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At least 1,117 records · Page 62

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NASA NTRS2010

NASA Tech Briefs, March 2010

Topics covered include: Software Tool Integrating Data Flow Diagrams and Petri Nets; Adaptive Nulling for Interferometric Detection of Planets; Reducing the Volume of NASA Earth-Science Data; Reception of Multiple Telemetry Signals via One Dish Antenna; Space-Qualified Traveling-Wave Tube; Smart Power Supply for Battery-Powered Systems; Parallel Processing of Broad-Band PPM Signals; Inexpensive Implementation of Many Strain Gauges; Constant-Differential-Pressure Two-Fluid Accumulator; Inflatable Tubular Structures Rigidized with Foams; Power Generator with Thermo-Differential Modules; Mechanical Extraction of Power From Ocean Currents and Tides; Nitrous Oxide/Paraffin Hybrid Rocket Engines; Optimized Li-Ion Electrolytes Containing Fluorinated Ester Co-Solvents; Probabilistic Multi-Factor Interaction Model for Complex Material Behavior; Foldable Instrumented Bits for Ultrasonic/Sonic Penetrators; Compact Rare Earth Emitter Hollow Cathode; High-Precision Shape Control of In-Space Deployable Large Membrane/Thin-Shell Reflectors; Rapid Active Sampling Package; Miniature Lightweight Ion Pump; Cryogenic Transport of High-Pressure-System Recharge Gas; Water-Vapor Raman Lidar System Reaches Higher Altitude; Compact Ku-Band T/R Module for High-Resolution Radar Imaging of Cold Land Processes; Wide-Field-of-View, High-Resolution, Stereoscopic Imager; Electrical Capacitance Volume Tomography with High-Contrast Dielectrics; Wavefront Control and Image Restoration with Less Computing; Polarization Imaging Apparatus; Stereoscopic Machine-Vision System Using Projected Circles; Metal Vapor Arcing Risk Assessment Tool; Performance Bounds on Two Concatenated, Interleaved Codes; Parameterizing Coefficients of a POD-Based Dynamical System; Confidence-Based Feature Acquisition; Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery; Universal Decoder for PPM of any Order; Algorithm for Stabilizing a POD-Based Dynamical System; Mission Reliability Estimation for Repairable Robot Teams; Processing AIRS Scientific Data Through Level 3; Web-Based Requesting and Scheduling Use of Facilities; AutoGen Version 5.0; Time-Tag Generation Script; PPM Receiver Implemented in Software; Tropospheric Emission Spectrometer Product File Readers; Reporting Differences Between Spacecraft Sequence Files; Coordinating "Execute" Data for ISS and Space Shuttle; Database for Safety-Oriented Tracking of Chemicals; Apparatus for Cold, Pressurized Biogeochemical Experiments; Growing B Lymphocytes in a Three-Dimensional Culture System; Tissue-like 3D Assemblies of Human Broncho-Epithelial Cells; Isolation of Resistance-Bearing Microorganisms; Oscillating Cell Culture Bioreactor; and Liquid Cooling/Warming Garment.

Source record↗

NASA NTRS2019

HelioSwarm: Swarm Mission Design in High Altitude Orbit for Heliophysics

Resolving the complex three-dimensional turbulent structures that characterize the solar wind requires contemporaneous spatially and temporally distributed measurements. HelioSwarm is a mission concept that will deploy multiple, co-orbiting satellites to use the solar wind as a natural laboratory for understanding the fundamental, universal process of plasma turbulence. The HelioSwarm transfer trajectory and science orbit use a lunar gravity assist to deliver the ESPA-class nodes attached to a large data transfer hub to a P/2 lunar resonant orbit. Once deployed in the science orbit, the free-flying, propulsive nodes use simple Cartesian relative motion patterns to establish baseline separations both along and across the solar wind flow direction.

lunar resonant orbit↗

NASA NTRS2019

HelioSwarm: Swarm Mission Design in High Altitude Orbit for Heliophysics

lunar resonant orbit↗

NASA NTRS2021

Campaign: Telemetry-based Biology for the Artemis Era and Beyond

We call for a major dedicated campaign to develop and fly autonomous biological payloads in lunar orbit and on the lunar surface during the next decade, followed by subsequent expansion to Martian orbit. This ambitious goal will require dedicated effort to develop hardware, biological models and data acquisition and processing techniques. We believe that it would be best achieved as a single comprehensive, NASA-led and funded mission project, analogous to planetary science missions. Furthermore, technological developments should be accompanied by collaborations within and between agencies and a robust program for acquisition and retention of talented scientists and engineers.

Egle Cekanaviciute↗

NASA NTRS2022

Mitigation Strategies for the Impact of Low Energy Laser Pulses in CALIOP Calibration and Level 2 Retrievals

Since mid-2016, the frequency of low energy laser pulses emitted by the CALIPSO lidar has been slowly increasing due to pressure losses in the canister housing the laser. While originally confined primarily to the South Atlantic Anomaly (SAA) region, these low energy pulses now occur intermittently around the globe. Low energy pulses can cause calibration biases and degrade the science quality of level 2 retrievals. We describe a new low energy mitigation (LEM) algorithm that will be implemented incrementally in future versions of the CALIOP data processing to identify and reject affected profiles during calibration and feature detection. The LEM algorithm effectively eliminates low energy calibration biases, improves level 2 retrievals, and minimizes level 2 data loss.

Jason Tackett↗

NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗

NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

Arlindo da SIlva↗

NASA NTRS2000

The University of Nebraska at Omaha Center for Space Data Use in Teaching and Learning

Within the context of innovative coursework and other educational activities, we are proposing the establishment of a University of Nebraska at Omaha (UNO) Center for the Use of Space Data in Teaching and Learning. This Center will provide an exciting and motivating process for educators at all levels to become involved in professional development and training which engages real life applications of mathematics, science, and technology. The Center will facilitate innovative courses (including online and distance education formats), systematic degree programs, classroom research initiatives, new instructional methods and tools, engaging curriculum materials, and various symposiums. It will involve the active participation of several Departments and Colleges on the UNO campus and be well integrated into the campus environment. It will have a direct impact on pre-service and in-service educators, the K12 (kindergarten through 12th grade) students that they teach, and other college students of various science, mathematics, and technology related disciplines, in which they share coursework. It is our belief that there are many exciting opportunities represented by space data and imagery, as a context for engaging mathematics, science, and technology education. The UNO Center for Space Data Use in Teaching and Learning being proposed in this document will encompass a comprehensive training and dissemination strategy that targets the improvement of K-12 education, through changes in the undergraduate and graduate preparation of teachers in science, mathematics and technology education.

Grandgenett, Neal↗

NASA NTRSDate not supplied

Primary Mission Threshold Crossing Events in the TESS SPOC Transit Search

We present an overview of the single- and multiple-sector results of the Science Processing Operations Center (SPOC) transit search in the primary Transiting Exoplanet Survey Satellite (TESS) mission. TESS was designed to survey bright stars in the greater Solar neighborhood in search of transiting exoplanets. Data were acquired at a 2-minute cadence for 16,000-20,000 pre-selected target stars in each 28-day observation sector and processed in the SPOC pipeline at NASA Ames Research Center. The photometry pipeline produced a systematic error corrected light curve for each target star. Light curves were searched for transiting planet signatures by sector for all target stars, and separately for target stars observed in multiple sectors. Potential transit signals for which the transiting planet detection threshold was exceeded and a series of transit consistency tests were passed are referred to as Threshold Crossing Events (TCEs). We highlight the full TCE population and the population of SPOC TCEs that were later identified as TESS Objects of Interest (TOIs). Characteristics of the TCE populations implied by limb-darkened transiting planet model fits are also presented. SPOC pipeline data products are delivered to the Mikulski Archive for Space Telescopes (MAST)(http://archive.stsci.edu/missions-and-data/tess) for access by the community. Funding for the TESS Mission has been provided by the NASA Science Mission Directorate.

TESS↗

NASA NTRS2012

Image Processing on the Cloud

No abstract available

Cloud Implementation↗

NASA NTRSDate not supplied

ICARTT File Format Enhancements: Supporting FAIRness and Data Discovery of Suborbital Campaign Data

Suborbital campaigns aim to accomplish a wide variety of goals and can include a variety of platforms, instruments, and parameters measured. In 2004, the ICARTT (International Consortium for Atmospheric Research on Transport and Transformation) standards were developed to fulfill data management needs for the ICARTT campaign. The ICARTT file format is text-based and composed of a header with important data description information and the data section. Built on the NASA Ames and GTE data formats, the ICARTT format was created to facilitate data exchange and promote collaborations among the science teams for achieving the ICARTT campaign goals. Due to its success and adaptation for use in many other field campaigns, the ICARTT file format became a NASA standard in 2010 and was amended in January 2017. These changes provided many enhancements, including the requirement for variable standard names. Primarily designed for airborne field studies, ICARTT has been further utilized for ground-based studies. NASA has made a commitment to build an inclusive open science community over the next decade. Open-source science strives to make publicly funded scientific research transparent, inclusive, accessible, and reproducible. The ICARTT format can host metadata that is critical for proper use of the data, particularly for in-situ measurements, and can enhance data discovery and accessibility. However, the required fields are often free text, meaning that the information is human readable, but not machine interpretable. Furthermore, the amount and type of information provided can vary significantly between principal investigators and campaigns. To support FAIR principles and interoperability, enhancements to the ICARTT standards are recommended. Possible recommendations include potential use of controlled and consistent vocabulary for variable standard name and certain common metadata elements; standardizing timestamps for easier data comparisons and analysis; and providing guidance on variable measurement units and how they are reported. Enhancing ICARTT metadata can further streamline the process to make suborbital data more readily available to the data user and improve variable-level metadata. Providing more variable-level metadata can enhance data searching and discovery, supporting NASA’s Open-Source Science Initiative (OSSI).

Megan Buzanowicz↗

NASA NTRS2007

Mars-GRAM Applications for Mars Science Laboratory Mission Site Selection Processes

An overview is presented of the Mars-Global Reference Atmospheric Model (Mars-GRAM 2005) and its new features. One important new feature is the "auxiliary profile" option, whereby a simple input file is used to replace mean atmospheric values from Mars-GRAM's conventional (General Circulation Model) climatology. An auxiliary profile can be generated from any source of data or alternate model output. Results are presented using auxiliary profiles produced from mesoscale model output (Southwest Research Institute's Mars Regional Atmospheric Modeling System (MRAMS) model and Oregon State University's Mars mesoscale model (MMM5) model) for three candidate Mars Science Laboratory (MSL) landing sites (Terby Crater, Melas Chasma, and Gale Crater). A global Thermal Emission Spectrometer (TES) database has also been generated for purposes of making 'Mars-GRAM auxiliary profiles. This data base contains averages and standard deviations of temperature, density, and thermal wind components, averaged over 5-by-5 degree latitude bins and 15 degree L(sub S) bins, for each of three Mars years of TES nadir data. Comparisons show reasonably good consistency between Mars-GRAM with low dust optical depth and both TES observed and mesoscale model simulated density at the three study sites. Mean winds differ by a more significant degree. Comparisons of mesoscale and TES standard deviations' with conventional Mars-GRAM values, show that Mars-GRAM density perturbations are somewhat conservative (larger than observed variability), while mesoscale-modeled wind variations are larger than Mars-GRAM model estimates. Input parameters rpscale (for density perturbations) and rwscale (for wind perturbations) can be used to "recalibrate" Mars-GRAM perturbation magnitudes to better replicate observed or mesoscale model variability.

Justh, Hilary↗

NASA NTRS2017

SAEVe: A Long Duration Small Sat Class Venus Lander - Seismic and Atmospheric Exploration of Venus

NASA's science mission directorate has put increasing emphasis on innovative, smaller, and lower cost missions to achieve their science objectives. One example of this was the recent call by the Planetary Science Division for cube and small satellite concepts expected to cost $100M or less, not including launch and weighing less than 180kg. Over 100 proposals were submitted suggesting that indeed this is a size of mission worthy of being considered in future planning. Nineteen missions were selected for study, one being a long-lived Venus mission called SAEVe, for Seismic and Atmospheric Exploration of Venus. The science objectives and relevance of SAEVe include: Is Venus seismically active? What can we learn about its crust (thickness and composition) and its interior (lithosphere, mantle, and core)? What can be learned about its evolutionary history or about the planet / atmosphere interactions? SAEVe begins to address these science questions with simple, but capable, instrumented probes that can survive on the surface of Venus and take temporal measurements over months something never attempted before. The data returned will further our understanding of the solar system and Earth, and aid in meeting the NASA Science Plan goal to ascertain the content, origin, and evolution of the solar system and the chemical and physical processes in our solar system. SAEVe is delivered to Venus as a ride-along on another mission to Venus. Its two small probes are placed into the Venus atmosphere via a single Stardust-like entry capsule, are ejected at different times, free fall, and decelerate in the thickening atmosphere to touchdown under 8 m/s2 or less. The probes will begin taking measurements and transmitting important parameters at or near the surface and will focus on measurements like seismic activity, heat flux, wind speed and direction, basic chemical abundances, temperature, and pressure. At preset intervals, the probes acquire the science measurements and beam the data to the orbiting host spacecraft. SAEVe will serve as a highly capable precursor and pave the way for larger and more complex lander missions to explore Venus.

lander↗

NASA NTRS2013

Contemplating Synergistic Algorithms for the NASA ACE Mission

ACE is a proposed Tier 2 NASA Decadal Survey mission that will focus on clouds, aerosols, and precipitation as well as ocean ecosystems. The primary objective of the clouds component of this mission is to advance our ability to predict changes to the Earth's hydrological cycle and energy balance in response to climate forcings by generating observational constraints on future science questions, especially those associated with the effects of aerosol on clouds and precipitation. ACE will continue and extend the measurement heritage that began with the A-Train and that will continue through Earthcare. ACE planning efforts have identified several data streams that can contribute significantly to characterizing the properties of clouds and precipitation and the physical processes that force these properties. These include dual frequency Doppler radar, high spectral resolution lidar, polarimetric visible imagers, passive microwave and submillimeter wave radiometry. While all these data streams are technologically feasible, their total cost is substantial and likely prohibitive. It is, therefore, necessary to critically evaluate their contributions to the ACE science goals. We have begun developing algorithms to explore this trade space. Specifically, we will describe our early exploratory algorithms that take as input the set of potential ACE-like data streams and evaluate critically to what extent each data stream influences the error in a specific cloud quantity retrieval.

precipitation↗

NASA NTRSDate not supplied

Functionality of the Python Packages for the HERMES Mission

The Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) is a set of four instruments that will fly on the Lunar Gateway, an orbital outpost which will support Artemis lunar operations. HERMES will focus on understanding the causes of space-weather variability as driven by the Sun and modulated by the magnetosphere. In this talk, we will discuss the open source approach of the HERMES Science Operation Center (SOC) team being implemented in a number of Python packages which all work together. We will describe the core package which contains Python interfaces for the loading, calibrating, plotting, validating, and saving of measurement data through Common Data Format (CDF) files making use of pycdf provided by spacepy. Each instrument also has a Python package developed using a package template and will provide specific calibration and processing functionality to each instrument. The packages make extensive use of the scientific Python ecosystem and maintain compatibility with PyHC standards. The abstraction of intricate, high heritage data formats, such as CDF files, in Python enables easier analysis and opens doors for greater participation in heliophysics science.

hermes↗

NASA NTRS2007

Primary Objective Grating Astronomical Telescope

It has been 370 years since a seventeenth century French mathematician, Mersenne, presciently sketched out an astronomical telescope based on dual parabolic reflectors. Since that time the concept of the primary objective has been virtually unchanged. Now a new class of astronomical telescope with a primary objective grating (POG) has been studied as an alternative. The POG competes with mirrors, in part, because diffraction gratings provide the very chromatic dispersion that mirrors defeat. The resulting telescope deals effectively with long-standing restrictions on multiple object spectroscopy (MOS). Other potential benefits include unprecedented apertures and collection areas. The new design also favors space deployment as a gossamer membrane. The inventor, Tom Ditto, first discovered that higher-order diffraction images contain hidden depth cues, for which he was granted a seminal range finding patent in 1987. Subsequently, he invented and patented 3D localizers, profilometers and microscopes using POGs. The POG telescope was placed in the public domain to expedite research. The function of a telescopes primary objective is to collect flux and to deliver images. Both functions dictate that size matters, and bigger is better. For that reason, there has been a steady push over the past century to ramp up the size of the primary mirror. However, for every doubling of mirror diameter, the elapsed time between initial effort and first light has also doubled. Meanwhile, costs escalated beyond the mirror alone, because larger instruments required larger enclosures and better pointing mechanisms. One key catalog of observation, spectrographic data, is far more difficult to amass than two-dimensional imagery. While the number of observable objects has increased with mirror size, the capacity to take spectra has not increased proportionately. In the best of circumstances, spectrograms are available for one per cent of the all objects surveyed. Spectroscopy was a historical afterthought introduced in the nineteenth century shortly after the invention of the diffraction grating and over a century after Newtons 1670 telescope. Spectroscopy is generally accomplished using a diffraction grating as the disperser in the secondary. The light being delivered to the spectrograph is first captured by a primary mirror which provides no chromatic magnification by itself. Sizeable spectrographs could not be deployed while diffraction gratings were rare commodities scribed using mechanical ruling engines that produced one grating line at a time. Today diffraction gratings are commonplace. Their recent availability is a product of both the invention of holography and the mass replication of surface microstructures. Holography permits all lines in a grating to be made simultaneously in a single photographic exposure. Holograms can then be reproduced by embossing processes. The improvement in replication is analogous to how Gutenberg changed the availability of books. The masters may be expensive, but the copies are not. Computer science is another technology that emerged in the second half of the twentieth century without which our proposed spectrographic instrument could not function due to the complexity of image processing required in data reduction. The employment of very large diffraction gratings as primary objectives for astronomical telescopes requires a novel

spectroscopy↗

NASA NTRS1982

Laser processing

Progress in the Progress ceramic materials is reported. Experiments and models for sintering and microstructure evolution are described. Models and data for understanding the kinetics of grain boundary motion and of pore coarsening and new materials for fuel cells and batteries; are developed. New experimental techniques using lasers for forming fine, monosized powders and for forming stable and metastable structures from liquids, and solar materials research are also developed. Colloidal science and ceramics processing are explored; and research programs on the presintering science necessary for controlled green microstructures are outlined.

Source record↗

NASA NTRS2011

Visualizing Airborne and Satellite Imagery

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Bierwirth, Victoria A.↗