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At least 271 records · Page 15

Spaceflight Operations Services Grid Prototype

NASA over the years has developed many types of technologies and conducted various types of science resulting in numerous variations of operations, data and applications. For example, operations range from deep space projects managed by JPL, Saturn and Shuttle operations managed from JSC and KSC, ISS science operations managed from MSFC and numerous low earth orbit satellites managed from GSFC that are varied and intrinsically different but require many of the same types of services to fulfill their missions. Also, large data sets (databases) of Shuttle flight data, solar system projects and earth observing data exist which because of their varied and sometimes outdated technologies are not and have not been fully examined for additional information and knowledge. Many of the applications/systems supporting operational services e.g. voice, video, telemetry and commanding, are outdated and obsolete. The vast amounts of data are located in various formats, at various locations and range over many years. The ability to conduct unified space operations, access disparate data sets and to develop systems and services that can provide operational services does not currently exist in any useful form. In addition, adding new services to existing operations is generally expensive and with the current budget constraints not feasible on any broad level of implementation. To understand these services a discussion of each one follows. The Spaceflight User-based Services are those services required to conduct space flight operations. Grid Services are those Grid services that will be used to overcome, through middleware software, some or all the problems that currently exists. In addition, Network Services will be discussed briefly. Network Services are crucial to any type of remedy and are evolving adequately to support any technology currently in development.

Bradford, Robert N.↗

Characterization of AIRS temperature and water vapor measurement capability using correlative observations

In this presentation we address several fundamental issues in the measurement of temperature and water vapor by AIRS: accuracy, precision, vertical resolution and biases as a function of cloud amount. We use two correlative data sources. First we compare AIRS total water vapor with that from the Advanced microwave Sounding Radiometer for EOS (AMSR-E) instrument, also onboard the Aqua spacecraft. AMSRE uses a mature methodology with a heritage including the operational Special Sensor Microwave Imager (SSM/I) instruments. AIRS and AMSR-E observations are collocated and simultaneous, providing a very large data set for comparison: about 200,000 over-ocean matches daily. We show small cloud-dependent biases between AIRS and AMSR-E total water vapor for several oceanic regions. Our second correlative data source is several hundred dedicated radiosondes launched during AIRS overpasses.

meteorology↗

Caloris Basin - An enhanced source for potassium in Mercury's atmosphere

Enhanced abundances of neutral K in the atmosphere of Mercury have been found above the longitude range containing Caloris Basin. Results of a large data set including six elongations of the planet between June 1986 and January 1988 show typical K column abundances of about 5.4 x 10 to the 8th K atmos/sq cm. During the observing period in October 1987, when Caloris Basin was in view, the typical K column was about 2.7 x 10 to the 9th K atoms/sq cm. Another large value was seen over the Caloris antipode in January 1988. This enhancement is consistent with an increased source of K from the well-fractured crust and regolith associated with this large impact basin. The phenomenon is localized because at most solar angles, thermal alkali atoms cannot move more than a few hundred kilometers from their source before being lost to ionization by solar ultraviolet radiation.

Sprague, Ann L.↗

Linear Spectral Analysis of Plume Emissions Using an Optical Matrix Processor

Plume spectrometry provides a means to monitor the health of a burning rocket engine, and optical matrix processors provide a means to analyze the plume spectra in real time. By observing the spectrum of the exhaust plume of a rocket engine, researchers have detected anomalous behavior of the engine and have even determined the failure of some equipment before it would normally have been noticed. The spectrum of the plume is analyzed by isolating information in the spectrum about the various materials present to estimate what materials are being burned in the engine. Scientists at the Marshall Space Flight Center (MSFC) have implemented a high resolution spectrometer to discriminate the spectral peaks of the many species present in the plume. Researchers at the Stennis Space Center Demonstration Testbed Facility (DTF) have implemented a high resolution spectrometer observing a 1200-lb. thrust engine. At this facility, known concentrations of contaminants can be introduced into the burn, allowing for the confirmation of diagnostic algorithms. While the high resolution of the measured spectra has allowed greatly increased insight into the functioning of the engine, the large data flows generated limit the ability to perform real-time processing. The use of an optical matrix processor and the linear analysis technique described below may allow for the detailed real-time analysis of the engine's health. A small optical matrix processor can perform the required mathematical analysis both quicker and with less energy than a large electronic computer dedicated to the same spectral analysis routine.

Gary, C. K.↗

An Orbital Meteoroid Stream Survey Using the Southern Argentina Agile Meteor Radar (SAAMER) Based on a Wavelet Approach

Over a million individually measured meteoroid orbits were collected with the Southern Argentina Agile MEteor Radar (SAAMER) between 2012-2015. This provides a robust statistical database to perform an initial orbital survey of meteor showers in the Southern Hemisphere via the application of a 3D wavelet transform. The method results in a composite year from all 4 years of data, enabling us to obtain an undisturbed year of meteor activity with more than one thousand meteors per day. Our automated meteor shower search methodology identified 58 showers. Of these showers, 24 were associated with previously reported showers from the IAU catalogue while 34 showers are new and not listed in the catalogue. Our searching method combined with our large data sample provides unprecedented accuracy in measuring meteor shower activity and description of shower characteristics in the Southern Hemisphere. Using simple modeling and clustering methods we also propose potential parent bodies for the newly discovered showers.

Meteor showers↗

Using Cloud-Based Storage Technologies for Earth Science Data

Cloud based infrastructure may offer several key benefits of scalability, built in redundancy and reduced total cost of ownership as compared with a traditional data center approach. However, most of the tools and software systems developed for NASA data repositories were not developed with a cloud based infrastructure in mind and do not fully take advantage of commonly available cloud-based technologies. Object storage services are provided through all the leading public (Amazon Web Service, Microsoft Azure, Google Cloud, etc.) and private (Open Stack) clouds, and may provide a more cost-effective means of storing large data collections online. We describe a system that utilizes object storage rather than traditional file system based storage to vend earth science data. The system described is not only cost effective, but shows superior performance for running many different analytics tasks in the cloud. To enable compatibility with existing tools and applications, we outline client libraries that are API compatible with existing libraries for HDF5 and NetCDF4. Performance of the system is demonstrated using clouds services running on Amazon Web Services.

Data↗

Online Visualization and Value Added Services of MERRA-2 Data at GES DISC

NASA climate reanalysis datasets from MERRA-2, distributed at the Goddard Earth Sciences Data and Information Services Center (GES DISC), have been used in broad research areas, such as climate variations, extreme weather, agriculture, renewable energy, and air quality, etc. The datasets contain numerous variables for atmosphere, land, and ocean, grouped into 95 products. The total archived volume is approximately 337 TB ( approximately 562K files) at the end of October 2017. Due to the large number of products and files, and large data volumes, it may be a challenge for a user to find and download the data of interest. The support team at GES DISC, working closely with the MERRA-2 science team, has created and is continuing to work on value added data services to best meet the needs of a broad user community. This presentation, using aerosol over Asia Monsoon as an example, provides an overview of the MERRA-2 data services at GES DISC, including: How to find the data? How many data access methods are provided? What are the best data access methods for me? How do download the subsetted (parameter, spatial, temporal) data and save in preferred spatial resolution and data format? How to visualize and explore the data online? In addition, we introduce a future online analytic tool designed for supporting application research, focusing on long-term hourly time-series data access and analysis.

Shen, Suhung↗

Data Mining and Analysis

The Data Mining project seeks to bring the capability of data visualization to NASA anomaly and problem reporting systems for the purpose of improving data trending, evaluations, and analyses. Currently NASA systems are tailored to meet the specific needs of its organizations. This tailoring has led to a variety of nomenclatures and levels of annotation for procedures, parts, and anomalies making difficult the realization of the common causes for anomalies. Making significant observations and realizing the connection between these causes without a common way to view large data sets is difficult to impossible. In the first phase of the Data Mining project a portal was created to present a common visualization of normalized sensitive data to customers with the appropriate security access. The tool of the visualization itself was also developed and fine-tuned. In the second phase of the project we took on the difficult task of searching and analyzing the target data set for common causes between anomalies. In the final part of the second phase we have learned more about how much of the analysis work will be the job of the Data Mining team, how to perform that work, and how that work may be used by different customers in different ways. In this paper I detail how our perspective has changed after gaining more insight into how the customers wish to interact with the output and how that has changed the product.

iss↗

High-latitude ion convection in the nighttime F region

A large data base of Atmosphere Explorer C measurements of the bulk ion velocity vector in the high-latitude F region has been examined. The concept of shear and rotational flow reversals is expanded upon to determine the extent to which the boundary between antisunward and sunward convection (i.e., a polar cap boundary) is an electrostatic equipotential. A most important factor in characterizing the nature of the large-scale geometrical configuration of the nighttime F region convection is the location and extent of quasi-equipotential regions of the convection reversal boundary.

Heelis, R. A.↗

Hierarchical and Parallelizable Direct Volume Rendering for Irregular and Multiple Grids

A general volume rendering technique is described that efficiently produces images of excellent quality from data defined over irregular grids having a wide variety of formats. Rendering is done in software, eliminating the need for special graphics hardware, as well as any artifacts associated with graphics hardware. Images of volumes with about one million cells can be produced in one to several minutes on a workstation with a 150 MHz processor. A significant advantage of this method for applications such as computational fluid dynamics is that it can process multiple intersecting grids. Such grids present problems for most current volume rendering techniques. Also, the wide range of cell sizes (by a factor of 10,000 or more), which is typical of such applications, does not present difficulties, as it does for many techniques. A spatial hierarchical organization makes it possible to access data from a restricted region efficiently. The tree has greater depth in regions of greater detail, determined by the number of cells in the region. It also makes it possible to render useful 'preview' images very quickly (about one second for one-million-cell grids) by displaying each region associated with a tree node as one cell. Previews show enough detail to navigate effectively in very large data sets. The algorithmic techniques include use of a kappa-d tree, with prefix-order partitioning of triangles, to reduce the number of primitives that must be processed for one rendering, coarse-grain parallelism for a shared-memory MIMD architecture, a new perspective transformation that achieves greater numerical accuracy, and a scanline algorithm with depth sorting and a new clipping technique.

Wilhelms, Jane↗

Lost in space: Onboard star identification using CCD star tracker data without an a priori attitude

There are many algorithms in use today which determine spacecraft attitude by identifying stars in the field of view of a star tracker. Some methods, which date from the early 1960's, compare the angular separation between observed stars with a small catalog. In the last 10 years, several methods have been developed which speed up the process and reduce the amount of memory needed, a key element to onboard attitude determination. However, each of these methods require some a priori knowledge of the spacecraft attitude. Although the Sun and magnetic field generally provide the necessary coarse attitude information, there are occasions when a spacecraft could get lost when it is not prudent to wait for sunlight. Also, the possibility of efficient attitude determination using only the highly accurate CCD star tracker could lead to fully autonomous spacecraft attitude determination. The need for redundant coarse sensors could thus be eliminated at substantial cost reduction. Some groups have extended their algorithms to implement a computation intense full sky scan. Some require large data bases. Both storage and speed are concerns for autonomous onboard systems. Neural network technology is even being explored by some as a possible solution, but because of the limited number of patterns that can be stored and large overhead, nothing concrete has resulted from these efforts. This paper presents an algorithm which, by descretizing the sky and filtering by visual magnitude of the brightness observed star, speeds up the lost in space star identification process while reducing the amount of necessary onboard computer storage compared to existing techniques.

Ketchum, Eleanor A.↗

Multi-reference evaluation of uncertainty in earth orientation parameter measurements

Uncertainties in polar motion and length-of-day measurements are evaluated empirically using several data series from the space-geodetic techniques of the global positioning system (GPS), satellite laser ranging (SLR), and very long baseline interferometry (VLBI) during 1997-2002. In the evaluation procedure employed here, known as the three-corner hat (TCH) technique, the signal common to each series is eliminated by forming pair-wise differences between the series, thus requiring no assumed values for the 'truth' signal. From the variances of the differenced series, the uncertainty of each series can be recovered when reasonable assumptions are made about the correlations between the series. In order to form the pair-wise differences, the series data must be given at the same epoch. All measurement data sets studied here were sampled at noon (UTC); except for the VLBI series, whose data are interpolated to noon and whose UT1 values are also numerically differentiated to obtain LOD. The numerical error introduced to the VLBI values by the interpolation and differentiation is shown to be comparable in magnitude to the values determined by the TCH method for the uncertainties of the VLBI series. The TCH estimates for the VLBI series are corrupted by such numerical errors mostly as a result of the relatively large data intervals. Of the remaining data sets studied here, it is found that the IGS Final combined series has the smallest polar motion and length-of-day uncertainties.

Combination↗

Characterizing Space Environments with Long-Term Space Plasma Archive Resources

A significant scientific benefit of establishing and maintaining long-term space plasma data archives is the ready access the archives afford to resources required for characterizing spacecraft design environments. Space systems must be capable of operating in the mean environments driven by climatology as well as the extremes that occur during individual space weather events. Long- term time series are necessary to obtain quantitative information on environment variability and extremes that characterize the mean and worst case environments that may be encountered during a mission. In addition, analysis of large data sets are important to scientific studies of flux limiting processes that provide a basis for establishing upper limits to environment specifications used in radiation or charging analyses. We present applications using data from existing archives and highlight their contributions to space environment models developed at Marshall Space Flight Center including the Chandra Radiation Model, ionospheric plasma variability models, and plasma models of the L2 space environment.

Minow, Joseph I.↗

The Ejectable Data Recorder: A Lean, Risk-Informed Approach for Hardware Development

NASA is developing the Orion spacecraft to transport crew from the Earth to the Moon as part of the Artemis series of missions. To provide a crew escape capability from pre-launch through ascent, the Orion vehicle is equipped with a Launch Abort System (LAS), built by Lockheed Martin, which pulls the capsule away from the launch vehicle in the event of an abort scenario. The Ascent Abort 2 (AA-2) test flight occurred on July 2, 2019,and tested a production version of the LAS to ensure that it can operate as intended, and to collect a large data set from hundreds of sensors on the vehicle to support Orion flight certification. In the original AA-2 architecture, a single-string set of communications antennas on the LAS would downlink all of the in-flight test data to ground stations. However, that communications architecture was predicted to have data dropouts during abort and jettison of the LAS, and would not support data transmission at all after LAS jettison. As a result, a comprehensive trade study was completed, yielding the addition of antennas on the crew module (CM), a buffer/rebroadcast capability for key portions of the flight, and an ejectable data recorder (EDR) subsystem. This EDR subsystem would serve as a backup to the radio frequency (RF) communications system, and would be non-flight critical, providing a unique capability that enabled management to take a different approach with the hardware and software development. The Crew Module and Separation Ring were developed as “Class 1”Flight Hardware, albeit with some tailoring approaches to enable efficiencies. The Class 1 designation requires full rigor for flight hardware and software, documenting everything that happens to a piece of hardware from procurement through disposal, requiring a full spectrum of acceptance tests, and the highest rigor of quality assurance processes. At the other end of the spectrum, Class 3hardware is controlled, but not intended for flight, and leaves the level of rigor up to the project manager. This classification is often used for research and development projects. Similarly,Class-1E has been recently defined at NASA for ISS payloads and technology development projects that are not flight critical and do not need the full rigor of Class 1 to be successful. The EDR subsystem was challenged at commencement to adopt a skunkworks and agile-like approach to hardware development, allowing for a different risk posture than the rest of the AA-2 hardware. After initially pursuing Class 1 processes, the EDR subsystem design evolved to incorporating numerous commercial components, leading to re-designation as a Class-1E subsystem. The resulting EDR subsystem was fully successful in meeting all flight system requirements, and achieved 100% retrieval of flight test data. This paper will discuss the risk posture of the EDR subsystem and the subsequent tailoring that was enacted as part of its Class-1E status.

EDR↗

Automated ISS Flight Utilities

During my internship at NASA Johnson Space Center, I worked in the Space Radiation Analysis Group (SRAG), where I was tasked with a number of projects focused on the automation of tasks and activities related to the operation of the International Space Station (ISS). As I worked on a number of projects, I have written short sections below to give a description for each, followed by more general remarks on the internship experience. My first project is titled "General Exposure Representation EVADOSE", also known as "GEnEVADOSE". This project involved the design and development of a C++/ ROOT framework focused on radiation exposure for extravehicular activity (EVA) planning for the ISS. The utility helps mission managers plan EVAs by displaying information on the cumulative radiation doses that crew will receive during an EVA as a function of the egress time and duration of the activity. SRAG uses a utility called EVADOSE, employing a model of the space radiation environment in low Earth orbit to predict these doses, as while outside the ISS the astronauts will have less shielding from charged particles such as electrons and protons. However, EVADOSE output is cumbersome to work with, and prior to GEnEVADOSE, querying data and producing graphs of ISS trajectories and cumulative doses versus egress time required manual work in Microsoft Excel. GEnEVADOSE automates all this work, reading in EVADOSE output file(s) along with a plaintext file input by the user providing input parameters. GEnEVADOSE will output a text file containing all the necessary dosimetry for each proposed EVA egress time, for each specified EVADOSE file. It also plots cumulative dose versus egress time and the ISS trajectory, and displays all of this information in an auto-generated presentation made in LaTeX. New features have also been added, such as best-case scenarios (egress times corresponding to the least dose), interpolated curves for trajectories, and the ability to query any time in the EVADES output. As mentioned above, GEnEVADOSE makes extensive use of ROOT version 6, the data analysis framework developed at the European Organization for Nuclear Research (CERN), and the code is written to the C++11 standard (as are the other projects). My second project is the Automated Mission Reference Exposure Utility (AMREU).Unlike GEnEVADOSE, AMREU is a combination of three frameworks written in both Python and C++, also making use of ROOT (and PyROOT). Run as a combination of daily and weekly cron jobs, these macros query the SRAG database system to determine the active ISS missions, and query minute-by-minute radiation dose information from ISS-TEPC (Tissue Equivalent Proportional Counter), one of the radiation detectors onboard the ISS. Using this information, AMREU creates a corrected data set of daily radiation doses, addressing situations where TEPC may be offline or locked up by correcting doses for days with less than 95% live time (the total amount time the instrument acquires data) by averaging the past 7 days. As not all errors may be automatically detectable, AMREU also allows for manual corrections, checking an updated plaintext file each time it runs. With the corrected data, AMREU generates cumulative dose plots for each mission, and uses a Python script to generate a flight note file (.docx format) containing these plots, as well as information sections to be filled in and modified by the space weather environment officers with information specific to the week. AMREU is set up to run without requiring any user input, and it automatically archives old flight notes and information files for missions that are no longer active. My other projects involve cleaning up a large data set from the Charged Particle Directional Spectrometer (CPDS), joining together many different data sets in order to clean up information in SRAG SQL databases, and developing other automated utilities for displaying information on active solar regions, that may be used by the space weather environment officers to monitor solar activity. I consulted my mentor Dr. Ryan Rios and Dr. Kerry Lee for project requirements and added features, and ROOT developer Edmond Offermann for advice on using the ROOT library. I also received advice and feedback from Dr. Janet Barzilla of SRAG, who tested my code. Besides these inputs, I worked independently, writing all of the code by myself. The code for all these projects is documented throughout, and I have attempted to write it in a modular format. Assuming that ROOT is updated accordingly, these codes are also Y2038-compliant (and Y10K-compliant). This allows the code to be easily referenced, modified and possibly repurposed for non-ISS missions in the future, should the necessary inputs exist. These projects have taught me a lot about coding and software design - I have become a much more skilled C++ programmer and ROOT user, and I also learned to code in Python and PyROOT (and its advantages and disadvantages compared to C++/ ROOT). Furthermore, I have learned about space radiation and radiation modeling, topics that greatly interest me as I pursue a degree in physics. Working alongside experimental physicists like Dr. Rios, I have developed a greater understanding and appreciation for experimental science, something I have always leaned towards but to which I lacked significant exposure. My work in SRAG has also given me the invaluable opportunity to witness the work environment for physicists at NASA, and what a career in academia may look like at a government laboratory such as NASA Johnson Space Center. As I continue my studies and look forward to graduate school and a future career, this experience at NASA has given me a meaningful and enjoyable opportunity to put my skills to use and see what my future career path might hold.

Offermann, Jan Tuzlic↗

Estimation of comprehensive forest variable sets from multiparameter SAR data over a large area with diverse species

Polarimetric and multifrequency data from the NASA/JPL airborne synthetic aperture radar (AIRSAR) have been used in a multi-tier estimation algorithm to calculate a comprehensive set of forest canopy properties including branch layer moisture and thickness, trunk density, trunk water content and diameter, trunk height, and subcanapy soil moisture. The estimation algorithm takes advantage of species-specific allometric relations, and is applied to a 100Km x 100Km area in the Canadian boreal region containing many different vegetation species types. The results show very good agreement with ground measurements taken at several focused and auxiliary study sites. This paper expands on the results reported in [1] and applies the algorithm on the regional scale.

variable estimation forestry multiparameter SAR↗

The characterization of widespread fatigue damage in fuselage structure

The characteristics of widespread fatigue damage (WSFD) in fuselage riveted structure were established by detailed nondestructive and destructive examinations of fatigue damage contained in a full size fuselage test article. The objectives of this were to establish an experimental data base for validating emerging WSFD analytical prediction methodology and to identify first order effects that contribute to fatigue crack initiation and growth. Detailed examinations were performed on a test panel containing four bays of a riveted lap splice joint. The panel was removed from a full scale fuselage test article after receiving 60,000 full pressurization cycles. The results of in situ examinations document the progression of fuselage skin fatigue crack growth through crack linkup. Detailed tear down examinations and fractography of the lap splice joint region revealed fatigue crack initiation sites, crack morphology, and crack linkup geometry. From this large data base, distributions of crack size and locations are presented and discussions of operative damage mechanisms are offered.

Piascik, Robert S.↗

The characterization of widespread fatigue damage in fuselage structure

The characteristics of widespread fatigue damage (WSFD) in fuselage riveted structure were established by detailed nondestructive and destructive examinations of fatigue damage contained in a full size fuselage test article. The objectives of this work were to establish an experimental data base for validating emerging WSFD analytical prediction methodology and to identify first order effects that contribute to fatigue crack initiation and growth. Detailed examinations were performed on a test panel containing four bays of a riveted lap splice joint. The panel was removed from a full scale fuselage test article after receiving 60,000 full pressurization cycles. The results of in situ examinations document the progression of fuselage skin fatigue crack growth through crack linkup. Detailed tear down examinations and fractography of the lap splice joint region revealed fatigue crack initiation sites, crack morphology and crack linkup geometry. From this large data base, distributions of crack size and locations are presented and discussions of operative damage mechanisms are offered.

Piascik, Robert S.↗