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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Final CRADA Report for Enhanced and Miniaturized Wireless Valve Position Indicator Prototype

Most operating nuclear power plants (NPPs) in the United States have received approval to extend their operating licenses to 60 years. Now the nuclear industry is preparing to extend operating licenses to 80 years. While NPPs are preparing for extensions (60 years and beyond), the nuclear industry is facing a unique economic sustainability challenge in the current energy market. According to the Nuclear Energy Institute (NEI), generating costs of U.S. reactors have risen by 28% over the last 12 years, which is impacting the competitiveness of nuclear power in a market being increasingly penetrated by natural gas and renewable energy. This is partly because of the fact that the present nuclear work practice is dependent on a large technical staff which results in high operation and maintenance (O&M) costs, accounting for approximately 66% of the total operating cost. To address these concerns and abide by the NEI’s “Delivering the Nuclear Promise Initiative,” the U.S. utilities are embracing digitalization of their work practice to lower the O&M costs and increase productivity and efficiency while maintaining a safe and reliable operation. To address these above-mentioned concerns, Idaho National Laboratory (INL) researchers (proposal team) have developed a wireless valve position indication (VPI) sensor system that can be retrofitted on three main manual valve types (extendible to other manual valve types) to replace manual valve position verification with digital verification and enable online monitoring of manual valves. The developed technology 1) is evaluated for electromagnetic interference, 2) has a low power consuming and miniaturized electronic board, 3) is mounted on adjustable and reconfigurable sensor mounting unit that can fit on an actual flow-loop (at Idaho State University-ISU) to enable online monitoring of manual valve types without any valve body modification, and 4) ensures robust, secure, and reliable real-time communication of manual valve position.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Resilient Autonomous Wind Farms: Preprint

With the advent of an increasing number of control strategies that seek to optimize wind turbine performance on a farm-level, taking account of individual wind turbine information to achieve wind farm-level objectives has become an increasingly important goal. Methods for controlling wind turbines on an individual and farm level have seen significant development, and an abundance of new implementations for gathering and using data from turbines have created potential for novel control mechanisms which can further optimize the performance and delivery characteristics of a wind farm. A key element of making these wind farms more efficient is to develop reliable algorithms that use local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. Making use of information from all wind turbines in a wind farm can enable such approaches as determining the atmospheric conditions across the farm, improving fault-finding, and enabling more efficient overall control of farm-wide optimizations through mechanisms such as wake-steering. However, these approaches typically involve a centralized communications and control center. In order to ensure the resilient operation of the farm, it is necessary to develop an approach which distributes the calculation and communication amongst multiple nodes throughout the farm. In this fashion, a redundant, robust, and secure network can be created, which can tolerate faults in calculation, communication, and even external attacks which seek to disrupt the operation of the wind farm. This paper introduces the use of the Raft Byzantine Fault Tolerance algorithm in the implementation of autonomous control of a wind farm. This implementation will allow for fault tolerance for malfunctioning nodes, sensors, transmitters, and connectors. This approach is equally extensible to account for malicious actors. It will be shown to achieve overall consensus, provided the number of faults/malicious nodes is less than 3$n$+1, where $n$ is the number of turbine cluster faults which may occur, and to be robust in the face of multiple arbitrary faults.

autonomous↗
DOE OSTI2020

Resilient Autonomous Wind Farms

With the advent of an increasing number of control strategies that seek to optimize wind turbine performance on a farm level, taking into account individual wind turbine information to achieve wind-farm-level objectives has become an increasingly important goal. Methods for controlling wind turbines on an individual and farm level have experienced significant development, and an abundance of new implementations for gathering and using data from turbines have created potential for novel control mechanisms that can further optimize the performance and delivery characteristics of a wind farm. A key element of making these wind farms more efficient is to develop reliable algorithms that use local sensor information that is already being collected, such as from local meteorological stations, nearby radars, sodars, and lidars, and supervisory control and data acquisition (SCADA) data. Making use of information from all wind turbines in a wind farm can enable such approaches as determining the atmospheric conditions across the farm, improving fault-finding, and ensuring more efficient overall control of farmwide optimizations through mechanisms such as wake steering. However, these approaches typically involve a centralized communications and control center. In order to ensure the resilient operation of the farm, it is necessary to develop an approach that distributes the calculation and communication amongst multiple nodes throughout the farm. In this fashion, a redundant, robust, and secure network can be created, which can tolerate faults in calculation, communication, and even external attacks that seek to disrupt the operation of the wind farm. This paper introduces the use of the Raft-Byzantine-Fault-Tolerant algorithm in the implementation of autonomous control of a wind farm. This implementation will allow for fault tolerance for malfunctioning nodes, sensors, transmitters, and connectors. This approach is equally extensible to account for malicious actors. It will...

fault tolerance↗
DOE OSTI2025

28nm front end ASIC and 12” LGADs for 3D integration

The 3DIntSenS Collaboration—a joint effort between SLAC, Fermilab, and LLNL—is developing enabling technologies for next-generation radiation imaging detectors that combine ultra-fine spatial resolution (≈10 μm) with precision timing (<20 ps), while maintaining low power <1 W/cm2 and high data throughput. The approach leverages 3D integration between advanced CMOS readout ASICs and finely pixelated LGAD sensors to achieve the performance and scalability required for large-area, high-rate applications. High-granularity, precision-timing detectors are essential for scientific advances in HEP, NP, BES, and FES, but widespread adoption is limited by the cost and complexity of 3D integration. To close this gap, the collaboration is developing LGAD sensors compatible with 12-inch commercial CMOS processes, enabling cost-effective integration with high-performance ASICs under development. We present the design and results from a 28 nm CMOS ASIC prototype, including a low-jitter front end, and in-pixel TDC demonstrating sub-10 ps timing resolution. We also report on the co-design and characterization of reticle-scale LGAD sensors with 50 μm and 100 μm pixels and introduce the next 10k-pixel ASIC designed for full 3D integration. These advances represent a critical step toward scalable, high-resolution radiation imaging systems for future scientific instrumentation.

England, Troy [Fermilab] (ORCID:0000000154405255)↗
DOE OSTI2019

Savannah River Site H-Canyon Collaborative Advanced Technology Demonstration (ATD) Program Review - 19499

The purpose of the Department of Energy-Environmental Management Office of Technology Development's (DOE-EM TD) Science of Safety (SOS) Robotics Initiative is to pull innovative commercial off the shelf (COTS) and near ready technologies to the field to expedite remaining EM mission clean up and enhance worker safety. A goal of this program is to demonstrate to DOE facilities the value of these available new technologies and their potential uses to solve difficult problems. In support of this goal, the Savannah River Site (SRS) H-Canyon Air Exhaust (HCAEX) tunnel biannual inspection task has been selected to demonstrate and evaluate the benefit of pulling advanced technology solutions to EM facilities. This is a highly collaborative task facilitated by SRNL and engaging SRS H-Canyon facility stakeholders, National Laboratory robotic and concrete inspection SMEs and university robotic and sensor researchers. Presently, the SRS HCAEX tunnel inspection consists of a visual examination to evaluate the structural integrity of the tunnel. Personal access is prohibited in the tunnel due to extreme conditions, thus the examination is accomplished remotely by deploying cameras mounted on a robotic crawler deployed into the tunnel. While the ability to see inside the tunnel in recent years has been highly valuable, it is desirable to have a better understanding of the environment to support a more thorough structural analysis and for long term planning purposes. This higher order of understanding can be accomplished through advanced COTS sensors and tools and those currently in development and near ready. The advanced technologies selected for demonstration will be evaluated for hosting on the FY19 HCAEX tunnel inspection crawler platform. The HCAEX ATD task is expected to be performed over a two-year period with year one now concluding. At WM2018, we presented the H-Canyon stakeholder's high priority inspection and remote handling needs, the collaboration team and the planned process of developing an integrated solution. This presentation will review the initial scope and inspection needs, then discuss the past year's progress to address these needs. The discussion includes the results of the Concrete Integrated Product Team (CIPT) formed to evaluate promising concrete NDE inspection technologies and a Lidar based tunnel mapping sensor suite solution. Highlighted in the discussion will be the engagement and pulling of university developed research and development to include student engagement through the formation and hosting of the SRNL Robotics and Sensors Intern team and collaboration with MSIPP funded Robotic Arm Concrete NDT Inspection University researchers. Lastly, the path forward to complete the demonstration will be presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

AOI [3]: Smart Refractory Sensor Systems for Wireless Monitoring of Temperature, Health, and Degradation of Slagging Gasifiers

The objective of the work was to develop refractory “smart bricks”, which would contain embedded temperature, strain/stress, and spallation sensors throughout the volume of highchromia (-Cr 2 O 3 ) refractory brick. The proposed work included work to interconnect the sensors to the reactor exterior, where the sensor signals may be processed by low-power electronics and transmitted wirelessly to a central processing hub. The data processing and wireless transmitter hardware was specifically designed to be isolated (with low power consumption) and to be adaptable to future implementation of energy-harvesting strategies for extended life. Finally, the collected data was incorporated into a model to estimate refractory degradation, a technique that could help monitor the health of the refractory in real-time. The long-term goal of this program was to demonstrate high-temperature, wireless sensor arrays for in situ three-dimensional (3-D) refractory monitoring or mapping for slagging gasification systems. The research was in collaboration with HarbisonWalker International (HWI) Technology Center in West Mifflin, PA. HWI is a leading developer and manufacturer of ceramic refractory products for high-temperature applications. The work completed focused on the following areas: 1) Investigation of the chemical stability, microstructural evolution, grain growth kinetics, degree of homogeneity (quantitative image analysis), and electrical properties of refractory oxide-silicide composites at temperatures between 750-1450ºC; 2) Fabrication of silicide-alumina composite and oxide thermocouples and thermistor preforms and the development of techniques to embed them into high-chromia refractory bricks to form “smart bricks”; 3) Utilization of commercial off-the-shelf discrete components to prototype circuits for interfacing between smart brick sensors and the wireless sensor network. The prototypes were then used to design an integrated circuit for thermistor, thermocouple, and capacitive-based smart brick sensor interfacing; 4) Interfacing of the smart bricks with embedded sensors with wireless motes thus yielding a complete signal chain. This end-to-end data collection system was tested on a furnace heated to 1350°C; 5) Development of a slag penetration model and a nonlinear unknown input filter for the data from the embedded sensors for estimating temperature and extent of slag penetration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

N-type organic electrochemical transistors with stability in water

Organic electrochemical transistors (OECTs) are receiving significant attention due to their ability to efficiently transduce biological signals. A major limitation of this technology is that only p-type materials have been reported, which precludes the development of complementary circuits, and limits sensor technologies. Here, we report the first ever n-type OECT, with relatively balanced ambipolar charge transport characteristics based on a polymer that supports both hole and electron transport along its backbone when doped through an aqueous electrolyte and in the presence of oxygen. This new semiconducting polymer is designed specifically to facilitate ion transport and promote electrochemical doping. Stability measurements in water show no degradation when tested for 2 h under continuous cycling. Furthermore, this demonstration opens the possibility to develop complementary circuits based on OECTs and to improve the sophistication of bioelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

First bulk and surface results for the ATLAS ITk Strip stereo annulus sensors

A novel microstrip sensor geometry, the stereo annulus, has been developed for use in the end-cap of the ATLAS experiment’s strip tracker upgrade at the HL-LHC. Its first implementation is in the ATLAS12EC sensors, a large-area, radiation-hard, single-sided, AC-coupled, n + -in-p design produced by the ITk Strip Sensor Collaboration and fabricated by Hamamatsu Photonics in early 2017. The results of the initial testing of two ATLAS12EC batches are presented here with a comparison to specification. The potential of the new sensor shape to reinvigorate endcap strip tracking is explained and its effects on sensor performance are isolated by comparing the bulk mechanical and electrical properties of the new sensor to the previous iteration of prototype, the conventional barrel ATLAS12A sensor. The surface properties of the new sensor are evaluated for full-size unirradiated sensors as well as for mini sensors unirradiated and irradiated with protons up to a fluence of 2.2 x 10 15 n eq cm -2 . The results show that the new stereo annulus ATLAS12EC sensors exhibit excellent performance and the expected irradiation evolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Integrated field phenotyping and management platform for crop development and precision agriculture

A field controller and sensor is presented as an elongate body having a hollow interior and axially opposite first and second ends with a first arm extending outward from the elongate body adjacent to the first axial end and a second arm extending outward from the elongate body adjacent to the second, axially opposite end. Each of the arms has an imaging device. The first arm imaging device is positioned to obtain images in a direction toward the second axial end of the elongate body. The second arm imaging device is positioned to obtain images in a direction toward the first axial end. The first and second arms are spaced apart from one another along a length of the elongate body at a distance sufficient to image a canopy of crop growth in a field in which the field controller and sensor is deployed. The sensor may be formed from modules that allow the operator the ability to vary the height of the sensor by stacking the modules together end to end, which in turn allows users to scale their particular system with varying crop sizes within crop rotations.

Shakoor, Nadia↗
DOE OSTI2024

Low-cost Retrofit Kit for Integral Reciprocating Compressors (IRCs) to Reduce Emissions and Enhance Efficiency

Methane emissions from natural gas engines within the oil and gas industry pose a significant environmental challenge, contributing approximately 34.1 MMTCO2 eq to the total of 239 MMTCO2 eq of methane emissions in 2021, according to the EPA report. In response to this pressing issue, a collaborative effort involving the University of Oklahoma and key industry partners—WAGO Automation, Mid Continental Rental, Elipsa, and Perscient—has resulted in the development of a retrofit kit designed to reduce emissions from integral reciprocating compressors (IRCs), which are integrated compressors and engines. The retrofit kit developed comprises an Air Management System (AMS), Integrated Sensors, and a Cloud-Connected Control Unit with Graphical User Interface (GUI)/Human-Machine Interface (HMI). This solution enhances operational efficiency, reduces emissions, and expands the operational envelope of IRCs in the natural gas industry. The project successfully completed all tasks, including the installation of a full-size IRC at a designated site in Oklahoma, the development of an optimized AMS, integration of sensors, and implementation of a data acquisition system. Significant achievements include a notable reduction in CH 4 emissions, up to 84% at specific loads, and the successful deployment of the retrofit kit in diverse field conditions. The system's capabilities were enhanced through the creation of a feedback control algorithm for the AMS using a correlation matrix illustrating relationships between engine parameters, and the design of a predictive and preventive maintenance platform. The project concluded with the deployment of the entire retrofit kit to another location, confirming its effectiveness in reducing emissions and enhancing IRC performance. The comprehensive solution offers valuable benefits for IRCs, making them invaluable assets in the natural gas industry.

03 NATURAL GAS↗
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 OSTI2019

Evaluating Laser-Induced Breakdown Spectroscopy Sensor Technology for Rapid Source Characterization of Rare Earth Elements

A prototype Laser Induced Breakdown Spectroscopy (LIBS) sensor is tested for the determination of rare earth elements (Eu and Yb) in liquid and solid samples. The sensor head, built using a monolithic passively Q-switched (PQSW) Nd:YAG laser, produced a 1064 nm laser beam with 3.3 ns pulses and an energy of 4.2 mJ. The measurements show good calibration linearity for both Eu and Yb with R 2 values above 0.99 for all analyzed spectral lines in liquid and solid samples. Limits of Detection (LODs) obtained were as low as 1 ppm, which are comparable to or better than those reported previously by using table top actively Q-switched systems. This study aims to develop a high sensitivity, field deployable sensor for characterizing existing and new sources of rare earth elements

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Prospects of using rare-earth hexaborides in thermoelectric single-photon detectors

The results of the numerical simulation of heat propagation processes occurring after the absorption of single photons with energies of 1 eV–1 keV in a three-layer sensor of a thermoelectric detector are analyzed. Different configurations of the sensor with a tungsten absorber, a thermoelectric layer of cerium hexaboride, and a tungsten heat sink are considered. It is shown that sensors for detecting photons of a specific spectral range with the required energy resolution and counting rate can be developed by varying the geometric sizes of the sensor layers. It is concluded that a three-layer sensor has a number of advantages in comparison with a single-layer sensor and has characteristics allowing consideration of the thermoelectric detector as a realistic alternative to superconducting single-photon detectors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An introduction to neuromorphic computing and its potential impact for unattended ground sensors

Neuromorphic computers are hardware systems that mimic the brain’s computational process phenomenology. This is in contrast to neural network accelerators, such as the Google TPU or the Intel Neural Compute Stick, which seek to accelerate the fundamental computation and data flows of neural network models used in the field of machine learning. Neuromorphic computers emulate the integrate and fire neuron dynamics of the brain to achieve a spiking communication architecture for computation. While neural networks are brain-inspired, they drastically oversimplify the brain’s computation model. Neuromorphic architectures are closer to the true computation model of the brain (albeit, still simplified). Neuromorphic computing models herald a 1000x power improvement over conventional CPU architectures. Sandia National Labs is a major contributor to the research community on neuromorphic systems by performing design analysis, evaluation, and algorithm development for neuromorphic computers. Space-based remote sensing development has been a focused target of funding for exploratory research into neuromorphic systems for their potential advantage in that program area; SNL has led some of these efforts. Recently, neuromorphic application evaluation has reached the NA-22 program area. This same exploratory research and algorithm development should penetrate the unattended ground sensor space for SNL’s mission partners and program areas. Neuromorphic computing paradigms offer a distinct advantage for the SWaP-constrained embedded systems of our diverse sponsor-driven program areas.

97 MATHEMATICS AND COMPUTING↗