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NASA NTRS2004

A Three-fold Outlook of the Ultra-Efficient Engine Technology Program Office (UEET)

The Ultra-Efficient Engine Technology (UEET) Office at NASA Glenn Research Center is a part of the Aeronautics Directorate. Its vision is to develop and hand off revolutionary turbine engine propulsion technologies that will enable future generation vehicles over a wide range of flight speeds. There are seven different technology area projects of UEET. During my tenure at NASA Glenn Research Center, my assignment was to assist three different areas of UEET, simultaneously. I worked with Kathy Zona in Education Outreach, Lynn Boukalik in Knowledge Management, and Denise Busch with Financial Management. All of my tasks were related to the business side of UEET. As an intern with Education Outreach I created a word search to partner with an exhibit of a Turbine Engine developed out of the UEET office. This exhibit is a portable model that is presented to students of varying ages. The word search complies with National Standards for Education which are part of every science, engineering, and technology teachers curriculum. I also updated a Conference Planning/Workshop Excel Spreadsheet for the UEET Office. I collected and inputted facility overviews from various venues, both on and off site to determine where to hold upcoming conferences. I then documented which facilities were compliant with the Federal Emergency Management Agency's (FEMA) Hotel and Motel Fire Safety Act of 1990. The second area in which I worked was Knowledge Management. a large knowledge management system online which has extensive documentation that continually needs reviewing, updating, and archiving. Knowledge management is the ability to bring individual or team knowledge to an organizational level so that the information can be stored, shared, reviewed, archived. Livelink and a secure server are the Knowledge Management systems that UEET utilizes, Through these systems, I was able to obtain the documents needed for archiving. My assignment was to obtain intellectual property including reports, presentations, or any other documents related to the project. My next task was to document the author, date of creation, and all other properties of each document. To archive these documents I worked extensively with Microsoft Excel. different financial systems of accounting such as the SAP business accounting system. I also learned the best ways to present financial data and shadowed my mentor as she presented financial data to both UEET's project management and the Resources Analysis and Management Office (RAMO). I analyzed the June 2004 financial data of UEET and used Microsoft Excel to input the results of the data. This process made it easier to present the full cost of the project in the month of June. In addition I assisted in the End of the Year 2003 Reconciliation of Purchases of UEET.

Graham, La Quilia E.↗
NASA NTRS2010

Environmental Impact Specification for Direct Space Weathering of Kuiper Belt and Oort Cloud Objects

The Direct Space Weathering Project of NASA's Outer Planets Research Program addresses specification of the plasma and energetic particle environments for irradiation and surface chemical processing of icy bodies in the outer solar system and the local interstellar medium. Knowledge of the radiation environments is being expanded by ongoing penetration of the twin Voyager spacecraft into the heliosheath boundary region of the outer heliosphere and expected emergence within the next decade into the very local interstellar medium. The Voyager measurements are being supplemented by remote sensing from Earth orbit of energetic neutral atom emission from this boundary region by NASA's Interstellar Boundary Explorer (IBEX). Although the Voyagers long ago passed the region of the Classical Kuiper Belt, the New Horizons spacecraft will encounter Pluto in 2015 and thereafter explore one or more KBOs, meanwhile providing updated measurements of the heliospheric radiation environment in this region. Modeling of ion transport within the heliosphere allows specification of time-integrated irradiation effects while the combination of Voyager and IBEX data supports projection of the in-situ measurements into interstellar space beyond the heliosheath. Transformation of model ion flux distributions into surface sputtering and volume ionization profiles provides a multi-layer perspective for space weathering impact on the affected icy bodies and may account for some aspects of color and compositional diversity. Other important related factors may include surface erosion and gardening by meteoritic impacts and surface renewal by cryovolcanism. Chemical products of space weathering may contribute to energy resources for the latter.

Cooper, John F.↗
NASA NTRSDate not supplied

Spaceflight Associated Neuro-Ocular Syndrome: A Brief for Astronaut Candidates

INTRODUCTION: Spaceflight Associated Neuro-ocular Syndrome (SANS) was first described in 2011 as a clinical process involving degradation of visual acuity and structural changes of the eye when exposed to microgravity. This syndrome poses a risk to astronaut vision, safety, and mission performance, especially during extended-duration missions. The modern astronaut cohort is a diverse group of men and women including scientists, engineers, teachers, pilots, business professionals, and artists. Given their diverse backgrounds, it is imperative all crews are educated on SANS risks and potential countermeasures. This education must be comprehensive and easily understood, regardless of academic background or specific expertise. TOPIC: A PowerPoint was created to serve as a presentation and stand-alone educational aid for all astronaut candidates (ASCANS). This medium was chosen as it can be updated dynamically as new information emerges. The brief was split into sections to facilitate organized delivery of complex content in easy-to-understand components. Sections included descriptive statistics, signs and symptoms, outcomes, myths and ongoing research, countermeasures, ongoing surveillance, and unknown and future directions. More research is necessary in order to understand this syndrome, and without continued ASCAN participation in research, acquisition of data will not be possible. These efforts will become increasingly critical with deep space and exploration missions. APPLICATION: We recommend regular use of this brief for all ASCANS, and potentially veteran crewmembers, given the high risks and potentially poor outcomes associated with SANS. For ASCANS, recommendations include that this brief be provided at the start of their training, with a bi-annual refresher course for all astronauts. This ensures they are current on SANS information, given the dynamic nature of this syndrome. Additionally, this brief will be made available to all as a self-study aid, utilized as a refresher immediately prior to launch. It is anticipated that this brief will promote the health, safety, and wellbeing of professional and private crews alike, during and after long-duration spaceflight. RESOURCES: Brunstetter, T., Tarver, B., & Tsung, A. (2022, October). Spaceflight Associated Neuro-ocular Syndrome (Sans) and its Risk to Nasa Astronauts. JSC Aerospace Medicine Clerkship. Houston, TX; Lyndon B. Johnson Space Center. Laurie, S. S., Macias, B. R., Pardon, L. P., Brunstetter, T., Tarver, W. J., Gibson, C. R., Greenwald, S. H., Jasien, K. V., Mason, S., & Tsung, A. (2022). (rep.). Evidence Report: Risk of Spaceflight Associated Neuro-ocular Syndrome (SANS). Houston, TX: National Aeronautics and Space Administration. Mader, T. H., Gibson, C. R., Pass, A. F., Kramer, L. A., Lee, A. G., Fogarty, J., ... & Polk, J. D. (2011). Optic disc edema, globe flattening, choroidal folds, and hyperopic shifts observed in astronauts after long-duration space flight. Ophthalmology, 118(10), 2058-2069. LEARNING OBJECTIVES: • The audience will be able to describe current Spaceflight Associated Neuro-ocular Syndrome (SANS) findings, significance, and countermeasures. • The audience will understand the importance of astronauts’ familiarity with SANS prior to flying and the large risks associated with this syndrome. CME QUESTIONS (3 QUESTIONS, MULTIPLE CHOICE A-D): 1. What is the approximate prevalence rate of SANS in astronauts? A. 22% B. 50% C. 66% D. 80% Answer: C. 2. Which of the ocular findings are NOT associated with SANS? A. Optic disc edema B. Retinal detachment C. Globe flattening D. Chorioretinal folds Answer: B. 3. Which of the following diagnostic technologies are NOT available in-flight? A. Ocular ultrasound B. Retinal photography C. MRI Orbit D. Optical Coherence Tomography (OCT) Answer: C.

Sara Stroble Mason↗
NASA NTRS2001

Road Extraction from AVIRIS Using Spectral Mixture and Q-Tree Filter Techniques

Accurate road location and condition information are of primary importance in road infrastructure management. Additionally, spatially accurate and up-to-date road networks are essential in ambulance and rescue dispatch in emergency situations. However, accurate road infrastructure databases do not exist for vast areas, particularly in areas with rapid expansion. Currently, the US Department of Transportation (USDOT) extends great effort in field Global Positioning System (GPS) mapping and condition assessment to meet these informational needs. This methodology, though effective, is both time-consuming and costly, because every road within a DOT's jurisdiction must be field-visited to obtain accurate information. Therefore, the USDOT is interested in identifying new technologies that could help meet road infrastructure informational needs more effectively. Remote sensing provides one means by which large areas may be mapped with a high standard of accuracy and is a technology with great potential in infrastructure mapping. The goal of our research is to develop accurate road extraction techniques using high spatial resolution, fine spectral resolution imagery. Additionally, our research will explore the use of hyperspectral data in assessing road quality. Finally, this research aims to define the spatial and spectral requirements for remote sensing data to be used successfully for road feature extraction and road quality mapping. Our findings will facilitate the USDOT in assessing remote sensing as a new resource in infrastructure studies.

Gardner, Margaret E.↗
NASA NTRS1993

Strategies in transition

A new vision has emerged within the Office of Space Science and Applications (OSSA), and within the agency as a whole, for how to design missions to be responsive to the changing budget environment of the 1990s. The overall space science and applications program had to be looked at, restructuring the most expensive and complex projects to bring down costs and ensure their place in the mission queue of the future. The recent restructuring of some of OSSA's largest programs in development and the work to improve efficiency for those in operation is part of OSSA's effort to free funds for more frequent space science missions in the future. Instead of more great observatories, we are looking toward a new vision encompassing a level of great activity through small, frequent missions. The strategy developed for attaining this vision was to lower costs by reducing size and complexity through new technology, while at the same time making progress in space science. The strategy comprises two interwoven parts: the flight program strategy of each of the science disciplines and OSSA's new-technology strategy. The overall purpose of all OSSA's efforts to date has been to free resources for maximizing the space science program in a tough fiscal environment.

Diaz, Alphonso V.↗
NASA NTRS2017

The Utility of a Small Pressurized Rover with Suit Ports for Lunar Exploration: A Geologist's Perspective

Rover trade study: As summarized recently, mission simulations at Black Point Lava Flow (Arizona) that included realistic extravehicular activity (EVA) tasking, accurate traverse timelines, and an in-loop science CAPCOM (or SciCOM) showed that a small pressurized rover (SPR) was a better mobility asset than an unpressurized rover (UPR). Traverses within the SPR were easier on crew than spending an entire day in a spacesuit, enhancing crew productivity at each station. The SPR, named Lunar Electric Rover (LER), and sometimes called the Space Exploration Vehicle (SEV), could also provide shelter during a suit malfunction, radiation event, or medical emergency that might occur on the Moon. Intravehicular activity (IVA) capabilities: From within the vehicle, crew could describe and photo-document distant features during drives between stations, as well as in the near-field, directly in front of the LER, providing an ability to begin EVA planning on approach to each outcrop prior to egress. The vehicle can rotate 360º without any lateral movement, providing views in all directions. It has high-visibility windows, a ForeCam, AftCam, port and starboard cameras, docking cameras, and a GigaPan camera. EVA capabilities: To reduce timeline, mass, and volumetric overhead, rapid egress and ingress were envisioned, replacing an airlock with lower cabin pressure than on the International Space Station and suit ports on the aft cabin wall [2]. When needed for closer inspection and sample collecting, crew could egress in about 10 minutes through suit ports. Crew use SuitCams for additional photo-documentation, transmit mobile observations verbally, and collect surface materials. Typical simulations involved 3 to 4 EVA stations/day and 2 to 3 hr/day of boots on the ground. This allowed crew to explore a far larger territory, with more complex geological and in situ resource utilization (ISRU) features, than would a single, longer-duration EVA at one location, while also minimizing crew time in a spacesuit. Additionally, the vehicle could be driven with crew locked into the suit ports. This approach could involve a driver in the cockpit with a suited crewmember in a suit port, or the vehicle could be driven from the aft deck with both crewmembers in their suit ports. This approach was used when distances between stops were short enough that vehicle ingress and egress were less efficient than remaining in the suits and driving. Utility of suit ports: The advantages of suit ports were clearly demonstrated in those field-based trade studies. To illustrate those advantages further, consider the consequences of a SPR without suit ports at the Apollo 17 landing site. At that site, the crew's second EVA was an approximately 18 km loop conducted in a UPR, called the Lunar Roving Vehicle (LRV), in 7 hr 36 min 56 s. The traverse was composed of 5 formal stations, plus 8 additional LRV stations where crew made brief scientific stops. In a scenario involving a SPR without suit ports, crew would go EVA through an airlock and probably be limited to a single EVA per day. In that case, crew could drive the SPR ~9 km from the landing site to station 2, go EVA, and complete station 2 tasks. However, to conduct station 3 tasks, the crew would then need to walk approximately 3 km to station 3, while ground control in Houston tele-robotically drives the LER to station 3. A walk of approximately 3 km is possible, as that is what the Apollo 14 crew did before LRVs were deployed, but it is a lengthy and potentially grueling EVA. Assuming crew completes station 3 tasks, they would likely need to re-enter the SPR, ending the day's EVA, and return to the landing site. They would not be able to walk the additional distances to stations 4 and 5 (the latter being about 6 km from station 3). Thus, crew in an SPR without suit ports would require two days to accomplish the same tasks Apollo 17 crew completed in a single day. If a future crew is involved in long duration traverses on the lunar surface, the deployment of a vehicle with suit ports would probably be a better solution.

Kring, David A.↗
NASA NTRS1992

Data distribution satellite

The Data Distribution Satellite (DDS), operating in conjunction with the planned space network, the National Research and Education Network and its commercial derivatives, would play a key role in networking the emerging supercomputing facilities, national archives, academic, industrial, and government institutions. Centrally located over the United States in geostationary orbit, DDS would carry sophisticated on-board switching and make use of advanced antennas to provide an array of special services. Institutions needing continuous high data rate service would be networked together by use of a microwave switching matrix and electronically steered hopping beams. Simultaneously, DDS would use other beams and on board processing to interconnect other institutions with lesser, low rate, intermittent needs. Dedicated links to White Sands and other facilities would enable direct access to space payloads and sensor data. Intersatellite links to a second generation ATDRS, called Advanced Space Data Acquisition and Communications System (ASDACS), would eliminate one satellite hop and enhance controllability of experimental payloads by reducing path delay. Similarly, direct access would be available to the supercomputing facilities and national data archives. Economies with DDS would be derived from its ability to switch high rate facilities amongst users needed. At the same time, having a CONUS view, DDS would interconnect with any institution regardless of how remote. Whether one needed high rate service or low rate service would be immaterial. With the capability to assign resources on demand, DDS will need only carry a portion of the resources needed if dedicated facilities were used. Efficiently switching resources to users as needed, DDS would become a very feasible spacecraft, even though it would tie together the space network, the terrestrial network, remote sites, 1000's of small users, and those few who need very large data links intermittently.

Stevens, Grady H.↗
NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗
NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗
NASA NTRS2001

Challenges Facing Design and Analysis Tools

The design and analysis of future aerospace systems will strongly rely on advanced engineering analysis tools used in combination with risk mitigation procedures. The implications of such a trend place increased demands on these tools to assess off-nominal conditions, residual strength, damage propagation, and extreme loading conditions in order to understand and quantify these effects as they affect mission success. Advances in computer hardware such as CPU processing speed, memory, secondary storage, and visualization provide significant resources for the engineer to exploit in engineering design. The challenges facing design and analysis tools fall into three primary areas. The first area involves mechanics needs such as constitutive modeling, contact and penetration simulation, crack growth prediction, damage initiation and progression prediction, transient dynamics and deployment simulations, and solution algorithms. The second area involves computational needs such as fast, robust solvers, adaptivity for model and solution strategies, control processes for concurrent, distributed computing for uncertainty assessments, and immersive technology. Traditional finite element codes still require fast direct solvers which when coupled to current CPU power enables new insight as a result of high-fidelity modeling. The third area involves decision making by the analyst. This area involves the integration and interrogation of vast amounts of information - some global in character while local details are critical and often drive the design. The proposed presentation will describe and illustrate these areas using composite structures, energy-absorbing structures, and inflatable space structures. While certain engineering approximations within the finite element model may be adequate for global response prediction, they generally are inadequate in a design setting or when local response prediction is critical. Pitfalls to be avoided and trends for emerging analysis tools will be described.

Knight, Norman F., Jr.↗
NASA NTRS2011

DoD-GEIS Rift Valley Fever Monitoring and Prediction System as a Tool for Defense and US Diplomacy

Over the last 10 years the Armed Forces Health Surveillance Center's Global Emerging Infections Surveillance and Response System (GEIS) partnering with NASA'S Goddard Space Flight Center and USDA's USDA-Center for Medical, Agricultural & Veterinary Entomology established and have operated the Rift Valley fever Monitoring and Prediction System to monitor, predict and assess the risk of Rift Valley fever outbreaks and other vector-borne diseases over Africa and the Middle East. This system is built on legacy DoD basic research conducted by Walter Reed Army Institute of Research overseas laboratory (US Army Medical Research Unit-Kenya) and the operational satellite environmental monitoring by NASA GSFC. Over the last 10 years of operation the system has predicted outbreaks of Rift Valley fever in the Horn of Africa, Sudan, South Africa and Mauritania. The ability to predict an outbreak several months before it occurs provides early warning to protect deployed forces, enhance public health in concerned countries and is a valuable tool use.d by the State Department in US Diplomacy. At the international level the system has been used by the Food and Agricultural Organization (FAD) and the World Health Organization (WHO) to support their monitoring, surveillance and response programs in the livestock sector and human health. This project is a successful testament of leveraging resources of different federal agencies to achieve objectives of force health protection, health and diplomacy.

Anyamba, Assaf↗
NASA NTRS2011

An Integrated Hydrological and Water Management Study of the Entire Nile River System - Lake Victoria to Nile Delta

The Nile basin River system spans 3 million km(exp 2) distributed over ten nations. The eight upstream riparian nations, Ethiopia, Eretria, Uganda, Rwanda, Burundi, Congo, Tanzania and Kenya are the source of approximately 86% of the water inputs to the Nile, while the two downstream riparian countries Sudan and Egypt, presently rely on the river's flow for most of the their needs. Both climate and agriculture contribute to the complicated nature of Nile River management: precipitation in the headwaters regions of Ethiopia and Lake Victoria is variable on a seasonal and inter-annual basis, while demand for irrigation water in the arid downstream region is consistently high. The Nile is, perhaps, one of the most difficult trans-boundary water issue in the world, and this study would be the first initiative to combine NASA satellite observations with the hydrologic models study the overall water balance in a to comprehensive manner. The cornerstone application of NASA's Earth Science Research Results under this project are the NASA Land Data Assimilation System (LDAS) and the USDA Atmosphere-land Exchange Inverse (ALEXI) model. These two complementary research results are methodologically independent methods for using NASA observations to support water resource analysis in data poor regions. Where an LDAS uses multiple sources of satellite data to inform prognostic simulations of hydrological process, ALEXI diagnoses evapotranspiration and water stress on the basis of thermal infrared satellite imagery. Specifically, this work integrates NASA Land Data Assimilation systems into the water management decision support systems that member countries of the Nile Basin Initiative (NBI) and Regional Center for Mapping of Resources for Development (RCMRD, located in Nairobi, Kenya) use in water resource analysis, agricultural planning, and acute drought response to support sustainable development of Nile Basin water resources. The project is motivated by the recognition that accurate, frequent, and spatially distributed estimates of the water balance are necessary for effective water management. This creates a challenge for watersheds that are large, include data poor regions, and/or span multiple nations. All of these descriptors apply to the Nile River basin, yet successful management of the Nile is critical for development and political stability in the region. For this reason, improved hydrological data to support cooperative water management in the Nile basin is a priority for USAID, the US State Department, the World Bank and other international organizations. In this project, the U.S. based research team is working with partners at RCMRD, Nile Basin Initiative (NBI), and their member national-level agencies to develop satellite-based land cover maps, satellite-derived evapotranspiration estimates (using the ALEXI algorithm), and NASA's Land Data Assimilation System (LDAS) customized to match identified information needs. The cornerstone applied sciences product of the project is the development of a customized "Nile LDAS" that will produce optimal estimates of hydrological states and fluxes, as vetted against the in situ observations of NBI and RCMRD member organizations and independent satellite-derived hydrological estimates. Nile LDAS will be applied to improve the reliability of emerging Decision Support Systems in applications that include drought monitoring, reservoir management, and irrigation planning. The end-users such as RCMRD, NBI, Ethiopian and Kenya Meteorological and Famine Early Warning System Network (FEWSNet) will be the eventual benefactors of this work. There will be a capacity building process involving the above end-user organizations and transfer the models and the results for these organizations to execute for future use. The team has already initiated this study and the early results of first years' work are shown. The plan is to complete this work by late 2013.

Habib, Shahid↗
NASA NTRS2010

Application of Satellite Observations to Manage Natural Disasters in the Lake Victoria Basin

Lake Victoria, the second largest fresh water lake in the Eastern part of Africa is a vital natural resource for the economic well being and prosperity of over 30 million people located in riparian regions of Uganda, Kenya and Tanzania. It covers a large area of about 68,870 km2 and produces a GDP of about US $30 billion per year. The region is also very much prone to natural disasters such as severe floods during heavy precipitation periods in the Eastern part of Africa. In addition to floods, the precipitation also produces large infestations of mosquito larvae due to the standing water in many areas. This further causes multiple vector borne diseases such as Malaria, Rift Valley Fever and more. These problems are of serious concern and require active and aggressive surveillance and management to minimize the loss of human and animal lives and property damage. Satellite imagery and observations along with the in situ measurements provide a great tool to analyze and study this area and inform the policy makers to make calculated policy decisions which are more beneficial to the environment. Recently, NASA and USAID have joined forces with the Regional Center for Mapping of Resources for Development (RCMRD) located in Nairobi, Kenya to utilize multiple NASA sensors such as TRMM, SRTM and MODIS to develop flood potential maps for the Lake Victoria Basin. The idea is to generate a flood forecasts and "nowcasts" that can be sent to the disaster management organizations of Uganda, Kenya, and Tanzania. Post flood event satellite imagery is becoming a common tool to assess the areas inundated by flooding. However, this work is unique undertaking by utilizing land imaging and atmospheric satellites to build credible flood potential maps. At same time, we are also studying the potential occurrence and spread of Rift Valley Fever disease based on the short term climate records and precipitation data. These activities require multi-nation coordination and agreements and multiple operational agencies within each respective country. It also requires credible in situ data such as precipitation, river flow rates and lake levels to further validate the global and regional Hood models and algorithms. This also requires a considerable amount of training and capacity building for the RCMRD experts who will help us validate the model results and eventually transition it for operational use. In a final analysis, Disaster management and humanitarian aid organizations need accurate and timely information for making decisions regarding deployment of relief teams and emergency supplies during major floods. Flood maps based on the use of satellite data have proven extremely valuable to such organizations for identifying the location, extent, and severity of these events. However, despite extraordinary efforts on the part of remote sensing data providers to rapidly deliver such maps, there is typically a delay of several days or even weeks from the on-set of flooding until such maps are available to the disaster management community. This paper summarizes efforts at NASA to address this problem through development of an integrated and automated process of a) flood forecasting b) flood detection, c) satellite data acquisition, d) rapid Hood mapping and distribution, and e) validation of Hood forecasting and detection products.

Habib, Shahid↗
NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Millimeter- and submillimeter-wave (mmWave, submm) radiometers provide significant information content on atmospheric water in liquid, ice, and vapor phases. Recent sensors, such as the Global Precipitation Measurement (GPM) or the Temporal Experiment for Storms and Tropical Systems Technology – Demonstration (TEMPEST-D), use mmWave bands to improve estimation of ice-phase precipitation, and future missions, such as the Atmosphere Observing System (AOS), will extend to submm to provide additional information on thinner ice clouds, linking clouds and precipitation and therefore elucidating the links between weather, climate, and the water cycle. To support the expanded use of mmWave/submm radiometry and exploit the available information content on condensed water mass, we demonstrate ice and liquid water path retrievals for NASA Goddard Space Flight Center's airborne radiometers the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) and the Configurable Scanning Submillimeter-wave Instrument/Radiometer (CoSSIR, formerly the Compact Scanning Submillimeter Imaging Radiometer). The analysis is based on data collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS) field campaign. A simulation study compares and contrasts retrievals for CoSMIR and CoSSIR, with CoSSIR demonstrating higher skill in ice retrievals, particularly for thin clouds, and the CoSMIR frequencies performing better for liquid. Additionally, we look at dual-polarized radiances observed by CoSMIR during the first two IMPACTS deployments to understand the polarization signatures induced by oriented hydrometeors. Results will be presented in the context of upcoming missions and sensors including AOS and the Ice Cloud Imager (ICI). We will describe the objectives for the expected first flight of the newly upgraded CoSSIR during the final IMPACTS deployment, and we will share novel science investigations we plan to undertake with CoSSIR's new capabilities. Popular Summary: Ice in clouds and falling snow is an important component of weather, climate, and water resources. To better use a new class of sensors that provide information on atmospheric ice, we developed an approach to measure ice clouds and falling snow using airborne data taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS), a field campaign to study winter storms. We look at the results for two similar instruments to understand how those differences affect these measurements of clouds and snow, and we further investigate the information the sensors can provide on properties of the clouds and snow.

Ian S Adams↗
NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Millimeter- and submillimeter-wave (mmWave, submm) radiometers provide significant information content on atmospheric water in liquid, ice, and vapor phases. Recent sensors, such as the Global Precipitation Measurement (GPM) or the Temporal Experiment for Storms and Tropical Systems Technology – Demonstration (TEMPEST-D), use mmWave bands to improve estimation of ice-phase precipitation, and future missions, such as the Atmosphere Observing System (AOS), will extend to submm to provide additional information on thinner ice clouds, linking clouds and precipitation and therefore elucidating the links between weather, climate, and the water cycle. To support the expanded use of mmWave/submm radiometry and exploit the available information content on condensed water mass, we demonstrate ice and liquid water path retrievals for NASA Goddard Space Flight Center's airborne radiometers the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) and the Configurable Scanning Submillimeter-wave Instrument/Radiometer (CoSSIR, formerly the Compact Scanning Submillimeter Imaging Radiometer). The analysis is based on data collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS) field campaign. A simulation study compares and contrasts retrievals for CoSMIR and CoSSIR, with CoSSIR demonstrating higher skill in ice retrievals, particularly for thin clouds, and the CoSMIR frequencies performing better for liquid. Additionally, we look at dual-polarized radiances observed by CoSMIR during the first two IMPACTS deployments to understand the polarization signatures induced by oriented hydrometeors. Results will be presented in the context of upcoming missions and sensors including AOS and the Ice Cloud Imager (ICI). We will describe the objectives for the expected first flight of the newly upgraded CoSSIR during the final IMPACTS deployment, and we will share novel science investigations we plan to undertake with CoSSIR's new capabilities. Popular Summary: Ice in clouds and falling snow is an important component of weather, climate, and water resources. To better use a new class of sensors that provide information on atmospheric ice, we developed an approach to measure ice clouds and falling snow using airborne data taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS), a field campaign to study winter storms. We look at the results for two similar instruments to understand how those differences affect these measurements of clouds and snow, and we further investigate the information the sensors can provide on properties of the clouds and snow.

Ian S Adams↗
NASA NTRS2011

International Space Station (ISS) Gas Logistics Planning in the Post Shuttle Era

Over its life the International Space Station (ISS) has received gas (nitrogen, oxygen, and air) from various sources. Nitrogen and oxygen are used in the cabin to maintain total pressure and oxygen partial pressures within the cabin. Plumbed nitrogen is also required to support on-board experiments and medical equipment. Additionally, plumbed oxygen is required to support medical equipment as well as emergency masks and most importantly EVA support. Gas are supplied to ISS with various methods and vehicles. Vehicles like the Progress and ATV deliver nitrogen (both as a pure gas and as air) and oxygen via direct releases into the cabin. An additional source of nitrogen and oxygen is via tanks on the ISS Airlock. The Airlock nitrogen and oxygen tanks can deliver to various users via pressurized systems that run throughout the ISS except for the Russian segment. Metabolic oxygen is mainly supplied via cabin release from the Elektron and Oxygen Generator Assembly (OGA), which are water electrolyzers. As a backup system, oxygen candles (Solid Fuel Oxygen Generators-SFOGs) supply oxygen to the cabin as well. In the past, a major source of nitrogen and oxygen has come from the Shuttle via both direct delivery to the cabin as well as to recharge the ISS Airlock tanks. To replace the Shuttle capability to recharge the ISS Airlock tanks, a new system was developed called Nitrogen/Oxygen Recharge System (NORS). NIORS consists of high pressure (7000 psi) tanks which recharge the ISS Airlock tanks via a blowdown fill for both nitrogen and oxygen. NORS tanks can be brought up on most logistics vehicles such as the HTV, COTS, and ATV. A proper balance must be maintained to insure sufficient gas resources are available on-orbit so that all users have the required gases via the proper delivery method (cabin and/or plumbed).

Leonard, Daniel J.↗
NASA NTRS2017

Current Safety Nets Within the U.S. National Airspace System

There are over 70,000 flights managed per day in the National Airspace System, with approximately 7,000 aircraft in the air over the United States at any given time. Operators of each of these flights would prefer to fly a user-defined “4D” trajectory (4DT), which includes arrival and departure times; preferred gates and runways at the airport; efficient, wind-optimal routes for departure, cruise and arrival phase of flight; and fuel efficient altitude profiles. To demonstrate the magnitude of this achievement a single flight from Los Angeles to Baltimore, accesses over 35 shared or “constrained” resources that are managed by roughly 30 air traffic controllers (at towers, approach control and en route sectors); along with traffic managers at 12 facilities, using over 22 different, independent automation system (including TBFM, ERAM, STARS, ASDE-X, FSM, TSD, GPWS, TCAS, etc.). In addition, dispatchers, ramp controllers and others utilize even more systems to manage each flight’s access to operator-managed resources. Flying an ideal 4DT requires successful coordination of all flight constraints among all flights, facilities, operators, pilots and controllers. Additionally, when conditions in the NAS change, the trajectories of one or more aircraft may need to be revised to avoid loss of flight efficiency, predictability, separation or system throughput. The Aviation Safety Network has released the 2016 airliner accident statistics showing a very low total of 19 fatal airliner accidents, resulting in 325 fatalities1. Despite several high profile accidents, the year 2016 turned out to be a very safe year for commercial aviation, Aviation Safety Network data show. Over the year 2016 the Aviation Safety Network recorded a total of 19 fatal airliner accidents [1], resulting in 325 fatalities. This makes 2016 the second safest year ever, both by number of fatal accidents as well as in terms of fatalities. In 2015 ASN recorded 16 accidents while in 2013 a total of 265 lives were lost. How can we keep it that way and not upset the apple cart by premature insertion of innovative technologies, functions, and procedures? In aviation, safety nets function as the last system defense against incidents and accidents. Current ground-based and airborne safety nets are well established and development to make them more efficient and reliable continues. Additionally, future air traffic control safety nets may emerge from new operational concepts.

Smith, Brian E.↗
NASA NTRS2022

A Robust Machine Learning Schema for Developing, Maintaining, and Disseminating Machine Learning Models

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of ML models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based modeling of material behavior at various length scales and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using ML techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus, effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train ML models and the defining model parameters and architectures within the Granta MI Platform. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in the prediction of material behavior, while following outlined best practices for effective data management. An effective schema for ML data and models can help prevent the recreation of virtual/real training data and surrogate models, help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Brandon L. Hearley↗