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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Video-Based Electroshocking Platform to Identify Lamprey Ammocoete Habitats: Field Validation and New Discoveries in the Columbia River Basin

A deep water electroshocking platform (DEP), developed to characterize larval lampreys (ammocoetes) and associated habitat in depths up to 15 m, was recently tested in the field. The DEP samples 0.55 m2∙min-1 without requiring ammocoete transport to the surface. Searches were conducted at a known rearing location (mouth of the Wind River, WA) and at locations on the Cowlitz River, WA, where ammocoetes had not previously been found. At the mouth of the Wind River, video imaged ammocoetes ranged from 50 to 150 mm in water depths between 1.5 m and 4.5 m and were more common in sediments containing organic silt. Ammocoetes (n=137) were detected at 61% of locations sampled (summer) and 50% of the locations sampled (winter). Following the field verification, the DEP was used on the lower 11.7 km of the Cowlitz River, WA. Ammocoetes (n=41) were found with a detection rate of 26% at specific search locations. Cowlitz River sediment containing ammocoetes was also dominated by silt with organic material, often downstream of alluvial bars in water depths from 0.8 to 1.7 m. Test results indicated a high sampling efficiency, favorable detection rates, and little or no impact to ammocoetes and their surrounding benthic environments.

Cowlitz River↗
DOE OSTI2025

Identifying rolling resistance and air resistance simultaneously for an electric truck

Accurately estimating rolling and air resistance is essential for predicting the energy consumption of vehicles. This study presents a field-based approach using a rolldown test to simultaneously determine rolling and air resistance coefficients. Unlike prior methods that frequently used simulations or models, we employ a goal programming methodology to improve precision and evaluate the actual vehicle and environmental conditions. Our methodology was tested using a Class 8 Freightliner eCascadia on a surveyed road section, ensuring controlled conditions for data collection. By analyzing the time–velocity relationship across multiple test runs, we derived resistance coefficients for both loaded and unloaded conditions. The study confirms that rolling resistance is largely independent of velocity at low speeds but exhibits a nonlinear dependency at higher speeds. Additionally, road surface conditions, tire condition, axle configuration, aerodynamic properties, and weather conditions significantly impact resistance values, emphasizing the need for real-world testing rather than relying solely on standardized projections. Our results align with existing literature while demonstrating the efficacy of the goal programming approach in refining resistance estimates. This work contributes to improved vehicle energy modeling, offering practical insights for fleet operators and policymakers seeking accurate energy consumption predictions for electric trucks operating under varying environmental conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Using excitation-energy dependent fission yields to identify key fissioning nuclei in r -process nucleosynthesis

The possibility that nucleosynthesis in neutron star mergers may reach fissioning nuclei introduces significant uncertainties in predicting the relative abundances of $r$-process material from such events. We evaluate the impact of using sets of fission yields given by the 2016 GEF code for spontaneous (sf), neutron-induced $((n, f))$, and $β$-delayed (βdf) fission processes which take into account the approximate initial excitation energy of the fissioning compound nucleus. We further explore energy-dependent fission dynamics in the $r$ process by considering the sensitivity of our results to the treatment of the energy sharing and de-excitation of the fission fragments using the FREYA code. We show that the asymmetric-to-symmetric yield trends predicted by GEF 2016 can reproduce the high-mass edge of the second $r$-process peak seen in solar data and examine the sensitivity of this result to the mass model and astrophysical conditions applied. We consider the effect of fission yields and barrier heights on the nuclear heating rates used to predict kilonova light curves. We find that fission barriers influence the contribution of 254 Cf spontaneous fission to the heating at ~100 d, such that a light curve observation consistent with such late-time heating would both confirm that actinides were produced in the event and imply the fission barriers are relatively high along the 254 Cf β-feeding path. We lastly determine the key nuclei responsible for setting the r-process abundance pattern by averaging over thirty trajectories from a 1.2–1.4 M ⊙ neutron star merger simulation. Finally, we show it is largely the odd-N nuclei undergoing $(Z, N)(n, f)$ and $(Z, N)β$df that control the relative abundances near the second peak. We find the 'hot spots' for β-delayed and neutron-induced fission given all mass models considered and show most of these nuclei lie between the predicted $N$ = 184 shell closure and the location of currently available experimental decay data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Identifying the most crucial parameters of the initial curvature profile for primordial black hole formation

Primordial black holes (PBHs) are an important tool in cosmology to probe the primordial spectrum of small-scale curvature perturbations that reenter the cosmological horizon during radiation domination epoch. We numerically solve the evolution of spherically symmetric highly perturbed configurations to clarify the criteria of PBHs formation using an extremely wide class of curvature profiles characterized by five parameters, (in contrast to only two parameters used in all previous papers) which specify the curvature profiles not only at the central region but also at the outer boundary of configurations. It is shown that formation or non-formation of PBHs is determined essentialy by only two master parameters one of which can be presented as an integral of curvature over initial configurations and the other is presented in terms of the position of the boundary and the edge of the core.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A new algorithm for identifying the flavour of B 0 s mesons at LHCb

A new algorithm for the determination of the initial flavour of B 0 s mesons is presented. The algorithm is based on two neural networks and exploits the b hadron production mechanism at a hadron collider. The first network is trained to select charged kaons produced in association with the B 0 s meson. The second network combines the kaon charges to assign the B 0 s flavour and estimates the probability of a wrong assignment. The algorithm is calibrated using data corresponding to an integrated luminosity of 3 fb –1 collected by the LHCb experiment in proton-proton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the B 0 s – B ¯ 0 s flavour oscillations in B 0 s → D – s π + decays, and by analysing flavour-specific B * s 2 (5840) 0 → B + K – decays. The tagging power measured in B 0 s → D – s π + decays is found to be (1.80 ± 0.19 (stat) ± 0.18 (syst))%, which is an improvement of about 50% compared to a similar algorithm previously used in the LHCb experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

IDENTIFYING POTENTIAL MARKERS OF THE SUN'S GIANT CONVECTIVE SCALE

Line-of-sight magnetograms from the Helioseismic and Magnetic Imager (HMI) of the Solar Dynamics Observatory (SDO) are analyzed using a diagnostic known as the magnetic range of influence (MRoI). The MRoI is a measure of the length over which a photospheric magnetogram is balanced and so its application gives the user a sense of the connective length scales in the outer solar atmosphere. The MRoI maps and histograms inferred from the SDO/HMI magnetograms primarily exhibit four scales: a scale of a few megameters that can be associated with granulation, a scale of a few tens of megameters that can be associated with super-granulation, a scale of many hundreds to thousands of megameters that can be associated with coronal holes and active regions, and a hitherto unnoticed scale that ranges from 100 to 250 Mm. We infer that this final scale is an imprint of the (rotationally driven) giant convective scale on photospheric magnetism. This scale appears in MRoI maps as well-defined, spatially distributed concentrations that we have dubbed ''g-nodes''. Furthermore, using coronal observations from the Atmospheric Imaging Assembly on SDO, we see that the vicinity of these g-nodes appears to be a preferred location for the formation of extreme-ultraviolet (and likely X-Ray) brightpoints. These observations and straightforward diagnostics offer the potential of a near real-time mapping of the Sun's largest convective scale, a scale that possibly reaches to the very bottom of the convective zone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

THE ORIGINS OF LIGHT AND HEAVY R-PROCESS ELEMENTS IDENTIFIED BY CHEMICAL TAGGING OF METAL-POOR STARS

Growing interests in neutron star (NS) mergers as the origin of r-process elements have sprouted since the discovery of evidence for the ejection of these elements from a short-duration γ-ray burst. The hypothesis of a NS merger origin is reinforced by a theoretical update of nucleosynthesis in NS mergers successful in yielding r-process nuclides with A > 130. On the other hand, whether the origin of light r-process elements are associated with nucleosynthesis in NS merger events remains unclear. We find a signature of nucleosynthesis in NS mergers from peculiar chemical abundances of stars belonging to the Galactic globular cluster M15. This finding combined with the recent nucleosynthesis results implies a potential diversity of nucleosynthesis in NS mergers. Based on these considerations, we are successful in the interpretation of an observed correlation between [light r-process/Eu] and [Eu/Fe] among Galactic halo stars and accordingly narrow down the role of supernova nucleosynthesis in the r-process production site. We conclude that the tight correlation by a large fraction of halo stars is attributable to the fact that core-collapse supernovae produce light r-process elements while heavy r-process elements such as Eu and Ba are produced by NS mergers. On the other hand, stars in the outlier, composed of r-enhanced stars ([Eu/Fe] ≳ +1) such as CS22892-052, were exclusively enriched by matter ejected by a subclass of NS mergers that is inclined to be massive and consist of both light and heavy r-process nuclides.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Simulations with machine learning potentials identify the ion conduction mechanism mediating non-Arrhenius behavior in LGPS

Abstract Li 10 Ge(PS 6 ) 2 (LGPS) is a highly concentrated solid electrolyte, in which Coulombic repulsion between neighboring cations is hypothesized as the underlying reason for concerted ion hopping, a mechanism common among superionic conductors such as Li 7 La 3 Zr 2 O 12 (LLZO) and Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 (LATP). While first principles simulations using molecular dynamics (MD) provide insight into the Li + transport mechanism, historically, there has been a gap in the temperature ranges studied in simulations and experiments. Here, we used a neural network potential trained on density functional theory (DFT) simulations, to run up to 40-nanosecond long MD simulations at DFT-like accuracy to characterize the ion conduction mechanisms across a range of temperatures that includes previous simulations and experimental studies. We have confirmed a Li + sublattice phase transition in LGPS around 400 K, below which the ab -plane diffusivity D a b ∗ is drastically reduced. Concomitant with the sublattice phase transition near 400 K, there is less cation-cation (cross) correlation, as characterized by Haven ratios closer to 1, and the vibrations in the system are more harmonic at lower temperature. Intuitively, at high temperature, the collection of vibrational modes may be sufficient to drive concerted ion hops. However, near room temperature, the vibrational modes available may be insufficient to overcome electrostatic repulsion, thus resulting in less correlated ion motion and comparatively slower ion conduction. Such phenomena of a sublattice phase transition, below which concerted hopping plays a less significant role, may be extended to other highly concentrated solid electrolytes such as LLZO and LATP.

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

LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data

We introduce an open-source software, LIQUID, for semi-automated processing and visualization of LC-MS/MS based lipidomics data. LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species.

Environmental Molecular Sciences Laboratory↗