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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Resonant excitation of internal gravity waves in cluster cooling flows

Orbital motions of galaxies in X-ray clusters will resonantly excite internal gravity waves (g-waves) that propagate in the plasma. The resonance corresponds to a match between the local Brunt-Vaisala oscillation frequency in the plasma and the appropriate Fourier component of the galactic gravitational potential. Radiated internal waves have an inward group velocity that carries them to the central region of the flow where they become tightly wrapped, geometrically amplified, and eventually dissipated. Waves transport energy and angular momentum, but probably not in amounts large enough to grossly alter the structure of a cooling flow, should one be present. All physical flow variables are finite at the resonance, and all energy and angular momentum deposited by a galaxy is carried inward by the waves. Nonlinear density and velocity fluctuations are likely to result from wave amplitude growth in the central regions of the flow, and a connection with the formation of emission-line filaments is a possibility.

Balbus, Steven A.↗
NASA NTRS1996

Dust and Sputtered Particle Streams in Cometary Atmosphere

Dynamics of dust particles in a comet atmosphere was investigated using Monte-Carlo simulation method taking into account radiation and gravitational forces applied to the particles. The model distribution function found out in VEGA experiments was chosen for calculations. Dust particles with masses more then 10(exp -10) g were considered. The delay effect for the big mass particles is shown. In this paper the boundary distribution function for sputtered particles drifting off the surface was determined using Nochilla's model. General dependences for the normal component of the relative mass velocity of sputtered particles are given as the function of particle energy normalized by Tomas-Fermi energy.

Svirschevsky, Stanislav B.↗
NASA NTRS1994

One-Arm Interferometric Detectors of Gravitational Waves

This paper presents the interferometric detection of gravitational waves using multiple bounce parallel-beam systems. Results show it is possible to remove laser frequency fluctuations from an offset paralllel-beam interferometer without removing the gravitational wave signal.

gravitational radiation one-arm interferometer non↗
NASA NTRS2006

Development of a Nonlinear Probability of Collision Tool for the Earth Observing System

The Earth Observing System (EOS) spacecraft Terra, Aqua, and Aura fly in constellation with several other spacecraft in 705-kilometer mean altitude sun-synchronous orbits. All three spacecraft are operated by the Earth Science Mission Operations (ESMO) Project at Goddard Space Flight Center (GSFC). In 2004, the ESMO project began assessing the probability of collision of the EOS spacecraft with other space objects. In addition to conjunctions with high relative velocities, the collision assessment method for the EOS spacecraft must address conjunctions with low relative velocities during potential collisions between constellation members. Probability of Collision algorithms that are based on assumptions of high relative velocities and linear relative trajectories are not suitable for these situations; therefore an algorithm for handling the nonlinear relative trajectories was developed. This paper describes this algorithm and presents results from its validation for operational use. The probability of collision is typically calculated by integrating a Gaussian probability distribution over the volume swept out by a sphere representing the size of the space objects involved in the conjunction. This sphere is defined as the Hard Body Radius. With the assumption of linear relative trajectories, this volume is a cylinder, which translates into simple limits of integration for the probability calculation. For the case of nonlinear relative trajectories, the volume becomes a complex geometry. However, with an appropriate choice of coordinate systems, the new algorithm breaks down the complex geometry into a series of simple cylinders that have simple limits of integration. This nonlinear algorithm will be discussed in detail in the paper. The nonlinear Probability of Collision algorithm was first verified by showing that, when used in high relative velocity cases, it yields similar answers to existing high relative velocity linear relative trajectory algorithms. The comparison with the existing high velocity/linear theory will also be used to determine at what relative velocity the analysis should use the new nonlinear theory in place of the existing linear theory. The nonlinear algorithm was also compared to a known exact solution for the probability of collision between two objects when the relative motion is strictly circular and the error covariance is spherically symmetric. Figure I shows preliminary results from this comparison by plotting the probabilities calculated from the new algorithm and those from the exact solution versus the Hard Body Radius to Covariance ratio. These results show about 5% error when the Hard Body Radius is equal to one half the spherical covariance magnitude. The algorithm was then combined with a high fidelity orbit state and error covariance propagator into a useful tool for analyzing low relative velocity nonlinear relative trajectories. The high fidelity propagator is capable of using atmospheric drag, central body gravitational, solar radiation, and third body forces to provide accurate prediction of the relative trajectories and covariance evolution. The covariance propagator also includes a process noise model to ensure realistic evolutions of the error covariance. This paper will describe the integration of the nonlinear probability algorithm and the propagators into a useful collision assessment tool. Finally, a hypothetical case study involving a low relative velocity conjunction between members of the Earth Observation System constellation will be presented.

McKinley, David P.↗
NASA NTRS2011

Stationkeeping of the First Earth-Moon Libration Orbiters: The ARTEMIS Mission

Libration point orbits near collinear locations are inherently unstable and must be controlled. For Acceleration Reconnection and Turbulence and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) Earth-Moon Lissajous orbit operations, stationkeeping is challenging because of short time scales, large orbital eccentricity of the secondary, and solar gravitational and radiation pressure perturbations. ARTEMIS is the first NASA mission continuously controlled at both Earth-Moon L1 and L2 locations and uses a balance of optimization, spacecraft implementation and constraints, and multi-body dynamics. Stationkeeping results are compared to pre-mission research including mode directions.

Folta, David↗
NASA NTRS2011

Low-Frequency Gravitational-Wave Science with eLISA/ NGO

We review the expected science performance of the New Gravitational-Wave Observatory (NGO, a.k.a. eLISA), a mission under study by the European Space Agency for launch in the early 2020s. eLISA will survey the low-frequency gravitational-wave sky (from 0.1 mHz to 1 Hz), detecting and characterizing a broad variety of systems and events throughout the Universe, including the coalescences of massive black holes brought together by galaxy mergers; the inspirals of stellar-mass black holes and compact stars into central galactic black holes; several millions of ultracompact binaries, both detached and mass transferring, in the Galaxy; and possibly unforeseen sources such as the relic gravitational-wave radiation from the early Universe. eLISA's high signal-to-noise measurements will provide new insight into the structure and history of the Universe, and they will test general relativity in its strong-field dynamical regime.

Amaro-Seoane, Pau↗
NASA NTRSDate not supplied

The Behavior of High-Velocity Dust Generated by Lander Plumes in the Lunar Environment

Lunar lander plumes are known to accelerate fine dust to speeds exceeding 2 km/s, and the resultant ejecta may remain in lunar orbit for extended periods of time. Such ejecta could become hazardous to objects in lunar orbit as well as systems on the surface. In order to understand the impact on orbiting lunar infrastructure such as Gateway, as well as assets on the lunar surface, here we consider the dynamics of the resultant high-velocity plume ejecta. Initial conditions were set by the expected near-term lunar activity and the known cone of accelerated dust generated by previous lunar landings. The effects of regular 3-body gravitation, solar radiation pressure, and electric field are included in the model. It is found that although the majority of sub-μm dust is carried away by solar wind and electric fields, about ~10% of the dust between 1.7 km/s and 2.3 km/s reimpacts the surface, much of it near the landing site. The hazard posed by that debris is a function of lander mass and distance from the landing site. The Gateway, when orbiting in the nominal NRHO at the time of a landing, is not expected to be significantly affected by the dust. However, other spacecraft in less elliptic orbits may be at greater risk.

Ejecta↗
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, there-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA's Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomatic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related 'omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata 'omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data-use, resulting in 40 enabled publications by open data. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA "Open Science Data Repositories (OSDR)" and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Flourescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to "big data" from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology.

omics↗
NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching. The use of health countermeasures and biomonitoring systems for space missions are required to counteract space health hazards and to support life to thrive in deep space (e.g., humans, animals, plants, crops; entire ecosystems within spacecrafts/habitats/spacesuits). The development of these mission components will be highly dependent on our understanding of basic biological and health responses to myriad space hazards (ionizing radiation, altered gravitational fields, altered day-night cycles, confined isolation, hostile-closed environments, distance-duration from Earth, planetary dust-regolith, and extreme temperatures/atmospheres). The fast-growing array of space biological and mission telemetry data, which in the past was simply archived after minimal analysis, holds great potential once applied to these mission challenges if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its multi-hierarchical, multi-modal, and heterogenous nature (molecular, cellular, tissue, organ, whole organism, behavior, ecosystem, microbiome; tabular, omics, imaging, video, biospecimen, environmental physical-chemical telemetry). This session focuses on current approaches in this domain such as: making space biological data FAIR (findable, accessible, interoperable, reusable), effective data ingestion/dissemination, observational versus experimental data, Open Science collaborations, data analysis techniques, AI/ML/knowledge graph/modeling methods, and data integration/discovery tools.

open science↗
NASA NTRSDate not supplied

NASA Open Science Data Repository: Maximizing Spaceflight Bioscience Data

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for data re-analysis and re-use via Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). To address the challenges posed by gaining new knowledge from a vast and diverse amount of biological, health and environmental data in space, the NASA Open Science Data Repository (OSDR - osdr.nasa.gov/bio) plays a crucial role in curating and openly publishing biological data from space-related experiments. Its design incorporates successes and lessons from NASA GeneLab, encompassing not only high-throughput sequencing data but also physiological, phenotypic, and telemetry data. The OSDR makes space biological data FAIR (findable, accessible, interoperable, reusable), and facilitates effective data ingestion, dissemination, and Open Science collaborations. The OSDR also has the capability to integrate human astronaut data with state-of-the-art security and accessibility procedures. We will discuss here several strategies that NASA’s Biological and Physical Science Division have put in place to maximize the return on investment for spaceflight bioscience data.

space biology↗
NASA NTRS1979

Gravitational time delay in orthogonally polarized radiation passing by the sun

Two parallel investigations into the degree, if any, to which orthogonally polarized rays are deflected differently on passing through the gravitational field of the sun were previously conducted. The first involved very long and intermediate length baseline radio interferometry. The second was initially based on observations of radiation transmitted by the Pioneer 6 spacecraft, on passing behind the sun in 1968. This work was extended by using Helios-A and Helios-B spacecraft. It was calculated that the differential deflection between orthogonally polarized components is less than one part in 10 to the 7th power of the total gravitational deflection, or less than about 10 to the -7th power arc sec, in total.

Harwit, M.↗
NASA NTRS1986

Random scattering approach to gravitational microlensing

Small random deflections of a narrow beam of radiation due to gravitational scattering by stars randomly distributed within the deflector plane are considered. Using a Fouriere transform method, the probability of scattering is obtained as a function of scattering angle for an arbitrary number of stars with an arbitrary distribution of masses. The probability density, expressed in proper units, depends on one parameter only: the effective number of stars. At small scattering angles the density is a Gaussian, and at large angles it falls off as the scattering angle to the minus fourth power. The probability distribution for scatterings is simply related to the angular distribution of the surface brightness of a macroimage, averaged over many microimages. The isophotes are ellipses, with the ratio of the major axis to the minor axis, determined by the dimensionless surface mass density and the shear of the lensing system. The number of stars that has to be included in the modeling of microlensing is proportional to the amplification due to the macrolens, and to the square of the dimensionless surface mass density.

Katz, N.↗
NASA NTRS1988

Origin and anisotropy of the cosmic submillimeter background

Some cosmological implications of the recently discovered submillimeter background (SMB) are discussed. Opacity and isotropy arguments show that if the background is due to dust emission it must originate at a high redshift z greater than about 10. Isotropy measurements are used to constrain the amplitude of dust optical-depth fluctuations and hence the scale of dust inhomogeneity. The observed flux, the inferred high z and high opacity imply that on small scales the mock gravitational instability driven by radiation pressure may have dominated gravitational effects.

Hogan, C. J.↗
NASA NTRS2013

Chandra Grating Spectroscopy of Three Hot White Dwarfs

High-resolution soft X-ray spectroscopic observations of single hot white dwarfs are scarce. With the Chandra Low-Energy Transmission Grating, we have observed two white dwarfs, one is of spectral type DA (LB1919) and the other is a non-DA of spectral type PG1159 (PG1520+525). The spectra of both stars are analyzed, together with an archival Chandra spectrum of another DA white dwarf (GD246). Aims. The soft X-ray spectra of the two DA white dwarfs are investigated in order to study the effect of gravitational settling and radiative levitation of metals in their photospheres. LB1919 is of interest because it has a significantly lower metallicity than DAs with otherwise similar atmospheric parameters. GD246 is the only white dwarf known that shows identifiable individual iron lines in the soft X-ray range. For the PG1159 star, a precise effective temperature determination is performed in order to confine the position of the blue edge of the GW Vir instability region in the HRD. Methods. The Chandra spectra are analyzed with chemically homogeneous as well as stratified NLTE model atmospheres that assume equilibrium between gravitational settling and radiative acceleration of chemical elements. Archival EUV and UV spectra obtained with EUVE, FUSE, and HST are utilized to support the analysis. Results. No metals could be identified in LB1919. All observations are compatible with a pure hydrogen atmosphere. This is in stark contrast to the vast majority of hot DA white dwarfs that exhibit light and heavy metals and to the stratified models that predict significant metal abundances in the atmosphere. For GD246 we find that neither stratified nor homogeneous models can fit the Chandra spectrum. The Chandra spectrum of PG1520+525 constrains the effective temperature to T(sub eff) = 150 000 +/- 10 000 K. Therefore, this nonpulsating star together with the pulsating prototype of the GWVir class (PG1159-035) defines the location of the blue edge of the GWVir instability region. The result is in accordance with predictions from nonadiabatic stellar pulsation models. Such models are therefore reliable tools to investigate the interior structure of GW Vir variables. Conclusions. Our soft X-ray study reveals that the understanding of metal abundances in hot DA white dwarf atmospheres is still incomplete. On the other hand, model atmospheres of hydrogen-deficient PG1159-type stars are reliable and reproduce well the observed spectra from soft X-ray to optical wavelengths.

Adamczak, J.↗