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NASA NTRS2022

Directed Acyclic Graph Guidance Documentation

For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks to astronaut health and performance that occur before, during and after spaceflight. The Human System Risk Board (HSRB), a Health and Medical Technical Authority (HMTA) Board at NASA Johnson Space Center, is the entity responsible for identifying, assessing, analyzing, and monitoring the official understanding of the risk or risk posture for each of the Human System Risks and determining – based on evaluation of the available evidence – when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce the risk that astronaut crews face during spaceflight. Historically, research, development and operations relevant to one risk have been conducted in isolation from other risks; these individual risk ‘silos’ enabled initial characterization of each specific risk. In spaceflight however, the impact of exposure to risk for astronaut crews is cumulative, and not independent of exposures or other risks, as all the adverse effects of the spaceflight environment begin at launch, continue throughout the duration of the mission and in some cases across the lifetime of the crews. In January of 2020, the HSRB at NASA embarked on a pilot project designed to assess the potential value of causal diagramming as a tool to facilitate understanding these cumulative and interdependent effects as applied within Human System Risk management. This process uses directed acyclic graphs as a means of formalizing a shared mental model of the causal flow of risk among Risk Board stakeholders. Initially this model was to improve communication among those stakeholders, but the potential value exceeds communication alone. Formalization of the process for creating these causal diagrams will enable the creation of a composite risk network that is vetted by members of the NASA community and configuration managed. The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. This document outlines the pilot process, the standardized approaches, and guidance for risk custodian teams when creating and updating DAGs as a part of the NASA Human System Risk Management process.

Risk↗
NASA NTRS2022

Directed Acyclic Graphs: A Tool for Understanding the NASA Human Spaceflight System Risks - Human System Risk Board

For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks to astronaut health and performance that occur before, during and after spaceflight. The Human System Risk Board (HSRB), a Health and Medical Technical Authority (HMTA) Board at NASA Johnson Space Center, is the entity responsible for identifying, assessing, analyzing, and monitoring the official understanding of the risk or risk posture for each of the Human System Risks and determining – based on evaluation of the available evidence – when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce the risk that astronaut crews face during spaceflight. Historically, research, development and operations relevant to one risk have been conducted in isolation from other risks; these individual risk ‘silos’ enabled initial characterization of each specific risk. In spaceflight however, the impact of exposure to risk for astronaut crews is cumulative, and not independent of exposures or other risks, as all the adverse effects of the spaceflight environment begin at launch, continue throughout the duration of the mission and in some cases across the lifetime of the crews. In January of 2020, the HSRB at NASA embarked on a pilot project designed to assess the potential value of causal diagramming as a tool to facilitate understanding of these cumulative and interdependent effects as applied within Human System Risk management. This process uses directed acyclic graphs as a means of formalizing a shared mental model of the causal flow of risk among Risk Board stakeholders. Initially this model was to improve communication among those stakeholders, but the potential value exceeds communication alone. The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. This document is a sister document to NASA/TM 20220006812 Directed Acyclic Graph Guidance Documentation (1). In that document, the basic guidance for creating and standardizing directed acyclic graphs as tools for cross-risk analysis is provided. This document contains the initial configuration managed DAGs that were created as a result of applying those principles. These initial versions were accepted by the HSRB in January of 2022. Each of the Human System Risks are represented by a DAG that has been reviewed by the larger Human Health and Performance community at NASA including life scientists, physical scientists, physicians, nurses, pharmacists, exercise specialists and more. These results show the starting point for Human System Risk DAGs as shared mental models and communication aids across the boundaries of the various expertise needed to understand and mitigate the human risks in spaceflight. Because they are a starting point, each of these DAGs can be expected to change over time as new or refined evidence becomes available. The process for updating these DAGs can be found in the JSC-66705 Human System Risk Management Plan (2) that is publicly available on the NASA Technical Reports Server.

Erik L. Antonsen↗
NASA NTRS2024

Redundancy: How Many Unreliable Spares are Needed for High Reliability and Confidence?

This paper investigates the number of redundant units needed to achieve high reliability with high confidence. The approach is developed for the case when the system failure rate is too high for a single unit to provide the required reliability over the mission duration. To achieve high reliability, N redundant units can be used, one operating unit and N – 1 spares. If the unit failure rate is f, the mission length is L, and f * L is small (not the case assumed here), the unit failure probability over the mission duration is F1 = f * L << 1. In this case, the probability that all N units will fail is Ffail = F1 N , and the needed redundancy N = LN(F)/LN(F1). For the case of large f * L assumed here, F1 = f * L > 1, and F1 is the expected number of failures during the mission. (When F1 = f * L << 1, F1 is the probability that a unit will fail during the mission. When F1 = f * L > 1, F1 is the expected number of failures during the mission.) The needed redundancy, N, to achieve the required N redundant unit reliability, FN, can be computed using the cumulative Poisson distribution with mean equal to F1. The number of spares, N - 1, is increased until the probability - that the total number of failures will be less than N -1 - is equal to the required reliability. The confidence that this reliability can be achieved can be computed using the cumulative Poisson distribution or the chi-square distribution. Since the measured unit failure rate, f, has some probabilistic uncertainty, the actual failure rate will be randomly higher or lower. This means that the reliability of the N redundant systems will be overestimated about half the time. Adding more redundant units increases the confidence that the required reliability will be achieved. For a fixed number of redundant units, the expected reliability and confidence can be traded off, since lower reliability goals will be achieved with higher confidence. Both the desired reliability and confidence can be specified as initial requirements and the needed number of redundant units estimated using the measured failure rate.

Redundancy↗
NASA NTRS2023

A New View of the Lunar South Pole from the Lunar Orbiter Laser Altimeter (LOLA)

Upcoming missions to the lunar south pole require detailed maps over large areas to fully characterize landing sites locally and regionally and to place their data into proper geologic context. To that end, we enhanced the Lunar Orbiter Laser Altimeter (LOLA) altimetry dataset for the south polar region, from which we produced new maps of topography, topographic roughness, and permanently shadowed regions (PSRs). The roughness maps reveal a diversity of terrains characterized by hectometer-scale roughness which is controlled in this region primarily by cratering and downslope mass transport. The south polar region is littered with linear roughness features of order ~1 – 10 km wide and ~10s – 100s of km long hypothesized to be secondary impacts within extended ejecta rays. Non uniformities in these features could reflect variations in secondary impactor properties and/or target terrain properties. Poleward of 80° S, the PSR cumulative size-frequency distribution (CSFD) shows an approximately power-law behavior whose exponent has a spatial variation of ~10%. PSRs with areas < 1 km2 contain 15 ± 5% of the total PSR area. Finally, we studied the effect of false positives and false negatives on the accuracy of the measured PSR cumulative size-frequency distribution (CSFD) and on the area for any individual PSR. The new maps presented here have many applications in the science and exploration of the lunar south polar region, such as geologic mapping and traverse planning.

Michael K. Barker↗
NASA NTRS2024

Evaluating Precipitation Events Using GPM IMERG 30-Minute Near Real-Time Precipitation Estimates

Accurately detecting and estimating precipitation at near–real time (NRT) is of utmost importance for the early detection and monitoring of hydrometeorological hazards. The precipitation product, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), provides NRT 0.1° and 30-min precipitation estimates across the globe with only a 4-h latency. This study was an evaluation of the GPM IMERG version 6 level-3 early run 30-min precipitation product for precipitation events from 2014 through 2020. The purpose of this research was to identify when, where, and why GPM IMERG misidentified and failed to detect precipitation events in California, Nevada, Arizona, and Utah in the United States. Precipitation events were identified based on 15-min precipitation from gauges and 30-min precipitation from the IMERG multisatellite constellation. False-positive and false-negative precipitation events were identified and analyzed to determine their characteristics. Precipitation events identified by gauges had longer duration and had higher cumulative precipitation than those identified by GPM IMERG. GPM IMERG had many false event detections during the summer months, suggesting possible virga event detection, which is when precipitation falls from a cloud but evaporates before it reaches the ground. The frequency and timing of the merged passive microwave (PMW) product and forward propagation were responsible for IMERG overestimating cumulative precipitation during some precipitation events and underestimating others. This work can inform experts that are using the GPM IMERG NRT product to be mindful of situations where GPM IMERG–estimated precipitation events may not fully resolve the hydrometeorological conditions driving these hazards.

Jessica R P Sutton↗
NASA NTRS2024

Flaring Activity for Low-mass Stars in the β Pictoris Moving Group

Stellar flares from K and M dwarfs release panchromatic radiation characterized by a significantly higher brightness temperature (∼9–20 kK) than the star. The increased frequency of magnetic activity on young low-mass stars results in the energy released during flaring events becoming a notable contributor to the radiation environment. This study focuses on the β Pictoris moving group (βPMG; 24 ± 3 Myr) for the analysis of young low-mass star flaring rates within the framework of larger flare studies. The calibration of long-term optical flare statistics is crucial to updating flare activity–age relations and the interpretation of exoplanet atmosphere observations. Using the βPMG, we develop a modular flare-extraction pipeline sensitive to low-mass stellar flares in observations from the Transiting Exoplanet Survey Satellite (TESS). This pipeline is built to characterize the flare properties of these stars such as total energy and cumulative flare rate. Consistent with previous studies, this sample (N = 49) shows higher cumulative flare rates than early-type and old field stars by at least an order of magnitude. Fitted flare frequency distributions for both early- and late-type M dwarfs show an average slope of 1.58 ± 0.23, with earlier stars flaring with lower or similar rates to late types. A typical member in this sample has daily (∼1 day−1) flares with TESS band energies of 1032–1033 erg. The optical flare rates and energies for this group provide essential context into the coevolution of host stars and associated planets.

Jordan Ealy↗
NASA NTRS2003

Simple gain probability functions for large reflector antennas of JPL/NASA

Simple models for the patterns as well as their cumulative gain probability and probability density functions of the Deep Space Network antennas are developed. These are needed for the study and evaluation of interference from unwanted sources such as the emerging terrestrial system, High Density Fixed Service, with the Ka-band receiving antenna systems in Goldstone Station of the Deep Space Network.

large reflector antenna probability density functi↗
NASA NTRS2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗
NASA NTRS1960

Aerospace medicine and biology. an annotated bibliography, 1954 literature, volume iii

While this third volume of the bibliography was in preparation, a number of changes and new developments took place which, it is hoped, will be instrumental in furthering the bibliography's main objective: to provide as rapidly as possible comprehensive coverage of the aerospace-medical and bio-astronautical literature. To begin with, it will be noted that the title of the compilation has been changed from Aviation Medicine to Aerospace Medicine and Biology. This will bring into relief the fact that the general subject scope of the bibliography has been expanded to include new areas of interest in space-medical and space-biological research. Thus, to the subject fields heretofore covered by the bibliography (a full listing of which may be found in the Preface to Volume 2) new ones have been added, such as Biological Rhythms, Biological Orientation, Closed Ecological Systems, Physiological and Psychological Effects of Heat, Cold, Isolation, Restraint, and many others. Another important change was administrative in nature. Sponsorship of the bibliography for the fiscal year 1959/60 was taken over by the U. S. Advanced Research Project Agency (ARPA), the U. S. Aeronautics and Space Administration (NASA), and the Defense Research Board of Canada. Under a substantially increased budget, the Library of Congress was enabled to produce two volumes during the fiscal year. The Library also agreed to prepare selected abstracts from the current aerospace and bio-astronautic literature, which are published monthly in Aerospace Medicine, the official organ of the Aerospace Medical Association.*) If the present rate of production can be maintained, it will be possible to bring the bibliography up to date within about three years. In format, style, and arrangement, this volume follows closely the preceding ones. References are arranged alphabetically by author; abstracts are informative; and full bibliographic information is provided, including foreign and translated titles, volume and issue numbers, place of publication (if foreign), inclusive paging, full dates, and library call numbers or other location symbols. While the bulk of the publication is devoted to journal articles, reports, and monographs published during the year 1954, items published in 1952 or 1953 not included in the preceding volumes have been incorporated in this volume. For quick identification, the publication years of these off-year references have been printed next to the first author's name. As before, cumulated corporate and secondary author and subject indexes are included, the latter being revised and enlarged considerably, in keeping with the over-all expansion of subject scope.

Aerospace medicine↗
NASA NTRS1965

An approach to metal fatigue

Cumulative fatigue damage based on investigation of fatigue limit associated with crack, crack propagation rate, and stress interaction cycle in metals

CRACK PROPAGATION↗
NASA NTRS1967

Computer program reduces calculation time of normal response functions

FORTRAN 2 computer program rapidly calculates parameters of maximum likelihood estimates from sensitivity experiment data populations. The program uses the Newton-Raphson iterative procedure to calculate the mean and standard deviation of portions of the cumulative normal response function.

Alexander, M. J.↗