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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically Air Traffic Control System Command Center (ATCSCC) planning telecon audio transcriptions. The ATCSCC hosts bi-hourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. Provided speech transcripts, ITN is the process of converting unformatted raw Automated Speaker Recognition (ASR) model transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a fine-tuned Bidirectional Encoder Representations from Transformers neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With an overall Punctuation Error Rate (PER) of 25.56 and Word Error Rate with Punctuation and Capitalization (WER PC) of 5.47, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

ATM↗
NASA NTRS2024

Augmenting RANS Turbulence Models Guided by Field Inversion and Machine Learning

This report investigates the use of a data-driven approach, viz., Field Inversion and Machine Learning (FIML), to improve conventional RANS turbulence models like the Spalart-Allmaras model and the Menter SST k-ω model. One of the crucial aspects of using an ML-based approach with limited training data to produce corrections that are generalizable to a large range of flow configurations is to design appropriate “features” (inputs to the ML model). A model, based on guidance from the FIML methodology, is presented in analytical form. An additional list of potential features is provided. Although these were not used in the present correction, they were considered in the course of its development, and are included to fully document the complete process employed in the present work.

turbulence modeling↗
NASA NTRS2013

Source Parameter Inversion for Recent Great Earthquakes from a Decade-long Observation of Global Gravity Fields

We quantify gravity changes after great earthquakes present within the 10 year long time series of monthly Gravity Recovery and Climate Experiment (GRACE) gravity fields. Using spherical harmonic normal-mode formulation, the respective source parameters of moment tensor and double-couple were estimated. For the 2004 Sumatra-Andaman earthquake, the gravity data indicate a composite moment of 1.2x10(exp 23)Nm with a dip of 10deg, in agreement with the estimate obtained at ultralong seismic periods. For the 2010 Maule earthquake, the GRACE solutions range from 2.0 to 2.7x10(exp 22)Nm for dips of 12deg-24deg and centroid depths within the lower crust. For the 2011 Tohoku-Oki earthquake, the estimated scalar moments range from 4.1 to 6.1x10(exp 22)Nm, with dips of 9deg-19deg and centroid depths within the lower crust. For the 2012 Indian Ocean strike-slip earthquakes, the gravity data delineate a composite moment of 1.9x10(exp 22)Nm regardless of the centroid depth, comparing favorably with the total moment of the main ruptures and aftershocks. The smallest event we successfully analyzed with GRACE was the 2007 Bengkulu earthquake with M(sub 0) approx. 5.0x10(exp 21)Nm. We found that the gravity data constrain the focal mechanism with the centroid only within the upper and lower crustal layers for thrust events. Deeper sources (i.e., in the upper mantle) could not reproduce the gravity observation as the larger rigidity and bulk modulus at mantle depths inhibit the interior from changing its volume, thus reducing the negative gravity component. Focal mechanisms and seismic moments obtained in this study represent the behavior of the sources on temporal and spatial scales exceeding the seismic and geodetic spectrum.

Parameter Inversion↗
NASA NTRS2019

Sensitivity of Inherent Optical Properties from Ocean Reflectance Inversion Models to Satellite Instrument Wavelength Suites

The Earth science community seeks to develop climate data records (CDRs) from satellite measurements of ocean color, a continuous data record that now exceeds 20 years. Space agencies will launch additional instruments in the coming decade that will continue this data record, including the NASA PACE spectrometer. Inherent optical properties (IOPs) quantitatively describe the absorbing and scattering constituents of seawater and can be estimated from satellite-observed spectroradiometric data using semi-analytical algorithms (SAAs). SAAs exploit the contrasting optical signatures of constituent matter at spectral bands observed by satellite sensors. SAA performance, therefore, depends on the spectral resolution of the satellite spectroradiometer. A CDR spanning SeaWiFS, MODIS, OLCI, and PACE, for example, would include IOPs derived using varied wavelength suites if all available wavelengths were considered. Here, we explored differences in derived IOPs that stem simply from the use of (eight) different wavelength suites of input radiometric measurements. Using synthesized data and SeaWiFS Level-3 mission-long composites, we demonstrated equivalent SAA performance for all wavelength suites, but that IOP retrievals vary by several percent across wavelength suites and as a function of water type. The differences equate to roughly ≤ 6, 12, and 7% for a(sub dg)(443), a(sub ph)(443), and b(sub bp)(443), respectively, for waters with C(sub a) ≤ 1 mg -cu m. These values shrink for sensors with similar wavelength suites (e.g., SeaWiFS, MODIS, and MERIS) and rise to substantially larger values for higher C(sub a) waters. Our results also indicate that including 400 nm (in the case of OLCI) influences the derived IOPs, using longer wavelengths (>600 nm) influences the derived IOPs when there is a red signal, and, including additional spectral information shows potential for improved IOP estimation, but not without revisiting SAA parameterizations and execution. While modest in scope, we believe this study contributes to the knowledge base for CDR development. The implication of ignoring such an analysis as CDRs continue to be developed is a prolonged inability to distinguish between algorithmic and environmental contributions to trends and anomalies in the IOP time-series.

ocean color satellites↗