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DOE OSTI2020

Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation

Autonomous electric vehicles (AEVs) provide unique opportunities to cope with the uncertainties of distributed energy generation in distribution networks. But the effects are limited by both inherent radial topology and the behaviors of decentralized AEVs. As such, we investigate the potential benefits of dynamic distribution network reconfiguration (DDNR), taking into account AEVs' spatial-temporal availability and their charging demand. We propose a mixed integer programming model to optimally coordinate the charging/discharging of AEVs with DDNR, while satisfying AEVs' original travel plan. Numerical studies based on a test system overlaying the IEEE 33-node test feeder and Sioux Falls transportation network show that DDNR and AEV complement each other, which improves the operation of the distribution system. We also conduct sensitivity analyses on inputs including renewable fluctuation and AEVs penetration level.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2000

Using Model-Based Reasoning for Autonomous Instrument Operation

Multiprobe missions are an important part of NASA's future: Cluster, Magnetospheric Multi Scale, Global Electrodynamics and Magnetospheric Constellation are representatives from the Sun-Earth Connections Theme. To make such missions robust, reliable, and affordable, ideally the many spacecraft of a constellation must be at least as easy to operate as one spacecraft is today. To support this need for scalability, science instrumentation must become increasingly easy to operate, even as this same instrumentation becomes more capable and advanced. Communication and control resources will be at a premium for future instruments. Many missions will be out of contact with ground operators for extended periods either to reduce operations cost or because of orbits that limit communication to weekly perigee transits. Autonomous capability is necessary if such missions are to effectively achieve their operational objectives. An autonomous system is one that acts given its situation in a mission appropriate manner without external direction to achieve mission goals. To achieve this capability autonomy must be built into the system through judicious design or through a built-in intelligence that recognizes system state and manages system response. To recognize desired or undesired system states, the system must have an implicit or explicit understanding of its expected states given its history and self observations. The systems we are concerned with, science instruments, can have stringent requirements for system state knowledge in addition to requirements driven by health and safety concerns. Without accurate knowledge of the system state, the usefulness of the science instrument may be severely limited. At the same time, health and safety concerns often lead to overly conservative instrument operations further reducing the effectiveness of the instrument. These requirements, coupled with overall mission requirements including lack of communication opportunities and tolerance of environmental hazards, frame the problem of constructing autonomous science instruments. we are developing a model of the Low Energy Neutral Atom instrument (LENA) that is currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. LENA is a particle detector that uses high voltage electrostatic optics and time-of-flight mass spectrometry to image neutral atom emissions from the denser regions of the Earth's magnetosphere. As with most spacecraft borne science instruments, phenomena in addition to neutral atoms are detected by LENA. Solar radiation and energetic particles from Earth's radiation belts are of particular concern because they may help generate currents that may compromise LENA's long term performance. An explicit model of the instrument response has been constructed and is currently in use on board IMAGE to dynamically adapt LENA to the presence or absence of energetic background radiations. The components of LENA are common in space science instrumentation, and lessons learned by modelling this system may be applied to other instruments. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. Our future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.

Johnson, Mike↗

NASA NTRS1991

Autonomous proximity operations using machine vision for trajectory control and pose estimation

A machine vision algorithm was developed which permits guidance control to be maintained during autonomous proximity operations. At present this algorithm exists as a simulation, running upon an 80386 based personal computer, using a ModelMATE CAD package to render the target vehicle. However, the algorithm is sufficiently simple, so that following off-line training on a known target vehicle, it should run in real time with existing vision hardware. The basis of the algorithm is a sequence of single camera images of the target vehicle, upon which radial transforms were performed. Selected points of the resulting radial signatures are fed through a decision tree, to determine whether the signature matches that of the known reference signatures for a particular view of the target. Based upon recognized scenes, the position of the maneuvering vehicle with respect to the target vehicles can be calculated, and adjustments made in the former's trajectory. In addition, the pose and spin rates of the target satellite can be estimated using this method.

Cleghorn, Timothy F.↗

NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗

NASA NTRSDate not supplied

m:N Operations of Autonomous Fleets

The presentation discusses the background and project framing for the m:N body of work in TTT. It also review the m:N technical challenge for Operations of Autonomous Fleets.

Kelley Hashemi↗

NASA NTRS1999

Autonomous Command Operation of the WIRE Spacecraft

This paper presents the end-to-end design architecture for an autonomous commanding capability to be used on the Wide Field Infrared Explorer (WIRE) mission for the uplink of command loads during unattended station contacts. The WIRE mission is the fifth and final mission of NASA's Goddard Space Flight Center Small Explorer (SMEX) series to be launched in March of 1999. Its primary mission is the targeting of deep space fields using an ultra-cooled infrared telescope. Due to its mission design WIRE command loads are large (approximately 40 Kbytes per 24 hours) and must be performed daily. To reduce the cost of mission operations support that would be required in order to uplink command loads, the WIRE Flight Operations Team has implemented an autonomous command loading capability. This capability allows completely unattended operations over a typical two-day weekend period.

Prior, Mike↗

NASA NTRS2019

Vehicle to Vehicle (V2V) Communication for Collision Avoidance for Multi-Copters Flying in UTM -TCL4

NASA’s UAS Traffic management (UTM) research initiative is aimed at identifying requirements for safe autonomous operations of UAS operating in dense urban environments. For complete autonomous operations vehicle to vehicle (V2V) communications has been identified as an essential tool. In this paper we simulate a complete urban operations in an high fidelity simulation environment. We design a V2V communication protocol and all the vehicles participating communicate over this system. We show how V2V communication can be used for finding feasible, collision-free paths for multi agent systems. Different collision avoidance schemes are explored and an end to end simulation study shows the use of V2V communication for UTM TCL4 deployment.

Chakrabarty, Anjan↗

NASA NTRSDate not supplied

Enabling Progressively Autonomous Medical Operations for Space Exploration

As NASA and its International Partners prepare to expand human space exploration beyond the International Space Station (ISS) to the Moon (and ultimately Mars) with the Artemis missions, the importance of evolving space medical operations in an Earth independent fashion becomes increasingly clear. Continuous human presence on the ISS for the past 20 years has demonstrated the successful development and execution of medical operations in low Earth orbit. However, this paradigm of ISS medical operations is dependent upon continuous real-time communications, frequent resupply missions, and the availability of rapid evacuation options. As the distance and time away from Earth increases, all of these dependencies will no longer be available. As a result, the paradigm of space medicine operations will need to become progressively more autonomous and less dependent upon mission support personnel on Earth

Kris Lehnhardt↗

DOE OSTI2020

Sandia Nuclear Cartridge Concept

Nuclear power offers the promise of long-term electrical power for remote areas. Recent advances in passive safety and long-life cores make a reactor that can be operated autonomously for 20 years or more a real possibility. This white paper discusses a reactor concept that offers the potential for further development, resulting in a permanently hermetically-sealed "nuclear cartridge." The term "nuclear cartridge" is meant to imply a nuclear energy source that can be inserted into a site and operated autonomously until its energy has been depleted, then withdrawn and replaced by another cartridge. The concept can be scaled for various sizes, ranging from about 1 megawatt-electric (MWe) to about 100 MWe. The paper also discusses the concept of Integrated Safety, Operations, Security, and Safeguards (ISOSS) by design as it applies to this reactor design. Finally, a discussion of smart grids and how they can benefit the transfer of power to the end user is included. The Nuclear Cartridge concept has been developed with the following characteristics in mind: highly reliable autonomous operation coupled with international monitoring, requiring minimal on-site operations personnel; walkaway passively safe design; cartridge replacement cycle on the order of 20 years; load following capability; physical security by design requiring minimal security personnel during operations; and proliferation resistance by design. As illustrated in figure 1, integrating the reactor with advanced power conversion, smart grids, and other sources of energy results in a resilient and sustainable energy source.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2014

Autonomous Mission Operations Roadmap

As light time delays increase, the number of such situations in which crew autonomy is the best way to conduct the mission is expected to increase. However, there are significant open questions regarding which functions to allocate to ground and crew as the time delays increase. In situations where the ideal solution is to allocate responsibility to the crew and the vehicle, a second question arises: should the activity be the responsibility of the crew or an automated vehicle function? More specifically, we must answer the following questions: What aspects of mission operation responsibilities (Plan, Train, Fly) should be allocated to ground based or vehicle based planning, monitoring, and control in the presence of significant light-time delay between the vehicle and the Earth?How should the allocated ground based planning, monitoring, and control be distributed across the flight control team and ground system automation? How should the allocated vehicle based planning, monitoring, and control be distributed between the flight crew and onboard system automation?When during the mission should responsibility shift from flight control team to crew or from crew to vehicle, and what should the process of shifting responsibility be as the mission progresses? NASA is developing a roadmap of capabilities for Autonomous Mission Operations for human spaceflight. This presentation will describe the current state of development of this roadmap, with specific attention to in-space inspection tasks that crews might perform with minimum assistance from the ground.

Mission Operations↗

NASA NTRS2004

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Dufrene, Warren R., Jr.↗

NASA NTRS2004

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Dufrene, Warren R., Jr.↗

NASA NTRS2001

Using Model-Based Reasoning for Autonomous Instrument Operation - Lessons Learned From IMAGE/LENA

Model-based reasoning has been applied as an autonomous control strategy on the Low Energy Neutral Atom (LENA) instrument currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. Explicit models of instrument subsystem responses have been constructed and are used to dynamically adapt the instrument to the spacecraft's environment. These functions are cast as part of a Virtual Principal Investigator (VPI) that autonomously monitors and controls the instrument. In the VPI's current implementation, LENA's command uplink volume has been decreased significantly from its previous volume; typically, no uplinks are required for operations. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. The components of LENA are common in space science instrumentation, and lessons learned by modeling this system may be applied to other instruments. Future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.

Johnson, Michael A.↗

NASA NTRS2005

Airborne Management of Traffic Conflicts in Descent With Arrival Constraints

NASA is studying far-term air traffic management concepts that may increase operational efficiency through a redistribution of decisionmaking authority among airborne and ground-based elements of the air transportation system. One component of this research, En Route Free Maneuvering, allows trained pilots of equipped autonomous aircraft to assume responsibility for traffic separation. Ground-based air traffic controllers would continue to separate traffic unequipped for autonomous operations and would issue flow management constraints to all aircraft. To evaluate En Route Free Maneuvering operations, a human-in-the-loop experiment was jointly conducted by the NASA Ames and Langley Research Centers. In this experiment, test subject pilots used desktop flight simulators to resolve conflicts in cruise and descent, and to adhere to air traffic flow constraints issued by test subject controllers. Simulators at NASA Langley were equipped with a prototype Autonomous Operations Planner (AOP) flight deck toolset to assist pilots with conflict management and constraint compliance tasks. Results from the experiment are presented, focusing specifically on operations during the initial descent into the terminal area. Airborne conflict resolution performance in descent, conformance to traffic flow management constraints, and the effects of conflicting traffic on constraint conformance are all presented. Subjective data from subject pilots are also presented, showing perceived levels of workload, safety, and acceptability of autonomous arrival operations. Finally, potential AOP functionality enhancements are discussed along with suggestions to improve arrival procedures.

Doble, Nathan A.↗

DOE OSTI2016

Development of solid materials for UF 6 sampling: FY16 Annual Report

A handheld implementation of the ABACC-developed Cristallini method, which captures uranium hexafluoride samples as an inert salt, was organized in FY17 and succeeded in demonstrating the handheld sampler concept with reactive hexafluoride gases. The Cristallini method relies on the use of a hydrated substrate to react the incoming hexafluoride resulting in the formation of a stable uranyl fluoride salt. The Cristallini method has been demonstrated as a facility modification installed near the sampling tap of a gas centrifuge enrichment plant. While very successful in reducing the hazards of uranium hexafluoride sample, the method still takes a considerable amount of time and can only be used in facilities where the apparatus has been installed; this arrangement generally prohibits the sampling of filled cylinders that have already exited the facility and have been deposited in the on-site tank storage yard. The handheld unit under development will allow the use of the Cristallini method at facilities that have not been converted as well as tanks in the storage yard. The handheld system utilizes an active vacuum system, rather than a passive vacuum system in the facility setup, to drive the uranium hexafluoride onto the adsorbing media. The handheld unit will be battery operated for fully autonomous operation and will include onboard pressure sensing and flushing capability. To date, the system concept of operations was demonstrated with tungsten hexafluoride that showed the active vacuum pump with multiple cartridges of adsorbing media was viable. Concurrently, the hardened prototype system was developed and tested; removable sample cartridges were developed (the only non-COTS component to date); and preparations were made for uranium tests and a domestic field test.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Regulatory Considerations for Nuclear Energy Applications of Digital Twin Technologies

Digital twins (DTs) in complex industrial and engineering applications have potential benefits that include increased operational efficiencies, enhanced safety and reliability, improved security engineering, reduced errors, faster information sharing, and better predictions. The interest in DT technologies continues to grow, and many of these advanced technologies are expected to experience rapid and wide industry adoption in the near future. Some of the potential application areas for DTs in the nuclear industry are design, licensing, plant construction, training simulators, predictive operations and maintenance, autonomous operation and control, failure and degradation prediction, physical protection modeling and simulation, and safety and reliability analyses. The Office of Nuclear Regulatory Research at the U.S. Nuclear Regulatory Commission (NRC) has initiated a future-focused research project to assess the regulatory viability of DTs for nuclear power plants and other NRC-regulated activities, such as fuel cycle facilities and operations. This report explores the potential impact of DT technologies in nuclear applications on NRC-regulated activities of interest. This report describes a nuclear DT system and its capabilities for nuclear power plant applications, followed by identification and discussion of some regulated activities that merit special consideration and present opportunities in implementing DT-enabling technologies and capabilities.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1995

Intermediate Levels of Autonomy within the SSM/PMAD Breadboard

The Space Station Module Power Management and Distribution (SSM/PMAD) bread-board is a test bed for the development of advanced power system control and automation. Software control in the SSM/PMAD breadboard is through co-operating systems, called Autonomous Agents. Agents can be a mixture of algorithmic software and expert systems. The early SSM/PMAD system was envisioned as being completely autonomous. It soon became apparent, though, that there would always be a need for human intervention, at least as long as a human interacts with the system in any way. In a system designed only for autonomous operation, manual intervention meant taking full control of the whole system, and loosing whatever expertise was in the system. Several methods for allowing humans to interact at an appropriate level of control were developed. This paper examines some of these intermediate modes of autonomy. The least humanly intrusive mode is simple monitoring. The ability to modify future behavior by altering a schedule involves high-level interaction. Modification of operating activities comes next. The coarsest mode of control is individual, unplanned operation of individual Power System components. Each of these levels is integrated into the SSM/PMAD breadboard, with support for the user (such as warnings of the consequences of control decisions) at every level.

Dugal-Whitehead, Norma R.↗