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At least 415 records · Page 23

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NASA NTRS2017

Monocrystalline Silicon and the Meta-Shell Approach to Building X-Ray Astronomical Optics

Angular resolution and photon-collecting area are the two most important factors that determine the power of an X-ray astronomical telescope. The grazing incidence nature of X-ray optics means that even a modest photon-collecting area requires an extraordinarily large mirror area. This requirement for a large mirror area is compounded by the fact that X-ray telescopes must be launched into, and operated in, outer space, which means that the mirror must be both lightweight and thin. Meanwhile the production and integration cost of a large mirror area determines the economical feasibility of a telescope. In this paper we report on a technology development program whose objective is to meet this three-fold requirement of making astronomical X-ray optics: (1) angular resolution, (2) photon-collecting area, and (3) production cost. This technology is based on precision polishing of monocrystalline silicon for making a large number of mirror segments and on the meta-shell approach to integrate these mirror segments into a mirror assembly. The meta-shell approach takes advantage of the axial or rotational symmetry of an X-ray telescope to align and bond a large number of small, lightweight mirrors into a large mirror assembly. The most important features of this technology include: (1) potential to achieve the highest possible angular resolution dictated by optical design and diffraction; and (2) capable of implementing every conceivable optical design, such as Wolter-I, Wolter-Schwarzschild, as well as other variations to one or another aspect of a telescope. The simplicity and modular nature of the process makes it highly amenable to mass production, thereby making it possible to produce very large X-ray telescopes in a reasonable amount of time and at a reasonable cost. As of June 2017, the basic validity of this approach has been demonstrated by finite element analysis of its structural, thermal, and gravity release characteristics, and by the fabrication, alignment, bonding, and X-ray testing of mirror modules. Continued work in the coming years will raise the technical readiness of this technology for use by SMEX, MIDEX, Probe, as well as major flagship missions.

Zhang, William W.↗

NASA NTRS2013

Orbiting Rainbows: Optical Manipulation of Aerosols and the Beginnings of Future Space Construction

Our objective is to investigate the conditions to manipulate and maintain the shape of an orbiting cloud of dust-like matter so that it can function as an ultra-lightweight surface with useful and adaptable electromagnetic characteristics, for instance, in the optical, RF, or microwave bands. 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. See Figure 1 for a scenario of application of this concept. The solution that we propose is to construct an optical system in space in which the nonlinear optical properties of a cloud of micron-sized particles are shaped into a specific surface by light pressure, allowing it to form a very large and lightweight aperture of an optical system, hence reducing overall mass and cost. Other potential advantages offered by the cloud properties as optical system involve possible combination of properties (combined transmit/receive), variable focal length, combined refractive and reflective lens designs, and hyper-spectral imaging. A cloud of highly reflective particles of micron-size acting coherently in a specific electromagnetic band, just like an aerosol in suspension in the atmosphere, would reflect the Sun's light much like a rainbow. The only difference with an atmospheric or industrial aerosol is the absence of the supporting fluid medium. 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 clouds 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 exoplanet 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, exoplanet 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. 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.

Space Construction↗

NASA NTRS2018

High Efficiency Megawatt Motor Conceptual Design

The High Efficiency Megawatt Motor (HEMM) is being designed to meet the needs of Electrified Aircraft Propulsion (EAP). The key objective of this work is to establish a motor technology which simultaneously attains high specific power (>16kW/kg ratio to electromagnetic weight) and high efficiency (>98%) by judicious application of high temperature superconducting wire and integrated thermal management. Another important feature is to achieve the performance goals with an eye to aircraft integration constraints. An electromagnetic analysis was performed which shows that the proposed HEMM design meets the performance objectives if key current capability and mechanical constraints are achieved. Sensitivity of motor power and performance to those parameters is illustrated. The HEMM technology could be applied to a range of aircraft types that require megawatt level electrical power.

Superconducting↗

NASA NTRS2019

High Efficiency Megawatt Motor Preliminary Design

The High Efficiency Megawatt Motor (HEMM) is being designed to meet the needs of Electrified Aircraft Propulsion (EAP). A preliminary design has been completed and risk reduction activities are being conducted in three key areas: cryogenic cooler design, superconducting rotor coil design and manufacturing, and stator thermal management. The key objective of HEMM is to establish a motor technology which simultaneously attains high specific power (>16kW/kg ratio to electromagnetic weight) and high efficiency (>98%) by judicious application of high temperature superconducting wire and integrated thermal management. Another important feature is to achieve the performance goals with an eye to aircraft integration constraints. An electromagnetic analysis was performed which shows that the proposed HEMM design meets the performance objectives if key current capability and mechanical constraints are achieved. The risk reduction activities are the first assessment of the key design features. The HEMM technology could be applied to a range of aircraft types that require megawatt level electrical power.

Jansen, Ralph H.↗

NASA NTRS2018

High Efficiency Megawatt Motor Conceptual Design

Jansen, Ralph H.↗

NASA NTRS2018

Preliminary Aerodynamic Measurements from a Magnetic Suspension and Balance System in a Low-Speed Wind Tunnel

An existing Magnetic Suspension and Balance System (MSBS) has been restored to operation in a small (octagonal test section, 6-inches across flats) low-speed wind tunnel as the first phase of a project to develop new dynamic test capabilities for planetary entry capsules at supersonic speeds. The MSBS and associated wind tunnel were originally designed and built at MIT and were subsequently relocated to NASA Langley Research Center. NASA ceased operations of the system in the late 1990s and it was transferred to Old Dominion University where it had been mothballed until the present work started in 2015. All-new position sensor electronics, electromagnet power supplies, digital controller, and other hardware have been developed, leading to more efficient and reliable operation. Important features of the new hardware will be briefly described. Wind tunnel testing has commenced, focusing first on static aerodynamics of re-entry capsule shapes. Some preliminary results will be reviewed, including comparison to reference data. The proposed extension to dynamic stability testing, using a variety of free-to-pitch approaches will be described. Finally, the preliminary design of the all-new Phase II (supersonic) system will be briefly outlined.

Schoenenberger, Mark↗

NASA NTRS2021

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the-art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts. The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners. However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen Michael Middleton↗

NASA NTRSDate not supplied

A materials-informatics based study of solid electrolytes and protective coatings for Li batteries

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes and protective coatings simultaneously possessing high ionic conductivity and wide electrochemical stability has proven to be a challenge. Here, we present a data-driven approach to explore the Li compound space for promising solid electrolytes and coatings. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds by computing Li+ migration barriers using bond-valence-based pair potentials, and stability windows using density functional theory energies. Using this database, we implement machine learning models that can accurately predict migration barriers and electrochemical stability windows for any new Li compound. Through feature engineering, we ensure that our models are both accurate and interpretable. We perform feature importance analysis on our models to highlight materials properties that can be tuned for future design of coatings/electrolytes. Our database and informatics approach provide a valuable tool for the rapid discovery of new solid-state battery chemistries.

Solid state batteries↗

NASA NTRS1997

Model Correlation for Mars Pathfinder Entry, Descent and Landing Simulation

Two multi-body drop tests were conducted to provide data to calibrate and verify a multi-body dynamics computer model, which was the major analytical tool used to study the entry, descent and landing (EDL) of the Mars Pathfinder mission. A general summary of the tests and important features of the simulation model are presented in this paper. Good correlation between between test results and analytical predictions were achieved.

Mars↗

NASA NTRS1998

New Insights into Coronae Evolution: Mapping on Venus

Coronae are geologically and geophysically important features on Venus, since they are thought to contribute to planetary heat loss. It is thus necessary to understand their role in space and time in the evolution of Venus. We show that the formation of corona annuli can be multistaged and that the position of the annulus does not always coincide with the main topographic ridges and troughs that outline the feature. We demonstrate that coronae do not all have the same relative ages with respect to adjacent units.

coronae↗

NASA NTRSDate not supplied

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts.1,2 The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners.1 However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen M Middleton↗

NASA NTRS2020

Potential vorticity structure of Titan's polar vortices from Cassini CIRS observations

The Cassini mission has provided the best opportunity to date to extensively study the seasonal variation in Titan’s atmosphere, with observations spanning almost half a Titan year (𝐿𝑠 = 293 − 93°). An important feature in the Titan middle-atmosphere is the formation of a polar vortex. Observations have shown that an initially well-developed northern vortex enriched with trace gas species gradually breaks down after spring equinox as a new vortex emerges in southern winter. Here we use Cassini CIRS observations to derive the temperature and composition of the middle-atmosphere. We use the gradient wind equation to first estimate the mean zonal winds, and then the Potential Vorticity (PV) throughout Titan’s atmosphere over the timespan of the Cassini mission. PV is a useful diagnostic quantity for studying the dynamics of polar vortices because it is materially conserved for adiabatic and frictionless flows, and can be inverted to find all other dynamical fields. Our results show the formation of a strong zonal jet in the winter hemisphere, with wind velocities reaching 220 m/s, which is consistent with previous studies. An annular PV structure is also observed over the winter poles, whereby a ring of PV encircles a local minima over the pole. Such distributions are often found to be unstable without a restoring force, yet they are seen here in numerous observations in both the northern and southern hemispheres. A comparison with the annular Martian vortices shows that latent heat release from condensation or subsidence-induced adiabatic heating may explain the origin and stability of the annulus. Finally, we investigate the evolution of the size of the vortices and the role of strong PV gradients as a dynamical mixing barrier for trace gas species across the vortex edge. We find that longer lived gases are less confined to the vortex than those with shorter photochemical lifetimes.

Conor Andrew Nixon↗

NASA NTRS2022

UAV Path Planning for Wildfires - Sustainably Fighting Wildfires with Automated Path Planning for UAVs

As the severity and frequency of wildfires increase, infrastructure, properties, national parks, animal habitats, and human lives (civilians and firefighters) are put at greater risk. This paper examines the possible application of algorithmic path planning for UAV reconnaissance to reduce damage and safety risks, as aforementioned. When the location of a wildfire is known, UAVs are immediately dispatched from an operating base to fly to the fire and support the firefighters as quickly as possible. Then, the algorithm incrementally analyzes different environmental factors to create a path for the UAV to follow. This work focuses on generating a path for the UAV to follow given a set of polygons representing obstacles. The most important features of this algorithm are its fast response time and obstacle maneuverability. The use of an efficient path planning algorithm could potentially save lives, infrastructure, and acres of forest destruction.

UAV↗

NASA NTRSDate not supplied

NASA Alternate Fecal Canister On-orbit Performance and Applicability to Exploration Missions

NASA developed a collapsible canister for the collection and containment of fecal deposits on long range exploration missions as well as on space stations where mass and volume are of great impact on spacecraft and propulsion designs. Developed as an alternative to the exploration toilet hard-sided canister, the container is a smaller volume for stowage in the unfilled state which allows better use of constrained volume on smaller vehicles for longer missions while still providing the important features of odor and solid/liquid contents containment when in the filled state. A reduction in mass was also achieved for the alternate fecal canister itself, although weight of the lid and contents are common to both the hard-side canister, and the alternate fecal canister. Details of the design, flight build and certification, and technology demonstration on ISS will be discussed. The discussion will include interface requirements and design solutions for use with the Universal Waste Management System (UWMS) as well as future extensibility for other toilet systems.

toilet↗

NASA NTRSDate not supplied

Squeezing Every Last 'Bit' of Information from Enceladus Mass Spectrometry

Potential opportunities to return to Enceladus in Discovery and Flagship class missions inspire development of next-generation instruments and creative approaches to sample collection, sample analysis, and data analysis and transmission strategies. Mass spectrometers (MS) are ideally suited to future Enceladus missions due to their analytical power in identifying a range of molecular and ionic compositions – including complex organics – and potentially astrobiologically-important features such as isotope ratios, chirality, and enantiomeric excess. However, long communication delays from Enceladus and limited bandwidth limits the data transmission from these higher-data-volume instruments, likely delaying mission-related response to new data. We explore the utility of data science and machine learning (ML) on isotope ratio (IR)MS data collected from laboratory analogs of Enceladus to: 1) process data quickly for rapid ground-based analyses, 2) understand if compositional and biosignature information could be extracted from IRMS data, and 3) evaluate whether onboard ML techniques could improve sample analysis, cadence, and transmission prioritization. Laboratory analogs analyzed isotopes of volatile CO2 that interacted with seawaters of varying composition, and include both abiotic and biotic (microbially-influenced) experiments. Enceladus’s alkaline oceans promote speciation of carbon into multiple forms (e.g., H2CO3 / CO2, HCO3-, and CO32-), each of which could be isotopically fractionated by abiotic or biotic reactions. Large (>2‰) changes in carbon isotopes (δ13C) are observed from some biotic experiments inoculated with complex microbial ecosystems relative to the abiotic seawaters. ML training and classification suggests that microbial samples can be distinguished from abiotic samples, yet that a broad range of microbial experiments are necessary to train ML models to cover a range of complexities including disequilibria, and isotopic and compositional fractionation.

geochemistry↗

NASA NTRS2023

An Updated Geomagnetic Index-Based Model for Determining the Latitudinal Extent of Energetic Electron Precipitation

Energetic Electron Precipitation (EEP) from the Earth's plasma sheet and the radiation belts is an important feature of atmospheric dynamics through their destruction of ozone in the lower thermosphere and mesosphere. Therefore, understanding the magnitude of the atmospheric impact of the Sun-Earth interaction requires a comprehensive understanding of the intensity and location of EEP. This study improves the accuracy of a previous pressure-corrected Dst model that predicts the equatorward extent of >43, >114, and >292 keV EEP using the measurements from the Medium Energy Proton Electron Detector detector of six National Oceanic and Atmospheric Administration/Polar Orbiting Environmental Satellites and EUMETSAT/METOP satellites. The improvement is achieved through multiple linear regression of pressure-corrected Dst and pressure-corrected Ring Current (RC) indices. The RC index mitigates the baseline variation of the Dst index that created an inherent solar cycle bias in the previous model. The new model is then extended to the Southern Hemisphere (SH) after removing the South Atlantic Anomaly longitudes from the data. More than 80% of the residuals lie within ±1.8° Corrected Geomagnetic Latitude (CGMLat) in the Northern Hemisphere and within ±1.98° CGMLat in the SH.

E. M. Babu↗

NASA NTRSDate not supplied

Diffraction by Sharp Edges of Noncanonical Shape with Mean Flow and Surface Impedance

This paper presents a study on diffraction by sharp edges of noncanonical edge shape in the presence of mean flow and surface impedance, which are important features for aircraft noise but have not been accounted for in previous studies on sharp-edge diffraction. An analytical formula for the diffracted pressure is derived by applying asymptotic analysis to the integral representation of the total pressure scattered by a geometry that contains sharp edges. The asymptotic analysis is presented as a systematic process that can be carried out to any order, if needed. An illustration is given to use a higher-order result to eliminate the singularity in the first-order result to make the solution regular in the entire parameter domain. The formula for the diffracted pressure is validated by experimental data and is applied to parametric studies to reveal the effects of noncanonical edge shape, mean flow and surface impedance, as well as the impact of these effects on the total scattered pressure in the presence of other scattering components.

Yueping Guo↗

NASA NTRSDate not supplied

Scalable Variable Charge Molecular Dynamics Simulations of Metal-Oxide Systems

Interfaces between metals and oxides are an important feature in many technologically relevant materials, e.g., oxidation of metal surfaces, oxide-dispersion strengthened (ODS) alloys, dielectric components, and thermal barrier coatings among others. Experimental studies of such interfaces are challenging since the majority are buried within the bulk, making computational modeling an attractive alternative. Molecular dynamics (MD) simulations operate at the length scales relevant to many interface-mediated mechanisms, but the requisite interatomic potentials for metal-oxide systems require computationally expensive variable charge schemes to account for the disparate bonding types, thus often limiting their effectiveness. Here we introduce several improvements to the charge transfer interatomic potential (CTIP) model which enable greater computational efficiency for large scale MD simulations. Then, using a new CTIP parametrization for the Ni-O system, we demonstrate its capabilities to capture critical atomic scale mechanisms associated with metal-oxide interfaces. Long time scale simulations (>10 ns) are used to investigate high temperature oxidation and oxide precipitation from the melt, and large length scale simulations (> 1 million atoms) are used to study the interaction of dislocations with oxide particles. We have implemented the new CTIP model in the widely used, open-source MD code LAMMPS.

Gabriel Plummer↗