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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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81 records · Page 5

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the “FAIRness” of NASA’s GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗

A Cool Tool for Deicing Planes

Nicknamed the "ice zapper," the Electro Expulsive Separation System (EESS) is an aircraft ice removal system that "pulverizes ice and removes layers of ice as thin as frost or as thick as an inch of glaze," according to the principle inventor of the technology. Patented by NASA's Ames Research Center, the EESS consists of layers of conductors encased in materials that are bonded directly to the airframe structure. When ice accumulates on the aircraft, an electric current is sent through the conductors, causing them to pulse. Even though the conductors move less than a twenty-thousandth of an inch in just a millisecond, the movement is sufficient to pulverize the ice. It is this highly accelerated motion that shatters the ice into particles the size of table salt; too small to be harmful to the aircraft. When compared with other systems in use, such as thermal deicers and pneumatic boots, the ice zapper does very well. Thermal deicers are fairly common, although they use an enormous amount of energy and present the possibility of ice refreezing. Pneumatic boots are not always effective because they require an inflation device that is unable to work until a quarter inch of ice has accumulated. With both systems, the ice that is loosened may still be large enough to cause problems for the plane once dislodged.

Source record↗

(abstract) Vibration Damping of the Cassini Spacecraft Structure

Cassini will be protected during launch ascent through the atmosphere by a lightweight aluminum payload fairing (PLF). As a result of the extreme noise levels generated by the powerful Titan IV at liftoff, and the acoustic transparency of the PLF, Cassini is predicted to experience severe acoustic levels. Furthermore, the high acoustic levels, coupled with the size and configuration of the spacecraft, will induce intense random vibration on the structure and critical spacecraft components. Efforts to mitigate the vibroacoustic environment by modifying the spacecraft structure were pursued. Preliminary studies indicated that a structural damping treatment using viscoelastic materials (VEMs) represented a viable technique of reducing vibration with minimum impact on weight, cost, and redesign. Tuned Vibration Absorbers (TVAs) - compact, single degree-of-freedom mechanical oscillators in which a VEM serves as the spring and damping element - will be used also. The operating principles, design, and installation of the TVAs are described, the test program is outlined, and test results are presented which show that significant vibration attenuation was achieved.

vibroacoustic environment↗

Mind the Gap: Addressing Data Gaps and Assessing Noise Mismodeling in LISA

Due to the sheer complexity of the Laser Interferometer Space Antenna (LISA) space mission, data gaps arising from instrumental irregularities and/or scheduled maintenance are unavoidable. Focusing on merger-dominated massive black hole binary signals, we test the appropriateness of the Whittle-likelihood on gapped data in a variety of cases. From first principles, we derive the likelihood valid for gapped data in both the time and frequency domains. Cheap-to-evaluate proxies to p-p plots are derived based on a Fisher-based formalism, and verified through Bayesian techniques. Our tools allow to predict the altered variance in the parameter estimates that arises from noise mismodeling, as well as the information loss represented by the broadening of the posteriors. The result of noise mismodeling with gaps is sensitive to the characteristics of the noise model, with strong low-frequency (red) noise and strong high-frequency (blue) noise giving statistically significant fluctuations in recovered parameters. We demonstrate that the introduction of a tapering window reduces statistical inconsistency errors, at the cost of less precise parameter estimates. We also show that the assumption of independence between inter-gap segments appears to be a fair approximation even if the data set is inherently coherent. However, if one instead assumes fictitious correlations in the data stream, when the data segments are actually independent, then the resultant parameter recoveries could be inconsistent with the true parameters. The theoretical and numerical practices that are presented in this work could readily be incorporated into global-fit pipelines operating on gapped data.

LISA↗

Potential Challenges in Near-Field Scanning Optical Microscopy for Space Applications

Near-field scanning optical microscopy (NSOM) also called scanning near-field optical microscopy (SNOM) is now well accepted as a powerful tool for sub-wavelength (nanoscale in the optical region) spatial resolution microscopy and a large number of related tasks. The importance lies in the fact of strategic advantages of standard microscopy but with significantly enhanced resolution. Since many modern optical diagnostic techniques have found useful applications in space, it is logical to consider the future role of NSOM in such situations. For example, protein crystal growth study under microgravity conditions is a valid candidate. If applied successfully, processes at molecular level can be studied during the growth. NSOM has already been demonstrated to be useful for the study of such crystals here on earth. The basic principle of NSOM can be illustrated. The illumination-collection mode is shown although several other possible approaches exist. In this, the sample is illuminated and the light from the sample is collected through the same tiny aperture opening. A tapered optical fiber is scanned near the sample surface. The tip is coated generally with a metal with a sub-wavelength aperture opening. The tip-sample distance is maintained constant while scanning. Thus, the optical signal available for collection is generally a function of the optical properties of the sample surface. Since the aperture is sub-wavelength in diameter and the tip is held very close (again in the sub-wavelength domain) to the surface, the lateral resolution in the sub-wavelength domain is obtained. Thus, the typical wavelength- order resolution of ordinary microscopy can be significantly enhanced while maintaining the strategic advantages (no need of sample in vacuum chamber, electron beams, etc). Commercial NSOM systems play a key role in the success and widespread acceptance of the tool. These commercial systems work fairly well in laboratory conditions on earth. However, they may not be deployed on a space mission as such with comparable outcome. In this communication we discuss several potential problems and some possible solutions.

Vikram, Chandra S.↗

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↗

Ultrasonic Nondestructive Characterization of Adhesive Bonds

Adhesives and adhesive joints are widely used in various industrial applications to reduce weight and costs, and to increase reliability. For example, advances in aerospace technology have been made possible, in part, through the use of lightweight materials and weight-saving structural designs. Joints, in particular, have been and continue to be areas in which weight can be trimmed from an airframe through the use of novel attachment techniques. In order to save weight over traditional riveted designs, to avoid the introduction of stress concentrations associated with rivet holes, and to take full advantage of advanced composite materials, engineers and designers have been specifying an ever-increasing number of adhesively bonded joints for use on airframes. Nondestructive characterization for quality control and remaining life prediction has been a key enabling technology for the effective use of adhesive joints. Conventional linear ultrasonic techniques generally can only detect flaws (delamination, cracks, voids, etc) in the joint assembly. However, more important to structural reliability is the bond strength. Although strength, in principle, cannot be measured nondestructively, a slight change in material nonlinearity may indicate the onset of failure. Furthermore, microstructural variations due to aging or under-curing may also cause changes in the third order elastic constants, which are related to the ultrasonic nonlinear parameter of the polymer adhesive. It is therefore reasonable to anticipate a correlation between changes in the ultrasonic nonlinear acoustic parameter and the remaining bond strength. It has been observed that higher harmonics of the fundamental frequency are generated when an ultrasonic wave passes through a nonlinear material. It seems that such nonlinearity can be effectively used to characterize bond strength. Several theories have been developed to model this nonlinear effect. Based on a microscopic description of the nonlinear interface binding force, a quantitative method was presented. Recently, a comparison between the experimental and simulated results based on a similar theoretical model was presented. A through-transmission setup for water immersion mode-converted shear waves was used to analyze the ultrasonic nonlinear parameter of an adhesive bond. In addition, ultrasonic guided waves have been used to analyze adhesive or diffusion bonded joints. In this paper, the ultrasonic nonlinear parameter is used to characterize the curing state of a polymer/aluminum adhesive joint. Ultrasonic through-transmission tests were conducted on samples cured under various conditions. The magnitude of the second order harmonic was measured and the corresponding ultrasonic nonlinear parameter was evaluated. A fairly good correlation between the curing condition and the nonlinear parameter is observed. The results show that the nonlinear parameter might be used as a good indicator of the cure state for adhesive joints.

Qu, Jianmin↗

Determining Locations by Use of Networks of Passive Beacons

Networks of passive radio beacons spanning moderate-sized terrain areas have been proposed to aid navigation of small robotic aircraft that would be used to explore Saturn s moon Titan. Such networks could also be used on Earth to aid navigation of robotic aircraft, land vehicles, or vessels engaged in exploration or reconnaissance in situations or locations (e.g., underwater locations) in which Global Positioning System (GPS) signals are unreliable or unavailable. Prior to use, it would be necessary to pre-position the beacons at known locations that would be determined by use of one or more precise independent global navigation system(s). Thereafter, while navigating over the area spanned by a given network of passive beacons, an exploratory robot would use the beacons to determine its position precisely relative to the known beacon positions (see figure). If it were necessary for the robot to explore multiple, separated terrain areas spanned by different networks of beacons, the robot could use a long-haul, relatively coarse global navigation system for the lower-precision position determination needed during transit between such areas. The proposed method of precise determination of position of an exploratory robot relative to the positions of passive radio beacons is based partly on the principles of radar and partly on the principles of radio-frequency identification (RFID) tags. The robot would transmit radar-like signals that would be modified and reflected by the passive beacons. The distance to each beacon would be determined from the roundtrip propagation time and/or round-trip phase shift of the signal returning from that beacon. Signals returned from different beacons could be distinguished by means of their RFID characteristics. Alternatively or in addition, the antenna of each beacon could be designed to radiate in a unique pattern that could be identified by the navigation system. Also, alternatively or in addition, sets of identical beacons could be deployed in unique configurations such that the navigation system could identify their unique combinations of radio-frequency reflections as an alternative to leveraging the uniqueness of the RFID tags. The degree of dimensional accuracy would depend not only on the locations of the beacons but also on the number of beacon signals received, the number of samples of each signal, the motion of the robot, and the time intervals between samples. At one extreme, a single sample of the return signal from a single beacon could be used to determine the distance from that beacon and hence to determine that the robot is located somewhere on a sphere, the radius of which equals that distance and the center of which lies at the beacon. In a less extreme example, the three-dimensional position of the robot could be determined with fair precision from a single sample of the signal from each of three beacons. In intermediate cases, position estimates could be refined and/or position ambiguities could be resolved by use of supplementary readings of an altimeter and other instruments aboard the robot.

Okino, Clayton↗

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↗