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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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Computer program provides a means of rapid data reduction of mass spectrograph data. The methods used are suited to mechanization on a digital computer since they consist of the systematic search of a large amount of tabular data and the unknown.
Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them efficiently transferable to the ground station is a twofold decision to make. Stronger compression methods, by distorting the data, can increase data throughput at the cost of accuracy which could affect scientific analysis of the data. On the other hand, preserving subtle details in the compressed data requires a high amount of data to be transferred, reducing the desired gains from compression. In this work, we propose a neural network-based lossy compression method to be used in NASA’s data-intensive imagery missions. We chose NASA’s Solar Dynamics Observatory (SDO) mission which transmits 1.4 terabytes of data each day as a proof of concept for the proposed algorithm. In this work, we propose an adversarially trained neural network, equipped with local and non-local attention modules to capture both the local and global structure of the image resulting in a better trade-off in rate-distortion (RD) compared to conventional hand-engineered codecs. The RD variational autoencoder used in this work is jointly trained with a channel-dependent entropy model as a shared prior between the analysis and synthesis transforms to make the entropy coding of the latent code more effective. We also studied how optimizing perceptual losses could help our neural compressor to preserve high-frequency details of the data in the reconstructed compressed image. Our neural image compression algorithm outperforms currently-in-use and state-of-the-art codecs such as JPEG and JPEG-2000 in terms of the RD performance when compressing extreme-ultraviolet (EUV) data. As a proof of concept for use of this algorithm in SDO data analysis, we have performed coronal hole (CH) detection using our compressed images, and generated consistent segmentations, even at a compression rate of ∼ 0.1 bits per pixel (compared to 8 bits per pixel on the original data) using EUV data from SDO.
The purpose of this investigation is to study methods and ways for rapid inversion programs involving the correlated k-method, and to modify the existing programs so that the rapid analysis of data can be accomplished. The earth's atmosphere as well as those around the planets consist of gases which emit radiation in the infrared spectral region, providing wealth of information about chemical and physical processes in the atmosphere. The atmospheric molecular constituents absorb and radiate by vibrational and rotational transitions, and the observed spectra exhibit characteristic spectral features in the region of the electromagnetic spectrum. The observed absorption or thermal emission spectra may be obtained with space-borne high resolution infrared spectrometers the 50-1000 micrometers spectral region. A detailed analysis of the observed spectra leads to information about the atmospheric thermal structure, composition, and the physical and chemical processes. The analytic techniques involve the development of radiative transfer models for the calculation of the observed radiance and transmittances for realistic atmospheric conditions and observational geometries, and the development of inversion methods for retrieval of atmospheric parameters from the observations.
Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.
Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.
The Quiet Spike F-15B flight research program investigated supersonic shock reduction using a 24-ft sub-scale telescoping nose boom on an F-15B airplane. The program primary flight test objective was to collect flight data for aerodynamic and structural models validation up to 1.8 Mach. Other objectives were to validate the mechanical feasibility of a morphing fuselage at the operational conditions and determine the near-field shock wave characterization. The stability and controls objectives were to assess the effect of the spike on the stability, controllability, and handling qualities of the aircraft and to ensure adequate stability margins across the entire research flight envelop. The two main stability and controls issues were the effects of the telescoping nose boom influenced aerodynamics on the F-15B aircraft flight dynamics and air data and angle of attack sensors. This paper reports on the stability and controls flight envelope clearance methods and flight test analysis of the F-15B Quiet Spike. Brief pilot commentary on typical piloting tasks, approach and landing, refueling task, and air data sensitivity to the flight control system are also discussed in this report.
Described here are nonlinear regression estimators for the three-Weibull distribution. Issues relating to the bias and invariance associated with these estimators are examined numerically using Monte Carlo simulation methods. The estimators were used to extract parameters from sintered silicon nitride failure data. A reliability analysis was performed on a turbopump blade utilizing the three-parameter Weibull distribution and the estimates from the sintered silicon nitride data.
The existing RocketWeb(TradeMark) Internet Analysis System (httr)://www.iohnsonrockets.com/rocketweb) provides an integrated set of advanced analysis tools that can be securely accessed over the Internet. Since these tools consist of both batch and interactive analysis codes, the system includes convenient methods for creating input files and evaluating the resulting data. The RocketWeb(TradeMark) system also contains many features that permit data sharing which, when further developed, will facilitate real-time, geographically diverse, collaborative engineering within a designated work group. Adding work group management functionality while simultaneously extending and integrating the system's set of design and analysis tools will create a system providing rigorous, controlled design development, reducing design cycle time and cost.
Characterization of the International Space Station (ISS) microbiome has been enabled by sample return and Earth-based analysis. As human exploration pushes beyond low-Earth orbit, microbial-related crew health, planetary protection, and space research requires in situ capabilities. Steps toward reducing Earth-dependence for complex sample analysis began in 2016 with the amplification of DNA within the miniPCR thermal cycler and DNA sequencing with the MinION sequencer onboard the ISS; for both, samples were prepared on Earth. In 2017, these platforms synergistically enabled the in-situ identification of unknown bacteria collected and cultured from ISS surfaces, thereby shifting the paradigm that microbial cultures had to be returned to Earth. The following year, a culture-independent, swab-to-sequencer method further advanced spaceflight microbiology, demonstrating that culturing could be excluded and provided enhanced insight into the bacterial profile of ISS surfaces. Based on the success of these payloads in confirming the ability to meet crew health identification requirements and the benefits accompanying a culture-independent method, the BioMole Facility was established by the medical operations Crew Health Care Systems team. BioMole is the set of hardware, consumables, and procedures required to support sample preparation and nanopore sequencing onboard the ISS. BioMole goals include expanding sample sources, comparing data to previous methods, demonstrating onboard data analytics, and validating new hardware. To date, comparative surface analysis, molecular- and culture-based, has been completed. Additionally, the demonstration of a sample-to-answer process was achieved when BioMole data was processed onboard using the IBM Open Data and AI Edge software platform installed on the ISS-residing Spaceborne Computer-2. The taxonomic profiles generated from the edge analysis were as expected and paralleled that of the downlinked processed data. Future BioMole efforts involve microbial profiling of the ISS water system, ISS validation of the MinION Mk1C, and an expansion to a research facility available to investigators.
Described here are nonlinear regression estimators for the three-parameter Weibull distribution. Issues relating to the bias and invariance associated with these estimators are examined numerically using Monte Carlo simulation methods. The estimators were used to extract parameters from sintered silicon nitride failure data. A reliability analysis was performed on a turbopump blade utilizing the three-parameter Weibull distribution and the estimates from the sintered silicon nitride data.
An overview of the methods of line-by-line and whole-band analysis developed by The Ohio State University spectroscopy group is presented.
Theoretical analysis of polarization filtering of synthetic-aperture-radar (SAR) returns provide hybrid method applied to either (1) maximize signal-to-noise ratio of return from given target or (2) enhance contrast between targets of two different types (that have different polarization properties). Method valid for both point and extended targets and for both monostatic and bistatic radars as well as SAR. Polarization information in return signals provides more complete description of radar-scattering properties of targets and used to obtain additional information about targets for use in classifying them, discriminating between them, or enhancing features of radar images.
This method is especially well suited for analyzing time-series data that represent nonstationary and nonlinear physical phenomena. The method is based principally on the concept of empirical mode decomposition (EMD), according to which any complicated signal (as represented by digital samples) can be decomposed into a finite number of functions, called "intrinsic mode functions" (IMFs), that admit well-behaved Hilbert transforms. The local energies and the instantaneous frequencies derived from the IMFs through Hilbert transforms can be used to construct an energy-frequency-time distribution, denoted a Hilbert spectrum.
According to various embodiments, a method is provided for determining aberration data for an optical system. The method comprises collecting a data signal, and generating a pre-transformation algorithm. The data is pre-transformed by multiplying the data with the pre-transformation algorithm. A discrete Fourier transform of the pre-transformed data is performed in an iterative loop. The method further comprises back-transforming the data to generate aberration data.
A method is presented for interim use in assessing the noise generated by fans and compressors in turbojet and turbofan engines. One-third octave band sound pressure levels consisting of broadband, discrete tone, and combination-tone noise components are predicted. Spectral distributions and directivity variations are specified. The method is based on that developed by other investigators with modifications derived from an analysis of full-scale, single-stage fan data. Comparisons of predicted and measured noise performance are presented, and requirements for improving the method are discussed.
Methods are derived for applying the V/Vmax variable when several complete samples are analyzed simultaneously. A new, related, variable, V(e)/V(a), which is superior to V/Vmax when sufficient observational data are available, is introduced. It is shown how statistically independent complete samples can be generated from partially overlapping samples such that each observed object appears only once in the analysis. These methods make it possible to combine the information from different complete samples, and to make an efficient use of all available data. Illustrative examples for quasars are given. It is shown how the generalized V/Vmax and V(e)/V(a) can be used to find the amount of cosmological evolution of quasars and its associated range of uncertainty.
Earth Observation data are a vital resource for studying long term changes, but the large data volumes can be challenging to analyze. Time series analysis in particular is hampered by the typical thin-time-slice file organization. We examine several potential solutions inspired in large part by the data-parallel methods that have arisen with cloud computing. These solutions include various combinations of data re-organization, spatial indexing, distributed storage and pre-computation that we term "Analytics Optimized Data Stores" (AODS). We find that even simple solutions (such as a data cube) produce more than an order of magnitude improvement; the best provide two to three orders of magnitude improvement. The most performant solutions have tradeoffs in terms of generality or storage footprint, but may nonetheless be useful components in data analytics frameworks where performance is critical.
A unique adaptation of the hydrogen-bubble flow visualization method was applied to measure velocity profiles and film thicknesses of very thin films on an inclined plane wall. Data were obtained in the three flow regions for a developing falling film with an initially uniform velocity profile and thickness less than or equal to 0.1 in. The measured profiles compared more favorably with parabolic profiles in the intermediate fully developed region than in the initial developing region. However, measured film thicknesses compared favorably with a simplified solution of the integral momentum equation based on parabolic velocity profiles. The results confirm the theoretical prediction that a relatively long distance may be required even for a thin film before nonaccelerating flow with a constant film thickness is obtained and Nusselt's classical analysis applies. The experimental technique was shown to be a practical experimental method for obtaining data for the two-dimensional laminar flow of thin liquid films.