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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Understanding and Overcoming Water-induced Interfacial Degradation in Si Modules (Final Technical Report)

Moisture ingress is an established issue for photovoltaic module durability. Durability studies probing moisture effects typically evaluate performance losses at the module level, attributing global power losses to the overall humidity condition of the test environment while leaving local module behavior unknown. This project successfully develops an in situ short-wave infrared probe of moisture content in PV modules with demonstrated detection limits better than 100 ppm in EVA-encapsulated Al-BSF and PERC architectures (66 µg/cm3) and applicability across the range of terrestrial conditions. Combining this optical moisture quantification method (water reflectometry detection, WaRD) with peel testing of interfaces, biased photoluminescence imaging of performance, and first principles computation, we correlate module moisture content and cell performance over the course of accelerated damp heat tests. By performing multi-level humidity and thermal accelerated testing over thousands of hours (0, 65 and 85% RH and 25, 65, and 85°C), we are able to attribute effects of individual environmental stresses and the dependence on module architecture. Using first-principles computational chemistry, we find that the decomposition of EVA to acetic acid (Norrish II) is thermodynamically preferred over a pathway to acetaldehyde (Norrish I), elucidating the underlying chemistry of encapsulant degradation. We also find it is likely that water segregates to the stable interfaces of the cell, especially the SiNx/EVA interface. We find that moisture is strongly correlated with reduction in adhesion at the interfaces of the cells, particularly at Ag fingers. We show uniquely that the peel strength required to delaminate the encapsulant from the front of the cell depends not only on the exposure to a high heat and humid environment, but also to the moisture content during the mechanical testing, indicating an important interaction between when mechanical stresses are faced in terms of the moisture content of the module and its durability. We find that the background sheet resistance (that is, the sheet resistance rise not attributable to finger interruptions or cracks) is substantially higher in the backsheet mini-modules vs glass-glass packages when humidity and temperature are faced. This increase in power loss due to the background resistance increase over time in damp heat in glass-backsheet modules resulted in ~3-4% larger decrease in relative PCE compared to glass-glass modules. In glass-backsheet modules, the effect of the moisture dose alone is comparable or greater than that of the combined temperature and water term, suggesting that glass-backsheet modules are overall more susceptible to moisture induced performance loss. Finally, we show that thin film PV modules are amenable to WaRD measurement, based on the ability to detect moisture in POE encapsulants or in the cell stack itself. The ease of WaRD measurement and its few requirements on the bill of materials should enable broad applicability of this technique for studying the effects of moisture in PV.

14 SOLAR ENERGY↗
DOE OSTI2021

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

This report details the results of a three-fold investigation of sensitivity analysis (SA) for machine learning (ML) explainability (MLE): (1) the mathematical assessment of the fidelity of an explanation with respect to a learned ML model, (2) quantifying the trustworthiness of a prediction, and (3) the impact of MLE on the efficiency of end-users through multiple users studies. We focused on the cybersecurity domain as the data is inherently non-intuitive. As ML is being using in an increasing number of domains, including domains where being wrong can elicit high consequences, MLE has been proposed as a means of generating trust in a learned ML models by end users. However, little analysis has been performed to determine if the explanations accurately represent the target model and they themselves should be trusted beyond subjective inspection. Current state-of-the-art MLE techniques only provide a list of important features based on heuristic measures and/or make certain assumptions about the data and the model which are not representative of the real-world data and models. Further, most are designed without considering the usefulness by an end-user in a broader context. To address these issues, we present a notion of explanation fidelity based on Shapley values from cooperative game theory. We find that all of the investigated MLE explainability methods produce explanations that are incongruent with the ML model that is being explained. This is because they make critical assumptions about feature independence and linear feature interactions for computational reasons. We also find that in deployed, explanations are rarely used due to a variety of reason including that there are several other tools which are trusted more than the explanations and there is little incentive to use the explanations. In the cases when the explanations are used, we found that there is the danger that explanations persuade the end users to wrongly accept false positives and false negatives. However, ML model developers and maintainers find the explanations more useful to help ensure that the ML model does not have obvious biases. In light of these findings, we suggest a number of future directions including developing MLE methods that directly model non-linear model interactions and including design principles that take into account the usefulness of explanations to the end user. We also augment explanations with a set of trustworthiness measures that measure geometric aspects of the data to determine if the model output should be trusted.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Nu Tools: Exploring Practical Roles for Neutrinos in Nuclear Energy and Security

For decades, physicists have used neutrinos from nuclear reactors to advance basic science. These pursuits have inspired many ideas for application of neutrino detectors in nuclear energy and security. While developments in neutrino detectors are now making some of these ideas technically feasible, their value in the context of real needs and constraints has been unclear. This report seeks to help focus the picture of where neutrino technology may find practical roles in nuclear energy and security. This report is the final product of the Nu Tools study, commissioned in 2019 by the DOE National Nuclear Security Administration (NNSA) Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D). The study was conducted over two years by a group of neutrino physicists and nuclear engineers. A central theme of the study and this report is that useful application of neutrinos will depend not only on advancing physics and technology but also on understanding the needs and constraints of potential end-users. The Study Approach emphasized broad end-user engagement. The major effort, undertaken from May to December 2020, was a series of engagements with the wider nuclear energy and security communities. Interviews with 41 experts revealed points of common understanding, which this report captures in three Cross-Cutting Findings, a Framework for Evaluating Utility, and seven Use Case Findings. The report concludes with two Recommendations. The findings and recommendations are summarized below. The respective ordering within each category does not represent a prioritization or implied value judgement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Electronic Structure Theory and Novel Materials

This grant supported research on electronic structure and materials theory, with focus on three main issues: (i) novel techniques to deal with correlation in the electronic ground-state, (ii) topological materials, (iii) the phase diagram of lattice spin models. Regarding (i), we applied to the homogeneous electron liquid an approach that we previously developed in the context of molecular systems. In this scheme the electronic occupation probabilities and the natural spin orbitals are used to construct an approximate two-body density matrix for the electronic ground-state. Regarding (ii) we used standard electronic structure methods based on density functional theory to model topological materials and interpret experimental observations. Finally, regarding (iii) we further developed a numerical approach to compute the renormalized couplings within real space renormalization group theory in the context of lattice spin models. The main findings were the following. (i) We found that with our approximate two-body density matrix, which works well for small molecules, is not sufficiently accurate for condensed phase systems. Missing a systematic way of improving on the adopted approximations, we decided not to pursue this approach. (ii) We performed two studies. In one, we investigated the influence of Te defects on the topological properties of a WTe2 monolayer, finding that while Te vacancies, even in modest concentration, destroy the topological character, Te adatoms do not, consistent with a recent experiment. In another study, we predicted Weyl semimetal character and strong anomalous Hall effect in the Heusler compensated ferrimagnet Ti2MnAl. (iii) We developed a new Monte Carlo method to do real space renormalization group calculations for lattice spin models. We subsequently extended the scheme to deal with lattice spin models in presence of quenched disorder, finding that the approach can distinguish systems with finite and strong disorder. In the finite disorder case, the method allows one to find with good approximation the critical coupling distribution and the critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Evolution of Two-Phase High Explosive Reactive Flow [Slides]

Reactive hydrodynamics involve rapid conversion of reactants to products along a detonation wave and needs a closure rule: P-T equilibrium. To calculate P-T equilibrium, we use a root finding method, which can be a computational bottleneck. We evolve the guess for the root finder rather than using the previous value to reduce iterations. Evolving products volume fraction Φ p for an initial root finding guess does reduce root finding iterations and seems to give the best results immediately following a detonation wave (reducing root finding iterations from 5 to 2).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

43-0434 Bridge Inspection Report 2021

The documentation includes the following: 1. 2021 NMDOT Bridge Inspection Report including Element Level Data Collection (in digital formats prepared by NMSU)--conforms to the National Bridge Inspection Standards and AASHTO Manual for Bridge Element Inspection; 2. 2021 Supplemental Report (in digital formats prepared by NMSU)--provides detailed information related to current condition of major bridge components; 3. 2021 Inspection Pictures (in digital format prepared by NMSU); 4. 2021 Delamination Map (in digital format prepared by LANL). During the 2021 inspection, three critical findings were reported to our LANL contact, Mr. Jonathan Stein, by text and/or email on June 26, 2021. 1. The south joint of the bridge had a modular section of the joint that could potentially come loose during the passing of vehicles. This was reported as a critical finding for safety. If the modular section becomes dislodged or deformed it could pose a serious hazard that could result in a punctured tire to vehicles, motorcyclists and/or bicyclist causing drivers/riders to lose control; 2. The bracket plate located at the north end of the bridge on the pedestrian walkway was corroded through and provides little protection to pedestrians and bicyclists. This was reported as a critical finding for safety to prevent injuries to people; 3. The north approach rail has three missing posts. These posts help ensure that traffic is redirected and the energy is absorbed by the rail. This was reported as a critical finding for safety. Additionally, the approach rail is on a curve with a nearby drop off. Immediate repair is recommended. Based on the 2021 inspection, the bridge deck is rated in "fair" condition. The chain drag performed on the deck identified several areas with delamination that are concentrated near the expansion joints, in the closure joint of the deck near the bridge centerline, and at the south end of the northbound lanes. The chain drag performed during the 2021 inspection revealed 215,333 sq. in. (1495 sq. ft) of delaminations and patched areas (not including the sidewalk). This is approximately a 600% increase from 2019. It is recommended that the delaminations and spalls with exposed rebar be repaired. The "delaminated area" map for the 2021 inspection is provided in the supplemental report.

42 ENGINEERING↗
DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Manipulation of Geographic Information in Global Seismology

Geographic data, such as seismic event locations, station locations, etc., are generally given in geographic latitude Φ ’, longitude θ , and depth below sea level, ζ , using the WGS84 ellipsoid as a reference. In software systems that use this type of geographic data, it is necessary to manipulate the data mathematically in order to perform such tasks as finding the angular distance or azimuth from one point to another, to find an array of points along a great circle, to rotate a point about a pole of rotation, to move a point some angular distance in a specified direction, to find the intersections of two great circles or to find the intersections of a great circle and a small circle. In this paper, equations are presented that convert geographic locations first to geocentric coordinates and then to Earth-centered Cartesian coordinates where many mathematical manipulations can be performed conveniently and efficiently.

58 GEOSCIENCES↗
DOE OSTI2026

Diesel Fuel Consumption in Prominent U.S. Open-Pit Mines: Site-Level Estimates

This report presents a comprehensive framework for estimating diesel fuel consumption and prices at open-pit mines in the United States. The framework includes transparent methods for calculating site-level diesel energy use when direct reporting is unavailable, and a structured confidence evaluation for each method. The framework is demonstrated to estimate current diesel consumption at 21 open-pit mines in the United States. Initial findings support ongoing efforts to strengthen the competitiveness and security of the U.S. industrial base by supporting data-driven supply chain analysis and decision-making, improved transparency in mining sector energy use, and targeted deployment of energy innovation and cost-reduction strategies. Future updates to the dataset—coupled with expanded data transparency and method validation—will help ensure that the findings remain relevant as the sector continues to evolve.

02 PETROLEUM↗
DOE OSTI2019

Resource Concentration Modulates the Fate of Dissimilated Nitrogen in a Dual-Pathway Actinobacterium

Respiratory ammonification and denitrification are two evolutionarily unrelated dissimilatory nitrogen (N) processes central to the global N cycle, the activity of which is thought to be controlled by carbon (C) to nitrate (NO 3 -) ratio. Here we find that Intrasporangium calvum C5, a novel dual-pathway denitrifier/respiratory ammonifier, disproportionately utilizes ammonification rather than denitrification when grown under low C concentrations, even at low C:NO 3 - ratios. This finding is in conflict with the paradigm that high C:NO 3 - ratios promote ammonification and low C:NO 3 - ratios promote denitrification. We find that the protein atomic composition for denitrification modules (NirK) are significantly cost minimized for C and N compared to ammonification modules (NrfA), indicating that limitation for C and N is a major evolutionary selective pressure imprinted in the architecture of these proteins. The evolutionary precedent for these findings suggests ecological importance for microbial activity as evidenced by higher growth rates when I. calvum grows predominantly using its ammonification pathway and by assimilating its end-product (ammonium) for growth under ammonium-free conditions. Genomic analysis of I. calvum further reveals a versatile ecophysiology to cope with nutrient stress and redox conditions. Metabolite and transcriptional profiles during growth indicate that enzyme modules, NrfAH and NirK, are not constitutively expressed but rather induced by nitrite production via NarG. Mechanistically, our results suggest that pathway selection is driven by intracellular redox potential (redox poise), which may be lowered when resource concentrations are low, thereby decreasing catalytic activity of upstream electron transport steps (i.e., the bc 1 complex) needed for denitrification enzymes. Our work advances our understanding of the biogeochemical flexibility of N-cycling organisms, pathway evolution, and ecological food-webs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Adiabatic Quantum Computation Applied to Deep Learning Networks

Training deep learning networks is a difficult task due to computational complexity, and this is traditionally handled by simplifying network topology to enable parallel computation on graphical processing units (GPUs). However, the emergence of quantum devices allows reconsideration of complex topologies. We illustrate a particular network topology that can be trained to classify MNIST data (an image dataset of handwritten digits) and neutrino detection data using a restricted form of adiabatic quantum computation known as quantum annealing performed by a D-Wave processor. We provide a brief description of the hardware and how it solves Ising models, how we translate our data into the corresponding Ising models, and how we use available expanded topology options to explore potential performance improvements. Although we focus on the application of quantum annealing in this article, the work discussed here is just one of three approaches we explored as part of a larger project that considers alternative means for training deep learning networks. The other approaches involve using a high performance computing (HPC) environment to automatically find network topologies with good performance and using neuromorphic computing to find a low-power solution for training deep learning networks. Our results show that our quantum approach can find good network parameters in a reasonable time despite increased network topology complexity; that HPC can find good parameters for traditional, simplified network topologies; and that neuromorphic computers can use low power memristive hardware to represent complex topologies and parameters derived from other architecture choices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗
DOE OSTI2025

Machine Learning-Driven Conservative-to-Primitive Conversion in Hybrid Piecewise Polytropic and Tabulated Equations of State

We present a novel machine learning (ML)-based method to accelerate conservative-to-primitive inversion, focusing on hybrid piecewise polytropic and tabulated equations of state. Traditional root-finding techniques are computationally expensive, particularly for large-scale relativistic hydrodynamics simulations. To address this, we employ feedforward neural networks (NNC2PS and NNC2PL), trained in PyTorch (2.0+) and optimized for GPU inference using NVIDIA TensorRT (8.4.1), achieving significant speedups with minimal accuracy loss. The NNC2PS model achieves 𝐿 1 and 𝐿 ∞ errors of 4.54 × 10 −7 and 3.44 × 10−6, respectively, while the NNC2PL model exhibits even lower error values. TensorRT optimization with mixed-precision deployment substantially accelerates performance compared to traditional root-finding methods. Specifically, the mixed-precision TensorRT engine for NNC2PS achieves inference speeds approximately 400 times faster than a traditional single-threaded CPU implementation for a dataset size of 1,000,000 points. Ideal parallelization across an entire compute node in the Delta supercomputer (dual AMD 64-core 2.45 GHz Milan processors and 8 NVIDIA A100 GPUs with 40 GB HBM2 RAM and NVLink) predicts a 25-fold speedup for TensorRT over an optimally parallelized numerical method when processing 8 million data points. Moreover, the ML method exhibits sub-linear scaling with increasing dataset sizes. We release the scientific software developed, enabling further validation and extension of our findings. By exploiting the underlying symmetries within the equation of state, these findings highlight the potential of ML, combined with GPU optimization and model quantization, to accelerate conservative-to-primitive inversion in relativistic hydrodynamics simulations.

conservative-to-primitive conversion↗
DOE OSTI2016

Bright [C ii] and dust emission in three z > 6.6 quasar host galaxies observed by ALMA

We present ALMA detections of the [C ii] 158 μm emission line and the underlying far-infrared (FIR) continuum of three quasars at 6.6 < z < 6.9 selected from the VIKING survey. The [C ii] line fluxes range between 1.6 and 3.4 Jy km s{sup −1} ([C ii] luminosities ∼(1.9–3.9) × 10{sup 9} L{sub ⊙}). We measure continuum flux densities of 0.56–3.29 mJy around 158 μm (rest frame), with implied FIR luminosities of (0.6–7.5) × 10{sup 12} L{sub ⊙} and dust masses M{sub d} = (0.7–24) × 10{sup 8} M{sub ⊙}. In one quasar we derive a dust temperature of 30{sub −9}{sup +12} K from the continuum slope, below the canonical value of 47 K. Assuming that the [C ii] and continuum emission are powered by star formation, we find star formation rates from 100 to 1600 M{sub ⊙} yr{sup −1} based on local scaling relations. The L{sub [C ii]}/L{sub FIR} ratios in the quasar hosts span a wide range from (0.3–4.6) × 10{sup −3}, including one quasar with a ratio that is consistent with local star-forming galaxies. We find that the strength of the L{sub [C ii]} and 158 μm continuum emission in z ≳ 6 quasar hosts correlates with the quasar’s bolometric luminosity. In one quasar, the [C ii] line is significantly redshifted by ∼1700 km s{sup −1} with respect to the Mg ii broad emission line. Comparing to values in the literature, we find that, on average, the Mg ii is blueshifted by 480 km s{sup −1} (with a standard deviation of 630 km s{sup −1}) with respect to the host galaxy redshift, i.e., one of our quasars is an extreme outlier. Through modeling we can rule out a flat rotation curve for our brightest [C ii] emitter. Finally, we find that the ratio of black hole mass to host galaxy (dynamical) mass is higher by a factor of 3–4 (with significant scatter) than local relations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Shadow of a colossus: A z = 2.44 galaxy protocluster detected in 3D Lyα forest tomographic mapping of the cosmos field

Using moderate-resolution optical spectra from 58 background Lyman-break galaxies and quasars at z∼2.3--3 within a 11.′5 × 13.′5 area of the COSMOS field (∼1200 deg{sup −2} projected area density or ∼2.4 h{sup −1} Mpc mean transverse separation), we reconstruct a 3D tomographic map of the foreground Lyα forest absorption at 2.2 < z < 2.5 with an effective smoothing scale of ϵ{sub 3D}≈2.5 h{sup −1} Mpc comoving. Comparing with 61 coeval galaxies with spectroscopic redshifts in the same volume, we find that the galaxy positions are clearly biased toward regions with enhanced intergalactic medium (IGM) absorption in the tomographic map. We find an extended IGM overdensity with deep absorption troughs at z = 2.45 associated with a recently discovered galaxy protocluster at the same redshift. Based on simulations matched to our data, we estimate the enclosed dark matter mass within this IGM overdensity to be M{sub dm}(z=2.45)=(1.1±0.6)×10{sup 14} h{sup −1}M{sub ⊙}, and argue based on this mass and absorption strength that it will form at least one z ∼ 0 galaxy cluster with M(z=0)=(3±1.5)×10{sup 14} h{sup −1}M{sub ⊙}, although its elongated nature suggests that it will likely collapse into two separate clusters. We also point out a compact overdensity of six MOSDEF galaxies at z = 2.30 within a r∼1 h{sup −1} Mpc radius and Δz ∼ 0.006, which does not appear to have a large associated IGM overdensity. These results demonstrate the potential of Lyα forest tomography on larger volumes to study galaxy properties as a function of environment, as well as revealing the large-scale IGM overdensities associated with protoclusters or other features of large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

ON POTASSIUM AND OTHER ABUNDANCE ANOMALIES OF RED GIANTS IN NGC 2419

Globular clusters are of paramount importance for testing theories of stellar evolution and early galaxy formation. Strong evidence for multiple populations of stars in globular clusters derives from observed abundance anomalies. A puzzling example is the recently detected Mg–K anticorrelation in NGC 2419. We perform Monte Carlo nuclear reaction network calculations to constrain the temperature–density conditions that gave rise to the elemental abundances observed in this elusive cluster. We find a correlation between stellar temperature and density values that provide a satisfactory match between simulated and observed abundances in NGC 2419 for all relevant elements (Mg, Si, K, Ca, Sc, Ti, and V). Except at the highest densities (ρ ≳ 10{sup 8} g cm{sup −3}), the acceptable conditions range from ≈100 MK at ≈10{sup 8} g cm{sup −3} to ≈200 MK at ≈10{sup −4} g cm{sup −3}. This result accounts for uncertainties in nuclear reaction rates and variations in the assumed initial composition. We review hydrogen-burning sites and find that low-mass stars, asymptotic giant branch (AGB) stars, massive stars, or supermassive stars cannot account for the observed abundance anomalies in NGC 2419. Super-AGB stars could be viable candidates for the polluter stars if stellar model parameters can be fine-tuned to produce higher temperatures. Novae, involving either CO or ONe white dwarfs, could be interesting polluter candidates, but a current lack of low-metallicity nova models precludes firmer conclusions. We also discuss whether additional constraints for the first-generation polluters can be obtained by future measurements of oxygen, or by evolving models of second-generation low-mass stars with a non-canonical initial composition.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Classical Oe stars in the field of the small magellanic cloud

We present 29 ± 1 classical Oe stars from RIOTS4 (the Runaways and Isolated O Type Star Spectroscopic Survey of the SMC), a spatially complete, spectroscopic survey of Small Magellanic Cloud (SMC) field OB stars. The two earliest are O6e stars, and four are earlier than any Milky Way (MW) Oe stars. We also find ten Ope stars, showing He i infill and/or emission; five appear to be at least as hot as ∼O7.5e stars. The hottest, star 77616, shows He ii disk emission, suggesting that even the hottest O stars can form decretion disks, and offers observational support for theoretical predictions that the hottest, fastest rotators can generate He{sup +}-ionizing atmospheres. Our data also demonstrate that Ope stars correspond to Oe stars earlier than O7.5e with strong disk emission. We find that in the SMC, Oe stars extend to earlier spectral types than in the MW, and our SMC Oe/O frequency, 0.26 ± 0.04, is much greater than the MW value, 0.03 ± 0.01. These results are consistent with angular momentum transport by stronger winds suppressing decretion disk formation at higher metallicity. In addition, the Oe star frequency in the SMC field is indistinguishable from that for clusters, which is consistent with the similarity between rotation rates in these environments, and contrary to the pattern for MW rotation rates. Thus, our findings strongly support the viscous decretion disk model and confirm that Oe stars are the high-mass extension of the Be phenomenon. Additionally, we find that Fe ii emission occurs among Oe stars later than O7.5e with massive disks, and we revise a photometric criterion for identifying Oe stars to J−[3.6]⩾0.1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Compact binary merger rates: Comparison with LIGO/Virgo upper limits

We compare evolutionary predictions of double compact object merger rate densities with initial and forthcoming LIGO/Virgo upper limits. We find that: (i) Due to the cosmological reach of advanced detectors, current conversion methods of population synthesis predictions into merger rate densities are insufficient. (ii) Our optimistic models are a factor of 18 below the initial LIGO/Virgo upper limits for BH–BH systems, indicating that a modest increase in observational sensitivity (by a factor of ∼2.5) may bring the first detections or first gravitational wave constraints on binary evolution. (iii) Stellar-origin massive BH–BH mergers should dominate event rates in advanced LIGO/Virgo and can be detected out to redshift z ≃ 2 with templates including inspiral, merger, and ringdown. Normal stars (<150 M{sub ⊙}) can produce such mergers with total redshifted mass up to M{sub tot,z}≃400 M{sub ⊙}. (iv) High black hole (BH) natal kicks can severely limit the formation of massive BH–BH systems (both in isolated binary and in dynamical dense cluster evolution), and thus would eliminate detection of these systems even at full advanced LIGO/Virgo sensitivity. We find that low and high BH natal kicks are allowed by current observational electromagnetic constraints. (v) The majority of our models yield detections of all types of mergers (NS–NS, BH–NS, BH–BH) with advanced detectors. Numerous massive BH–BH merger detections will indicate small (if any) natal kicks for massive BHs.

79 ASTRONOMY AND ASTROPHYSICS↗