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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

On the accuracy of Hipparcos using binary stars as a calibration tool

Stellar binary systems, specifically those that present the most accurate available orbital elements, are a reliable tool to test the accuracy of astrometric observations. We selected all 35 binaries with these characteristics. Our objective is to provide standard uncertainties for the positions and parallaxes measured by Hipparcos relative to this trustworthy set, as well as to check supposed correlations between several parameters (measurement residuals, positions, magnitudes, and parallaxes). In addition, using the high-confidence subset of visual–spectroscopic binaries, we implemented a validation test of the Hipparcos trigonometric parallaxes of binary systems that allowed the evaluation of their reliability. Standard and non-standard statistical analysis techniques were applied in order to achieve well-founded conclusions. In particular, errors-in-variables models such as the total least-squares method were used to validate Hipparcos parallaxes by comparison with those obtained directly from the orbital elements. Previously, we executed Thompson's τ technique in order to detect suspected outliers in the data. Furthermore, several statistical hypothesis tests were carried out to verify if our results were statistically significant. A statistically significant trend indicating larger Hipparcos angular separations with respect to the reference values in 5.2 ± 1.4 mas was found at the 10{sup −8} significance level. Uncertainties in the polar coordinates θ and ρ of 1.°8 and 6.3 mas, respectively, were estimated for the Hipparcos observations of binary systems. We also verified that the parallaxes of binary systems measured in this mission are absolutely compatible with the set of orbital parallaxes obtained from the most accurate orbits at least at the 95% confidence level. This methodology allows us to better estimate the accuracy of Hipparcos observations of binary systems. Indeed, further application to the data collected by Gaia should yield a standard procedure to compare both data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Interannual variability in global mean sea level estimated from the CESM Large and Last Millennium Ensembles

To better understand global mean sea level (GMSL) as an indicator of climate variability and change, contributions to its interannual variation are quantified in the Community Earth System Model (CESM) Large Ensemble and Last Millennium Ensemble. Consistent with expectations, the El Niño/Southern Oscillation (ENSO) is found to exert a strong influence due to variability in rainfall over land (PL) and terrestrial water storage (TWS). Other important contributors include changes in ocean heat content (OHC) and precipitable water (PW). The temporal evolution of individual contributing terms is documented. The magnitude of peak GMSL anomalies associated with ENSO generally are of the order of 0.5 mm·K -1 with significant inter-event variability, with a standard deviation (σ) that is about half as large The results underscore the exceptional rarity of the 2010/2011 La Niña-related GMSL drop and estimate the frequency of such an event to be about only once in every 75 years. In addition to ENSO, major volcanic eruptions are found to be a key driver of interannual variability. Associated GMSL variability contrasts with that of ENSO as TWS and PW anomalies initially offset the drop due to OHC reductions but short-lived relative to them. Furthermore, responses up to 25 mm are estimated for the largest eruptions of the Last Millennium.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Uncertainty and Sensitivity Analysis of TREAT Transient Test #15

The U.S. Department of Energy (DOE) is preparing for the resumption of transient testing using the Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory (INL). In order to support the analysis of TREAT operation and experiment planning, the MAMMOTH reactor physics team has recently begun development of uncertainty and sensitivity analysis for the TREAT core simulated via MAMMOTH. MAMMOTH is a high-fidelity three-dimensional transient multi-physics code developed at INL under the DOE-NE Advanced Modeling and Simulation program (NEAMS) [1]. This research is part of the development presenting some initial uncertainty and sensitivity analysis of TREAT Transient Test #15 [2]. In this summary, we employ the Sobol sampling strategy implemented in RAVEN [3] to efficiently perform the sensitivity and uncertainty analysis. The idea is using Sobol functional decomposition with generalized polynomial chaos (gPC) expansions to estimate the responses of interest [4]. The gPC coefficients are then computed via the spectral projection method with sparse grid approach. In addition, this strategy includes evaluation of the second or higher order sensitivity indices, allowing the study of interactions between several input variables. The principal focus of this analysis is to quantify the uncertainties in the total power and maximum fuel temperatures with respect to uncertainties in the initial transient conditions, such as rated power, fuel temperature, graphite fuel density and control rod boron concentration. In addition, both the first order and second order time-dependent sensitivity indices are computed and analyzed. The results show that the interactions between initial control rod boron concentration and the rated power will contribute at most 1% to the total uncertainty of the power peak.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Uncertainty and Sensitivity Analysis of TREAT Transient Test no. 15

The U.S. Department of Energy (DOE) is preparing for the resumption of transient testing using the Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory (INL). In order to support the analysis of TREAT operation and experiment planning, the MAMMOTH reactor physics team has recently begun development of uncertainty and sensitivity analysis for the TREAT core simulated via MAMMOTH. MAMMOTH is a high-fidelity three-dimensional transient multi-physics code developed at INL under the DOE-NE Advanced Modeling and Simulation program (NEAMS). This research is part of the development presenting some initial uncertainty and sensitivity analysis of TREAT Transient Test no. 15. In this summary, we employ the Sobol sampling strategy implemented in RAVEN to efficiently perform the sensitivity and uncertainty analysis. The idea is using Sobol functional decomposition with generalized polynomial chaos (gPC) expansions to estimate the responses of interest. The gPC coefficients are then computed via the sparse grid spectral projection method. In addition, this strategy includes evaluation of the second or higher order sensitivity indices, allowing the study of interactions between several input variables. The principal focus of this analysis is to quantify the uncertainties in the total power and maximum fuel temperatures with respect to uncertainties in the initial transient conditions, such as rated power, fuel temperature, graphite fuel density and control rod boron concentration. In addition, both the first order and second order time-dependent sensitivity indices are computed and analyzed. The results show that the interactions between initial control rod boron concentration and the rated power will contribute at most 1% to the total uncertainty of the power peak.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Low-symmetry polymorph of GaP upends bonding paradigms of metallic high-pressure III–V compounds

Here, the pressure-induced polymorphism of binary octet compounds has long been considered a settled problem although the possible atomic disordering of some phases remains a puzzling observation. Taking GaP as a case study, we conclude, through x-ray microdiffraction and first-principles calculations, that its high-pressure metallic phase (previously reported as being disordered) adopts in fact an ordered base-centered monoclinic structure previously unknown in this class of compounds. The formation of layered patterns with variable degrees of interlayer dimerization, as observed in GaP, marks a paradigm shift of our understanding of ordering in octet high-pressure phases which calls for a more extensive re-examination. A rich polymorphism with fine tuning of chemical and physical properties can be envisioned.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Examination of Mean Stress Calculation Approaches in Rock Mechanics

The mean stress, as a fundamental statistical property of a group of stress data, is essential for stress variability characterisation. However, currently in rock mechanics, the mean stress is customarily and erroneously calculated by separately averaging the principal stress magnitudes and orientations. In order to draw the attention of our community to the appropriate approach for stress variability characterisation, here we compare the customary scalar/vector mean with that obtained by the mathematically rigorous tensorial approach—the Euclidean mean. Calculation of mean stress using both a small group of actual in situ stress measurement results and a large group of simulated stress data (obtained using the combined finite– discrete element method, FEMDEM) demonstrates that the two approaches yield different results. Further investigation of these results shows that the scalar/vector approach may yield non-unique and non-orthogonal mean principal stresses, and these may deviate significantly from those of the Euclidean mean. Our calculations and comparisons reveal that the scalar/ vector approach is deficient because it processes the principal stress magnitudes and orientations separately as independent quantities and ignores the connection between them. Conversely, the tensorial approach appropriately averages the tensors that simultaneously carry not only the information of stress magnitudes and orientations, but also the inherent relations between them. Therefore, arbitrarily using scalar/vector mean stress of in situ stress measurements as input in further rock engineering analyses may yield significantly erroneous results. Finally, we advise that stress data should be statistically processed in a tensorial manner using tensors referred to a common Cartesian coordinate system.

58 GEOSCIENCES↗
DOE OSTI2017

Regulating Multiple Variables To Understand the Nucleation and Growth and Transformation of PbS Nanocrystal Superlattices

Nanocrystals (NCs) can self-assemble into ordered superlattices with collective properties, but the ability for controlling NC assembly remains poorly understandable toward achievement of desired superlattice. This paper regulates several key variables of PbS NC assembly (e.g., NC concentration and solubility, solvent type, evaporation rate, seed mediation and thermal treatment), and thoroughly exploits the nucleation and growth as well as subsequent superlattice transformation of NC assembles and underneath mechanisms. PbS NCs in toluene self-assemble into a single face-centered-cubic (fcc) and body-centered-cubic (bcc) superlattice, respectively, at concentrations ≤17.5 and ≥70 mg/mL, but an intermediate concentration between them causes the coexistence of the two superlattices. Differently, NCs in hexane or chloroform self-assemble into only a single bcc superlattice. Distinct controls of NC assembly in solvent with variable concentrations confirm the NC concentration/solubility mediated nucleation and growth of superlattice, in which an evaporation-induced local gradient of NC concentration causes simultaneous nucleation of the two superlattices. The observation for the dense packing planes of NCs in fast growing fcc rather than bcc reveals the difference of entropic driving forces responsible for the two distinct superlattices. Decelerating the solvent evaporation does not amend the superlattice symmetry, but improves the superlattice crystallinity. In addition to shrinking the superlattice volume, thermal treatment also transforms the bcc to an fcc superlattice at 175 °C. Through a seed-meditated growth, the concentration-dependent superlattice does not change lattice symmetry over the course of continuous growth, whereas the newly nucleated secondary small nuclei through a concentration change have relatively higher surface energy and quickly dissolve in solution, providing additional NC sources for the ripening of the primarily nucleated larger and stable seeds. Finally, the observations under multiple controls of assembly parameters not only provide insights into the nucleation and growth as well as transformation of various superlattice polymorphs but also lay foundation for controlled fabrication of desired superlattice with tailored property.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

Abstract A unified conceptual framework for river corridors requires synthesis of diverse site‐, method‐ and discipline‐specific findings. The river research community has developed a substantial body of observations and process‐specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site‐, scale‐, and mechanism‐specific observations begins the process of synthesis. Machine learning is particularly well‐suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a fifth order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively‐generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favour the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Watersheds and stream networks viewed longitudinally: Example insights from novel spatial portrayals of watershed characteristics

Abstract Longitudinal depictions of watershed structure and characteristics, including topography, stream networks, wetlands, ground water levels, and land use, can provide watershed knowledge and understanding unavailable from standard plan view maps. Three case studies provide examples of knowledge gained by applying longitudinal views of stream networks, watershed hydrologic behavior, and land use distributions. Longitudinal views of mountain stream networks show extreme variability in the slope‐area relationships of low Strahler order streams, large discontinuities in drainage area (large parts of drainage area space are absent in networks), and large variations in network curvature. Longitudinal views of a groundwater‐dominated headwater watershed increase the inference available from limited groundwater observations and clearly reveal how groundwater connections affect the permanence of surface water features and the distribution of vadose zone storage in the landscape. Plotting land uses longitudinally illuminates and allows a quantitative analysis of how land uses are distributed relative to topographic position. Viewing watersheds and stream networks longitudinally can provide new insights into watershed forms and processes and motivate new questions and research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Scaling Relations for Intercalation Induced Damage in Electrodes

Mechanical degradation, owing to intercalation induced stress and microcrack formation, is a key contributor to the electrode performance decay in lithium-ion batteries (LIBs). The stress generation and formation of microcracks are caused by the solid state diffusion of lithium in the active particles. Here in this work, scaling relations are constructed for diffusion induced damage in intercalation electrodes based on an extensive set of numerical experiments with a particle-level description of microcrack formation under disparate operating and cycling conditions, such as temperature, particle size, C-rate, and drive cycle. The microcrack formation and evolution in active particles is simulated based on a stochastic methodology. A reduced order scaling law is constructed based on an extensive set of data from the numerical experiments. The scaling relations include combinatorial constructs of concentration gradient, cumulative strain energy, and microcrack formation. Lastly, the reduced order relations are further employed to study the influence of mechanical degradation on cell performance and validated against the high order model for the case of damage evolution during variable current vehicle drive cycle profiles.

25 ENERGY STORAGE↗
DOE OSTI2014

A proposal for assessing study quality: Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument

The quality of exposure assessment is a major determinant of the overall quality of any environmental epidemiology study. The use of biomonitoring as a tool for assessing exposure to ubiquitous chemicals with short physiologic half-lives began relatively recently. These chemicals present several challenges, including their presence in analytical laboratories and sampling equipment, difficulty in establishing temporal order in cross-sectional studies, short- and longterm variability in exposures and biomarker concentrations, and a paucity of information on the number of measurements required for proper exposure classification. To date, the scientific community has not developed a set of systematic guidelines for designing, implementing and interpreting studies of short-lived chemicals that use biomonitoring as the exposure metric or for evaluating the quality of this type of research for WOE assessments or for peer review of grants or publications. We describe key issues that affect epidemiology studies using biomonitoring data on short-lived chemicals and propose a systematic instrument – the Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument – for evaluating the quality of research proposals and studies that incorporate biomonitoring data on short-lived chemicals. Quality criteria for three areas considered fundamental to the evaluation of epidemiology studies that include biological measurements of short-lived chemicals are described: 1) biomarker selection and measurement, 2) study design and execution, and 3) general epidemiological study design considerations. We recognize that the development of an evaluative tool such as BEES-C is neither simple nor non-controversial. We hope and anticipate that the instrument will initiate further discussion/debate on this topic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Why is it still too warm or cold in my house? Examining the relationships between energy efficient capital and household energy insecurity

Here, this paper examines the relationships between energy efficient (EE) capital technology and household energy insecurity in the United States. The theoretical model of these relationships employs household production theory to capture the demand for and production of household energy services, and a stochastic production frontier approach to describe how having access to and the usage intensity of EE capital technology could help alleviate inefficiency in the production of household energy services. A working hypothesis formulated from the theoretical model posits that having EE capital technology in the home will reduce the level of household energy insecurity experienced. The extent of energy insecurity experienced is inferred from an energy insecurity index value assigned to each household, generated via the application of a dichotomous Rasch model to questions contained in the 2015 Residential Energy Consumption Survey. Noting the potential simultaneous relationship that exists between a household having access to and the usage intensity of EE capital technology and the experience of being energy insecure, an instrumental variables approach was employed to estimate a series of ordered logit models. Results suggest access to EE capital technology in the form of Energy Star® appliances, Energy Star® windows, or a SMART thermostat does not reduce the probability of experiencing a greater level of energy insecurity. Nor does the usage intensity of EE capital. Thus, policy instruments designed to alleviate household energy insecurity may need to go beyond simply helping households obtain EE capital technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Do We Need to Parameterize Mesoscale Convective Organization to Mitigate the MJO-Mean State Trade-Off?

Modifications in cumulus parameterizations that improve Madden-Julian oscillation (MJO) simulation tend to degrade the mean state—known as the MJO-mean state trade-off. The impacts of parameterizing mesoscale convective organization on the relationship between the MJO and the mean state simulation fidelity are examined. A series of experiments are made with a general circulation model that parameterizes the mesoscale convective organization and simulates well both the MJO and the mean state. In the control simulation, a prognostic nondimensional variable (Ω) represents the degree of convective organization. In order to examine the effect of the parameterized convective organization, fixed Ω values are imposed in a series of constrained experiments. The fixed-Ω simulations show a negative relationship between the MJO and the mean state simulation fidelity. The control simulation is deviated from the negative relationship, suggesting the parameterized mesoscale convective organization helps general circulation models to mitigate the MJO-mean state trade-off.

58 GEOSCIENCES↗
DOE OSTI2014

Cryogenic test of the 4 K / 2 K insert for the ARIEL e-Linac cryomodule

The ARIEL project at TRIUMF requires a 50 MeV superconducting electron linac consisting of five nine cell 1.3 GHz cavities divided into three cryomodules with one, two and two cavities in each module respectively. LHe is distributed in parallel to each module at 4 K and at ∼1.2 bar. Each module has a cryogenic insert on board that receives the 4 K liquid and produces 2 K into a cavity phase separator. The module combines a 4 K phase separator, a plate and fin heat exchanger from DATE and a J-T valve expanding into the 2 K phase separator. The unit also supplies 4 K liquid to thermal intercepts in the module in siphon loops that return the vaporized liquid to the 4 K reservoir. For testing purposes the unit is outfitted with a dummy 2 K phase separator and thermal intercepts with variable heaters that mimic the final heat loads in order to test the cryogenic performance. The design of the 4 K / 2 K insert, the results of the cold tests and a summary of the test infrastructure including cryogenics services will be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Revisiting the definition of the electronic chemical potential, chemical hardness, and softness at finite temperatures

We extend the definition of the electronic chemical potential (μ{sub e}) and chemical hardness (η{sub e}) to finite temperatures by considering a reactive chemical species as a true open system to the exchange of electrons, working exclusively within the framework of the grand canonical ensemble. As in the zero temperature derivation of these descriptors, the response of a chemical reagent to electron-transfer is determined by the response of the (average) electronic energy of the system, and not by intrinsic thermodynamic properties like the chemical potential of the electron-reservoir which is, in general, different from the electronic chemical potential, μ{sub e}. Although the dependence of the electronic energy on electron number qualitatively resembles the piecewise-continuous straight-line profile for low electronic temperatures (up to ca. 5000 K), the introduction of the temperature as a free variable smoothens this profile, so that derivatives (of all orders) of the average electronic energy with respect to the average electron number exist and can be evaluated analytically. Assuming a three-state ensemble, well-known results for the electronic chemical potential at negative (−I), positive (−A), and zero values of the fractional charge (−(I + A)/2) are recovered. Similarly, in the zero temperature limit, the chemical hardness is formally expressed as a Dirac delta function in the particle number and satisfies the well-known reciprocity relation with the global softness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Extended MHD modeling of tearing-driven magnetic relaxation

Discrete relaxation events in reversed-field pinch relevant configurations are investigated numerically with nonlinear extended magnetohydrodynamic modeling, including the Hall term in Ohm’s law and first-order ion finite Larmor radius effects. Our results show variability among relaxation events, where the Hall dynamo effect may help or impede the MHD dynamo effect in relaxing the parallel current density profile. The competitive behavior arises from multi-helicity conditions where the dominant magnetic fluctuation is relatively small. The resulting changes in parallel current density and parallel flow are aligned in the core, consistent with experimental observations. Analysis of simulation results also confirms that force density from fluctuation-induced Reynolds stress arises subsequent to the drive from fluctuation-induced Lorentz force density. Transport of momentum density is found to be dominated by the fluctuation-induced Maxwell stress over most of the cross section with viscous and gyroviscous contributions being large in the edge region. The findings resolve a discrepancy with respect to the relative orientation of current density and flow relaxation, which had not been realized or investigated in Ref. [King et. al. Phys. Plasmas 19, 055905 (2012)], where only the magnitude of flow relaxation is actually consistent with experimental results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Swift X-ray telescope observations of the nova-like cataclysmic variables MV Lyr, BZ Cam, and V592 Cas

We present a total of ∼45 ks (3 × 15 ks) of Swift X-Ray Telescope (XRT) observations for three nonmagnetic nova-like (NL) cataclysmic variables (CVs; MV Lyr, BZ Cam, V592 Cas) in order to study characteristics of boundary layers (BLs) in CVs. The nonmagnetic NLs are found mostly in a state of high mass accretion rate (≥1 × 10{sup –9} M {sub ☉} yr{sup –1}), and some show occasional low states. Using the XRT data, we find optically thin multiple-temperature cooling flow type emission spectra with X-ray temperatures (kT {sub max}) of 21-50 keV. These hard X-ray-emitting BLs diverge from simple isobaric cooling flows, indicating X-ray temperatures that are of virial values in the disk. In addition, we detect power-law emission components from MV Lyr and BZ Cam and plausibly from V592 Cas, which may be a result of the Compton scattering of the optically thin emission from the fast wind outflows in these systems and/or Compton upscattering of the soft disk photons. The X-ray luminosities of the (multitemperature) thermal plasma emission in the 0.1-50.0 keV range are (0.9-5.0) × 10{sup 32} erg s{sup –1}. The ratio of the X-ray and disk luminosities (calculated from the UV-optical wavelengths) yields an efficiency (L{sub x} /L {sub disk}) ∼ 0.01-0.001. Given this non-radiative ratio for the X-ray-emitting BLs with no significant optically thick blackbody emission in the soft X-rays (consistent with ROSAT observations), together with the high/virial X-ray temperatures, we suggest that high-state NL systems may have optically thin BLs merged with ADAF-like flows and/or X-ray coronae. In addition, we note that the axisymmetric bipolar and/or rotation-dominated fast-wind outflows detected in these three NLs (particularly BZ Cam and V592 Cas) or some other NL may also be explained in the context of ADAF-like BL regions.

79 ASTRONOMY AND ASTROPHYSICS↗