Results for “MITIGATION” — Page 79

NASA NTRSDate not supplied

Lunar Regolith Trajectories as a Result of Plume Surface Interactions

Lunar regolith is ejected from the impingement points of descent engine plumes. Such particles pose potential risks to surface operations, sites of scientific and historical interest, and orbiting spacecraft. Consequently, determining the resultant trajectories of these particles is necessary in order to estimate and mitigate risk. Here we present the ranges, impact latitudes, times of flight, and maximum altitudes for particles accelerated by a plume surface interaction at the lunar south pole. Using launch angles determined from observations and simulations, and for velocities <1:6 km/s, particles pose little risk. However, above 1:6 km/s the risks increase, and the results become highly sensitive to the initial angle. In addition, gravitational and non-gravitational processes will introduce perturbations to high-velocity trajectories resulting in a reduction in precision. Therefore, while local topography or artificial berms may mitigate trajectories with low initial angles, it remains important to place tight constraints on the potential launch angles of particles accelerated by plume surface interactions through simulations and experimentation. If these angles are indeed constrained to within a few degrees of the horizon, the risks posed by accelerated regolith particles at any velocity will be minimal.

Daniel Batcheldor↗

NASA NTRSDate not supplied

In-Time Safety Assessment & Risk Prediction for Unmanned Aerial Systems

One of the critical challenges in emerging autonomous systems is timely mitigation of hazards encountered during operation which may not be known or accounted for at the time of design. Efficient execution of unmanned systems therefore demands a paradigm shift from scheduled periodic maintenance to predictive risk analysis that includes condition-based-monitoring, real-time reliability assessment and hazard mitigation. Particularly, the state-of-health parameters needs to be computed at the component level, unit level as well as the integrated system level. While in the former two levels, the physics of health propagation may be based on underlying electro-mechanical properties, system level prognostics often relies on data-driven models. Further, uncertainty from model, measurements and input sources should be accurately quantified to generate meaningful prediction results that can be fed into reliable decision making processes. Finally, the expected risk and time to failure has to be computed based on the current state-of-health of the overall system. This talk presents a conceptual design of such an in-time safety assurance approach for unmanned aerial vehicles (UAV) operating at low altitudes near and over populated areas. Typical in-flight hazard incidents include unplanned detour, proximity to obstacles, mid-flight component faults, limited battery life and poor quality of GPS measurements. Safety assessment therefore comprises trajectory generation and re-plan, battery RUL computation, distributed fault diagnostics and uncertainty management of predicted trajectory based on GPS measurement noise. The entire monitoring framework will be demonstrated on simulated as well as real UAV flight experiments conducted at the NASA Langley Research Center. This tutorial will therefore guide the audience through a step-by-step tracking of an autonomous system with focus on in-time risk prediction in the presence of unforeseen hazards and uncertain environment.

diagnostics↗

NASA NTRS2021

Collaborative Communications Between A Human and A Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACCto which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced air mobility↗

NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗

NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗

NASA NTRSDate not supplied

Conceptual Thermal Control System Design for a Lunar Surface Habitat

NASA is currently considering a Surface Habitat (SH) to provide 30-60 day habitability for a crew of up to four to explore the Lunar surface at a South Pole location. The SH concept is comprised of an inflatable volume for the habitable space, a metallic airlock and a descent stage with access to a pressurized rover and other surface assets provided through the airlock. A conceptual architecture for the SH Thermal Control System (TCS) is presented with resource estimates. The TCS design employs a dual loop architecture with a water/propylene glycol mix for the internal crew spaces with a freeze tolerant coolant utilized for the external loop. The internal loop is partitioned into low and moderate temperature service with a sublimator available for operational scenarios prior to thermal radiator deployment (or redeployment). Analytical models are utilized to optimize radiator geometry/orientation as well as the TCS internal/external loop architecture. Heritage hardware is utilized for the TCS concept wherever possible and low mass, dust tolerant, deployable/retractable thermal radiators (in partial gravity) present a technology challenge. The TCS must accommodate infrequent eclipse periods lasting up to 100 hours in duration and mitigation strategies to reduce the energy needed to maintain the SH and associated systems above survival temperature limits during this period are explored. Mitigation options include retractable or freezable radiators, other reconfigurable radiator geometries, alternate fluids, re-generable heat exchangers, temperature excursions, thermal energy storage and optimized inflatable optical properties. Finally, TCS sensitivity to SH Electrical Power System (EPS) growth is considered with both operational and dormant impacts quantified.

Thermal Control↗

NASA NTRSDate not supplied

An Approach for Identifying IASMS Services, Functions, and Capabilities From Data Sources

Assuring safety in the NAS with the inclusion of new entrants that are part of Advanced Air Mobility (AAM) will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using semi-autonomous/autonomous vehicles. Overcoming these AAM safety assurance challenges is the focus of the In-time Aviation Safety Management System (IASMS). The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs)designed to manage operational risks, identify unknown risks, and inform system design to mitigate risk. This paper describes a broad approach for identifying SFCs involving technology trends in research, assessment of known and unknown risks in safety reports, and causal and contributing factors in aviation accidents and incidents. This approach leverages these sources to identify potential SFCs that enable the Monitor, Assess, and Mitigate (M-A-M)functionality that represents the enabling framework of the IASMS.

Kyle Ellis↗

NASA NTRSDate not supplied

Bowtie Analysis of the Effects of Unmanned Aircraft on Air Traffic Control

Within the aviation domain, there is a growing industry demand to develop and integrate remotely piloted operations into the National Airspace System. However, it is not yet well understood how the integration of unmanned aircraft with impact air traffic control, and specifically, the air traffic controllers who are at the sharp end of this safety critical system. This research presented in this paper aimed to begin to address this gap in understanding by identifying and exploring potential hazards associated with introducing Unmanned Aircraft into the national airspace system, and identify possible mitigations to reduce identified risks. A bowtie risk analysis methodology was used to identify and analyze hazards. A focus-group format discussion was conducted with nine subject matter experts as participants. Findings identified five areas of potential risk, each associated with multiple hazards. Mitigations for each hazard are reported. Findings have essential implications for the safe and efficient integration of unmanned aircraft into the national airspace.

Tamsyn Edwards↗

NASA NTRS2021

Bowtie Analysis of the Effects of Unmanned Aircraft on Air Traffic Control

Within the aviation domain, there is a growing industry demand to develop and integrate remotely piloted operations into the National Airspace System. However, it is not yet well understood how the integration of unmanned aircraft with impact air traffic control, and specifically, the air traffic controllers who are at the sharp end of this safety critical system. This research presented in this paper aimed to begin to address this gap in understanding by identifying and exploring potential hazards associated with introducing Unmanned Aircraft into the national airspace system, and identify possible mitigations to reduce identified risks. A bowtie risk analysis methodology was used to identify and analyze hazards. A focus-group format discussion was conducted with nine subject matter experts as participants. Findings identified five areas of potential risk, each associated with multiple hazards. Mitigations for each hazard are reported. Findings have essential implications for the safe and efficient integration of unmanned aircraft into the national airspace.

unmanned aerial vehicles↗

NASA NTRSDate not supplied

Conceptual Thermal Control System Design for a Lunar Surface Habitat

NASA is currently considering a Surface Habitat (SH) to provide 30-60 day habitability for a crew of up to four to explore the Lunar surface at a South Pole location. The SH concept is comprised of an inflatable volume for the habitable space, a metallic airlock and a descent stage with access to a pressurized rover and other surface assets provided through the airlock. A conceptual architecture for the SH Thermal Control System (TCS) is presented with resource estimates. The TCS design employs a dual loop architecture with a water/propylene glycol mix for the internal crew spaces with a freeze tolerant coolant utilized for the external loop. The internal loop is partitioned into low and moderate temperature service with a sublimator available for operational scenarios prior to thermal radiator deployment (or redeployment). Analytical models are utilized to optimize radiator geometry/orientation as well as the TCS internal/external loop architecture. Heritage hardware is utilized for the TCS concept wherever possible and low mass, dust tolerant, deployable/retractable thermal radiators (in partial gravity) present a technology challenge. The TCS must accommodate infrequent eclipse periods lasting up to 100 hours in duration and mitigation strategies to reduce the energy needed to maintain the SH and associated systems above survival temperature limits during this period are explored. Mitigation options include retractable or freezable radiators, other reconfigurable radiator geometries, alternate fluids, re-generable heat exchangers, temperature excursions, thermal energy storage and optimized inflatable optical properties. Finally, TCS sensitivity to SH Electrical Power System (EPS) growth is considered with both operational and dormant impacts quantified.

Thermal Control↗

NASA NTRSDate not supplied

In-situ Lunar Launch and Landing Pad Construction with Regolith-Thermoset Polymer Composite Materials

Lunar launch and landing pads are necessary to mitigate risks to lander/ascent vehicles and surrounding surface assets from rocket plume ejected regolith. The current state of the art of landing and launching from the lunar surface is to land/launch on unprepared regolith surfaces. Though this has been a relatively successful approach, significant risks exist for the Artemis Program due to higher thrust levels leading to increased ejecta and cratering, presence of co-located assets in the ejecta path, and potential strict surface levelness requirements. Regolith-thermoset polymer composite materials were developed and evaluated for off Earth launch and landing pad applications. Performance under hot fire conditions was assessed for two simulated Starship lunar launch/landing environments, one targeting thermal conditions and the second targeting pressure conditions. Paver test articles were prepared at 20% and 11% polymer mass fractions. Sintered paver test articles were prepared with 20% polymer grouting filling the seams between pavers. Though significant erosion was experienced during the more extreme thermal testing conditions, all test articles successfully mitigated regolith ejecta from plume effects. A concept for preparing and emplacing the materials was developed and tested in laboratory conditions. The testing evaluated the feasibility of using twin and single screw extruder technology to mix, convey and deposit materials. Both the twin and single screw extruders were capable of processing and extruding the composite with a maximum of 90% mass fraction of regolith achieved by the twin screw extruder.A primary risk for application of regolith-thermoset polymer composites as lunar launch/landingpad is the mass of polymer required to be landed on the moon. Calculations were performed that show that a 100 m diameter, 0.025 m thick pad with polymer mass fraction of 15% will require a payload mass of 72 mt to the Lunar surface. This is below the planned Starship payload capacity to the lunar surface of 100 mt. The regolith-thermoset polymer composite based construction approach proved feasibility in three critical areas: performance under launch/landing conditions, demonstration of a mixing and depositing strategy, and fitting within the planned lunar payload capacity. It is recommended that materials and systems be developed to TRL 6 for a small-scale lunar demonstration of emplacement of a launch/landing pad via a CLPS mission to support Artemis Program roadmap gap closure activities.

ISRU↗

NASA NTRS2021

Maya Forest Water Resources I: Using NASA Earth Observations to Map Forested Inundation in the Maya Forest

As climate change increases the severity and frequency of extreme weather events in the tropics, it is vital for the safety of local communities and the health of ecosystems to monitor seasonal inundation. Forested inundation affects the ability of forested wetlands to provide ecosystem services, such as flood mitigation, water filtration, carbon storage, and erosion mitigation. While ground-based monitoring has traditionally been used to map inundation extent, those methods are costly and time-intensive. The NASA DEVELOP team focused on seasonal inundation throughout 2008 in the Maya Forest, when changes in inundation were drastic. To monitor seasonal inundation, our team used in situ field data and Earth observations from Landsat 7 Enhanced Thematic Mapper (ETM+), Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) 1, Shuttle Radar Topography Mission (SRTM), and products from the Ice, Cloud, and Land Elevation Satellite (ICESat). The team applied a Random Forest algorithm to Landsat 7 imagery, generating an object-level land cover classification with an overall accuracy of 72.1% and forest class with 100% recall and 78% precision. The team applied L-band backscatter thresholds from existing literature to forest-masked ALOS imagery and refined the thresholds in an iterative process using field data and hydrology models to delineate seasonal inundation extent. These publicly available data products help end users from Belize’s Land Information Center (LIC) and Forest Department, Guatemala’s Center for Monitoring and Evaluation (CEMEC), and Mexico’s El Colegio de la Frontera Sur (ECOSUR) to inform land management and protect community infrastructure.

Madelyn Savan↗

NASA NTRS2022

Soil Respiration Phenology Improves Modeled Phase of Terrestrial Net Ecosystem Exchange in Northern Hemisphere

In the northern hemisphere, terrestrial ecosystems transition from net sources of CO2 to the atmosphere in winter to net ecosystem carbon sinks during spring. The timing (or phase) of this transition, determined by the balance between ecosystem respiration (RECO) and primary production, is key to estimating the amplitude of the terrestrial carbon sink. We diagnose an apparent phase bias in the RECO and net ecosystem exchange (NEE) seasonal cycles estimated by the Terrestrial Carbon Flux (TCF) model framework and investigate its link to soil respiration mechanisms. Satellite observations of vegetation canopy conditions, surface meteorology, and soil moisture from the NASA SMAP Level 4 Soil Moisture product are used to model a daily carbon budget for a global network of eddy covariance flux towers. Proposed modifications to TCF include: the inhibition of foliar respiration in the light (the Kok effect); a seasonally varying litterfall phenology; an O2 diffusion limitation on heterotrophic respiration (RH); and a vertically resolved soil decomposition model. We find that RECO phase bias can result from bias in RECO magnitude and that mechanisms which reduce northern spring RECO, like substrate and O2 diffusion limitations, can mitigate the phase bias. A vertically resolved soil decomposition model mitigates this bias by temporally segmenting and lagging RH. Applying these model enhancements at Continuous Soil Respiration (COSORE) sites verifies their improvement of RECO and NEE skill compared to in situ observations (up to ∆RMSE = −0.76 g C m−2 d −1 35 ). Ultimately, these mechanisms can improve prior estimates of NEE for atmospheric inversion studies.

Soil respiration↗

NASA NTRS2021

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor

Drought is one of the most ecologically and economically devastating natural phenomena affecting the United States, causing the U.S. economy billions of dollars in damage, and driving widespread degradation of ecosystem health. Many drought indices are implemented to monitor the current extent and status of drought so stakeholders such as farmers and local governments can appropriately respond. Methods toforecast drought conditions weeks to months in advance are less common but would provide a more effective early warning system to enhance drought response, mitigation, and adaptation planning. To resolve this issue, we introduce DroughtCast, a machine learning framework for forecasting the United States Drought Monitor (USDM). DroughtCast operates on the knowledge that recent anomalies in hydrology and meteorology drive future changes in drought conditions. We use simulated meteorology and satellite observed soil moisture as inputs into a recurrent neural network to accurately forecast the USDM between 1 and 12 weeks into the future. Our analysis shows that precipitation, soil moisture, and temperature are the most important input variables when forecasting future drought conditions. Additionally, a case study of the 2017 Northern Plains Flash Drought shows that DroughtCast was able to forecast a very extreme drought event up to 12 weeks before its onset. Given the favorable forecasting skill of the model, DroughtCast may provide a promising tool for land managers and local governments in preparing for and mitigating the effects of drought.

Machine Learning↗

NASA NTRS2021

Colorado Ecological Forecasting: Monitoring Post-fire Cheatgrass (Bromus tectorum) Distribution to Inform Management Planning

Cheatgrass (Bromus tectorum) is a species of concern across the western United States as it has the potential to outcompete native plant species, reduce biodiversity, and diminish nutrient availability for ungulates. Furthermore, because cheatgrass can quickly dominate disturbed landscapes it has the potential to exacerbate wildfire risk by increasing fuel loads. In 2020, the Cameron Peak fire burned more than 200,000 acres on the Arapaho and Roosevelt National Forests in Colorado. These issues are of imminent concern for our partners at the Forest Service (USFS), as they are tasked with wildfire risk and invasive species mitigation. Disturbances such as wildfires can substantially increase the rate and extent of cheatgrass spread. Current cheatgrass mitigation methods rely on field crews to physically locate cheatgrass on the landscape, which takes time, money, and extensive manpower. Here, we developed two Random Forest models within the Software for Assisted Habitat Modeling (SAHM) using remote sensing predictors derived from Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The first model identified suitable cheatgrass habitat while the other detected cheatgrass presence during the 2021 growing season. Topographic variables were found to be the most important in driving the habitat suitability model. Cheatgrass detection was also found to be possible within a short timespan with limited imagery surrounding a phenological shift of the plant. Maps produced from these models provide natural resource managers the ability to implement early detection and rapid response to prevent the spread of cheatgrass to new locations.

DEVELOP Tech Paper↗

NASA NTRSDate not supplied

Design for Minimum Casualty Area – The IXPE Case

The Imaging X-Ray Polarimetry Explorer (IXPE) is a new international space observatory in NASA’s Small Explorer program, designed in a collaboration between the Italian Space Agency and NASA’s Marshall Space Flight Center, and built by Ball Aerospace. IXPE has an expected launch in November 2021, to a 600-km altitude equatorial orbit. IXPE is an astrophysics mission using three telescope assemblies to measure the polarization of cosmic X-rays. Each assembly is composed of a mirror module assembly (MMA) with 24 nested nickel-cobalt cylindrical shells and a unique, polarization-sensitive, gas pixel detector (GPD) within the detector unit (DU). As a NASA mission, IXPE must adhere to the orbital debris mitigation requirements specified in NASA Standard 8719.14 [1]; in the present work, we will only discuss reentry human casualty risk. As initially designed, the IXPE observatory exceeded NASA’s casualty risk threshold. IXPE does not include a propulsion system to perform a controlled reentry at the end of mission to mitigate the ground casualty risk. To reduce the risk from the uncontrolled reentry of this observatory, the IXPE design team worked with the NASA Orbital Debris Program Office to reduce the debris casualty area through design-for-demise and containment methods. The flight design of IXPE is now compliant with the ground casualty risk requirement at a casualty probability of 1:13,100 compared to a casualty requirement of better than 1:10,000.

C Ostrom↗

NASA NTRSDate not supplied

Enabling a Voice Management System for Space Applications

The sustainable missions beyond Low Earth Orbit (LEO) envisioned for NASA’s Artemis program will require autonomous capabilities. Moreover, Artemis mission crews will need a means to efficiently interact with a spacecraft’s autonomous systems. This interaction can be facilitated by voice and speech communications because voice-based controls enable users to interact hands- and eyes-free, allowing the user to better focus on critical tasks. The goal of our project was to explore the knowledge and technology needed to successfully design effective Voice User Interfaces (VUIs) for autonomous systems utilizing Human Centered Design (HCD) principles. The focus of the human factors’ aspect of engineering, pays close attention to psychological and physiological principles in the development of autonomous crew operation systems. A main objective was to understand how a crew member, through voice interaction, could efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project was a part of the NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The work from the BLiSS Team, at the University of Michigan, resulted in the design of a system persona, Diego, to which an astronaut may quickly build trust with autonomous systems, to alleviate known stressors on mental health expected during long duration space missions. Optimal software to facilitate integration of the system persona into a reference Lunar orbiting Gateway station was defined. Additionally, a Speech to Text (STT) system and a Graphical User Interface (GUI) that could be implemented in future missions was developed on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2020 project leveraged previous technology developed by the BLiSS team to incorporate a voice-based interface into NASA’s Platform for Autonomous Systems (NPAS) software. This required technologies to convert voice to text, conduct semantic interpretations, and convert responses from the autonomous system to text and to speech; additionally, the spacecraft background noise environment was assessed, a noise mitigation technique was developed, and a relatable personality for the autonomous system was developed in order to facilitate human-like conversations. The success of our effort was largely due to the diversity of the team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The diverse perspectives fostered elaborate discussions, resulting in the conception of three main subsystems: (1) User-System, (2) NPAS-System, and (3) Environment-System. The VUI was unique and had to be efficient and intuitive. For this project, 5 subteams were formed, each with a separate objective, Voice Design team, Background Noise Mitigation team, Software Integration team and Graphical User Interface team. The BLiSS team crafted a personality for the VUI to enable human-like conversation and drive user adoption and trust. User surveys were completed and used to help determine the required VUI system personality traits by capturing perspectives and expectations of prospective “Artemis Generation Astronauts”. To further simulate human-like conversations, the system had to be able to quickly interpret user speech and be able to integrate with NASA’s NPAS platform for quick and reliable information transfer. The outcomes of our research were: (1) a working prototype user interface, that is compatible with NASA’s NPAS platform; (2) software that demonstrates the ability of the VUI system to interpret user requests and respond appropriately; (3) the capability to implement fully expanded conversations between user and system using intuitive communication in four request categories; and (4) software and hardware recommendations that optimize the system’s ability to operate in a noisy environment. Our research has laid the foundation for the development of VUI’s for autonomy, and provides a baseline for future VUI developments.

Voice user interface↗

NASA NTRSDate not supplied

Neo – Mars Adaptive Training Integrative Knowledge System (MATRIKS) to Improve Operational Performance and its Neural Basis for Spaceflight

With prolonged mission durations, spaceflight crews will become increasingly dependent on onboard technologies for knowledge acquisition and maintenance. It is expected that not all skills and knowledge required for these missions can be retained and retrieved based on pre-mission training alone. Limited and delayed communication will significantly constrain support from Mission Control and crews will increasingly rely on autonomous onboard technologies to successfully perform post-landing operations. With the present project we will target NASA’s particular interest in developing and assessing an adaptive, just-in-time countermeasure that will consolidate and improve skills that are most relevant to space flight operations. To achieve this aim, NASA established a Virtual NASA Specialized Center of Research (VNSCOR)referred to as “Mars Adaptive Training Integrative Knowledge System (MATRIKS)”, comprising the following three projects: (1) “Trinity–Multi-Environment Virtual Training for Long Duration Exploration Missions”, PI: A. Anderson (UC Boulder); (2) “Morpheus–A Haptic Sensory Supplement to Optimize In-Flight Adaptive Training for Human Control of Spacecraft Robotic Arms”, PI: S. Robinson, UC Davis); and the present project “Neo–Adaptive Training integrative knowledge System to Improve Operational Performance and its Neural Basis for Spaceflight” (UPenn, PI: A.C. Stahn). Neo leverages a validated workstation called 6DF that simulates a rendezvous and docking maneuver using real spacecraft flight dynamics. It is designed to (1) train and improve sensorimotor skills relevant for inflight and post-landing operational tasks; (2) feature an autonomous and adaptive training approach that does not rely on feedback from flight operations on the ground; (3) maximize the transfer of mission-relevant motor skills; (4) allow the assessment of the neural circuitry underlying the task; and (5) deliver the training in a motivating and meaningful way to astronauts. Neocomprises two overarching aims: First, we will identify the neural circuitry underlying spaceflight relevant tasks by performing a subset of the 6DFtaskduring functional magnetic resonance imaging (MRI)in a total of up to N=30 subjects with varying levels of 6DF training experience. Second, as part of the above-mentioned VNSCOR MATRIKS the proposed 6DF autonomous intelligent tutor system will be integrated in an additive manner with a haptic feedback intervention (Morpheus), and a multi-environment virtual trainer(Trinity).It is expected that Neo, Morpheus and Trinity mutually complement each other to facilitate an effective countermeasure tool to acquire and retain operational skills that are critical for exploration class missions. To assess the efficacy of this combined effort, the VNSCOR MATRIKS will collect data inN=16 crew members in one HERA campaign of 45 days duration with N=16 crew members(four missions with N=4 crew member seach).The primary goal is to identify changes in operational performance as assessed by NASA’s simulator of Canadarm2 operations, i.e., Robotic On-board Trainer (ROBoT-r) in response to MATRIKS. As part of Neo we will also identify if, and to what extent MATRIKS will promote transfer to general cognitive performance (Cognition battery), distinctive visuo-spatial tasks critical for telerobotic tasks (Spatial Cognition battery), and affect brain structural changes and the neural circuitry of key brain networks expected to be relevant for spaceflight-related performance. At the conclusion of the research, we will have defined and demonstrated the use of a neuroscience-based, adaptive training integrative knowledge system to potentially mitigate visuo-spatial and sensorimotor brain changes associated with prolonged isolation and confinement to reduce the likelihood or impact of potential decrements in human performance capabilities during long-duration space missions. The expected significance of this 4-year project relates to its relevance for facilitating effective countermeasure tools to acquire and retain operational skills that are critical for exploration class missions. This will support the development of necessary countermeasures and technologies in support of human space exploration, focusing on mitigating operational performance risks.

A C Stahn↗