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NASA NTRSDate not supplied

Assured Contingency Landing Management for Advanced Air Mobility

Advanced Air Mobility (AAM) is quickly developing as a new air transportation system that moves people and packages in the regions previously not / less served by the current aviation systems. Such AAM must operate safely despite the potential to encounter hazards and experience anomalies and failures in-flight. It becomes especially important to have systematic auto-mitigation strategies to perform safe contingency actions in AAM flight operations, as pilots have limited Situational Awareness (SA) and limited time to make prompt decisions when encountering failures/anomalies in high-density low altitude airspace. This paper presents Assured Contingency Landing Management (ACLM) with an online landing strategy selection to decide between the following three options when a contingency landing is required: (1) Return-to-launch landing site, (2) Land immediately at a nearby clear but unprepared site, (3) Land at a prepared landing site from the approximate footprint. Our presented algorithm shows a real-time auto-mitigation loop with multiple threads that run simultaneously to check controllability, reachability, and intermediate decisions to hold/ loiter or continue the flight plan as the landing strategy solution is being computed. Case study simulation is demonstrated with the safety-critical propulsion system and battery system and shows how different failure scenarios impact the landing strategy selection.

Autonomous Mitigation↗

NASA NTRS2001

Collaboration Between NASA Centers of Excellence on Autonomous System Software Development

Software for space systems flight operations has its roots in the early days of the space program when computer systems were incapable of supporting highly complex and flexible control logic. Control systems relied on fast data acquisition and supervisory control from a roomful of systems engineers on the ground. Even though computer hardware and software has become many orders of magnitude more capable, space systems have largely adhered to this original paradigm In an effort to break this mold, Kennedy Space Center (KSC) has invested in the development of model-based diagnosis and control applications for ten years having broad experience in both ground and spacecraft systems and software. KSC has now partnered with Ames Research Center (ARC), NASA's Center of Excellence in Information Technology, to create a new paradigm for the control of dynamic space systems. ARC has developed model-based diagnosis and intelligent planning software that enables spacecraft to handle most routine problems automatically and allocate resources in a flexible way to realize mission objectives. ARC demonstrated the utility of onboard diagnosis and planning with an experiment aboard Deep Space I in 1999. This paper highlights the software control system collaboration between KSC and ARC. KSC has developed a Mars In-situ Resource Utilization testbed based on the Reverse Water Gas Shift (RWGS) reaction. This plant, built in KSC's Applied Chemistry Laboratory, is capable of producing the large amount of Oxygen that would be needed to support a Human Mars Mission. KSC and ARC are cooperating to develop an autonomous, fault-tolerant control system for RWGS to meet the need for autonomy on deep space missions. The paper will also describe how the new system software paradigm will be applied to Vehicle Health Monitoring, tested on the new X vehicles and integrated into future launch processing systems.

Goodrich, Charles H.↗

NASA NTRS2015

Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team

A team is defined as: "two or more individuals who interact socially and adaptively, have shared or common goals, and hold meaningful task interdependences; it is hierarchically structured and has a limited life span; in it expertise and roles are distributed; and it is embedded within an organization/environmental context that influences and is influenced by ongoing processes and performance outcomes" (Salas, Stagl, Burke, & Goodwin, 2007, p. 189). From the NASA perspective, a team is commonly understood to be a collection of individuals that is assigned to support and achieve a particular mission. Thus, depending on context, this definition can encompass both the spaceflight crew and the individuals and teams in the larger multi-team system who are assigned to support that crew during a mission. The Team Risk outcomes of interest are predominantly performance related, with a secondary emphasis on long-term health; this is somewhat unique in the NASA HRP in that most Risk areas are medically related and primarily focused on long-term health consequences. In many operational environments (e.g., aviation), performance is assessed as the avoidance of errors. However, the research on performance errors is ambiguous. It implies that actions may be dichotomized into "correct" or "incorrect" responses, where incorrect responses or errors are always undesirable. Researchers have argued that this dichotomy is a harmful oversimplification, and it would be more productive to focus on the variability of human performance and how organizations can manage that variability (Hollnagel, Woods, & Leveson, 2006) (Category III1). Two problems occur when focusing on performance errors: 1) the errors are infrequent and, therefore, difficult to observe and record; and 2) the errors do not directly correspond to failure. Research reveals that humans are fairly adept at correcting or compensating for performance errors before such errors result in recognizable or recordable failures. Astronauts are notably adept high performers. Most failures are recorded only when multiple, small errors occur and humans are unable to recognize and correct or compensate for these errors in time to prevent a failure (Dismukes, Berman, Loukopoulos, 2007) (Category III). More commonly, observers record variability in levels of performance. Some teams commit no observable errors but fail to achieve performance objectives or perform only adequately, while other teams commit some errors but perform spectacularly. Successful performance, therefore, cannot be viewed as simply the absence of errors or the avoidance of failure Johnson Space Center (JSC) Joint Leadership Team, 2008). While failure is commonly attributed to making a major error, focusing solely on the elimination of error(s) does not significantly reduce the risk of failure. Failure may also occur when performance is simply insufficient or an effort is incapable of adjusting sufficiently to a contextual change (e.g., changing levels of autonomy).

Landon, Lauren Blackwell↗

NASA NTRS2012

Science Benefits of Onboard Spacecraft Navigation

Primitive bodies (asteroids and comets), which have remained relatively unaltered since their formation, are important targets for scientific missions that seek to understand the evolution of the solar system. Often the first step is to fly by these bodies with robotic spacecraft. The key to maximizing data returns from these flybys is to determine the spacecraft trajectory relative to the target body-in short, navigate the spacecraft- with sufficient accuracy so that the target is guaranteed to be in the instruments' field of view. The most powerful navigation data in these scenarios are images taken by the spacecraft of the target against a known star field (onboard astrometry). Traditionally, the relative trajectory of the spacecraft must be estimated hours to days in advance using images collected by the spacecraft. This is because of (1)!the long round-trip light times between the spacecraft and the Earth and (2)!the time needed to downlink and process navigation data on the ground, make decisions based on the result, and build and uplink instrument pointing sequences from the results. The light time and processing time compromise navigation accuracy considerably, because there is not enough time to use more accurate data collected closer to the target-such data are more accurate because the angular capability of the onboard astrometry is essentially constant as the distance to the target decreases, resulting in better "plane-of- sky" knowledge of the target. Excellent examples of these timing limitations are high-speed comet encounters. Comets are difficult to observe up close; their orbits often limit scientists to brief, rapid flybys, and their coma further restricts viewers from seeing the nucleus in any detail, unless they can view the nucleus at close range. Comet nuclei details are typically discernable for much shorter durations than the roundtrip light time to Earth, so robotic spacecraft must be able to perform onboard navigation. This onboard navigation can be accomplished through a self- contained system that by eliminating light time restrictions dramatically improves the relative trajectory knowledge and control and subsequently increases the amount of quality data collected. Flybys are one-time events, so the system's underlying algorithms and software must be extremely robust. The autonomous software must also be able to cope with the unknown size, shape, and orientation of the previously unseen comet nucleus. Furthermore, algorithms must be reliable in the presence of imperfections and/or damage to onboard cameras accrued after many years of deep-space operations. The AutoNav operational flight software packages, developed by scientists at the Jet Propulsion Laboratory (JPL) under contract with NASA, meet all these requirements. They have been directly responsible for the successful encounters on all of NASA's close-up comet-imaging missions (see Figure !1). AutoNav is the only system to date that has autonomously tracked comet nuclei during encounters and performed autonomous interplanetary navigation. AutoNav has enabled five cometary flyby missions (Table!1) residing on four NASA spacecraft provided by three different spacecraft builders. Using this software, missions were able to process a combined total of nearly 1000 images previously unseen by humans. By eliminating the need to navigate spacecraft from Earth, the accuracy gained by AutoNav during flybys compared to ground-based navigation is about 1!order of magnitude in targeting and 2!orders of magnitude in time of flight. These benefits ensure that pointing errors do not compromise data gathered during flybys. In addition, these benefits can be applied to flybys of other solar system objects, flybys at much slower relative velocities, mosaic imaging campaigns, and other proximity activities (e.g., orbiting, hovering, and descent/ascent).

Autonomy↗

NASA NTRSDate not supplied

Developing Mars-Based Clinical Scenarios for an Earth Independent Medical Operations (EIMO) – Based Decision Support Service

As crewed missions move beyond Low-Earth Orbit, pre-mission planning cannot fully buy down the medical risks of exploration-class missions. Martian missions, where increased hazards exist, (such as long-duration spaceflight, surface-level EVA operations, and communications delays) will require a paradigm shift in the structure of a medical system. An Earth-Independent Medical Operations-based Medical System (EIMO-MS) will need to optimize four critical domains to help provide medical care: utilization of Pre-Mission Planning, augmentation of Acute and Prolonged Medical Decision Making, automated tracking of Resource Management, and assistance in Task Load Balance. The ideal EIMO-MS will be able to accomplish this goal by having an interactive, adaptable interface that will be able to provide real-time medical services. It must respond based on the level of crewmember training, medical situation, and available medical and non-medical resources. To showcase the capabilities and requirements of such a sophisticated automated MS, a series of clinical scenarios of escalating complexity were developed with clinical and systems engineering input. These scenarios describe in clinical detail what a theoretical future medical system, enhanced with multiple information streams (such as a medical database, an AI-based Decision Support System, real-time monitoring, enhanced in-situ laboratory imaging, etc.) can achieve in conjunction with a trained and experienced crew. Scenarios are comprised of: a context section including objectives and applicable spaceflight environment, a highlighted assumptions section, a clinical narrative section, and a systems engineering activity diagram demonstrating the integrated Medical System (MS). The “swim lanes” of the activity diagram act as the logistical core of each scenario and show how the MS will interact with the crew, ground support, and other in-flight systems. The Design Reference Mission that is used for the scenarios is based on existing reference mission profiles [1] with a projected 30-sol stay on the Martian surface. Scenarios span the spectrum from planned evaluations, minor medical care, urgent care, surgical guidance, critical and expectant management, and behavioral health care. Mission complexity will exponentially increase during deep space and Mars exploration-class missions, and medical support for these missions will likewise need to increase in autonomy and adaptability. The integrated system that will support these missions will need to provide assistance in a variety of anticipated and unforeseen scenarios. These medical scenarios, guided by clinician input, are initial steps in crafting the requirements for an EIMO-based medical system. By working in a systems engineering framework, requirements and capabilities can be extracted and mapped while maintaining a clinical core.

Prashant Parmar↗

NASA NTRS2018

Coronal Imaging with the Solar Ultraviolet Imager

Coronal imaging capabilities of the Solar UltraViolet Imager (SUVI) on the Geostationary Operational Environmental Satellite-16 (GOES-16) are investigated. Launched in 2016, GOES-16 is stationed at 75.2 deg W longitude and accommodates both terrestrial and space weather instruments. SUVI is one of two instruments observing the Sun, providing solar images in six extreme ultraviolet (EUV) wavelengths: 94A, 131A, 171A, 195A, 284A and 304A. Mounted on a two axis gimballed Sun Pointed Platform (SPP), its 53 arcminute square field of view is nominally Sun-centered to provide high dynamic range images in all six wavelengths every four minutes. Analyses of on-orbit data indicated that SUVI had sufficient dynamic range and sensitivity in the 171A and 195A wavelengths to image the corona to the largest heights above the Sun to date while simultaneously imaging the Sun. The 1.6 megapixel Charge Coupled Device (CCD) detector enables the capture of the fine features of the corona. On-orbit calibration tests requiring movement of the SUVI line-of-sight off the Sun, demonstrated that the resulting dynamic disturbance didn't adversely impact the earth-pointing instrument performance. Combining these factors, we conducted a test to assess the performance of SUVI as an EUV extremely wide-field coronal imager by off-pointing the SPP around the Sun and synthesizing an image that's about 4 times the diameter of the Sun. The capability to perform coronal imaging at these two wavelengths is demonstrated by off-pointing the SUVI boresight to nine locations around the Sun and generating a composite coronal image that extends to approx. 4 solar radii. For this purpose, we exploited the satellite's ability to provide stable, fine pointing, even during the slews. Various exposure durations were considered during the first trial and a composite coronal image is obtained for each wavelength. The results are promising. The off-pointing locations and the exposure duration are being refined for the subsequent trials. The routine use of an ultraviolet solar imager as both an imager and a EUV coronagraph would be the first of its kind and is an exciting development. The on-orbit solar coronagraphs to date provide white light images with fields of view extending from 4-15 solar radii. Earlier, Seaton, et al investigated the evolution of the corona in EUV near the solar surface with the data from the Sun Watcher with Active Pixels and Image Processing (SWAP) EUV solar telescope on board the Project for On-Board Autonomy 2 (PROBA2). The presence of corona in EUV even to 4 solar radii is not known. The results of these experiments will begin to fill this void.

Tadikonda, Sivakumara K.↗

NASA NTRS2018

Coronal Imaging with the Solar Ultraviolet Imager

Coronal imaging capabilities of the Solar UltraViolet Imager (SUVI) on the Geostationary Operational Environmental Satellite-16 (GOES-16) are investigated. Launched in 2016, GOES-16 is stationed at 75.2 deg W longitude and accommodates both terrestrial and space weather instruments. SUVI is one of two instruments observing the Sun, providing solar images in six extreme ultraviolet (EUV) wavelengths: 94A, 131A, 171A, 195A, 284A and 304A. Mounted on a two axis gimballed Sun Pointed Platform (SPP), its 53 arc minute square field of view is nominally Sun-centered to provide high dynamic range images in all six wavelengths every four minutes. Analyses of on-orbit data indicated that SUVI had sufficient dynamic range and sensitivity in the 171A and 195A wavelengths to image the corona to the largest heights above the Sun to date while simultaneously imaging the Sun. The 1.6 megapixel Charge Coupled Device (CCD) detector enables the capture of the fine features of the corona. On-orbit calibration tests requiring movement of the SUVI line-of-sight off the Sun, demonstrated that the resulting dynamic disturbance didn't adversely impact the earth-pointing instrument performance. Combining these factors, we conducted a test to assess the performance of SUVI as an EUV extremely wide-field coronal imager by off-pointing the SPP around the Sun and synthesizing an image that's about 4 times the diameter of the Sun. The capability to perform coronal imaging at these two wavelengths is demonstrated by off-pointing the SUVI boresight to nine locations around the Sun and generating a composite coronal image that extends to approx. 4 solar radii. For this purpose, we exploited the satellite's ability to provide stable, fine pointing, even during the slews. Various exposure durations were considered during the first trial and a composite coronal image is obtained for each wavelength. The results are promising. The off-pointing locations and the exposure duration are being refined for the subsequent trials. The routine use of an ultraviolet solar imager as both an imager and a EUV coronagraph would be the first of its kind and is an exciting development. The on-orbit solar coronagraphs to date provide white light images with fields of view extending from 4-15 solar radii. Earlier, Seaton, et al investigated the evolution of the corona in EUV near the solar surface with the data from the Sun Watcher with Active Pixels and Image Processing (SWAP) EUV solar telescope on board the Project for On-Board Autonomy 2 (PROBA2). The presence of corona in EUV even to 4 solar radii is not known. The results of these experiments will begin to fill this void.

Tadikonda, Sivakumara K.↗

NASA NTRSDate not supplied

Advances in Autonomous Communications and Operations: Tes-N Series

Advances in nanosat subsystems over the past decade have taken the CubeSat standard from a communication-limited educational tool to a powerful platform enabling space research. The potential for autonomous operations may greatly increase the capability of downlinking even larger data sets. This is enabled through miniaturization of software-defined radio/cognitive communication solutions and a rapidly growing number of ground stations and satellite network crosslinks. The TechEdSat-n orbital flight series is currently demonstrating experiments using cognitive communication concepts including User Initiated Service (UIS) and High-rate Delay Tolerant Networks (HDTN), which show a significant step toward improved capability. At the core of this is the use of the Iridium L-band Short Burst Data (SBD) modems, pioneered by TES-n for space applications. SBD enables unique rapid command, control, and scheduling to initiate the UIS and HDTN protocols. This occurs by performing GPS-assisted on-orbit ephemeris determination, enabling negotiation with high bandwidth ground assets to repeatedly downlink over a specific commercial or government-owned ground station. The technique is RF band-agnostic and may be extended to higher bandwidth stations and SDRs. This may also include free-space optical communication, through both laser and omnidirectional LEDs, which can provide an attractive protocol for downlinking very large datasets over far fewer ground stations. In addition, this may be extended to lunar applications for such future concepts as LunaNet, whereby scheduling and cognitive technologies can assist in greatly improving Earth downlink capabilities with ground stations which will see greater competition for usage. Lastly, the NASA Communication Service Program (CSP), intended to eventually replace the NASA Tracking and Data Relay Satellite System (TDRSS) will also demonstrate the feasibility of commercially-provided satellite communication capabilities. All of these combined advances, including large advances in on-board computation on small platforms, will result in more remarkable data processing capability – yielding even more as of yet unknown discoveries.

Autonomy↗

NASA NTRSDate not supplied

A Science-Focused Artificial Intelligence (AI) Responding in Real-Time to New Information: Capability Demonstration for Ocean World Missions

Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.

astrobiology↗

NASA NTRSDate not supplied

Towers: Critical Initial Infrastructure for the Moon, Such as a Power Module Support

Towers are an efficient structure commonly used to elevate systems against a gravity field, such as above the surface of a planet or the Moon. Towers can be used to elevate antennas, transmitters and sensors for communication, navigation, and observation infrastructure in support of surface operations. Near the Lunar poles, elevation of rotating solar panels enables nearly continuous panel illumination for solar power production despite the Sun remaining near the horizon year-round. Further, once technology is developed for tower assembly, this same technology can be extended to the assembly of a variety of structures including rocket blast containment shields, bridges, shelters, and habitats from either Earth-sourced or Lunar-sourced structural members. Environmental factors on the Lunar surface are vastly different than those found on Earth and have significant impact on the design of towers. Towers designed for the Lunar surface have no heritage nor Earth analog. The designs discussed herein are therefore breaking new ground creating a fundamentally new class of structures outside of current experience and intuition. The purpose of this paper is to: a) describe the unique environmental factors affecting tower design on the Lunar surface compared to Earth-based systems, b) evaluate two structural forms for the tower; telescoping tubes and an assembled truss, as well as c)provide recommendations on when each structural form is most suitable. A major contribution presented in the current paper is to provide parametric plots and supporting equations of mass and volume versus module power level and blanket height above the Lunar surface for the solar array application, to enable system level studies of optimum power module distribution and size. A secondary contribution are plots of the mass and volume of aluminum or structural glass required for assembled truss towers formed from Lunar derived structural members. An objective of achieving 1 MW of total power has been used to enable comparison of structural forms, because the total mass of solar arrays is consistent. It will be shown that for moderate module sizes, up to ~50 kW power modules, based on a telescoping tube tower have advantages, but for power modules from 50 kW to 200 kW an assembled truss tower can be created with half to one third of the tube tower mass. More significantly, when shipped from Earth, an assembled truss tower can be packed into 1/14th to 1/25th of the tube tower volume. Truss designs in the 100 kW to 200 kW range will be shown to be a favorable when assembled from either graphite-epoxy angles shipped from Earth or aluminum angles fabricated from Lunar materials. 50 kW towers are an attractive choice for both a telescoping or assembled tower with the solar arrays elevated 10 m above the Lunar surface, while increased solar array elevation favors 100 kW to 200 kW power modules.

assembly↗