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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assurance by Design for Cyber Physical Data-Driven Systems

Currently, Cyber Physical Data-Driven Systems (CPDDS) employ machine learning for the classification, data fusion, and control of our nation’s infrastructure, such as the power grid, transportation networks (e.g., fuel distribution, air traffic control), and DoD long-duration collaborative autonomous platforms including unmanned underwater, ground, surface, space, and aerial systems. Many CPDDSs are system-of-systems that should be designed to communicate over disadvantaged networks. It is important to assure that the CPDDSs are resilient against physical and cyber threats by design. Additionally, their design should tolerate misclassification errors resulting from natural and/or adversarial distribution shifts within their data driven components. The all-domain nature of the problem of assuring the design of CPDDSs requires a multi-disciplinary perspective as outlined in this chapter.

Chikkagoudar, Satish↗
DOE OSTI2018

Telerobotic Control of Dexterous Dual-Arm Robots for D and D Operations - 18622

Robotic systems hold the potential to significantly reduce exposure of workers to hazardous environments such as in the deactivation and decommissioning (D and D) of nuclear facilities. Our goal is to enable an operator with minimal training to easily control a remote dual-arm robot to perform demolition tasks with hand tools. We propose a system that combines semi-autonomous coordination of the robot's arms with an intuitive operator interface based on virtual reality (VR) technology. A limb coordination system enables independent control of the robot arms, as well as coupled motion required to hold and manipulate rigid bodies such as reciprocating saws, angle grinders and crow bars. Using a VR head mounted display and stereo video from the robot for situational awareness and tracked VR hand controllers to command robot arm movement, an operator will be able to walk up to the control console, pick up the controllers, engage the manipulators, fly the grippers, grasp a tool with one or both robot arms and easily move them in unison to perform tasks. We present preliminary results using simulation and a physical dual-arm platform based on the Johns Hopkins University Applied Physics Laboratory's Modular Prosthetic Limb, an anthropomorphic device that provides hyper-dexterous human-like manipulation capabilities. Anticipated benefits of the robotic system for D and D operations include improved situational awareness, increased mission complexity, and reduced operator training time, workload, and task execution times. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Self-Security for Grid-Interactive Smart Inverters Using Steady-State Reference Model

Smart inverters exchange information with other devices through a shared communication link, making the inverters more prone to receive harmful commands from external parties. This erroneous data can be received due to an anomaly in the system, such as a device fault, unintentional utility operator action, or a cyber-attack. In this paper, a device-level self-security strategy is implemented using reference models for a grid-interactive inverter to examine the incoming power setpoints, detect the anomalies, and protect the system accordingly. The PQ setpoints received from the utility supervisory controller are autonomously examined using the inverter’s normal and stable operating regions before engaging the setpoints to the inverter’s local controller. Grid parameters are estimated in real-time during the examination process. The efficacy of the self-security algorithm is tested using a three-phase 3-kVA SiC-MOSFET inverter and a 12-kW NHR 9410 regenerative grid emulator. The results verify that the proposed method can detect harmful PQ setpoints that can cause abnormal or unstable inverter operation.

Gursoy, Mehmetcan↗
DOE OSTI2022

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗
DOE OSTI2025

Human Factors Considerations for Anticipated Uses of Autonomy in Advanced Reactor Technologies

The objective of this report is examine anticipated advanced reactor designs that incorporate high levels of autonomy in operation of advanced reactor systems or facilities, and to begin identifying the human factors engineering (HFE) considerations relevant to those designs. The insights gained will help identify areas where U.S. Nuclear Regulatory Commission (NRC) may need to develop or update review guidance to adequately address HFE considerations essential for safe operation. The adequacy of existing guidance, along with recommendations for updates or new guidance, may be addressed in future reports. We use the term “landscape analysis” to describe the review, analysis, and characterization of publicly available information on the anticipated future state of the industry regarding particular technologies or operational concepts. This landscape analysis considers the potential range of advanced reactor automation concepts that may be used for monitoring and controlling nuclear systems and facilities, including the potential for highly automated, near autonomous, or fully autonomous operation of advanced nuclear reactors.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping

Application of artificial intelligence (AI), and more specifically machine learning, to the physical sciences has expanded significantly over the past decades. In particular, science-informed AI, also known as scientific AI or inductive bias AI, has grown from a focus on data analysis to now controlling experiment design, simulation, execution and analysis in closed-loop autonomous systems. The CAMEO (closed-loop autonomous materials exploration and optimization) algorithm employs scientific AI to address two tasks: learning a material system’s composition-structure relationship and identifying materials compositions with optimal functional properties. By integrating these, accelerated materials screening across compositional phase diagrams was demonstrated, resulting in the discovery of a best-in-class phase change memory material. Key to this success is the ability to guide subsequent measurements to maximize knowledge of the composition-structure relationship, or phase map. In this work we investigate the benefits of incorporating varying levels of prior physical knowledge into CAMEO’s autonomous phase-mapping. This includes the use of ab-initio phase boundary data from the AFLOW repositories, which has been shown to optimize CAMEO’s search when used as a prior.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Fuzzy logic techniques for rendezvous and docking of two geostationary satellites

Large assemblings in space require the ability to manage rendezvous and docking operations. In future these techniques will be required for the gradual build up of big telecommunication platforms in the geostationary orbit. The paper discusses the use of fuzzy logic to model and implement a control system for the docking/berthing of two satellites in geostationary orbit. The system mounted in a chaser vehicle determines the actual state of both satellites and generates torques to execute maneuvers to establish the structural latching. The paper describes the proximity operations to collocate the two satellites in the same orbital window, the fuzzy guidance and navigation of the chaser approaching the target and the final Fuzzy berthing. The fuzzy logic system represents a knowledge based controller that realizes the close loop operations autonomously replacing the conventional control algorithms. The goal is to produce smooth control actions in the proximity of the target and during the docking to avoid disturbance torques in the final assembly orbit. The knowledge of the fuzzy controller consists of a data base of rules and the definitions of the fuzzy sets. The knowledge of an experienced spacecraft controller is captured into a set of rules forming the Rules Data Base.

Ortega, Guillermo↗
NASA NTRS2005

Neurovestibular and Sensorimotor Studies in Space and Earth Benefits

This review summarizes what has been learned from studies of human neurovestibular system in weightless conditions, including balance and locomotion, gaze control, vestibular-autonomic function and spatial orientation, and gives some examples of the potential Earth benefits of this research. Results show that when astronauts and cosmonauts return from space flight, both the peripheral and central neural processes are physiologically and functionally altered. There are clear distinctions between the virtually immediate adaptive compensations to weightlessness and those that require longer periods of time to adapt. However, little is known to date about the adaptation of sensory-motor functions to long-duration space missions in weightlessness and to the transitions between various reduced gravitational levels, such as on the Moon and Mars. Results from neurovestibular research in space have substantially enhanced our understanding of the mechanisms and characteristics of postural, gaze, and spatial orientation deficits, analogous to clinical cases of labyrinthine-defective function. Also, space neurosciences research has participated in the development and application of significant new technologies, such as video recording and processing of three-dimensional eye movements and posture, hardware for the unencumbered measurement of head and body movement, and procedures for investigating otolith function on Earth. In particular, devices such as centrifugation or off-vertical axis rotation could enhance clinical neurological testing because it provides linear acceleration which specifically stimulates the otolith organs in a frequency range close to natural head and body movement.

Clement, Gilles↗
DOE OSTI2022

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗
NASA NTRS2004

Future of Fuel Savings

Using automation to free up controllers for more strategic management of air traffic is one approach being studied by NASA as it seeks to boost airspace system capacity and efficiency, thereby saving fuel. Heinz Erzberger, a NASA Ames Research Center senior scientist, says the Advanced Airspace Concept (AAC) has been studied for several years. It could increase efficiency 15% by providing optimal routes that cut airlines direct operating costs. A 25% increase in landings on existing runways could follow an important benefit. AAC is one of the efforts to be reviewed by the Joint Planning and Development Organization, an FAA-led initiative by six federal agencies to redesign the U.S. air transportation system by 2025. The main goal is to triple air traffic capacity within 20 years to avert the sort of gridlock that would make fuel consumption only one of many travel nightmares. The automated system approach would allow aircraft to fly optimal trajectories. A trajectory would be defined in the standard three dimensions and eventually include the fourth, time. The management of air traffic by the data-linked exchange of trajectories would start at high altitude and eventually move down to lower altitudes. The automated concept is an outgrowth of the type of tools developed by NASA for use by FAA controllers in managing traffic flows over the years, including ones that optimize routings for the best fuel burn. But AAC would push automation further to reduce workload so controllers can focus on "solving strategic control problems, managing traffic flow during changing weather and ... other unusal events." One key component, the automated trajectory server (ATS), is a ground systems that would rely on software to manage flight path requests from aircrews and controllers. But, Erzberger acknowledges, "The FAA's current plan for upgrades to air traffic services does not include [allowing] the future ground system to issue separation-critical clearances of trajectory changes autonomously to aircraft via data link without explicit approval of a controller," as the AAC proposes. The AAC enables pilots or controllers to data link requests for a trajectory change to the ATS for approval after they are deconflicted with the paths of other aircraft. To divert around storms, for example, pilots could data link their trajectory preference to the ATS. Since several aircraft might request similar routes, the computer would then have to suggest alternatives. This could be accomplished without pilot-controller radio calls, a big bottleneck now. The ATS would have a built-in conflict monitor to call for a resolution (turn, climb or descend), when loss of separation is likely in 1-20 min. The AAC system would reduce controller errors by 90%, according to NASA Ames estimates. The AAC would have a back-up program to assure separation-Tactical Separation Assurance (TSAFE). It s designed to detect short-term traffic conflicts within 3-4 min. of loss of separation. The last line of defense would still be provided by traffic alert & collision avoidance systems (TCAS).

Hughes, David↗
DOE OSTI2023

Mean-field limit of a hybrid system for multi-lane multi-class traffic

This article aims to study coupled mean-field equation and ODEs with discrete events motivated by vehicular traffic flow. Precisely, multi-lane traffic flow in presence of human-driven and autonomous vehicles is considered, with autonomous vehicles possibly influenced by external policymakers. First, a finite-dimensional hybrid system is developed based on the continuous Bando-Follow-the-Leader dynamics coupled with discrete events due to lane-change maneuvers. Then the mean-field limit of the finite-dimensional hybrid system is rigorously derived for the dynamics of the human-driven vehicles. The microscopic lane-change maneuvers of the human-driven vehicles generate a source term for the mean-field PDE. This leads to an infinite-dimensional hybrid system described by coupled Vlasov-type PDE, ODEs, and discrete events.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

New potentials of NIICHIMMASH's thermal vacuum facilities

The potentialities of existing test facilities as to simulating space environment governing factors for spacecraft successful development thermal vacuum testing are analyzed, ways of modernizing existing test facilities and specific proposals on their redesign are considered. The problem of spacecraft (S/C) ground development in simulated external environments, the solution of which started more than 30 years ago, has not lost its urgency today. Stringent requirements on S/C active lifetime under space conditions, module large dimensions, great number of extension elements and complicated mode of their interaction in long mission do not allow S/C designers to abandon ground tests. S/C thermal modes development is a combination of calculations, thermal vacuum tests and actions on improving S/C design and its thermal control system. Traditionally, tests are carried out by stages from component and end unit level verifications to complex tests of modules and S/C as a whole. In our opinion, sufficient correctness of calculated models and experience gained in organizations designing space systems allow to reduce cost and time of autonomous tests. Unfortunately, this is not true for complex (integrated) thermal vacuum tests. More than that, their recent programs include tasks of verifying other (than thermal control system) systems if S/C for operation under space simulated conditions. The outlined circumstances are the main reason for critical review of the potentialities of the existing test base, and of NIICHIMMASH's two large thermal vacuum chambers, first of all. The reasons for and ways of enlargement of these facilities potentially are analyzed and the results attained are described.

Afanassiev, N. A.↗
NASA NTRS2004

Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control modes that are selected according to some performance or operational criteria. As the engine degrades, parameters shift from their nominal values. Thus, when a new control mode is swapped in, a variable that is being brought under control might have an excessive initial error. The new adaptive algorithm adjusts the controller gains on the basis of the level of degradation to minimize the disruptive influence of the large error on other variables and to recover the desired thrust response.

Litt, Jonathan S.↗
NASA NTRS1991

Experiences With The JPL Telerobot Testbed

Report identifies problems and technological gaps existing in robotic systems integration. Focuses upon problems experienced during development of Telerobot Testbed System at NASA's Jet Propulsion Laboratory (JPL): integrated robotic testbed used to develop, implement, and evaluate performance of advanced concepts in autonomous, teleautonomous, and teleoperated control of robotic manipulators. Report provides information used to guide and expedite development of future integrated robotic systems.

Stone, Henry W.↗
NASA NTRS1987

SOLON: An autonomous vehicle mission planner

The State-Operator Logic Machine (SOLON) Planner provides an architecture for effective real-time planning and replanning for an autonomous vehicle. The highlights of the system, which distinguish it from other AI-based planners that have been designed previously, are its hybrid application of state-driven control architecture and the use of both schematic representations and logic programming for the management of its knowledge base. SOLON is designed to provide multiple levels of planning for a single autonomous vehicle which is supplied with a skeletal, partially-specified mission plan at the outset of the vehicle's operations. This mission plan consists of a set of objectives, each of which will be decomposable by the planner into tasks. These tasks are themselves comparatively complex sets of actions which are executable by a conventional real-time control system which does not perform planning but which is capable of making adjustments or modifications to the provided tasks according to constraints and tolerances provided by the Planner. The current implementation of the SOLON is in the form of a real-time simulation of the Planner module of an Intelligent Vehicle Controller (IVC) on-board an autonomous underwater vehicle (AUV). The simulation is embedded within a larger simulator environment known as ICDS (Intelligent Controller Development System) operating on a Symbolics 3645/75 computer.

Dudziak, M. J.↗
NASA NTRS2013

Advancing Autonomous Operations Technologies for NASA Missions

This paper discusses the importance of implementing advanced autonomous technologies supporting operations of future NASA missions. The ability for crewed, uncrewed and even ground support systems to be capable of mission support without external interaction or control has become essential as space exploration moves further out into the solar system. The push to develop and utilize autonomous technologies for NASA mission operations stems in part from the need to reduce cost while improving and increasing capability and safety. This paper will provide examples of autonomous technologies currently in use at NASA and will identify opportunities to advance existing autonomous technologies that will enhance mission success by reducing cost, ameliorating inefficiencies, and mitigating catastrophic anomalies

Cruzen, Craig↗
NASA NTRS2013

Advancing Autonomous Operations Technologies for NASA Missions

This paper discusses the importance of implementing advanced autonomous technologies supporting operations of future NASA missions. The ability for crewed, uncrewed and even ground support systems to be capable of mission support without external interaction or control has become essential as space exploration moves further out into the solar system. The push to develop and utilize autonomous technologies for NASA mission operations stems in part from the need to reduce operations cost while improving and increasing capability and safety. This paper will provide examples of autonomous technologies currently in use at NASA and will identify opportunities to advance existing autonomous technologies that will enhance mission success by reducing operations cost, ameliorating inefficiencies, and mitigating catastrophic anomalies.

Cruzen, Craig↗