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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Source Diagnostic Fan II (22-Inch) Duct Mode Characteristics as Measured by the Rotating Rake Mode Measurement System while Operated in the NASA Glenn 9x15 Low Speed Wind Tunnel

A 22-inch scale model of the Honeywell Quiet High Speed Fan II was tested in the NASA Glenn 9- by 15-foot Low Speed Wind Tunnel at a tunnel Mach number of 0.10. This was an entry to investigate the effect of “stator clocking” on noise. The fan consisted of a moderately aft swept rotor, and an aft swept set of stator vanes. The fan stage consisted of 22 rotor blades, 50 stator vanes, and 10 downstream support struts. A set of stator vanes designed for lower noise was tested as well as a baseline stator vane set. The stator assembly could be rotated several degrees to adjust the clocking angle between the stator vane pack and the strut assembly. All configurations were with a hard wall duct (no acoustic treatment). The NASA Glenn Research Center’s Rotating Rake Mode Measurement System was utilized to obtain a complete map of the acoustic duct modes present in the ducted fan. The system is a radial rake emersed into the duct that continuously rotates about the duct centerline. For the two stator configurations, data were acquired at several different fan speeds which included nominal, approach, cutback, and takeoff conditions. Analysis of the mode power level results at the fan fundamentals showed the improved designed set resulted in lower rotor-stator and rotor-strut interaction acoustic levels for the interaction modes. Varying the angle between the stators and struts was shown to be a viable method to achieve a minimum in rotor-strut interaction mode power level. Multiple-pure-tones generated by the Quiet High Speed Fan II in the inlet were also measured.

Fan Noise↗
NASA NTRSDate not supplied

Source Diagnostic Fan II (22-inch) Duct Mode Characteristics as Measured by the Rotating Rake Mode Measurement System while Operated in the NASA Glenn 9x15 Low Speed Wind Tunnel

The second entry of the Source Diagnostic Test (SDT2) was a continuation of the first SDT entry with additional parameters tested. The rotor, stators, and general flow path hardware used in SDT2 were the same as those for SDT1. This included a radial baseline set of stator vanes, which had a vane count such that the rotor-stator interaction at the fan blade passing fundamental was cut-off, as is typical for modern turbofans. Two sets of stator vanes were designed and tested with a count generating a cut-on rotor-stator interaction at the fan blade passing fundamental. One of the sets maintained the no aerodynamic sweep as the radial baseline, the other was designed with leading edge sweep with the intent to generate lower noise. The NASA Glenn Research Center’s Rotating Rake Mode Measurement System was utilized to obtain a complete map of the acoustic duct modes present. The system is a radial rake emersed into the duct that continuously rotates about the duct centerline. For each of the three stator vane configurations, data were acquired at several different fan speeds which included nominal, approach, cutback, and takeoff conditions. Analysis of the mode power level results at the fan fundamentals showed the improved designed set resulted in lower rotor-stator interaction mode acoustic levels. Multiple-pure tones generated by the M5 rotor in the inlet were also measured.

Turbofan↗
NASA NTRS2022

2021 Corrective Measures Implementation and Interim Measures Annual Status Report: Summary of Biosparge System Operation and Maintenance, and Interim Groundwater Monitoring Mobile Launch Platform Rehabilitation Sites / Vehicle Assembly Building Area (SWMU 056) Kennedy Space Center, Florida

This report presents a summary of the Corrective Measures Implementation (CMI) and Interim Measure (IM) implementation activities that occurred from January 2021 through December 2021 at the Mobile Launch Platform Rehabilitation Sites (MLP)/Vehicle Assembly Building (VAB) Area, Solid Waste Management Unit 056 (SWMU 056), located at the John F. Kennedy Space Center, Florida. The following summaries briefly describe areas within SWMU 056 identified by historical site investigation activities where groundwater monitoring and remedial actions have been implemented to date.

Randall K. Sillan↗
NASA NTRSDate not supplied

Transient Aircraft Soot Emissions Indicate That Steady-State Measurements Likely Underestimate Real-World, Take-Off Emissions: Time-Varying Aircraft Take-Off Emissions Indices Measured at Los Angeles International Airport

Aircraft engine emissions are unique among mobile pollution sources in that their impacts affect the local air quality near airports as well as upper tropospheric composition and climate over regional-to-hemispheric scales. Furthermore, air travel and its resulting emissions are expected to rebound from the recent COVID-related lows to increase dramatically over the next several decades. Given the multi-decade service lifetime of many commercial aircraft, it is critically important to quantitatively understand the real-world emissions coming from these engines in order to inform environmental assessment and modelling activities. Here, we present a detailed analysis of aircraft emissions during take-off operations at Los Angeles International Airport. The data were collected as part of the NASA Alternative Fuel Effects on Contrails and Cruise Emissions (ACCESS) project in May 2014, and the dataset is publicly available as described by Moore et al. [1]. In particular, we focus on the time-varying nature of the plume concentrations where clear differences in particle size and non-volatile particle fraction are observed during the early portion of the take-off plume relative to the later portion of the plume. We compare the transient emissions indices measured here to engine certification values in the International Civil Aviation Organization (ICAO) Emissions Databank, which suggests that steady-state measurements may underestimate the real-world, non-volatile particle emissions. The implications of this finding for modelling aircraft particle emissions will be discussed.

Richard H. Moore↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
DOE OSTI2025

Energy resolution and gain measurements in Argon-based gas mixtures: Exploring Ar:CF 4 for low energy measurements with TPCs

Time Projection Chambers (TPCs) are among the most advanced charged-particle detectors. Gas-filled TPCs have tracking capabilities that provide 3D-imaging of charged particles with a good energy resolution for spectroscopy. Different gas mixtures have different properties that determine the energy resolution as well as the spatial resolution. Therefore, optimization of operating conditions is required to simultaneously obtain adequate gain, energy resolution, spatial/track resolution, as well as higher drift velocities for high counting rates applications. Ar:CF 4 gas mixture has higher electron drift velocities and lower electron diffusion, which makes it an attractive candidate for TPC filling gas for low energy nuclear physics applications as compared to commonly used Ar:CH 4 and Ar:CO 2 gas mixtures, namely when tracking information is needed. However, other properties, including energy resolution and gain, remain largely unexplored in Ar:CF 4 especially at pressures and other operating conditions relevant for low-energy nuclear physics applications. Here, in this paper we report on gain and energy resolution measurements, using Gas Electron Multipliers (GEMs), in the less explored Ar:CF 4 mixture (Alfonsi et al., 2006), as well as in the more commonly used gas mixtures Ar:CH 4 and Ar:CO 2 . In addition to obtaining energy resolution and gain, we provide results from Garfield++ simulations for gain fluctuations, and their impact on energy resolution is discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Protecting backaction-evading measurements from parametric instability

Noiseless measurement of a single quadrature in systems of parametrically coupled oscillators is theoretically possible by pumping at the sum and difference frequencies of the two oscillators, realizing a backaction-evading (BAE) scheme. Although this would hold true in the simplest scenario for a system with pure three-wave mixing, implementations of this scheme are hindered by unwanted higher-order parametric processes that destabilize the system and add noise. We show analytically that detuning the two pumps from the sum and difference frequencies can stabilize the system and fully recover the BAE performance, enabling operation at otherwise inaccessible cooperativities. We also show that the acceleration demonstrated in a weak-signal-detection experiment [Jiang , PRX Quantum 4, 020302 (2023)] was only achievable because of this detuning technique.

Ruddy, E. P.↗
DOE OSTI2024

233 U oxide Measurement Campaign Data: Passive and Active Neutron Multiplicity Measurements of Uranium Oxide Samples at Oak Ridge National Laboratory

During FY2023, three measurement campaigns were conducted at Oak Ridge National Laboratory. The goal was to quantify the neutron signatures of samples of uranium oxide containing uranium 233 and uranium-235. This report presents the neutron multiplicity data obtained using the large volume active well coincidence counter (LV-AWCC).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗