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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 811 records · Page 45

An Update on the Geothermal Data Repository's Data Standards and Pipelines: Geospatial Data and Distributed Acoustic Sensing Data: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented data standards and automated data pipelines for the following data types: 1) drilling data, 2) geospatial datasets, and 3) DAS data. An additional data pipeline is proposed for stimulation data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how we can improve this process.

cloud-optimized↗

An Update on the Geothermal Data Repository's Data Standards and Pipelines: Geospatial Data and Distributed Acoustic Sensing Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented data standards and automated data pipelines for the following data types: 1) drilling data, 2) geospatial datasets, and 3) DAS data. An additional data pipeline is proposed for stimulation data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how we can improve this process.

cloud-optimized↗

Nanocomposite-seeded epitaxial growth of single-domain lithium niobate thin films for surface acoustic wave devices

A method for making LNO film, including the steps of identifying a substrate, identifying a deposition target, placing the substrate and deposition target in a deposition environment, evolving target material into the deposition environment, and depositing evolved target material onto the substrate to yield an LNO film. The deposition environment defines a temperature of between 500 degrees Celsius and 750 degrees Celsius and a pressure of about 10 −6 Torr. A seed or buffer layer may be first deposited onto the substrate, wherein the seed layer is about 30 mole percent gold and about 70 LiNbO 3 .

Wang, Haiyan↗

Acoustic resonance chamber

A system for determining gas characteristics at high altitudes in embodiments of the present invention may have one or more of the following features: (a) a high-altitude balloon having one or more of the following features: (a) a balloon, (b) a balloonsat operably coupled to the balloon, (c) an air path chamber wherein gas at a high altitude can occupy the air path chamber, (d) a first speaker located on a substrate within the air path chamber, wherein the first speaker takes an electrical signal input and creates a first sound wave, and (e) a second speaker located on the substrate facing opposite of the first speaker located outside of the air path chamber, wherein the second speaker takes the electrical signal and creates a second sound wave.

Kolb, Lowell↗

Detection and Perception of Sound by Eagles and Surrogate Raptors

One overarching objective of this program of study was the accumulation of objective, scientifically valid information relating to auditory performance of bald and golden eagles that may be used to guide the development of acoustic alerting/deterrence technologies intended to discourage encroachment into wind energy air spaces. To that end, analyses aimed at the characterization of sensitivity to sound in bald and golden eagles, along with findings in the supra-threshold, dynamic frequency spaces related to response latencies and amplitudes, leads us to conclude that bald, and golden eagles navigate the same basic working auditory space, as in other known and thus far characterized members of the diurnal raptor family. Specifically, bald and golden eagles, along with other raptor species within the group, operate in an auditory space characterized by a frequency band at least four octaves wide and centered on 2 kHz, with an upper frequency limit between 6 and 10 kHz at 80 dB SPL and a lower frequency limit that almost certainly extends below 0.2 kHz. Consequently, we recommend that signal designers use these data as a guideline in efforts to design effective and efficient acoustic alerting/deterrent systems. It is important to note that signal energy broadcast outside of this frequency band at moderate levels will not contribute to the efficacy of a deterrent but will add an unnecessary fraction to the overall acoustic pollution budget. The importance of this consideration is heightened by contemporaneous concerns related to the transmission of noise broadcast by wind energy farms. In addition, based on analyses of data acquired from red-tailed hawks using the same experimental paradigm and data acquisition system, we conclude that auditory function in the red-tailed hawk is sufficiently like that observed in bald and golden eagles to permit its use as a surrogate species. Response waveforms, threshold-frequency curves, and input-output characteristics match those of eagles closely. It should be noted however, that differences in sensitivity and slightly extended high-frequency limits of hearing should be taken into account when extrapolating findings from one species to the others. Although the inclusion of behavioral tests of red-tailed hawks to acoustic stimuli was beyond the scope of this investigation, future efforts to assess response parameters like signal-type preference and habituation rate will further elucidate their suitability to serve as eagle surrogates in behavioral studies; nonetheless, the species in question are well matched with respect to basic auditory performance. A second essential objective of this program of study was the acoustic characterization of a subset of calls comprising the vocal repertoires of bald and golden eagles that may be used to supplement auditory performance findings in the effort to guide the development of acoustic alerting signals. With regard to that objective, the vocal repertoires of both bald and golden eagle species are rich and varied. While similar in spectrographic structure, distinctive differences are also clear. Generally, golden eagles produce some calls with shorter durations, and similar “sounding” calls exhibit distinctively different spectrographic patterns than those of bald eagles. Both species produce calls that contain a wide variety of nonlinear elements that operate to enhance the rich and varied nature of commonly observed vocal products. Comparison of the average power spectra of commonly observed bald and golden eagle calls with threshold-frequency curves leads to the conclusion that call energies fall within the frequency bounds of hearing. Further, the acoustic energy of calls considered in this report tend to fall into overlapping, but different frequency ranges of the acoustic sensitivity curve. This condition may encourage signal designers to vary the frequency content of acoustic deterrence signals in the field. Finally, preliminary observations relating to the tendencies and proclivities of bald eagles to attend to the acoustic landscape lead to the conclusion that eagles monitor their immediate sound environment assiduously. Individuals respond to a variety of natural and synthetic sound signals reliably and, perhaps most relevant in the context of the engineering of acoustic alerting/deterrence technologies, habituation to most sounds considered in this effort was minimal. These preliminary results, while calling for extended behavioral testing, are promising and set the stage for the exportation of behavioral studies into real world scenarios.

17 WIND ENERGY↗

Chiral microwave nonreciprocity demonstrated via Rayleigh and Sezawa modes supported in an Al 0.58 ⁢Sc 0.42 ⁢N/4⁢H–Si⁢C platform

Chirality plays a crucial role in the helicity mismatch between surface acoustic waves and magnetic spin waves, leading to nonreciprocal transmission of acoustic power for coupled magnetoacoustic modes. Acoustic modes with both longitudinal and shear strain exhibit elliptical particle displacements, making them chiral, and different acoustic modes can exhibit different helicities of this elliptical particle displacement. Here, we study chiral acoustic modes with different helicities supported on the same piezoelectric platform and their interaction with magnetic spin waves. Our study demonstrates that the nonreciprocal transmission of acoustic power is driven by the helicity mismatch effect and, specifically, that the handedness of the nonreciprocity is based on whether the surface acoustic wave has retrograde (Rayleigh mode) or prograde (Sezawa mode) elliptical particle displacement with respect to the propagation direction. We found the transmission nonreciprocity to be significant, with 7.3 dB/mm for the retrograde particle displacement (Rayleigh mode at 2.358 GHz) and 3.3 dB/mm for prograde particle displacement (Sezawa mode at 3.112 GHz). Furthermore, this work highlights that piezoelectric platforms can be engineered to support acoustic modes with opposite helicities to enable frequency-selective nonreciprocal radiofrequency and microwave components, such as isolators and circulators, through coupled acoustic spin wave interactions.

42 ENGINEERING↗