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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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CCSDS White Paper for BPv7 Red Book Discussion Topics
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The JAGWAR Prowls LIGO/Virgo O3 Paper I: Radio Search of a Possible Multimessenger Counterpart of the Binary Black Hole Merger Candidate S191216ap
We present a sensitive search with the Karl G. Jansky Very Large Array for the radio counterpart of the gravitational wave candidate S191216ap, which is classified as a binary black hole merger and suggested to be a possible multimessenger event, based on the detection of a high-energy neutrino and a TeV photon. We carried out a blind search at C band (4–8 GHz) over 0.3 deg2 of the gamma-ray counterpart of S191216ap reported by the High-Altitude Water Cerenkov Observatory (HAWC). Our search, spanning three epochs over 130 days of postmerger and having a mean source-detection threshold of 75 μJy beam−1 (4σ), yielded five variable sources associated with active galactic nucleus activity and no definitive counterpart of S191216ap. We find <2% (3.0% ± 1.3%) of the persistent radio sources at 6 GHz to be variable on a timescale of <1 week (week–months), consistent with previous radio variability studies. Our 4σ radio luminosity upper limit of ∼1.2 × 1028 erg s−1 Hz−1 on the afterglow of S191216ap, within the HAWC error region, is 5–10 times deeper than previous binary black hole (BBH) radio afterglow searches. Comparing this upper limit with theoretical expectations given by Perna et al. for putative jets launched by BBH mergers, for on-axis jets with energy ≃1049 erg, we can rule out jet opening angles ≲ 20° (assuming that the counterpart lies within the 1σ HAWC region that we observed).
NASA Deep Space Network Commitments for Human Missions to the Moon and Beyond: Paper 1530
No abstract provided
SCaN Quantum Briefing - Conference Paper
This preface and the following four talks are meant to Give an overview of NASA-SCaN quantum comm. program, Highlight the new drive, Outline the vision, Stress the active pursuit of partnerships.
TFAWS Active Thermal Paper Session: Europa Clipper Thermal Subsystem Overview
No abstract provided
TFWAS Interdisciplinary Paper Session: Ultrasonic Additive Manufacturing (UAM) of Liquid Cold Plate Heat Exchangers for NASA Thermal Management Applications
No abstract provided
Space Grant Final Paper
The purpose of this internship was to begin the development of an APK that would subscribe to NavCam and video stream via UDP. This project involved having the Astrobee Robot Software installed, the Astrobee Android Repository, and the use of an android emulator. While the final APK currently cannot stream via UDP, it can still subscribe to the topic, which for me was already a challenge.
Recommendations from the ISWAT G3 Surface Charging Paper
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Snow4Flow: Concept Paper for a NASA Earth Venture Suborbital-4 Investigation
Snow4Flow was proposed as a large ($30M cost cap) Earth Venture Suborbital (EVS-4) mission in April 2023 and selected as such in April 2024. It will commence pending an Investigation Confirmation Review in 2025. Its airborne and ground campaigns are presently expected to occur in March–May 2027–2029. Quantifying the ongoing retreat of glaciers and ice sheets – and projecting their futures – are major societal concerns due to their contribution to sea-level rise and influence on water resources, natural hazards, and associated socioeconomic impacts. The ability to confidently project glacier and ice-sheet mass change is limited by a severe lack of observations that reliably constrain both their input (Snow) and output (Flow) mass fluxes. Snow4Flow will capture the spatial variability in snow accumulation and ice volume across 4 Northern Hemisphere (NH) regions containing hundreds of rapidly changing glaciers to deliver more reliable, societally relevant projections of land-ice change. This major advance requires spatially extensive radar-sounding surveys that are not possible from orbit (Fig. 1). This EVS-4 mission will drive foundational improvements to NH land-ice boundary conditions and forcing data – including orographic precipitation patterns in alpine environments, ice thickness and subglacial topography – and directly leverages them into state-of-the-art models and projections. Our key science questions are: 1. How will NH glaciers respond to climate change through the end of the 21st century? 2. How does snow accumulation vary in regions of high topographic relief?
Performance Optimization for Lunar Extravehicular Activity Readiness (POLAR) Study: Methods Paper
To better understand which aspects of physical fitness may be most related to performance during Lunar surface operations and thereby help to inform the current NASA fitness standards, much can be learned from fields encompassing the “tactical athlete.” Other physically demanding professions such as law enforcement, military, or rescue professionals often require candidates to meet occupationally-relevant fitness standards. The determination of such standards is a multistep process, including both objective and subjective measures, to determine tasks essential to occupational performance and identify the minimal fitness profile needed to meet physical demands of the job. Notably, fitness is only one component which may contribute to the demands of astronaut selection, flight assignment, and occupational performance. Utilizing a framework to systematically determine which domains of fitness most contribute to relevant job tasks can aid in the refinement of current NASA-STD-3001 fitness standards. Therefore, NASA’s Exercise Physiology & Countermeasures Laboratory conducted the Performance Optimization for Lunar Extravehicular Activity Readiness (POLAR) study to identify and examine a comprehensive list of fitness tests (including NASA-STD-3001 assessments: 1-Repetition Maximum [1-RM] bench press and deadlift) and determine preliminary relationships between identified fitness parameters and novel Artemis-relevant tasks to help inform future investigations for the continued development of aerobic and muscular fitness standards for surface EVAs. This was accomplished through 1) a review of the literature relating fitness assessments to simulated or real EVA performance to identify fitness tests that are most correlated with simulated EVA task performance; 2) a task analysis following a modified framework for physical employment standards development to down select mission critical tasks; and 3) development and pilot testing of a novel, portable Artemis-relevant EVA task circuit to relate to a battery of fitness assessments. The current report describes the methodology used to complete the task analysis, EVA task circuit development, and the pilot study.
Scalable Low-Cost Fabrication of Disposable Paper Sensors for DNA Detection
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Will AI write scientific papers in the future?
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Hydroponics for plant cultivation in space – a white paper
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Issues Regarding the Assimilation of Cloud and Precipitation Data
This is the authors' response to a set of criticisms regarding a previously published work. It briefly addresses the main criticisms. In particular, it explains why some papers identified as having some fundamental flaws were referenced in the original work without detailed exposition of those flaws. It also explains why parts of the conclusion criticized as being contradictory are, in fact, not. It further highlights the need for more publishing of scientific criticisms. In the December 2007, special issue of the Journal of Atmospheric Sciences devoted to the Workshop on Assimilation of Satellite Cloud and Precipitation Observations, the authors published an article summarizing the many critical issues that render observations of cloud and precipitation difficult to analyze. Essentially, these include the inaccuracies of both current instruments and the relationships between what is actually observed (infrared or microwave energy detected at the altitude of the satellite) to what is desired (e.g., estimates of cloud drop sizes or rain rates) and the chaotic nature of atmospheric behavior and the complex mathematics describing it. The paper also included recommendations for future research and brief descriptions of many previous works concerning the subject. One reader is now attempting to publish a criticism of that paper. Her three complaints are that there was insufficient explanation of the identification of some cited works as being fundamentally flawed, that as a review the paper should have referenced some works additional to those it did, and that two recommendations were contradictory. Each of these complaints is addressed briefly in this response. First we explain why a brief list of works cited in our paper were identified as "flawed" with only a brief explanation. The design and conduct of the experiments reported in those papers violate well-established fundamentals such that, once the errors are recognized, their interpretations are no longer supported. Unfortunately, over the years, no researchers have bothered to publish criticisms of those papers, such that there are now too many to address in any single paper not devoted to that purpose. Yet, those papers are so often cited that we could not simply ignore them. Furthermore, if we had cited them without warning our readers regarding their flaws, we would have perpetrated a great disservice. In our response, however, we do offer further explanation of why some details, neglected in these papers, are critical to proper scientific evaluation. Neither did we offer insufficient references. Although we intentionally did not claim to be a "review' paper, we did cite 100 papers. That number is approximately 5 times the usual amount cited in journal articles. Although we only referenced few papers published after 2005, that was because our manuscript was submitted in January 2006, with its final, editorially-reviewed form in June 2006. We therefore could not reference papers published after this date. The problem here is that our paper was "in press" for 18 months. Finally, we explain that a careful reading of our paper reveals that our recommendations are not contradictory. Essentially, although we recommend 2 very distinct research approaches, these are complimentary and either alone is insufficient to accelerate progress. In conclusion, we recommend that the scientific community expends greater effort in publishing careful scientific criticisms so that others do not face the same dilemma we did. Likely this requires some reward system for doing so.
Application of ML/AI for Identifying Earth Science Datasets in Research Publications
NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).