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At least 19 records

Fusion Propulsion Z-Pinch Engine Concept

Fusion-based nuclear propulsion has the potential to enable fast interplanetary transportation. Due to the great distances between the planets of our solar system and the harmful radiation environment of interplanetary space, high specific impulse (Isp) propulsion in vehicles with high payload mass fractions must be developed to provide practical and safe vehicles for human spaceflight missions. The Z-Pinch dense plasma focus method is a Magneto-Inertial Fusion (MIF) approach that may potentially lead to a small, low cost fusion reactor/engine assembly1. Recent advancements in experimental and theoretical understanding of this concept suggest favorable scaling of fusion power output yield 2. The magnetic field resulting from the large current compresses the plasma to fusion conditions, and this process can be pulsed over short timescales (10(exp -6 sec). This type of plasma formation is widely used in the field of Nuclear Weapons Effects testing in the defense industry, as well as in fusion energy research. A Decade Module 2 (DM2), approx.500 KJ pulsed-power is coming to the RSA Aerophysics Lab managed by UAHuntsville in January, 2012. A Z-Pinch propulsion concept was designed for a vehicle based on a previous fusion vehicle study called "Human Outer Planet Exploration" (HOPE), which used Magnetized Target Fusion (MTF) 3 propulsion. The reference mission is the transport of crew and cargo to Mars and back, with a reusable vehicle.

Miernik, J.↗

Z-Pinch Pulsed Plasma Propulsion Technology Development

Fusion-based propulsion can enable fast interplanetary transportation. Magneto-inertial fusion (MIF) is an approach which has been shown to potentially lead to a low cost, small reactor for fusion break even. The Z-Pinch/dense plasma focus method is an MIF concept in which a column of gas is compressed to thermonuclear conditions by an axial current (I approximates 100 MA). Recent advancements in experiments and the theoretical understanding of this concept suggest favorable scaling of fusion power output yield as I(sup 4). This document presents a conceptual design of a Z-Pinch fusion propulsion system and a vehicle for human exploration. The purpose of this study is to apply Z-Pinch fusion principles to the design of a propulsion system for an interplanetary spacecraft. This study took four steps in service of that objective; these steps are identified below. 1. Z-Pinch Modeling and Analysis: There is a wealth of literature characterizing Z-Pinch physics and existing Z-Pinch physics models. In order to be useful in engineering analysis, simplified Z-Pinch fusion thermodynamic models are required to give propulsion engineers the quantity of plasma, plasma temperature, rate of expansion, etc. The study team developed these models in this study. 2. Propulsion Modeling and Analysis: While the Z-Pinch models characterize the fusion process itself, propulsion models calculate the parameters that characterize the propulsion system (thrust, specific impulse, etc.) The study team developed a Z-Pinch propulsion model and used it to determine the best values for pulse rate, amount of propellant per pulse, and mixture ratio of the D-T and liner materials as well as the resulting thrust and specific impulse of the system. 3. Mission Analysis: Several potential missions were studied. Trajectory analysis using data from the propulsion model was used to determine the duration of the propulsion burns, the amount of propellant expended to complete each mission considered. 4. Vehicle Design: To understand the applicability of Z-Pinch propulsion to interplanetary travel, it is necessary to design a concept vehicle that uses it -- the propulsion system significantly impacts the design of the electrical, thermal control, avionics and structural subsystems of a vehicle. The study team developed a conceptual design of an interplanetary vehicle that transports crew and cargo to Mars and back and can be reused for other missions. Several aspects of this vehicle are based on a previous crewed fusion vehicle study -- the Human Outer Planet Exploration (HOPE) Magnetized Target Fusion (MTF) vehicle. Portions of the vehicle design were used outright and others were modified from the MTF design in order to maintain comparability.

Polsgrove, Tara↗

Z-Pinch Magneto-Inertial Fusion Propulsion Engine Design Concept

Fusion-based nuclear propulsion has the potential to enable fast interplanetary transportation. Due to the great distances between the planets of our solar system and the harmful radiation environment of interplanetary space, high specific impulse (Isp) propulsion in vehicles with high payload mass fractions must be developed to provide practical and safe vehicles for human spaceflight missions. Magneto-Inertial Fusion (MIF) is an approach which has been shown to potentially lead to a low cost, small fusion reactor/engine assembly (1). The Z-Pinch dense plasma focus method is an MIF concept in which a column of gas is compressed to thermonuclear conditions by an estimated axial current of approximately 100 MA. Recent advancements in experiments and the theoretical understanding of this concept suggest favorable scaling of fusion power output yield as I(sup 4) (2). The magnetic field resulting from the large current compresses the plasma to fusion conditions, and this is repeated over short timescales (10(exp -6) sec). This plasma formation is widely used in the field of Nuclear Weapons Effects (NWE) testing in the defense industry, as well as in fusion energy research. There is a wealth of literature characterizing Z-Pinch physics and existing models (3-5). In order to be useful in engineering analysis, a simplified Z-Pinch fusion thermodynamic model was developed to determine the quantity of plasma, plasma temperature, rate of expansion, energy production, etc. to calculate the parameters that characterize a propulsion system. The amount of nuclear fuel per pulse, mixture ratio of the D-T and nozzle liner propellant, and assumptions about the efficiency of the engine, enabled the sizing of the propulsion system and resulted in an estimate of the thrust and Isp of a Z-Pinch fusion propulsion system for the concept vehicle. MIF requires a magnetic nozzle to contain and direct the nuclear pulses, as well as a robust structure and radiation shielding. The structure, configuration, and materials of the nozzle must meet many severe requirements. The configuration would focus, in a conical manner, the Deuterium-Tritium (D-T) fuel and Lithium-6/7 liner fluid to meet at a specific point that acts as a cathode so the Li-6 can serve as a current return path to complete the circuit. In addition to serving as a current return path, the Li liner also serves as a radiation shield. The advantage to this configuration is the reaction between neutrons and Li-6 results in the production of additional Tritium, thus adding further fuel to the fusion reaction and boosting the energy output. To understand the applicability of Z-Pinch propulsion to interplanetary travel, it is necessary to design a concept vehicle that uses it. The propulsion system significantly impacts the design of the electrical, thermal control, avionics, radiation shielding, and structural subsystems of a vehicle. The design reference mission is the transport of crew and cargo to Mars and back, with the intention that the vehicle be reused for other missions. Several aspects of this vehicle are based on a previous crewed fusion vehicle study called Human Outer Planet Exploration (HOPE), which employed a Magnetized Target Fusion (MTF) propulsion concept. Analysis of this propulsion system concludes that a 40-fold increase of Isp over chemical propulsion is predicted. This along with a greater than 30% predicted payload mass fraction certainly warrants further development of enabling technologies. The vehicle is designed for multiple interplanetary missions and conceivably may be suited for an automated one-way interstellar voyage.

Miernik, Janie H.↗

A scale space feature based registration technique for fusion of satellite imagery

Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

Raghavan, Srini↗

Data Fusion With Uncertainty Quantification for Sub-City-Scale Air Quality Assessment and Forecasting

Many information sources can support air quality assessment and forecasting, including atmospheric chemistry model outputs, satellite retrievals of column chemical and aerosol constituents, and surface-based air quality monitoring data from both regulatory and low-cost instruments. Systematic integration of these data sources provides a major opportunity to improve understanding and management of air quality, but also presents technical barriers, especially in resource- and data-constrained settings in the Global South. This presentation describes a data fusion system, currently under development using the Google Earth Engine platform, which aims to integrate the information sources listed above to support comprehensive sub-city-scale assessment and management of air quality. Furthermore, the data fusion framework includes provisions for the quantification of uncertainties in the resulting fused estimates based on the variability of and among the input data sources. These capabilities will allow air quality managers to better understand their local air quality situation, including relative confidence in the fused estimates for different constituents, locations, and times, leading to better informed air quality management decisions. This presentation covers the underlying methodology of the data fusion and uncertainty quantification approaches, provides an update on the status of its implementation, and presents early qualitative and quantitative results.

Carl Malings↗

Channel Wall Nozzle Manufacturing Technology Advancements for Liquid Rocket Engines

A regeneratively-cooled nozzle is a critical component for expansion of the hot gases to enable high temperature and performance liquid rocket engines systems. Channel wall nozzles are a design solution used across the propulsion industry as a simplified method to fabricate the nozzle structure with internal coolant passages. The scale and complexity of the channel wall nozzle (CWN) design is challenging to fabricate leading to extended lead times and higher costs. Some of these challenges include: 1) unique and high temperature materials, 2) Tight tolerances during manufacturing and assembly to contain high pressure propellants, 3) thin-walled features to maintain adequate wall temperatures, and 4) Unique manufacturing process operations and tooling. The United States (U.S.) National Aeronautics and Space Administration (NASA) along with U.S. specialty manufacturing vendors are maturing modern fabrication techniques to reduce complexity and decrease costs associated with channel wall nozzle manufacturing technology. Additive Manufacturing (AM) is one of the key technology advancements being evaluated for channel wall nozzles. Much of additive manufacturing for propulsion components has focused on powder bed fusion, but the scale is not yet feasible for application to large scale nozzles. NASA is evolving directed energy deposition (DED) techniques for nozzles including arc-based deposition, blown powder deposition, and Laser Wire Direct Closeout (LWDC). There are different approaches being considered for fabrication of the nozzle and each of these DED processes offer unique process steps for rapid fabrication. The arc-based and blown powder deposition techniques are being used for the forming of the CWN liner. A variety of materials are being demonstrated including Inconel 625, Haynes 230, JBK-75, and NASA HR-1. The blown powder DED process is also being demonstrated for forming an integral channel nozzle in a single operation in similar materials. The LWDC process is a method for closing out the channels within the liner and forming the structural jacket using a localized laser wire deposition technique. Identical materials mentioned above have been used for this process in addition to bimetallic closeout (C-18150–SS347, and C-18150–Inconel 625). NASA has completed process development, material characterization, and hot-fire testing on a variety of these channel wall nozzle fabrication techniques. This paper will present an overview of the various processes and materials being evaluated and the results from the hot-fire testing. Future development and technology focus areas will also be discussed relative to channel wall nozzle manufacturing.

Gradl, Paul R.↗

Spatial Variability of Barrow-Area Shore-Fast Sea Ice and Its Relationships to Passive Microwave Emissivity

Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10,19, and 37 GHz. This depolarization .would yield overestimates of total ice concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity.

Maslanik, J. A.↗

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗

Additive Manufacturing Model-Based Process Metrics: Reduced Order Modeling of the Laser Powder Bed Fusion Process

The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. In this work, we describe a fully parallel reduced order modeling approach that has been developed to evaluate the evolution of AM processes, termed the AM moment measure method. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology and terminology of the approach will be described, and computed build maps will be calculated and compared for various laser powder bed fusion (LPBF) builds of Ti-6Al-4V. Such comparative results develop understanding of how the sequential process actions can affect the LPBF-AM build quality and microstructure variability.

Laser Powder Bed Fusion↗

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P < 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P < 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Yu, Yifan↗

Data Fusion and Mining Techniques to Map Water Use and Drought across Spatial and Temporal Scales

As the world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor (in this case, initially MODIS with a planned transition to VIIRS) rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. This presentation will focus on global applications for mapping water use and drought using data mining and data fusion across spatial scales extending from 5-km to 30-m “field-scale” estimates.

Christopher Hain↗

Helium destruction and gamma-ray line emission in accreting neutron stars

The prevalent gamma-ray production channel of a neutron star - emission of 2.2-MeV photons from neutron-proton recombination - is reconsidered. The 2.2-MeV gamma-ray line flux and Compton-scattered continuum are calculated. The flux of gravitationally redshifted 2.2-MeV photons from the brightest accreting X-ray source Scorpius X-1 is about 10 exp -6 gamma/sq cm s, a factor of 20 below the sensitivities on the Compton Gamma-Ray Observatory. The destruction of accreted He-4 leads to significant abundances of lighter elements (D, H-3, He-3) in the upper atmosphere, which are determined. The destroyed He-4 is reformed through fusion reactions a few scale heights beneath the photosphere, and thus does not hamper H-ray bursts.

Bildsten, Lars↗

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↗

Principles of Directed Energy Deposition for Aerospace Applications

Metal Additive Manufacturing is changing how components are fabricated for rocket propulsion and aerospace applications. Many additive manufacturing technologies are evolving, and active research is being conducted across academia, industry, and government to advance processes, materials, design, post-processing and applications. While much focus has been on Laser Powder Bed Fusion (LPBF) techniques, several large-scale techniques are also rapidly evolving using directed energy deposition (DED).

Additive Manufacturing↗