Results for “PANDEMIC MONITORING”

NASA NTRSDate not supplied

Tracking 2020 Decreases in Carbon Dioxide Due to the COVID19 Pandemic in NASA’s GEOS Modeling system: Implications for Space-Based Carbon Monitoring

The COVID19 pandemic led to abrupt, worldwide changes in human activity and related emissions of air pollutants and greenhouse gases that are unprecedented in modern times. NASA satellites have demonstrated their ability to observe some of these impacts, particularly in relation to short-lived gases like nitrogen dioxide (NO2), which is emitted primarily from transportation. Bottom-up analyses of carbon dioxide (CO2) emissions suggest that the growth of atmospheric CO2 has also slowed, but differences are much more subtle than for NO2 because of the lifetime of atmospheric CO2 and sectoral differences in emission reductions. Estimates of CO2 from NASA’s Orbiting Carbon Observatory 2 (OCO-2) provide a unique view of COVID19 impacts, but observed changes in the column-average CO2 can be difficult to interpret because of gaps in spatial coverage. Assimilating these data into the Goddard Earth Observing System (GEOS), an integrated Earth system model with an advanced Constituent Data Assimilation System (CoDAS), helped to reveal changes in CO2 that are consistent with separate, bottom-up analyses of emissions reductions. Both indicate that from February-April of 2020, the growth in CO2 over Europe, North America, and Asia was roughly 0.3 ppm less than during the previous four years. Anomalies derived from gap-filled GEOS OCO-2 CoDAS products contribute to a joint effort by the world’s space agencies to track COVID19 impacts on the Earth. However, attribution of these changes is complicated by interannual variability in atmospheric circulation and the influence of climate on ocean and land carbon sinks. We discuss these results from the perspective of space-based carbon monitoring, which has received considerable support over the past decade from NASA. Our results demonstrate the accomplishments of current sensors and data assimilation systems, but also highlight challenges in providing high quality, low latency information to the public. In particular, understanding and attributing CO2 changes during 2020 requires year-specific information about land and ocean fluxes, which is often delayed for months or even years. We discuss current limitations and potential solutions to address these lags, which would support more reliable and timely space-based carbon monitoring.

COVID-19↗

NASA NTRSDate not supplied

NASA's Professional DEVELOPment - Evaluating 10 Weeks of Capacity Building

Under NASA’s Applied Sciences, the NASA DEVELOP Program is centered on dual capacity building. Projects bring together partners and participants to learn how Earth observation data can enhance environmental decision-making practices and inform action. During their time with DEVELOP, participants build technical skills around remotely sensed data and professional skills through interactions with team members, science advisors, and partners. To further refine the participant experience, DEVELOP explores which technical and professional skills individuals report improving during the 10-week program. An analysis of self-reported assessments from 2018 to 2021 included projects that were conducted in-person and virtually. Participants consistently indicated a strong improvement in technical and professional skills yet there was clear variation between in-person and virtual opportunities. When comparing between 2019 and 2021, self-reporting showed a higher percentage of participants reporting an increase in networking in the virtual environment and an increase in building professional relationships with project partners virtually. This analysis suggests that professional opportunities available in the virtual environment may in fact bolster early career scientists’ networking abilities. This presentation will identify DEVELOP’s approach to monitoring and evaluation, highlight interesting trends introduced by the pandemic, and lessons learned.

Sarah Payne↗

NASA NTRS2024

Herpesviruses in Saliva and Their Clinical Significance

Saliva has been used as a source of biological markers for a wide spectrum of normal and disease states for a long time. It is a non-invasive, easily accessible, and self-collected body fluid that contains a variety of measurable biological substances. While mostly water, saliva also contains ions, carbohydrates, proteins and peptides, exfoliated cells, nucleic acids, and microorganisms. Saliva can reflect tissue levels of some natural substances and a large variety of molecules introduced for therapeutic use, emotional status; hormonal status, immunological status, neurological effects, and nutritional and metabolic status. It can also be used to monitor a variety of drugs including marijuana, cocaine, and alcohol. It is the most cost-effective approach for screening large population in community mass screening programs and for longitudinal sampling of hospitalized individuals aimed at monitoring viral load dynamics and treatment response. During the COVID-19 pandemic, scientific evidence emerged indicating that molecular tests performed on saliva have diagnostic sensitivity and specificity comparable to those observed with nasopharyngeal swabs for SARS-CoV-2 RNA detection. The presence of IgA and IgG antibodies at the mucosal level has been demonstrated to influence the progression of viral infection and the severity of clinical manifestation. As saliva contains both respiratory secretions and immunological components, it has wide applications, ranging from clinical diagnostics to post-vaccine disease burden and immunity surveillance.

Douglass Diak↗

NASA NTRS2021

Spatial Variation of Fine Particulate Matter Levels in Nairobi Before and During the COVID-19 Curfew: Implications for Environmental Justice

The temporary decrease of fine particulate matter (PM(sub 2.5)) concentrations in many parts of the world due to the COVID-19 lockdown spurred discussions on urban air pollution and health. However there has been little focus on sub-Saharan Africa, as few African cities have air quality monitors and if they do, these data are often not publicly available. Spatial differentials of changes in PM(sub 2.5) concentrations as a result of COVID also remain largely unstudied. To address this gap, we use a serendipitous mobile air quality monitoring deployment of eight Sensirion SPS 30 sensors on motorbikes in the city of Nairobi starting on 16 March 2020, before a COVID-19 curfew was imposed on 25 March and continuing until 5 May 2020. We developed a random-forest model to estimate PM(sub 2.5) surfaces for the entire city of Nairobi before and during the COVID-19 curfew. The highest PM(sub 2.5) concentrations during both periods were observed in the poor neighborhoods of Kariobangi, Mathare, Umoja, and Dandora, located to the east of the city center. Changes in PM(sub 2.5) were heterogeneous over space. PM(sub 2.5) concentrations increased during the curfew in rapidly urbanizing, the lower-middle-class neighborhoods of Kahawa, Kasarani, and Ruaraka, likely because residents switched from LPG to biomass fuels due to loss of income. Our results indicate that COVID-19 and policies to address it may have exacerbated existing air pollution inequalities in the city of Nairobi. The quantitative results are preliminary, due to sampling limitations and measurement uncertainties, as the available data came exclusively from low-cost sensors. This research serves to highlight that spatial data that is essential for understanding structural inequalities reflected in uneven air pollution burdens and differential impacts of events like the COVID pandemic. With the help of carefully deployed low cost sensors with improved spatial sampling and at least one reference-quality monitor for calibration, we can collect data that is critical for developing targeted interventions that address environmental injustice in the African context.

Environmental justice↗

NASA NTRS2021

Ultra Long-Lived, Self-Surveying Autonomous Air Quality Sensing - Executive Summary

We set out to evolve ultra-low power air quality sensing technologies developed at JSC to add a highly accurate positioning sensor based on SBIR technology to give a self-surveying air quality monitoring platform with years-long lifetime on a small, disposable coin cell battery. Using Radio Frequency Identification (RFID) technology for data transport, the system can take advantage of RFID-based inventory management systems in place on lunar exploration assets to provide this capability with extremely small SWAP impacts. Years-long operational lifetimes enable flexible, autonomous environmental monitoring during lengthy intervals between and unprecedented situational awareness during crewed missions. Software integration of the localization system into the JSC RFID sensing platform was advanced, but the COVID-19 pandemic complicated and slowed maturation of the localization system SBIR product, and center closure indefinitely deferred a final hardware integration and system demonstration. In the meantime, progress was made to mature the air-quality sensing platform for flight, including hardware, software, antenna, and mechanical improvements. The underlying RFID sensing capability was also adapted to a drawer motion sensing system, which is currently (FY21) being taken toward an ISS flight demonstration as part of the RFID Enhanced Autonomous Logistics Management (REALM)-3 experiment.

Raymond Summers Wagner↗

NASA NTRSDate not supplied

Has NO(2) in Metropolitan Areas Returned to Pre-COVID-19 Levels as Measured by OMI Satellite Data?

Nitrogen oxides (NOx = NO + NO2) are primarily emitted through the combustion of fossil fuels, such as automobiles and power plants. NOx can contribute to chemical reactions that produce ozone and fine particulate matter (PM2.5) pollution. Using tropospheric vertical column density (TVCD) NO2 data from satellite hyperspectral instruments, such as the Ozone Monitoring Instrument (OMI) on board NASA’s EOS Aura satellite, one can monitor changes in NO2 pollution during “black-swan” events, such as mobility restrictions during COVID-19 lockdowns. Our OMI team has created the Global Nitrogen Dioxide Monitoring Home Page (https://so2.gsfc.nasa.gov/no2/no2_index.html ) where we display NO2 TVCD time series, animated maps, and COVID-specific NO2 anomalies comparing to a pre-COVID five-year average for 317 cities and regions around the world. During the pandemic as a result of the widespread lockdowns, many areas saw low NO2 anomalies superimposed on the natural weather related NO2 changes, such as seasonal NO2 cycle. Has NO2 levels returned to pre-Covid-19 levels in large metropolitan areas? We analyze NO2 time series from March through September for the years 2020-2023 using as a reference the average NO2 from 2015-2019 for those months. We will present data from selected cities that represent all countries.

Keith D Evans↗

NASA NTRSDate not supplied

Hazards of Lunar Surface Exploration: Determining the Immunogenicity/Allergenicity of Lunar Dust

There are multiple Apollo program reports of lunar dust (LD) exposure leading to significant upper respiratory symptoms in select crewmembers. Possible mechanisms include particulate irritation, oxidization and release of noxious gas, or legitimate adaptive immune-mediated response. Although sterile non-protein matter would not be expected to be an allergen, one Apollo flight surgeon reported increasing symptoms upon repeated exposure, with associated eosinophilia indicative of allergy (*Acta Astronautica. 2008 63 (7–10): 980–987). Many ISS crews display a pattern of persistent immune system dysregulation and latent virus reactivation (NPJ Microgravity. 2015 Sep 3; 1:15013; NPJ Microgravity. 2017 Apr 12; 3:11). Some ISS crews manifest atypical respiratory and/or dermatitis symptoms which could have an allergic pathogenesis (J Allergy Clin. Immunol. Pract. 2016 Jul-Aug; 4(4):759-762.e8). It is logical to anticipate crew immune dysregulation would worsen during prolonged deep space missions. Planetary surface hazards will only complicate crew health risks. This study hypothesizes that LD exposure can alter susceptible individuals’ immune responses such that repeated exposure will elicit an IgE mediated allergic response either to the LD itself or concomitant antigen exposure during spaceflight. This will adversely increase clinical and operational impacts for long-duration lunar astronauts and affect countermeasure requirements for surface vehicles. Specific aims for this study are (1) Does in vitro LD exposure result in increased histamine from human peripheral blood basophils? (2) Can LD impact the capacity of CD4+ helper and/or CD19+ B-cell mediated IgE production? To address these questions, a set of in-vitro cell culture experiments will be employed (short and long term) using human peripheral blood mononuclear cells (PBMC) and basophils from both atopic and non-atopic individuals, as well as established human basophil and mast cell lines. Cells will be co-cultured with cellular mitogens, common recall antigens (tetanus, Der p1), nickel (as a possible allergenic component of LD), with or without graded amounts of LD, to study whether LD exposure for varying time intervals will alter the generation of selective immune responses associated with clinical allergic reactions. Measured outputs include supernatant-derived IgE, tryptase, histamine and selected cytokine levels. Cellular activation will be monitored by assessing activation markers via flow cytometry. EM/x-ray analysis will be used to determine cellular interactions with dust particles. The minimal amount of LD (Apollo 14 dust) and controls/simulants have been requested. This study, originally planned as an FY20/21 activity, was delayed due to the COVID pandemic. It is now scheduled to be performed during FY22.

Brian Crucian↗

NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗

NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗

NASA NTRS2020

Remote Support of ISS Payload Operations During the COVID19 Pandemic

As part of the Human Health and Performance Contract (HHPC) with the NASA Johnson Space Center, the Human Research Program’s (HRP) Research Operations and Integration (ROI) element conducts the planning, implementation, and closing of human research operations on-board the International Space Station (ISS). These operations are supported out of the Telescience Support Center (TSC) located in the Mission Control Center at Houston’s Johnson Space Center (MCC-H). HRP ROI has an Emergency Response Plan in place to allow for remote operations to be completed in the case of inclement weather or other natural disaster; however, nominally, the remote support is only expected to last one to two weeks. In response to the COVID-19 global pandemic, HRP ROI was challenged to complete a quick transition to supporting on-orbit operations remotely and distanced for an indefinite amount of time. This shift in ground support required close collaboration with various external groups as well as the implementation or adaptation of various technologies and tools to ensure no loss of science data. Operational adjustments were put into place for ground commanding, telemetry monitoring, personnel staffing and private and public audio and video with the ISS. Adjustments were also put in place for communication and collaboration with MCC-H, the Payload Operation and Integration Center (POIC) at Marshall Space Flight Center (MSFC), as well as between the various HRP ROI console team members spread across Houston, TX. The ability to successfully support a variety of on-orbit operations from any remote location is more in demand as the commercialization of low Earth orbit is expanding.

Operations↗

NASA NTRS2020

Electromagnetic Pain Relief/Blocking: Feasibility Assessment

Context/Background: Astronauts use pharmaceuticals during spaceflight to manage acute and chronic pain, but use of analgesics will have drawbacks for exploration-class missions because the shelf life of these medications is limited, resupply will be curtailed, astronauts may develop tolerance and/or addiction to these medications, and side effects can include impairment of cognitive abilities. Electromagnetic devices have been developed that treat pain terrestrially by affecting neuromodulation–dubbed “electroceuticals”, these devices have varied mechanisms of action that either stimulate or suppress neural activity in the central nervous system or peripheral nerves. Objective/Purpose: The available literature was reviewed and FDA-approved pain treatments (both pharmacological and non-pharmacological), as well as those currently under development, were assessed for their suitability for use in exploration class spaceflight missions. Data Sources: Due to the COVID-19 pandemic and the resulting closure of libraries, data sources were restricted to those available digitally. Online database searches included PubMed, U.S. Patent and Trademark Office, federal grant award databases (National Aeronautics and Space Administration (NASA), Department of Defense (DoD), National Institutes of Health (NIH)), and general internet searches. More than 1,600 records were reviewed in this effort. Study Selection/Eligibility Criteria: Targeted searches included different aspects of pain management. Priority was given to review studies, to cover as much of the available literature as possible in this limited effort. Study Appraisal and Synthesis Methods/Data Extraction and Data Synthesis: The titles of the studies and the awards that were obtained by searching online databases were reviewed and further information was sought for the relevant titles. Abstracts or award summaries were generally available online; for journal abstracts, full text articles were either available online or were requested via interlibrary loan. Results: An overwhelming majority of the literature focuses on the treatment of chronic rather than acute pain because it is assumed that acute pain only rarely fails to resolve and instead transitions into chronic pain when the central nervous system becomes hypersensitized. The available electromagnetic devices marketed for pain treatment have varying levels of invasiveness, use different mechanisms of action, and have demonstrated varying efficacy when evaluated scientifically. A truly noninvasive, highly efficient device is desired for use during spaceflight. One portable, self-contained, FDA-approved device was identified that, from preliminarily assessment, best met these criteria; the device noninvasively applies pulsed shortwave therapy (PSWT) to modify pain signals from peripheral nerves, however, the device has limited battery life and the effects are relatively non-selective in type of neural signal modified. Limitations: This current effort, although extensive, did not identify a comprehensive list of all alternatives for pain treatment. Once the pandemic limitations are lifted, a longer, more thorough effort may find additional options. Conclusions/Implications: The ideal electromagnetic pain treatment device for use on exploration-class spaceflight missions does not yet exist, but it may be available soon. It is not feasible for NASA to develop medical devices due to the schedule constraints for pending exploration-class missions, but adapting a promising device that is already FDA-approved might be an option. Monitoring research that is ongoing at other federal agencies is recommended, and further review of the candidate PSWT device identified in this current effort may be warranted.

Carol Mullenax↗

NASA NTRSDate not supplied

Electromagnetic Pain Relief/Blocking: Feasibility Assessment

CONTEXT/BACKGROUND Astronauts use pharmaceuticals during spaceflight to manage acute and chronic pain, but use of analgesics will have drawbacks for exploration-class missions because the shelf life of these medications is limited, resupply will be curtailed, astronauts may develop tolerance and/or addiction to these medications, and side effects can include impairment of cognitive abilities. Electromagnetic devices have been developed that treat pain terrestrially by affecting neuromodulation–dubbed “electroceuticals”, these devices have varied mechanisms of action that either stimulate or suppress neural activity in the central nervous system or peripheral nerves. OBJECTIVE/PURPOSE The available literature was reviewed and FDA-approved pain treatments (both pharmacological and non-pharmacological), as well as those currently under development, were assessed for their suitability for use in exploration class spaceflight missions. DATA SOURCES Due to the COVID-19 pandemic and the resulting closure of libraries, data sources were restricted to those available digitally. Online database searches included PubMed, U.S. Patent and Trademark Office, federal grant award databases (National Aeronautics and Space Administration (NASA), Department of Defense (DoD), National Institutes of Health (NIH)), and general internet searches. More than 1,600 records were reviewed in this effort. STUDY SELECTION/ELIGIBILITY CRITERIA Targeted searches included different aspects of pain management. Priority was given to review studies, to cover as much of the available literature as possible in this limited effort. STUDY APPRAISAL AND SYNTHESIS METHODS/DATA EXTRACTION AND DATA SYNTHESIS The titles of the studies and the awards that were obtained by searching online databases were reviewed and further information was sought for the relevant titles. Abstracts or award summaries were generally available online; for journal abstracts, full text articles were either available online or were requested via interlibrary loan. RESULTS An overwhelming majority of the literature focuses on the treatment of chronic rather than acute pain because it is assumed that acute pain only rarely fails to resolve and instead transitions into chronic pain when the central nervous system becomes hypersensitized. The available electromagnetic devices marketed for pain treatment have varying levels of invasiveness, use different mechanisms of action, and have demonstrated varying efficacy when evaluated scientifically. A truly noninvasive, highly efficient device is desired for use during spaceflight. One portable, self-contained, FDA-approved device was identified that, from preliminarily assessment, best met these criteria; the device noninvasively applies pulsed shortwave therapy (PSWT) to modify pain signals from peripheral nerves, however, the device has limited battery life and the effects are relatively non-selective in type of neural signal modified. LIMITATIONS This current effort, although extensive, did not identify a comprehensive list of all alternatives for pain treatment. Once the pandemic limitations are lifted, a longer, more thorough effort may find additional options. CONCLUSIONS/IMPLICATIONS The ideal electromagnetic pain treatment device for use on exploration-class spaceflight missions does not yet exist, but it may be available soon. It is not feasible for NASA to develop medical devices due to the schedule constraints for pending exploration-class missions, but adapting a promising device that is already FDA-approved might be an option. Monitoring research that is ongoing at other federal agencies is recommended, and further review of the candidate PSWT device identified in this current effort may be warranted.

C A Mullenax↗

NASA NTRSDate not supplied

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

NASA NTRS2021

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

NASA NTRS2022

Visual Odometry Thinking While Driving for the Curiosity Mars Rover's Three-Year Test Campaign: Impact of Evolving Constraints on Verification and Validation

Over the first 9 years of the Mars Science Laboratory (MSL) Curiosity rover's surface mission, more than 87\% of its driving has been performed using Visual Odometry (VO). The benefits of using VO during driving are that it minimizes rover position uncertainty and can be used to monitor wheel slip, halting a drive if excessive wheel slip is occurring. The VO implementation on board Curiosity acquires and processes VO images in between drive steps while the rover is stationary. A VO Thinking While Driving (VTWD) flight software capability has been developed which enables the processing of VO images during rover driving, increasing the distance Curiosity can drive with VO in a given time period up to as much as 1.75x total distance. Verification and Validation (V\&V) of the capability has been challenging due to impacts from the COVID-19 pandemic and unavailability of the JPL Mars Yard outdoor test site. The VTWD V\&V test procedures were modified to use a small indoor space with Mars-like terrain. This paper describes the 3 year V\&V effort under challenging conditions to approve the VTWD capability for use on the Curiosity rover.

Rankin, Arturo↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗