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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 271 records · Page 15

Constraints on cosmological parameters from gamma-ray burst peak photon energy and bolometric fluence measurements and other data

ABSTRACT We use measurements of the peak photon energy and bolometric fluence of 119 gamma-ray bursts (GRBs) extending over the redshift range of 0.3399 ≤ z ≤ 8.2 to simultaneously determine cosmological and Amati relation parameters in six different cosmological models. The resulting Amati relation parameters are almost identical in all six cosmological models, thus validating the use of the Amati relation in standardizing these GRBs. The GRB data cosmological parameter constraints are consistent with, but significantly less restrictive than, those obtained from a joint analysis of baryon acoustic oscillation and Hubble parameter measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Does jackknife scale really matter for accurate large-scale structure covariances?

ABSTRACT The jackknife method gives an internal covariance estimate for large-scale structure surveys and allows model-independent errors on cosmological parameters. Using the SDSS-III BOSS CMASS sample, we study how the jackknife size and number of resamplings impact the precision of the covariance estimate on the correlation function multipoles and the error on the inferred baryon acoustic scale. We compare the measurement with the MultiDark Patchy mock galaxy catalogues, and we also validate it against a set of lognormal mocks with the same survey geometry. We build several jackknife configurations that vary in size and number of resamplings. We introduce the Hartlap factor in the covariance estimate that depends on the number of jackknife resamplings. We also find that it is useful to apply the tapering scheme to estimate the precision matrix from a limited number of resamplings. The results from CMASS and mock catalogues show that the error estimate of the baryon acoustic scale does not depend on the jackknife scale. For the shift parameter α, we find an average error of 1.6 per cent, 2.2 per cent and 1.2 per cent, respectively, from CMASS, Patchy, and lognormal jackknife covariances. Despite these uncertainties fluctuate significantly due to some structural limitations of the jackknife method, our α estimates are in reasonable agreement with published pre-reconstruction analyses. Jackknife methods will provide valuable and complementary covariance estimates for future large-scale structure surveys.

Favole, Ginevra (ORCID:000000028218563X)↗

Determining the range of validity of quasar X-ray and UV flux measurements for constraining cosmological model parameters

ABSTRACT We use six different cosmological models to study the recently released compilation of X-ray and UV flux measurements of 2038 quasars (QSOs) which span the redshift range 0.009 ≤ z ≤ 7.5413. We find, for the full QSO data set, that the parameters of the X-ray and UV luminosities LX−LUV relation used to standardize these QSOs depend on the cosmological model used to determine these parameters, i.e. it appears that the full QSO data set includes QSOs that are not standardized and so cannot be used for the purpose of constraining cosmological parameters. Subsets of the QSO data, restricted to redshifts z ≲ 1.5–1.7 obey the LX−LUV relation in a cosmological-model-independent manner, and so can be used to constrain cosmological parameters. The cosmological constraints from these lower z, smaller QSO data subsets are mostly consistent with, but significantly weaker than, those that follow from baryon acoustic oscillation and Hubble parameter measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Identification of High-Frequency Transverse Acoustic Modes in Multi-Nozzle Can Combustors

Abstract High frequency thermoacoustic instabilities are problematic for lean-premixed gas turbines. Identifying which acoustic mode is being excited is important, in that it provides insight into potential mitigation measures and mechanical stress/life. However, the frequency spacing between modes becomes quite close for high frequency instabilities in a can combustor. This makes it difficult to distinguish between the modes (e.g., the first transverse mode vs. a higher order axial/mixed mode) based upon frequency calculations alone, which inevitably have uncertainties in boundary conditions, temperature profiles, and combustion response. This paper presents a methodology to simultaneously identify the acoustic mode shapes in the axial and azimuthal directions from acoustic pressure measurements. Multiple high temperature pressure transducers, located at distinct axial and azimuthal positions, are flush mounted in the combustor wall. The measured pressure oscillations from each sensor are then used to reconstruct the pressure distributions by using a least squares method in conjunction with a solution of a three dimensional wave equation. In order to validate the methodology, finite element method (FEM) calculations with estimated post-flame temperature is used to provide the candidate frequencies and corresponding mode shapes. The results demonstrate the reconstructed mode shapes and standing/spinning character of transverse waves, as well as the associated frequencies, both of which are consistent with the FEM predictions. Nodal line location was also extracted from the experimental data during the instabilities in the pressure data.

Kim, J.↗

Persistent Acoustic Sensing for Monitoring A Reactor Facility - Oral Presentation

Measurements over the past few years, taking place within the Multi-Informatics for Nuclear Operations Scenarios (MINOS) project, show that infrasound and low-frequency acoustic monitoring can detect, and often quantify, activities that occur on-site at a large research reactor. Observable activities include: crane translation, lifting, and lowering; differentiation between loaded and unloaded crane operations; access door opening and closing; vehicle operations; and cooling tower fan operation. Advanced data analytic and spectral feature extraction methods can be used to interpret selected signatures to reach a deeper understanding of different reactor activities. These measurements are being conducted using a network of smartphones that continuously operate in conjunction with cloud-based architectures. A recent addition to the system is the development and deployment of a real-time, cloud-based analytic framework that supports near-real-time alarming which can facilitate tip-and-cue protocols. This paper will present recent research advances in this area including studies to explore the transferability of learned parameters from one smartphone to another, the detectability of events from multiple sensors at different locations simultaneously, and the feasibility of porting analytical tools directly to the smartphones to allow edge computing with optimized configurations.

42 ENGINEERING↗

Impact and mitigation of spectroscopic systematics on DESI DR1 clustering measurements

The large scale structure catalogs within DESI Data Release 1 (DR1) use nearly 6 million galaxies and quasars as tracers of the large-scale structure of the universe to measure the expansion history with baryon acoustic oscillations and the growth of structure with redshift-space distortions. In order to take advantage of DESI's unprecedented statistical power, we must ensure that the galaxy clustering measurements are unaffected by non-cosmological density fluctuations. One source of spurious fluctuations comes from variation in galaxy density with spectroscopic observing conditions, lowering the redshift efficiency (and thus galaxy density) in certain areas of the sky. We measure the uniformity of the redshift success rate for DESI luminous red galaxies (LRG), bright galaxies (BGS) and quasars (QSO), complementing the detailed discussion of emission line galaxy (ELG) systematics in a companion paper [1]. We find small but significant fluctuations of up to 3% in redshift success rate with the effective spectroscopic signal-to-noise, and create and describe weights that remove these fluctuations. We also describe the process to identify and remove data from certain poorly performing fibers from DESI DR1, and measure the stability of the redshift success rate with time. Finally, we find small but significant correlations of redshift success rate with position on the focal plane, survey speed, and number of exposures required, and show the impact of weights correcting these trends on the power spectrum multipoles and on cosmological parameters from BAO and RSD fits. These corrections change the best-fit parameters by <15% of their statistical errors, and thus contribute negligibly to the overall DESI error budget.

cosmological parameters from LSS↗

Origin of Intrinsically Low Thermal Conductivity in a Garnet-Type Solid Electrolyte: Linking Lattice and Ionic Dynamics with Thermal Transport

Understanding thermal transport in solid electrolytes is essential for improving the performance, reliability, and safety of all-solid-state batteries. Garnet-type lithium-ion conductors are promising candidates for solid electrolytes, yet their thermal-transport mechanisms remain poorly understood. Here, we connect the lattice and ion dynamics of single-crystal garnet-type Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 to its intrinsically low thermal conductivity. Our study reveals that the single crystals grown by the floating-zone method exhibit remarkably low glasslike thermal conductivity. Using first-principles calculations and inelastic-neutron-scattering measurements, we identify both the acoustic and numerous optical phonon modes, which stem from the complex crystal structure of the material. Notably, a low-energy optical branch exhibits an avoided crossing with acoustic phonons near 7 meV. These optical modes can enhance the scattering of heat-carrying acoustic phonons and reduce thermal conductivity. Furthermore, the calculated Grüneisen parameters are large, especially for the vibrational modes around 6 meV, indicating strong anharmonicity, with a noticeable contribution from lithium-ion vibrations. A two-channel thermal-transport model is employed to describe the weak temperature dependence of the thermal conductivity, which can be attributed to the substantial contribution of diffuson transport facilitated by the abundance of optical phonons and intrinsic anharmonicity. These results offer valuable insights into the thermal transport in a broad class of ionic conductors of interest for energy conversion and storage applications.

Ab initio calculations↗

Radar - 449MHz - North Bend, OR (OTH) - Reviewed Data

**Winds.** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and are combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature.** To measure atmospheric temperature, a radio acoustic sounding system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60 m up to 3.5 km for the 449 MHz. **Moments and Spectra.** The raw spectra and moments data are available for all dwells along each beam and are stored in daily files. For each day, there are files labeled "header" and "data." These files are generated by the radar data acquisition system (LAP-XM) and are encoded in a proprietary binary format. Values of spectral density at each Doppler velocity (FFT point), as well as the radial velocity, signal-to-noise ratio, and spectra width for the selected signal peak are included in these files. Attached zip files, *449mhz-spectra-data-extraction.zip* and *449mhz-moment-data-extraction.zip*, include executables to unpack the spectra, (GetSpectra32.exe) and moments (GetMomSp32.exe), respectively. Documentation on usage and output file formats also are included in the zip files.

17 WIND ENERGY↗

Radar - 449MHz - Forks, WA (FKS) - Reviewed Data

**Winds.** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and are combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature.** To measure atmospheric temperature, a radio acoustic sounding system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60 m up to 3.5 km for the 449 MHz. **Moments and Spectra.** The raw spectra and moments data are available for all dwells along each beam and are stored in daily files. For each day, there are files labeled "header" and "data." These files are generated by the radar data acquisition system (LAP-XM) and are encoded in a proprietary binary format. Values of spectral density at each Doppler velocity (FFT point), as well as the radial velocity, signal-to-noise ratio, and spectra width for the selected signal peak are included in these files. Attached zip files, *449mhz-spectra-data-extraction.zip* and *449mhz-moment-data-extraction.zip*, include executables to unpack the spectra, (GetSpectra32.exe) and moments (GetMomSp32.exe), respectively. Documentation on usage and output file formats also are included in the zip files.

17 WIND ENERGY↗

Radar - 449MHz - Astoria, OR (AST) - Reviewed Data

**Winds.** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and are combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature.** To measure atmospheric temperature, a radio acoustic sounding system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60 m up to 3.5 km for the 449 MHz. **Moments and Spectra.** The raw spectra and moments data are available for all dwells along each beam and are stored in daily files. For each day, there are files labeled "header" and "data." These files are generated by the radar data acquisition system (LAP-XM) and are encoded in a proprietary binary format. Values of spectral density at each Doppler velocity (FFT point), as well as the radial velocity, signal-to-noise ratio, and spectra width for the selected signal peak are included in these files. Attached zip files, *449mhz-spectra-data-extraction.zip* and *449mhz-moment-data-extraction.zip*, include executables to unpack the spectra, (GetSpectra32.exe) and moments (GetMomSp32.exe), respectively. Documentation on usage and output file formats also are included in the zip files.

17 WIND ENERGY↗

Seismology on Venus with infrasound observations from balloon and orbit

The study of Venus' evolution is inexorably linked with studying its interior properties, which can be investigated by performing seismic studies on the planet. However, seismology on Venus has long eluded planetary scientists due to technological challenges presented by high surface temperature and pressure, which limit lifetimes of surface-based instrumentation. In this white paper, we present two complementary techniques for performing seismology on Venus by measuring the low-frequency acoustic signature (infrasound) produced by seismic activity through coupling between the solid planet and the atmosphere. These techniques may be implemented with technology available today, without the use of high-temperature electronics.

79 ASTRONOMY AND ASTROPHYSICS↗

Radar - ANL Wind Profiler with RASS, Yakima - Raw Data

**Winds** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature** To measure atmospheric temperature, a radio acoustic sound system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60-m up to 3.5k m for the 449 MHz.

17 WIND ENERGY↗

Radar - ANL Wind Profiler, Walla Walla - Raw Data

**Winds** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature** To measure atmospheric temperature, a radio acoustic sound system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60-m up to 3.5k m for the 449 MHz.

17 WIND ENERGY↗

Radar - ANL Wind Profiler with RASS, Goldendale - Raw Data

**Winds** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature** To measure atmospheric temperature, a radio acoustic sound system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60-m up to 3.5k m for the 449 MHz.

17 WIND ENERGY↗

Radar - ESRL Wind Profiler with RASS, Prineville - Raw Data

**Winds** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature** To measure atmospheric temperature, a radio acoustic sound system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60-m up to 3.5k m for the 449 MHz.

17 WIND ENERGY↗