Results for “TFAWS Short Course” — Page 5

NASA NTRSDate not supplied

The Origin of Palimpsests

Palimpsests are the most enigmatic impact features observed on icy worlds of the Solar System. Palimpsests are large impact features which are bright, old, mostly flat, and roughly circular. They range from >150 to ~350 km in diameter and sometimes exhibit recognizable associated radial secondary ejecta crater strings beyond their rims. Curiously, among all the Solar System's icy worlds, palimpsests are exclusively seen on the icy Galilean moons. Palimpsests are obviously different than similarly sized impact features seen on other icy satellites. For example, Evander, a 350 km diameter peak-ring impact basin on Saturn’s moon Dione, has a very low depth/diameter ratio of 0.008, indicating significant viscous relaxation. Nevertheless, it still retains short wavelength topography including a prominent central peak, peak ring, and a continuous rim, none of which are seen at palimpsests. Palimpsests display an approximately circular, and dominating, expanse of undulating plains, which is level with surrounding terrain and shows no recognizable rim. At the center of palimpsests are smooth central plains that are enclosed by a low scarp. Central plains material superposes the surrounding undulating plains and is littered with small blocks reminiscent of “small chaos” on Europa. Palimpsests have yet to be explored using modern impact simulation tools. We have begun to investigate two competing hypotheses: (A) Palimpsests form on targets which have a preexisting near-subsurface layer that is liquid or solid but very weak, and is excavated as proximal ejecta; or (B) They form in a solid ice target underlain by a steep thermal gradient that strongly influences the resulting impact feature, including the production of impact-induced melting at depth that is then a major component of proximal ejecta. Our results will have profound implications for the early thermal history of the icy Galilean satellites. We will test our two hypotheses for the formation of palimpsests on Ganymede (where they are both best observed and preserved) by means of 2D iSALE hydrodynamic simulations of impacts into ice targets that will be structured according to the scenarios for each hypothesis, with select runs in 3D. We have already conducted a pilot study using 2D iSALE that has yielded promising results, which we will report out at the meeting.

palimpsests↗

NASA NTRS1962

Manned Lunar Landing Via Rendezvous

In any mission description, the vehicles, the flight profiles, and the astrionics hardware to im- plement the mission are all tightly interwoven things. A final result evolves only after many iterations to the solution are made. This paper will describe one of these iterations in the Saturn C-5 Earth Orbit Rendezvous approach to the Manned Lunar Landing Program. Since the iter- ation to be described in an nthone, there exists some basis for the hope that the perturbation from the final solution is small. This paper is not concerned with the landing itself, but only with those operations leading to injection of the space craft into the lunar trans- fer trajectory. However, as is to be expected, it is the target conditions which set the pace for the overall operation. The entire operation must be sized to culminate at a time and place which places the lunar target in an attainable position. The procedure would call for a burst of activity lasting over a relatively short time as compared to the long and extensive preparations leading up to it. The activity must be aimed at the opening of the lunar "launch window". Figure 1 illustrates the variation in the velocity increment required to launch a vehicle into a lunar transfer trajectory from a 485 kilometer earth orbit. The minima are at irregularly spaced intervals and are a func- tion of the inclination of the lunar and the earth satellite planes and of the position of the moon in its orbit around the earth (i. e. , the day of the month). In an operations analysis these spacings will influence the number of vehicles on the launch pad (primary and back-up) , their state of readi- ness, the firing rate, and also the flight profile to be chosen. Whether it is decided to go by "con- necting" or by "tanking" mode, the objective must be to get the spacecraft in the launch ready state at the opening of one of these launch windows. It may be desired that the first vehicle be capable of remaining in a functionally capable state even after bridging one or more of the gaps between the windows. This consideration will influence the design of the vehicles as well as the operational modes to be designed into the flight control hard- ware. For example, a sleep switch may be de- sirable from the standpoint of savings in battery we ight.

LUNAR LANDING↗

NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

NASA NTRS1999

System Identification for Integrated Aircraft Development and Flight Testing [l'Identification Des Systemes Pour le Developpement Integre des Aeronefs et les Essais en Vol]

Over the last decades flight vehicles such as aircraft and helicopters entering service and requiring increased operational effectiveness have with few exceptions experienced prolonged flight test development to achieve full certification. In many cases the original requirements had later to be reduced to enable release to service. The impact on the customer, and manufacturer has been considerable leading to increased costs and or reduced operational capabilities. These costly experiences are largely a result of the flight vehicle not behaving as modelled and designed. The evaluation of flight test data can be used as a tool for validating windtunnel results and mathematical models describing the flight dynamical behaviour. In this sense the uncertainty of important aerodynamic stability and control parameters can be reduced and the confidence of aircraft mathematical models improved. An additional important factor comes from the implementation of active control systems offering the promise of significantly increased flight vehicle performance and operational capability. This approach extends the traditional trade-offs between aerodynamics, structures and propulsion systems to include full- time, full-authority fly-by-wire/light systems. It is imperative that the aerodynamic stability and control parameters of such integrated flight and propulsion control systems have to turn out inflight as predicted, since inherent stability margins will be lower and the flight control system must correct these deficiencies to provide flight critical redundancy and safety. With the methodology of system identification from flight tests it is possible to sense the control inputs and the flight vehicle reactions Such as accelerations, rates and attitudes. The mathematical model, e.g. the model structure and parameters, has to be determined from the relationship of the measured control inputs and the system's responses. The aim of this symposium was to review the present state of the art of flight vehicle system and parameter identification techniques, and to provide a critical appraisal of current methods developed and applied to flight test data in a number of NATO nations. Particular emphasis was placed on practical aspects and lessons learned in order to generate information useful to the flight test community in industry and government agencies. The technical papers share invaluable experience and emphasize the advances of flight vehicle system identification over the last years to the point where confidence and robustness level is now reasonably high. The symposium covered overviews of identification methodologies, flight test techniques, recent aircraft and helicopter application programs, and a session of short papers covering up-to-the-minute flight test results. A final discussion included prepared comments from experts and concluded with key issues learned in the application of system identification and future research needs. The essential benefits to NATO nations can be condensed as follows: More accurate mathematical models for high bandwidth flight control systems, Improved assessment and evaluation of flying qualities, High fidelity mathematical models for flight vehicle development and mission training simulators, and generally, Reduced flight test time and costs.

Advisory Group for Aerospace Research and Developm↗

NASA NTRS2026

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra↗

NASA NTRS2003

Ultra-High-Temperature Ceramics Evaluated for Aeropropulsion Use

Ultra-high-temperature ceramics (UHTC) are a group of materials consisting of zirconium diboride (ZrB2) or hafnium diboride (HfB2) plus silicon carbide (SiC), and in some instances, carbon (C). They offer a combination of properties that make them candidates for airframe leading edges on sharp-bodied reentry vehicles. These UHTCs perform well in the environment for such applications (i.e., air at low pressures). The purpose of this study at the NASA Glenn Research Center was to examine three of these materials under conditions more representative of a propulsion environment: that is, higher oxygen partial pressure and total pressure. Relatively long, multiple-exposure cycles were emphasized. We completed an in-house study of ZrB2 plus 20 vol% SiC (abbreviated as ZS), ZrB2 plus 14 vol% SiC and 30 vol% C (ZSC), and SCS-9a SiC fiber-reinforced ZrB2 plus 20 vol% SiC (ZSS). HfB2-based compositions were not included in the study because of their high cost. The capability of UHTC for propulsion applications must be compared with that of mature, available, and commercially used ceramics such as silicon nitride (e.g., AS-800) to put things in proper perspective. In terms of mechanical properties, UHTCs fall short in terms of strength and fracture toughness. At about 1300 C, the creep resistance of ZS appears to be superior to the creep resistance reported for AS-800. However, the stress rupture life for Si3N4 under stress and temperature conditions similar to those used in this study is measured in hundreds of hours. Because of oxidation, ZS could not achieve such lives. In terms of oxidation resistance, acceptable amounts of material recession in 1 hour to thousands of hours, depending on the specific propulsion application, are on the order of 100 to 300 mm. This converts to an acceptable range of parabolic recession rate constants kp" of approximately less than or equal to 10(exp -1) to 10(exp -2) square millimeters per hour for a 1-hr application. For a 100-hr application, an acceptable range of kp" would be less than or equal to those values divided by 100. For the more oxidation resistant ZS material, measured parabolic recession rate constants were 4.7 x 10(exp -3) millimeters per hour at 1327 C, 7.8 x 10(exp -2) square millimeters per hour at 1627 C, and 1.3 millimeters per hour at 1927 C. Thus, recession rate constants for ZS are acceptable at 1327 C for a 1-hr application, but here silicon nitride is a superior material. At 1627 C, ZS oxidation is marginal for a 1-hr application, but dimensional growth would be an issue. In a 100-hr application, ZS cannot be considered at any temperature. Our cursory examination of thermal shock, both from a theoretical and experimental viewpoint, indicated that the ZS and ZSC UHTCs are inferior to AS-800 silicon nitride. On the basis of this limited study, UHTCs are not ready to be considered as aeropropulsion materials for any applications longer than a few minutes. Current materials suffer from aggressive oxidation and moisture attack (Quynhgiao Nguyen, NASA Glenn, and Raymond C. Robinson, QSS Group, Inc., Cleveland, OH, 2002, private communication), and they are susceptible to thermal shock. For long-term propulsion applications, major improvements in environmental durability are needed. Work is in progress to improve the oxidation resistance of UHTC materials.

Stanley R Levine↗

NASA NTRSDate not supplied

Thin-Film Embedded Sensors for Battery Health Monitoring

Hybrid or all-electric aircraft are being developed as the next generation of aircraft to both allow new forms of aviation and decrease environmental impact. Since these types of aircraft are based on high-capacity battery technology, safe operation of these batteries becomes increasingly important. In particular, the potential for battery failure due to uncontrolled chemical reactions resulting in thermal runaway, catastrophic failure, and battery fires must be addressed in order for such battery technology to have the level of safety needed for standard aviation implementation. Efforts to ensure battery safety often involve engineering solutions that seek to contain rather than prevent such events by early detection. Such approaches increase the system weight and decrease the power per unit mass provided by the battery system. Existing methods for measuring battery parameters to determine the battery state-of-health are limited. These methods include electrical measurements of the cell current and/or voltage output as well as temperature measurements taken externally on the cell surface. Such external temperature measurements are limited in their ability to provide early warning of impending battery failure. In response, an effort to develop sensors operating internal to battery for health monitoring has been ongoing in the NASA Sensor-based Prognostics to Avoid Runaway Reactions & Catastrophic Ignition (SPARRCI) project. The basic approach associated with this sensor work is the deposition of thin film sensors on the battery separator located between the anode and cathode of the battery. These thin film sensors are then monitored to determine changes in battery parameters and health. Microfabrication techniques are employed to minimize the overall impact of the sensors on battery operation through the implementation of sensors with minimal size, weight, and power consumption. The thickness of the films, which are fabricated through physical vapor deposition (sputtering), are on the order of thousands of angstroms and can have minimal surface area. Thin film sensors for system health management have been implemented for a many decades on complex components for aerospace applications. However, the application of thin films of this type on a battery separator for internal battery monitoring applications has not previously been demonstrated to our knowledge. This paper describes the development of sensors for the internal battery monitoring through the use of thin film sensor technology. Thin metal films were successfully deposited on a battery separator polymer material with good adherence and electrical continuity. Multiple types of sensors have been deposited, as well as lead connections from the sensor to the edge of the separator material. The ability of these thin film sensors immersed in electrolyte to perform multiple types of battery parameter measurements has been demonstrated. For example, a multiparameter sensor system measured multiple properties simultaneously inside of a pouch cell over a wide temperature range. Further, real time measurement of interior temperature changes in a battery pouch cell with an integrated interior temperature sensor was demonstrated. These changes include detecting a fault in the battery (shorting) in situ with rapid response time (less than a minute) corresponding to a more limited response by a temperature sensor mounted externally. Other aspects of monitoring battery health were also explored, such as real-time measurement of simulated dendrite growth/metal deposition by sensor on separator material demonstrated. Future efforts will include improvements in the durability of the sensor structure to allow introduction of the approach into standard battery fabrication techniques. Overall, this work is a step forward in providing a method to prevent catastrophic battery failures and provide a foundation for safer, lighter, and higher energy batteries for the electric aircraft industry.

thin film battery health↗