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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Submicron and Nanoparticulate Matter Removal by HEPA-Rated Media Filters and Packed Beds of Granular Materials

Contaminants generated aboard crewed spacecraft by diverse sources consist of both gaseous chemical contaminants and particulate matter. Both HEPA media filters and packed beds of granular material, such as activated carbon, which are both commonly employed for cabin atmosphere purification purposes have efficacy for removing nanoparticulate contaminants from the cabin atmosphere. The phenomena associated with particulate matter removal by HEPA media filters and packed beds of granular material are reviewed relative to their efficacy for removing fine (less than 2.5 micrometers) and ultrafine (less than 0.01 micrometers) sized particulate matter. Considerations are discussed for using these methods in an appropriate configuration to provide the most effective performance for a broad range of particle sizes including nanoparticulates.

Perry, J. L.↗
NASA NTRS1987

Statistical treatment of fluctuations in the gravitational focusing of light due to stellar masses within a gravitational lens

When light from small, distant sources in the universe is gravitationally focused by an intervening galaxy, the gravitational lens can be influenced by the granularity of the matter distribution which is caused by the stellar (or other compact) masses in the galaxy. A largely analytic, statistical calculation for a gravitational lens due to a collection of compact masses - valid for sources of finite size and for large (as well as small) 'optical depths' for the lens - is developed to treat fluctuations in the light caused by such 'microfocusing' effects. Previous treatments have been either numerical simulations of the Monte Carlo type or limited to single-star (i.e., low-optical-depth) effects.

Deguchi, Shuji↗
NASA NTRS2024

On the Role of Friction and Particle Size Distribution in Granular Packings

Packing of particles in a disordered arrangement has tremendous significance in both condensed matter physics and engineering applications. The last three decades have seen remarkable progress in our understanding of the physics of granular packings that has been largely facilitated by a rapid growth in the power of modern computers. Although granular packings are ubiquitous in diverse natural settings, from clogging of powders in hoppers to the crowding of living cells, a significant motivation for modeling granular packings has emerged from a proposal that the transition from a fluid-like state to a solid-like state of a granular material upon increasing volume fraction, called jamming, is intimately related to the origins of glass transition in thermal systems. As such, a majority of modeling efforts have focused on the jamming behavior of an idealized granular material: frictionless, monodisperse sphere. While such studies have illuminated the rich physics of jamming, granular materials in nature and engineering practice are rarely frictionless or monodisperse. The analogous research on the packing of these ‘real-world’ granular materials is still not fully developed. Besides requiring the exploration of a huge parameter space, three key computational considerations have inhibited their modeling: (i) traditional computational methods are not adept at simulating mechanically-stable packings of frictional particles near the jamming transition; (ii) standard algorithms of contact detection in discrete element methods are impractical to simulate granular packings with a wide distribution of particle sizes; (iii) a lack of well-established contact mechanics models of friction that can accurately reproduce experimental data. This chapter will review the latest computational advances to simulate the jamming of size-dispersed frictional particles, and describe the rich microstructural diversity that emerges in their packings.

granular↗
NASA NTRS2017

NIAC Phase II Orbiting Rainbows: Future Space Imaging with Granular Systems

Inspired by the light scattering and focusing properties of distributed optical assemblies in Nature, such as rainbows and aerosols, and by recent laboratory successes in optical trapping and manipulation, we propose a unique combination of space optics and autonomous robotic system technology, to enable a new vision of space system architecture with applications to ultra-lightweight space optics and, ultimately, in-situ space system fabrication. Typically, the cost of an optical system is driven by the size and mass of the primary aperture. The ideal system is a cloud of spatially disordered dust-like objects that can be optically manipulated: it is highly reconfigurable, fault-tolerant, and allows very large aperture sizes at low cost. This new concept is based on recent understandings in the physics of optical manipulation of small particles in the laboratory and the engineering of distributed ensembles of spacecraft swarms to shape an orbiting cloud of micron-sized objects. In the same way that optical tweezers have revolutionized micro- and nano-manipulation of objects, our breakthrough concept will enable new large scale NASA mission applications and develop new technology in the areas of Astrophysical Imaging Systems and Remote Sensing because the cloud can operate as an adaptive optical imaging sensor. While achieving the feasibility of constructing one single aperture out of the cloud is the main topic of this work, it is clear that multiple orbiting aerosol lenses could also combine their power to synthesize a much larger aperture in space to enable challenging goals such as exo-planet detection. Furthermore, this effort could establish feasibility of key issues related to material properties, remote manipulation, and autonomy characteristics of cloud in orbit. There are several types of endeavors (science missions) that could be enabled by this type of approach, i.e. it can enable new astrophysical imaging systems, exo-planet search, large apertures allow for unprecedented high resolution to discern continents and important features of other planets, hyperspectral imaging, adaptive systems, spectroscopy imaging through limb, and stable optical systems from Lagrange-points. Furthermore, future micro-miniaturization might hold promise of a further extension of our dust aperture concept to other more exciting smart dust concepts with other associated capabilities. Our objective in Phase II was to experimentally and numerically investigate how to optically manipulate and maintain the shape of an orbiting cloud of dust-like matter so that it can function as an adaptable ultra-lightweight surface. Our solution is based on the aperture being an engineered granular medium, instead of a conventional monolithic aperture. This allows building of apertures at a reduced cost, enables extremely fault-tolerant apertures that cannot otherwise be made, and directly enables classes of missions for exoplanet detection based on Fourier spectroscopy with tight angular resolution and innovative radar systems for remote sensing. In this task, we have examined the advanced feasibility of a crosscutting concept that contributes new technological approaches for space imaging systems, autonomous systems, and space applications of optical manipulation. The proposed investigation has matured the concept that we started in Phase I to TRL 3, identifying technology gaps and candidate system architectures for the space-borne cloud as an aperture.

Quadrelli, Marco B.↗
NASA NTRSDate not supplied

Electrostatic Regolith Interaction Experiment (ERIE) Electrometer Instrument Development

The Electrostatic Regolith Interaction Experiment (ERIE) is a joint venture between the University of Central Florida (UCF) Center for Microgravity Research (CMR) and the NASA Kennedy Space Center (KSC) Electrostatics and Surface Physics Laboratory (ESPL) seeking to examine charged dust grain behavior in a microgravity environment. Two separate systems have been combined for this suborbital flight experiment: the COLLisions Into Dust Experiment (COLLIDE) developed by the UCF CMR and the Wheel Electrostatic Spectrometer (WES) developed by the NASA KSC ESPL. This combination will advance the understanding of the natural and induced charged grain behavior on the Moon, asteroids, and other low gravity bodies comprised of charged dust particles. COLLIDE retains granular material under vacuum in a shallow tray behind a metal door, which then opens and releases the particles into a larger open volume when microgravity is achieved. The experiment is observed with a high-speed camera, such that the motions of these particles can then be tracked so the kinematics of each grain may be analyzed. The original application for this apparatus was to study cratering events into granular beds, but electrostatic repulsion was detected in the early frames of the video data returned from completed experiments, so a re-flight with a focus on these events was proposed. Agitation of the grains during launch combined with the frictional charge transfer between the grains and the door as it slides open provides an opportunity to use this setup to observe material tribocharging and charged particle behaviors in microgravity. In this updated version, the charged particles released into the chamber will traverse through an electric field produced by high voltage parallel plates and their resulting trajectories will be determined by their net charges. WES was originally developed to characterize the triboelectric properties of the Martian regolith through the contact of a rover wheel with the surface as it rotates. Improvements were made upon this legacy system to develop a sensor suite that will be installed within the COLLIDE door to measure charge transferred between the granular material and insulating disks protruding through the door. These insulator disks span the triboelectric series so, as they slide across the particulate matter when the door opens, each will accumulate a charge consistent with its relative position to the grains within the series. This charge on each insulator is distributed between two capacitances in series with an electrometer amplifier returning an analog voltage proportional to the charge accumulated. Calibration of this system has been performed using applications of known charge to the inputs and characterization of the frictional charge transfer between various regolith simulants and the sensor insulators is currently being examined in the lab.

Electrostatics↗
NASA NTRS2021

Asthma and Particulate Matter Pollution: Insights from Health Survey and Air Quality Monitoring in the Buzzard Point, Washington, DC Neighborhood

Air pollution, climate change, and other environmental factors contribute to increasing asthma in manycities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution.A partnership between residents, concerned citizens, scientists, and educators has been working for envi-ronmental health in a DC neighborhood located on a major roadway, next to concrete batch plants andclose to several construction projects. A 2016 Community Health and Safety Study by the DC Departmentof Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to healthimpacts from recent construction in the area, compared with the surrounding areas, due to lower averageincome and higher percentage of seniors and children. This work presents neighborhood health surveysand air quality monitoring data at a more granular, local level than available from DC governmentagencies. The health surveys documented residents’ experiences around air pollution, asthma,and other health concerns. A key finding was evidence that asthma might be undercounted in thisneighborhood; among residents who did not indicate a diagnosis of asthma, many discussed havingsymptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate thatfederal air quality standards have been violated. Real-time PM data, however,illustrated how current PMstandards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that areconsistent with resident concerns.

Shizuka Hsieh↗
NASA NTRS2021

Chapter 3: Suspensions, foams, emulsions, colloids, and granular materials--self-healing, tuning gravity, and life support for exploration

At the suggestion of NASA’s Physical Science Research Program in the Space Life and Physical Science Research and Application Division, Paul Chaikin, Noel Clark, and Sidney Nagel organized a focus session and workshop for the 2020 American Physical Society (APS) March meeting under the auspices of the Division of Soft Matter. Three overarching themes emerged from the workshop and are presented with additional details: • Machines made out of machines • Scalable self-sustaining ecosystems • Active materials and metamaterials This report lays out only some of the potential directions for soft matter dynamics over the next two decades. It also lays out the role that gravity plays in the organization of the basic building blocks of matter. Not only will research on soft matter have tremendous application towards understanding its behavior in our terrestrial environment, but also potentially in other NASA programs such as planetary science, exploration, robotics, etc. Attached is a White Paper for the Decadal Survey that consists of an extended Title along with the previous Introduction and Chapter 2.3 from NASA/CP-20205010493.

Soft matter↗
NASA NTRS1992

The contribution of galaxy clusters to the soft X-ray background

The present paper examines models for the expected contribution to the X-ray background (XRB) from clusters of galaxies in a flat universe with a spectrum of fluctuations corresponding to the standard cold dark matter picture and for a power-law spectrum P(k) varies as k sup n with n = -2. A self-similar scaling model for clusters proposed by Kaiser (1986) is presented, along with several variants. Photon statistics from synthesized maps of deep Einstein fields show a granularity similar to that deduced by Hamilton and Helfand (1987) from the Einstein data but overproduces by a large factor the number of discrete sources observed as clusters, and the fluctuation limit derived from the recent correlation analyses of the background. Two alternative models are designed to be consistent with the local luminosity function data; for these, expected deep images for the Rosat satellite are generated. Clusters of galaxies should be a significant source of background at energies around 2 keV, and it is proposed that clusters of galaxies contribute up to 30 percent of the unresolved component.

Blanchard, A.↗
NASA NTRS2021

Grand Challenges in Soft Matter Science: Prospects for Microgravity Research

At the suggestion of NASA’s Physical Science Research Program in the Space Life and Physical Science Research and Application Division, Paul Chaikin, Noel Clark, and Sidney Nagel organized a focus session and workshop for the 2020 American Physical Society (APS) March meeting under the auspices of the Division of Soft Matter. Three overarching themes emerged from the workshop and are presented with additional details: •Machines made out of machines •Scalable self-sustaining ecosystems •Active materials and metamaterials This report lays out only some of the potential directions for soft matter dynamics over the next two decades. It also lays out the role that gravity plays in the organization of the basic building blocks of matter. Not only will research on soft matter have tremendous application towards understanding its behavior in our terrestrial environment, but also potentially in other NASA programs such as planetary science, exploration, robotics, etc.

Microgravity↗
NASA NTRSDate not supplied

Artificial Intelligence (AI) Methods for Augmenting the IMPACT Tool Evidence Library

Development of the Evidence Library for use with the IMPACT probability risk assessment tool took several years and involved a staggering amount of effort from a multi-disciplinary team. A very significant amount of the labor effort to collect, assess and finalize the Clinical Finding Form (CliFF) for each of the 119 medical conditions was provided by physician subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team. Many AI tools such as ChatGPT are excellent at summarizing large amounts of information and the current project was initiated to determine how such tools might streamline laborious processes, e.g., review and summarization of many scientific research publications, to execute key steps more efficiently in the process of developing CliFFs. The process for collecting the evidence which is found in the CliFFs is well documented in the Evidence Library Methods document (ELM; HRP-48036*). Using ELM and the CliFF development instructions as a guideline, a team of developers is leveraging Microsoft Azure AI tools and services along with open-source frameworks, to construct an AI-assisted automated pipeline. This pipeline is designed to search, retrieve, and process the necessary data sources, and ultimately help generate the final version of a CliFF. Currently, the large language model evaluates the relevance of each source material to spaceflights, either as direct evidence or as an analog. Additionally, the model assists in extracting keywords and generating brief summaries to enhance augmented retrieval and search processes in later stages of CliFF development. Once the data is ready, the model can perform semantic search and retrieval, generating and extracting valuable information for the CliFF. For instance, it can handle epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. The steps that required reading and summarizing articles were viewed as providing the greatest return on investment since large language models are very efficient and accurate in summarizing large amounts of text. Since labor effort to complete the original CliFF was not recorded with sufficient granularity, comparisons with an AI tool-generated CliFF will provide merely an approximation of time saved. Upon completion of the process, the CliFF for the medical condition “appendicitis” generated with the support of AI-based methods will serve as a proof-of-concept and will be compared to the original appendicitis CliFF to determine if use of the tools resulted in content and conclusory similarity. Based upon the results from face validation of the two CliFFs, modifications to the process will be made if necessary and additional condition CliFFs will be evaluated. Ultimately, CliFFs for the entire set of medical conditions will be created with the assistance of AI tools. Depending on the cost savings realized, CliFFs for additional medical conditions can be created to expand the Evidence Library. Future direction includes specifying the characteristics of the reviewer (prompting the AI tools to generate output assuming the reviewer is a sub-specialist physician, or nurse or EMT/medic) to determine if the effects on AI-generated output are different based on knowledge, skills and abilities. *Exploration Medical Capability Evidence Library Methods, HRP-48036 Rev A, July 2022.

Ali Al↗