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NASA NTRS1999

HALOE Algorithm Improvements for Upper Tropospheric Sounding

This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth UARS Science Investigator Program entitled "HALOE Algorithm Improvements for Upper Tropospheric Soundings." The goal of this effort is to develop and implement major inversion and processing improvements that will extend HALOE measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first-year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multi-channel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others.

McHugh, Martin J.↗

NASA NTRSDate not supplied

Generating Essential Climate Variables from Multiple Satellite Hyperspectral Remote Sensors

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. There are two shortcomings of this approach. First, it is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Secondly, differences in level-2 retrieval algorithms can lead to errors in the fused multi-satellite data. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to data collected from Atmospheric Infrared Sounder (AIRS) on Aqua satellite and Cross-track Infrared Sounder (CrIS) on SNPP and NOAA20 and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Atmosphere Observing System (AOS).

Xu Liu↗

NASA NTRS2019

Remote Sensing of Daytime Water Leaving Reflectances of Oceans and Large Inland Lakes from EPIC onboard the DSCOVR Spacecraft at Lagrange-1 Point

The NASA’s Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) satellite has been making multiple observations of the entire sunlit Earth in a given day from the Sun-Earth Lagrangian L1 point since the summer of 2015. EPIC contains 10 narrow channels in the 317–780 nm solar spectral range. The data acquired with EPIC have already been used in a variety of scientific investigations, including the study of the global ozone levels, aerosol index and aerosol optical depth, UV reflectivity of clouds over land and ocean, cloud height over land and ocean, and vegetation indices. In this article, we report that EPIC data, particularly for the data measured with narrow channels centered near 443, 551, and 680 nm, can also have important applications in remote sensing of ocean color in different geographical regions. We have modified a version of a multi-channel atmospheric correction algorithm for Moderate Resolution Imaging Spectro Radiometer (MODIS) ocean color applications and adapted the algorithm for processing EPIC data. We present three case studies on water leaving reflectance retrievals from EPIC data acquired over a large turbid river, inland lakes, and oceans. We conclude that a future ocean color instrument on board a satellite at the L1 point, which provides continuous view of the full sunlit disk of the Earth, will complement and extend ocean color observations with the low Earth observing polar orbital and geostationary satellite instruments in both the spatial and time domains.

remote sensing↗

DOE OSTI2026

Evaluation of an event-driven 3FI ASIC for spectroscopic X-ray detection with synchrotron radiation

The novel design and evaluation on the NSLS-II beamline of the 3FI application-specific integrated circuit (ASIC) bump-bonded to a simple, planar, 2D segmented silicon sensor are presented. The ASIC was developed for full-field fluorescence spectral X-ray imaging (3FI). It is a small-scale prototype that features a square array of 32 × 32 pixels, and the size of the pixels is 100 µm × 100 µm. The ASIC was implemented in a 65 nm CMOS integrated circuit fabrication process. Each pixel incorporates a charge-sensitive amplifier, a shaping filter, a discriminator, a peak detector and a sample-and-hold circuit, allowing detection of events and storage of signal amplitudes. The system operates in a frameless event-driven readout mode, outputting analog values for threshold-triggered events, allowing high-speed multi-element X-ray fluorescence data acquisition. The 3FI ASIC achieves per-channel spectrometric performance at a power consumption of only 200 µW per pixel, with nearly all dissipation confined to the analog front-end. An energy resolution is measured at the level of 308 eV full width at half-maximum (FWHM) at 8.04 keV (Cu Kα), and 138 eV FWHM at 3.69 keV (Ca Kα). This per-pixel capability makes the prototype suitable for in situ trace element microanalysis in biological and environmental studies. Moreover, the frameless architecture of the detector is designed to address limitations of conventional X-ray fluorescence microscopy, which typically requires mechanical scanning, by enabling continuous high-throughput data acquisition in future full-field implementations.

47 OTHER INSTRUMENTATION↗

NASA NTRS2012

NASA/SPoRT's GOES-R Activities in Support of Product Development, Management, and Training

The NASA Short-term Prediction Research and Transition (SPoRT) Center supports many activities within the GOES-R Proving Grounds (PG). These include the development of imagery from existing instrumentation as a proxy to future Advanced Baseline Imager (ABI) capabilities on GOES-R. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) instruments are used to provide a glimpse of the multi-spectral capabilities that will become the norm as the number of channels and data rate dramatically increase with GOES-R. The NOAA/NWS has plans to provide operational users with all ABI channels at the highest resolution. Data fusion of individual channels into composite red, green, and blue imagery products will assist the end user with this future wave of information. While increasing the efficiency in the operational use of ABI channels, these composites provide only qualitative information. Within the GOES-R PG, SPoRT and other partners are exploring ways to include quantitative information as part of the composite imagery. However, limitations in local hardware processing and/or data bandwidth for users of the GOES-R data stream are challenges to overcome. This presentation will discuss the creation of these composite images as well as possible solutions to address these processing challenges. In a similar manner the Geostationary Lightning Mapper (GLM) to be launched on GOES-R presents several data management challenges. The GLM is a pioneering instrument to quantify total lightning from a geostationary platform. The expected data frequency from the GLM is to be at a sub-minute interval. Users of such a data set may have little experience in handling such a rapid update of information. To assist users, SPoRT is working with the NWS to develop tools within the user fs decision support system to allow tracking and analysis of total lightning from a storm-based perspective. This presentation will discuss the challenges and progress of this tool development work. With new data and products comes the need for user Training. Within the GOES-R PG SPoRT is supporting the demonstration of these future products by providing various training materials to end users. A summary of training provided to operational users will be discussed.

Fuell, Kevin K.↗

NASA NTRS1984

Time series modeling of human operator dynamics in manual control tasks

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Biezad, D. J.↗

NASA NTRS1984

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

Biezad, D. J.↗

DOE OSTI2022

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗

NASA NTRS2001

High Speed PC Based Data Acquisition and Instrumentation for Measurement of Simulated Low Earth Orbit Thermally Induced Disturbances

The Hubble Space Telescope (HST) Disturbance Verification Test (DVT) was conducted to characterize responses of the Observatory's new set of rigid solar array's (SA3) to thermally induced 'creak' or stiction releases. The data acquired in the DVT were used in verification of the HST Pointing Control System on-orbit performance, post-Servicing Mission 3B (SM3B). The test simulated the on-orbit environment on a deployed SA3 flight wing. Instrumentation for this test required pretest simulations in order to select the correct sensitivities. Vacuum compatible, highly accurate accelerometers and force gages were used for this test. The complexity of the test, as well as a short planning schedule, required a data acquisition system that was easy to configure, highly flexible, and extremely robust. A PC Windows oriented data acquisition system meets these requirements, allowing the test engineers to minimize the time required to plan and perform complex environmental test. The SA3 DVT provided a direct practical and complex demonstration of the versatility that PC based data acquisition systems provide. Two PC based data acquisition systems were assembled to acquire, process, distribute, and provide real time processing for several types of transducers used in the SA3 DVT. A high sample rate digital tape recorder was used to archive the sensor signals. The two systems provided multi-channel hardware and software architecture and were selected based on the test requirements. How these systems acquire and processes multiple data rates from different transducer types is discussed, along with the system hardware and software architecture.

Sills, Joel W., Jr.↗

NASA NTRS1990

Near infrared radiances observed by the UK C130 multi-channel radiometer during the marine stratocumulus IFO and preliminary comparison with model calculations

A preliminary analysis of some of the narrow band radiance data measured on the U.K. Meteorological Office's C130 aircraft during the marine stratocumulus intensive field observation of First ISCCP Regional Experiment (FIRE), San Diego 29 June to 18 July 1987, is presented. The data are compared with Monte Carlo calculations of the reflectance and transmittance of the cloud based upon the observed droplet size distribution. The main scientific question being addressed is whether there is any evidence of anomalous absorption within the cloud which had been observed in similar measurements (Rozenberg et al., 1974; Twomey and Cocks, 1982; Foot, 1988). The measurements also indicate the potential for remotely sensing cloud properties. The data and method of presentation discussed here clearly separates out clouds in terms of the size of the cloud droplets. All of the daytime C130 FIRE flights have been studied and are consistent with the data presented here. There appears to be no peculiarities that might arise, for example if pollution were to be a significant factor in determining cloud absorption. Variation in the inferred size parameters, r sub e, along runs are also very small.

Foot, J. S.↗

NASA NTRSDate not supplied

Linear Array Photodiode and Data Acquisition System Development for Multi-Point Line FLDI Measurements

The continuous development and advancement of multi-point line focused laser differential interferometry (FLDI) instruments requires larger numbers of acquisition channels to make more finely spatially resolved measurements of high-frequency flow fluctuations. No current off-the-shelf system exists for these line FLDI measurements, and so a single unified system consisting of a linear array photodiode, required electronics, and a data acquisition system has been developed to enhance the measurement resolution, both spatially and temporally. A printed circuit board was developed on which the linear array photodiode is mounted for inclusion into an existing FLDI system, and amplifier breakout boards incorporate electronics to condition the signal for the data acquisition system while retaining the necessary high frequency response. The data acquisition system uses a National Instruments chassis and multiple oscilloscope modules, with a specially-designed LabVIEW user interface for laboratory and wind tunnel setup, calibration, and testing. Details regarding the development of the linear array photodiode system and the data acquisition system are provided, and systematic testing of all components is presented, culminating in a test of the system integrated into an existing line FLDI system for measurements of a turbulent jet.

Joshua M Weisberger↗

DOE OSTI2021

Topological Machine Learning Methods for Power System Responses to Contingencies

While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remains untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topology-based system that depends on a neural network architecture for impact metric classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn more about the complex relationships between electrical properties and local topological measurements on their simulated response to contingencies for the NREL-SIIP power system.

contingency analysis↗

NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗

NASA NTRS2002

Atmospheric electron x-ray spectrometer

The present invention comprises an apparatus for performing in-situ elemental analyses of surfaces. The invention comprises an atmospheric electron x-ray spectrometer with an electron column which generates, accelerates, and focuses electrons in a column which is isolated from ambient pressure by a:thin, electron transparent membrane. After passing through the membrane, the electrons impinge on the sample in atmosphere to generate characteristic x-rays. An x-ray detector, shaping amplifier, and multi-channel analyzer are used for x-ray detection and signal analysis. By comparing the resultant data to known x-ray spectral signatures, the elemental composition of the surface can be determined.

Feldman, Jason E.↗

NASA NTRS2008

HST Super Lightweight Interchangeable Carrier (SLIC) Static Test

The HST Super Light Weight Interchangeable Carrier Static Test program calls for a total of 15 load cases with an average of 9 simultaneous push/pull locations per load case. This testing program represents the most complex static test ever attempted at Goddard Space Flight Center. Many unique multi-pull fixtures were designed to apply the simultaneous loading. Additionally, a total of 600 channels of data required processing for each loadcase. A total of 1100 separate strain gages were installed on SLIC. A team of 15 trained technicians were needed to apply test loads via mechanical hand pumps for several load cases. All 15 load cases were successfully conducted within 15 weeks. The ManTech team successfully tested all SLIC 1200 interface clips to the required testing loads. Several unique designs were needed to address testing challenges as loadline interference, Payload Safety, payload flexibility and opposing load applications.

Chambers, William V.↗

NASA NTRS2012

High-Speed, Multi-Channel Serial ADC LVDS Interface for Xilinx Virtex-5 FPGA

Analog-to-digital converters (ADCs) are used in scientific and communications instruments on all spacecraft. As data rates get higher, and as the transition is made from parallel ADC designs to high-speed, serial, low-voltage differential signaling (LVDS) designs, the need will arise to interface these in field programmable gate arrays (FPGAs). As Xilinx has released the radiation-hardened version of the Virtex-5, this will likely be used in future missions. High-speed serial ADCs send data at very high rates. A de-serializer instantiated in the fabric of the FPGA could not keep up with these high data rates. The Virtex-5 contains primitives designed specifically for high-speed, source-synchronous de-serialization, but as supported by Xilinx, can only support bitwidths of 10. Supporting bit-widths of 12 or more requires the use of the primitives in an undocumented configuration, a non-trivial task. A new SystemVerilog design was written that is simpler and uses fewer hardware resources than the reference design described in Xilinx Application Note XAPP866. It has been shown to work in a Xilinx XC5VSX24OT connected to a MAXIM MAX1438 12-bit ADC using a 50-MHz sample clock. The design can be replicated in the FPGA for multiple ADCs (four instantiations were used for a total of 28 channels).

Taylor, Gregory H.↗

NASA NTRS1994

Applications drivers for data parking on the Information Superhighway

As the cost of data storage continues to decline (currently about one-millionth of its cost four decades ago) entirely new applications areas become economically feasible. Many of these new areas involved the extraordinarily high data rates and universal connectivity soon to be provided by the National Information Infrastructure (NII). The commonly held belief is that the main driver for the NII will be entertainment applications. We believe that entertainment applications as currently touted (multi-media, 500 video channels, video-on-demand, etc.) will play an important but far from dominant role in the development of the NII and its data storage components. The most pervasively effective drivers will be medical applications such as telemedicine and remote diagnosis, education and environmental monitoring. These applications have a significant funding base and offer a clearly perceived opportunity to improve the nation's standard of living. The NII's wideband connectivity both nationwide and worldwide requires a broad spectrum of data storage devices with a wide-range of performance capabilities. These storage centers will be dispersed throughout the system. Magnetic recording devices will fill the majority of these new data storage requirements for at least the rest of this century. The storage needs of various application areas and their respective market sizes will be explored. The comparative performance of various magnetic technologies and competitive alternative storage systems will be discussed.

Johnson, Clark E., Jr.↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗