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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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At least 415 records · Page 23
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NASA NTRSDate not supplied

Heliospheric energetic particle transport: Analysis of near-field-aligned particle propagation for SEP events observed by Wind and MAVEN

Magnetic field alignments of spacecraft over large distances in the heliosphere are rare and are usually very limited in duration. Cruise phases of planetary transfers, however, are an exception to this rule, given the Hohmann-Parker effect. The transfer of the MAVEN s/c in 2014 is one such example. Multiple (~10) solar particle events occurred and were detected at both MAVEN and the Wind s/c, originating from solar activity near the foot points of both s/c. We show initial analysis results of the data collected by the solar wind and energetic particle instruments on both s/c while they were more than 0.2 AU apart, but practically Parker field aligned. Using a 1D model, we present initial simulations in qualitative agreement with energetic electron measurements. Next step is to implement the 2D model with approximate particle release from the Sun, and transport durations between Sun, Earth, and MAVEN. We will discuss implications for this data-model comparison, including the possibility to constrain particle scattering inside 1 AU, as well as its radial dependence between Earth and MAVEN.

Solar Energetic Particles↗
NASA NTRS2023

Large Photospheric Doppler Shift in Solar Active Region 12673: I. Field-Aligned Flows

Delta (δ) sunspots sometimes host fast photospheric flows along the central magnetic polarity inversion line (PIL). Here we study the strong Doppler shift signature in the central penumbral light bridge of solar active region NOAA 12673. Observations from the Helioseismic and Magnetic Imager (HMI) indicate highly sheared, strong magnetic fields. Large Doppler shifts up to 3.2 km s −1 appeared during the formation of the light bridge and persisted for about 16 hours. A new velocity estimator, called DAVE4VMwDV, reveals fast converging and shearing motion along the PIL from HMI vector magnetograms, and recovers the observed Doppler signal much better than an old version of the algorithm. The inferred velocity vectors are largely (anti-)parallel to the inclined magnetic fields, suggesting that the observed Doppler shift contains significant contribution from the projected, field-aligned flows. High-resolution observations from the Hinode/Spectro-Polarimeter (SP) further exhibit a clear correlation between the Doppler velocity and the cosine of the magnetic inclination, which is in agreement with HMI results and consistent with a field-aligned flow of about 9.6 km s −1 . The complex Stokes profiles suggest significant gradients of physical variables along the line of sight. We discuss the implications on the δ-spot magnetic structure and the flow-driving mechanism.

Solar active region magnetic fields↗
NASA NTRS2024

Alignment of NASA’s Human System Risks with Technological Capability Gaps to Enable Integrated Research and Technology Development Strategic Planning

BACKGROUND: Radiation, reduced gravity, distance from earth, isolation and confinement, and habitation within artificially created and controlled life support environments are hazards that present risk to human space explorers. NASA’s Human System Risk Board (HSRB) maintains a set of twenty-nine different Human System Risks with subject matter experts from across the agency providing regular updates to the estimated likelihood and consequence associated with each risk. The Human Research Program (HRP) has historically used these risk classifications as a primary basis for identifying and prioritizing human research investments aimed at characterizing and/or mitigating the respective human system risks. In many cases, technology development is required to mature and validate risk mitigation strategies, however, NASA’s primary technology development programs have not typically used Human System Risks as a basis for strategic planning. A primary function of the Environmental Control and Life Support Systems (ECLSS) – Crew Health and Performance (CHP) System Capability Leadership Team (SCLT) is to continually identify, review, and update technological capability gaps and to establish and oversee multiyear strategic roadmaps aimed at guiding NASA’s technology development priorities in these areas. These roadmaps are intended to be agency-wide and independent of any program, directorate, or other organization within NASA. DESCRIPTION: The SCLT and HRP collaborated to establish a set of Human System Capability Gaps, which establish a formal linkage between the capability gaps used to prioritize investments across much of NASA, and the Human System Risks that are primarily used to inform and prioritize human research. This set of twenty-eight gaps was developed by subject matter experts, and each gap mapped to the primary associated Human System Risks. The gaps and risk mapping were then reviewed and approved via the HSRB, thereby formally aligning the research-focused Human System Risks with the technology-focused capability gaps. DISCUSSION: This effort has enabled development of integrated roadmaps and budget coordination with research and technology development activities that are formally linked to agency-recognized capability gaps and Human System Risks. Close and ongoing coordination between the SCLT, HRP, Mars Campaign Office, and the Health & Medical Technical Authority (HMTA) is essential to ensure alignment and prioritization of CHP-related research and technology development to enable NASA’s future exploration missions.

Andrew F J Abercromby↗
NASA NTRS2024

A Fair, Economically-Efficient, Incentive-Aligned, Scalable Airspace Auction Mechanism for UAV Traffic Management

Unmanned Aerial Vehicles (UAVs) are increasingly used in a wide range of applications such as cinematography, package delivery, and surveying. As a result, regulators have become interested in developing UAV Traffic Management (UTM) systems to coordinate UAV traffic. One possible framework for UTM is a combinatorial auction. Under this framework, airspace is modeled as a grid of space-time cells. UAV operators bid on sets of cells which collectively form flight paths for their UAVs. An ideal airspace auction should: be fair, be incentive-aligned, be scalable, allocate airspace economically-efficiently, enable price discovery, and reduce the work required to participate where possible. In this paper, we propose the first auction mechanism for airspace allocation that meets the criteria above. Our mechanism: (a) is provably economically-efficient, fair and incentive-aligned, (b) shares pricing information with bidders and (c) has features which reduce the burden of participating. We evaluate our mechanism on scenarios based on a Japan Aerospace Exploration Agency (JAXA) case study and find that it can scale to 26,000 bids.

Robert Allan Morris↗
NASA NTRSDate not supplied

Machine Learning Algorithms for Alignment Verification of the Roman Space Telescope

The Nancy Grace Roman Telescope is a NASA observatory designed to unravel the secrets of dark energy and dark matter, search for and image exoplanets, and explore many topics in infrared optics. Scheduled to launch no earlier than October 2026, this 2.4 meter aperture telescope has a field of view 100 times greater than the Hubble Space Telescope. The mission is currently in its construction phase, where the telescope and its two instruments will soon be aligned together to ensure proper pupil matching. To help verify this alignment, multiple point sources above the entrance pupil of the telescope will illuminate the optical path through the telescope-instrument system, and shadows of various obstructions in the system will be analyzed using machine learning algorithms to determine the pupil matching error. This presentation discusses the test approach and the machine learning algorithms employed, as well as our uncertainty predictions based on a modeled Monte-Carlo analysis of the test.

Telescope↗
NASA NTRSDate not supplied

STARscan: Spatial Targeting and Alignment Rig for Scanning

The Spatial Targeting and Alignment Rig for Scanning (STARScan) is a 3D photogrammetry system developed at NASA Ames Research Center to address bottlenecks in pre/post-test scanning of arcjet test articles. It reduces scan time from 15 minutes with handheld laser scanners to under 2 minutes, while maintaining high accuracy (±0.2-0.5 mm). STARScan integrates an array of cameras, a 3D-printed rack, turntable, and LED light panels, all controlled via a user-friendly graphical user interface (GUI). The system offers tools for scan visualization, mesh analysis, and data export, automating tasks such as alignment of pre/post-test scans, material recession measurements, surface roughness assessment, and curvature analysis. By integrating scanning, imaging, and post-processing into one application, STARScan significantly improves efficiency in scanning and analyzing arcjet test samples.

Ablation↗
NASA NTRSDate not supplied

Natural Language Processing for Extracting Rich Disease Data Aligned To Satellite Meteorological Data

Global climate change is redefining our understanding of how diseases spread. In Sri Lanka, vector-borne diseases such as dengue fever, encephalitis, and leptospirosis historically surged during the monsoon seasons when temperatures were high enough for mosquito eggs to hatch. Unfortunately, due to rising temperatures and more erratic rainfall patterns, mosquito eggs can now hatch year-round and are increasingly unpredictable, leading to an alarmingly increasing number of hospitalizations and deaths. More data is needed to adapt our response to these diseases in an increasingly warmer world. In the contemporary landscape, a wealth of disease information is available, yet accessibility remains limited due to unstructured data formats such as PDFs. Therefore, converting unstructured disease reports into structured formats is necessary for effectively leveraging data. This paper introduces a comprehensive framework for collecting unstructured disease reports and transforming them into analyzable formats. By creating separate models tailored to each data format, we can ensure accuracy compared to general models. These straightforward models enhance accessibility and empower other researchers to use our tools. The returned structured data can then be harnessed for analysis, statistical purposes, and informing evidence-based public health interventions, thus facilitating more informed decision-making in healthcare. We deploy this framework to produce geospatial data for Sri Lanka and Brazil for many different conditions and align these data with satellite environmental data, providing for the first time a structured, aligned powerful dataset for disease modeling.

Open Source Open Science↗
NASA NTRSDate not supplied

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.

Paul D Mckee↗
NASA NTRSDate not supplied

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.

Paul McKee↗
NASA NTRS2024

SOLES XII. The Aligned Orbit of TOI-2533 b, a Transiting Brown Dwarf Orbiting an F8-type Star

Brown dwarfs occupy a middle ground in mass space between gaseous giant planets and ultracool dwarf stars, and the characterisation of their orbital orientations may shed light on how these neighbouring objects form. We present an analysis of the Rossiter–McLaughlin effect across the transit of TOI-2533 b, a brown dwarf on a moderately eccentric (e b = 0.2476 ± 0.0090) and wide-separation (a b /R ⋆ = 13.34 ± 0.30) orbit around an F8-type star, using data from the NEID/WIYN spectrograph in combination with archival photometry and radial velocity observations. Spin-orbit analyses of brown dwarfs are relatively rare, and TOI-2533 stands out as the fifth brown dwarf system with a measured spin–orbit constraint. We derive a sky-projected stellar obliquity of λ = −7° ± 14° for TOI-2533 b, finding that the brown dwarf is consistent with spin–orbit alignment. Our joint model also indicates that TOI-2533 b falls near the lower bound of the hydrogen-burning minimum mass range (M b = 74.9 ± 5.3 M Jup ). Ultimately, we find that TOI-2533 b is consistent with formation from disc fragmentation in a primordially spin–orbit aligned orientation, although we cannot rule out the possibility that the system has been tidally realigned during its lifetime.

Thiago Ferreira dos Santos↗
NASA NTRS1966

Azimuth axis optical alignment system Final report

Azimuth axis optical alignment system to monitor and measure attitude or angular position of remote object about azimuth axis using phase information imposed on returning beam of light

POLARIZED LIGHT↗
NASA NTRS2011

Alignment and Characterization of High Uniformity Imaging Spectrometers

Imaging spectrometers require precise adjustments, in some cases at the sub-micrometer level, in order to achieve auniform response over both the spectral and spatial dimensions. We describe a set of measurement techniques and theircorresponding alignment adjustments to achieve the 95% or higher uniformity specifications required for Earthobservingimaging spectrometers. The methods are illustrated with measurements from the Next Generation Imaging Spectrometer system that has been built at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Offner spectrometer↗
NASA NTRS2018

Alignment and Testing for a Freeform Telescope

Currently there is a strong desire to make Earth science less expensive. Freeform optics make these missions less expensive because they allow an optical designer to use fewer mirrors to create roughly the same effect. The main issue with using freeforms is how closely the substrate can be milled to its prescription. Over this summer, our team looked at two freeforms made by Corning Inc. using a brand new process to determine how close these optics are to their set prescriptions and how well NASA could align them.

Alignment↗
NASA NTRS2024

Calculating the High-Latitude Ionospheric Electrodynamics Using A Machine Learning-Based Field-Aligned Current Model

We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML-AIM). ML-AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020, https://doi.org/10.1029/2020JA027908), the FAC-derived auroral conductance model of Robinson et al. (2020, https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993, https://doi.org/10.1029/92gl02109). The ML-AIM inputs are 60-min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML-AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML-AIM produces physically accurate ionospheric potential patterns such as the two-cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML-AIM, the Weimer (2005, https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data-assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML-AIM than others. ML-AIM is unique and innovative because it predicts ionospheric responses to the time-varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005, https://doi.org/10.1029/2004ja010884) designed to provide a quasi-static ionospheric condition under quasi-steady solar wind/IMF conditions. Plans are underway to improve ML-AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.

auroral electrodynamics↗