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NASA NTRS2005

A Starfish Preplanetary Nebula: IRAS 19024+0044

Using the Hubble Space Telescope, we have imaged the OH/IR star IRAS 19024+0044 (I19024) at 0.6, 0.8, 1.1, and 1.6 micrometers, as part of our surveys of candidate preplanetary nebulae. The images show a multipolar nebula of size approximately equal to 3.'7 2.'3, with at least six elongated lobes emanating from the center of the nebula. Two of the lobes show limb-brightened tips having point-symmetric structure with respect to the expected location of the central star. The central region shows two dark bands southwest and northeast of a central shallow maximum that may be either two inclined dusty toroidal structures or the dense parts of a single wide, inhomogeneous, toroid. Avery faint, surface brightness-limited, diffuse halo surrounds the lobes. Long-slit/echelle optical spectroscopy obtained at the Mount Palomar and Keck observatories shows a spatially compact source of H(alpha) emission; the H(alpha) line shows a strong, narrow, central core with very broad (+/-1000 km/sec), weak wings, and a narrower blueshifted absorption feature signifying the presence of an approximately 100 km/sec(exp -1) outflow. The spectrum is characterized by a strong, relatively featureless, continuum and lacks the strong forbidden emission lines characteristic of planetary nebulae, confirming that IRAS 19024 is a preplanetary nebula; the spectral type for the central star, although uncertain, is most likely early G. Interferometric observations of the CO J = 1 -0 line emission with the Owens Valley Radio Interferometer show a marginally resolved molecular envelope (size 5.'5 x 4.'4) with an expansion velocity of 13 km/sec (exp -1), resulting from the asymptotic giant branch (AGB) progenitor's dense, slow wind. We derive a kinematic distance of 3.5 kpc to I19024, based on its radial velocity. The bolometric flux is 7:3 x 10(exp -9) erg s(exp -1) cm(exp -2), and the luminosity 2850 L. The relatively low luminosity of I19024, in comparison with stellar evolutionary models, indicates that the initial mass of its central star was approximately 1-1.5 solar mass. The lobes, which appear to be hollow structures with dense walls, have a total mass greater than or equal to about 0.02 solar mass. The lobes, which appear to be hollow structures with dense walls, have a total mass greater than or equal to about 0.02 solar mass. The dusty tori in the center have masses of a few times 10(exp -3) solar mass. The faint halo has a power-law radial surface brightness profile with an exponent of about -3 and most likely represents the remnant spherical circumstellar envelope formed as a result of constant mass loss during the AGB expansion age of less than or approximately equal to 2870 yr, giving a mass-loss rate of greater than or approximately equal to 10(exp -5) solar mass yr (exp -1), The far-infrared fluxes of I19024 indicate the presence of a large mass of cool dust in the nebula, from a simple model we infer the presence of 'cool' (109 K) and 'warm' (280 K) components of dust mass 5.7 x 10(exp -4) and 1.5 x 10(exp -7) solar mass. We discuss our results for I19024 in the light of past and current ideas for the dramatic transformation of the morphology and kinematics of mass-ejecta as AGB stars evolve into planetary nebulae.

circumstellar matter↗
NASA NTRS2010

A Mesoscale Analysis of Column-Integrated Aerosol Properties in Northern India During the TIGERZ 2008 Pre-Monsoon Period and a Comparison to MODIS Retrievals

The Indo-Gangetic Plain (IGP) of the northern Indian subcontinent produces anthropogenic pollution from urban, industrial and rural combustion sources nearly continuously and is affected by convection-induced winds driving desert and alluvial dust into the atmosphere during the premonsoon period. Within the IGP, the NASA Aerosol Robotic Network (AERONET) project initiated the TIGERZ measurement campaign in May 2008 with an intensive operational period from May 1 to June 23, 2008. Mesoscale spatial variability of aerosol optical depth (AOD, tau) measurements at 500mn was assessed at sites around Kanpur, India, with averages ranging from 0.31 to 0.89 for spatial variability study (SVS) deployments. Sites located downwind from the city of Kanpur indicated slightly higher average aerosol optical depth (delta Tau(sub 500)=0.03-0.09). In addition, SVS AOD area-averages were compared to the long-tenn Kanpur AERONET site data: Four SVS area-averages were within +/- 1 cr of the climatological mean of the Kanpur site, while one SVS was within 2sigma below climatology. For a SVS case using AERONET inversions, the 440-870mn Angstrom exponent of approximately 0.38, the 440-870mn absorption Angstrom exponent (AAE) of 1.15-1.53, and the sphericity parameter near zero suggested the occurrence of large, strongly absorbing, non-spherical aerosols over Kanpur (e.g., mixed black carbon and dust) as well as stronger absorption downwind of Kanpur. Furthermore, the 3km and lOkm Terra and Aqua MODIS C005 aerosol retrieval algorithms at tau(sub 550) were compared to the TIGERZ data set. Although MODIS retrievals at higher quality levels were comparable to the MODIS retrieval uncertainty, the total number of MODIS matchups (N) were reduced with subsequent quality levels (N=25, QA>=0; N=9,QA>=l; N=6, QA>=2; N=1, QA=3) over Kanpur during the premonsoon primarily due to the semi-bright surface, complex aerosol mixture and cloud-contaminated pixels. The TIGERZ 2008 data set provided a unique opportunity to measure the spatial and temporal variations of aerosol loading in the IGP. The strong aerosol absorption derived from ground-based sun/sky radiometer measurements suggested the presence of a predominately black carbon and dust mixture during the pre-monsoon period. Consistent with the elevated heat-pump hypothesis, these absorbing aerosols found across Kanpur and the greater IGP region during the pre-monsoon period likely induced regional atmospheric warming, which lead to a more rapid advance of the southwest Asian monsoon and above normal precipitation over northern India in June 2008.

Giles, D. M.↗
DOE OSTI2020

Functionalized Magnetic Nanoparticles for Technetium Sequestration from Groundwater

Technetium 99 (Tc) is among the most common environmental contaminants at DOE sites and one of the most common risk drivers in low- and high-level waste disposal sites. The majority of Tc is generated from anthropogenic sources, such as nuclear power plants, global weapons, nuclear storage facilities and medical applications. Through these sources, Tc contamination has been unintentionally introduced in to the environment. The most common chemical form of Tc is Tc(VII)O{sub 4}{sup -}. Due to its high solubility and mobility, Tc can enter the food chain and cause adverse health effects to humans. Currently, ion exchange resins and reduction processes are the most common approaches for Tc immobilization. Although these techniques have shown to be effective, they also possess major drawbacks, such as high cost, low adsorption capacity, and complex creation and maintenance. Therefore, development of more efficient and simple technologies for the remediation of Tc-contaminated systems are needed. Functionalized magnetic nanoparticles have been used to remove organic and inorganic contaminants from water resources. These nanoparticles have attracted extensive attention as an adsorbent material due to their large surface area, high efficiency, low-cost, easy functionalization and separation with a magnet. This study seek to develop functionalized magnetic iron oxide nanoparticles for the efficient removal of Tc and other heavy metal contaminants from water resources under ambient conditions. Objectives: Synthesize magnetic iron oxide nanoparticles and functionalize their surface with Cetyltrimethylammonium Bromide (CTAB) and tetraethyl-orthosilicate (TEOS). Characterize the synthesized nanoparticles using scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS), Dynamic Light Scattering (DLS) and Zeta PALS. Perform adsorption studies to evaluate their adsorption behavior and capacity for (a) Technetium using Rhenium (ReO{sub 4}{sup -}) as a surrogate and (b) heavy metals, e.g. Cu{sup 2+}. Conclusions: Magnetic iron oxide nanoparticles were successfully functionalized with CTAB and TEOS. The functionalization of the iron oxide nanoparticles affects their surface charge and their hydrodynamic diameter. The addition of CTAB or TEOS decreased the hydrodynamic diameter of the nanoparticles due to repulsive and steric forces. The SEM micrographs show spherical nanoparticles of different sizes. The EDX analysis shows the presence of iron and oxygen from the iron oxide crystalline structure, and the different constituents of the CTAB and TEOS molecules. Proof-of-concept shows the successful adsorption of rhenium (ReO{sub 4}{sup -}) and copper Cu{sup 2+}) onto CTAB-Fe{sub 2}O{sub 3} and TEOS-Fe{sub 2}O{sub 3} respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Overview of new MAST physics in anticipation of first results from MAST Upgrade

We report that the mega amp spherical tokamak (MAST) was a low aspect ratio device (R/a = 0.85/0.65 ~ 1.3) with similar poloidal cross-section to other medium-size tokamaks. The physics programme concentrates on addressing key physics issues for the operation of ITER, design of DEMO and future spherical tokamaks by utilising high resolution diagnostic measurements closely coupled with theory and modelling to significantly advance our understanding. An empirical scaling of the energy confinement time that favours higher power, lower collisionality devices is consistent with gyrokinetic modelling of electron scale turbulence. Measurements of ion scale turbulence with beam emission spectroscopy and gyrokinetic modelling in up-down symmetric plasmas find that the symmetry of the turbulence is broken by flow shear. Near the non-linear stability threshold, flow shear tilts the density fluctuation correlation function and skews the fluctuation amplitude distribution. Results from fast particle physics studies include the observation that sawteeth are found to redistribute passing and trapped fast particles injected from neutral beam injectors in equal measure, suggesting that resonances between the m = 1 perturbation and the fast ion orbits may be playing a dominant role in the fast ion transport. Measured D–D fusion products from a neutron camera and a charged fusion product detector are 40% lower than predictions from TRANSP/NUBEAM, highlighting possible deficiencies in the guiding centre approximation. Modelling of fast ion losses in the presence of resonant magnetic perturbations (RMPs) can reproduce trends observed in experiments when the plasma response and charge-exchange losses are accounted for. Measurements with a neutral particle analyser during merging-compression start-up indicate the acceleration of ions and electrons. Transport at the plasma edge has been improved through reciprocating probe measurements that have characterised a geodesic acoustic mode at the edge of an ohmic L-mode plasma and particle-in-cell modelling has improved the interpretation of plasma potential estimates from ball-pen probes. The application of RMPs leads to a reduction in particle confinement in L-mode and H-mode and an increase in the core ionization source. The ejection of secondary filaments following type-I ELMs correlates with interactions with surfaces near the X-point. Simulations of the interaction between pairs of filaments in the scrape-off layer suggest this results in modest changes to their velocity, and in most cases can be treated as moving independently. A stochastic model of scrape-off layer profile formation based on the superposition of non-interacting filaments is in good agreement with measured time-average profiles. Transport in the divertor has been improved through fast camera imaging, indicating the presence of a quiescent region devoid of filament near the X-point, extending from the separatrix to $ψ_n$ ~ 1.02. Simulations of turbulent transport in the divertor show that the angle between the divertor leg on the curvature vector strongly influences transport into the private flux region via the interchange mechanism. Coherence imaging measurements show counter-streaming flows of impurities due to gas puffing increasing the pressure on field lines where the gas is ionised. MAST Upgrade is based on the original MAST device, with substantially improved capabilities to operate with a Super-X divertor to test extended divertor leg concepts. SOLPS-ITER modelling predicts the detachment threshold will be reduced by more than a factor of 2, in terms of upstream density, in the Super-X compared with a conventional configuration and that the radiation front movement is passively stabilised before it reaches the X-point. 1D fluid modelling reveals the key role of momentum and power loss mechanisms in governing detachment onset and evolution. Analytic modelling indicates that long legs placed at large major radius, or equivalently low at the target compared with the X-point are more amenable to external control. With MAST Upgrade experiments expected in 2019, a thorough characterisation of the sources of the intrinsic error field has been carried out and a mitigation strategy developed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Experimental characterization of a section of a spherically imploding plasma liner formed by merging hypersonic plasma jets

In this work, we report experimental results on merging of hypersonic plasma jets, which is the fundamental building block for forming spherically imploding plasma liners as a potential standoff compression driver for magneto-inertial fusion. Jets are formed and launched by contoured-gap coaxial plasma guns mounted at the six vertices and the center of a hexagon covering approximately one-tenth of the surface area of a 9-ft-diameter spherical chamber. First, from experiments with two and three merging jets of four different species (N, Ar, Kr, and Xe), we show that (1) density spatial non-uniformities can be large (with electron-density jumps ranging from 2.9 for N to 6.6 for Xe) when shocks form upon jet merging, but smaller (density jumps <2) when shocks do not form; (2) jet impurities (20% Ti in these experiments) can increase the level of density spatial non-uniformity by increasing the collisionality of jet merging, leading to shock formation rather than potentially more desirable shockless jet merging; and (3) the liner Mach number can remain high (≳10), as required for plasma liners to be an effective compression driver. Secondly, from experiments with six and seven merging jets using Ar, we present results with improved jet-to-jet mass balance of <2% across jets, including (1) evidence of substantially increased balance in the jet merging and symmetry of the liner structure and (2) potentially favorable changes in the jet-merging morphology with the addition of the seventh jet. Ultimately, for both experiments, we present comparisons between experimental and synthetic data from three-dimensional hydrodynamic codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2008

Energy Deposition Processes in Titan's Upper Atmosphere

Most of Titan's atmospheric organic and nitrogen chemistry, aerosol formation, and atmospheric loss are driven from external energy sources such as Solar UV, Saturn's magnetosphere, solar wind and galactic cosmic rays. The Solar UV tends to dominate the energy input at lower altitudes of approximately 1100 km but which can extend down to approximately 400 km, while the plasma interaction from Saturn's magnetosphere, Saturn's magnetosheath or solar wind are more important at higher altitudes of approximately 1400 km, but the heavy ion plasma [O(+)] of approximately 2 keV and energetic ions [H(+)] of approximately 30 keV or higher from Saturn's magnetosphere can penetrate below 950km. Cosmic rays with energies of greater than 1 GeV can penetrate much deeper into Titan's atmosphere with most of its energy deposited at approximately 100 km altitude. The haze layer tends to dominate between 100 km and 300 km. The induced magnetic field from Titan's interaction with the external plasma can be very complex and will tend to channel the flow of energy into Titan's upper atmosphere. Cassini observations combined with advanced hybrid simulations of the plasma interaction with Titan's upper atmosphere show significant changes in the character of the interaction with Saturn local time at Titan's orbit where the magnetosphere displays large and systematic changes with local time. The external solar wind can also drive sub-storms within the magnetosphere which can then modify the magnetospheric interaction with Titan. Another important parameter is solar zenith angle (SZA) with respect to the co-rotation direction of the magnetospheric flow. Titan's interaction can contribute to atmospheric loss via pickup ion loss, scavenging of Titan's ionospheric plasma, loss of ionospheric plasma down its induced magnetotail via an ionospheric wind, and non-thermal loss of the atmosphere via heating and sputtering induced by the bombardment of magnetospheric keV ions and electrons. This energy input evidently drives the large positive and negative ions observed below approximately 1100 km altitude with ion masses exceeding 10,000 daltons. We refer to these ions as seed particles for the aerosols observed below 300 km altitude. These seed particles can be formed, for example, from the polymerization of acetylene (C2H2) and benzene (C6H6) molecules in Titan's upper atmosphere to form polycyclic aromatic hydrocarbons (PAH) and/or fullerenes (C60). In the case of fullerenes, which are hollow spherical carbon shells, magnetospheric keV [O(+)] ions can become trapped inside the fullerenes and eventually find themselves inside the aerosols as free oxygen. The aerosols are then expected to fall to Titan's surface as polymerized hydrocarbons with trapped free oxygen where unknown surface chemistry can take place.

Sittler, Edward C., Jr.↗
NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗
DOE OSTI2016

The role of Dark Matter sub-halos in the non-thermal emission of galaxy clusters

Annihilation of Dark Matter (DM) particles has been recognized as one of the possible mechanisms for the production of non-thermal particles and radiation in galaxy clusters. Previous studies have shown that, while DM models can reproduce the spectral properties of the radio halo in the Coma cluster, they fail in reproducing the shape of the radio halo surface brightness because they produce a shape that is too concentrated towards the center of the cluster with respect to the observed one. However, in previous studies the DM distribution was modeled as a single spherically symmetric halo, while the DM distribution in Coma is found to have a complex and elongated shape. In this work we calculate a range of non-thermal emissions in the Coma cluster by using the observed distribution of DM sub-halos. We find that, by including the observed sub-halos in the DM model, we obtain a radio surface brightness with a shape similar to the observed one, and that the sub-halos boost the radio emission by a factor between 5 and 20%, thus allowing to reduce the gap between the annihilation cross section required to reproduce the radio halo flux and the upper limits derived from other observations, and that this gap can be explained by realistic values of the boosting factor due to smaller substructures. Models with neutralino mass of 9 GeV and composition τ{sup +} τ{sup −}, and mass of 43 GeV and composition b b-bar can fit the radio halo spectrum using the observed properties of the magnetic field in Coma, and do not predict a gamma-ray emission in excess compared to the recent Fermi-LAT upper limits. These findings make these DM models viable candidate to explain the origin of radio halos in galaxy clusters, avoiding the problems connected to the excessive gamma-ray emission expected from proton acceleration in most of the currently proposed models, where the acceleration of particles is directly or indirectly connected to events related to clusters merging. Therefore, DM models deserve to be better studied both from the theoretical and observational sides; the best spectral bands where it is possible to obtain better information are the radio and the gamma-ray bands, while we do not expect a strong emission in the X-ray band.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗