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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
DOE OSTI2024

Designing Remote Monitoring for Smart Manufacturing Facilities: Hazard Identification and Classification

This study investigates the process of hazard identification in complex manufacturing environments during the design phase, emphasizing the significance of the design process in developing designs that effectively mitigate hazards in contexts with numerous variables, such as a variety of machines, sensors, actuators, and agents. Through a mixed-methods approach, the objective of this work is to understand how the evolution of design outcomes across various stages might influence a designer’s ability to recognize both standard and novel hazards. To achieve this understanding, an experimental design task was conducted with six designers from a national lab specializing in manufacturing technologies. This approach combined qualitative and quantitative data analysis from a one-hour virtual session with participants. Findings suggest that the complexity of identifying hazards in a high-dimensional design space is challenging within a limited time frame and that the identification of hazards is significantly influenced by the stage of the design task and the initial design decisions, indicating the need for extended time and strategic initial planning in the design process to enhance hazard identification.

Ballestas, Caseysimone↗
DOE OSTI2021

High-Performance Piezoelectric MEMS Manufacturing & Application on Micro Power Generators (CRADA Final Report)

This project aimed to develop and characterize a micro-fabrication technology for wafer-scale heterogeneous integration of bulk piezoelectric materials on silicon substrates that could enable manufacturing of high-performance micro transducers. Typical technical challenges for piezoelectric microfabrication technologies are high-temperature processing, non-uniform film quality, and low process repeatability, which will be addressed during this project. Progress was made on preliminary research towards development of a technology platform that will enable a new micro-fabrication process to provide the highest electromechanical coupling among any other thin/thick-film deposition methods available today. This work has tested and characterized samples that we hope will further our goal of refining and enabling existing micro transducers to achieve unprecedentedly high performance. This project focused solely on the characterization of the proposed microfabrication process technology, and it did not consist of design or manufacturing of new transducers, such as sensors, actuators or energy harvesters based on this fabrication process. Future work will be aimed at the research and development of process steps specifically to enable integration of on-chip electronics with piezoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Moore Machine Motion Controls Refurbishment Statement of Work and Specification

Diamond Turning Machines known as “Moore” machines are used in the production of Potassium diHydrogen Phosphate (KDP) optics required for the National Ignition Facility (NIF). These machines are owned by the Department of Energy, as provided by Lawrence Livermore National Security LLC (LLNS). Moore Machines 1 and 2 are located at the Gooch & Housego (G&H) facility in Highland Heights, OH. The existing Aerotech motion controllers, motor drivers/amplifiers, input/output (I/O) hardware, control computer, software user interface, human machine interface (HMI), cabling, and encoders are beyond service life and require replacement. This Statement of Work (SoW) defines the motion control system refurbishment requirements for the Moore diamond turning machines designated Moore 1 and Moore 2. The motion controls system design shall include a motion control computer, control software, motor drive amplifiers and controllers, linear scale encoders, rotary encoders, HMI, power distribution, emergency stop (E-Stop) and interlocks, cabling, switches, solenoids, transducers, sensors, actuators, ancillary system interfaces, and related components necessary for a complete machine tool control system. The Subcontractor shall include effort to standardize systems between the two machines if reasonably possible.

42 ENGINEERING↗
DOE OSTI2026

CONTROL AND DATA ACQUISITION IN A CYBER-PHYSICAL MIDSTREAM TESTBED

This thesis presents the development of a laboratory-scale cyber–physical midstream pipeline testbed designed to address this gap and support research in industrial control systems security. The platform integrates pumps, valves, sensors, programmable logic controllers (PLCs), and a human–machine interface (HMI) to emulate the monitoring and control architecture of real pipeline operations. The physical process is implemented as a closed-loop liquid circulation system designed to replicate flow behavior characteristic of midstream pipeline infrastructure. The testbed enables real-time data acquisition of key process variables, including flow rate and pressure facilitating the generation of datasets representative of normal pipeline operation. A threat model encompassing common ICS attack vectors was developed, including sensor spoofing, command injection, false data injection, denial-of-service attacks, and relay manipulation. Multiple attack scenarios were implemented and evaluated to demonstrate how cyber intrusions targeting sensors, actuators, networks, and software propagate into measurable physical consequences in pipeline flow and pressure. The developed platform serves as a practical, cost-effective environment for experimentation, education, and future cybersecurity research in midstream pipeline systems.

42 ENGINEERING↗
DOE OSTI2025

Synergistic effects of Pd single atoms and nanoclusters boosting SnO 2 gas sensing performance

Tin(IV) oxide-supported Pd is a promising heterogenous catalyst for CO oxidation relevant for environmental cleanup reactions. In this study, an atomically dispersed Pd catalyst on SnO 2 (ADC Pd/SnO 2 ) hybrid material is successfully synthesized via a straightforward wet chemistry method and is found to exhibit superior performance toward CO sensing. Ex situ EXAFS analysis confirms the formation of single Pd atoms and small Pd nanoclusters stabilized on the SnO 2 (110) surface. Further, the material exhibits high efficiency in generating adsorbed O 2 - as well as high activity in catalyzing CO oxidation at low temperatures, resulting in exceptional sensitivity and selectivity toward CO in comparison to pure SnO 2 and Pd nanoparticles loaded on SnO 2 respectively. In situ FTIR measurements unravel CO adsorption kinetics on ADC Pd/SnO 2 under reaction conditions, and a possible sensing mechanism is put forth in which CO is transformed into CO 2 by reaction with active oxygen species; and concurrently, carbon-related species (bicarbonates and carbonates) are formed and decomposed into CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Piezoelectric Actuation of Graphene-Coated Polar Structures

Ferroelectric materials based on lead zirconate titanate (PZT) are widely used as sensors and actuators because of their strong piezoelectric activity. However, their application is limited because of the high processing temperature, brittleness, lack of conformal deposition, and a limited possibility to be integrated with the microelectromechanical systems (MEMS). Recent studies on the piezoelectricity in the 2-D materials have demonstrated their potential in these applications, essentially due to their flexibility and integrability with the MEMS. In this work, we deposited a few layer graphene (FLG) on the amorphous oxidized Si 3 N 4 membranes and studied their piezoelectric response by sensitive laser interferometry and rigorous finite-element modeling (FEM) analysis. Modal analysis by FEM and comparison with the experimental results show that the driving force for the piezoelectric-like response can be a polar interface layer formed between the residual oxygen in Si 3 N 4 and the FLG. The response was about 14 nm/V at resonance and could be further enhanced by adjusting the geometry of the device. These phenomena are fully consistent with the earlier piezoresponse force microscopy (PFM) observations of the piezoelectricity of the graphene on SiO 2 and open up an avenue for using graphene-coated structures in the MEMS.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sensing Electrical Networks Securely & Economically (SENSE)

The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Achieving Cyber-Resilience for Power Systems using a Learning, Model-Assisted Blockchain Framework

The secure integration and management of distributed energy resources (DER) and power aggregators in the electric grid requires secure communications and a physics-aware Command and Control (C2) strategy. A Blockchain (BC)-based overlay network was developed to provide a security layer for the existing power grid network that mitigates risks in current and legacy network and C2 protocols. By integrating a Model-Assisted Machine Learning (MAML) framework with a Secure Blockchain Overlay Network (SBON) a defense-in-depth strategy was achieved. In our approach, the MAML framework leveraged a smart contract framework to gather network data and learn the dynamics of DER to develop detection strategies for attacks targeting sensors and actuators used by DER. The MAML framework learned dynamical systems models for individual DERs to detect sensor attacks. For DER we utilized a Digital Twin (DT) to accelerate the learning process for a model resistant to stealthy attacks. The project created DT for PV inverters and BESS. The DTs were coupled with a model-assisted, data-driven learning of DER behavior. Specifically, we evaluated architectures for model-based learning with model-free fine-tuning. Additionally, differential privacy techniques were used to obfuscate data, while still allowing the computation of attack detection results based on obfuscated data. The SBON developed leverages a private permissioned blockchain network orchestrated with the Hyperledger Fabric framework. To connect the cyber world, which orchestrates the blockchain fabric, and the physical world where the power network resides, we developed a system implementation to enable the secure interaction of the physical world and the abstracted blockchain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Secure Data Logging and Processing with Blockchain and Machine Learning (Final Report)

Secure Data Logging and Processing with Blockchain and Machine Learning (ML) research is focused on the development of a platform to securely log and process sensor data in fossil power plants. The platform integrates two emerging technologies, blockchain and ML, and incorporates several innovative mechanisms to ensure the integrity, reliability, and resiliency of power systems. The goal is to protect the power plant from various cyberattacks such as false data injection and denial of service attacks using these technologies. The research goal was enabled by the following Research Project Objectives: 1) Secure authentication and identity verification of sensor nodes, actuators, and other equipment within a network. 2) Development of mechanisms that ensure only data sent by legitimate sensors are accepted and stored in the data repository. 3) Development of data aggregation methodologies using ML / Deep Learning (DL) algorithms to minimize noise / faulty data. 4) Implementation of the blockchain technologies to provide data security using secured IOTA framework & nodes.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Distributed, Intelligent Edge-Sensing for a Smarter Grid

The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.

Kulkarni, Shreyas Bhalchandra↗
DOE OSTI2020

FALCON: Framework for Anomaly Detection in Industrial Control Systems

Industrial Control Systems (ICS) are used to control physical processes in critical infrastructure. These systems are used in a wide variety of operations such as water treatment, power generation and distribution, and manufacturing. While the safety and security of these systems are of serious concern, recent reports have shown an increase in targeted attacks aimed at manipulating physical processes to cause catastrophic consequences. This trend emphasizes the need for algorithms and tools that provide resilient and smart attack detection mechanisms to protect ICS. In this paper, we propose an anomaly detection framework for ICS based on a deep neural network. The proposed methodology uses dilated convolution and long short-term memory (LSTM) layers to learn temporal as well as long term dependencies within sensor and actuator data in an ICS. The sensor/actuator data are passed through a unique feature engineering pipeline where wavelet transformation is applied to the sensor signals to extract features that are fed into the model. Additionally, this paper explores four variations of supervised deep learning models, as well as an unsupervised support vector machine (SVM) model for this problem. The proposed framework is validated on Secure Water Treatment testbed results. This framework detects more attacks in a shorter period of time than previously published methods.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Revealing Three-Dimensional Morphology in Nanoporous Gold Using Three-Dimensional X-Ray Fresnel Coherent Diffractive Imaging Tomography

Nanoporous metals fabricated by dealloying have a unique bi-continuous, sponge-like porous structure with ultra-high surface area. The unique properties of these materials, especially nanoporous gold, have numerous potential applications in sensors and actuators and in energy-related applications such as catalytic materials, super-capacitors, and battery supports. The degree of porosity and size of the metal ligaments are critical parameters that determine many properties and thus govern the functionalities of nanoporous metals in many applications including energy storage and conversion. Additionally, we used Fresnel coherent diffractive imaging combined with tomographic reconstruction to quantify the nanoscale three-dimensional spatial distribution and homogeneity of the porosity and ligament size within a bulk sample of nanoporous gold. The average porosity and its standard deviation along the axial direction through the sample were determined, as well as the characteristic feature size and its standard deviation. The result shows that free corrosion is an effective way to create homogeneous nanoporous metals with sample sizes on the order of 1 µm.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Postirradiation Examination of WIRE-21 Experiment Irradiated in the High Flux Isotope Reactor

Westinghouse Electric Company is developing wireless sensors to monitor the centerline temperature and internal pressure of commercial light-water reactor fuel rods during irradiation. Oak Ridge National Laboratory and Westinghouse Electric Company developed the Wireless Instrumented RB Experiment 2021 (WIRE-21) to test wireless temperature and pressure sensor technologies in a removable beryllium position in the High Flux Isotope Reactor. The experiment was irradiated for a total of 75 days, at temperatures ranging from approximately 150°C to 400°C, resulting in a peak fast (energy > 0.1 MeV) neutron fluence of about 3 × 10 21 n/cm 2 . The temperature was intentionally cycled multiple times to compare the response of the wireless temperature sensor to collocated thermocouples. Similarly, the pressure sensor was actuated in multiple steps to compare the response of the wireless measurement to excore pressure transducers (Petrie et al., 2023). After irradiation, the experiment was disassembled in the Irradiated Fuels Examination Laboratory (IFEL) hot cell at Oak Ridge National Laboratory with the intent to recover sensor and dosimetry components, document the as-irradiated condition of the hardware, and investigate possible causes of the sensor behavior observed during irradiation. The postirradiation examination successfully recovered and preserved key WIRE-21 components. After the housing was removed using a milling machine, the internal experiment sections were examined. All eight fiber-optic sensors were recovered, cut, and stored. The silicon carbide thermometry, temperature sensor, pressure sensor, lower spacer, and selected pressure and temperature cable sections were also removed and stored. The metal bellows of the pressure sensor was found to be plastically deformed, indicating that it had been properly pressurized during irradiation and generally behaved as expected. X-ray diffraction analysis of a section of one of the irradiated inductor cores within the pressure sensor was performed and confirmed the presence of phase-pure alpha ferrite (i.e., no unexpected phase transformations). Inductance testing was performed on the irradiated pressure sensor cores using an unirradiated test coil, and DC resistance measurements of the transceiver coils were also performed. The measurements with irradiated inductor cores assembled inside unirradiated coils showed slightly reduced inductance compared to measurements made with unirradiated cores, but the difference was not sufficient to explain the more significant reductions in inductance that were observed in-pile. Therefore, it is suspected that degradation of the inductor coils (specifically the wire wrapping) is responsible for the reduced inductance observed in-pile.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The global energy footprint of information and communication technology electronics in connected Internet-of-Things devices

Information and communication technology (ICT) has been critical to the emergence of a new Internet-of-Things (IoT) era, as a rapidly increasing number and variety of IoT electronic devices in a wide range of end-use sectors require massive data communication in terms of volume, velocity/speed, and variety. Additionally, semiconductor technology advancements have played a key role in ICT and unlike the past ICT energy footprint analysis, which focused on the final electronic product, an attempt has been made to examine the global energy impacts for the period 2016–2025 based on the market forecasts of three major IoT IC types, i.e., sensors and actuators, connectivity, and processor ICs distributed among four major IoT device components.Total global IoT semiconductor primary energy demand is projected to increase from 2 EJ in 2016 to 35 EJ by 2025, resulting mainly from a substantial projected increase energy needed in the manufacturing of ICs, with growth in the use of sensors and energy-intensive next fab generation manufacturing. Unlike the trend in manufacturing energy, total global operational energy use is projected to decrease significantly with the development of smaller transistor size, low-power devices, and faster wireless data communication technology. Total operational energy is projected to significantly decrease from 118 TWh/year (1,2 EJ/year) to less than 1 TWh/year (0.003 EJ/year) in spite of a significantly higher anticipated growth in its market size during the 2016–2025 forecast period. Its annual share of total primary energy use is projected to reach an insignificant level of 0.01% by the end of 2025, consistent with the past limited electronic product life cycle analyses besides the analysis focus here limited to ICs in IoT devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Dynamic, resilient virtual sensing system and shadow controller for cyber-attack neutralization

An industrial asset may have monitoring nodes (e.g., sensor or actuator nodes) that generate current monitoring node values. An abnormality detection and localization computer may receive the series of current monitoring node values and output an indication of at least one abnormal monitoring node that is currently being attacked or experiencing a fault. An actor-critic platform may tune a dynamic, resilient state estimator for a sensor node and output tuning parameters for a controller that improve operation of the industrial asset during the current attack or fault. The actor-critic platform may include, for example, a dynamic, resilient state estimator, an actor model, and a critic model. According to some embodiments, a value function of the critic model is updated for each action of the actor model and each action of the actor model is evaluated by the critic model to update a policy of the actor-critic platform.

Roychowdhury, Subhrajit↗
DOE OSTI2026

MARVEL Instrumentation, Control, and Software Considerations

This paper details the various I&C considerations and design decisions made throughout the MARVEL (Micro-reactor Applications Research Validation and Evaluation) project, including sensor and actuator selection, safety-related functionality, digital control hardware and software, and testing methodologies. Key challenges such as managing radiation, temperature, and space constraints are discussed, along with the trade-offs between using standard equipment and custom solutions. The successful integration of off-the-shelf components, the emphasis on minimizing safety-related instrumentation, and the lessons learned from prototyping and testing are highlighted. The authors aim to provide insights that can benefit future micro-reactor designs and emphasize the importance of real-world testing in advancing reactor technology.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗