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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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
NASA NTRSDate not supplied

Air Traffic Management Response to Vertiport Closure

Increasing quantities of urban air mobility operations requires consideration of various contingencies associated with novel operational tempos and airspace management practices. This paper explores a contingency scenario in which a single vertiport closes unexpectedly during high tempo operations. Dynamic re-planning is explored as a function performed both by operators using common operating procedures and through emergency assistance from air traffic control. Implications for airspace capacity, infrastructure requirements, and vehicle energy reserves are discussed.

UAM↗
NASA NTRS1990

Automated control of hierarchical systems using value-driven methods

An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

Pugh, George E.↗
DOE OSTI2023

Rapidly Viable Sustained Grid

Rapid recovery of power flow, possibly after a blackout, is a crucial need arising in scenarios that are increasingly becoming more frequent; here, solutions for rapid viability of power while the grid is being restored are urgently needed to keep critical infrastructure (CI) online. Increasingly, after the initial recovery phase, sustenance of reliable power requires assistive services to the grid for long periods of time. Even though the need is urgent, there is only sparse effort present toward a comprehensive framework/strategy for making power rapidly viable with an emphasis on sustained grid ancillary services; which is the focus of this proposal. The proposed concept envisions four phases. In the first phase, when a large portion of power is disrupted (see Figure 1(a)), emphasis is on bringing CI online with the objective of maximizing the time horizon of power viability using resources available at the CI. In the second phase (Figure 1(b)), neighborhood resources are tightly coordinated that forms the CI’s central-core (CC) to provide guaranteed viability of CI over a longer horizon. In the third phase, self-organizing power networks are expanded in a distributed layer supporting the central-core (Figure 1(c)). In the fourth phase, separate CI-networks coalesce and are controlled in a coordinated fashion to provide grid ancillary services (AS), such as primary frequency control and enhancing grid resiliency. With time, system efficiencies and penetration of renewables increase, while the time-horizon of guaranteed sustenance of CI is maximized. Under proposed work, the concept will be instantiated with a focus on medical centers as CI. Comprehensive power hardware in the loop strategies and emulated field tests will guide and validate devised solutions. A strong T2M effort to commercialize resulting technology is outlined. The proposed technology will be transformative for the grid. It will fundamentally change the way large contingencies are managed where power systems and critical infrastructure transition from being fragile to being robust using intelligent, self-organizing control for coordinating resources, enhanced resiliency and use of sustainable energy sources.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Towards Learning-Based Architectures for Sensor Impact Evaluation in Building Controls

Advanced control algorithms for building systems are known to have significant potential in reducing energy consumption while optimizing thermal comfort. The success of such algorithms is critically contingent on several different types of sensor systems, which are in turn, used for continuous monitoring, identification and estimation of several important building states, such as temperatures, humidity, air quality, power consumption and occupancy status. Nonidealities in any of these sensors can lead to significant performance degradation of the control functionalities, and may lead to unwanted sub-optimal building operation. In this paper, we provide a simulation example with a high-fidelity building model, for a particular use-case of advanced optimization-based control in buildings, i.e., occupancy-based controls. We show how imperfections in occupancy sensing can offset performance. Subsequently, we discuss a novel learning-based architecture to efficiently evaluate the impact of sensor nonidealities for building systems, in context of advanced control algorithms.

Bhattacharya, Saptarshi↗
NASA NTRS1988

Contingency rescheduling of spacecraft operations

Spacecraft activity scheduling was a focus of attention in artificial intelligence recently. Several scheduling systems were devised which more-or-less successfully address various aspects of the activity scheduling problem, though most of these are not yet mature, with the notable expection of NASA's ESP. Few current scheduling systems, however, make any attempt to deal fully with the problem of modifying a schedule in near-real-time in the event of contingencies which may arise during schedule execution. These contingencies can include resources becoming unavailable unpredictably, a change in spacecraft conditions or environment, or the need to perform an activity not scheduled. In these cases it becomes necessary to repair an existing schedule, disrupting ongoing operations as little as possible. Normal scheduling is just a part of that which must be accomplished during contingency rescheduling. A prototype system named MAESTRO was developed for spacecraft activity scheduling. MAESTRO is briefly described with a focus on recent work in the area of real-time contingency handling. Included is a discussion of some of the complexities of the scheduling problem and how they affect contingency rescheduling, such as temporal constraints between activities, activities which may be interrupted and continued in any of several ways, and different ways to choose a resource complement which will allow continuation of an activity. Various heuristics used in MAESTRO for contingency rescheduling is discussed, as are operational concerns such as interaction of the scheduler with spacecraft subsystems controllers.

Britt, Daniel L.↗
NASA NTRS2005

Shuttle Orbiter Contingency Abort Aerodynamics: Real-Gas Effects and High Angles of Attack

An important element of the Space Shuttle Orbiter safety improvement plan is the improved understanding of its aerodynamic performance so as to minimize the "black zones" in the contingency abort trajectories [1]. These zones are regions in the launch trajectory where it is predicted that, due to vehicle limitations, the Orbiter will be unable to return to the launch site in a two or three engine-out scenario. Reduction of these zones requires accurate knowledge of the aerodynamic forces and moments to better assess the structural capability of the vehicle. An interesting aspect of the contingency abort trajectories is that the Orbiter would need to achieve angles of attack as high as 60deg. Such steep attitudes are much higher than those for a nominal flight trajectory. The Orbiter is currently flight certified only up to an angle of attack of 44deg at high Mach numbers and has never flown at angles of attack larger than this limit. Contingency abort trajectories are generated using the data in the Space Shuttle Operational Aerodynamic Data Book (OADB) [2]. The OADB, a detailed document of the aerodynamic environment of the current Orbiter, is primarily based on wind-tunnel measurements (over a wide Mach number and angle-of-attack range) extrapolated to flight conditions using available theories and correlations, and updated with flight data where available. For nominal flight conditions, i.e., angles of attack of less than 45deg, the fidelity of the OADB is excellent due to the availability of flight data. However, at the off-nominal conditions, such as would be encountered on contingency abort trajectories, the fidelity of the OADB is less certain. The primary aims of a recent collaborative effort (completed in the year 2001) between NASA and Boeing were to determine: 1) accurate distributions of pressure and shear loads on the Orbiter at select points in the contingency abort trajectory space; and 2) integrated aerodynamic forces and moments for the entire vehicle and the control surfaces (body flap, speed brake, and elevons). The latter served the useful purpose of verification of the aerodynamic characteristics that went into the generation of the abort trajectories.

Prabhu, Dinesh K.↗
NASA NTRS2010

Space Shuttle Probabilistic Risk Assessment (SPRA) Iteration 3.2

The Shuttle is a very reliable vehicle in comparison with other launch systems. Much of the risk posed by Shuttle operations is related to fundamental aspects of the spacecraft design and the environments in which it operates. It is unlikely that significant design improvements can be implemented to address these risks prior to the end of the Shuttle program. The model will continue to be used to identify possible emerging risk drivers and allow management to make risk-informed decisions on future missions. Potential uses of the SPRA in the future include: - Calculate risk impact of various mission contingencies (e.g. late inspection, crew rescue, etc.). - Assessing the risk impact of various trade studies (e.g. flow control valves). - Support risk analysis on mission specific events, such as in flight anomalies. - Serve as a guiding star and data source for future NASA programs.

Boyer, Roger L.↗
NASA NTRS2010

International Space Station Aeromedical Support in Star City, Russia

The Space Medicine Division at Johnson Space Center works with the International Space Station s international partners (IP) to accomplish assigned health care tasks. Each IP may assign a flight surgeon to support their assigned crewmembers during all phases of training, in-flight operations, and postflight activities. Because of the extensive amount of astronaut training conducted in Star City; NASA, in collaboration with its IPs, has elected to keep a flight surgeon assigned to NASA s Star City office to provide support to the U.S., Canadian, Japanese, and European astronauts during hazardous training activities and provide support for any contingency landings of Soyuz spacecraft in Kazakhstan. The physician also provides support as necessary to the Mission Control Center in Moscow for non-Russian crew-related activities. In addition, the physician in Star City provides ambulatory medical care to the non-Russian-assigned personnel in Star City and visiting dependents. Additional work involves all medical supplies, administration, and inventory. The Star City physician assists in medical evacuation and/or in obtaining support from western clinics in Moscow when required care exceeds local resources. Overall, the Russians are responsible for operations and the medical care of the entire crew when training in Star City and during launch/landing operations. However, they allow international partner flight surgeons to care for their crewmembers as agreed to in the ISS Medical Operations Requirements Document. Medical support focuses on pressurized, monitored, and other hazardous training activities. One of the most important jobs is to act as a medical advocate for the astronauts and to reduce the threat that these hazardous activities pose. Although the Russians have a robust medical system, evacuation may be needed to facilitate ongoing medical care. There are several international medical evacuation companies that provide this care.

Cole, Richard↗
NASA NTRS2013

Mars Sample Return Using Commercial Capabilities: ERV Trajectory and Capture Requirements

Mars Sample Return was presented as the highest priority planetary science mission of the next decade [1]. Lemke et al. [2] present a Mars Sample Return mission concept in which the sample is returned directly from the surface of Mars to an Earth orbit. The sample is recovered in Earth Orbit instead of being transferred between spacecraft in Mars Orbit. This paper provides the details of this sample recovery in Earth orbit and presents as such a sub-element of the overall Mars sample return concept given in [2]. We start from the assumption that a Mars Ascent Vehicle (MAV), initially landed on Mars using a modified SpaceX Dragon capsule, has successfully delivered the sample, already contained within an Earth Return Vehicle (ERV), to a parking orbit around Mars. From the parking orbit, the ERV imparts sufficient Delta-V to inject itself into an earthbound trajectory and to be captured into an Earth orbit eventually. We take into account launch window and Delta-V considerations as well as the additional constraint of increased safety margins imposed by planetary protection regulations. We focus on how to overcome two distinct challenges of the sample return that are driven by the issues of planetary protection: (1) the design of an ERV trajectory meeting all the requirements including the need to avoid contamination of Earth's atmosphere; (2) the concept of operations for retrieving the Martian samples in Earth orbit in a safe way. We present an approach to retrieve the samples through a rendezvous between the ERV and a second SpaceX Dragon capsule. The ERV executes a trajectory that brings it from low Mars orbit (LMO) to a Moon-trailing Earth orbit at high inclination with respect to the Earth-Moon plane. After a first burn at Trans-Earth Injection (TEI), the trajectory uses a second burn at perigee during an Earth flyby maneuver to capture the ERV in Earth orbit. The ERV then uses a non-propulsive Moon flyby to come to a near-circular Moon-trailing orbit. To perform the Earth Orbit Rendezvous (EOR), a second Dragon capsule is then launched from Earth and a similar lunar flyby is performed to rendezvous with the ERV. The requirements for rendezvous, close proximity operations and capture of the sample canister are described. A concept of operations for sample retrieval is presented along with design specifications of the ERV, the required modifications to the Dragon capsule, as well as the hardware, software, sensors, actuators, and capture mechanisms used. In our concept, a container is mounted to the front hatch of Dragon, capable of accommodating the sample canister and sealing it from the rest of the capsule. The sample canister is captured using a robotic arm with a magnetic grappling mechanism. Dragon then performs a propulsive maneuver to return to Earth for a controlled re-entry while the ERV (sans sample container) is left in the Moon trailing orbit. Contingency cases and related mitigation strategies are also discussed, including the advantages and disadvantages of performing the ERV rendezvous with a crew.

Faber, Nicolas F.↗
NASA NTRS2018

Determining Thermal Capabilities for External Transfer Operations on the International Space Station

External transfers on the International Space Station (ISS) have a degree of difficulty caused by the severity of the radiative thermal environment and the complexity of the operational choreography to perform the installation and activation of the hardware. These transfers can be performed robotically, by astronauts during an Extra Vehicular Activity (EVA - spacewalk), or combination of robotic/crew operations. Robotic transfers may include capability to intermittently power the hardware; while the hardware remains unpowered for EVA operations. Robotic transfers can be staged to occur in a favorable thermal environment, though typically take longer than a transfer by crew during an EVA where the hardware may not be robotically compatible. The hardware is under passive thermal control, use of optics/multi-layer insulation/heaters, while being transferred from/to a visiting vehicle, airlock, stowage platform, or external ISS structure and may include additional design components, such as removable protective blankets, to meet the transfer requirements. Thermal analysis must be performed to determine the capability of the hardware being transferred to provide the Mission Control team the products necessary to plan and execute the operation while establishing an awareness for any contingency response. An overview of the thermal aspects in planning these types of transfer operations, the analytical approaches and assumptions, and examples of results are provided in this paper.

Thermal↗
DOE OSTI2022

A Data-Driven Democratized Control Architecture for Regional Transmission Operators

As probably the most complicated and critical infrastructure system, U.S. power grids become increasingly vulnerable to extreme events such as cyber-attacks and severe weather, as well as higher DER penetrations and growing information mismatch among system operators, utilities (transmission or generation owners), and end-users. This paper proposes a data-driven democratized control architecture considering two democratization pathways to assist transmission system operators, with a targeted use case of developing online proactive islanding strategies. Detailed discussions on load capability profiling at transmission buses and disaggregation of DER generations are provided and illustrated with real-world utility data. By Combining network and operational constraints, transmission system operators can be equipped with new tools built on top of this architecture, to derive accurate, proactive, and strategic islanding decisions to incorporate the wide range of dynamic portfolios and needs when facing extreme events or unseen grid contingencies.

Power System Reliability, Islanding, Democratized ↗
NASA NTRS2005

Identifying Contingency Requirements using Obstacle Analysis on an Unpiloted Aerial Vehicle

This paper describes experience using Obstacle Analysis to identify contingency requirements on an unpiloted aerial vehicle. A contingency is an operational anomaly, and may or may not involve component failure. The challenges to this effort were: ( I ) rapid evolution of the system while operational, (2) incremental autonomy as capabilities were transferred from ground control to software control and (3) the eventual safety-criticality of such systems as they begin to fly over populated areas. The results reported here are preliminary but show that Obstacle Analysis helped (1) identify new contingencies that appeared as autonomy increased; (2) identify new alternatives for handling both previously known and new contingencies; and (3) investigate the continued validity of existing software requirements for contingency handling. Since many mobile, intelligent systems are built using a development process that poses the same challenges, the results appear to have applicability to other similar systems.

fault protection↗
NASA NTRS1979

Construction in space - Toward a fresh definition of the man/machine relation

The EVA (extravehicular activity) project forming part of the space construction process is reviewed. The manual EVA constuction, demonstrated by the crew of Skylab 3 by assembling a modest space structure in the form of the twin-pole sunshade, is considered, indicating that the experiment dispelled many doubts about man's ability to execute routine and contingency EVA operations. Tests demonstrating the feasibility of remote teleoperator rendezvous, station keeping, and docking operations, using hand controllers for direct input and television for feedback, are noted. Future plans for designing space construction machines are mentioned.

Watters, H. H.↗
NASA NTRS2009

Apollo 13 Guidance, Navigation, and Control Challenges

Combustion and rupture of a liquid oxygen tank during the Apollo 13 mission provides lessons and insights for future spacecraft designers and operations personnel who may never, during their careers, have participated in saving a vehicle and crew during a spacecraft emergency. Guidance, Navigation, and Control (GNC) challenges were the reestablishment of attitude control after the oxygen tank incident, re-establishment of a free return trajectory, resolution of a ground tracking conflict between the LM and the Saturn V S-IVB stage, Inertial Measurement Unit (IMU) alignments, maneuvering to burn attitudes, attitude control during burns, and performing manual GNC tasks with most vehicle systems powered down. Debris illuminated by the Sun and gaseous venting from the Service Module (SM) complicated crew attempts to identify stars and prevented execution of nominal IMU alignment procedures. Sightings on the Sun, Moon, and Earth were used instead. Near continuous communications with Mission Control enabled the crew to quickly perform time critical procedures. Overcoming these challenges required the modification of existing contingency procedures.

Goodman, John L.↗
DOE OSTI2023

Ultrafast enhancement of electron-phonon coupling via dynamic quantum well states

Abstract The density of states at the Fermi surface controls many material properties by influencing the low-energy interactions of conductive electrons. Typically, external tuning knobs generate only small perturbations to the density of states in crystals, since their band structure depends strongly on the lattice potential. In contrast, quantum well states are contingent on a localized potential extrinsic to the crystal lattice and can be easily modified leading to changes in the density of states at the Fermi level. Here, we are able to control the quantum well potential on the surface of Bi 2 Se 3 with light, driving a density of states singularity below E F at ultrafast timescales, thereby triggering a reversible Lifshitz transition. We reveal a substantial ultrafast enhancement of the electron-phonon coupling with repercussions on the relaxation dynamics in the system. We argue that the relaxation dynamics are governed largely by the interplay of the dynamic density of states of the quantum wells with c -axis scattering from the $${A}_{{{{{{{{\rm{1g}}}}}}}}}^{2}$$ A 1g 2 optical phonon mode. These results demonstrate a powerful way to enhance electron-boson interaction on ultrafast timescales providing new avenues for controlling material properties and driving novel quantum phases of matter.

Ciocys, Samuel T.↗