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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Upgraded fiber-optic sensor system for dynamic strain measurement in Spallation Neutron Source

We describe an upgraded fiber-optic sensor system and its performance in measuring the dynamic strains in a mercury target of the Spallation Neutron Source (SNS). Strains result from dynamic pressure waves in the stainless-steel mercury target induced by short (~700 ns), intense (up to 23.3 kJ), high-energy (~1 GeV) proton pulses. In the upgraded sensor system, the output of each sensor head is interrogated with a compact, all-fiber based Faraday Michelson interferometer, which generates interference signals with a steady phase shift. Strain waveforms are recovered from the phase-shifted interference signals using a high-speed digital signal processing procedure developed in our previous work. We demonstrate successful measurements of dynamic strain pulses, e.g., 400με over 190μs , on a recently installed SNS target using the upgraded sensor system. The measured strain waveforms are analyzed for more than 20 sensor locations and/or orientations, and provide information regarding the temporal structure of strain profiles and dependence of the strain magnitude on the proton powers of 200 – 1400 kW. The new interrogator also measures the radiation-induced-attenuation (RIA) in the optical fiber, enabling experimental investigations of RIA profiles induced by a 700-ns radiation pulse. The radiation effects on the strain measurement performance are discussed over a radiation dose range of up to 4×10 8 Gy and an RIA compensation method is proposed. The measurements allow insight into the response of this unique piece of equipment and can be used for validation of simulations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A Cryogenic readout integrated circuit with analog pile-up and in-Pixel ADC for high frame rate Skipper CCD-in-CMOS Sensors

The Skipper CCD-in-CMOS Parallel Read-Out Circuit V2 (SPROCKET2) is designed to enable high frame rate readout of Skipper CCD-in-CMOS image sensors. The SPROCKET2 pixel is fabricated in a 65 nm CMOS process and occupies a 60$\mu$m $\times$ 60$\mu$m footprint. SPROCKET2 is intended to be heterogeneously integrated with a pixelated Skipper CCD-in-CMOS sensor, such that one readout pixel is connected to a multiplexed array of 16 active image sensor pixels, to match their spatial geometry. Our design benefits from the Skipper CCD-in-CMOS sensor's non-destructive readout capability to achieve exceptionally low noise through multi-sampling and averaging while optimizing for total power consumption. The pixel readout utilizes correlated double sampling to minimize 1/f noise and includes "pile-up" of ten successive samples in the analog domain before digitizing at a rate of 66.7 ksps. Measurement results of in-pixel serial SAR ADC show DNL and INL of ~0. 44 LSB and 0.58 LBS respectively. A large area array of 20,000 SPROCKET2 ADC pixels (multiplexed 1:16 to 320,000 sensor pixels) is currently under test. By reading out data over a 10 Gbps optical link, this pixel design enables a frame rate of $\sim$ 4 kfps for large sensing areas with minimal sensing deadtime. In the highest gain mode, the pixelated ADC has an input-referred resolution of 10$\mu$V with a simulated power consumption of 50$\mu$W. The pixel operates with constant current draw to minimize power-rail crosstalk.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Full Scale 3D Computational Model of the Industrial -Scale Coal Fired Boiler Performance for Temperature Sensor Installation Guidance

Abstract Nearly 30% of the electricity is generated by using coal as the primary fuel in the US. One of the major concerns in coal-fired power plants is the failure of boiler tubes that leads to unscheduled maintenance and has a huge economical and societal impact. High temperature flue gas along with ash pass over the boiler tubes, which over time leads to tube failure. Therefore, developing temperature sensors for harsh environments and install them for temperature sensing and boiler tube lifetime prediction is an urgent need. On the side of sensor development, the location of the sensor installation is important for stable sensing performance and easy calibration. In this study, computational fluid dynamics and heat transfer modeling are adopted to establish a full-scale 3-dimensional model of a coal-fired boiler to investigate the flue gas temperature distribution within the boiler and identify the proper locations for sensor installation. We proposed three criteria to select the temperature sensor installation location: (1) select the boiler tube panel away from the sidewalls, (2) select the boiler tube section closer to the top wall of the boiler; and (3) select the boiler tube on the back of the boiler panel (not directly facing the flue gas flow). In these regions, the flue gas temperature is stable, providing an ideal environment for stable temperature sensing and calibration.

Gupta, Tanuj↗
DOE OSTI2021

A stretchable and strain-unperturbed pressure sensor for motion interference–free tactile monitoring on skins

A stretchable pressure sensor is a necessary tool for perceiving physical interactions that take place on soft/deformable skins present in human bodies, prosthetic limbs, or soft robots. However, all existing types of stretchable pressure sensors have an inherent limitation, which is the interference of stretching with pressure sensing accuracy. Here, we present a design for a highly stretchable and highly sensitive pressure sensor that can provide unaltered sensing performance under stretching, which is realized through the synergistic creations of an ionic capacitive sensing mechanism and a mechanically hierarchical microstructure. Via this optimized structure, our sensor exhibits 98% strain insensitivity up to 50% strain and a low pressure detection limit of 0.2 Pa. With the capability to provide all the desired characteristics for quantitative pressure sensing on a deformable surface, this sensor has been used to realize the accurate sensation of physical interactions on human or soft robotic skin.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.

Siddiquee, Masudur R.↗
DOE OSTI2018

In Vitro Sugar Interference Testing With Amperometric Glucose Oxidase Sensors

Background: Electrochemical enzymatic glucose sensors are intended to measure blood or interstitial fluid glucose concentrations. One class of these glucose sensors are continuous glucose monitors (CGMs), indicated for tracking and trending of glucose concentrations in interstitial fluid and as an adjunct to blood glucose testing. Currently approved CGMs employ a glucose oxidase (GOx) electrochemical detection scheme. Potential interfering agents can impact the accuracy of results obtained by glucose sensors, including CGMs. Methods: Seven sugars, seven sugar alcohols, and three artificial sweeteners were in vitro screened for interference with amperometric glucose oxidase (GOx) sensors at concentrations greater than physiologic concentrations. Galactose was investigated further at physiologically relevant concentrations using a custom amperometric system. Furthermore, glucose and galactose calibration experiments were conducted to facilitate multiple enzyme kinetic analysis approaches (Michaelis-Menten and Hill equation) to understand the potential source and mechanism of interference from galactose. Results: Under in vitro testing, except for galactose, xylose and mannose, all screened compounds exhibited interference bias, expressed in mean absolute relative difference (MARD), of ⩽ 20% even at concentrations significantly higher than normal physiologic concentrations. Galactose exhibited, CGM-dependent, MARD of 47-72% and was subjected to further testing. The highest recorded mean relative difference (MRD) was 6.9 ± 1.3% when testing physiologically relevant galactose concentrations (0.1-10 mg/dL). Enzyme kinetic analysis provided calculations of maximum reaction rates ([Formula: see text]), apparent Michaelis constants ([Formula: see text]), and Hill equation h parameters for glucose and galactose substrates for the enzymes in the CGMs. Conclusion: Under the conditions of in vitro screening, 14 of the 17 compounds did not exhibit measuarable interference. Galactose exhibited the highest interference during screening, but did not substantially interfere with CGMs under the conditions of in vitro testing at physiologically relevant concentrations. Enzyme kinetic analysis conducted with galactose supported the notion that (1) the reactivity of GOx enzyme toward nonglucose sugars and (2) the presence of enzymatic impurities (such as galactose oxidase) are two potential sources for sugar interference with GOx glucose sensors, and thus, should be considered during device development.

Boehm, Ryan↗
DOE OSTI2019

R&D for new silicon pixel sensors for the High Luminosity phase of the CMS experiment at LHC

The High Luminosity upgrade of the CERN LHC collider (HL-LHC) demands a new high-radiation–tolerant solid-state pixel sensor capable of surviving fluencies up to a few 10$^{16} n_{eq}/\mathrm{cm}^2$ at ~ 3 cm from the interaction point. To this extent the INFN ATLAS-CMS joint research activity, in collaboration with Fondazione Bruno Kessler (FBK), is aiming at the development of thin n -in- p –type pixel sensors for the HL-LHC. The R&D covers both planar and single-sided 3D columnar pixel devices made with the Si-Si Direct Wafer Bonding technique, which allows for the production of sensors with 100 μm and 130 μm active thickness for planar sensors, and 130 μm for 3D sensors, the thinnest ones ever produced so far. The first prototypes of hybrid modules, bump-bonded to the present CMS readout chip, have been tested on beam. The first results on their performance before and after irradiation are presented

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Chem/bio wearable sensors: current and future direction

Abstract Examples of existing and emerging wearable sensors for chemical and biological threat agents are reviewed and essential enabling developments identified. Wearables are described as inward looking sensors (self-monitoring) and outward looking sensors (environmental sensors). The future potential for wearable sensors, expected capabilities, and key challenges are summarized.

wearables, Chemical Weapons Agent Detection, Bioth↗
DOE OSTI2023

Yakima River Basin Temporal Study: Sensor and Sample Data from Wenas Creek following the Evans Canyon Fire in Washington, USA

The Evans Canyon Fire occurred in Washington in August 2020 and burned 76,000 acres of the semi-arid shrub-steppe landscape at low to moderate severities. This fire burned across the Wenas Creek watershed, allowing for a sampling design that included a portion of the stream within the burned area and a reference site upstream of the burn. Monthly data was collected at an unburned (W10) and burned (W20) site from November 2020 to August 2022 for in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata. This dataset is comprised of one folder with field photos and one main data folder containing (1) sensor and sample field protocols; (2) file-level metadata (flmd); (3) data dictionary (dd); (4) international geo-sample number (IGSN) mapping file; (5) field metadata; (6) readme; (7) methods codes; (8) dissolved organic carbon (DOC; measured as non-purgeable organic carbon; NPOC); (9) total nitrogen (TN); (10) total suspended solids (TSS); (11) sensor data (specific conductance, pH, total dissolved solids, temperature, pressure, dissolved oxygen, and turbidity) averages; and (12) sensor installation methods. All files are .csv, .jpg, .jpeg, or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Biases of the MET Temperature and Relative Humidity Sensor (HMP45) Report

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Data Quality (DQ) Office was alerted to a potential bias in the surface meteorological instrumentation (MET) temperature when compared with a nearby Mesonet station. This led to an investigation into this problem that was expanded to include many of the other extended facilities (EF) and both the temperature and relative humidity (RH) variables. For this study, the Mesonet was used as the standard reference due to results that showed an increased accuracy in high-humidity environments along with the fact that the Mesonet had previous documented a problem with the HMP45C sensors. Some differences between the sites were taken into account during the analysis: 1. ARM MET sensors were upgraded from an HMP35 to an HMP45 throughout 2007 2. Mesonet switched to aspirated shields in 2009 – To mitigate the differences between aspirated and non-aspirated measurements, data were only analyzed when the wind speed was higher than 3 m/s. This reduced the uncertainty for the non-aspirated measurements from 1.51 ºC to 0.4 ºC. 3. ARM MET is mounted 0.5m higher than the Mesonet station (2.0m versus 1.5m) – This is assumed to have a negligible effect on the differences. 4. Sites were not co-located – For some locations, the distances between sites were as much as 45 km. As part of the investigation into the differences, the Mesonet had reported that the HMP45 sensors had a low-temperature bias in high-humidity environments. This was verified at two different sites where the ARM measurements were compared with the Mesonet measurements. The Mesonet provided redundant temperature measurements from two different sensors at each site. These measurements compared fairly well, while the ARM sensor showed a bias overnight when the humidities were higher. After reviewing the yearly average differences in the data and analyzing the RH data during fog events when we assume it should be 100%, we determined that a majority of the sites have a bias in the RH compared to the Mesonet sites, but that only a few sites show a bias in the temperature measurements that are outside the range of instrument uncertainties. We note that there can be a lot of variability across some of the distances between the MET and Mesonet sites and these biases reported herein should not be used as offsets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Hyperspectral Sensors Final Report CRADA No. TC02173.0

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Science Applications International Corporation (SAIC), National Security Space Operations/SRBU, to develop longwave infrared (LWIR) hyperspectral imaging (HSI) sensors for airborne and potentially ground and space, platforms. LLNL has designed and developed LWIR HSI sensors since 1995. The current generation of these sensors has applications to users within the U.S. Department of Defense and the Intelligence Community. User needs are for multiple copies provided by commercial industry. To gain the most benefit from the U.S. Government’s prior investments in LWIR HSI sensors developed at LLNL, transfer of technology and know-how from LLNL HSI experts to commercial industry was needed. The overarching purpose of the CRADA project was to facilitate the transfer of the necessary technology from LLNL to SAIC thereby allowing the U.S. Government to procure LWIR HSI sensors from this company.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Tunable Impedance Spectroscopy Sensors via Selective Nanoporous Materials.

Impedance spectroscopy was leveraged to directly detect the sorption of I 2 by selective adsorption into nanoporous metal organic frameworks (MOF). Films of three different types of MOF frameworks, respectively, were drop cast onto platinum interdigitated electrodes, dried, and exposed to gaseous I 2 at 25, 40, or 70 C. The MOF frameworks varied in topology from small pores (equivalent to I 2 diameter) to large pore frameworks. The combination of the chemistry of the framework and pore size dictated quantity and kinetics of I 2 adsorption. Air, argon, methanol, and water were found to produce minimal changes in ZIF-8 impedance. Independent of MOF framework characteristics, all resultant sensors showed high response to I 2 in air. As an example of sensor output, I 2 was readily detected at 25 C in air within 720 s of exposure, using an un-optimized sensor geometry with a small pored MOF. Further optimization of sensor geometry, decreasing MOF film thicknesses and maximizing sensor capacitance, will enable faster detection of trace I 2 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Embedded Sensors and Controls to Improve Component Performance and Reliability - Final Report

Oak Ridge National Laboratory has researched embedded instrumentation and controls (I&C) for extreme environments under the Department of Energy, Office of Nuclear Energy's Nuclear Energy Enabling Technology program. Advanced sensors and controls have the potential to dramatically increase the performance and efficiency of nuclear reactor components, however, the extreme environments of exiting and advanced reactor designs limit the options for sensors, actuators, and control designs. To address two of the extreme environment challenges to embedded I&C, the focus of this research is to fill technology gaps needed for electromagnetic systems that can operate at temperatures greater than 700 C in corrosive environments. A magnetically suspended, canned-rotor pump was chosen for the embedded I&C development platform because it is a system with a practical need in industry and because the sensors, actuators, and embedded I&C technologies needed to successfully build this platform will be widely applicable to any high-temperature components that utilize electromagnetic interactions. This design also eliminates the need for pump seals and mechanical bearings which are the main sources of pump failures and maintenance costs. During the project a conceptual design for the high-temperature magnetically suspended pump was developed and analyzed for manufacturability and reliability. Specifications for the materials, control system, sensors, mechanical performance, high-temperature wiring, and electromagnetic properties were developed for the conceptual design. The canned rotor design of the high-temperature pump presents unique fluid force characteristics arising from the thin fluid channel between the rotor and stator. A model of the fluid forces was developed and the impact of these forces on the stability and performance of magnetic bearing controllers was studied. Then a room temperature bench-scale magnetic testbed was designed and fabricated for testing the performance of sensors and electromagnetic actuators, modern control design techniques, closed-loop system identification, state estimation, and model uncertainty. Finally, a loop-scale testbed with submerged magnetic bearings was designed and fabricated. This testbed will be used to analyze the stability and performance of control system designs in response to the nonlinear and cross-coupling fluid effects between the shaft axes of motion, rotordynamics, gyroscopic effects, and impeller disturbances.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The Contact Stress Sensor _ Proposal to the FY2020 Technology Tech Mat Grants Program

The technology to be advanced is a very small and thin Contact Stress Sensor (CSS) that measures the contact stress between two contacting surfaces. It will be used to monitor the internal condition of a weapon in the stockpile over periods of decades. Monitoring the load path of a complex weapon assembly offers an important verification of the weapon’s mechanical state in both quasi-static or dynamic environments. Concurrently, the sensor can be used to measure temperature. This is useful for sensor calibration while installed in a system, as well as thermal monitoring in regions of the system that are difficult to access. Thus, the CSS is one way to monitor the internal “health” of a weapon. A sensor is shown below with each sensor being less then 2mm in width and 125 microns in thickness.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Developing Fugitive Emissions Sensor Networks

This document summarizes research performed under the Laboratory Directed Research and Development (LDRD) project titled Developing Fugitive Emissions Sensor Networks: New Optimization Algorithms for Monitoring, Measurement and Verification. The purpose of this project is to develop methods and software to enhance detection programs through optimal design of the sensor network. This project includes both software development and field work. While this project is focused on methane emissions, the sensor placement optimization framework can be applied to a wide range of applications, including the placement of water quality sensors, surveillance cameras, fire and chemical detectors. This research has the potential to improve national security by improving the way sensors are deployed in the field.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2021

Testing of Instrumentation and Control Sensors and Cables for Small Modular Reactors

As advanced reactor concepts like small modular reactors (SMRs) progress towards design maturity and commercial deployment, it is important to assess their instrumentation and control (I&C) system sensors and cables to assure their safe, reliable, and efficient operation throughout their service lifetimes. The I&C system of any nuclear power plant (NPP) is the central nervous system of the plant and is made up of field devices such as sensors which are connected via cables to analog and/or digital systems. These systems are responsible for control and/or protection of the plant. The performance of I&C sensors and cables is dependent on several factors, including plant operating conditions. In particular, the plant operation can affect the static (accuracy) and dynamic (response) performance of the sensor, whereas the surrounding ambient environment can impact the remaining useful life of the cables, connectors, and other associated components within I&C sensor circuits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Evaluation of Low Cost Infrasound Sensor Packages

Sandia National Laboratories has tested and evaluated the performance of the following five models of low-cost infrasound sensors and sensor packages: Camas microphone, Gem Infrasound Logger, InfraBSU sensor, Raspberry Boom, and the Samsung S10 smartphone utilizing the Redvox app. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, self-noise, dynamic range, response, passband, linearity, sensitivity variation due to changes in static pressure and temperature, and sensitivity to vertical acceleration. The infrasound monitoring community has leveraged such sensors and integrated packages in novel ways; better understanding the performance of these units serves the geophysical monitoring community.

42 ENGINEERING↗