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At least 811 records · Page 45

All sources NASA NTRS DOE OSTI

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 OSTI2014

Provenance In Sensor Data Management: A Cohesive, Independent Solution

In today's information-driven workplaces, data is constantly undergoing transformations and being moved around. The typical business-as-usual approach is to use email attachments, shared network locations, databases, and now, the cloud. More often than not, there are multiple versions of the data sitting in different locations and users of this data are confounded by the lack of metadata describing its provenance, or in other words, its lineage. Our project is aimed to solve this issue in the context of sensor data. The Oak Ridge National Laboratory's Building Technologies Research and Integration Center has reconfigurable commercial buildings deployed on the Flexible Research Platforms (FRPs). These FRPs are instrumented with a large number of sensors which measure a number of variables such as HVAC efficiency, relative humidity, and temperature gradients across doors, windows, and walls. Sub-minute resolution data from hundreds of channels is acquired. This sensor data, traditionally, was saved to a shared network location which was accessible to a number of scientists for performing complicated simulation and analysis tasks. The sensor data also participates in elaborate quality assurance exercises as a result of inherent faults. Sometimes, faults are induced to observe building behavior. It became apparent that proper scientific controls required not just managing the data acquisition and delivery, but to also manage the metadata associated with temporal subsets of the sensor data. We built a system named ProvDMS, or Provenance Data Management System for the FRPs, which would both allow researchers to retrieve data of interest as well as trace data lineage. This provides researchers a one-stop shop for comprehensive views of various data transformation allowing researchers to effectively trace their data to its source so that experiments, and derivations of experiments, may be reused and reproduced without much overhead of the repeatability of experiments that use it. Using these traces, researchers can determine exactly what happens to data as it moves through its life cycle.

Hensley, Zachary P↗

DOE OSTI2013

Crack Propagation Analysis Using Acoustic Emission Sensors for Structural Health Monitoring Systems

Aerospace systems are expected to remain in service well beyond their designed life. Consequently, maintenance is an important issue. A novel method of implementing artificial neural networks and acoustic emission sensors to form a structural health monitoring (SHM) system for aerospace inspection routines was the focus of this research. Simple structural elements, consisting of flat aluminum plates of AL 2024‐T3, were subjected to increasing static tensile loading. As the loading increased, designed cracks extended in length, releasing strain waves in the process. Strain wave signals, measured by acoustic emission sensors, were further analyzed in post‐processing by artificial neural networks (ANN). Several experiments were performed to determine the severity and location of the crack extensions in the structure. ANNs were trained on a portion of the data acquired by the sensors and the ANNs were then validated with the remaining data. The combination of a system of acoustic emission sensors, and an ANN could determine crack extension accurately. The difference between predicted and actual crack extensions was determined to be between 0.004 in. and 0.015 in. with 95% confidence. These ANNs, coupled with acoustic emission sensors, showed promise for the creation of an SHM system for aerospace systems.

42 ENGINEERING↗

DOE OSTI2016

Sensor Fish Communicator

The Sensor Fish collects information that can be used to evaluate conditions encountered by juvenile salmonids and other fish as they pass through hydroelectric dams on their way to the ocean. Sensor Fish are deployed in turbines, spillways, and sluiceways and measure changes in pressure, angular rate of change, and linear acceleration during passage. The software is need to make Sensor Fish fully functional and easy to use. Sensor Fish Communicator (SFC) links to Sensor Fish, allowing users to control data collection settings and download data. It may also be used to convert native raw data (.raw2) files into Comma Separated Variable (.csv) files and plot the results. The multiple capabilities of the SFC allow hardware communication, data conversion, and data plotting with one application.

Source record↗

DOE OSTI2016

Image Processing Occupancy Sensor

The Image Processing Occupancy Sensor, or IPOS, is a novel sensor technology developed at the National Renewable Energy Laboratory (NREL). The sensor is based on low-cost embedded microprocessors widely used by the smartphone industry and leverages mature open-source computer vision software libraries. Compared to traditional passive infrared and ultrasonic-based motion sensors currently used for occupancy detection, IPOS has shown the potential for improved accuracy and a richer set of feedback signals for occupant-optimized lighting, daylighting, temperature setback, ventilation control, and other occupancy and location-based uses. Unlike traditional passive infrared (PIR) or ultrasonic occupancy sensors, which infer occupancy based only on motion, IPOS uses digital image-based analysis to detect and classify various aspects of occupancy, including the presence of occupants regardless of motion, their number, location, and activity levels of occupants, as well as the illuminance properties of the monitored space. The IPOS software leverages the recent availability of low-cost embedded computing platforms, computer vision software libraries, and camera elements.

Source record↗

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 OSTI2016

A light-emitting diode- (LED-) based absorption sensor for simultaneous detection of carbon monoxide and carbon dioxide

Here, a sensor was developed for simultaneous measurements of carbon monoxide (CO) and carbon dioxide (CO 2 ) fluctuations in internal combustion engine exhaust gases. This sensor utilizes low-cost and compact light-emitting diodes (LEDs) that emit in the 3–5 µm wavelength range. An affordable, fast response sensor that can measure these gases has a broad application that can lead to more efficient, fuel-flexible engines and regulation of harmful emissions. Light emission from LEDs is spectrally broader and more spatially divergent when compared to that of lasers, which presented many design challenges. Optical design studies addressed some of the non-ideal characteristics of the LED emissions. Measurements of CO and CO 2 were conducted using their fundamental absorption bands centered at 4.7 µm and 4.3 µm, respectively, while a 3.6 µm reference LED was used to account for scattering losses (due to soot, window deposits, etc.) common to the three measurement LEDs. Instrument validation and calibration was performed using a laboratory flow cell and bottled-gas mixtures. The sensor was able to detect CO 2 and CO concentration changes as small as 30 ppm and 400 ppm, respectively. Because of the many control and monitor species with infra-red absorption features, which can be measured using the strategy described, this work demonstrates proof of concept for a wider range of fast (250 Hz) and low-cost sensors for gas measurement and process monitoring.

47 OTHER INSTRUMENTATION↗

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 OSTI2013

Sensor Characteristics Reference Guide

The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systems through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information.

Cree, Johnathan V.↗

DOE OSTI2014

Development of a 1 x N Fiber Optic Sensor Array for Carbon Sequestration Site Monitoring

A fiber sensor array for sub-surface CO 2 concentrations measurements was developed for monitoring geologic carbon sequestration sites. The fiber sensor array uses a single temperature tunable distributed feedback (DFB) laser operating with a nominal wavelength of 2.004 μm. Light from this DFB laser is direct to one of the 4 probes via an in-line 1 x 4 fiber optic switch. Each of the 4 probes are buried and allow the sub-surface CO 2 to enter the probe through Millipore filters that allow the soil gas to enter the probe but keeps out the soil and water. Light from the DFB laser interacts with the CO 2 before it is directed back through the in-line fiber optic switch. The DFB laser is tuned across two CO 2 absorption features where a transmission measurement is made allowing the CO 2 concentration to be retrieved. The fiber optic switch then directs the light to the next probe where this process is repeated allowing sub-surface CO 2 concentration measurements at each of the probes to be made as a function of time. The fiber sensor array was deployed for fifty-eight days beginning June 19, 2012 at the Zero Emission Research Technology (ZERT) field site where sub-surface CO 2 concentrations were monitored. Background measurements indicate the fiber sensor array can monitor background levels as low as 1,000 parts per million (ppm). A thirty four day sub-surface release of 0.15 tones CO 2 /day began on July 10, 2012. The elevated subsurface CO 2 concentration was easily detected by each of the four probes with values ranging to over 60,000 ppm, a factor of greater than 6 higher than background measurements. The fiber sensor array was also deploy at the Big Sky Carbon Sequestration Partnership (BSCSP) site in north-central Montana between July 9th and August 7th, 2013 where background measurements were made in a remote sequestration site with minimal infrastructure. The project provided opportunities for two graduate students to participate in research directly related to geologic carbon sequestration. Furthermore, commercialization of the technology developed is being pursued with five different companies via the Department of energy SBIR/STTR program

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

Micro-Structured Sapphire Fiber Sensors for Simultaneous Measurements of High-T and Dynamic Gas Pressure in Harsh Environments

This is the final report for the program “Micro-Structured Sapphire Fiber Sensors for Simultaneous Measurements of High Temperature and Dynamic Gas Pressure in Harsh Environments”, funded by NETL, and performed by Missouri University of Science and Technology, Clemson University and University of Cincinnati from October 1, 2009 to September 30, 2014. Securing a sustainable energy economy by developing affordable and clean energy from coal and other fossil fuels is a central element to the mission of The U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL). To further this mission, NETL funds research and development of novel sensor technologies that can function under the extreme operating conditions often found in advanced power systems. The main objective of this research program is to conduct fundamental and applied research that will lead to successful development and demonstration of robust, multiplexed, microstructured silica and single-crystal sapphire fiber sensors to be deployed into the hot zones of advanced power and fuel systems for simultaneous measurements of high temperature and gas pressure. The specific objectives of this research program include: 1) Design, fabrication and demonstration of multiplexed, robust silica and sapphire fiber temperature and dynamic gas pressure sensors that can survive and maintain fully operational in high-temperature harsh environments. 2) Development and demonstration of a novel method to demodulate the multiplexed interferograms for simultaneous measurements of temperature and gas pressure in harsh environments. 3) Development and demonstration of novel sapphire fiber cladding and low numerical aperture (NA) excitation techniques to assure high signal integrity and sensor robustness.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2015

Pulse Tube Interference in Cryogenic Sensor Resonant Circuits (Final Paper)

Transition edge sensors (TES) are extremely sensitive superconducting sensors, operating at 100 mK, which can be used to detect X-rays and Cosmic Microwave Background. The goal of our project is to design the electronics to read out an array of 10000 of these sensors by using microwave signals. However, we noticed the pulse tube used to maintain cryogenic temperatures caused interference in our readout. To determine the cause of the signal distortions, we used a detector with a 370 MHz sampling rate to collect and analyze sensor data. Although this data provided little information towards the nature of the noise, it was determined through a maintenance procedure than the 0.3 mm stainless steel wires were being vibrated due to acoustic waves, which distorted the signal. Replacing this wire appeared to cease the interference from the sensor data.

42 ENGINEERING↗

DOE OSTI2015

Pulse Tube Interference in Cryogenic Sensors - Oral Presentation [Slides]

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Multifunctional Integrated Sensors (MFISES)

Many emerging IoT applications require sensing of multiple physical and environmental parameters for: completeness of information, measurement validation, unexpected demands, improved performance. For example, a typical outdoor weather station measures temperature, humidity, barometric pressure, light intensity, rainfall, wind speed and direction. Existing sensor technologies do not directly address the demand for cost, size, and power reduction in multi-paramater sensing applications. Industry sensor manufacturers have developed integrated sensor systems for inertial measurements that combine accelerometers, gyroscopes, and magnetometers, but do not address environmental sensing functionality. In existing research literature, a technology gap exists between the functionality of MEMS sensors and the real world applications of the sensors systems.

42 ENGINEERING↗

DOE OSTI2015

Commercializing Wide Range Sensor

The purpose of the CRADA was to allow Sandia National Laboratories (Sandia) to assist H2Scan Corporation, in the transfer of the Wide Range Hydrogen Sensor (WRS) to commercial applications. The overall goal was to develop a very stable, low-cost hydrogen (H 2 ) sensor that functioned in the complex environments of H 2 production facilities, petrochemical plants, power plants, and in the H 2 transportation economy. This project has resulted in improved H 2 sensor performance with greater resistance to the contaminants found in these environments than possible previously. Benefits include: improved H2 sensor performance, new markets and improved competitive position for H2scan, greater chemical sensor expertise and a more robust chemical testing capability at Sandia that can be applied to DOE’s nuclear weapons mission, and job creation and economic development for the public.

08 HYDROGEN↗