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At least 217 records · Page 12

Expanding NASA and Roscosmos Scientific Collaboration on the International Space Station

The International Space Station (ISS) is a world-class laboratory orbiting in space. NASA and Roscosmos have developed a strong relationship through the ISS Program Partnership, working together and with the other ISS Partners for more than twenty years. Since 2013, based on a framework agreement between the Program Managers, NASA and Roscosmos are building a joint program of collaborative research on ISS. This international collaboration is developed and implemented in phases. Initially, members of the ISS Program Science Forum from NASA and TsNIIMash (representing Roscosmos) identified the first set of NASA experiments that could be implemented in the "near term". The experiments represented the research categories of Technology Demonstration, Microbiology, and Education. Through these experiments, the teams from the "program" and "operations" communities learned to work together to identify collaboration opportunities, establish agreements, and jointly plan and execute the experiments. The first joint scientific activity on ISS occurred in January 2014, and implementation of these joint experiments continues through present ISS operations. NASA and TsNIIMash have proceeded to develop "medium term" collaborations, where scientists join together to improve already-proposed experiments. A major success is the joint One-Year Mission on ISS, with astronaut Scott Kelly and cosmonaut Mikhail Kornienko, who returned from ISS in March, 2016. The teams from the NASA Human Research Program and the RAS Institute for Biomedical Problems built on their considerable experience to design joint experiments, learn to work with each other's protocols and processes, and share medical and research data. New collaborations are being developed between American and Russian scientists in complex fluids, robotics, rodent research and space biology, and additional human research. Collaborations are also being developed in Earth Remote Sensing, where scientists will share data from imaging systems mounted on ISS as well as other orbiting spacecraft to improve our understanding of the Earth and its climate. NASA and Roscosmos continue to encourage international scientific cooperation and expanded use of the ISS Laboratory. "Long-term", larger collaborations will achieve scientific objectives that no single national science team or agency can achieve on its own. The joint accomplishments achieved so far have paved the way for a stronger international scientific community and improved results and benefits from ISS.

Hasbrook, Pete↗

An Overview of the Performance of the Chandra X-ray Observatory

The Chandra X-ray Observatory is the X-ray component of NASA's Great Observatory Program which includes the recently launched Spitzer Infrared Telescope, the Hubble Space Telescope (HST) for observations in the visible, and the Compton Gamma-Ray Observatory (CGRO) which, after providing years of useful data has reentered the atmosphere. All these facilities provide, or provided, scientific data to the international astronomical community in response to peer-reviewed proposals for their use. The Chandra X-ray Observatory was the result of the efforts of many academic, commercial, and government organizations primarily in the United States but also in Europe. NASA s Marshall Space Flight Center (MSFC) manages the Project and provides Project Science; Northrop Grumman Space Technology (NGST - formerly TRW) served as prime contractor responsible for providing the spacecraft, the telescope, and assembling and testing the Observatory; and the Smithsonian Astrophysical Observatory (SAO) provides technical support and is responsible for ground operations including the Chandra X-ray Center (CXC). Telescope and instrument teams at SAO, the Massachusetts Institute of Technology (MIT), the Pennsylvania State University (PSU), the Space Research Institute of the Netherlands (SRON), the Max-Planck Institut fur extraterrestrische Physik (MPE), and the University of Kiel support also provide technical support to the Chandra Project. We present here a detailed description of the hardware, its on-orbit performance, and a brief overview of some of the remarkable discoveries that illustrate that performance.

Weisskopf, M. C.↗

Minerva: User-Centered Science Operations Software Capability for Future Human Exploration

In June of 2016, the Biologic Analog Science Associated with Lava Terrains (BASALT) research project conducted its first field deployment, which we call BASALT-1. BASALT-1 consisted of a science-driven field campaign in a volcanic field in Idaho as a simulated human mission to Mars. Scientists and mission operators were provided a suite of ground software tools that we refer to collectively as Minerva to carry out their work. Minerva provides capabilities for traverse planning and route optimization, timeline generation and display, procedure management, execution monitoring, data archiving, visualization, and search. This paper describes the Minerva architecture, constituent components, use cases, and some preliminary findings from the BASALT-1 campaign.

Deans, Matthew↗

Minerva: User-Centered Science Operations Software Capability for Future Human Exploration

In June of 2016, the Biologic Analog Science Associated with Lava Terrains (BASALT) research project conducted its first field deployment, which we call BASALT-1. BASALT-1 consisted of a science-driven field campaign in a volcanic field in Idaho as a simulated human mission to Mars. Scientists and mission operators were provided a suite of ground software tools that we refer to collectively as Minerva to carry out their work. Minerva provides capabilities for traverse planning and route optimization, timeline generation and display, procedure management, execution monitoring, data archiving, visualization, and search. This paper describes the Minerva architecture, constituent components, use cases, and some preliminary findings from the BASALT-1 campaign.

Deans, Matthew↗

The Kepler Data Processing Handbook: A Field Guide to Prospecting for Habitable Worlds

The Kepler telescope hurtled into orbit in March 2009, initiating NASA's first mission to discover Earth-size planets orbiting Sun-like stars. Kepler simultaneously collected data for approximately 165,000 target stars at a time over its four-year mission, identifying over 4700 planet candidates, over 2300 confirmed or validated planets, and over 2100 eclipsing binaries. While Kepler was designed to discover exoplanets, the long-term, ultrahigh photometric precision measurements it achieved made it a premier observational facility for stellar astrophysics, especially in the field of asteroseismology, and for variable stars, such as RR Lyrae. The Kepler Science Operations Center (SOC) was developed at NASA Ames Research Center to process the data acquired by Kepler from pixel-level calibrations all the way to identifying transiting planet signatures and subjecting them to a suite of diagnostic tests to establish or break confidence in their planetary nature. Detecting small, rocky planets transiting Sun-like stars presents a variety of daunting challenges, including achieving an unprecedented photometric precision of ~20 ppm on 6.5-hour timescales, and supporting the science operations, management, processing, and repeated reprocessing of the accumulating data stream. A newly revised and expanded version of the Kepler Data Processing Handbook (KDPH) has been released to support the legacy archival products. The KDPH details the theory, design and performance of the algorithms supporting each data processing step. This paper presents an overview of the KDPH and features illustrations of several key algorithms in the Kepler Science Data Processing Pipeline. Kepler was selected as the 10th mission of the Discovery Program. Funding for this mission is provided by NASA, Science Mission Directorate.

high performance computing↗

Results from the NASA Spacecraft Fault Management Workshop: Cost Drivers for Deep Space Missions

Fault Management, the detection of and response to in-flight anomalies, is a critical aspect of deep-space missions. Fault management capabilities are commonly distributed across flight and ground subsystems, impacting hardware, software, and mission operations designs. The National Aeronautics and Space Administration (NASA) Discovery & New Frontiers (D&NF) Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for five missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that four out of the five missions studied had significant overruns due to underestimating the complexity and support requirements for fault management. As a result of this and other recent experiences, the NASA Science Mission Directorate (SMD) Planetary Science Division (PSD) commissioned a workshop to bring together invited participants across government, industry, and academia to assess the state of the art in fault management practice and research, identify current and potential issues, and make recommendations for addressing these issues. The workshop was held in New Orleans in April of 2008. The workshop concluded that fault management is not being limited by technology, but rather by a lack of emphasis and discipline in both the engineering and programmatic dimensions. Some of the areas cited in the findings include different, conflicting, and changing institutional goals and risk postures; unclear ownership of end-to-end fault management engineering; inadequate understanding of the impact of mission-level requirements on fault management complexity; and practices, processes, and tools that have not kept pace with the increasing complexity of mission requirements and spacecraft systems. This paper summarizes the findings and recommendations from that workshop, particularly as fault management development issues affect operations and the development of operations capabilities.

Newhouse, Marilyn E.↗

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as SAR data provides high resolution (5-10 m) imagery, unaffected by cloud cover and light availability (day vs. night), common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band (once operational and available on the GEE repository) synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow product to determine regional snow coverage, which affects land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd wetland located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management.

Inundation↗

Geothermal research and development program of the US Atomic Energy Commission

Within the overall federal geothermal program, the Atomic Energy Commission has chosen to concentrate on development of resource utilization and advanced research and technology as the areas most suitable to the expertise of its staff and that of the National Laboratories. The Commission's work in geothermal energy is coordinated with that of other agencies by the National Science Foundation, which has been assigned lead agency by the Office of Management and Budget. The objective of the Commission's program, consistent with the goals of the total federal program is to facilitate, through technological advancement and pilot plant operations, achievement of substantial commercial production of electrical power and utilization of geothermal heat by the year 1985. This will hopefully be accomplished by providing, in conjunction with industry, credible information on the economic operation and technological reliability of geothermal power and use of geothermal heat.

Werner, L. B.↗

The development of an intelligent user interface for NASA's scientific databases

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 effort is to develop a friendly and intelligent user interface service that is based on expert systems and natural language processing technologies. This paper presents the design concepts, development approach and evaluation of performance of a prototype Intelligent User Interface Subsystem (IUIS) supporting an operational database.

Campbell, William J.↗

The development of an intelligent user interface for NASA's scientific databases

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 effort is to develop a friendly and intelligent user interface service that is based on expert systems and natural language processing technologies. This paper presents the design concepts, development approach and evaluation of performance of a prototype Intelligent User Interface Subsystem (IUIS) supporting an operational database.

Campbell, William J.↗

Characterization of Evidence for Human System Risk Assessment

Understanding the kinds of evidence available and using the best evidence to answer a question is critical to evidenced-based decision-making, and it requires synthesis of evidence from a variety of sources. Categorization of human system risks in spaceflight, in particular, focuses on how well the integration and interpretation of all available evidence informs the risk statement that describes the relationship between spaceflight hazards and an outcome of interest. A mature understanding and categorization of these risks requires: 1) sufficient characterization of risk, 2) sufficient knowledge to determine an acceptable level of risk (i.e., a standard), 3) development of mitigations to meet the acceptable level of risk, and 4) identification of factors affecting generalizability of the evidence to different design reference missions. In the medical research community, evidence is often ranked by increasing confidence in findings gleaned from observational and experimental research (e.g., "levels of evidence"). However, an approach based solely on aspects of experimental design is problematic in assessing human system risks for spaceflight. For spaceflight, the unique challenges and opportunities include: (1) The independent variables in most evidence are the hazards of spaceflight, such as space radiation or low gravity, which cannot be entirely duplicated in terrestrial (Earth-based) analogs, (2) Evidence is drawn from multiple sources including medical and mission operations, Lifetime Surveillance of Astronaut Health (LSAH), spaceflight research (LSDA), and relevant environmental & terrestrial databases, (3) Risk metrics based primarily on LSAH data are typically derived from available prevalence or incidence data, which may limit rigorous interpretation, (4) The timeframe for obtaining adequate spaceflight sample size (n) is very long, given the small population, (5) Randomized controlled trials are unattainable in spaceflight, (6) Collection of personal and environmental data on the astronaut population may create opportunities for advanced analytics and human-environment modeling that goes beyond that achieved in isolated experimental designs; and (7) Translation of relevant research to operations is a complex, transdisciplinary enterprise in which the approach must apply across the physical, biological, behavioral, and social sciences. The approach to synthesizing evidence must address both source and fidelity of data, and reflect the most general attributes of quality of evidence in science and engineering: reliability and validity. The authors are developing a two-factor approach which includes the various kinds of evidence required to understand risks and for the integrated interpretation of all evidence that is essential to develop standards and countermeasures. A unified framework for aggregating and assessing different kinds of evidence provides a consistent, traceable, evidence-based decision-making process to translate research to operations in an environment where engineers, scientists, physicians, and managers all engage in analyzing the trade space of vehicle design, standards, requirements and solutions for spaceflight.

Steinberg, S. L.↗

NASA-ESA Spacelab systems and programs; Proceedings of the Seminar, Washington, DC, April 23, 24, 1981

Topics discussed include the development status of the Space Shuttle and Spacelab, with attention to Spacelab subsystem performance capabilities and Shuttle-Spacelab flight operations; Spacelab data management and software for science applications, ESA and Space Shuttle pointing systems, and the Space Shuttle's Office of Space and Terrestrial Applications (OSTA)-1 payload. Also covered are the lessons learned from the first Spacelab mission, the pallet-only mode verification flight of the second Spacelab mission, the objectives of the Spacelab mission D1, its role in the German space program, and its implementation, the impact of Spacelab on space-based life sciences research, the high resolution, large area modular reflector array X-ray telescope to be used by Spacelab, and Space Shuttle contamination effects on UV coronagraphic observations.

Moore, J. W.↗

Internship at the Office of the Chief Scientist

The NASA Ames Research Center (ARC) Office of the Chief Scientist (OCS) is part of the Center Management. The OCS adds value to the organization by encouraging and facilitating innovation and value to the Agency, Nation, and the scientific community through its well-developed, diverse, and strategically formed charter. The OCS provides the Center with the oversight and advice by facilitating and evaluating the Scientific Innovation Fund (SIF) and promoting science-based research partnerships. Additionally, the Office contributes to to the Agency by organizing annual Summer Series Colloquia, Workshops, and support to the Early Career Network, which allows for international and inter-agency collaborations. Working at the OCS allowed me to further learn about the working of the Office and how the Office engages and provides guidance with rest of the Center and the Agency. As part of my internship, I am working on developing the initial infrastructure required for the organization of the Standardized Distributed Workshop and further developing the layout for the Hibernation Workshop. The Standardized Distributed System workshop will investigate the scope of developing and using standardized distributed systems for a wide range of applications including satellite systems, aerospace-oriented systems, water-based systems, automobiles, and various other robotics applications. The goal of this workshop is to determine the feasibility of developing a standardized distributed system that can be customized for different technological applications, which will enable resource sharing, openness, robustness, and fault tolerance. This workshop will bring together experts from different fields, including satellite operations, unmanned aerial vehicles, aircraft operation and management, and artificial intelligence to provide a global evaluation of the aspects associated with the development and adoption of distributed systems. The workshop will also guide the participants through state of the art distributed systems, discuss some of the challenges in designing control systems with a distributed structure, and consider the future of distributed system based technologies for future applications. Additionally, I am also working on finalizing the details and documentation for the proposed Hibernation Workshop. This workshop will address the phenomenon of hibernation through three major aspects: hibernation on Earth, hibernation in space, and knowledge gaps in the approaches to future deep space exploration. The primary objective of the workshop is to explore the current state of science in the area of hibernation, and as a scientific community, explore the gaps and challenges preventing this scientific field from advancing to the next level. This workshop will consist of presentations, panel discussions, and breakout sessions focused on addressing this scientific field, and bringing experts from educational and commercial sectors together. As a part of my internship report, I will be document the process of planning these workshops and further provide a brief summary of my experience with the 2016 NASA Ames Summer Series and various professional visits.

ISU↗

The role of small missions in planetary and lunar exploration

The Space Studies Board of the National Research Council charged its Committee on Planetary and Lunar Exploration (COMPLEX) to (1) examine the degree to which small missions, such as those fitting within the constraints of the Discovery program, can achieve priority objectives in the lunar and planetary sciences; (2) determine those characteristics, such as level of risk, flight rate, target mix, university involvement, technology development, management structure and procedures, and so on, that could allow a successful program; (3) assess issues, such as instrument selection, mission operations, data analysis, and data archiving, to ensure the greatest scientific return from a particular mission, given a rapid deployment schedule and a tightly constrained budget; and (4) review past programmatic attempts to establish small planetary science mission lines, including the Planetary Observers and Planetary Explorers, and consider the impact management practices have had on such programs. A series of small missions presents the planetary science community with the opportunity to expand the scope of its activities and to develop the potential and inventiveness of its members in ways not possible within the confines of large, traditional programs. COMPLEX also realized that a program of small planetary missions was, in and of itself, incapable of meeting all of the prime objectives contained in its report 'An Integrated Strategy for the Planetary Sciences: 1995-2010.' Recommendations are provided for the small planetary missions to fulfill their promise.

Source record↗

Sensor to User - NASA/EOS Data for Coastal Zone Management Applications Developed from Integrated Analyses: Verification, Validation and Benchmark Report

The NASA Applied Sciences Program seeks to transfer NASA data, models, and knowledge into the hands of end-users by forming links with partner agencies and associated decision support tools (DSTs). Through the NASA REASoN (Research, Education and Applications Solutions Network) Cooperative Agreement, the Oceanography Division of the Naval Research Laboratory (NRLSSC) is developing new products through the integration of data from NASA Earth-Sun System assets with coastal ocean forecast models and other available data to enhance coastal management in the Gulf of Mexico. The recipient federal agency for this research effort is the National Oceanic and Atmospheric Administration (NOAA). The contents of this report detail the effort to further the goals of the NASA Applied Sciences Program by demonstrating the use of NASA satellite products combined with data-assimilating ocean models to provide near real-time information to maritime users and coastal managers of the Gulf of Mexico. This effort provides new and improved capabilities for monitoring, assessing, and predicting the coastal environment. Coastal managers can exploit these capabilities through enhanced DSTs at federal, state and local agencies. The project addresses three major issues facing coastal managers: 1) Harmful Algal Blooms (HABs); 2) hypoxia; and 3) freshwater fluxes to the coastal ocean. A suite of ocean products capable of describing Ocean Weather is assembled on a daily basis as the foundation for this semi-operational multiyear effort. This continuous realtime capability brings decision makers a new ability to monitor both normal and anomalous coastal ocean conditions with a steady flow of satellite and ocean model conditions. Furthermore, as the baseline data sets are used more extensively and the customer list increased, customer feedback is obtained and additional customized products are developed and provided to decision makers. Continual customer feedback and response with new improved products are required between the researcher and customer. This document details the methods by which these coastal ocean products are produced including the data flow, distribution, and verification. Product applications and the degree to which these products are used successfully within NOAA and coordinated with the Mississippi Department of Marine Resources (MDMR) is benchmarked.

Hall, Callie↗

ASTAR Flight Test: Overview and Spacing Results

The purpose of the NASA Langley Airborne Spacing for Terminal Arrival Routes (ASTAR) research aboard the Boeing ecoDemonstrator aircraft was to demonstrate the use of NASA's ASTAR algorithm using contemporary tools of the Federal Aviation Administration's Next Generation Air Transportation System (NEXTGEN). EcoDemonstrator is a Boeing test program which utilizes advanced experimental equipment to accelerate the science of aerospace and environmentally friendly technologies. The ASTAR Flight Test provided a proof-of-concept flight demonstration that exercised an algorithmic-based application in an actual aircraft. The test aircraft conducted Interval Management operations to provide time-based spacing off a target aircraft in non-simulator wind conditions. Work was conducted as a joint effort between NASA and Boeing to integrate ASTAR in a Boeing supplied B787 test aircraft while using a T-38 aircraft as the target. This demonstration was also used to identify operational risks to future flight trials for the NASA Air Traffic Management Technology Demonstration expected in 2017.

Roper, Roy D.↗

From the Knowledge-based Digital Platform (KbDP) Concept for Advanced Air Mobility Research to a Preliminary Prototype

Advanced Air Mobility (AAM) encompasses a range of innovative operational and technological changes to aviation (electric aircraft, increasingly automated aircraft, increasingly automated airspace operations, etc.) that are transforming aviation’s role in everyday movement of people and goods. There are multiple associated concepts and use cases for AAM, all interrelated, including small Unmanned Aircraft System (UAS) Traffic Management (UTM), Upper-Class E Traffic Management (ETM), Extensible Traffic Management (xTM), Regional Air Mobility (RAM), and Urban Air Mobility (UAM). These AAM operations must integrate with traditional Air Traffic Management (ATM) operations, as well as non-aviation modes of transportation and logistics. National Aeronautics and Space Administration (NASA) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from the information database, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Expected benefits of this concept include improved technology transfers from research to production, improved research portfolio investments, and research outcomes that are more integrated with all aspects of the multi-modal transportation problem. The preliminary KbDP prototype has been realized using UAM as a pathfinder use case and developed by a team of system engineer, software developer, data scientist, and interns.

Systems Engineering↗

Introduction to Air Traffic Management

The presentation introduces students and faculty to air traffic management with focus on air traffic data for data-science. Starting with the common attributes of transportation systems — highway transportation, air transportation and data transportation, the initial set of slides discuss the purpose of data-science in air traffic management, reasons why air traffic management is challenging, and the multidisciplinary nature of air traffic management research. The history of flight from 1903 — Wright Flyer — to 1987 — formation of the National Air Traffic Controllers Association — is briefly discussed. The national airspace system is described in terms of airports in the U. S., air traffic control facilities (flight service stations, terminal, enroute and system command center), airspace geometry (sectors, airways and navaids), governing regulations and directives, airspace classification (Class A through G), special use airspace, visual flight rules and instrument flight rules. The contents of a flight-plan are described. Weather briefing is discussed. The surveillance equipment used for surface, terminal area and enroute are described, and the aircraft states obtained using the surveillance data are listed. Airline operations control functions — schedule development, flight planning, resource scheduling and flight following — are noted. Next, the roles and responsibilities of air traffic controllers and traffic flow managers are discussed. Separation standards and conflict resolution techniques are outlined. Finally, traffic flow management techniques are reviewed with an illustrative example.

Air Traffic Management↗