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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

CMB and random flights: temperature and polarization in position space

The fluctuations in the temperature and polarization of the cosmic microwave background are described by a hierarchy of Boltzmann equations. In its integral form, this Boltzmann hierarchy can be converted from the usual Fourier-space base into a position-space and causal description. We show that probability densities for random flights play a key role in this description. The integral system can be treated as a perturbative series in the number of steps of the random flights, and the properties of random flight probabilities impose constraints on the domains of dependence. We show that, as a result of these domains, a Fourier-Bessel decomposition can be employed in order to calculate the random flight probability densities. We also illustrate how the H-theorem applies to the cosmic microwave background: by using analytical formulae for the asymptotic limits of these probability densities, we show that, as the photon distribution approaches a state of equilibrium, both the temperature anisotropies and the net polarization must vanish.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Stabilization of circular Rydberg atoms by circularly polarized infrared laser fields

The ionization dynamics of circular Rydberg states in strong circularly polarized infrared (800 nm) laser fields is studied by means of numerical simulations with the time-dependent Schroedinger equation. We find that at certain intensities, related to the radius of the Rydberg states, atomic stabilization sets in, and the ionization probability decreases as the intensity is further increased. Moreover, there is a strong dependence of the ionization probability on the rotational direction of the applied laser field, which can be understood from a simple classical analogy.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2012

Follow-on to a report on the Applicability of the “Gallet equation” to the vegetation clearances of NERC Reliability Standard FAC-003-2

In earlier work, a study done at the Pacific Northwest National Laboratory examined a NERC proposed standard specifying clearances between vegetation and power lines. The method proposed for calculating the clearances was based on the results of testing for high-voltage line designs. An equation developed to relate the results of testing with rod-plane gaps to proposed tower window sizes was incorporated into the calculations. The equation in question, sometimes called the “Gallet equation,” describes the insulation performance of the atmosphere for air gaps of a few meters. The equation was described in the PNNL study as a good and simple-to-use way to solve a problem made difficult by the nonlinear interactions of the variables. For calculations based on this equation, a certain set of assumptions must be made. In particular, a value for a quantity called the “gap factor” is needed. This is the amount by which the gap to be modeled by the equation is stronger than the reference gap that was used in developing the Gallet equation. That reference gap is the gap between a rod and a plane. This follow-on report examines the effect on flashover probabilities of assuming an incorrect value for the gap factor. In particular, the flashover probability is found that would result from using a value of 1.3 when a gap factor of 1.0 should be applied. It is shown that with these assumptions the probability of a flashover changes from being extremely unlikely (about 1 in 1000 chance) to a virtual certainty (about 97% chance).

high voltage: flashover: Gallet equation↗
DOE OSTI2023

Moving Beyond Mortality: Development and Application of a Desirability of Outcome Ranking (DOOR) Endpoint for Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia

Abstract Background Hospital-acquired and ventilator-associated bacterial pneumonia (HABP/VABP) are frequently caused by multidrug-resistant organisms. Patient-centered endpoints in clinical trials are needed to develop new antibiotics for HABP/VABP. Desirability of outcome ranking (DOOR) is a paradigm for the design, analysis, and interpretation of clinical trials based on a patient-centered, benefit-risk evaluation. Methods A multidisciplinary committee created an infectious diseases DOOR endpoint customized for HABP/VABP, incorporating infectious complications, serious adverse events, and mortality. We applied this to 2 previously completed, large randomized controlled trials for HABP/VABP. ZEPHyR compared vancomycin to linezolid and VITAL compared linezolid to tedizolid. For each trial, we evaluated the DOOR distribution and probability, including DOOR component and partial credit analyses. We also applied DOOR in subgroup analyses. Results In both trials, the HABP/VABP DOOR demonstrated similar overall clinical outcomes between treatment groups. In ZEPHyR, the probability that a participant treated with linezolid would have a more desirable outcome than a participant treated with vancomycin was 50.2% (95% confidence interval [CI], 45.1%­−55.3%). In VITAL, the probability that a participant treated with tedizolid would have a more desirable outcome than a participant treated with linezolid was 48.7% (95% CI, 44.8%–52.6%). The DOOR component analysis revealed that participants treated with tedizolid had a less desirable outcome than those treated with linezolid when considering clinical response alone. However, participants with decreased renal function had improved overall outcomes with tedizolid. Conclusions The HABP/VABP DOOR provided more granular information about clinical outcomes than is typically presented in clinical trials. HABP/VABP trials would benefit from prospectively using DOOR.

Immunology↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

A flexible numerical approach for quantification of epistemic uncertainty

In the field of uncertainty quantification (UQ), epistemic uncertainty often refers to the kind of uncertainty whose complete probabilistic description is not available, largely due to our lack of knowledge about the uncertainty. Quantification of the impacts of epistemic uncertainty is naturally difficult, because most of the existing stochastic tools rely on the specification of the probability distributions and thus do not readily apply to epistemic uncertainty. And there have been few studies and methods to deal with epistemic uncertainty. A recent work can be found in [J. Jakeman, M. Eldred, D. Xiu, Numerical approach for quantification of epistemic uncertainty, J. Comput. Phys. 229 (2010) 4648–4663], where a framework for numerical treatment of epistemic uncertainty was proposed. The method is based on solving an encapsulation problem, without using any probability information, in a hypercube that encapsulates the unknown epistemic probability space. If more probabilistic information about the epistemic variables is known a posteriori, the solution statistics can then be evaluated at post-process steps. In this paper, we present a new method, similar to that of Jakeman et al. but significantly extending its capabilities. Most notably, the new method (1) does not require the encapsulation problem to be in a bounded domain such as a hypercube; (2) does not require the solution of the encapsulation problem to converge point-wise. In the current formulation, the encapsulation problem could reside in an unbounded domain, and more importantly, its numerical approximation could be sought in L{sup p} norm. These features thus make the new approach more flexible and amicable to practical implementation. Both the mathematical framework and numerical analysis are presented to demonstrate the effectiveness of the new approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

High bias machine learning for antineutrino-based safeguards for small reactors

The statistical methods used for antineutrino detection will need to be improved to effectively monitor the inventory of next-generation nuclear reactors. In this sensitivity study, we evaluate machine learning models compared to previously used statistical approaches to identify diversion scenarios in a simulated Advanced Fast Reactor (AFR)-100. A chi-square goodness-of-fit technique, which individually compares the simulated antineutrino yields to the expected antineutrino yield, resulted in precise but low diversion detection probability. Various support vector machine (SVM) models were applied with diverse training datasets to evaluate the robustness of the method towards unexpected or “unseen” diversion scenarios. Furthermore, our results indicate that while the SVM models significantly improved the detection probability of near-field antineutrino-based safeguards, up to a probability of ~0.04, for the simulated small reactor, the detection system still needs improvements to reach the 0.2 detection limit established by the International Atomic Energy Agency.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

Uncertainty quantification for nuclear density functional theory and information content of new measurements

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A proposed criteria to identify wind turbine drivetrain bearing loads that induce roller slip based white-etching cracks

In this article, the type of roller slip behavior that may result in the formation of white-etching cracks (WECs) in wind turbine gearbox bearings is identified. A new hypothesis based on the inner raceway normal contact load magnitude at the time of roller slip is proposed as the probable cause of WECs. For this purpose, the maximum normal contact loads are identified when roller slip occurs in high-speed shaft bearings at different mean wind speeds. Subsequently, the annual probability of occurrence of the maximum normal loads are obtained. The probability of maximum load under slip exceeding a limit probability is hypothesized as a probable cause for WEC. In order to apply the proposed hypothesis, two different wind turbines high-speed shaft bearings are used: the cylindrical roller bearing of the General Electric 1.5 SLE turbine and the tapered roller bearing of Vestas V52 turbine. Both the chosen bearings are on the generator side of the high-speed shaft. For both turbines, measurement data together with analytical models are used for identifying the slip and the maximum normal contact loads. We propose forecasting the probability of exceedance of a threshold maximum normal contact load level during slip to identify the possibility for inducing WECs.

17 WIND ENERGY↗
DOE OSTI2024

Coverage, repulsion, and reactivity of hydrogen on High-Entropy alloys

Modeling hydrogen evolution reaction (HER) activity probability on IrPdPtRhRu(1 1 1) high-entropy alloys. Determining hydrogen coverages based on ligand effects and generalized hydrogen–hydrogen repulsion. The rate of H 2 formation is highly impacted by the level of hydrogen coverage on the catalyst surface. In search of optimal catalytic properties high-entropy alloys (HEA) are promising candidates that utilize the compositional space of multiple elements. Based on simulations of HEA model (1 1 1) surfaces with a range of hydrogen coverages, distributions of binding energies are used to construct a framework that approximates the probability that adsorbed hydrogen may lead to the formation of H 2 as a function of applied potential. By optimizing the alloy compositions for the highest activity probability at given potentials the best and most efficient catalyst candidates for HER can be identified. Treating hydrogen–hydrogen repulsion effects and binding energy separately, we find that the repulsion is larger for HEAs than for pure metals. Differing isotherm slopes in the mean adsorption and desorption energies demonstrate a possible hysteresis for hydrogen adsorption on HEAs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Impact of Resonant Magnetic Perturbations on the Toroidal Location of the Runaway Electron Final Loss Strike Point

It is demonstrated that the peak toroidal impact phase of the post-disruption runaway electrons (REs) can be varied shot-to-shot by means of applied static non-axisymmetric (3D) magnetic fields, or resonant magnetic perturbations (RMPs). In the experiments, high-current (500 kA), purged RE plateaus (i.e. low impurity post-disruption plasmas with current carried completely by REs) were terminated on the DIII-D tokamak center post (CP). The global toroidal impact peak of the REs appears to be dominantly set by the toroidal phase of a wall-locked tearing mode, typically (m/n) = (2/1), but sometimes (m/n) = (3/2). In the absence of external RMP, the locked mode reliably locks close to a preferred toroidal phase Φ ≃ 75◦ probably set by intrinsic error fields. With applied RMP, the locked mode and RE impact phase is pushed to a new location. When the tearing mode is (m/n) = (2/1), the phase is well controlled and tracks the applied RMP phase, but in the case of an (m/n) = (3/2) tearing mode, the new phase location is not well controlled. These results could have application in ITER and other fusion power plant (FPP) - sized tokamaks as a method for spreading disruption first wall damage from REs

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

Nanoparticles synthesis of tungsten disulfide via AOT-based microemulsions

Graphical abstract: A controlled synthesis of WS2 nanoparticles (most probably inorganic fullerene (IF)) via microemulsion was applied for the first time to prepare WS2 (7–12 nm) by acidification of the water cores of the AOT reverse microemulsion. Highlights: ► An innovative reverse microemulsion technique was developed for WS{sub 2} synthesis. ► WS{sub 2} nanoparticles were obtained with narrow size distribution in range of 7–12 nm. ► Operating cost of microemulsion was lower in contrast to quartz reactor method. ► WS{sub 2} morphology could be controlled to obtain highly active and selective catalysts. ► Lower size of WS{sub 2} in this study overcomes the shortcoming of quartz reactor method. -- Abstract: The tungsten disulfide (WS{sub 2}) nanoparticles (most probably inorganic fullerene (IF)) with a narrow size distribution were synthesized by a reverse micelle technique for the first time. The particle size was controlled by varying water-to-surfactant molar ratio (W{sub 0}), aging time and reagent concentration. The synthesized WS{sub 2} nanoparticles were characterized by zetasizer, UV–visible spectrophotometers and transmission electron microscopy (TEM). The WS{sub 2} nanoparticles with particle diameter size of 7–12 nm were obtained via 24 h aging time. The particle size was controlled by changing the aging time and molar ratio of water/surfactant. Doubling W{sub 0} increased the amount and particle size of WS{sub 2} by 22 and 26%, respectively. The effect of aging time in the range of 6–24 h was investigated and the complete disappearance of yellowish color at 24 h resulted in an optically clear solution, which was the indication of WS{sub 2} formation with 100% conversion of reactant ((NH{sub 4}){sub 2}WS{sub 4}) in the batch reactor.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Electric field step in air gap streamer discharges

Electric field (E-field) in air gap streamer discharges under positive lightning impulse was measured by specifically developed integrated electro-optic sensors. An E-field step phenomenon was observed. The E-field firstly agreed with the Laplace field, then suddenly increased with a rise time of {mu}s. The occurrence probability of this phenomenon increased as the applied voltage increased. The discharge current waveforms and photos taken by a fast camera prove the E-field step was caused by the space net charge. From the E-step rise time and the corona area range, the average electron drift speed under the experiment situation was estimated about 0.2 x 10{sup 6} - 0.6x 10{sup 6} m/s.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Turn Your Half-Cut Cells for a Stronger Module

Here, we employ an existing model of crystalline silicon photovoltaic module cell fracture to explore the effect of cell size and orientation on their probability of fracture under module uniform loading. In addition, we also apply continuum damage mechanics to modify this model to consider the effect of cell fracture on the probability of subsequent cell fracture. We elucidate that cell fracture increases the probability of subsequent cell fracture and that rectangular modules containing half-cells aligned with the module's long orientation are much more robust against cell fracture than full-cell and half-cell short orientation modules.

14 SOLAR ENERGY↗
DOE OSTI2011

Peptide identification

Peptides are identified from a list of candidates using collision-induced dissociation tandem mass spectrometry data. A probabilistic model for the occurrence of spectral peaks corresponding to frequently observed partial peptide fragment ions is applied. As part of the identification procedure, a probability score is produced that indicates the likelihood of any given candidate being the correct match. The statistical significance of the score is known without necessarily having reference to the actual identity of the peptide. In one form of the invention, a genetic algorithm is applied to candidate peptides using an objective function that takes into account the number of shifted peaks appearing in the candidate spectrum relative to the test spectrum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Estimating the probability of fish encountering a marine hydrokinetic device

We report strong tidal currents in eastern Maine, USA, make that region attractive for tidal power development. We know very little about the effects of marine hydrokinetic (MHK) devices on fish, yet many fish species use tidal currents for movements. We used empirical data from stationary and mobile hydroacoustic surveys to examine the probability that fish would be at the depth of an MHK device and may therefore encounter it. The probability was estimated using three components: 1) probability of fish being at device-depth when the device was absent; 2) probability of fish behavior changing to avoid the device in the far-field; and 3) probability of fish being at device-depth in the near-field when the device was present. Furthermore, there were differences in probabilities of fish encountering the MHK device based on month, diel condition and tidal stage. The maximum probability of fish encountering the whole device was 0.432 (95% CI: [0.305, 0.553]), and the probability of fish encountering only device foils was 0.058 (95% CI: [0.043, 0.073]). Mobile hydroacoustics indicated that fish likely avoided the device with horizontal movement beginning 140 m away. Finally, we estimated the encounter probability for one device, but results can be applied to arrays, which may have bay-wide implications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Efficient high-fidelity TRISO statistical failure analysis using Bison: Applications to AGR-2 irradiation testing

The ability of tri-structural isotropic (TRISO) fuel to contain fission products is largely dictated by the quality of the manufacturing process, since most of the fission product release is expected to occur due to coating layer failure in a small number of particles containing defects. The Bison fuel performance code has capabilities to predict failure in individual particles, accounting for the presence of defects, and to apply statistical analysis methods to compute the probability of failure in a set of fuel particles. Bison has recently undergone significant development both to improve its physical representations of fuel particle behavior and to improve the efficiency of its statistical failure calculations. Physical model improvements include new capabilities to account for the pressure generated by fission gases on inner pyrolytic carbon (IPyC) crack surfaces and to use local material coordinate orientation to accurately incorporate the anisotropy in the material properties in aspherical particles. To improve statistical modeling efficiency, a direct integration approach which involves directly integrating the failure probability function associated with statistically varying parameters has been developed. The direct integration approach is much more efficient than the Monte Carlo (MC) schemes commonly employed, and allows Bison to directly run high-dimensional fuel performance models, which improves the accuracy of failure probability calculations. Finally, a set of benchmark problems is considered here to compare the MC and direct integration approaches, and a statistical failure analysis of compacts in the Advanced Gas Reactor (AGR)-2 experiments is performed using the direct integration approach.

36 MATERIALS SCIENCE↗