SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The Microrover Flight Experiment (MFEX) is a NSAS OACT (Office of Advanced Concepts and Technology) flight experiment which, integrated with the Mars Pathfinder (MPF) lander and spacecraft system, landed on Mars on July 4, 1997.
The National Aeronautics and Space Administration (NASA) and the Department of Defense (DoD) are planning Space System of Systems (SoS) to address the new challenges of space exploration, defense, communications, navigation, Earth observation, and science. In addition, these complex systems must provide interoperability, enhanced reliability, common interfaces, dynamic operations, and autonomy in system management. Both NASA and the DoD have chosen to meet the new demands with high data rate communication systems and space Internet technologies that bring Internet Protocols (IP), routers, servers, software, and interfaces to space networks to enable as much autonomous operation of those networks as possible. These technologies reduce the cost of operations and, with higher bandwidths, support the expected voice, video, and data needed to coordinate activities at each stage of an exploration mission. In this paper, we discuss, in a generic fashion, how the architectural approaches and processes are being developed and used for defining a hypothetical communication and navigation networks infrastructure to support lunar exploration. Examples are given of the products generated by the architecture development process.
The Mars Geoscience Aerobot (MGA) is a proposed Mars aerobot (robotic aerovehicle) mission featuring advanced capabilities for surface imagimg and atmospheric science. Development of the MGA mission has been catalyzed by science objectives that include surface geology and atmospheric measurements. The MGA consists of a superpressure balloon that is reflective on top and white on the bottom to avoid condensation CO&sub2; frost during the night. The MGA also features a
As NASA exploration moves beyond earth's orbit, the need exists for long duration space systems that are resilient to events that compromise safety and performance. Fortunately, technology advances in autonomy, robotic manipulators, and modular plug-and-play architectures over the past two decades have made in-space vehicle assembly and servicing possible at acceptable cost and risk. This study evaluates future space systems needed to support scientific observatories and human/robotic Mars exploration to assess key structural design considerations. The impact of in-space assembly is discussed to identify gaps in structural technology and opportunities for new vehicle designs to support NASA's future long duration missions.
The airspace is becoming more and more complicated, and will continue to do so in the future with the integration of Unmanned Aerial Vehicles (UAVs), autonomy, spacecraft, other forms of aviation technology into the airspace. The new technology and complexity increases the importance and difficulty of safety assurance. Additionally, testing new technologies on complex aviation systems & systems of systems can be very difficult, expensive, and sometimes unsafe in real life scenarios. Prognostic methodology provides an estimate of the health and risks of a component, vehicle, or airspace and knowledge of how that will change over time. That measure is especially useful in safety determination, mission planning, and maintenance scheduling. The developed testbed will be used to validate prediction algorithms for the real-time safety monitoring of the National Airspace System (NAS) and the prediction of unsafe events. The framework injects flight related anomalies related to ground systems, routing, airport congestion, etc. to test and verify algorithms for NAS safety. In our research work, we develop a live, distributed, hardware-in-the-loop testbed for aviation and airspace prognostics along with exploring further research possibilities to verify and validate future algorithms for NAS safety. The testbed integrates virtual aircraft using the X-Plane simulator and X-PlaneConnect toolbox, UAVs using onboard sensors and cellular communications, and hardware in the loop components. In addition, the testbed includes an additional research framework to support and simplify future research activities. It enables safe, accurate, and inexpensive experimentation and research into airspace and vehicle prognosis that would not have been possible otherwise. This paper describes the design, development, and testing of this system. Software reliability, safety and latency are some of the critical design considerations in development of the testbed. Integration of HITL elements in the development phases and veri cation/ validation are key elements to this report.
After the 2003 Mars Exploration Rovers (MER) Mission, NASA plans to send a larger, longer life Mobile Science Laboratory (MSL) in 2009. This rover is planned to last 500 days, travel ten kilometers, and demonstrate autonomous capabilities that reduce the number of communication cycles now needed to achieve successful completion of activities on the surface.
Results are presented on a comparison of nutritional values of and human psychological responses to algae and of higher plants considered for growth as food on long-term missions in space, together with the technological complexities of growing these plants. The comparison shows the advantages of higher plants, with results suggesting that a high level of material recycling can be obtained. It is noted that the issue of space gravity may be not a major problem for plants because of the possibility that phototropism can provide an alternative sense of direction. Problems of waste recycling can be solved in association with plant cultivation, and a high degree of autonomy of food production can be obtained.
The first mission of NASA's New Millennium Program, Deep Space 1, has, as one of its principal demonstration-technologies, the first autonomous optical navigation system to be used in deep space.
INTRODUCTION TO MIM DEVICES Multi-functional Integrated Medical (MIM) devices conveniently incorporate multiple medical system capabilities within one device. The NASA Exploration Medical Integrated Product Team (XM-IPT) sponsored a market survey and trade study which identified the Tempus ProTM and the LifeBot 10® as the MIM devices that best met the evaluation criteria of the trade study. The Tempus ProTM (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) and LifeBot 10® (LifeBot Health, Chicago, IL) both provide vital sign measurements such as blood pressure, electrocardiograms, heart rate, end tidal CO2, respiration rate, pulse oximetry and temperature along with ultrasound imaging. A video laryngoscopy capability is unique to the Tempus ProTM, while the LifeBot 10® supports connectivity with a digital stethoscope, otoscope, eye exam camera, and dermatoscope. Both devices include procedural guidance capabilities and have various data transmission and report generation features. TECHNOLOGY DEMONSTRATIONS NASA’s exploration-class missions will have severe resource constraints, long return trip durations, significant communication delays, and limited resupply opportunities. The medical systems of these missions will need to fit within an Earth-Independent Medical Operations (EIMO) construct. Key features of an EIMO medical system include: 1) technologies that support the prevention, diagnosis, and treatment of spaceflight medical events; 2) components that meet mass, volume, power and crew time/training constraints; 3) consideration of the medical skill level of the astronaut caregiver; 4) collection, storage and analysis of medical data within a central data architecture; and 5) incorporation of appropriate guidance and support tools that allow crew autonomy. Evaluations are underway to determine if it will be beneficial to include MIM devices within exploration medical systems by conducting a series of planned technical demonstrations. Exploration Atmosphere Chamber studies are being performed to determine MIM functionality in a high oxygen concentration atmosphere. A side-by-side comparison of the Tempus ProTM and LifeBot 10® will be performed during ground-based demonstrations. Use of the MIM devices within an EIMO medical scenario simulation will be practiced during ground-based demonstrations in preparation for International Space Station (ISS) demonstrations of the MIM device. These various demonstrations are designed to gather evidence for or against the inclusion of MIM devices within an EIMO medical system. EXPECTED DEMONSTRATION OUTCOMES Information will be gained about the feasibility, benefits, and challenges of using a multifunctional, all-in-one, medical device for medical diagnosis. Information will also be collected about performance differences as available ground support decreases. Gaining this understanding will allow for further development of exploration medical system capabilities, which take the EIMO construct into consideration.
Most current methods for determining maneuvers and thrust firing sequences depend on explicit and predetermined commands generated by a combination of on-board systems and ground-based human-in-the-loop methods. For spacecraft and space structures with changing mass properties and thruster configurations, such as the Deep Space Gateway as it changes configurations throughout its lifetime, determining these commands can be time-consuming and computationally intensive. However, recent work within the Lie GroupSE (3) has offered ways of autonomously determining the location, power, precision, and capabilities of thrusters in any arbitrary position. Furthermore, a method for determining thruster firing sequences based on an arbitrary control input (both translational and rotational in a coupled, 6-element vector) and arbitrary thruster configurations has also recently been developed. When combining these methods, any spacecraft with any mass properties and thruster configurations can be understood in terms of controllability limits and thruster firing sequences can be generated quickly and with low computational load, thus extending the autonomous capabilities of deep space missions. In this work, this method is presented and explored in terms of computational load, robustness in the presence of uncertainty, and overall performance. The capabilities of this method are also examined in the case of the Deep Space Gateway both in fully controllable configurations and uncontrollable configurations.
The Galileo mission and spacecraft, consisting of a Jupiter-orbiter and an atmospheric entry probe, are discussed. Components will include: magnetometers and plasma-wave antennas on a boom, high-gain antenna, probe vehicle, two different bus electronics packages, and a radioisotope thermoelectric generator. Instruments, investigators and objectives are tabulated for both probe science and orbiter science investigations. Requirements in the design of the attitude and articulation control system are very stringent because of the complex dynamics, flexible body effects, the need for autonomy, and the severe radiation environment in the Jupiter nighborhood. Galileo was intended to be ready for launch via Space Shuttle in May of 1986.
BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.
The Lunar Gateway space station will be operated with less human oversight and control than any human spacecraft thus far. An autonomous software control architecture has been developed to allow the spacecraft to maintain safe operations of the vehicle during times of no human involvement. The development of these autonomous control functionalities has been both technical and process driven. Given that the Gateway will be built modularly with contributions from all over the world, the systems engineering processes had to be shaped to fit with the contractual and political realities of the construction of the international lunar habitat. This paper will describe these challenges and contributions to the development of human spacecraft for sustainable deep space missions.
NASA has initiated a program to demonstrate a Satellite Servicer System prototype in a series of flight tests with the Space Shuttle. When the commitment to an operational system has been demonstrated, it is anticipated that a variety of missions will develop that can productively use the servicing capability. Rendezvous and proximity operations contain key enabling technologies needed for an effective operational system. Guidance, navigation and control hardware and operational techniques must be integrated into the program. Supporting sensor technology may limit or enhance the capability of the system depending on its readiness. Requirements for docking the spacecraft in the system concept development and technology requirements are reviewed. Examples of the initial assessment of technology readiness and applications opportunities are discussed. The degree of autonomy is of particular interest.
The deep-space environment and relative transportation accessibility of the Weak Stability Boundary (WSB) region connecting the Earth-Moon and Sun-Earth libration points makes the Sun-Earth L2 an attractive operating location for future observatories. A summary is presented of key characteristics of future observatories designed to operate in this region. The ability to service observatories that operate within the region around the Lagrange points may greatly enhance their reliability, lifetime, and scientific return. The range of servicing missions might begin with initial deployment, assembly, test, and checkout. Post-assembly servicing missions might also include maintenance and repair, critical fluids resupply, and instrument upgrades. We define the range of servicing missions that can be performed with extravehicular activity, with teleoperated robots, and with autonomous robots. We then describe deployment scenarios that affect payload design. A trade study is summarized of the benefits and risks of alternative servicing sites, including at the International Space Station, at other low-Earth-orbit locations, at the Earth-Moon L1 location, and on-site at the Sun-Earth L2 location. Required technology trades and development issues for observatory servicing at each site, and with each level of autonomy, are summarized.
This presentation presents an overview of work performed at NASA Ames Research Center in 2017. The work concerns the analysis of current aircraft system management displays, and the initial development of an interface for providing information about aircraft system status. The new interface proposes a shift away from current aircraft system alerting interfaces that report the status of physical components, and towards displaying the implications of degradations on mission capability. The proposed interface describes these component failures in terms of operational consequences of aircraft system degradations. The research activity was an effort to examine the utility of different representations of complex systems and operating environments to support real-time decision making of off-nominal situations. A specific focus was to develop representations that provide better integrated information to allow pilots to more easily reason about the operational consequences of the off-nominal situations. The work is also seen as a pathway to autonomy, as information is integrated and understood in a form that automated responses could be developed for the off-nominal situations in the future.
Advances in artificial intelligence (A.I.) over the last decade opens new opportunities for NASA to advance the state of the art in autonomous missions beyond low-Earth-orbit. Still, many challenges remain before these technologies can be deployed on manned spacecraft. This presentation summarizes many of these challenges, provides recommendations on how to address these problems, and provides an example of NASA’s Autonomous Power Controller's A.I.-based fault detection system.
This paper is concerned with the physics-based simulation of light tracked vehicles operating on rough deformable terrain. The focus is on small autonomous vehicles, which weigh less than 100 lb and move on deformable and rough terrain that is feature rich and no longer representable using a continuum approach. A scenario of interest is, for instance, the simulation of a reconnaissance mission for a high mobility lightweight robot where objects such as a boulder or a ditch that could otherwise be considered small for a truck or tank, become major obstacles that can impede the mobility of the light autonomous vehicle and negatively impact the success of its mission. Analyzing and gauging the mobility and performance of these light vehicles is accomplished through a modeling and simulation capability called Chrono::Engine. Chrono::Engine relies on parallel execution on Graphics Processing Unit (GPU) cards.