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NASA NTRS2020

In-time System-wide Safety Assurance (ISSA) Concept of Operations and Design Considerations for Urban Air Mobility (UAM)

Emerging operations involving Advanced Air Mobility (AAM), such as Urban Air Mobility (UAM), pose a challenge to safety assurance and to accessibility within the National Airspace System (NAS).In particular, the public has a low tolerance for risk in aviation and the current NAS tends to be labor-intensive with limited ability to scale up for UAM. In response to this landscape, NASA is collaborating with industry to define a Concept of Operations (ConOps) for In-time System-Wide Safety Assurance (ISSA) for scalable UAM involving a service-oriented architecture. This architecture focuses safety investments for technological solutions that can overcome safety related barriers for emerging operations. By working with industry, consensus can be reached on desirable system traits that are based on integration and fusion of data and leverage increasingly autonomous and automated systems. These complex systems can identify anomalies, precursors, and trends that together enable more proactive management of operational risks. AAM and UAM elevate the need for risk management in relation to increasing density and heterogeneity of vehicles and operations. Whereas safety in today’s NAS is built on a history of programs and technologies that react to incidents and accidents, AAM presents an opportunity to leverage that experience and its implications and proactively integrate safety into the earliest designs of vehicles and systems. In a perfect world AAM and UAM would not be inherently dangerous but until then ensuring the highest quality of safety requirements is the bridge to mitigating risks.

In-Time System-Wide Safety Assurance↗

NASA NTRS2022

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

NASA NTRS2004

Formation acquisition sensor for the Terrestrial Planet Finder (TPF) mission

The Terrestrial Planet Finder (TPF) pre-project, an element of NASA’s Origins Program, is currently investigating multiple implementation architectures for finding earth-like planets around other stars. One of the technologies being developed is the Formation Flying Interferometer (FFI). The FFI is envisioned to consist of up to seven spacecraft, each with an infrared telescope, flying in precise formation within +/- l cm of pre-determined trajectories for synchronized observations. The spacecraft to- spacecraft separations are variable between 20 m to 100m during observations to support various interferometer configurations in the planet-finding mode. The challenges involved with TPF autonomous operations, ranging from formation acquisition and formation maneuvering, to high precision formation flying during science observations are unprecedented for deep space missions. To meet these challenges, the Formation Sensor Testbed (FST) under the TPF technology program will develop and demonstrate the key technology of the formation acquisition sensor. Key performance targets for the acquisition sensor are an instantaneous 4phi-steradian field of view and simultaneous range and bearing-angle measurements for multiple spacecraft with accuracy better than 50 cm and 1 degree, respectively. In this paper, we will describe the TPF FFI mission concept, the key formation flying challenges, the acquisition sensor design, the key design challenges, and the current plan to mitigate these design challenges.

Purcell, George H. Jr.↗

NASA NTRSDate not supplied

LEIA: An Investigation of Radiation Risks to Biology at the Lunar South Pole

Radiation and reduced gravity pose biological risks to crewed deep space exploration. At the cellular level, radiation damage can be amplified by reduced gravity. Empirical evidence on cellular responses to beyond low Earth orbit (BLEO) environments is imperative to develop effective countermeasures for crew health and in-space biomanufacturing. The Lunar Explorer Instrument for Space Biology Applications (LEIA) project is developing an instrument suite to be delivered to the south polar region of the Moon by the Commercial Lunar Payload Services (CLPS) program. This presentation will provide an overview of the LEIA hardware, experiments, and mission timeline. The LEIA instruments include the BioSensor, the ARES charged particle detector, and the Mini-FND. The BioSensor is an autonomous light emitting diode (LED)-based spectrophotometer and microfluidic incubator. The BioSensor activates yeast cultures and can measure cell growth, metabolic activity, and carotenoid production. The ARES is a Timepix-based charged particle radiation detector that measures dose, dose rate, and linear energy transfer spectra. The Mini-FND is a fast neutron detector that measures albedo neutron flux and energy spectra. Combined, these instruments will be used for yeast genetics experiments to quantify growth, metabolism, and synthetic biology-enabled production of human nutrients, while taking real time measurements of biologically relevant radiation exposure on the lunar surface. These data will be used to test the importance of selected DNA damage repair and reactive oxygen species defense pathways in mitigating cellular damage from lunar surface radiation.

Yeast↗

NASA NTRSDate not supplied

LEIA: An Investigation of Radiation Risks to Biology at the Lunar South Pole

Yeast↗

NASA NTRSDate not supplied

Interoperable Services to Mitigate Lunar Position, Navigation, and Timing Challenges

Across the Earth, both civilian and government endeavors enjoy a built-in reliance on a position, navigation, and timing (PNT) infrastructure to which they are largely blind. Whether walking, driving, flying, or orbiting, Earth-centric PNT systems that have evolved over decades provide a core functionality to which we have grown accustomed for these pursuits. As NASA joins with other government space agencies and commercial partners to return humans to the Moon in a sustained manner within the current decade, expectations for PNT knowledge and timeliness at the Moon rival those on Earth. The need exists to develop a viable lunar-centric PNT infrastructure to support the planned human and robotic exploits. Navigating within the influence of the Moon presents its own set of challenges. Identification, understanding, and use of a unified reference frame and time system on which navigation is based becomes a fundamental need at the Moon. In addition to the unified foundational elements, measurement liability, dynamic conditions that require Earth-independent autonomous operations, and standards for PNT signals and message-based data exchange each represent distinct challenges to navigation in a burgeoning operational lunar environment. The PNT services planned as part of the lunar communications and navigation relay architecture known as LunaNet aid in surmounting the challenges. LunaNet interoperability specifications stipulate standards for signal parameters, messages, and lunar reference systems for PNT services. Within LunaNet’s defined interoperability resides the concept of a Reference Signal to provide communication signals specifically structured to enable measurement of pseudorange, Doppler, and time transfer by the recipient. One such signal type, the Augmented Forward Signal (AFS), functions as the mainstay for LunaNet PNT, while also serving the data needs for ubiquitous broadcast of network access and rapid unscheduled dissemination of alerts and messages. The presence of a geometrically distributed network of orbiting nodes transmitting the AFS forms the basis for the Lunar Augmented Navigation System (LANS), that delivers both radio navigation and data to multiple users in the lunar environment simultaneously. After reviewing the challenges associated with lunar navigation, this paper will describe the concepts and rationale behind the LunaNet PNT services. By borrowing techniques from Earth-centric Global Navigation Satellite Services (GNSS), the Tracking and Data Relay Satellite System, and the Consultative Committee for Space Data Standards, PNT from LunaNet aids to overcome challenges faced for accurate lunar navigation.

LunaNet↗

NASA NTRSDate not supplied

Interoperable Services to Mitigate Lunar Position, Navigation, and Timing Challenges

Navigation↗

NASA NTRSDate not supplied

Microbial Optical Data Processing: A Key Step in the Metabolic Assessment of Lunar Explorer Instrument for Space Biology Applications (LEIA) and Biosentinel’s Payload Data

The BioSensor payload platform on BioSentinel and LEIA autonomously collects optical data from microbial model organisms in liquid culture. The BioSensor is designed to monitor metabolic activity using absorbance measurements of cell density and alamarBlue, a readily available colorimetric redox indicator dye. BioSentinel, a pioneering NASA CubeSat, uses yeast to study deep space radiation. LEIA investigates radiation and lunar gravity response. The experimental setup includes 16 wells equipped with three LEDs (570, 630, and 850 nm) and their corresponding photodetectors. One well is a calibration control without biology while the rest have desiccated cultures. Autonomous rehydration initiates the experiment. Data from the BioSensor are received from the flight and ground units, enabling comparison to uncover location-based metabolic rate variations. This study presents a Python Jupyter notebook developed for efficient data processing of multiple CSV files containing date and time columns, temperature, and well illumination data. It offers a user-friendly interface while maintaining computational power, automatically recognizing and iteratively processing data files in a user-input path. A Hampel filter with a short window eliminates outlier artifacts from sensor dropout. Because absorbance is a relative measurement, conversion from raw illumination requires defining a “blank” value, so the first data points are averaged to provide the necessary denominator. A cube-root function correction mitigates undesired drift caused by air pockets during the fluidic card filling phase, maintaining optical path length consistency. Beer-Lambert's law is applied to further convert absorbance values to cell and dye form concentrations, the desired science parameters. The processed data are saved and visualized as SVG plots. Future plans include extracting specific science parameters from the processed data like growth rate and metabolic rate, and identification of features corresponding to metabolic and phenotypic shifts such as starvation, shifts from aerobic to anaerobic growth, and osmotic stresses.

Space biology↗

NASA NTRSDate not supplied

Designing for Advanced Aerial Mobility: Human-Autonomy Teaming and In-Time System-Wide Safety Assurance

The continued growth of aviation shall require new innovative technologies and operational concepts to meet the ever-increasing demands on air transportation. The NASA Advanced Air Mobility (AAM) project focuses on emerging aviation markets, such as Urban Air Mobility (UAM). UAM is defined as “...a safe and efficient system for air passenger and cargo transportation within an urban area. It is inclusive of small package delivery and other urban unmanned aerial system services and supports a mix of onboard/ground-piloted and increasingly autonomous operations” ([1]). The AAM project emphasizes technology development and validating system-level concepts and solutions in coordination with other NASA Aeronautics Research Mission Directorate (ARMD) projects to enable UAM metro- and micro-plex vertiport and airspace concepts of operations. The NASA AAM research portfolio includes the concepts of Remote Supervisor-in-Command (RSC) and Fleet and Airspace Manager (FAM) as possible human roles for consumer fleet providers. NASA research in RSC is focused on development of guidelines and standards for remote pilots/operators passively and actively controlling a large fleet of autonomous aircraft. For FAM, flight and ground system concepts and technologies to enable high density homogeneous operations at increased scale from vertiport(s), and coordination with other humans in the systems (e.g., UAM urban airspace manager, Air Traffic Control) are key research areas. The envisioned UAM operations are posited to require autonomous systems to enable functions ranging from fleet and resource management to vehicle control. Although automation has become increasingly sophisticated and ubiquitous in civil aviation, autonomy represents a significant evolution in automation, which has generally been limited in functional scope and capability. As autonomy takes on increasing responsibilities, humans and machines will be required to work together in new and different ways [2], rather than traditional design approaches focused on how machines (i.e., autonomy) can do the work of people. The emerging field of human-autonomy teaming (HAT) represents a comprehensive and prioritized research-driven approach to enable the success of future emerging aviation market applications through capabilities and principles that facilitate humans and machine working and thinking better together. The NASA Transformational Tools and Technologies (TTT) Autonomous System (AS) Sub-project was created to assist with the transition into higher levels of autonomy to enable new modes of air transportation, such as UAM. TTT-AS has identified HAT as a key research need to enable UAM while maintaining today’s ultra-safe aviation system safety levels. The latter challenge has been taken up by the NASA System-Wide Safety (SWS) Project, which recognizes that aviation safety, as it evolves, shall require new ways of thinking about safety to include integration of a wide-range of existing and new safety systems and practices, enhanced tools and technologies, increased access to data and data fusion, improved data analysis capabilities, enhanced in-time risk monitoring and detection, hazard prioritization and mitigation, safety assurance decision-support, and in-time integrated system analytics [3].The operational concept of UAM represents a variety of work that has been termed, “work-as-imagined” to characterize the idea that how people think that work is done and how work is actually done are often not the same [4]. To ensure design success and system safety, looking at “work-as-done” provides a comparative approach toward UAM concept and technology design through examination of corresponding analogs found today in aviation (e.g., on-demand operations) and other transportation domains (e.g., port operations). The paper shall discuss various alternative applications with specific focus on airline operation center (AOC) operations, and unmanned aerial system (UAS) command-and-control to inform scaled-versions of FAM and RSC, respectively, and with consideration of the national airspace system contextual environment. The tenets and principles of the HAT field and current NASA research efforts under the TTT-AS sub-project shall also be described. Finally, the SWS sub-project efforts to develop In-Time System-Wide Safety Assurance (ISSA) and In-Time Safety Management Systems (IASMS) are discussed in terms of how “in-time” safety assurance may be conceptualized for the on-demand mobility air taxi “work-as-imagined” operational concept [5]. As part of this effort, concepts from the emerging field of resilience engineering, are being studied. Traditional approaches to aviation safety have focused on what can go wrong and how to prevent it. Another approach to thinking about system safety should reflect not only “avoiding things that go wrong” (protective safety) but also “ensuring that things go right” (productive safety), that enables a system to exhibit the resilient performance [6] necessary for the success of the future aviation system emerging concepts of operations. The paper shall describe efforts focused on how productive safety and resilience may enable a more complete approach to system safety thinking and design of ISSA and IASMS for UAM. Future directions and research needs shall also be discussed.

resilience↗

NASA NTRS2014

NASA Tech Briefs, March 2014

Topics include: Data Fusion for Global Estimation of Forest Characteristics From Sparse Lidar Data; Debris and Ice Mapping Analysis Tool - Database; Data Acquisition and Processing Software - DAPS; Metal-Assisted Fabrication of Biodegradable Porous Silicon Nanostructures; Post-Growth, In Situ Adhesion of Carbon Nanotubes to a Substrate for Robust CNT Cathodes; Integrated PEMFC Flow Field Design for Gravity-Independent Passive Water Removal; Thermal Mechanical Preparation of Glass Spheres; Mechanistic-Based Multiaxial-Stochastic-Strength Model for Transversely-Isotropic Brittle Materials; Methods for Mitigating Space Radiation Effects, Fault Detection and Correction, and Processing Sensor Data; Compact Ka-Band Antenna Feed with Double Circularly Polarized Capability; Dual-Leadframe Transient Liquid Phase Bonded Power Semiconductor Module Assembly and Bonding Process; Quad First Stage Processor: A Four-Channel Digitizer and Digital Beam-Forming Processor; Protective Sleeve for a Pyrotechnic Reefing Line Cutter; Metabolic Heat Regenerated Temperature Swing Adsorption; CubeSat Deployable Log Periodic Dipole Array; Re-entry Vehicle Shape for Enhanced Performance; NanoRacks-Scale MEMS Gas Chromatograph System; Variable Camber Aerodynamic Control Surfaces and Active Wing Shaping Control; Spacecraft Line-of-Sight Stabilization Using LWIR Earth Signature; Technique for Finding Retro-Reflectors in Flash LIDAR Imagery; Novel Hemispherical Dynamic Camera for EVAs; 360 deg Visual Detection and Object Tracking on an Autonomous Surface Vehicle; Simulation of Charge Carrier Mobility in Conducting Polymers; Observational Data Formatter Using CMOR for CMIP5; Propellant Loading Physics Model for Fault Detection Isolation and Recovery; Probabilistic Guidance for Swarms of Autonomous Agents; Reducing Drift in Stereo Visual Odometry; Future Air-Traffic Management Concepts Evaluation Tool; Examination and A Priori Analysis of a Direct Numerical Simulation Database for High-Pressure Turbulent Flows; and Resource-Constrained Application of Support Vector Machines to Imagery.

Source record↗

NASA NTRS2017

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level precision at a range of two meters with a 1U target.

Carter, C.↗

NASA NTRS2017

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However, it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level accuracy at a range of two meters with a 1U target.

Carter, Christopher↗

NASA NTRSDate not supplied

Flight Testing of In-Time Safety Assurance Technologies for UAS Operations

Ongoing research at NASA is driven by a strategic plan defined by the Aeronautics Research Mission Directorate and a vision for future In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. In both visions, system safety awareness and provision are expanded through increased access to relevant data; integrated analysis and predictive capabilities; improved real-time detection and alerting of domain-specific hazards; decision support, and in some cases, automated risk mitigation strategies. One primary research focus is to develop means by which more timely (i.e., “in-time”) actions may be taken to mitigate precursors, anomalies, or trends that are observed during operations. In this paper, we describe such means as a collection of Services, Functions, and Capabilities (SFCs) that are supported by an underlying information system. For example, an integrated risk assessment capability is envisioned that continuously monitors safety-related metrics and margins and recommends timely operational changes. Assessment functions and/or services can be based on data analytics and predictive models derived from heterogeneous data sets that span relevant indicator metrics and their time histories. Likewise, on-board functions can identify and reduce susceptibility to precursor conditions that have led (and can lead) to aircraft loss-of-control or out-of-control accidents. This paper summarizes development and testing of such an information system tailored to hazards anticipated for future highly autonomous flight missions near and over densely populated areas. Testing is accomplished via simulation and by using small, unmanned aircraft operating over a test range at NASA’s Langley Research Center. Flight plans and test scenarios are defined to emulate several use-cases, including package delivery; reconnaissance; fire management; and urban air taxi vertiport operations. Two test phases are summarized with Phase 1 occurring in (2019-2020) and Phase 2 ongoing (2021-present). Results focus on SFC performance, technology readiness level assessment, and requirements discovery/validation. Companion papers are cited throughout for additional details on the recent testing.

safety management↗

NASA NTRS2015

Critical Team Composition Issues for Long-Distance and Long-Duration Space Exploration: A Literature Review, an Operational Assessment, and Recommendations for Practice and Research

Prevailing team effectiveness models suggest that teams are best positioned for success when certain enabling conditions are in place (Hackman, 1987; Hackman, 2012; Mathieu, Maynard, Rapp, & Gilson, 2008; Wageman, Hackman, & Lehman, 2005). Team composition, or the configuration of member attributes, is an enabling structure key to fostering competent teamwork (Hackman, 2002; Wageman et al., 2005). A vast body of research supports the importance of team composition in team design (Bell, 2007). For example, team composition is empirically linked to outcomes such as cooperation (Eby & Dobbins, 1997), social integration (Harrison, Price, Gavin, & Florey, 2002), shared cognition (Fisher, Bell, Dierdorff, & Belohlav, 2012), information sharing (Randall, Resick, & DeChurch, 2011), adaptability (LePine, 2005), and team performance (e.g., Bell, 2007). As such, NASA has identified team composition as a potentially powerful means for mitigating the risk of performance decrements due to inadequate crew cooperation, coordination, communication, and psychosocial adaptation in future space exploration missions. Much of what is known about effective team composition is drawn from research conducted in conventional workplaces (e.g., corporate offices, production plants). Quantitative reviews of the team composition literature (e.g., Bell, 2007; Bell, Villado, Lukasik, Belau, & Briggs, 2011) are based primarily on traditional teams. Less is known about how composition affects teams operating in extreme environments such as those that will be experienced by crews of future space exploration missions. For example, long-distance and long-duration space exploration (LDSE) crews are expected to live and work in isolated and confined environments (ICEs) for up to 30 months. Crews will also experience communication time delays from mission control, which will require crews to work more autonomously (see Appendix A for more detailed information regarding the LDSE context). Given the unique context within which LDSE crews will operate, NASA identified both a gap in knowledge related to the effective composition of autonomous, LDSE crews, and the need to identify psychological and psychosocial factors, measures, and combinations thereof that can be used to compose highly effective crews (Team Gap 8). As an initial step to address Team Gap 8, we conducted a focused literature review and operational assessment related to team composition issues for LDSE. The objectives of our research were to: (1) identify critical team composition issues and their effects on team functioning in LDSE-analogous environments with a focus on key composition factors that will most likely have the strongest influence on team performance and well-being, and 1 Astronaut diary entry in regards to group interaction aboard the ISS (p.22; Stuster, 2010) 2 (2) identify and evaluate methods used to compose teams with a focus on methods used in analogous environments. The remainder of the report includes the following components: (a) literature review methodology, (b) review of team composition theory and research, (c) methods for composing teams, (d) operational assessment results, and (e) recommendations.

Bell, Suzanne T.↗

NASA NTRS2008

John F. Kennedy Space Center's Technology Development and Application 2006-2007 Report

Topics covered include: Reversible Chemochromic Hydrogen Detectors; Determining Trajectory of Triboelectrically Charged Particles, Using Discrete Element Modeling; Using Indium Tin Oxide To Mitigate Dust on Viewing Ports; High-Performance Polyimide Powder Coatings; Controlled-Release Microcapsules for Smart Coatings for Corrosion Applications; Aerocoat 7 Replacement Coatings; Photocatalytic Coatings for Exploration and Spaceport Design; New Materials for the Repair of Polyimide Electrical Wire Insulation; Commodity-Free Calibration; Novel Ice Mitigation Methods; Crack Offset Measurement With the Projected Laser Target Device; New Materials for Structural Composites and Protective Coatings; Fire Chemistry Testing of Spray-On Foam Insulation (SOFI); Using Aerogel-Based Insulation Material To Prevent Foam Loss on the Liquid-Hydrogen Intertank; Particle Ejection and Levitation Technology (PELT); Electrostatic Characterization of Lunar Dust; Numerical Analysis of Rocket Exhaust Cratering; RESOLVE Projects: Lunar Water Resource Demonstration and Regolith Volatile Characterization; Tribocharging Lunar Soil for Electrostatic Beneficiation; Numerically Modeling the Erosion of Lunar Soil by Rocket Exhaust Plumes; Trajectory Model of Lunar Dust Particles; Using Lunar Module Shadows To Scale the Effects of Rocket Exhaust Plumes; Predicting the Acoustic Environment Induced by the Launch of the Ares I Vehicle; Measuring Ultrasonic Acoustic Velocity in a Thin Sheet of Graphite Epoxy Composite; Hail Size Distribution Mapping; Launch Pad 39 Hail Monitor Array System; Autonomous Flight Safety System - Phase III; The Photogrammetry Cube; Bird Vision System; Automating Range Surveillance Through Radio Interferometry and Field Strength Mapping Techniques; Next-Generation Telemetry Workstation; GPS Metric Tracking Unit; and Space-Based Range.

Source record↗

NASA NTRS2016

HIAD on ULA (HULA) Orbital Reentry Flight Experiment Concept

This paper describes a proposed orbital velocity reentry flight test of a Hypersonic Inflatable Aerodynamic Decelerator (HIAD). The flight test builds upon ground development activities that continue to advance the materials, design, and manufacturing techniques for the inflatable structure and flexible thermal protection system (F-TPS) that comprise the inflatable heat shield. While certain aspects of material and system performance can be assessed using a variety of ground testing capabilities, only orbital velocity energy on a trajectory through the gradient density of the atmosphere can impart the combined aerodynamic and aeroheating design environments in real time. To achieve this at limited cost, the HIAD would be delivered to a spin-stabilized entry trajectory as a secondary payload on the Centaur stage of a United Launch Alliance (ULA) Atlas V launch vehicle. Initial trajectory studies indicate that the combination of launch vehicle capability and achievable reentry vehicle ballistic numbers make this a strategic opportunity for technology development. This 4 to 6 meter diameter scale aeroshell flight, referred to as HIAD on ULA (HULA), would also contribute to ULA asset recovery development. ULA has proposed that a HIAD be utilized as part of the Sensible, Modular, Autonomous Return Technology (SMART) initiative to enable recovery of the Vulcan launch vehicle booster main engines [1], including a Mid-Air Recovery (MAR) to gently return these assets for reuse. Whereas HULA will attain valuable aerothermal and structural response data toward advancing HIAD technology, it may also provide a largest-to-date scaled flight test of the MAR operation, which in turn would allow the examination of a nearly pristine post-entry aeroshell. By utilizing infrared camera imaging, HULA will also attain aft-side thermal response data, enhancing understanding of the aft side aerothermal environment, an area of high uncertainty. The aeroshell inflation will utilize a heritage design compressed gas system to minimize development costs. The data will be captured to both an onboard recorder and a recorder that is jettisoned and recovered separately from the reentry vehicle to mitigate risk. This paper provides an overview, including the architecture and flight concept of operations, for the proposed HULA flight experiment.

Dinonno, J. M.↗

NASA NTRS2018

Ground Autonomy for an Aging Spacecraft

As it approaches the sixteenth of a 5 year prime mission, NASA's Solar Radiation and Climate Experiment (SORCE) mission continues to meet and exceed all science requirements while operating with severely degraded batteries. By 2013, the batteries had degraded such that the On Board Computer (OBC) could not be powered through eclipse. This prevents science data collection in eclipse and erases over 99% of all stored science and engineering telemetry. To mitigate these problems, the Flight Operations Team (FOT) at the Laboratory for Atmospheric and Space Physics (LASP) adopted a new operations scheme. "Daylight Only Operations" (DO-OP) transitions the spacecraft from safemode to science mode every orbit. This involved heavily automating the transition process using ground autonomy to improve spacecraft recovery time to 6 minutes - down from 3 orbits of manual commanding. While highly successful, this method of operations poses daily challenges that must be overcome using increasingly complex ground software.

Autonomous Operations↗

NASA NTRS2024

Testing of Advanced Capabilities to Enable In-time Safety Management and Assurance for Future Flight Operations

In order to refine an initial Concept of Operations, explore Concepts of Use, and expose/validate requirements for future In-Time Aviation Safety Management Systems (IASMS), testing architectures were created, along with a set of capabilities and underlying information exchange protocols. These systems were conceived and developed based on hazards associated with two envisioned urban area flight domains: (1) highly autonomous small uncrewed aerial systems (sUAS) operating at low altitudes, and (2) highly autonomous air taxis. The initial scope of this development is described in [1]; this report provides an update, focusing on the subsequent developments and test activities. As stated in [1], it is important to note that there are many capabilities already in use by the industry (or soon to be in use) that will play critical roles in future IASMS designs. Those reported here were developed to address a gap in the current state-of-the-art regarding specific hazards/risks, and/or to allow for investigation of the interplay between and across hazard types — particularly regarding how overall safety risk can be reduced or managed effectively. Results of testing and development activities are organized by the operational phase wherein a particular capability would be employed (i.e., preflight, in-flight, and post-flight/off-line). Pre-flight: A set of capabilities were developed to help mitigate safety risk prior to flight (e.g., during flight and mission planning). Results of testing summarize (1) validation activities to raise the Technology Readiness Level (TRL) and (2) evaluation activities where the capabilities were applied to flight/mission planning procedures and used by operators/pilots. For the latter, flight plans were automatically assessed, and operators/pilots were notified of hazardous flight segments so as to enable adjustment of the flight plan and re-evaluation, and/or to better inform go/no-go decisions. Capabilities addressed hazards associated with power consumption, third-party risk, wind, navigation system performance, radiofrequency interference, and proximity to geo-spatial threats (e.g., buildings, trees, and no-fly zones). In-flight: Flight experiments tested capabilities that detect and respond to hazards encountered during flight. In the first series, safety hazards were monitored and assessed onboard, and system-generated mitigation maneuvers were recorded (but not acted upon by the vehicle). In the second series, mitigation maneuver commands directed the aircraft in response to safety hazards (i.e., auto-mitigation). The sUAS used for testing is described in full, as is the test architecture, which included commercial avionics, research avionics, and onboard software designed to detect, assess, and respond to hazards. The onboard system was designed as a run-time assurance framework, consistent with [2] and supportive of both supervisory and automated modes. The primary functions included: real-time risk assessment (RTRA), auto-pilot monitoring, constraint monitoring, and contingency select/triggering. RTRA performs integrated risk assessment considering data from several hazard-related monitors (e.g., battery, motors, navigation, communications, population density, and loss-of-control). Post-flight/off-line: Data monitored and recorded during flights can enable IASMS capabilities that execute after flights have completed (or “off-line”). These include: (1) the ability to identify anomalies and trends that may only be observable when comparing data spanning a number of similar flights; (2) the ability to update and validate pre-flight and in-flight capabilities and any underlying models to improve their performance; (3) the ability to report anomalies/off-nominals that may indicate design changes or maintenance actions are needed; and (4) the ability for humans involved in operations to report safety-relevant observations to help in understanding the flight data and/or the operational context of a flight. Progress on three such capabilities is summarized; the first investigates anomaly detection given a limited set of flight logs and applies an approach previously used for space operations. The second explores what could be identified using a larger set of flight logs, including from web-based forums where flight logs are posted by sUAS autopilot users. The third creates a new means of collecting information on UAS incidents and accidents via the Aviation Safety Reporting System (ASRS).

sUAS↗