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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 NTRS2012

Achieving Accuracy Requirements for Forest Biomass Mapping: A Spaceborne Data Fusion Method for Estimating Forest Biomass and Lidar Sampling Error

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission (+/-20 Mg/ha or 20%, the greater of the two, for at least 80% of grid cells). A data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional-global extents. A general framework for mapping above ground live forest biomass density (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify contiguous areas (>0.5 ha) that are relatively homogenous in remote sensing metrics (forest patches). We used this image-derived data with simulated spaceborne LiDAR derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (LVIS) to compute AGB and estimate LiDAR sampling error for forest patches and 100 m, 250 m, 500 m, and 1 km grid cells. At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. First, this data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting. Second, a data fusion approach for estimating AGB using simulated spaceborne LiDAR with SAR and passive optical image combinations reduced forest AGB sampling errors 12%-38% from those where LiDAR is used with SAR or passive optical alone. In absolute terms, sampling errors were reduced from 14-40 Mg/ha to 11-28 Mg/ha across all grid scales and prediction methods, where minimum sampling errors were 11, 15, 18, and 22 Mg/ha for 1 km, 500 m, 250 m, and 100 m grid scales, respectively. Third, spaceborne global scale accuracy requirements were achieved whereby at least 80% of the grid cells at 100 m, 250 m, 500 m, and 1 km grid levels met AGB accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500 m and 250 m grid level, respectively..

LiDAR↗
NASA NTRS2017

Gaussian Mixture Models for Temporal Depth Fusion

Sensing the 3D environment of a moving robot is essential for collision avoidance. Most 3D sensors produce dense depth maps, which are subject to imperfections due to various environmental factors. Temporal fusion of depth maps is crucial to overcome those. Temporal fusion is traditionally done in 3D space with voxel data structures, but it can be approached by temporal fusion in image space, with potential benefits in reduced memory and computational cost for applications like reactive collision avoidance for micro air vehicles. In this paper, we present an efficient Gaussian Mixture Models based depth map fusion approach, introducing an online update scheme for dense representations. The environment is modeled from an ego-centric point of view, where each pixel is represented by a mixture of Gaussian inverse-depth models. Consecutive frames are related to each other by transformations obtained from visual odometry. This approach achieves better accuracy than alternative image space depth map fusion techniques at lower computational cost.

Matthies, Larry↗
NASA NTRS2005

A novel tiered sensor fusion approach for terrain characterization and safe landing assessment

This paper presents a novel tiered sensor fusion methodology for real-time terrain safety assessment. A combination of active and passive sensors, specifically, radar, lidar, and camera, operate in three tiers according to their inherent ranges of operation. Low-level terrain features (e.g. slope, roughness) and high-level terrain features (e.g. hills, craters) are integrated using principles of reasoning under uncertainty. Three methodologies are used to infer landing safety: Fuzzy Reasoning, Probabilistic Reasoning, and Evidential Reasoning. The safe landing predictions from the three fusion engines are consolidated in a subsequent decision fusion stage aimed at combining the strengths of each fusion methodology. Results from simulated spacecraft descents are presented and discussed.

fuzzy reasoning↗
NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗
NASA NTRSDate not supplied

Nuclear Fusion Space Propulsion Research, Experimentation, Theory Development, and Systems Analysis Efforts Led by the NASA Glenn Research Center (1994-2004)

This review paper summarizes work performed from 1994 to 2004 by a several interrelated government, academic, and industry teams led by the NASA Glenn Research Center. The nuclear fusion space propulsion system concept was predicated on a spherical torus reactor, which enabled manned missions to the outer planets in less than one year. Moderate thrust levels (1,000’s lbf)from direct nuclear fusion exhaust plasma via a magnetic nozzle enabled high thrust-to-weight. An entire vehicle conceptual design, including an artificial gravity crew habitat, was created by the NASA Glenn Research Center. The proof of concept experiment test article and facility upgrade was performed at the Ohio State University which also included staff from the Ohio Aerospace Institute and Science Applications International Corporation.The governing equations for the plasma physics theory of magnetic nozzle operation were derived by the Los Alamos National Laboratory. A preliminary investigation of a proof of concept test utilizing Coaxial Helicity Ejection as a means to supply plasma for propulsion at the National Spherical Torus Experiment reactor was outlined by the Princeton Plasma Physics Laboratory. An industry standard on nuclear fusion propulsion conceptual design was created by two AIAA teams. Despite extremely modest funding levels, significant progress was made advancing the state of the art.The result was a coordinated conceptual, theoretical, and experimental design effort to guide fusion space propulsion development.

Nuclear fusion↗
NASA NTRSDate not supplied

Lattice Confinement Fusion & Fast Fission for Space

Lattice Confinement Fusion (LCF) 1 • Fusion of hydrogen isotopes into helium isotopes • No tokamak magnets or laser power supplies • Nuclear fuel is confined and triggered within lattice • Nuclear reactions enhanced by electron screening • Extended Electrodynamics (EED) role • NASA published results in Physical Review C 2,3 • Locally hot but globally cold • Commercialized in 2025 to produce medical radioisotopes 4 Lattice Confinement Fusion Fast-Fission Hybrid Reactor • Fusion neutrons fission uranium, spent fuel rods or thorium • No enriched uranium, cleaner fission! • Demonstrated with US Navy and GEC • Supported by NASA STMD (NIAC) and NSF Application • LEO, Deep Space Power and High I sp Propulsion • (Terrestrial)

lattice confinement fusion↗
NASA NTRS1972

The emissivities of liquid metals at their fusion temperatures

A survey of the literature through 1969 shows an almost total lack of experimental emissivity data for metals in the liquid state. The emissivities for several transition metals and various other metals and compounds in the liquid state at their fusion temperatures have been determined. The technique used involves electromagnetic levitation-induction heating of the materials in an inert atmosphere. The brightness temperature of the liquid phase of the material is measured as the material is heated through fusion. Given a reliable value of the fusion temperature, which is available for most pure substances, one may readily calculate an emissivity for the liquid phase at the fusion temperatures. Even in cases where melting points are poorly known, the brightness temperatures are unique parameters, independent of the temperature scale and measured for a chemically defined system at a fixed point. Better emissivities may be recalculated as better melting point data become available.

Bonnell, D. W.↗
NASA NTRS1972

The emissivities of liquid metals at their fusion temperatures.

The emissivities for several transition metals and various other metals and compounds in the liquid state at their fusion temperatures have been determined in this laboratory. The technique used involves electromagnetic levitation-induction heating of the materials in an inert atmosphere. The brightness temperature of the liquid phase of the material is measured as the material is heated through fusion. Given a reliable value of the fusion temperature, which is available for most pure substances, one may readily calculate an emissivity for the liquid phase at the fusion temperature. Even in cases where melting points are poorly known, the brightness temperatures are unique parameters, independent of the temperature scale and measured for a chemically defined system at a fixed point.

Bonnell, D. W.↗
NASA NTRS1978

Evaluation of performance of select fusion experiments and projected reactors

The performance of NASA Lewis fusion experiments (SUMMA and Bumpy Torus) is compared with other experiments and that necessary for a power reactor. Key parameters cited are gain (fusion power/input power) and the time average fusion power, both of which may be more significant for real fusion reactors than the commonly used Lawson parameter. The NASA devices are over 10 orders of magnitude below the required powerplant values in both gain and time average power. The best experiments elsewhere are also as much as 4 to 5 orders of magnitude low. However, the NASA experiments compare favorably with other alternate approaches that have received less funding than the mainline experiments. The steady-state character and efficiency of plasma heating are strong advantages of the NASA approach. The problem, though, is to move ahead to experiments of sufficient size to advance in gain and average power parameters.

Miley, G. H.↗
NASA NTRS1991

Mars manned fusion spaceship

Fusion Propulsion has an enormous potential for space exploration in the near future. In the twenty-first century, a usable and efficient fusion rocket will be developed and in use. Because of the great distance between other planets and Earth, efficient use of time, fuel, and payload is essential. A nuclear spaceship would provide greater fuel efficiency, less travel time, and a larger payload. Extended missions would give more time for research, experiments, and data acquisition. With the extended mission time, a need for an artificial environment exists. The topics of magnetic fusion propulsion, living modules, artificial gravity, mass distribution, space connection, and orbital transfer to Mars are discussed. The propulsion system is a magnetic fusion reactor based on a tandem mirror design. This allows a faster, shorter trip time and a large thrust to weight ratio. The fuel proposed is a mixture of deuterium and helium-3. Helium-3 can be obtained from lunar mining. There will be minimal external radiation from the reactor resulting in a safe, efficient propulsion system.

Hedrick, James↗
NASA NTRS1991

Fusion energy for space missions in the 21st century: Executive summary

Future space missions were hypothesized and analyzed, and the energy source of their accomplishment investigated. The missions included manned Mars, scientific outposts to and robotic sample return missions from the outer planets and asteroids, as well as fly-by and rendezvous missions with the Oort Cloud and the nearest star, Alpha Centauri. Space system parametric requirements and operational features were established. The energy means for accomplishing missions where delta v requirements range from 90 km/sec to 30,000 km/sec (High Energy Space Mission) were investigated. The need to develop a power space of this magnitude is a key issue to address if the U.S. civil space program is to continue to advance as mandated by the National Space Policy. Potential energy options which could provide the propulsion and electrical power system and operational requirements were reviewed and evaluated. Fusion energy was considered to be the preferred option and was analyzed in depth. Candidate fusion fuels were evaluated based upon the energy output and neutron flux. Additionally, fusion energy can offer significant safety, environmental, economic, and operational advantages. Reactors exhibiting a highly efficient use of magnetic fields for space use while at the same time offering efficient coupling to an exhaust propellant or to a direct energy convertor for efficient electrical production were examined. Near term approaches were identified. A strategy that will produce fusion powered vehicles as part of the space transportation infrastructure was developed. Space program resources must be directed toward this issue as a matter of the top policy priority.

Schulze, Norman R.↗
NASA NTRS1992

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Schenker, Paul S.↗
NASA NTRS1992

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

Schenker, Paul S.↗
NASA NTRS1994

Fusion powered human transport to Mars (UWFR94)

In the future, two important technological dreams will have become reality: fusion will be a viable power source, and human settlement on Mars will be feasible, desirable, and even necessary. Merging these two concepts is especially attractive for the aerospace engineer because of the high specific power that will be possible with fusion (on the order 10 kW/kg). The UWFR94, a large, fusion-powered, human-transport ship, is designed to transport 100 passengers between earth and Mars in approximately thirty days. This relatively short transit time, which mitigates the need for artificial gravity, is made possible by a Polywell inertial electrostatic fusion reactor capable of 20 kW/kg. The mass of each reactor is 37 metric tons and the fuel used is (3)He-(3)He. The electricity generated drives the propulsion system, composed of nine ion thrusters and 780 tons of xenon propellant. The payload consists of three independent, identical cylinders housing the crew, and has a mass of approximately 400 tons. The aluminum cylinders' radius and length are 3 and 12 meters, respectively, with a thickness of 6 cm (15 cm in the solar flare safe rooms). Atmospheric reentry is avoided by constructing and repairing the UWFR94 in space, and by transferring crew and cargo to shuttle-like vehicles for transportation to the planet upon arrival.

Cappellari, John↗
NASA NTRS2001

Expression of the Acyl-Coenzyme A: Cholesterol Acyltransferase GFP Fusion Protein in Sf21 Insect Cells

The enzyme acyl-coenzyme A:cholesterol acyltransferase (ACAT) is an important contributor to the pathological expression of plaque leading to artherosclerosis n a major health problem. Adequate knowledge of the structure of this protein will enable pharmaceutical companies to design drugs specific to the enzyme. ACAT is a membrane protein located in the endoplasmic reticulum.t The protein has never been purified to homogeneity.T.Y. Chang's laboratory at Dartmouth College provided a 4-kb cDNA clone (K1) coding for a structural gene of the protein. We have modified the gene sequence and inserted the cDNA into the BioGreen His Baculovirus transfer vector. This was successfully expressed in Sf2l insect cells as a GFP-labeled ACAT protein. The advantage to this ACAT-GFP fusion protein (abbreviated GCAT) is that one can easily monitor its expression as a function of GFP excitation at 395 nm and emission at 509 nm. Moreover, the fusion protein GCAT can be detected on Western blots with the use of commercially available GFP antibodies. Antibodies against ACAT are not readily available. The presence of the 6xHis tag in the transfer vector facilitates purification of the recombinant protein since 6xHis fusion proteins bind with high affinity to Ni-NTA agarose. Obtaining highly pure protein in large quantities is essential for subsequent crystallization. The purified GCAT fusion protein can readily be cleaved into distinct GFP and ACAT proteins in the presence of thrombin. Thrombin digests the 6xHis tag linking the two protein sequences. Preliminary experiments have indicated that both GCAT and ACAT are expressed as functional proteins. The ultimate aim is to obtain large quantities of the ACAT protein in pure and functional form appropriate for protein crystal growth. Determining protein structure is the key to the design and development of effective drugs. X-ray analysis requires large homogeneous crystals that are difficult to obtain in the gravity environment of earth. Protein crystals grown in microgravity are often larger and have fewer defects than those grown on earth. The analysis of higher quality space-grown crystals will assist in structure-based drug design. We have successfully grown GCAT-infected Sf21 cells in both adhesion and suspension cultures. Expression levels of GCAT in cell lines such as Sf9 and High Five appear to be reduced. We intend to replicate GCAT expression in all three cell lines using the NASA rotating wall bioreactor which effectively duplicates a microgravity environment. The bioreactor itself could be launched to study the expression of the GFP and GCAT proteins in the actual microgravity environment achieved in orbit.

Mahtani, H. K.↗
NASA NTRS2001

Gene Fusion: A Genome Wide Survey

As a well known fact, organisms form larger and complex multimodular (composite or chimeric) and mostly multi-functional proteins through gene fusion of two or more individual genes which have independent evolution histories and functions. We call each of these components a module. The existence of multimodular proteins may improves the efficiency in gene regulation and in cellular functions, and thus may give the host organism advantages in adaptation to environments. Analysis of all gene fusions in present-day organisms should allow us to examine the patterns of gene fusion in context with cellular functions, to trace back the evolution processes from the ancient smaller and uni-functional proteins to the present-day larger and complex multi-functional proteins, and to estimate the minimal number of ancestor proteins that existed in the last common ancestor for all life on earth. Although many multimodular proteins have been experimentally known, identification of gene fusion events systematically at genome scale had not been possible until recently when large number of completed genome sequences have been becoming available. In addition, technical difficulties for such analysis also exist due to the complexity of this biological and evolutionary process. We report from this study a new strategy to computationally identify multimodular proteins using completed genome sequences and the results surveyed from 22 organisms with the data from over 40 organisms to be presented during the meeting. Additional information is contained in the original extended abstract.

Liang, Ping↗
NASA NTRS2001

Facility Monitoring: A Qualitative Theory for Sensor Fusion

Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

Figueroa, Fernando↗
NASA NTRS2004

Development of an Information Fusion System for Engine Diagnostics and Health Management

Aircraft gas-turbine engine data are available from a variety of sources including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data Fusion is the integration of data or information from multiple sources, to achieve improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This paper describes a basic PHM Data Fusion architecture being developed in alignment with the NASA C17 Propulsion Health Management (PHM) Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center (GRC), NASA Dryden Flight Research Center (DFRC) and Pratt & Whitney (P&W) have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion as applied to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This paper will provide a broad overview of this work, discuss some of the methodologies employed and give some illustrative examples.

Volponi, Allan J.↗