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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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Cryogenic or multipurpose seals made by using new materials. Seal possesses sufficient flexibility to contain high-pressure fluids regardless of dimensional changes from eigher pressure and/or temperature effects. Seal system operates in dual mode. Increased pressure supplements total sealing effort of seal system, which self-compensates for thermal contraction.
It is likely that future high resolution earth observation imaging systems will utilize self-scanned IR detectors. In an initial step toward this goal, an IR imaging system operating in the 10 to 12 micron spectral region has been developed. This system uses a 9-element HgCdTe/CCD linear array operating in the photoconductive mode, nine pre-amplifiers and a silicon CCD multiplexer integrated into a focal plane assembly. Opto-mechanical techniques are used to scan the scene and images are produced in real time. The imaging performance of this system is described and measurements of noise, responsivity, specific detectivity, and detector sensitivity profiles are presented. The requirements for more advanced detector arrays for use in future NASA remote sensing missions are also discussed.
Several recent helicopter vibration reduction research programs are described. Results of studies of blade design parameters in rotor vibratory response and of an advanced blade design for reduced vibration are examined. An optimization approach to develop a general automated procedure for rotor blade design is described, and analytical results for an articulated rotor operating at a steady 160 kt flight condition are reported. The use of a self-adaptive controller to implement higher harmonic control in closed-loop fashion is addressed, and a computer simulation used to evaluate and compare the performance of alternative algorithms included in the generic active controller is discussed. Results are presented for steady level flight conditions, short-duration maneuvers, blade stresses and rotor performance, blade-appended aeroelastic devices, vibratory airloads, wake-induced blade airloads, and airloads from blade motions, the interaction of rotor and fuselage, and the interaction of rotor and empennage.
Some proposed space exploration missions are examined. Consideration is given to requirements for human expeditions to Phobos and Mars and for establishing a lunar observatory and a permanent, self-sufficient facility on Mars. Earth-to-orbit transportation, propellant management, extraterrestrial construction and operations, life support technology, space transfer systems, and automation and robotics are examined in terms of proposed missions.
Proposed static random-access memory for computer features improved error-detecting and -correcting capabilities. New self-testing scheme provides for detection and correction of errors at any time during normal operation - even while data being written into memory. Faults in equipment causing errors in output data detected by repeatedly testing every memory cell to determine whether it can still store both "one" and "zero", without destroying data stored in memory.
Self-repriming heat pipe intrinsically inhibits formation of bubbles and quickly eliminates them if formed. Operation completely passive: no control mechanisms or additional source of energy needed. Suited to service in remote, unattended place.
A new test rig has been developed for evaluating foil air bearings at high temperatures and speeds. These bearings are self acting hydrodynamic air bearings which have been successfully applied to a variety of turbomachinery operating up to 650 C. This unique test rig is capable of measuring bearing torque during start-up, shut-down and high speed operation. Load capacity and general performance characteristics, such as durability, can be measured at temperatures to 700 C and speeds to 70,000 rpm. This paper describes the new test rig and demonstrates its capabilities through the preliminary characterization of several bearings. The bearing performance data from this facility can be used to develop advanced turbomachinery incorporating high temperature oil-free air bearing technology.
The Oil-Free Turbomachinery team at the NASA Glenn Research Center has unlocked one of the mysteries surrounding foil air bearing performance. Foil air bearings are self-acting hydrodynamic bearings that use ambient air, or any fluid, as their lubricant. In operation, the motion of the shaft's surface drags fluid into the bearing by viscous action, creating a pressurized lubricant film. This lubricating film separates the stationary foil bearing surface from the moving shaft and supports load. Foil bearings have been around for decades and are widely employed in the air cycle machines used for cabin pressurization and cooling aboard commercial jetliners. The Oil-Free Turbomachinery team is fostering the maturation of this technology for integration into advanced Oil-Free aircraft engines. Elimination of the engine oil system can significantly reduce weight and cost and could enable revolutionary new engine designs. Foil bearings, however, have complex elastic support structures (spring packs) that make the prediction of bearing performance, such as load capacity, difficult if not impossible. Researchers at Glenn recently found a link between foil bearing design and load capacity performance. The results have led to a simple rule-of-thumb that relates a bearing's size, speed, and design to its load capacity. Early simple designs (Generation I) had simple elastic (spring) support elements, and performance was limited. More advanced bearings (Generation III) with elastic supports, in which the stiffness is varied locally to optimize gas film pressures, exhibit load capacities that are more than double those of the best previous designs. This is shown graphically in the figure. These more advanced bearings have enabled industry to introduce commercial Oil-Free gas-turbine-based electrical generators and are allowing the aeropropulsion industry to incorporate the technology into aircraft engines. The rule-of-thumb enables engine and bearing designers to easily size and select bearing technology for a new application and determine the level of complexity required in the bearings. This new understanding enables industry to assess the feasibility of new engine designs and provides critical guidance toward the future development of Oil-Free turbomachinery propulsion systems.
We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.
The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship s flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm s design, along with mathematical models of the algorithm s performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required.
The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship's flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm's design, along with mathematical models of the algorithm's performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required.
Videogame Modulation Concept enhances the challenge of gameplay by requiring self-regulation of physiological responses to overcome the “unnecessary obstacles” of attenuation of effect of operator input (joystick, button & motion-control dampening) and disruption of aiming (cursor movement modulation).
Rotating detonation engines (RDEs) represent a novel propulsion technology where incoming reactants are consumed by a self-sustaining detonation wave that travels azimuthally around an annular combustion chamber. In theory, the operating mode of these devices approximates a constant-volume combustion Humphry cycle. This represents a 5-15% increase in thermal efficiency over current rockets and air breathing systems operating on constant-pressure combustion Brayton cycles. The use of liquid fuels in RDEs represent unique challenges in terms of performance and operability. However, the fundamental physics involved in spray breakup, evaporation, and combustion are not well understood inside these devices. This research seeks to provide direct insight into these processes by adding a single liquid fuel injector into an otherwise hydrogen-air RDE to evaluate the breakup and refill dynamics. Visualization is performed by 200-1000 kHz laser induced fluorescence of liquid phase diesel (355 nm) and or kerosene (266 nm).
With much higher levels of distributed energy resources - variable generation, energy storage, and controllable loads just to mention a few - being deployed into power systems, the data deluge from pervasive metering of energy grids, and the shaping of multi-level ancillary-service markets, current frameworks to monitoring, controlling, and optimizing large-scale energy systems are becoming increasingly inadequate. This position paper outlines the concept of 'Autonomous Energy Grids' (AEGs) - systems that are supported by a scalable, reconfigurable, and self-organizing information and control infrastructure, can be extremely secure and resilient (self-healing), and self-optimize themselves in real-time for economic and reliable performance while systematically integrating energy in all forms. AEGs rely on scalable, self-configuring cellular building blocks that ensure that each 'cell' can self-optimize when isolated from a larger grid as well as partaking in the optimal operation of a larger grid when interconnected. To realize this vision, this paper describes the concepts and key research directions in the broad domains of optimization theory, control theory, big-data analytics, and complex system modeling that will be necessary to realize the AEG vision.
NASA human spaceflight missions are inherently dynamic and require frequent scheduling changes in order to adapt to changing mission priorities and objectives. Tactical level changes to the mission plan are traditionally made by a team of expert planners and operations specialists on the ground. However, astronauts are expected to execute missions more autonomously during future long duration missions. Astronauts will need to take on some of the responsibility of managing their own schedule while still abiding by the numerous constraints required by human spaceflight operations. This paper summarizes salient elements of crew performance in NASA’s Human Exploration Research Analog Campaign 3. Analog crewmembers completed a series of self-scheduling exercises to evaluate Playbook’s usability towards enabling self-scheduling without support from ground control. Playbook is a self-scheduling software tool designed and developed by our team. We also investigated how to best communicate self-scheduling tasks and constraints to the crew in order to facilitate efficient self-scheduling during isolation in a realistic environment. Our analysis identified that 30 minutes was sufficient to complete complex self-scheduling tasks. Our evaluation also identified differences between individual and collaborative performance; analog crewmembers completed self-scheduling exercises more quickly as a team as opposed to individually and reported lower subjective difficulty ratings overall.
The JLAB LLRF 3.0 system has been developed and is replacing the 30-year-old LLRF systems in the CEBAF accelerator. The LLRF system builds upon 25 years of design and operational RF control experience (digital and analog), and our recent collaboration in the design of the LCLSII LLRF system. The new system also incorporates a cavity control algorithm using a fully functional phase and amplitude locked Self Exciting Loop (SELAP). The first system (controlling 8 cavities) was installed and commissioned in August of 2021. Since then the new LLRF system has been operating with cavity gradients up to 20 MV/m, and electron beam currents up to 350 uA. This paper discusses the operational experience of the LLRF 3.0 SELAP algorithm along with other software and firmware tools like cavity and klystron characterization and quench detection.
Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.
Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.