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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 253 records · Page 14

All sources NASA NTRS DOE OSTI

NASA NTRS1989

Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

Zia, Omar↗

DOE OSTI2024

A Typing Discipline for High-Assurance Control Systems

This poster describes a typing discipline for high-assurance industrial systems based on three novel type systems. The first type system, information flow control (IFC), controls the flow of data through the system. The second system, dependent session types, restricts messages exchanged during the execution of a communication protocol to avoid dangerous states. The third system uses dimensional analysis to avoid subtle bugs that adversaries can exploit to cause the system to enter a dangerous state. This poster describes how a combination of these approaches can prevent sophisticated cyber attacks, such as the infamous Stuxnet incident, from occurring. In addition, we provide experimental evidence to support the claim that these approaches can be applied in control systems that are resource-constrained.

42 - ENGINEERING↗

NASA NTRS1994

Testing For EM Upsets In Aircraft Control Computers

Effects of transient electrical signals evaluated in laboratory tests. Method of evaluating nominally fault-tolerant, aircraft-type digital-computer-based control system devised. Provides for evaluation of susceptibility of system to upset and evaluation of integrity of control when system subjected to transient electrical signals like those induced by electromagnetic (EM) source, in this case lightning. Beyond aerospace applications, fault-tolerant control systems becoming more wide-spread in industry; such as in automobiles. Method supports practical, systematic tests for evaluation of designs of fault-tolerant control systems.

Belcastro, Celeste M.↗

DOE OSTI2021

Cyber-Informed Engineering Case Study of an Integrated Hydrogen Generation Plant

Strategies for securing digital instrumentation and control (I&C) systems within the nuclear industry are provided by multiple standards and guidance documents. However, since selection and use of security controls outlined in these documents are frequently only considered during or after installation, there are often limitations on their use, such as technological constraints related to design or operation. Furthermore, alternative controls intended to provide the same or similar security countermeasure as the primary control may also be infeasible at these stages, leaving the I&C system vulnerable to cyber-attacks. The limitations associated with ‘bolting on’ security controls late in the systems engineering lifecycle can be reduced by integrating Cyber-Informed Engineering (CIE) into the process. This paper evaluates the use of CIE during the high-level design stage of a hydrogen generation project where heat and electricity are provided by a nuclear power plant. Applying CIE to this project highlighted potential cyber vulnerabilities of the initial design, leading to recommendations for process flow and I&C system design modifications to reduce, and at times eliminate, the risk from both deliberate and unintentional cyber incidents.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1990

The procedure safety system

Telerobotic operations, whether under autonomous or teleoperated control, require a much more sophisticated safety system than that needed for most industrial applications. Industrial robots generally perform very repetitive tasks in a controlled, static environment. The safety system in that case can be as simple as shutting down the robot if a human enters the work area, or even simply building a cage around the work space. Telerobotic operations, however, will take place in a dynamic, sometimes unpredictable environment, and will involve complicated and perhaps unrehearsed manipulations. This creates a much greater potential for damage to the robot or objects in its vicinity. The Procedural Safety System (PSS) collects data from external sensors and the robot, then processes it through an expert system shell to determine whether an unsafe condition or potential unsafe condition exists. Unsafe conditions could include exceeding velocity, acceleration, torque, or joint limits, imminent collision, exceeding temperature limits, and robot or sensor component failure. If a threat to safety exists, the operator is warned. If the threat is serious enough, the robot is halted. The PSS, therefore, uses expert system technology to enhance safety thus reducing operator work load, allowing him/her to focus on performing the task at hand without the distraction of worrying about violating safety criteria.

Obrien, Maureen E.↗

DOE OSTI2025

Attempting to Develop the World’s Most Cost-Effective Metal 3D Printing Technology Through Industrial Adoption of a High-Temperature Electro-Magnetic Nozzle for 3D Printing and Computer Numerical Control Integration

This project aimed to make a practical system capable of sustained metal deposition in air engineered with industrial integration and controls. The Al-Ce wire feedstock was tailored with appropriate deposition and solidification properties for direct reactive interface printing (DRIP), and the goal was to integrate onto a Hybrid Manufacturing Technologies system for producing test parts without a controlled environment.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Attempting to Develop the World’s Most Cost-Effective Metal 3D Printing Technology Through Industrial Adoption of a High-Temperature Electro-Magnetic Nozzle for 3D Printing and Computer Numerical Control Integration

36 MATERIALS SCIENCE↗

DOE OSTI2022

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Cyber Secure Sensor Network for Fossil Fuel Power Generation Assets Monitoring

The energy sector is undergoing digital transformation which is to say more and more power generation assets have become automated and connected to the internet. The connected sensors can tap into plants to monitor the health of assets and manage fleets remotely. These are just some of the benefits digitalization is bringing to the power industry. Within a power plant, control systems are no longer concerned with one system or one piece of equipment, but rather whole fleet of assets inter-connected with smart sensors which have the function of continuously monitoring and transmitting real-time operational data to operators. These connected systems will form a part of the industrial internet of things (IIoT). The big data scenarios provide benefits of performing system prognostics and optimization which is a key selling point of power plant digitalization.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2026

Cybersecurity Center for Offshore Wind Energy (Final Project Report)

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models with SCADA infrastructure, and deployed a scaled physical turbine and associated sensors. High-resolution operational and side-channel data streams were collected and used to refine machine-learning (ML)-based attack detection systems and to extend the WindCRAFT framework to multi-turbine threat scenarios. The project demonstrated a realistic, scalable environment for evaluating cyber threats, validated attack detection approaches using enriched datasets, and identified new multi-turbine and inter-turbine communication attack vectors. The resulting testbed, models, and security mechanisms provide a foundation for ongoing R&D and deployment of cyber-resilient offshore wind energy systems.

17 WIND ENERGY↗

DOE OSTI2022

Machine Learning for Automated Metadata Assignment in Buildings: Cooperative Research and Development (Final Report, CRADA Number CRD-18-00767)

RealTerm Energy and NREL have identified a shared vision to evaluate opportunities to facilitate the organization and assignment of metadata to building control system (BCS) data via industry-informed machine learning (ML). Manual metadata assignment is labor intensive and costly, slowing down any Energy Management and Information System (EMIS) deployment in the building space. This project aims to develop methodologies to accurately assign this metadata and significantly decrease the level of effort associated with deploying EMIS. The objective of this project is to identify/design methodologies to assign metadata to HVAC control points automatically. The identified methodologies will be programmed in analytics algorithms so they can ingest a list of points and produce a detailed tagging following the Haystack classification nomenclature. To validate the efficacy of each methodology, tagging results will be compared utilizing a list of points extracted from RealTerm's building database-as well as data extracted from the NREL campus via the Intelligent Campus program-enabling testing against large datasets with real world challenges. The developed methodologies may leverage building manager/operator input on a limited basis to add context to the classifying algorithms. The partnership aims to advance global efforts in areas related to the DOE missions through improving operational performance of commercial buildings. It is well documented that buildings fall out of commission after they are occupied, wasting significant energy and incurring associated costs simply due to poor operational performance. Emerging EMIS technologies that perform continuous commissioning help to address this issue, yet integration of these systems can be labor intensive both for the technology vendor and the building owner/operator. This project will enable more efficient and cost-effective analytics for buildings, enabling improvement in building operations at lower cost points.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

A 100 kW 1.3 GHz Magnetron System with Amplitude and Phase Control

Calabazas Creek Research, Inc., Fermilab, and Communications & Power Industries, LLC, developed a 100 kW peak, 10 kW average, 1.3 GHz, magnetron-based, RF system for driving accelerators. Efficiency varied between 81% and 87%. Phase locking uses a novel approach that provides fast amplitude and phase control when coupled into a superconducting accelerator cavity [1]. The system was successfully tested at Fermilab and produced 100 kW in 1.5 ms pulses at a repetition rate of 2 pps. A locking bandwidth of 0.9 MHz was achieved with a drive signal of 269 W injected through a 4 port circulator. The phase locking signal was 25 dB below the magnetron output power. The spectrum of the phase locked magnetron was suitable for driving accelerator cavities. Phase modulation was demonstrated to 50 kHz (the limit of the available driver source). The average power was limited by available conditioning time. Scaling indicates 42 kW of average power should be achievable. Estimated cost is less than $1/Watt of delivered RF power, exclusive of power supplies or modulators. System design and performance measurements will be presented.

43 PARTICLE ACCELERATORS↗

NASA NTRS1985

Automated Solar-Panel Fabricator

Automated computer-controlled system based on standard commercial industrial robot takes solar cells and other raw materials and assembles them into completed solar panels.

Hagerty, J. J.↗

DOE OSTI2024

Using Hardware-In-The-Loop Methodology to Develop Test Systems

Hardware in the Loop (HIL) testing methodologies have become widespread in industry. Typically, they focus on developing control algorithms for systems such as autonomous vehicles or aircraft. An oft overlooked aspect of product development is the design and fabrication of a test system for validating that the product meets requirements. Abstractly, a test system differs little from a control system—testers provide signals to the unit, monitor feedback, and base decisions on the results. While the time scales may differ, the functionalities are conceptually similar. Viewed in this light, it becomes natural to extend HIL approaches to tester development. By replacing a physical unit with a proxy model deployed to a real-time or pseudo real-time target, test systems can be developed in parallel with the design and fabrication of a first production unit. This saves considerable time in the life cycle from conceptual design to realized product. This manuscript demonstrates the process flow using a capacitive discharge unit as an exemplar.

42 ENGINEERING↗

DOE OSTI2024

Living-off-the-land Techniques Unlikely to Supplant Energy Sector-Focused OT-Specific Malware

Despite increased reports of energy sector-focused threat actors using living-off-the-land (LOTL) techniques, it is unlikely LOTL techniques will wholly supplant malware in energy sector operational technology (OT)-focused cyber operations. Threat actors leverage LOTL techniques to access energy sector networks, abstracting process information and maintaining persistence. Although threat actors using LOTL techniques have successfully interrupted energy sector industrial control environments, designed features of OT-specific malware likely increase the cyber-physical impact of an attack and delay recovery of critical functions and services. Malicious actors will very likely continue to use LOTL techniques for stealth, while designing malware to bolster final impacts on cyber-physical systems in energy sector OT environments.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Securing Smart Manufacturing: Detection of Cyber-Physical Attacks in CNC-Based Systems

As Industry 4.0 advances, the integration of computer numerical control (CNC) machines and advanced manufacturing technologies is transforming production into smart manufacturing systems that blend physical and digital processes as cyber-physical systems. However, this increased cyber-physical connectivity exposes manufacturing systems to cyber threats that can cause severe operational and financial disruptions. This paper presents a comparative study on cyber attacks and anomaly detection techniques in manufacturing, focusing on network traffic from CNC machines. The data extracted from network packets includes machine commands and control signals exchanged between the machine's interface and control system, crucial for maintaining operational integrity. We explore two types of cyber attacks, design modification and command injection, which pose substantial risks to CNC machine productivity and system integrity. Our investigation involves experiments on a real CNC system, highlighting the urgent need for effective detection mechanisms. To address these threats, we evaluate three anomaly detection methods: dynamic time warping (DTW), rolling average, and a deep learning, long short-term memory (LSTM) time-series-based autoencoder. Each is assessed for its effectiveness in identifying anomalous behaviors caused by the attacks. Our findings demonstrate the unique strengths and limitations of each detection technique, providing a deeper understanding of their applicability in realworld manufacturing environments. The comparative analysis indicates that while certain methods are highly effective against specific attack types, others offer broader applicability across different attacks. This study contributes to the accurate detection of anomalies in CNC machining processes, thereby enhancing the reliability and security of smart manufacturing systems against diverse cyber threats.

Williams, Bethanie [Tennessee Technological Univer↗

DOE OSTI2023

Operational control with set-points tuning - application to mobile robots

This paper proposes a novel method for the optimal tuning of set points for multiple-layered control system structure widely seen in robotics and other complex industrial processes composed of a number of subsystems. The terminal sliding mode control (SMC) is used as the low-level control strategy to ensure the stability of subsystems. When uncertainties exist, it can be shown that the deteriorated system performance will be improved by the outer loop with set points tuning. For this purpose, the learning of the new set point is designed to compensate for the effects caused by uncertainties during the system operation. At the same time, the system is proven to stay with the original set point when the compensation is introduced. A practical application to a holonomic mobile robot system is given to illustrate the presented method. Desired results have been obtained.

42 ENGINEERING↗

NASA NTRS1988

Force control of a multi-arm robot system

A force-compensated control method for multiple manipulators is presented that allows coordinated manipulation of a jointly grasped object. In this scheme, each arm independently carries out the motions required to realize the desired motion of a prescribed point on the manipulated object. The approach has been implemented and demonstrated on a laboratory system consisting of two industrial, computer-controller manipulators.

Alberts, Thomas E.↗