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NASA NTRS2009

Towards Designing an Integrated Architecture for NEO Characterization, Mitigation, Scientific Evaluation, and Resource Utilization

This poster reviews the planning and design for an integrated architecture for characterization, mitigation, scientific evaluation and resource utilization of near earth objects. This includes tracks to observe and characterize the nature of the threat posed by a NEO, and deflect if a significant threat is posed. The observation stack can also be used for a more complete scientific analysis of the NEO.

Adams, Robert B.↗

NASA NTRS2009

Ares V: New Opportunities for Scientific Payloads

What if scientists and payload planners had access to three to five times the volume and five to nine times the mass provided by today's launch vehicles? This simple question can lead to numerous exciting possibilities, all involving NASA's new Ares V cargo launch vehicle now on the drawing board. Multiple scientific fields and payload designers have that opportunity with the Ares V cargo launch vehicle, being developed at NASA as the heavy-lift component of the U.S. Space Exploration Policy. When the Ares V begins flying late next decade, its capabilities will significantly exceed the 1960s-era Saturn V or the current Space Shuttle, while it benefits from their engineering, manufacturing, and infrastructure heritage. It will send more crew and cargo to more places on the lunar surface than Apollo and provide ongoing support to a permanent lunar outpost. Moreover, it will restore a strategic heavy-lift U.S. asset, which can support human and robotic exploration and scientific ventures for decades to come. Assessment of astronomy payload requirements since Spring 2008 has indicated that Ares V has the potential to support a range of payloads and missions. Some of these missions were impossible in the absence of Ares V's capabilities. Collaborative design/architecture inputs, exchanges, and analyses have already begun between scientists and payload developers. A 2008 study by a National Research Council (NRC) panel, as well as analyses presented by astronomers and planetary scientists at two weekend conferences in 2008, support the position that Ares V has benefit to a broad range of planetary and astronomy missions. This early dialogue with Ares V engineers is permitting the greatest opportunity for payload/transportation/mission synergy and the least financial impact to Ares V development. In addition, independent analyses suggest that Ares V has the opportunity to enable more cost-effective mission design.

Creech, Steve↗

NASA NTRS2009

Circuits Enhance Scientific Instruments and Safety Devices

Since its founding in 1958, NASA has pioneered the use of different frequencies on the electromagnetic spectrum - including X-ray, microwave, and infrared wavelengths - to gather information about distant celestial bodies. During the 1962 Mariner 2 mission, NASA used microwave radiometers that operated in the range of 15-23 gigahertz (GHz) to assess the surface temperature of Venus and to determine the percentage of water vapor in its atmosphere. Today, there is another area on the spectrum proving uniquely useful to scientists: the terahertz (THz) range, spanning from about 100 GHz-10,000 GHz. (1 THz equals approximately 1,000 GHz.) Terahertz frequencies span the lesser-known gap on the electromagnetic spectrum between microwave radiation and infrared (and visible) light, falling within the spectral range where most simple molecules resonate. This molecular resonance makes terahertz particularly useful for chemical spectroscopy and the remote sensing of specific molecules. In the 1990s, NASA began using frequencies above 300 GHz (more than an order of magnitude higher than the instrumentation on Mariner 2) to perform spectral analysis of molecular clouds and planetary atmospheres. Instruments using these higher frequencies have included the Microwave Limb Sounder (MLS) on the Upper Atmosphere Research Satellite (UARS), deployed from 1991-2001, and the Microwave Instrument for the Rosetta Orbiter (MIRO), launched in 2004. With UARS-MLS, NASA used advanced terahertz receivers to measure the emission signatures from atmospheric molecules, providing researchers with valuable data about the changes in the Earth s protective ozone layer. MIRO, set to rendezvous with the comet 67P Churyumov-Gerasimenko in 2014, will use terahertz instrumentation to analyze the comet s dust and gases. Although NASA has been a driving force behind the development of terahertz technology, scientific equipment for terahertz research - including transmitters, receivers, and basic test and measurement equipment - is not widely available, making scientific experiments in this range between traditional electronics and quantum photonics more costly and greatly limiting commercial development in the field. Given NASA s interest in studying distant bodies in space as well as in improving life on Earth, the Agency has collaborated with private industry to develop terahertz technologies.

Source record↗

NASA NTRS2007

Automated Detection of Events of Scientific Interest

A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

James, Mark↗

NASA NTRS2010

A Scientific Revolution: The Hubble and James Webb Space Telescopes

Astronomy is going through a scientific revolution, responding to a flood of data from the Hubble Space Telescope, other space missions, and large telescopes on the ground. In this talk, I will discuss some of the important discoveries of the last decade, from dwarf planets in the outer Solar System to the mysterious dark energy that overcomes gravity to accelerate the expansion of the Universe. The next decade will be equally bright with the newly refurbished Hubble and the promise of its successor, the James Webb Space Telescope. An infrared-optimized 6.5m space telescope, Webb is designed to find the first galaxies that formed in the early universe and to peer into the dusty gas clouds where stars and planets are born. With MEMS technology, a deployed primary mirror and a tennis-court sized sunshield, the mission presents many technical challenges. I will describe Webb's scientific goals, its design and recent progress in constructing the observatory. Webb is scheduled for launch in 2014.

Gardner, Jonathan P.↗

NASA NTRS2010

Wings In Orbit: Scientific and Engineering Legacies of the Space Shuttle

This Space Shuttle book project reviews Wings In Orbit-scientific and engineering legacies of the Space Shuttle. The contents include: 1) Magnificent Flying Machine-A Cathedral to Technology; 2) The Historical Legacy; 3) The Shuttle and its Operations; 4) Engineering Innovations; 5) Major Scientific Discoveries; 6) Social, Cultural, and Educational Legacies; 7) Commercial Aerospace Industries and Spin-offs; and 8) The Shuttle continuum, Role of Human Spaceflight.

Hale, N. Wayne↗

NASA NTRS2011

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

MatLab(R) (MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many cou ntries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its re al strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbo x. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using s ymbolic operations. MatLab in its interpreter programming language fo rm (command interface) is similar with well known programming languag es such as C/C++, support data structures and cell arrays to define c lasses in object oriented programming. As such, MatLab is equipped with most ofthe essential constructs of a higher programming language. M atLab is packaged with an editor and debugging functionality useful t o perform analysis of large MatLab programs and find errors. We belie ve there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and ana lysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applicati ons. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientifi c problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabu lar format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed. The presentation will emphasize creating practIcal scripts (pro grams) that extend the basic features of MatLab TOPICS mclude (1) Ma trix and vector analysis and manipulations (2) Mathematical functions (3) Symbolic calculations & functions (4) Import/export data files (5) Program lOgic and flow control (6) Writing function and passing parameters (7) Test application programs

Sen, Syamal K.↗

NASA NTRS2008

Actions Needed to Ensure Scientific and Technical Information is Adequately Reviewed at Goddard Space Flight Center, Johnson Space Center, Langley Research Center, and Marshall Space Flight Center

This audit was initiated in response to a hotline complaint regarding the review, approval, and release of scientific and technical information (STI) at Johnson Space Center. The complainant alleged that Johnson personnel conducting export control reviews of STI were not fully qualified to conduct those reviews and that the reviews often did not occur until after the STI had been publicly released. NASA guidance requires that STI, defined as the results of basic and applied scientific, technical, and related engineering research and development, undergo certain reviews prior to being released outside of NASA or to audiences that include foreign nationals. The process includes technical, national security, export control, copyright, and trade secret (e.g., proprietary data) reviews. The review process was designed to preclude the inappropriate dissemination of sensitive information while ensuring that NASA complies with a requirement of the National Aeronautics and Space Act of 1958 (the Space Act)1 to provide for the widest practicable and appropriate dissemination of information resulting from NASA research activities. We focused our audit on evaluating the STI review process: specifically, determining whether the roles and responsibilities for the review, approval, and release of STI were adequately defined and documented in NASA and Center-level guidance and whether that guidance was effectively implemented at Goddard Space Flight Center, Johnson Space Center, Langley Research Center, and Marshall Space Flight Center. Johnson was included in the review because it was the source of the initial complaint, and Goddard, Langley, and Marshall were included because those Centers consistently produce significant amounts of STI.

Information management↗

NASA NTRS2006

Representation of Serendipitous Scientific Data

A computer program defines and implements an innovative kind of data structure than can be used for representing information derived from serendipitous discoveries made via collection of scientific data on long exploratory spacecraft missions. Data structures capable of collecting any kind of data can easily be implemented in advance, but the task of designing a fixed and efficient data structure suitable for processing raw data into useful information and taking advantage of serendipitous scientific discovery is becoming increasingly difficult as missions go deeper into space. The present software eases the task by enabling definition of arbitrarily complex data structures that can adapt at run time as raw data are transformed into other types of information. This software runs on a variety of computers, and can be distributed in either source code or binary code form. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware. It has no specific memory requirements and depends upon the other software with which it is used. This program is implemented as a library that is called by, and becomes folded into, the other software with which it is used.

James, Mark↗

NASA NTRS2004

Prioritizing Scientific Data for Transmission

A software system has been developed for prioritizing newly acquired geological data onboard a planetary rover. The system has been designed to enable efficient use of limited communication resources by transmitting the data likely to have the most scientific value. This software operates onboard a rover by analyzing collected data, identifying potential scientific targets, and then using that information to prioritize data for transmission to Earth. Currently, the system is focused on the analysis of acquired images, although the general techniques are applicable to a wide range of data modalities. Image prioritization is performed using two main steps. In the first step, the software detects features of interest from each image. In its current application, the system is focused on visual properties of rocks. Thus, rocks are located in each image and rock properties, such as shape, texture, and albedo, are extracted from the identified rocks. In the second step, the features extracted from a group of images are used to prioritize the images using three different methods: (1) identification of key target signature (finding specific rock features the scientist has identified as important), (2) novelty detection (finding rocks we haven t seen before), and (3) representative rock sampling (finding the most average sample of each rock type). These methods use techniques such as K-means unsupervised clustering and a discrimination-based kernel classifier to rank images based on their interest level.

Castano, Rebecca↗

NASA NTRS2003

Software for Planning Scientific Activities on Mars

Mixed-Initiative Activity Plan Generator (MAPGEN) is a ground-based computer program for planning and scheduling the scientific activities of instrumented exploratory robotic vehicles, within the limitations of available resources onboard the vehicle. MAPGEN is a combination of two prior software systems: (1) an activity-planning program, APGEN, developed at NASA s Jet Propulsion Laboratory and (2) the Europa planner/scheduler from NASA Ames Research Center. MAPGEN performs all of the following functions: Automatic generation of plans and schedules for scientific and engineering activities; Testing of hypotheses (or what-if analyses of various scenarios); Editing of plans; Computation and analysis of resources; and Enforcement and maintenance of constraints, including resolution of temporal and resource conflicts among planned activities. MAPGEN can be used in either of two modes: one in which the planner/scheduler is turned off and only the basic APGEN functionality is utilized, or one in which both component programs are used to obtain the full planning, scheduling, and constraint-maintenance functionality.

Ai-Chang, Mitchell↗

NASA NTRS2012

Test Driven Development of Scientific Models

Test-Driven Development (TDD) is a software development process that promises many advantages for developer productivity and has become widely accepted among professional software engineers. As the name suggests, TDD practitioners alternate between writing short automated tests and producing code that passes those tests. Although this overly simplified description will undoubtedly sound prohibitively burdensome to many uninitiated developers, the advent of powerful unit-testing frameworks greatly reduces the effort required to produce and routinely execute suites of tests. By testimony, many developers find TDD to be addicting after only a few days of exposure, and find it unthinkable to return to previous practices. Of course, scientific/technical software differs from other software categories in a number of important respects, but I nonetheless believe that TDD is quite applicable to the development of such software and has the potential to significantly improve programmer productivity and code quality within the scientific community. After a detailed introduction to TDD, I will present the experience within the Software Systems Support Office (SSSO) in applying the technique to various scientific applications. This discussion will emphasize the various direct and indirect benefits as well as some of the difficulties and limitations of the methodology. I will conclude with a brief description of pFUnit, a unit testing framework I co-developed to support test-driven development of parallel Fortran applications.

Clune, Thomas L.↗

NASA NTRS2012

Social Networking Adapted for Distributed Scientific Collaboration

Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and messaging encryption; and g) Easy-to-use intuitive workflow.

Karimabadi, Homa↗

NASA NTRS2013

Educational NASA Computational and Scientific Studies (enCOMPASS)

Educational NASA Computational and Scientific Studies (enCOMPASS) is an educational project of NASA Goddard Space Flight Center aimed at bridging the gap between computational objectives and needs of NASA's scientific research, missions, and projects, and academia's latest advances in applied mathematics and computer science. enCOMPASS achieves this goal via bidirectional collaboration and communication between NASA and academia. Using developed NASA Computational Case Studies in university computer science/engineering and applied mathematics classes is a way of addressing NASA's goals of contributing to the Science, Technology, Education, and Math (STEM) National Objective. The enCOMPASS Web site at http://encompass.gsfc.nasa.gov provides additional information. There are currently nine enCOMPASS case studies developed in areas of earth sciences, planetary sciences, and astrophysics. Some of these case studies have been published in AIP and IEEE's Computing in Science and Engineering magazines. A few university professors have used enCOMPASS case studies in their computational classes and contributed their findings to NASA scientists. In these case studies, after introducing the science area, the specific problem, and related NASA missions, students are first asked to solve a known problem using NASA data and past approaches used and often published in a scientific/research paper. Then, after learning about the NASA application and related computational tools and approaches for solving the proposed problem, students are given a harder problem as a challenge for them to research and develop solutions for. This project provides a model for NASA scientists and engineers on one side, and university students, faculty, and researchers in computer science and applied mathematics on the other side, to learn from each other's areas of work, computational needs and solutions, and the latest advances in research and development. This innovation takes NASA science and engineering applications to computer science and applied mathematics university classes, and makes NASA objectives part of the university curricula. There is great potential for growth and return on investment of this program to the point where every major university in the U.S. would use at least one of these case studies in one of their computational courses, and where every NASA scientist and engineer facing a computational challenge (without having resources or expertise to solve it) would use enCOMPASS to formulate the problem as a case study, provide it to a university, and get back their solutions and ideas.

Memarsadeghi, Nargess↗

NASA NTRS2014

Using NASA-Unique Lunar Sample Disks and Resources to Inspire and Promote Scientific Inquiry

The opportunity for educators and students across the nation to hold precious, NASA lunar samples in their hands and examine materials brought back by astronauts during the Apollo era is an experience and memory that can last a lifetime. Combine that experience with the opportunity to be engaged with hands-on activities that promote scientific inquiry and an understanding of the importance of these samples...now you are preparing our nation's future scientific explorers.

Allen, J.↗

NASA NTRS2013

Profiling and Improving I/O Performance of a Large-Scale Climate Scientific Application

Exascale computing systems are soon to emerge, which will pose great challenges on the huge gap between computing and I/O performance. Many large-scale scientific applications play an important role in our daily life. The huge amounts of data generated by such applications require highly parallel and efficient I/O management policies. In this paper, we adopt a mission-critical scientific application, GEOS-5, as a case to profile and analyze the communication and I/O issues that are preventing applications from fully utilizing the underlying parallel storage systems. Through in-detail architectural and experimental characterization, we observe that current legacy I/O schemes incur significant network communication overheads and are unable to fully parallelize the data access, thus degrading applications' I/O performance and scalability. To address these inefficiencies, we redesign its I/O framework along with a set of parallel I/O techniques to achieve high scalability and performance. Evaluation results on the NASA discover cluster show that our optimization of GEOS-5 with ADIOS has led to significant performance improvements compared to the original GEOS-5 implementation.

Exascale↗

NASA NTRS2014

Geospace Missions for Space Weather and the Next Scientific Challenges

Currently there is an active international flotilla of spacecraft that continuously observe and measure the dynamic space environment that surrounds our planet. These spacecraft have remote sensors for photons and particles, and in situ instruments for plasmas, fields and particles. They provide the data input to guide, motivate, and validate predictive space weather models used by decision makers and for a myriad of scientific investigations. This talk will briefly survey the current Geospace missions relevant to space weather, what they observe, and why. This talk will conclude with the description of two most significant scientific challenges that must be met in order to advance our understanding and prediction of space weather, and its impacts to society. They are the genesis and evolution of ionospheric variability and the interplanetary magnetic field. Concepts of possible solutions for these two challenges will be discussed.

Spann, James↗

NASA NTRS2014

Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code.We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higherquality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the Big-Data analysis environments.

Kuo, Kwo-Sen↗