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NASA NTRS1992

Deep near-infrared survey of the Southern Sky (DENIS)

DENIS (Deep Near-Infrared Survey of the Southern Sky) will be the first complete census of astronomical sources in the near-infrared spectral range. The challenges of this novel survey are both scientific and technical. Phenomena radiating in the near-infrared range from brown dwarfs to galaxies in the early stages of cosmological evolution, the scientific exploitation of data relevant over such a wide range requires pooling expertise from several of the leading European astronomical centers. The technical challenges of a project which will provide an order of magnitude more sources than given by the IRAS space mission, and which will involve advanced data-handling and image-processing techniques, likewise require pooling of hardware and software resources, as well as of human expertise. The DENIS project team is composed of some 40 scientists, computer specialists, and engineers located in 5 European Community countries (France, Germany, Italy, The Netherlands, and Spain), with important contributions from specialists in Australia, Brazil, Chile, and Hungary. DENIS will survey the entire southern sky in 3 colors, namely in the I band at a wavelength of 0.8 micron, in the 1.25 micron J band, and in the 2.15 micron K' band. The sensitivity limits will be 18th magnitude in the I band, 16th in the J band, and 14.5th in the K' band. The angular resolution achieved will be 1 arcsecond in the I band, and 3.0 arcseconds in the J and K' bands. The European Southern Observatory 1 m telescope on La Silla will be dedicated to survey use during operations expected to last four years, commencing in late 1993. DENIS aims to provide the astronomical community with complete digitized infrared images of the full southern sky and a catalogue of extracted objects, both of the best quality and in readily accessible form. This will be achieved through dedicated software packages and specialized catalogues, and with assistance from the Leiden and Paris Data Analysis Centers. The data will be mailed on DAT tapes from La Silla to the two Data Analysis Centers for further processing. Two centers are necessary because of the shear quantity of data and because of the complementary roles the Centers will develop, each exploiting its own particular expertise. The Leiden Data Analysis Center (LDAC) will extract objects, establish their parameters, and archive them into a source catalogue. The LDAC will collaborate with the Groningen Space Research group that has gained experience in infrared image handling from the IRAS satellite. The Paris Data Analysis Center (PDAC) will be responsible for archiving and preprocessing the raw data to provide a homogeneous set of data suitable for further reduction in both the Leiden and Paris data analysis streams. The PDAC will also extract and archive images for the sources flagged by the LDAC as extended, and create a catalogue of galaxies. In exploiting the DENIS data we foresee the collaboration with other data analysis centers, such as the Observatoire de Lyon where the relevant DENIS catalogue of galaxies can be incorporated into their extragalactic database. The Point Sources and the Small Extended Sources catalogues could be incorporated in the Late Type Star database at Montpellier, and in the SIMBAD database as CDS. At Groningen the IRAS Point Source catalogue and/or image data can be merged with the DENIS catalogues. At Meudon algorithms and software will be developed with main goal assessing the limits reachable for the homogeneity and intrinsic consistency between the ensemble of the images in the data base (flat-fielding, relative positioning of the fields, bootstrapped flux calibration) but also for the data analysis.

Deul, E.↗

NASA NTRS2006

Processing TES Level-1B Data

TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.

DeBaca, Richard C.↗

NASA NTRS1999

Wilberforce Power Technology in Education Program

The Wilberforce Power Technology in Education Program is a multipart program. Three key parts of this program will be described. They are: (1) WISE-The Wilberforce Summer Intensive Experience. This annual offering is an educational program which is designed to provide both background reinforcement and a focus on study skills to give the participants a boost in their academic performance throughout their academic careers. It is offered to entering Wilberforce students. Those students who take advantage of WISE learn to improve important skills which enable them to work at higher levels in mathematics, science and engineering courses throughout their college careers, but most notably in the first year of college study. (2) Apply technology to reaming. This is being done in several ways including creating an electronic chemistry text with hypertext links to a glossary to help the students deal with the large new vocabulary required to describe and understand chemistry. It is also being done by converting lecture materials for the Biochemistry class to PowerPoint format. Technology is also being applied to learning by exploring simulation software of scientific instrumentation. (3) Wilberforce participation in collaborative research with NASA's John H. Glenn Research Center at Lewis Field. This research has focused on two areas in the past year. The first of these is the deposition of solar cell materials. A second area involves the development of polymeric materials for incorporation into thin film batteries.

Gordon, Edward M.↗

NASA NTRS2015

Global Precipitation Measurement Mission Launch and Commissioning

During launch and early operation of the Global Precipitation Measurement (GPM) Mission, the Guidance, Navigation and Control (GNC) analysis team encountered four main on orbit anomalies. These include: (1) unexpected shock from Solar Array deployment, (2) momentum buildup from the Magnetic Torquer Bars (MTBs) phasing errors, (3) transition into Safehold due to albedo-induced Course Sun Sensor (CSS) anomaly, and (4) a flight software error that could cause a Safehold transition due to a Star Tracker occultation. This paper will discuss ways GNC engineers identified and tracked down the root causes. Flight data and GNC on board models will be shown to illustrate how each of these anomalies were investigated and mitigated before causing any harm to the spacecraft. On May 29, 2014, GPM was handed over to the Mission Flight Operations Team after a successful commissioning period. Currently, GPM is operating nominally on orbit, collecting meaningful scientific data that will significantly improve our understanding of the Earth's climate and water cycle.

Guidance Navigation and Control↗

NASA NTRS1987

The crustal dynamics intelligent user interface anthology

The National Space Science Data Center (NSSDC) has initiated an Intelligent Data Management (IDM) research effort which has, as one of its components, the development of an Intelligent User Interface (IUI). The intent of the IUI is to develop a friendly and intelligent user interface service based on expert systems and natural language processing technologies. The purpose of such a service is to support the large number of potential scientific and engineering users that have need of space and land-related research and technical data, but have little or no experience in query languages or understanding of the information content or architecture of the databases of interest. This document presents the design concepts, development approach and evaluation of the performance of a prototype IUI system for the Crustal Dynamics Project Database, which was developed using a microcomputer-based expert system tool (M. 1), the natural language query processor THEMIS, and the graphics software system GSS. The IUI design is based on a multiple view representation of a database from both the user and database perspective, with intelligent processes to translate between the views.

Short, Nicholas M., Jr.↗

NASA NTRS2022

Science Autonomy for Ocean Worlds Astrobiology: A Perspective

Astrobiology missions to ocean worlds in our solar system must overcome both scientific and technological challenges due to extreme temperature and radiation conditions, long communication times, and limited bandwidth. While such tools could not replace ground-based analysis by science and engineering teams, machine learning algorithms could enhance the science return of these missions through development of autonomous science capabilities. Examples of science autonomy include onboard data analysis and subsequent instrument optimization, data prioritization (for transmission), and real-time decision-making based on data analysis. Similar advances could be made to develop streamlined data processing software for rapid ground-based analyses. Here we discuss several ways machine learning and autonomy could be used for astrobiology missions, including landing site selection, prioritization and targeting of samples, classification of “features” (e.g., proposed biosignatures) and novelties (uncharacterized, “new” features, which may be of most interest to agnostic astrobiological investigations), and data transmission.

ocean worlds↗

NASA NTRS2015

Global Precipitation Measurement Mission Launch and Commissioning

During launch and early operation of the Global Precipitation Measurement (GPM) Mission, the Guidance, Navigation, and Control (GN&C) analysis team encountered four main on-orbit anomalies. These include: (1) unexpected shock from Solar Array deployment, (2) momentum buildup from the Magnetic Torquer Bars (MTBs) phasing errors, (3) transition into Safehold due to albedo induced Course Sun Sensor (CSS) anomaly, and (4) a flight software error that could cause a Safehold transition due to a Star Tracker occultation. This paper will discuss ways GN&C engineers identified the anomalies and tracked down the root causes. Flight data and GN&C on-board models will be shown to illustrate how each of these anomalies were investigated and mitigated before causing any harm to the spacecraft. On May 29, 2014, GPM was handed over to the Mission Flight Operations Team after a successful commissioning period. Currently, GPM is operating nominally on orbit, collecting meaningful scientific data that will significantly improve our understanding of the Earth's climate and water cycle.

Guidance Navigation and Control↗

NASA NTRS1994

PI in the sky: The astronaut science advisor on SLS-2

The Astronaut Science Advisor (ASA, also known as Principal-Investigator-in-a-Box) is an advanced engineering effort to apply expert systems technology to experiment monitoring and control. Its goal is to increase the scientific value of information returned from experiments on manned space missions. The first in-space test of the system will be in conjunction with Professor Larry Young's (MIT) vestibulo-ocular 'Rotating Dome' experiment on the Spacelab Life Sciences 2 mission (STS-58) in the Fall of 1993. In a cost-saving effort, off-the-shelf equipment was employed wherever possible. Several modifications were necessary in order to make the system flight-worthy. The software consists of three interlocking modules. A real-time data acquisition system digitizes and stores all experiment data and then characterizes the signals in symbolic form; a rule-based expert system uses the symbolic signal characteristics to make decisions concerning the experiment; and a highly graphic user interface requiring a minimum of user intervention presents information to the astronaut operator. Much has been learned about the design of software and user interfaces for interactive computing in space. In addition, we gained a great deal of knowledge about building relatively inexpensive hardware and software for use in space. New technologies are being assessed to make the system a much more powerful ally in future scientific research in space and on the ground.

Hazelton, Lyman R.↗

NASA NTRSDate not supplied

Scientific Content Curation in an Open Science Era

Today’s open science environment, in combination with the Big Data era, means more scientific data, software, tools, documentation, publications and other resources are available than ever. The promise of the open science era is that scientists will spend less time reinventing the wheel and more time doing actionable research. Yet navigating this vast and complex information landscape can feel overwhelming to scientists trying to get their bearings. In this presentation, we define and discuss the importance of scientific content curation for enhancing discovery and use of scientific data and information. We also share two examples of scientific content curation in action: the Catalog of Archived Suborbital Earth Science Investigations (CASEI) and the Science Discovery Engine (SDE).

Kaylin Bugbee↗

NASA NTRS2017

The Integrated Medical Model: Outcomes from Independent Review

In 2016, the Integrated Medical Model (IMM) v4.0 underwent an extensive external review in preparation for transition to an operational status. In order to insure impartiality of the review process, the Exploration Medical Capabilities Element of NASA's Human Research Program convened the review through the Systems Review Office at NASA Goddard Space Flight Center (GSFC). The review board convened by GSFC consisted of persons from both NASA and academia with expertise in the fields of statistics, epidemiology, modeling, software development, aerospace medicine, and project management (see Figure 1). The board reviewed software and code standards, as well as evidence pedigree associated with both the input and outcomes information. The board also assesses the models verification, validation, sensitivity to parameters and ability to answer operational questions. This talk will discuss the processes for designing the review, how the review progressed and the findings from the board, as well as summarize the IMM project responses to those findings. Overall, the board found that the IMM is scientifically sound, represents a necessary, comprehensive approach to identifying medical and environmental risks facing astronauts in long duration missions and is an excellent tool for communication between engineers and physicians. The board also found IMM and its customer(s) should convene an additional review of the IMM data sources and to develop a sustainable approach to augment, peer review, and maintain the information utilized in the IMM. The board found this is critically important because medical knowledge continues to evolve. Delivery of IMM v4.0 to the Crew Health and Safety (CHS) Program will occur in the 2017. Once delivered for operational decision support, IMM v4.0 will provide CHS with additional quantitative capability in to assess astronaut medical risks and required medical capabilities to help drive down overall mission risks.

medical equipment↗

NASA NTRS1994

The validation by measurement theory of proposed object-oriented software metrics

Moving software development into the engineering arena requires controllability, and to control a process, it must be measurable. Measuring the process does no good if the product is not also measured, i.e., being the best at producing an inferior product does not define a quality process. Also, not every number extracted from software development is a valid measurement. A valid measurement only results when we are able to verify that the number is representative of the attribute that we wish to measure. Many proposed software metrics are used by practitioners without these metrics ever having been validated, leading to costly but often useless calculations. Several researchers have bemoaned the lack of scientific precision in much of the published software measurement work and have called for validation of software metrics by measurement theory. This dissertation applies measurement theory to validate fifty proposed object-oriented software metrics (Li and Henry, 1993; Chidamber and Kemerrer, 1994; Lorenz and Kidd, 1994).

Neal, Ralph D.↗

NASA NTRS1995

The Validation by Measurement Theory of Proposed Object-Oriented Software Metrics

Neal, Ralph D.↗

NASA NTRS1996

The Validation by Measurement Theory of Proposed Object-Oriented Software Metrics

Neal, Ralph D.↗

NASA NTRS2023

Trades, Architecture, and Design of the Joint Augmented Reality Visual Informatics (Joint AR) Product

Future expeditions will enable exploration and study of the planetary surfaces of the Moon and Mars by performing extravehicular activity (EVA) operations. Present-day International Space Station (ISS) EVA operations require an intricate and tight choreography of crew, space suits, tools, systems, and flight teams to plan, train, and execute with limited advanced informatics. Additionally, EVA operations, aside from the Apollo Lunar surface missions, have predominately focused on maintenance and construction tasks where success criteria are clearly measurable. However, future exploration missions expect to enable crew to carry out scientific objectives in increasingly Earth-independent ways. In this paper, the Joint Augmented Reality Visual Informatics System (Joint AR) characterizes the design space for developing a modular augmented reality (AR) device for a spacesuit form factor that can support crew decision-making for EVA. This paper highlights the project’s experience with a product-focused management style and use-case centered systems engineering approach to iteratively design, build, and test. The Joint AR product features were defined via trade studies and market analysis of previous EVA display efforts, various AR components such as optics, commercial AR systems, light engines, data interfaces, graphics engine software and analog test beds. We outline the defining architectural design decisions, including safety criticality considerations, suit mounting interfaces, computer architectures, and partnership contracting mechanisms. The outcomes of these studies, architecture decisions, and management requirements result in a recommended design which is the Joint AR product. We discuss the evolution, development of these system components, and what work remains. We hope to share a unified understanding of various design decisions and how they impact the future of crew members’ access to data during Lunar and Martian EVAs. This ongoing effort can enable a community-wide discovery process toward realizing necessary AR features and capabilities for future missions.

Augmented Reality↗

NASA NTRS1993

A compilation of technology spinoffs from the US Space Shuttle Program

As the successful transfer of NASA-developed technology is a stated mission of NASA, the documentation of such transfer is vital in support of the program. The purpose of this report is to document technology transfer, i.e. 'spinoffs', from the U.S. Space Shuttle Program to the commercial sector. These spinoffs have their origin in the many scientific and engineering fields associated with the shuttle program and, as such, span many diverse commercial applications. These applications include, but are not limited to, consumer products, medicine, industrial productivity, manufacturing technology, public safety, resources management, materials processing, transportation, energy, computer technology, construction, and environmental applications. To aide to the generation of this technology spinoff list, significant effort was made to establish numerous and complementary sources of information. The primary sources of information used in compiling this list include: the NASA 'Spinoff' publication, NASA Tech Briefs, the Marshall Space Flight Center (MSFC) Technology Utilization (TU) Office, the NASA Center for Aerospace Information (CASI), the NASA COSMIC Software Center, and MSFC laboratory and contractor personnel. A complete listing of resources may be found in the bibliography of this report. Additionally, effort was made to insure that the obtained information was placed in electronic database form to insure that the subsequent updating would be feasible with minimal effort.

Jackson, David Jeff↗

NASA NTRS1995

Scientific Visualization and Computational Science: Natural Partners

Scientific visualization is developing rapidly, stimulated by computational science, which is gaining acceptance as a third alternative to theory and experiment. Computational science is based on numerical simulations of mathematical models derived from theory. But each individual simulation is like a hypothetical experiment; initial conditions are specified, and the result is a record of the observed conditions. Experiments can be simulated for situations that can not really be created or controlled. Results impossible to measure can be computed.. Even for observable values, computed samples are typically much denser. Numerical simulations also extend scientific exploration where the mathematics is analytically intractable. Numerical simulations are used to study phenomena from subatomic to intergalactic scales and from abstract mathematical structures to pragmatic engineering of everyday objects. But computational science methods would be almost useless without visualization. The obvious reason is that the huge amounts of data produced require the high bandwidth of the human visual system, and interactivity adds to the power. Visualization systems also provide a single context for all the activities involved from debugging the simulations, to exploring the data, to communicating the results. Most of the presentations today have their roots in image processing, where the fundamental task is: Given an image, extract information about the scene. Visualization has developed from computer graphics, and the inverse task: Given a scene description, make an image. Visualization extends the graphics paradigm by expanding the possible input. The goal is still to produce images; the difficulty is that the input is not a scene description displayable by standard graphics methods. Visualization techniques must either transform the data into a scene description or extend graphics techniques to display this odd input. Computational science is a fertile field for visualization research because the results vary so widely and include things that have no known appearance. The amount of data creates additional challenges for both hardware and software systems. Evaluations of visualization should ultimately reflect the insight gained into the scientific phenomena. So making good visualizations requires consideration of characteristics of the user and the purpose of the visualization. Knowledge about human perception and graphic design is also relevant. It is this breadth of knowledge that stimulates proposals for multidisciplinary visualization teams and intelligent visualization assistant software. Visualization is an immature field, but computational science is stimulating research on a broad front.

Uselton, Samuel P.↗

NASA NTRS2016

Finding Stuff Underwater: Open-Source Tools for Underwater Field Science

Since 2009, we have been developing and testing Exploration Ground Data Systems (xGDS). xGDS is a software suite, built on open-source web technologies, for supporting NASA terrestrial field science analog missions. We will describe our recent work supporting underwater mapping and dive operations at the Pavilion Lake Research Project (PLRP - www.pavilionlake.com). At PLRP we used open-source mapping technologies to meet an operational need to quickly guide divers and underwater vehicles to locations of interest, and the scientific goal of building a map showing the locations and characteristics of the microbialites at the bottom of the lake. We will discuss some of the benefits and lessons-learned from our recent transition from Google Earth to OpenLayers as the primary mapping engine to support our work. Well also explain the challenges we faced and solutions weve developed to support mapping and data collection in an underwater environment.Beyond their immediate value for advancing scientific research on Earth, NASA analogs explore new ideas for supporting scientists working in extreme environments (e.g. underwater) to develop best practices for future human missions to the Moon or Mars. Science at PLRP involved imaging, sampling and characterizing microbialites growing beneath the surface of an alpine lake in British Columbia. To support PLRP operations and science, xGDS helped plan data collection tasks and provided accurate tracking and mapping of the locations of the underwater assets (human-piloted submersibles, remotely operated vehicles (ROVs) and human divers) collecting imagery and samples from the lake. The data collected during our field work was registered with precursor bathymetry data collected by an autonomous underwater vehicle (AUV) and was globally located on a satellite base layer map of the area surrounding the lake.

Earth analogs↗

NASA NTRS2022

On-Orbit Performance of the Spitzer Space Telescope: Science Meets Engineering

The Spitzer Space Telescope operated for over 16 years in an Earth-trailing solar orbit, returning not only a wealth of scientific data but also, as a by-product, spacecraft and instrument engineering data that will be of interest to future mission planners. These data will be particularly useful because Spitzer operated in an environment essentially identical to that at the L2 LaGrange point, where many future astrophysics missions will operate. In particular, the radiative cooling demonstrated by Spitzer has been adopted by other infrared space missions, from JWST to SPHEREx. We aim to facilitate the utility of the Spitzer engineering data by collecting the more unique and potentially useful portions into a single, readily accessible publication. We avoid discussion of less unique systems, such as the telecom, flight software, and electronics systems, and do not address the innovations in mission and science operations that the Spitzer team initiated. These and other items of potential interest are addressed in references supplied in an appendix to this paper.

Spitzer↗