that the Itokawa regolith could contain ~20 l m−3 of solar-wind-derived water and that such water reservoirs are probably ubiquitous on airless worlds throughout our Galaxy. The production of this isotopically light water reservoir by solar wind implantation into fine-grained silicates may have been a particularly important process in the early Solar System, potentially providing a means to recreate Earth’s current water isotope ratios.
The Kronecker product is an important matrix operation with a wide range of applications in signal processing, graph theory, quantum computing and deep learning. In this work, we introduce a generalization of the fast Johnson–Lindenstrauss projection for embedding vectors with Kronecker product structure, the Kronecker fast Johnson–Lindenstrauss transform (KFJLT). The KFJLT reduces the embedding cost by an exponential factor of the standard fast Johnson–Lindenstrauss transform’s cost when applied to vectors with Kronecker structure, by avoiding explicitly forming the full Kronecker products. We prove that this computational gain comes with only a small price in embedding power: consider a finite set of p points in a tensor product of d constituent Euclidean spaces ⊗1k=d Rnk, and let N = Πdk=1 nk. With high probability, a random KFJLT matrix of dimension m × N embeds the set of points up to multiplicative distortion (1 ± ε) provided m ≿ ε−2 log2d−1 (p) log N. We conclude by describing a direct application of the KFJLT to the efficient solution of large-scale Kronecker-structured least squares problems for fitting the CP tensor decomposition.
High-quality factor resonant cavities are challenging structures to model in electromagnetics owing to their large sensitivity to minute parameter changes. Therefore, uncertainty quantification (UQ) strategies are pivotal to understanding key parameters affecting the cavity response. We discuss here some of these strategies focusing on shielding effectiveness (SE) properties of a canonical slotted cylindrical cavity that will be used to develop credibility evidence in support of predictions made using computational simulations for this application.
Garcia, Raphael F.; Murdoch, Naomi; Lorenz, Ralph; Spiga, Aymeric; Bowman, Daniel B.; Lognonne, Philippe; Banfield, Don; Banerdt, William B.
The unprecedented quality and sampling rate of seismometer and pressure sensors of the InSight Mars mission allow us to investigate infrasound through its pressure and ground deformation signals. This study focuses on compliance effects induced by acoustic waves propagating almost horizontally close to the surface. The compliance of acoustic waves is first estimated using the compliance estimates from pressure perturbations moving at wind speed. Then, a marker of compliance events is used to detect events of ground deformation induced by pressure variations, in three frequency bands from 0.4 to 3.2 Hz, from InSight sol 180 to 690. Additional selection criteria are imposed on the detected events to focus on acoustic waves and to remove various noise sources (e.g., wind effects or seismometer artifacts). After an automated selection, the visual inspection of the records allows us to validate two infrasound candidates that cannot be related to pressure perturbations moving at wind speed nor to known noise sources. For our highest quality infrasound candidate, the relation between this event and a convective vortex occuring 10 s later is tested. The azimuth of the vortex position at the time of infrasound detection is not consistent with the arrival azimuth of the suspected infrasound inferred from the polarization of seismometer records, thus the link between these two phenomena cannot be demonstrated. Further investigations would require a better understanding of wind-related noise impacting InSight sensors and of the effects of lateral variations of subsurface mechanical properties on the ground deformations induced by atmospheric pressure variations.
Sandia provided technical assistance to Energy Cloud to support the assessment of Energy Cloud’s technology for air filtration of the SARS-CoV-2 virus. The Energy Cloud system was developed to filter the SARS-CoV-2 virus from commercial HVAC systems, ducts, and enclosed rooms without generating ozone. The project included a 3-week experimental series with aerosolized SARS-CoV-2 virus at the University of Southern California’s biosafety level 3 (BSL-3) laboratory. USC provided the facility as well as experimentally derived measurements and assessment of the Energy Cloud system efficacy for SARSCoV-2 filtration from air handling systems.
This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year (FY) 2021 and is a continuation of the FY2020 progress report. In this report, we only report the changes made to the current sodium pool fire model in MELCOR. We modified and corrected many control functions to enhance the current model from the FY2020 report. This year’s enhancements relate to better agreement of the suspended aerosol measurement from JAEA’s F7 series tests. Staff from Sandia and JAEA conducted the validation studies of the sodium pool fire model in MELCOR. To validate this pool fire model with the latest enhancement, JAEA sodium pool fire experiments (F7-1 and F7-2) were used. The results of the calculation, including the code-to-code comparisons are discussed as well as suggestions for further model improvement. Finally, recommendations are made for new MELCOR simulations for FY2022.
There are urgent calls to action by the NAE, the Nobel Prize Summit, the UN, and global scientists to address and solve, in this decade (2020 – 2030), crucial and widely recognized global challenges to peace and security before they become more complex and more environmentally, financially, and socially costly; before we reach the point of no return.
A resonant cavity undergoes three distinct behaviors with increasing frequency: 1) fundamental modes, localized in frequency with well defined modal distribution; 2) undermoded region, where modes are still separated, but are sufficiently perturbed by small imperfections that their spectral positions (and distributions) are statistical in nature; and 3) overmoded region, where modes overlap, field distributions follow stochastic distributions, and the slot acts as if in free space. Understanding the penetration through slots in the overmoded region is of great interest, and is the focus of this article. Since full-wave solvers may not be able to provide a timely answer for very high frequencies due to a lack of memory and/or computation resources, we develop bounding methods to estimate worst-case average and maximum fields within the cavity. After discussing the bounding formulation, we compare its results to full-wave simulations at the first, second, and third resonance supported by the slot in the case of a cylindrical cavity. Note that the bounding formulation indicates that results are nearly independent of cavity shape: only the cavity volume, frequency, and cavity quality factor affect the overmoded region, making this formulation a powerful tool to assess electromagnetic interference and electromagnetic compatibility effects within cavities.
The friction behavior of metals is directly linked to the mechanisms that accommodate deformation. We examine the links between mechanisms of strengthening, deformation, and the wide range of friction behaviors that are exhibited by shearing metal interfaces. Specifically, the focus is on understanding the shear strength of nanocrystalline and nanostructured metals, and conditions that lead to low friction coefficients. Grain boundary sliding and the breakdown of Hall–Petch strengthening at the shearing interface are found to generally and predictably explain the low friction of these materials. While the following is meant to serve as a general discussion of the strength of metals in the context of tribological applications, one important conclusion is that tribological research methods also provide opportunities for probing the fundamental properties and deformation mechanisms of metals.
We report carbon impurity ion incident angles and deposition rates, along with silicon erosion rates, from measurements of micro-engineered trenches on a silicon surface exposed to L-mode deuterium plasmas at the DIII-D divertor. Post exposure ex-situ analysis determined elemental maps and concentrations, carbon deposition thicknesses, and erosion of silicon surfaces. Carbon deposition profiles on the trench floor showed carbon ion shadowing that was consistent with ERO calculations of average carbon ion angle distributions (IADs) for both polar and azimuthal angles. Measured silicon net erosion rates negatively correlated with the deposited carbon concentration at different locations. Differential erosion of surfaces on two different ion-downstream trench slope structures suggested that carbon deposition rate is affected by the carbon ion incident angle and significantly suppressed the surface erosion. The results suggest the C impurity ion incident angles, determined by the IADs and surface morphology, strongly affect erosion rates as well as the main ion (D, T, He) incident angles.
The Message Passing Interface (MPI) remains the dominant programming model for scientific applications running on today's high-performance computing (HPC) systems. This dominance stems from MPI's powerful semantics for inter-process communication that has enabled scientists to write applications for simulating important physical phenomena. MPI does not, however, specify how messages and synchronization should be carried out. Those details are typically dependent on low-level architecture details and the message characteristics of the application. Therefore, analyzing an application's MPI resource usage is critical to tuning MPI's performance on a particular platform. The result of this analysis is typically a discussion of the mean message sizes, queue search lengths and message arrival times for a workload or set of workloads. While a discussion of the arithmetic mean in MPI resource usage might be the most intuitive summary statistic, it is not always the most accurate in terms of representing the underlying data. In this paper, we analyze MPI resource usage for a number of key MPI workloads using an existing MPI trace collector and discrete-event simulator. Our analysis demonstrates that the average, while easy and efficient to calculate, is a useful metric for characterizing latency and bandwidth measurements, but may not be a good representation of application message sizes, match list search depths, or MPI inter-operation times. Additionally, we show that the median and mode are superior choices in many cases. We also observe that the arithmetic mean is not the best representation of central tendency for data that are drawn from distributions that are multi-modal or have heavy tails. The results and analysis of our work provide valuable guidance on how we, as a community, should discuss and analyze MPI resource usage data for scientific applications.
Wang, Fei; Yan, Xueliang; Chen, Xin; Snyder, Nathan; Nastasi, Michael; Hattar, Khalid M.; Cui, Bai
The solid-state joining of oxide-dispersion-strengthened (ODS) austenitic steels was achieved using a pulsed electric current joining (PECJ) process. Microstructures of the austenitic grain structures and oxide dispersions in the joint areas were characterized using electron microscopy. Negligible grain growth was observed in austenitic grain structures, while slight coarsening of oxide dispersions occurred at a short holding time. The mechanisms of the PECJ process may involve three steps that occur simultaneously, including the sintering of mechanical alloying powders in the bonding layer, formation of oxide dispersions, and bonding of the mechanical alloying powders with the base alloy. The high hardness and irradiation resistance of ODS alloys were retained in the joint areas. This research revealed the fundamental mechanisms during the PECJ process, which is beneficial for its potential applications during the advanced manufacturing of ODS alloys.
A 3 foot x 3 foot x 3 foot aluminum solar collector was manufactured using computer numerical control. The interior of the device included six triangular dimpled fins for enhanced heat transfer. The interior vertical wall on the south side was also dimpled. The solar collector working fluid was based on water, and the collector consisted solely of passive heat transfer mechanisms (no moving parts), making it ideal for off-the-grid and rural applications. Two types of heat transfer experiments were conducted. One experiment had external flat heaters attached on the top and the front side, while the other four sides were insulated. Except for the bottom surface, the second experiment had all its exterior surfaces sprayed with black solar paint to collect as much solar heat as possible. Temperature data as a function of time was collected using 14 thermocouples spread strategically throughout the solar collector. In addition, computational fluid dynamics (CFD) simulations were conducted using the dynamic Smagorinsky large eddy simulation turbulence model. The first simulation considered that both the top and front surfaces were exposed to a fixed temperature of 313.7 K (105 °F), while the remaining four surfaces were insulated. For the second simulation, all conditions were the same, except that the temperature for both heated surfaces was raised to 350 K (170.3 °F). The two temperatures are expected to bound the solar collector operational temperature during the late- Spring, Summer, and early-Fall months. The solar collector design, experimental data, CFD output, and a discussion of five manufacturing approaches and costs are documented in this report.
This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena. The experiments focus on providing data to better characterize the arc to improve the prediction of arc energy emitted during a HEAF event. An open box experiment allow for direct observation of the arc, which allows diagnostic instrumentation to record the phenomenological data needed for better characterization of the arc energy source term. The data collected supports characterization of the arc and arc jet, enclosure breach, material loss, and electrical properties. These results will be used to better characterizing the hazard for improvements in fire probabilistic risk assessment (PRA) realism. The experiments were performed at KEMA Labs located in Chalfont, Pennsylvania. The experimental design, setup, and execution were completed by staff from the NRC, the National Institute of Standards and Technology (NIST), Sandia National Laboratories (SNL) and KEMA Labs. In addition, representatives from the Electric Power Research Institute (EPRI) observed some of the experimental setup and execution. The HEAF experiments were performed between August 22, 2020 and September 18, 2020 on near-identical 51 cm (20 in) cube metal boxes suspended from a Unistrut support structure. The three-phase arcing fault was initiated at the ends of the conductors oriented vertically and located at the center of the box. Either aluminum or copper conductors were used for the conductors. The low-voltage experiments used 1 000 volts AC, while the medium-voltage experiments used 6 900 volts AC consistent with other recently completed experiments. Durations of the experiment ranged from 1 s to 5 s with fault currents ranging from 1 kA to 30 kA. Real-time electrical operating conditions, including voltage, current and frequency, were measured during the experiments. Heat fluxes and incident energies were measured with plate thermometers, radiometers, and slug calorimeters at various locations around the electrical enclosures. The experiments were documented with normal and high-speed videography, infrared imaging and photography.
This document summarily provides brief descriptions of the MELCOR code enhancement made between code revision number 18019and 21440. Revision 18019 represents the previous official code release; therefore, the modeling features described within this document are provided to assist users that update to the newest official MELCOR code release, 21440. Along with the newly updated MELCOR Users’ Guide [2] and Reference Manual [3], users are aware and able to assess the new capabilities for their modeling and analysis applications.
Silicon-based layered nanocomposites, comprised of covalent-metal interfaces, have demonstrated elevated resistance to radiation. The amorphization of the crystalline silicon sublayer during irradiation and/or heating can provide an additional mechanism for accommodating irradiation-induced defects. In this study, we investigated the mechanical strength of irradiated Si-based nanocomposites using atomistic modeling. We first examined dose effects on the defect evolution mechanisms near silicon-gold crystalline and amorphous interfaces. Our simulations reveal the growth of an emergent amorphous interfacial layer with increasing dose, a dominant factor mitigating radiation damage. We then examined the effect of radiation on the mechanical strength of silicon-gold multilayers by constructing yield surfaces. These results demonstrate a rapid onset strength loss with dose. Nearly identical behavior is observed in bulk gold, a phenomenon that can be rooted to the formation of radiation-induced stacking fault tetrahedra which dominate the dislocation emission mechanism during mechanical loading. Taken together, these results advance our understanding of the interaction between radiation-induced point defects and metal-covalent interfaces.
Rezaul Karim, Mohammad; Narasimhachary, Santosh; Radaelli, Francesco; Amann, Christian; Dayal, Kaushik; Silling, Stewart A.; Germann, Timothy C.
Conventional engineering methods oftentimes have challenges in the quantification of crack nucleation processes from manufacturing defects that are relevant for engineering component lifing. We present peridynamic simulation framework for the description of the crack nucleation process from cluster of non-metallic inclusions in aluminum alloys. Our non-local simulation framework characterizes crack nucleation process as multiple micro-crack nucleation events from individual inclusions, and eventually one micro-crack dominates. We define individual stages of the crack nucleation process, i.e., nucleation, micro-crack, technical, and crack initiation, that allow a quantification and meta model development of both the individual stages and the entire crack nucleation process.
The earth texture with complex morphological geometry and compositions such as shale and carbonate rocks, is typically characterized with sparse field samples because of an expensive and time-consuming characterization process. Accordingly, generating arbitrary large size of the geological texture with similar topological structures at a low computation cost has become one of the key tasks for realistic geomaterial reconstruction and subsequent hydro-mechanical evaluation for science and engineering applications. Recently, generative adversarial neural networks (GANs) have demonstrated a potential of synthesizing input textural images and creating equiprobable geomaterial images for stochastic analysis of hydrogeological properties, for example, the feasibility of CO2 storage sites and exploration of unconventional resources. However, the texture synthesis with the GANs framework is often limited by the computational cost and scalability of the output texture size. In this study, we proposed a spatially assembled GANs (SAGANs) that can generate output images of an arbitrary large size regardless of the size of training images with computational efficiency. The performance of the SAGANs was evaluated with two and three dimensional (2D and 3D) rock image samples widely used in geostatistical reconstruction of the earth texture and Lattice-Boltzmann (LB) simulations were performed to compare pore-scale flow patterns and upscaled permeabilities of training and generated geomaterial images. We demonstrate SAGANs can generate the arbitrary large size of statistical realizations with connectivity and structural properties and flow characteristics similar to training images, and also can generate a variety of realizations even on a single training image. In addition, the computational time was significantly improved compared to standard GANs frameworks.
We present a novel approach to information retrieval and document analysis based on graph analytic methods. Traditional information retrieval methods use a set of terms to define a query that is applied against a document corpus to identify the documents most related to those terms. In contrast, we define a query as a set of documents of interest and apply the query by computing mean hitting times between this set and all other documents on a document similarity graph abstraction of the semantic relationships between all pairs of documents. We present the steps of our approach along with a simple example application illustrating how this approach can be used to find documents related to two or more documents or topics of interest.
Sandia National Laboratories has long used the Munson-Dawson (M-D) model to predict the geomechanical behavior of salt caverns used to store oil at the Strategic Petroleum Reserve (SPR). Salt creep causes storage caverns to deform inward, thus losing volume. This loss of volume affects the salt above and around the caverns, puts stresses and strains on borehole casings, and creates surface subsidence which affects surface infrastructure. Therefore, accurate evaluation of salt creep behavior drives decisions about cavern operations. Parameters for the M-D model are typically fit against laboratory creep tests, but nearly all historic creep tests have been performed at equivalent stresses of 8 MPa or higher. Creep rates at lower equivalent stresses are very slow, such that tests take months or years to run, and the tests are sensitive to small temperature perturbations (<0.1°C). A recent collaboration between US and German researchers, recently characterized the creep behavior at low equivalent (deviatoric) stresses (<8 MPa) of salt from the Waste Isolation Pilot Plant. In addition, the M-D model was recently extended to include a low stress creep “mechanism”. This paper details new simulations of SPR caverns that use this extended M-D model, called the M-D Viscoplastic model. The results show that the inclusion of low stress creep significantly alters the prediction of steady-state cavern closure behavior and indicate that low stress creep is the dominant displacement mechanism at the dome scale. The implications for evaluating cavern and well integrity are demonstrated by investigating three phenomena: the extent of stress changes around the cavern; the predicted vertical strains applied to wellbore casings; and the evaluation of oscillating stress changes around the cavern due to oil sale cycles and their potential effect on salt fatigue.
Particle-in-cell, direct simulation Monte Carlo simulations reveal that ion-acoustic instabilities excited in presheaths can cause significant ion heating. Ion-acoustic instabilities are excited by the ion flow toward a sheath when the neutral gas pressure is small enough and the electron temperature is large enough. A series of 1D simulations were conducted in which neutral plasma (electrons and ions) was uniformly sourced with an ion temperature of 0.026 eV and different electron temperatures (0.1 eV-50 eV). Ion heating was observed when the electron-to-ion temperature ratio exceeded the minimum value predicted by linear response theory to excite ion-acoustic instabilities at the sheath edge (T e / T i ≈ 28). When this threshold was exceeded, the temperature equilibration rate between ions and electrons rapidly increased near the sheath so that the local temperature ratio did not significantly exceed the threshold for instability. This resulted in significant ion heating near the sheath edge, which also extended back into the bulk plasma; presumably due to wave reflection from the sheath. This ion-acoustic wave heating mechanism was found to decrease for higher neutral pressures, where ion-neutral collisions damp the ion-acoustic waves and ion heating is instead dominated by inelastic collisions in the presheath.
The essential data for interior and thermal evolution models of the Earth and super-Earths are the density and melting of mantle silicate under extreme conditions. Here, we report an unprecedently high melting temperature of MgSiO3 at 500 GPa by direct shockwave loading of pre-synthesized dense MgSiO3 (bridgmanite) using the Z Pulsed Power Facility. We also present the first high-precision density data of crystalline MgSiO3 to 422 GPa and 7200 K and of silicate melt to 1254 GPa. The experimental density measurements support our density functional theory based molecular dynamics calculations, providing benchmarks for theoretical calculations under extreme conditions. The excellent agreement between experiment and theory provides a reliable reference density profile for super-Earth mantles. Furthermore, the observed upper bound of melting temperature, 9430 K at 500 GPa, provides a critical constraint on the accretion energy required to melt the mantle and the prospect of driving a dynamo in massive rocky planets.
We’re happy to report that the full-aperture upgrade project, started in FY18, is now complete and short-pulse target experiments are underway. The table below lists the present performance level of ZPW. Additional laser improvements are in progress to increase the laser energy and pulse contrast along with implementing a correction for achromatic aberrations to reduce the focused spot size and pulse width.
Organophosphorus hydrolase (OPH) is a metalloenzyme that can hydrolyze organophosphorus agents resulting in products that are generally of reduced toxicity. The best OPH substrate found to date is diethyl p-nitrophenyl phosphate (paraoxon). Most structural and kinetic studies assume that the binding orientation of paraoxon is identical to that of diethyl 4-methylbenzylphosphonate, which is the only substrate analog co-crystallized with OPH. In the current work, we used a combined docking and molecular dynamics (MD) approach to predict the likely binding mode of paraoxon. Then, we used the predicted binding mode to run MD simulations on the wild type (WT) OPH complexed with paraoxon, and OPH mutants complexed with paraoxon. Additionally, we identified three hot-spot residues (D253, H254, and I255) involved in the stability of the OPH active site. We then experimentally assayed single and double mutants involving these residues for paraoxon binding affinity. The binding free energy calculations and the experimental kinetics of the reactions between each OPH mutant and paraoxon show that mutated forms D253E, D253E-H254R, and D253E-I255G exhibit enhanced substrate binding affinity over WT OPH. Interestingly, our experimental results show that the substrate binding affinity of the double mutant D253E-H254R increased by 19-fold compared to WT OPH.
Layered boron compounds have attracted significant interest in applications from energy storage to electronic materials to device applications, owing in part to a diversity of surface properties tied to specific arrangements of boron atoms. Here we report the energy landscape for surface atomic configurations of MgB2 by combining first-principles calculations, global optimization, material synthesis and characterization. We demonstrate that contrary to previous assumptions, multiple disordered reconstructions are thermodynamically preferred and kinetically accessible within exposed B surfaces in MgB2 and other layered metal diborides at low boron chemical potentials. Such a dynamic environment and intrinsic disordering of the B surface atoms present new opportunities to realize a diverse set of 2D boron structures. We validated the predicted surface disorder by characterizing exfoliated boron-terminated MgB2 nanosheets. We further discuss application-relevant implications, with a particular view towards understanding the impact of boron surface heterogeneity on hydrogen storage performance.
Membrane fusion is a critical step in enveloped virus entry and infection; however, molecular understanding of enveloped virus entry and treatment options remain limited. In recent decades, advances in imaging have facilitated the development of methods to study single virus events and membrane organization providing insight towards entry mechanisms. Through these advances, membrane composition and organization have been shown to play a critical role in the entry process. This LDRD uses model membrane platforms and basic biophysics to investigate entry mechanisms of enveloped viruses and understand membrane-based delivery technologies. This team has established foundations for using membrane-based platforms and biophysical techniques at Sandia to characterize membrane fusion.
Journal of Water Resources Planning and Management
Haxton, Terranna; Klise, Katherine A.; Laky, Daniel; Murray, Regan; Laird, Carl D.; Burkhardt, Jonathan B.
Drinking water systems commonly use manual or grab sampling to monitor water quality, identify or confirm issues, and verify that corrective or emergency response actions have been effective. In this paper, the effectiveness of regulatory sampling locations for emergency response is explored. An optimization formulation based on the literature was used to identify manual sampling locations to maximize overall nodal coverage of the system. Results showed that sampling locations could be effective in confirming incidents for which they were not designed. When evaluating sampling locations optimized for emergency response against regulatory scenarios, the average performance was reduced by 3%-4%, while using optimized regulatory sampling locations for emergency response reduced performance by 7%-10%. Secondary constraints were also included in the formulation to ensure geographical and water age diversity with minimal impact on the performance. This work highlighted that regulatory sampling locations provide value in responding to an emergency for these networks.
The PSL has reviewed the documentation and data provided by NNSS–Livermore Operations with respect to this proficiency test. This proficiency test was performed to assess NNSS–Livermore Operations’ ability to perform scattering parameter calibrations. The level of documentation was satisfactory. On 12/28/2021, NNSS–Livermore Operations reported the data for the proficiency test conducted on the attenuator. NNSS–Livermore Operations performed this proficiency test using an Anritsu vector network analyzer, an electronic calibration module, and verification kit. The PSL used a Keysight vector network analyzer and mechanical calibration kit. The PSL results included in this proficiency test report were taken on June 23, 2020.
Image-based simulation, the use of 3D images to calculate physical quantities, relies on image segmentation for geometry creation. However, this process introduces image segmentation uncertainty because different segmentation tools (both manual and machine-learning-based) will each produce a unique and valid segmentation. First, we demonstrate that these variations propagate into the physics simulations, compromising the resulting physics quantities. Second, we propose a general framework for rapidly quantifying segmentation uncertainty. Through the creation and sampling of segmentation uncertainty probability maps, we systematically and objectively create uncertainty distributions of the physics quantities. We show that physics quantity uncertainty distributions can follow a Normal distribution, but, in more complicated physics simulations, the resulting uncertainty distribution can be surprisingly nontrivial. We establish that bounding segmentation uncertainty can fail in these nontrivial situations. While our work does not eliminate segmentation uncertainty, it improves simulation credibility by making visible the previously unrecognized segmentation uncertainty plaguing image-based simulation.
In-silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench-scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation-based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal-based feature selection might have on both model performance and identification of key molecular substructures. We found that causal-based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.
Kirby, James; Geiselman, Gina M.; Yaegashi, Junko; Kim, Joonhoon; Zhuang, Xun; Tran-Gyamfi, Mary B.; Prahl, Jan P.; Sundstrom, Eric R.; Gao, Yuqian; Munoz, Nathalie; Burnum-Johnson, Kristin E.; Benites, Veronica T.; Baidoo, Edward E.K.; Fuhrmann, Anna; Seibel, Katharina; Webb-Robertson, Bobbie J.M.; Zucker, Jeremy; Nicora, Carrie D.; Tanjore, Deepti; Magnuson, Jon K.; Skerker, Jeffrey M.; Gladden, John M.
Background: Mitigation of climate change requires that new routes for the production of fuels and chemicals be as oil-independent as possible. The microbial conversion of lignocellulosic feedstocks into terpene-based biofuels and bioproducts represents one such route. This work builds upon previous demonstrations that the single-celled carotenogenic basidiomycete, Rhodosporidium toruloides, is a promising host for the production of terpenes from lignocellulosic hydrolysates. Results: This study focuses on the optimization of production of the monoterpene 1,8-cineole and the sesquiterpene α-bisabolene in R. toruloides. The α-bisabolene titer attained in R. toruloides was found to be proportional to the copy number of the bisabolene synthase (BIS) expression cassette, which in turn influenced the expression level of several native mevalonate pathway genes. The addition of more copies of BIS under a stronger promoter resulted in production of α-bisabolene at 2.2 g/L from lignocellulosic hydrolysate in a 2-L fermenter. Production of 1,8-cineole was found to be limited by availability of the precursor geranylgeranyl pyrophosphate (GPP) and expression of an appropriate GPP synthase increased the monoterpene titer fourfold to 143 mg/L at bench scale. Targeted mevalonate pathway metabolite analysis suggested that 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGR), mevalonate kinase (MK) and phosphomevalonate kinase (PMK) may be pathway bottlenecks are were therefore selected as targets for overexpression. Expression of HMGR, MK, and PMK orthologs and growth in an optimized lignocellulosic hydrolysate medium increased the 1,8-cineole titer an additional tenfold to 1.4 g/L. Expression of the same mevalonate pathway genes did not have as large an impact on α-bisabolene production, although the final titer was higher at 2.6 g/L. Furthermore, mevalonate pathway intermediates accumulated in the mevalonate-engineered strains, suggesting room for further improvement. Conclusions: This work brings R. toruloides closer to being able to make industrially relevant quantities of terpene from lignocellulosic biomass.
Big Data in the area of Remote Sensing has been growing rapidly. Remote sensors are used in surveillance, security, traffic, environmental monitoring, and autonomous sensing. Real-time detection of small moving targets using a remote sensor is an ongoing, challenging problem. Since the object is located far away from the sensor, the object often appears too small. The object’s signal-to-noise-ratio (SNR) is often very low. Occurrences such as camera motion, moving backgrounds (e.g., rustling leaves), low contrast and resolution of foreground objects makes it difficult to segment out the targeted moving objects of interest. Due to the limited appearance of the target, it is tough to obtain the target’s characteristics such as its shape and texture. Without these characteristics, filtering out false detections can be a difficult task. Detecting these targets, would often require the detector to operate under a low detection threshold. However, lowering the detection threshold could lead to an increase of false alarms. In this paper, the author will introduce a new method that improves the probability to detect low SNR objects, while decreasing the number of false alarms as compared to using the traditional baseline detection technique.
Identifying and planning preservation and curation activities associated with geospatial data will improve the ability of the U.S. Department of Energy Office of Legacy Management (LM) to support their core mission of protecting human health and the environment. This report documents the development LM's strategy for preserving and curating geospatial data within the context of LM's data-lifecycle-management framework. The strategy consists of preservation and curation elements, specific activities, and key enabling factors that ensure LM's geospatial data is maintained. Preservation elements enable the effective preservation of LM's geospatial data and recognizes that strategies need to be flexible to adapt to ongoing changes in scale, technology, and standards. Key enabling factors are intended to highlight critical data management responsibilities that must be addressed by LM to meet its preservation and curation objectives. A summary of best practices for geospatial data preservation is provided as part of the strategy.
Shu, Yi; Galles, Daniel; Tertuliano, Ottman A.; Mcwilliams, Brandon A.; Yang, Nancy Y.; Cai, Wei; Lew, Adrian J.
The study of microstructure evolution in additive manufacturing of metals would be aided by knowing the thermal history. Since temperature measurements beneath the surface are difficult, estimates are obtained from computational thermo-mechanical models calibrated against traces left in the sample revealed after etching, such as the trace of the melt pool boundary. Here we examine the question of how reliable thermal histories computed from a model that reproduces the melt pool trace are. To this end, we perform experiments in which one of two different laser beams moves with constant velocity and power over a substrate of 17-4PH SS or Ti-6Al-4V, with low enough power to avoid generating a keyhole. We find that thermal histories appear to be reliably computed provided that (a) the power density distribution of the laser beam over the substrate is well characterized, and (b) convective heat transport effects are accounted for. Poor control of the laser beam leads to potentially multiple three-dimensional melt pool shapes compatible with the melt pool trace, and therefore to multiple potential thermal histories. Ignoring convective effects leads to results that are inconsistent with experiments, even for the mild melt pools here.
The addition of active, nonlinear, and nonreciprocal functionalities to passive piezoelectric acoustic wave technologies could enable all-acoustic and therefore ultra-compact radiofrequency signal processors. Toward this goal, we present a heterogeneously integrated acoustoelectric material platform consisting of a 50 nm indium gallium arsenide epitaxial semiconductor film in direct contact with a 41° YX lithium niobate piezoelectric substrate. We then demonstrate three of the main components of an all-acoustic radiofrequency signal processor: passive delay line filters, amplifiers, and circulators. Heterogeneous integration allows for simultaneous, independent optimization of the piezoelectric-acoustic and electronic properties, leading to the highest performing surface acoustic wave amplifiers ever developed in terms of gain per unit length and DC power dissipation, as well as the first-ever demonstrated acoustoelectric circulator with an isolation of 46 dB with a pulsed DC bias. Finally, we describe how the remaining components of an all-acoustic radiofrequency signal processor are an extension of this work.
The CSISAR tool is GUI based and very simple to use. The algorithms are robust, and the unique processing flows, that the user is stepped through, virtually eliminate the possibility of error in GEOINT production. An integrated data manager is a key part of the CSISAR system. This data manager keeps track of the data available to a user and informs the user of what data is available and what can be done with that data. This keeps the user from having to be trained in the nuances of the algorithms. CSISAR also has an integrated product manager, which helps the user identify, view and manage previously made products. CSISAR was originally developed in 2010-2011 as a Windows based system. It was updated in 2015 to be a Linux based system. This SAND report is intended to make the Product Description and User’s Guide for CSISAR (originally included within the software) more widely available. New is a brief addition of Linux-specific installation details.
Dennett, Cody A.; Dacus, Benjamin R.; Barr, Christopher M.; Clark, Trevor; Bei, Hongbin; Zhang, Yanwen; Short, Michael P.; Hattar, Khalid M.
Defects and microstructural features spanning the atomic level to the microscale play deterministic roles in the expressed properties of materials. Yet studies of material evolution in response to environmental stimuli most often correlate resulting performance with one dominant microstructural feature only. Here, the dynamic evolution of swelling in a series of Ni-based concentrated solid solution alloys under high-temperature irradiation exposure is observed using continuous, in situ measurements of thermoelastic properties in bulk specimens. Unlike traditional evaluation techniques which account only for volumetric porosity identified using electron microscopy, direct property evaluation provides an integrated response across all defect length scales. In particular, the evolution in elastic properties during swelling is found to depend significantly on the entire size spectrum of defects, from the nano- to meso-scales, some of which are not resolvable in imaging. Observed changes in thermal transport properties depend sensitively on the partitioning of electronic and lattice thermal conductivity. This emerging class of in situ experiments, which directly measure integrated performance in relevant conditions, provides unique insight into material dynamics otherwise unavailable using traditional methods.
The atomic cluster expansion is a general polynomial expansion of the atomic energy in multi-atom basis functions. Here we implement the atomic cluster expansion in the performant C++ code PACE that is suitable for use in large-scale atomistic simulations. We briefly review the atomic cluster expansion and give detailed expressions for energies and forces as well as efficient algorithms for their evaluation. We demonstrate that the atomic cluster expansion as implemented in PACE shifts a previously established Pareto front for machine learning interatomic potentials toward faster and more accurate calculations. Moreover, general purpose parameterizations are presented for copper and silicon and evaluated in detail. We show that the Cu and Si potentials significantly improve on the best available potentials for highly accurate large-scale atomistic simulations.
Mellors, Robert J.; Abbott, Robert A.; Steedman, David; Podrasky, David; Pitarka, Arben
Fiber optic distributed acoustic sensors (DAS) are becoming a widely used tool for seismic sensing. Here we examine recordings of two subsurface chemical explosions, DAG-1 and DAG-3, each of which was about one metric ton (TNT equivalent), that were recorded from a helical fiber installed in two boreholes 80 m away from the source location. Several clear phases including the initial P wave, a weak S wave, and a surface reflected P wave are observed on the helical DAS data. We estimate a velocity model using arrival times measured from the fiber. The DAS waveform data were compared with colocated accelerometers at specific depths in both frequency and time domains. The spectra of the DAS data matched spectra estimated from the accelerometer records. Comparisons of observed waveform shape between the accelerometer records and the fiber measurements (strain-rate) show reasonable agreement except for the data near the event depth. The DAS data and the accelerometer agreed in relative amplitudes but we had difficulties in matching absolute amplitudes, possibly due to errors in metadata. Synthetic strain-rate waveforms were calculated using a 2D wavenumber algorithm and matched the waveform shape and relative amplitudes. In general, DAS is effective at recording strong ground motions at high spatial density. Comparison of the synthetic seismograms with observed data indicate that the waveforms are not consistent with a pure isotropic explosion source and that the observed S waves originate from very near the source region.
Cerjan, Alexander W.; Jorg, Christina; Vaidya, Sachin; Augustine, Shyam; Benalcazar, Wladimir A.; Hsu, Chia W.; Von Freymann, Georg; Rechtsman, Mikael C.
In the past decade, symmetry-protected bound states in the continuum (BICs) have proven to be an important design principle for creating and enhancing devices reliant upon states with high-quality (Q) factors, such as sensors, lasers, and those for harmonic generation. However, as we show, current implementations of symmetry-protected BICs in photonic crystal slabs can only be found at the center of the Brillouin zone and below the Bragg diffraction limit, which fundamentally restricts their use to single-frequency applications. By microprinting a three-dimensional (3D) photonic crystal structure using two-photon polymerization, we demonstrate that this limitation can be overcome by altering the radiative environment surrounding the slab to be a 3D photonic crystal. This allows for the protection of a line of BICs by embedding it in a symmetry bandgap of the crystal. This concept substantially expands the design freedom available for developing next-generation devices with high-Q states.
Many innate immune receptors function collaboratively to detect and elicit immune responses to pathogens, but the physical mechanisms that govern the interaction and signaling crosstalk between the receptors are unclear. In this study, we report that the signaling crosstalk between Fc gamma receptor (FcγR) and Toll-like receptor (TLR)2/1 can be overall synergistic or inhibitory depending on the spatial proximity between the receptor pair on phagosome membranes. Using a geometric manipulation strategy, we physically altered the spatial distribution of FcγR and TLR2 on single phagosomes. We demonstrate that the signaling synergy between FcγR and TLR2/1 depends on the proximity of the receptors and decreases as spatial separation between them increases. However, the inhibitory effect from FcγRIIb on TLR2-dependent signaling is always present and independent of receptor proximity. The overall cell responses are an integration from these two mechanisms. This study presents quantitative evidence that the nanoscale proximity between FcγR and TLR2 functions as a key regulatory mechanism in their signaling crosstalk.
LaFleur, Chris B.; Taylor, Gabriel; Putorti Jr., Anthony D.; Salley, Mark H.
This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena for low-voltage metal enclosed switchgear containing aluminum conductors. This report covers full-scale laboratory experiments using representative nuclear power plant (NPP) three-phase electrical equipment. Electrical, thermal, and pressure data were recorded for each experiment and documented in this report. This report covers experiments performed on two low-voltage switchgear units with each unit consisting of two vertical sections. The data collected supports characterization of the low-voltage HEAF hazard and these results will be used to support potential improvements in fire probabilistic risk assessment (PRA) methods. The experiments were performed at KEMA Labs located in Chalfont, Pennsylvania. The experimental design, setup, and execution were completed by staff from the NRC, the National Institute of Standards and Technology (NIST), Sandia National Laboratories (SNL) and KEMA. In addition, representatives from the Electric Power Research Institute (EPRI) observed some of the experimental setup and execution. The HEAF experiments were performed between August 26 and Augsut 29, 2019 on nearidentical Westinghouse Type DS low-voltage metal-enclosed indoor switchgear. The threephase arcing fault was initiated on the aluminum main bus or in select cases on the copper bus stabs near the breaker. These experiments used either nominal 480 volts AC or 600 volts AC. Durations of the experiments ranged from approximately 0.4 s to 8.3 s with fault currents ranging from approximately 9.2 kA to 19.3 kA. Real-time electrical operating conditions, including voltage, current and frequency, were measured during the experiments. Heat fluxes and incident energies were measured with plate thermometers, radiometers, and slug calorimeters at various locations around the electrical enclosures. Environmental measurements of breakdown, conductivity and electromagnetics were also taken. The experiments were documented with normal and high-speed videography, infrared imaging and photography. The results, while limited, indicated the difficulty in maintaining and sustaining low-voltage arcs on aluminum components of sufficient duration and at a single point as observed operating experience.
Curwen, Christopher A.; Addamane, Sadhvikas J.; Reno, John L.; Shahili, Mohammad; Kawamura, Jonathan H.; Briggs, Ryan M.; Karasik, Boris S.; Williams, Benjamin S.
We compare the performance of 10 and 5 μm thick metal-metal waveguide terahertz quantum-cascade laser ridges operating around 2.7 THz and based on a 4-well phonon depopulation active region design. Thanks to reduced heat dissipation and lower thermal resistance, the 5 μm thick material shows an 18 K increase in continuous wave operating temperature compared to the 10 μm material, despite a lower maximum pulsed-mode operating temperature and a larger input power density. A maximum continuous wave operating temperature of 129 K is achieved using the 5 μm thick material and a 15 μm wide ridge waveguide, which lased up to 155 K in the pulsed mode. The use of thin active regions is likely to become increasingly important to address the increasing input power density of emerging 2- and 3-well active region designs that show the highest pulsed operating temperatures.
Ing, Nicole; Deng, Kai; Chen, Yan; Aulitto, Martina; Gin, Jennifer W.; Pham, Thanh L.; Petzold, Christopher J.; Singer, Steve W.; Bowen, Benjamin; Sale, Kenneth L.; Simmons, Blake A.; Singh, Anup K.; Adams, Paul D.; Northen, Trent R.
Lignocellulosic biomass is composed of three major biopolymers: cellulose, hemicellulose and lignin. Analytical tools capable of quickly detecting both glycan and lignin deconstruction are needed to support the development and characterization of efficient enzymes/enzyme cocktails. Previously we have described nanostructure-initiator mass spectrometry-based assays for the analysis of glycosyl hydrolase and most recently an assay for lignin modifying enzymes. Here we integrate these two assays into a single multiplexed assay against both classes of enzymes and use it to characterize crude commercial enzyme mixtures. Application of our multiplexed platform based on nanostructure-initiator mass spectrometry enabled us to characterize crude mixtures of laccase enzymes from fungi Agaricus bisporus (Ab) and Myceliopthora thermophila (Mt) revealing activity on both carbohydrate and aromatic substrates. Using time-series analysis we determined that crude laccase from Ab has the higher GH activity and that laccase from Mt has the higher activity against our lignin model compound. Inhibitor studies showed a significant reduction in Mt GH activity under low oxygen conditions and increased activities in the presence of vanillin (common GH inhibitor). Ultimately, this assay can help to discover mixtures of enzymes that could be incorporated into biomass pretreatments to deconstruct diverse components of lignocellulosic biomass.