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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1991

Inferring vegetation characteristics using a knowledge-based system

A knowledge-based system for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input is developed. A portion of this system has been developed to discriminate between user-defined vegetation classes using spectral and directional reflectance relationships. This discrimination program was used to classify targets into user-defined ground cover and plant height classes. The program learns class descriptors from samples (both positive and negative) of spectral, directional reflectance data of natural surfaces (bare soils, natural vegetation, and agricultural vegetation). The system is designed to handle any combination of directional view angles. The explicit relationships used in the class descriptions include greater-than relationships between combinations of two view angles and maximum and minimum value relationships. The class descriptions are used to classify an unknown target using the same directional views. The program was tested by learning class descriptions of various categories of percent ground cover and vegetation height.

Kimes, D. S.↗

NASA NTRS2021

Planetary Boundary Layer Height Estimates From ICESat-2 and CATS Backscatter Measurements

The lowest layer of the atmosphere in which all human activity occurs is called the Planetary Boundary Layer (PBL). All physical interactions with the surface, such as heat and moisture transport, pollution dispersion and transport happen in this relatively shallow layer. The ability to understand and model the complex interactions that occur in the PBL is very important to air quality, weather prediction and climate modeling. A fundamental and physically important property of the PBL is its thickness or height. This work presents two methods to obtain global PBL height using satellite lidar data from the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) and the Cloud-Aerosol Transport System (CATS). The first method is a straightforward backscatter threshold technique and the second is a machine learning approach known as a Convolutional Neural Network. The PBL height retrievals from the two methods are compared with each other and with PBL height from the NASA GEOS MERRA-2 reanalysis. The lidar-retrieved PBL heights have a high degree of spatial correlation with the model heights but are generally higher over ocean (∼400 m) and over northern hemisphere high latitude regions (∼1,000 m). Over mid-latitude and tropical land areas, the satellite estimated PBL heights agree well with model mid-day estimates. This work demonstrates the feasibility of using satellite lidar backscatter measurements to obtain global PBL height estimates, as well as determining seasonal and regional variability of PBL height.

Stephen P Palm↗

NASA NTRS1985

Transport of trace species deduced from LIMS observations

One of the critical problems in the middle atmosphere at this time is understanding the interaction between atmospheric motions and photochemistry, and the way in which these two processes maintain the distributions of photochemically active species such as ozone. Recent work has shown that a great deal can be learned by considering the zonally averaged distributions and transports, i.e., working in the latitude-altitude plane. This 2-dimensional approach has been used in the past in Eulerian formation. Recent work (DUNKERTON, 1978) has shown that formulating the transport problems in terms of the residual mean circulation, which has similarity to the Lagrangian mean motion, results in a more physical picture of the way in which the transport takes place. Here, data from the Limb Infrared Monitor of the Stratosphere (LIMB) experiment are used to investigate how well the residual mean formulation works with real data, in the sense of asking how well the predicted ozone changes match those in regions of the lower stratosphere in which chemical changes may be neglected. This allows a test of the approximations that are made, and of the strengths and weaknesses of this approach to transport calculation.

Gille, J. C.↗

NASA NTRS1989

SSME fault monitoring and diagnosis expert system

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

Ali, Moonis↗

NASA NTRS2010

Virtualization in the Operations Environments

Virtualization provides the opportunity to continue to do "more with less"---more computing power with fewer physical boxes, thus reducing the overall hardware footprint, power and cooling requirements, software licenses, and their associated costs. This paper explores the tremendous advantages and any disadvantages of virtualization in all of the environments associated with software and systems development to operations flow. It includes the use and benefits of the Intelligent Platform Management Interface (IPMI) specification, and identifies lessons learned concerning hardware and network configurations. Using the Huntsville Operations Support Center (HOSC) at NASA Marshall Space Flight Center as an example, we demonstrate that deploying virtualized servers as a means of managing computing resources is applicable and beneficial to many areas of application, up to and including flight operations.

Pitts, Lee↗

NASA NTRS2010

Utilization of Virtual Server Technology in Mission Operations

Felton, Larry↗

NASA NTRS1998

Teaching Soil Science in Primary and Secondary Schools

Earth's thin layer of soil is a fragile resource, made up of minerals, organic materials, air, water, and billions of living organisms. Soils plays a variety of critical roles that sustain life on Earth. If we think about soil, we tend to see it first as the source of most of the food we eat and the fibers we use, such as wood and cotton. Few students realize that soils also provide the key ingredients to many of the medicines (including antibiotics), cosmetics, and dyes that we use. Fewer still understand the importance of soils in integrating, controlling, and regulating the movement of air, water, materials, and energy between the hydrosphere, lithosphere, atmosphere, and biosphere. Because soil sustains life, it offers both a context and a natural laboratory for investigating these interactions. The enclosed poster, which integrates soil profiles with typical landscapes in which soils form, can also help students explore the interrelationships of Earth systems and gain an understanding of our soil resources. The poster, produced jointly by the American Geological Institute and the Soil Science Society of America, aims to increase awareness of the importance of soil, as does the GLOBE (Global Learning and Observations To Benefit the Environment) Program. Vice President Al Gore instituted the GLOBE Program on Earth Day of 1993 to increase environmental awareness of individuals throughout the world, contribute to a better scientific understanding of the Earth, and help all students reach higher levels of achievement in science and mathematics. GLOBE functions as a partnership between scientists, students, and teachers in which scientists design protocols for specific measurements they need for their research that can be performed by K-12 students. Teachers are trained in the GLOBE protocols and teach them to their students. Students make the measurements, enter data via the Internet to a central data archive, and the data becomes available to scientists and the general community. Students benefit by having a "hands-on"experience in science, math, and technology, using their local environment as a learning laboratory, as well as contact with scientists and other students around the world. Soil investigations have become an essential component of GLOBE. The protocols that have been developed so far within the GLOBE program include GPS Location, Atmosphere/Climate, Soil Characterization, Soil Moisture and Temperature, Land Cover/Biometry, Hydrology, and Satellite Image Classification. For the GLOBE Soil Characterization Protocol, students explore the physical. chemical, and morphological properties of the soil at their study site. They are asked to dig a pit or use an auger to about 1 meter at at least 2 sites.

Levine, Elissa R.↗

NASA NTRS2017

Near Earth Asteroid Scout Solar Sail Engineering Development Unit Test Suite

The Near Earth Asteroid (NEA) Scout project is a 6U reconnaissance mission to investigate a near Earth asteroid utilizing an 86m(sub 2) solar sail as the primary propulsion system. This will be the largest solar sail NASA has launched to date. NEA Scout is currently manifested on the maiden voyage of the Space Launch System in 2018. In development of the solar sail subsystem, design challenges were identified and investigated for packaging within a 6U form factor and deployment in cis-lunar space. Analysis was able to capture understanding of thermal, stress, and dynamics of the stowed system as well as mature an integrated sail membrane model for deployed flight dynamics. Full scale system testing on the ground is the optimal way to demonstrate system robustness, repeatability, and overall performance on a compressed flight schedule. To physically test the system, the team developed a flight sized engineering development unit with design features as close to flight as possible. The test suite included ascent vent, random vibration, functional deployments, thermal vacuum, and full sail deployments. All of these tests contributed towards development of the final flight unit. This paper will address several of the design challenges and lessons learned from the NEA Scout solar sail subsystem engineering development unit. Testing on the component level all the way to the integrated subsystem level. From optical properties of the sail material to fold and spooling the single sail, the team has developed a robust deployment system for the solar sail. The team completed several deployments of the sail system in preparation for flight at half scale (4m) and full scale (6.8m): boom only, half scale sail deployment, and full scale sail deployment. This paper will also address expected and received test results from ascent vent, random vibration, and deployment tests.

Lockett, Tiffany Russell↗

NASA NTRSDate not supplied

Space Suit Portable Life Support System Oxygen Regulator History, Development, & Testing Results

An oxygen regulator has been in development for the Exploration Extravehicular Mobility Unit (xEMU) Portable Life Support System (PLSS). The regulator provides the necessary oxygen pressure control for the crew member during prebreathe, Extra-Vehicular Activity (EVA), post EVA airlock operations, and Decompression Sickness (DCS) treatment. It has been over four decades since a new spacesuit oxygen regulator has been designed. The regulator and EMU that is presently used on the International Space Station (ISS) was developed for the space shuttle program without any significant changes made throughout its service life. The xEMU spacesuit oxygen regulator is based on the previous EMU Secondary Oxygen Pack (SOP). The new design integrates numerous improvements and changes including an innovative approach to regulator architecture, a more robust first stage pressure sensing mechanism, digital actuation control, and electronic pressure sensing. These upgrades replace manual control linkages, physical gauges, and enable infinitely variable pressure set points. The new setpoints can decrease prebreathe time and make in suit DCS treatment possible. Throughout its four iterations design concerns have been addressed, safety features have been added, and the envelope of the regulator designed to fit inside the xEMU PLSS package. This paper will review the history, design, testing, and lessons learned during the development of the xEMU PLSS Oxygen Regulator.

Ryan Eric Ogilvie↗

NASA NTRSDate not supplied

Space Suit Portable Life Support System (PLSS) Oxygen Regulator History, Development, & Testing Results

Ryan Ogilvie↗

NASA NTRS1992

Workshop on the Physics and Chemistry of Magma Oceans from 1 Bar to 4 Mbar

Evidence for the existence of magma oceans is discussed in great detail, and among the many new items introduced were high-pressure phase equilibrium experiments, calculations of depth of impact-produced melting, models incorporating crystal growth rates with degree of crystallinity and convection, and models of hard turbulent convection. It was agreed that before we can point to some present-day observable parameters and confidently establish the existence of magma oceans, we must learn much more about their phase equilibria and solidification dynamics.

Agee, Carl B.↗

NASA NTRS2003

The autonomous sciencecraft constellations

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in a hybrid multi-layer control architecture to enable a virtual spacecraft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Autonomous Sciencecraft Experiment ASE AI technolo↗

NASA NTRS2002

Spacecraft autonomy using onboard processing for a SAR constellation mission

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in a hybrid multi-layer control architecture to enable a virtual spacecruft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Autonomous Sciencecraft Experiment ASE virtual spa↗

NASA NTRS2011

Fermi-LAT Gamma-ray Bursts and Insight from Swift

A new revolution in GRB observation and theory has begun over the last 3 years since the launch of the Fermi gamma-ray space telescope. The new window into high energy gamma-rays opened by the Fermi-LAT is providing insight into prompt emission mechanisms and possibly also afterglow physics. The LAT detected GRBs appear to be a new unique subset of extremely energetic and bright bursts. In this talk I will discuss the context and recent discoveries from these LAT GRBs and the large database of broadband observations collected by Swift over the last 7 years and how through comparisons between the Swift, GBM, and LAT GRB samples, we can learn about the unique characteristics and relationships between each population.

Racusin, Judith L.↗

NASA NTRS2011

How I Learned to Stop Worrying and Love the SWCX Emission

In the last twenty years solar wind change exchange (SWCX) X-ray emission has gone from a significant and irritating background component of unknown origin for astrophysical observations to a field of study in its own right. On one hand, it provides an uncertain offset to observations of extended astrophysical objects and the diffuse X-ray background, and severely compromises the interpretation of many results. On the other hand, SWCX emission has the potential to shed light on physical phenomena in the near-Earth environment and the solar system. In addition, charge exchange emission may prove significant in many other areas of astrophysical diffuse X-ray emission such as supernova remnants. I will present an historical background from the perspective of studying the diffuse X-ray background, cover a variety of SWCX observations and implications, and discuss the realm of possible research and practical applications based on SWCX emission

Snowden, Steven↗

NASA NTRS1990

Fault diagnosis

The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to examine pilot mental models of the aircraft subsystems and their use in diagnosis tasks. Future research plans include piloted simulation evaluation of the diagnosis decision aiding concepts and crew interface issues. Information is given in viewgraph form.

Abbott, Kathy↗

NASA NTRS2002

Enhancing Science Teacher Training Using Water Resources and GLOBE

Heritage College, located on the Yakama Indian Reservation in south central Washington state, serves a multicultural, underserved, rural population and trains teachers to staff the disadvantaged school districts on and surrounding the reservation. In-service teachers and pre-service teachers in the area show strength in biology but have weak backgrounds in chemistry and mathematics. We are addressing this problem by providing a 2-year core of courses for 3 groups of 25 students (15 pre-service and 10 in-service teachers) using GLOBE to teach integrated physical science and mathematics. At the conclusion of the program, the students will qualify for science certification by Washington State. Water resources are the focal point of the curriculum because it is central to life in our desert area. The lack or excess of water, its uses, quality and distribution is being studied by using GIS, remote sensing and historical records. Students are learning the methodology to incorporate scientific protocols and data into all aspects of their future teaching curriculum. In addition, in each of the three years of the project, pre-service teachers attended a seminar series during the fall semester with presentations by collaborators from industry, agriculture, education and government agencies. Students used NASA educational materials in the presentations that they gave at the conclusion of the seminar series. All pre- and in-service teachers continue to have support via a local web site for Heritage College GLOBE participants.

Falco, James W.↗

NASA NTRS2021

Optimal Experimental Design With Fast Neural Network Surrogate Models

Designing optimal experiments minimizes the uncertainty of results and maximizes the efficient use of resources. Herein, machine learning surrogate models and the approximate coordinate exchange (ACE) algorithm are used to determine optimum experimental designs over large or arbitrarily restrictive design spaces. Optimal experimental design is particularly salient in materials science where experiments are expensive and material properties must often be inferred indirectly. The proposed framework is demonstrated by finding optimal experiments with which the hidden constituent properties of composite materials can be most efficiently inferred from observable experimental outcomes. The optimum experimental design is given by an information-theoretic criteria, which maximizes the conditional mutual information between the hidden properties and the expected experimental outcomes. To perform tractable optimization a neural network is trained as a surrogate model to mimic a physics based simulation, which can calculate the expected experimental outcome based on a candidate experimental design and sampled constituent properties. The ACE algorithm is used to optimize over large design spaces with many tests and controlled parameters where an exhaustive search would be intractable even with the surrogate model. Using this approach, optimal experimental designs that are consistent with those produced by heuristic knowledge and established best practices are found; then optimal designs in larger design spaces where heuristic knowledge is unavailable are examined.

machine learning↗