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At least 325 records · Page 18

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DOE OSTI2014

SU-E-T-455: Characterization of 3D Printed Materials for Proton Beam Therapy

Purpose: The widespread availability of low cost 3D printing technologies provides an alternative fabrication method for customized proton range modifying accessories such as compensators and boluses. However the material properties of the printed object are dependent on the printing technology used. In order to facilitate the application of 3D printing in proton therapy, this study investigated the stopping power of several printed materials using both proton pencil beam measurements and Monte Carlo simulations. Methods: Five 3–4 cm cubes fabricated using three 3D printing technologies (selective laser sintering, fused-deposition modeling and stereolithography) from five printers were investigated. The cubes were scanned on a CT scanner and the depth dose curves for a mono-energetic pencil beam passing through the material were measured using a large parallel plate ion chamber in a water tank. Each cube was measured from two directions (perpendicular and parallel to printing plane) to evaluate the effects of the anisotropic material layout. The results were compared with GEANT4 Monte Carlo simulation using the manufacturer specified material density and chemical composition data. Results: Compared with water, the differences from the range pull back by the printed blocks varied and corresponded well with the material CT Hounsfield unit. The measurement results were in agreement with Monte Carlo simulation. However, depending on the technology, inhomogeneity existed in the printed cubes evidenced from CT images. The effect of such inhomogeneity on the proton beam is to be investigated. Conclusion: Printed blocks by three different 3D printing technologies were characterized for proton beam with measurements and Monte Carlo simulation. The effects of the printing technologies in proton range and stopping power were studied. The derived results can be applied when specific devices are used in proton radiotherapy.

07 ISOTOPE AND RADIATION SOURCES↗

NASA NTRS1993

Objective determination of image end-members in spectral mixture analysis

Spectral mixture analysis was shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. The essence of the first phase of the approach is to determine a set of image end-members that best account for the spectral variance in an image cube within a constrained, linear least squares mixing model. The selection of the image end-member is usually achieved using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. The problem of image end-member determination was approached objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Tompkins, Stefanie↗

NASA NTRS1993

Objective determination of image end-members in spectral mixture analysis of AVIRIS data

Spectral mixture analysis has been shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. Applications of AVIRIS data have ranged from mapping soils and bedrock to ecosystem studies. During the first phase of the approach, a set of end-members are selected from an image cube (image end-members) that best account for its spectral variance within a constrained, linear least squares mixing model. These image end-members are usually selected using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. We approach the problem of image end-member determination objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Tompkins, Stefanie↗

DOE OSTI2017

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1992

Quantitative image processing in fluid mechanics

The current status of digital image processing in fluid flow research is reviewed. In particular, attention is given to a comprehensive approach to the extraction of quantitative data from multivariate databases and examples of recent developments. The discussion covers numerical simulations and experiments, data processing, generation and dissemination of knowledge, traditional image processing, hybrid processing, fluid flow vector field topology, and isosurface analysis using Marching Cubes.

Hesselink, Lambertus↗

NASA NTRS2000

Effect of Crystal Orientation on Analysis of Single-Crystal, Nickel-Based Turbine Blade Superalloys

High-cycle fatigue-induced failures in turbine and turbopump blades is a pervasive problem. Single-crystal nickel turbine blades are used because of their superior creep, stress rupture, melt resistance, and thermomechanical fatigue capabilities. Single-crystal materials have highly orthotropic properties making the position of the crystal lattice relative to the part geometry a significant and complicating factor. A fatigue failure criterion based on the maximum shear stress amplitude on the 24 octahedral and 6 cube slip systems is presented for single-crystal nickel superalloys (FCC crystal). This criterion greatly reduces the scatter in uniaxial fatigue data for PWA 1493 at 1,200 F in air. Additionally, single-crystal turbine blades used in the Space Shuttle main engine high pressure fuel turbopump/alternate turbopump are modeled using a three-dimensional finite element (FE) model. This model accounts for material orthotrophy and crystal orientation. Fatigue life of the blade tip is computed using FE stress results and the failure criterion that was developed. Stress analysis results in the blade attachment region are also presented. Results demonstrate that control of crystallographic orientation has the potential to significantly increase a component's resistance to fatigue crack growth without adding additional weight or cost.

Swanson, G. R.↗

DOE OSTI2017

Blind Millimeter Line Emitter Search using ALMA Data Toward Gravitational Lensing Clusters

We present the results of a blind millimeter line emitter search using ALMA Band 6 data with a single-frequency tuning toward four gravitational lensing clusters (RXJ1347.5−1145, Abell S0592, MACS J0416.1−2403, and Abell 2744). We construct 3D signal-to-noise ratio (S/N) cubes with 60 and 100 MHz binning, and search for millimeter line emitters. We do not detect any line emitters with a peak S/N > 5, although we do find a line emitter candidate with a peak S/N ≃ 4.5. These results provide upper limits to the CO(3−2), CO(4−3), CO(5−4), and [C ii] luminosity functions at z ≃ 0.3, 0.7, 1.2, and 6, respectively. Because of the magnification effect of gravitational lensing clusters, the new data provide the first constraints on the CO and [C ii] luminosity functions at unprecedentedly low luminosity levels, i.e., down to ≲10{sup −3} – 10{sup −1} Mpc{sup −3} dex{sup −1} at L{sub CO}{sup ′}∼10{sup 8}--10{sup 10} K km s{sup −1} pc{sup 2} and ≲10{sup −3}–10{sup −2} Mpc{sup −3} dex{sup −1} at L{sub [CII]}∼10{sup 8}--10{sup 10} L{sub ⊙}, respectively. Although the constraints to date are not yet stringent, we find that the evolution of the CO and [C ii] luminosity functions are broadly consistent with the predictions of semi-analytical models. This study demonstrates that the wide observations with a single-frequency tuning toward gravitational lensing clusters are promising for constraining the CO and [C ii] luminosity functions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Number series of atoms, interatomic bonds and interface bonds defining zinc-blende nanocrystals as function of size, shape and surface orientation: Analytic tools to interpret solid state spectroscopy data

Semiconductor nanocrystals (NCs) experience stress and charge transfer by embedding materials or ligands and impurity atoms. In return, the environment of NCs experiences a NC stress response which may lead to matrix deformation and propagated strain. Up to now, there is no universal gauge to evaluate the stress impact on NCs and their response as a function of NC size d{sub NC}. I deduce geometrical number series as analytical tools to obtain the number of NC atoms N{sub NC}(d{sub NC}[i]), bonds between NC atoms N{sub bnd}(d{sub NC}[i]) and interface bonds N{sub IF}(d{sub NC}[i]) for seven high symmetry zinc-blende (zb) NCs with low-index faceting: {001} cubes, {111} octahedra, {110} dodecahedra, {001}-{111} pyramids, {111} tetrahedra, {111}-{001} quatrodecahedra and {001}-{111} quadrodecahedra. The fundamental insights into NC structures revealed here allow for major advancements in data interpretation and understanding of zb- and diamond-lattice based nanomaterials. The analytical number series can serve as a standard procedure for stress evaluation in solid state spectroscopy due to their deterministic nature, easy use and general applicability over a wide range of spectroscopy methods as well as NC sizes, forms and materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1995

Implementation and Characterization of Three-Dimensional Particle-in-Cell Codes on Multiple-Instruction-Multiple-Data Massively Parallel Supercomputers

A three-dimensional electrostatic particle-in-cell (PIC) plasma simulation code has been developed on coarse-grain distributed-memory massively parallel computers with message passing communications. Our implementation is the generalization to three-dimensions of the general concurrent particle-in-cell (GCPIC) algorithm. In the GCPIC algorithm, the particle computation is divided among the processors using a domain decomposition of the simulation domain. In a three-dimensional simulation, the domain can be partitioned into one-, two-, or three-dimensional subdomains ("slabs," "rods," or "cubes") and we investigate the efficiency of the parallel implementation of the push for all three choices. The present implementation runs on the Intel Touchstone Delta machine at Caltech; a multiple-instruction-multiple-data (MIMD) parallel computer with 512 nodes. We find that the parallel efficiency of the push is very high, with the ratio of communication to computation time in the range 0.3%-10.0%. The highest efficiency (> 99%) occurs for a large, scaled problem with 64(sup 3) particles per processing node (approximately 134 million particles of 512 nodes) which has a push time of about 250 ns per particle per time step. We have also developed expressions for the timing of the code which are a function of both code parameters (number of grid points, particles, etc.) and machine-dependent parameters (effective FLOP rate, and the effective interprocessor bandwidths for the communication of particles and grid points). These expressions can be used to estimate the performance of scaled problems--including those with inhomogeneous plasmas--to other parallel machines once the machine-dependent parameters are known.

Lyster, P. M.↗

NASA NTRS1998

Coronagraphic Observations of the Lunar Sodium Exosphere Near the Lunar Surface

The sodium exosphere of the Moon was observed using a solar coronagraph to occult the illuminated surface of the Moon. Exceptionally dust-free atmospheric conditions were required to allow the faint emission from sunlight scattered by lunar sodium atoms to be distinguished from moonlight scattered from atmospheric dust. At 0300 UT on April 22, 1994, ideal conditions prevailed for a few hours, and one excellent image of the sodium exosphere was measured, with the Moon at a phase angle of 51 deg, 81 % illuminated. Analysis of the image data showed that the weighted mean temperature of the exosphere was 1280 K and that the sodium column density varied approximately as cosine-cubed of the latitude. A cosine-cubed variation is an unexpected result, since the flux per unit area of solar photons and solar particles varies as the cosine of latitude. It is suggested that this can be explained by a temperature dependence for the sputtering of sodium atoms from the surface. This is a characteristic feature of chemical sputtering, which has been previously proposed to explain the sodium exosphere of Mercury. A possible interaction between chemical sputtering and solar photons is suggested.

Potter, A. E.↗

NASA NTRS2001

Band-Moment Compression of AVIRIS Hyperspectral Data and its Use in the Detection of Vegetation Stress

A remote sensing campaign was conducted over a U.S. Department of Agriculture test farm at Shelton, Nebraska. An experimental field was set off in plots that were differentially treated with anhydrous ammonia. Four replicates of 0-kg/ha to 200-kg/ha plots, in 50-kg/ha increments, were set out in a random block design. Low-altitude (GSD of 3 m) Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral data were collected over the site in 224 bands. Simultaneously, ground data were collected to support the airborne imagery. In an effort to reduce data load while maintaining or enhancing algorithm performance for vegetation stress detection, band-moment compression and analysis was applied to the AVIRIS image cube. The results indicated that band-moment techniques compress the AVIRIS dataset significantly while retaining the capability of detecting environmentally induced vegetation stress.

Estep, L.↗

NASA NTRS2020

Preparing for Delivery of the Lunar Ice Cube Compact IR Spectrometer Payload

Lunar Ice Cube, scheduled to be launched on ARTEMIS I in late 2021, is a deep space cubesat mission with the goalsof demonstrating 1) a cubesat-scale instrument (BIRCHES) capable of addressing NASA HEOMD Strategic KnowledgeGaps related to lunar volatile distribution (abundance, location, and transportation physics of water ice), and 2) cubesatpropulsion, via the Busek BIT 3 RF Ion engine. The mission will also demonstrate the AIM/IRIS microcryocooler for thefirst time in deep space. BIRCHES integration is nearly complete, with several changes made to the thermal design toimprove detector performance. Final preflight instrument testing and calibration, our ongoing concern to be emphasizedhere, have been delayed due to the mandated closure rules of NASA facilities. Lunar Ice Cube, along with two othercubesats deployed from ARTEMIS I, Lunar Flashlight and LunaH-Map, will be the first deep cubesat missions to deliverscience data to the Planetary Data System.

Mason, D.↗

DOE OSTI2024

How to Safely Build 100-plus Kilograms of Weapons-Grade Plutonium

The goal of the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project was to reduce compensating errors by utilizing machine learning to both help determine which reactions contain compensating errors as well as optimizing an experiment which can be used to maximally reduce these errors. Compensating errors can adversely impact the predictive power of application simulations, and therefore it’s useful to further constrain nuclear data and reduce these errors. The EUCLID project included building two configurations at the National Criticality Experiments Research Center (NCERC). These two configurations had very different geometries (one was cube-like and one was slab-like). Previous works focus on selection of the target experiment(s), radiation transport capabilities developed in the project, the experiment optimization, and the performance of the experiments. This work will focus only on the safety aspects of performing this experiment, which utilized over 100 kg of weapons-grade plutonium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

GAS GAPS IN THE PROTOPLANETARY DISK AROUND THE YOUNG PROTOSTAR HL TAU

We have analyzed the HCO{sup +} (1–0) data of the Class I–II protostar, HL Tau, obtained from the Atacama Large Millimeter/submillimeter Array long baseline campaign. We generated the HCO{sup +} image cube at an angular resolution of ∼0.″07 (∼10 au) and performed azimuthal averaging on the image cube to enhance the signal-to-noise ratio and measure the radial profile of the HCO{sup +} integrated intensity. Two gaps at radii of ∼28 and ∼69 au and a central cavity are identified in the radial intensity profile. The inner HCO{sup +} gap is coincident with the millimeter continuum gap at a radius of 32 au. The outer HCO{sup +} gap is located at the millimeter continuum bright ring at a radius of 69 au and overlaps with the two millimeter continuum gaps at radii of 64 and 74 au. On the contrary, the presence of the central cavity is likely due to the high optical depth of the 3 mm continuum emission and not the depletion of the HCO{sup +} gas. We derived the HCO{sup +} column density profile from its intensity profile. From the column density profile, the FWHM widths of the inner and outer HCO{sup +} gaps are both estimated to be ∼14 au, and their depths are estimated to be ∼2.4 and ∼5.0. These results are consistent with the expectation from the gaps opened by forming (sub-)Jovian mass planets, while placing tight constraints on the theoretical models solely incorporating the variation of dust properties and grain sizes.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2018

Nature of and Lessons Learned from Lunar Ice Cube and the First Deep Space Cubesat 'Cluster'

Cubesats operating in deep space face challenges Earth-orbiting cubesats do not. 15 deep space cubesat 'prototypes' will be launched over the next two years including the two MarCO cubesats, the 2018 demonstration of dual communication system at Mars, and the 13 diverse cubesats being deployed from the SLS EM1 mission within the next two years. Three of the EM1 cubesat missions, including the first deep space cubesat 'cluster', will be lunar orbiters with remote sensing instruments for lunar surface/regolith measurements. These include: Lunar Ice Cube, with its 1-4 micron broadband IR spectrometer, BIRCHES, to determine volatile distribution as a function of time of day; Lunar Flashlight, to confirm the presence of surface ice at the lunar poles, utilizing an active source (laser), and looking for absorption features in the returning signal; and LunaH-Map to characterize ice at or below the surface at the poles with a compact neutron spectrometer. In addition, the BIRCHES instrument on Lunar Ice Cube will provide the first demonstration of a microcryocooler (AIM/IRIS) in deep space. Although not originally required to do so, all will be delivering science data to the Planetary Data System, the first formal archiving effort for cubesats. 4 of the 20 recently NASA-sponsored (PSDS3) study groups for deep space cubesat/smallsat mission concepts were lunar mission concepts, most involving 12U cubesats. NASA SIMPLEX 2/SALMON 3 AO will create ongoing opportunities for low-cost missions as 'rides' on government space program or private sector vehicles as these become available.

Bujold, Emily↗

NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗

NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

Artificial Intelligence↗

DOE OSTI2012

ORNL Automated-In-Motion Evaluation Environment (AIMVEE) User Training and Testing Materials - U.S. Copyright TXu 1-797-273

The AIMVEE/WIM system electronically retrieves deployment information, identifies vehicle automatically, and determines total weight, individual wheel weight, individual axle weights, axle spacing, and center-of-balance for any wheeled vehicle in motion. The AIMVEE/WIM system can also perform these functions statically for both wheel vehicles and cargo with information. The AIMVEE/WIM system incorporates digital images and applies cubing algorithms to determine length, width, height for cubic dimensions of both vehicle and cargo. Once all this information is stored, it electronically links to data collection and dissemination systems to provide actual weight and measurement information for planning, deployment, and in-transit visibility. The Static Scale Conversion (SSC) system is an unique enhancement to the AIMVEE/WIM system. It enables a SSC to weigh and measure vehicles and cargo dynamically (i.e., as they pass over the large scale and is included in the AIMVEE computer code base. The material copyrighted is the ORNL Automated-In-Motion Vehicle Evaluation Environment (AIMVEE)/Weigh-In-Motion User Training and Testing material. It includes instructional material in the set-up, operation and tear-down of the AIMVEE/WIM system. It also includes a final exam associated with the training.

Automated-in-Motion Evaluation Environment (AIMVEE↗