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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

G2 Autonomous Control for Cryogenic Delivery Systems

The Independent System Health Management-Autonomous Control (ISHM-AC) application development for cryogenic delivery systems is intended to create an expert system that will require minimal operator involvement and ultimately allow for complete autonomy when fueling a space vehicle in the time prior to launch. The G2-Autonomous Control project is the development of a model, simulation, and ultimately a working application that will control and monitor the cryogenic fluid delivery to a rocket for testing purposes. To develop this application, the project is using the programming language/environment Gensym G2. The environment is an all-inclusive application that allows development, testing, modeling, and finally operation of the unique application through graphical and programmatic methods. We have learned G2 through training classes and subsequent application development, and are now in the process of building the application that will soon be used to test on cryogenic loading equipment here at the Kennedy Space Center Cryogenics Test Laboratory (CTL). The G2 ISHM-AC application will bring with it a safer and more efficient propellant loading system for the future launches at Kennedy Space Center and eventually mobile launches from all over the world.

cryogenic fluids↗
DOE OSTI2024

Space Nuclear Power Autonomous Control Algorithm and Control Element Test Bed

Nuclear thermal rockets are currently NASA’s preferred option for use in a manned mission to Mars in the 2040s. The communication delay between an Earth ground station and a spacecraft heading toward Mars can be up to 20 min. Therefore, controlling the nuclear rocket engine would require either a full-time reactor operator on the mission or an autonomous control system for the reactor. The latter idea of making space nuclear reactors fully autonomous has drawn more interest from stakeholders, but such an autonomous control system must be rigorously tested and validated before it is certified for human use. The cost of a full ground test for a space nuclear reactor is tremendous, so a nonnuclear mock reactor test bed was created to test and validate control elements and control algorithms for space nuclear reactors. The test bed consists of control element hardware that inputs physical measurement data into a reactor emulator to produce the reactor’s performance under steady-state, transient, and fault conditions. The control element hardware consists of six full-sized control drums equipped with servo drives and motors and is instrumented with optical encoders, resolvers, and torque sensors for drum movement characterization. In addition to the drums, a two-phase flow loop was designed and built to mimic the valves and turbomachinery associated with the propellant flow through a nuclear thermal rocket engine; components such as pressure sensors, flow meters, thermocouples, and tachometers are instrumented throughout the loop to characterize the fluid flow, valve, and turbomachinery behavior of the system. The data from the physical hardware (e.g., drum position, propellant flow rates) are input to a nuclear reactor simulator to determine the actual nuclear reactor parameters, and the data are sent back to a control algorithm to complete the control loop. The ability to conduct numerous tests of the control systems and autonomous algorithms can help validate the instrumentation and control aspects for a space nuclear reactor for every possible fault situation.

Wilson, Brandon↗
DOE OSTI2025

Intelligent Surrogate Model Development: Boosting Computational Efficiency for Autonomous Control of Advanced Reactors

Advanced reactors promise enhanced safety, greater efficiency, and waste reductions. To fully realize these benefits, it is crucial to address the need for autonomous or semi-autonomous control systems that require fewer operators. This research primarily supports the MARVEL autonomous control system, which requires real-time operation. However, the current RELAP5 reactor thermal hydraulic transient simulation is excessively time-consuming. Therefore, this study aims to leverage deep learning techniques to develop a surrogate model, providing a more efficient and accurate alternative for real-time performance. The model was trained using a combination of one-timestep prediction and scheduled sampling. It was then used for recursive prediction of the reactor state. This developed surrogate model significantly improves computational efficiency, achieving a 12 times acceleration.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2022

On-the-fly autonomous control of neutron diffraction via physics-informed Bayesian active learning

We demonstrate the first live, autonomous control over neutron diffraction experiments by developing and deploying ANDiE: the autonomous neutron diffraction explorer. Neutron scattering is a unique and versatile characterization technique for probing the magnetic structure and behavior of materials. However, instruments at neutron scattering facilities in the world is limited, and instruments at such facilities are perennially oversubscribed. We demonstrate a significant reduction in experimental time required for neutron diffraction experiments by implementation of autonomous navigation of measurement parameter space through machine learning. Prior scientific knowledge and Bayesian active learning are used to dynamically steer the sequence of measurements. We show that ANDiE can experimentally determine the magnetic ordering transition of both MnO and Fe 1.09 Te all while providing a fivefold enhancement in measurement efficiency. Furthermore, in a hypothesis testing post-processing step, ANDiE can determine transition behavior from a set of possible physical models. ANDiE's active learning approach is broadly applicable to a variety of neutron-based experiments and can open the door for neutron scattering as a tool of accelerated materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cyber threat assessment of machine learning driven autonomous control systems of nuclear power plants

We report advanced cyber-attacks against critical infrastructure and the energy sector are becoming more common. With the invention of autonomous control systems (ACS) within advanced nuclear reactor designs, system designers, reactor operators, and regulators must consider cybersecurity during the design and operational phases. This article provides a cyber threat assessment of machine learning (ML)-based digital twinning (DT) technologies in the context of advanced reactor ACS. A cyber–physical testbed was created to emulate nuclear reactor digital instrumentation and controls (I&C) and act as a basis for the ACS. The ACS was designed as two plant-level DTs predicting reactor malfunctions and determining control actions and two component-level DTs responsible for classifying component states and forecasting component inputs and outputs (I/O). Two duplicate ACS designs– one using a traditional ML framework and one using an automated ML (AutoML) framework– were created and tested against cyber-attacks on training data, real-time process data, and ML model architectures to determine their respective qualitative cyber-risk in terms of likelihood and impact. Both frameworks showed similar cyber-resilience against training, real-time, and ML architecture attacks, proving that neither is inherently more secure. Recommended safeguard and security measures are posed to system designers, reactor operators, and regulators to maintain the cybersecurity of ML-based DT technologies such as ACS, prompting a holistic view of shared responsibility for maintaining cyber-secure ML-based systems.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1993

Supervised autonomous control, shared control, and teleoperation for space servicing

A local-remote telerobot system for single- and dual-arm supervised autonomy, shared control, and teleoperation has been demonstrated. The system is composed of two distinct parts: the local site, where the operator resides; and the remote site, where the robots reside. The system could be further separated into dual local sites communicating with a common remote site. This is valuable for potential space missions where a space based robotic system may be controlled either by a space based operator or by a ground based operator. Also, multiple modes of control integrated into a common system are valuable for satisfying different servicing scenarios. The remote site single arm control system is described, and its parameterization for different supervised autonomous control, shared control, and teleoperation tasks are given. Experimental results are also given for selected tasks. The tasks include compliant grasping, orbital replacement unit changeout, bolt seating and turning, electronics card removal and insertion, and door opening.

Backes, Paul G.↗
NASA NTRS2003

An Autonomous Control System for an Intra-Vehicular Spacecraft Mobile Monitor Prototype

This paper presents an overview of an ongoing research and development effort at the NASA Ames Research Center to create an autonomous control system for an internal spacecraft autonomous mobile monitor. It primary functions are to provide crew support and perform intra- vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the mission roles and high-level functional requirements for an autonomous mobile monitor. The mobile monitor prototypes, of which two are operational and one is actively being designed, physical test facilities used to perform ground testing, including a 3D micro-gravity test facility, and simulators are briefly described. We provide an overview of the autonomy framework and describe each of its components, including those used for automated planning, goal-oriented task execution, diagnosis, and fault recovery. A sample mission test scenario is also described.

Dorais, Gregory A.↗
NASA NTRS1989

Multi-level manual and autonomous control superposition for intelligent telerobot

Space telerobots are recognized to require cooperation with human operators in various ways. Multi-level manual and autonomous control superposition in telerobot task execution is described. The object model, the structured master-slave manipulation system, and the motion understanding system are proposed to realize the concept. The object model offers interfaces for task level and object level human intervention. The structured master-slave manipulation system offers interfaces for motion level human intervention. The motion understanding system maintains the consistency of the knowledge through all the levels which supports the robot autonomy while accepting the human intervention. The superposing execution of the teleoperational task at multi-levels realizes intuitive and robust task execution for wide variety of objects and in changeful environment. The performance of several examples of operating chemical apparatuses is shown.

Hirai, Shigeoki↗
DOE OSTI2025

Enhancing Autonomous Control of Microreactors Using Multi-Agent Reinforcement Learning

In order for microreactors to be economically competitive, operation costs will need to be minimized through some degree of autonomous control. Previous work has demonstrated the effectiveness of reinforcement learning (RL) for load-following control in a drum-controlled microreactor. This study extends that work by exploring the potential of RL to independently control each of the reactor’s drums. We compare a single-agent RL approach with a multi-agent RL (MARL) framework, testing them for generalization across different load-following power profiles and control timescales, and for robustness in cases of randomly disabled control drums. Since the point kinetics simulation environment used in this study cannot resolve spatial effects, we assume that in the absence of spatially localized disturbances, optimal drum movements should be symmetrical. We demonstrate that single-agent RL is able to achieve accurate performance only when symmetric actions are ignored; otherwise, it fails to train a useful controller. Meanwhile, the MARL framework performs symmetric actions by design and trains a robust, accurate agent, as evidenced by mean absolute errors in power matching of 0.41% for the training power profile, 0.68% for a profile with half the drums disabled, and 0.21% for a profile on a realistic load-following time horizon.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1990

Autonomous control

KSC has been developing the Knowledge-Based Autonomous Test Engineer (KATE), which is a tool for performing automated monitoring, diagnosis, and control of electromechanical devices. KATE employs artificial intelligence computing techniques to perform these functions. The KATE system consists of a generic shell and a knowledge base. The KATE shell is the portion of the system which performs the monitoring, diagnosis, and control functions. It is generic in the sense that it is application independent. This means that the monitoring activity, for instance, will be performed with the same algorithms regardless of the particular physical device being used. The knowledge base is the portion of the system which contains specific functional and behavorial information about the physical device KATE is working with. Work is nearing completion on a project at KSC to interface a Texas Instruments Explorer running a LISP version of KATE with a Generic Checkout System (GCS) test-bed to control a physical simulation of a shuttle tanking system (humorously called the Red Wagon because of its color and mobility). The Autonomous Control System (ACS) project supplements and extends the KATE/GCS project by adding three other major activities. The activities include: porting KATE from the Texas Instruments Explorer machine to an Intel 80386-based UNIX workstation in the LISP language; rewriting KATE as necessary to run on the same 80386 workstation but in the Ada language; and investigating software and techniques to translate ANSI Standard Common LISP to Mil Standard Ada. Primary goals of this task are as follows: (1) establish the advantages of using expert systems to provide intelligent autonomous software for Space Station Freedom applications; (2) determine the feasibility of using Ada as the run-time environment for model-based expert systems; (3) provide insight into the advantages and disadvantagesof using LISP or Ada in the run-time environment for expert systems; and (4) compare the performance of the 80386 processor to a symbolic processor as a delivery vehicle for expert systems.

Brown, Barbara↗
DOE OSTI2022

Data coverage assessment on neural network based digital twins for autonomous control system

We report in a recently developed Nearly Autonomous Management and Control (NAMAC) system, neural networks (NNs) are used to develop digital twins for diagnosis (DT-Ds). However, NNs are not usually considered extrapolation models and may result in large errors if they are applied to unseen data outside the training data (uncovered). In this study, we propose a data coverage assessment (DCA) to determine if the NN-based DT-Ds are extrapolated based on their epistemic uncertainty. The uncertainty quantification algorithms and uncertainty thresholds are selected based on the confusion matrix of classifying evaluation data into covered or uncovered data. To demonstrate the adaptability of the proposed framework, we applied it to a basic feedforward neural network and a more advanced recurrent neural network based on a more nonlinear database. Case studies show that the proposed framework can distinguish unseen data for both basic and advanced applications with proper uncertainty quantification algorithms and thresholds.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1999

Information Technology and the Autonomous Control of a Mars In-Situ Propellant Production System

With the rapidly increasing performance of information technology, i.e., computer hardware and software systems, as well as networks and communication systems, a new capability is being developed that holds the clear promise of greatly increased exploration capability, along with dramatically reduced design, development, and operating costs. These new intelligent systems technologies, utilizing knowledge-based software and very high performance computer systems, will provide new design and development tools, scheduling mechanisms, and vehicle and system health monitoring capabilities. In addition, specific technologies such as neural nets will provide a degree of machine intelligence and associated autonomy which has previously been unavailable to the mission and spacecraft designer and to the system operator. One of the most promising applications of these new information technologies is to the area of in situ resource utilization. Useful resources such as oxygen, compressed carbon dioxide, water, methane, and buffer gases can be extracted and/or generated from planetary atmospheres, such as the Martian atmosphere. These products, when used for propulsion and life-support needs can provide significant savings in the launch mass and costs for both robotic and crewed missions. In the longer term the utilization of indigenous resources is an enabling technology that is vital to sustaining long duration human presence on Mars. This paper will present the concepts that are currently under investigation and development for mining the Martian atmosphere, such as temperature-swing adsorption, zirconia electrolysis etc., to create propellants and life-support materials. This description will be followed by an analysis of the information technology and control needs for the reliable and autonomous operation of such processing plants in a fault tolerant manner, as well as the approach being taken for the development of the controlling software. Finally, there will be a brief discussion of the verification and validation process so crucial to the implementation of mission-critical software.

Gross, Anthony R.↗
NASA NTRS2014

An Architecture to Enable Autonomous Control of Spacecraft

Autonomy is required for manned spacecraft missions distant enough that light-time communication delays make ground-based mission control infeasible. Presently, ground controllers develop a complete schedule of power modes for all spacecraft components based on a large number of factors. The proposed architecture is an early attempt to formalize and automate this process using on-vehicle computation resources. In order to demonstrate this architecture, an autonomous electrical power system controller and vehicle Mission Manager are constructed. These two components are designed to work together in order to plan upcoming load use as well as respond to unanticipated deviations from the plan. The communication protocol was developed using "paper" simulations prior to formally encoding the messages and developing software to implement the required functionality. These software routines exchange data via TCP/IP sockets with the Mission Manager operating at NASA Ames Research Center and the autonomous power controller running at NASA Glenn Research Center. The interconnected systems are tested and shown to be effective at planning the operation of a simulated quasi-steady state spacecraft power system and responding to unexpected disturbances.

space power systems↗
NASA NTRS2004

Simulation-Based Verification of Autonomous Controllers via Livingstone PathFinder

AI software is often used as a means for providing greater autonomy to automated systems, capable of coping with harsh and unpredictable environments. Due in part to the enormous space of possible situations that they aim to addrs, autonomous systems pose a serious challenge to traditional test-based verification approaches. Efficient verification approaches need to be perfected before these systems can reliably control critical applications. This publication describes Livingstone PathFinder (LPF), a verification tool for autonomous control software. LPF applies state space exploration algorithms to an instrumented testbed, consisting of the controller embedded in a simulated operating environment. Although LPF has focused on NASA s Livingstone model-based diagnosis system applications, the architecture is modular and adaptable to other systems. This article presents different facets of LPF and experimental results from applying the software to a Livingstone model of the main propulsion feed subsystem for a prototype space vehicle.

Lindsey, A. E.↗
NASA NTRS1987

An integrated approach to space station power system autonomous control

Space Station electrical power management must be accomplished autonomously in order to decrease both airborne and ground support costs. Attention is presently given to the augmentation of terrestrial utility algorithmic decision aids for power dispatching for space station use, using expert systems to direct power demand analyses and the integration of results into operational decisions. Functions to be thus managed encompass power scheduling, energy allocation, failure cause diagnoses, goal proposal and plan preparation, consequence evaluation, and execution plan selection. The operating states of the system are normal, preventive, emergency, and restorative.

Dolce, James L.↗
NASA NTRS2003

Agent Based Software for the Autonomous Control of Formation Flying Spacecraft

Distributed satellite systems is an enabling technology for many future NASA/DoD earth and space science missions, such as MMS, MAXIM, Leonardo, and LISA [1, 2, 3]. While formation flying offers significant science benefits, to reduce the operating costs for these missions it will be essential that these multiple vehicles effectively act as a single spacecraft by performing coordinated observations. Autonomous guidance, navigation, and control as part of a coordinated fleet-autonomy is a key technology that will help accomplish this complex goal. This is no small task, as most current space missions require significant input from the ground for even relatively simple decisions such as thruster burns. Work for the NMP DS1 mission focused on the development of the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. NMRA integrates traditional real-time monitoring and control with components for constraint-based planning, robust multi-threaded execution, and model-based diagnosis and reconfiguration. The complexity of using an autonomous approach for space flight software was evident when most of its capabilities were stripped off prior to launch (although more capability was uplinked subsequently, and the resulting demonstration was very successful).

How, Jonathan P.↗