Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sensor performance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Satellite Ocean Color Sensor Design Concepts and Performance Requirements

In late 1978, the National Aeronautics and Space Administration (NASA) launched the Nimbus-7 satellite with the Coastal Zone Color Scanner (CZCS) and several other sensors, all of which provided major advances in Earth remote sensing. The inspiration for the CZCS is usually attributed to an article in Science by Clarke et al. who demonstrated that large changes in open ocean spectral reflectance are correlated to chlorophyll-a concentrations. Chlorophyll-a is the primary photosynthetic pigment in green plants (marine and terrestrial) and is used in estimating primary production, i.e., the amount of carbon fixed into organic matter during photosynthesis. Thus, accurate estimates of global and regional primary production are key to studies of the earth's carbon cycle. Because the investigators used an airborne radiometer, they were able to demonstrate the increased radiance contribution of the atmosphere with altitude that would be a major issue for spaceborne measurements. Since 1978, there has been much progress in satellite ocean color remote sensing such that the technique is well established and is used for climate change science and routine operational environmental monitoring. Also, the science objectives and accompanying methodologies have expanded and evolved through a succession of global missions, e.g., the Ocean Color and Temperature Sensor (OCTS), the Seaviewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Medium Resolution Imaging Spectrometer (MERIS), and the Global Imager (GLI). With each advance in science objectives, new and more stringent requirements for sensor capabilities (e.g., spectral coverage) and performance (e.g., signal-to-noise ratio, SNR) are established. The CZCS had four bands for chlorophyll and aerosol corrections. The Ocean Color Imager (OCI) recommended for the NASA Pre-Aerosol, Cloud, and Ocean Ecosystems (PACE) mission includes 5 nanometers hyperspectral coverage from 350 to 800 nanometers with three additional discrete near infrared (NIR) and shortwave infrared (SWIR) ocean aerosol correction bands. Also, to avoid drift in sensor sensitivity from being interpreted as environmental change, climate change research requires rigorous monitoring of sensor stability. For SeaWiFS, monthly lunar imaging accurately tracked stability at an accuracy of approximately 0.1% that allowed the data to be used for climate studies [2]. It is now acknowledged by the international community that future missions and sensor designs need to accommodate lunar calibrations. An overview of ocean color remote sensing and a review of the progress made in ocean color remote sensing and the variety of research applications derived from global satellite ocean color data are provided. The purpose of this chapter is to discuss the design options for ocean color satellite radiometers, performance and testing criteria, and sensor components (optics, detectors, electronics, etc.) that must be integrated into an instrument concept. These ultimately dictate the quality and quantity of data that can be delivered as a trade against mission cost. Historically, science and sensor technology have advanced in a "leap-frog" manner in that sensor design requirements for a mission are defined many years before a sensor is launched and by the end of the mission, perhaps 15-20 years later, science applications and requirements are well beyond the capabilities of the sensor. Section 3 provides a summary of historical mission science objectives and sensor requirements. This progression is expected to continue in the future as long as sensor costs can be constrained to affordable levels and still allow the incorporation of new technologies without incurring unacceptable risk to mission success. The IOCCG Report Number 13 discusses future ocean biology mission Level-1 requirements in depth.

Ocean Color↗
NASA NTRS1992

A survey and analysis of commercially available hydrogen sensors

The performance requirements for hydrogen detection in aerospace applications often exceed those of more traditional applications. In order to ascertain the applicability of existing hydrogen sensors to aerospace applications, a survey was conducted of commercially available point-contact hydrogen sensors, and their operation was analyzed. The operation of the majority of commercial hydrogen sensors falls into four main categories: catalytic combustion, electrochemical, semiconducting oxide sensors, and thermal conductivity detectors. The physical mechanism involved in hydrogen detection for each main category is discussed in detail. From an understanding of the detection mechanism, each category of sensor is evaluated for use in a variety of space and propulsion environments. In order to meet the needs of aerospace applications, the development of point-contact hydrogen sensors that are based on concepts beyond those used in commercial sensors is necessary.

Hunter, Gary W.↗
NASA NTRS2015

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗
NASA NTRS2015

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗
NASA NTRS2016

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Diagnosis↗
DOE OSTI2021

High-Performance Piezo-Electrocatalytic Sensing of Ascorbic Acid with Nanostructured Wurtzite Zinc Oxide

We report nanostructured piezoelectric semiconductors offer unprecedented opportunities for high-performance sensing in numerous catalytic processes of biomedical, pharmaceutical, and agricultural interests, leveraging piezocatalysis that enhances the catalytic efficiency with the strain-induced piezoelectric field. Here, we design and demonstrate for the first time a cost-efficient, high-performance piezo-electrocatalytic sensor for detecting L-ascorbic acid (AA), a critical chemical for many organisms, metabolic processes, and medical treatments. We prepared ZnO nanorods and nanosheets to characterize and compare their efficacy for the piezo-electrocatalysis of AA. The electrocatalytic efficacy of AA was significantly boosted by the piezoelectric polarization induced in the nanostructured semiconducting ZnO catalysts. We elucidated the charge transfer between the strained ZnO nanostructures and AA to reveal the mechanism for the related piezo-electrocatalytic process. The low-temperature synthesis of high-quality ZnO nanostructures allows the low-cost, scalable production and integration directly into wearable electrocatalytic sensors whose performance could be boosted by otherwise wasted mechanical energy from the working environment, e.g., the human-generated mechanical signals.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

One-Step Ahead Prediction of Thermal Mixing Tee Sensors with Long Short Term Memory (LSTM) Neural Networks

High-temperature advanced reactors under development, such as sodium fast reactors (SFR) and molten salt cooled reactors (MSCR), are expected to offer lower levelized cost of energy (LCOE) compared to existing light water reactor (LWR’s). In the existing light water reactors (LWR’s), operation and maintenance (O&M) expenses constitute the largest fraction of the total operating cost. Some of the O&M costs are related maintenance of sensors which can fail due to exposure to harsh environment in a reactor. The O&M costs of Advanced Reactor (AR)’s are expected to constitute a significant fraction of the total cost as well, because of high temperature and radiation level in AR are likely to cause material fatigue and premature failure of sensors and components. The O&M costs in AR’s could be reduced through integration of advanced informatics of performance-related sensors into a digital twin designed for reactor monitoring. For example, machine learning (ML) could be employed for real-time validation and correction of performance-related sensors, and reducing the number of performance-related physical sensor units through virtual sensing. As part of the effort, we investigate real-time validation of thermal hydraulic sensors through one-step ahead forecasting of sensor values using long short-term memory (LSTM) recurrent neural networks (RNN). The sensors are installed in a flow loop containing a thermal mixing tee, which is a common experimental model to study thermal fatigue in a thermal hydraulic loop. In addition, nonlinear transients generated in a thermal mixing tee constitute a good challenge data set for training and validation of ML algorithms. Sensors in this study include thermocouples, flow meters, and optical fibers for distributed temperature sensing. In one experiment, measurement data sets were obtained for a loop was filled with water, and in another experiment, measurements were performed on a loop filled with liquid metal Galinstan. We have also conducted preliminary investigation of one-step ahead prediction of fiber optics-based distributed temperature sensing with LSTM networks. In predicting fiber-based temperature measurements, we treated each gauge pitch of the fiber as an independent sensor. Accuracy of one-step ahead forecasting was estimated by calculating root mean square error (RMSE) for the test segment of time series of each sensor. RMSE’s for temperature sensors in water loop were, for the most part, lower than for the same sensors in Galinstan loop. The RMSE’s for flow meters were similar for both loops. The RMSE’s for distributed temperature measured with the fiber optic sensor were similar to those of the point sensors. Results of this study demonstrated the capability of LSTM one-step ahead forecasting with RMSE comparable to uncertainty in sensor measurements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2004

Development and Performance of the Oxygen Sensor in the CSA-CP Aboard the International Space Station

A combustion products analyzer (CPA) was built for use on Shuttle in response to several thermodegradation incidents that had occurred during early flights. The CPA contained sensors that measured carbon monoxide, hydrogen chloride, hydrogen cyanide, and hydrogen fluoride. These marker compounds, monitored by the CPA, were selected based upon the likely products to be released in a spacecraft fire. When the Toxicology Laboratory group at Johnson Space Center (JSC) began to assess the air quality monitoring needs for the International Space Station (ISS), the CPA was the starting point for design of an instrument to monitor the atmosphere following a thermodegradation event. The final product was significantly different from the CPA and was named the compound specific analyzer-combustion products (CSA-CP). The major change from the CPA that will be the focus of this paper was the replacement of an unreliable hydrogen fluoride (HF) sensor with an oxygen sensor. A reliable HF sensor was not commercially available, but as the toxicology group reviewed the overall monitoring strategy for ISS, it appeared that a portable oxygen sensor to backup the major constituent analyzer was needed. Therefore, an oxygen sensor replaced the HF sensor in the new instrument. This paper will describe the development, deployment, and performance of the CSA-CP oxygen sensor on both Shuttle and ISS. Also, data for CSA-CP oxygen sensor accuracy at nominal and reduced pressures will be presented.

Limero, Thomas↗
DOE OSTI2025

Estimation of cutting tool wear using an elastomeric tactile sensor

Machining performance of cutting tools and part quality are affected by the geometric condition of the cutting edge, which is influenced by thermomechanical loads experienced during the process. Tool condition monitoring (TCM) systems provide insight for timely replacement of cutting tools. However, existing TCM systems are expensive and require specialized equipment or sensors, hindering widespread adoption. A novel TCM system is developed herein using an elastomeric tactile sensor. Sensor images of the cutting edge are used to quantify wear using two distinct algorithms. In the first algorithm, the unworn and worn edges are identified based on Canny edge detect. In the second, the unworn edge is identified using edge detection while the region of wear is identified using a relative intensity method. In both cases, the maximum wear width is calculated based on an experimentally determined pixel to-physical distance scale. The TCM system is first used to estimate flank wear on a solid carbide helical end mill before evaluating its robustness by employing it to estimate insert wear of an indexable helical end mill. Measurements are also performed manually using an optical microscope and a high-resolution focus variation microscope for verification. The novel technique estimates flank wear in the solid carbide tool with a high accuracy of 98%. Larger discrepancies are observed for the inserts, however, with overlapping uncertainties. In conclusion, the technique shows promise in adaptability, automation, and closed loop control of machine tools.

Machining↗
NASA NTRS1993

In-flight measurement of the National Oceanic and Atmospheric Administration (NOAA)-10 static Earth sensor error

Analysis performed in the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) measures error in the static Earth sensor onboard the National Oceanic and Atmospheric Administration (NOAA)-10 spacecraft using flight data. Errors are computed as the difference between Earth sensor pitch and roll angle telemetry and reference pitch and roll attitude histories propagated by gyros. The flight data error determination illustrates the effect on horizon sensing of systemic variation in the Earth infrared (IR) horizon radiance with latitude and season, as well as the effect of anomalies in the global IR radiance. Results of the analysis provide a comparison between static Earth sensor flight performance and that of scanning Earth sensors studied previously in the GSFC/FDD. The results also provide a baseline for evaluating various models of the static Earth sensor. Representative days from the NOAA-10 mission indicate the extent of uniformity and consistency over time of the global IR horizon. A unique aspect of the NOAA-10 analysis is the correlation of flight data errors with independent radiometric measurements of stratospheric temperature. The determination of the NOAA-10 static Earth sensor error contributes to realistic performance expectations for missions to be equipped with similar sensors.

Harvie, E.↗
NASA NTRS1995

Fabrication of Fabry-Perot Interferometer Sensors and Characterization of their Performances for Aircraft Inspection

This work provides the information for fabricating Fabry-Perot Interferometer sensors and their performances. The Fabry-Perot Interferometer sensors developed here will be used for the detection of flaws in aircraft structures. The sequel also contains discussion of the experimental setups for the Ultrasonic technique and the Fabry-Perot Interferometer.

Pendergrass, LeRuth Q.↗
DOE OSTI2020

Enhancing ZnO nanowire gas sensors using Au/Fe 2 O 3 hybrid nanoparticle decoration

Heterojunctions are an important strategy for designing high performance electrical sensor materials and related devices. Herein, a new type of metal-semiconductor hybrid nanoparticle has been successfully used to remarkably sensitize the surface of ZnO nanowires for detecting NO 2 with high responses over a broad temperature window ranging from room temperature to 600 °C. These hybrid nanoparticles are comprised of iron oxide nanowires with well dispersed single crystalline Au nanoparticles. The hybrid nanoparticle decorated ZnO nanowires have achieved a giant response, as high as 74 500 toward NO 2 gas, about 42 times that of Au decorated ZnO nanowire sensors. This dramatic enhancement may be attributed to the efficient charge transfer across the Au–Fe 2 O 3 Schottky and Fe 2 O 3 –ZnO semiconductor heterojunction interfaces. Due to the incorporation of thermally-stable Fe 2 O 3 nanoparticles as the support of Au nanoparticles, the working temperature of nanowire sensors was successfully extended to higher temperatures, with an increase of 200 °C, from 400 °C to 600 °C. Such a combination of semiconductor heterojunction and semiconductor-metal Schottky contact presents a new strategy for designing high performance electrical sensors with high sensitivity, stability, selectivity, and wide operation temperature window, which are potentially suitable for advanced energy systems such as automotive engines and power plants.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Incipient Sensor Fault Impacts on Building Performance Through HVAC Controls: A Pilot Study

Sensors are crucial input components for HVAC controls. Studies show faults are common for buidings and HVAC systems. Sensors with faults will compromise the control perfrormance regardless how advanced of the control algorithms. Majority studies assume the sensor fault to be constant the whole year. In reality, the sensor faults might evolve or develop with time, which is essentially the incipient (i.e. evolving) fault. The incipient sensor faults impacts remain a research gap. This study aims to investigate the incipient sensor fault impacts to control sequences of multi-zone VAV boxes and AHU system following the ASHRAE Guideline 36-2018: High-Performance Sequences of Operation.

Li, Yanfei↗
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 ↗
NASA NTRS1980

Focal-plane optimization for detector noise limited performance in cryogenic Fourier transform spectrometer /FTS/ sensors

A study was performed to determine the optimum focal plane configuration including optics, filters and detector-preamplifier selection. The configuration was optimized particularly with respect to minimizing the noise level, but fabrication considerations for a cryogenic environment were also taken into account. The noise terms from source, background, detector electronics and charged particle radiation were quantitatively evaluated. It appears that noise equivalent spectral radiance less than 10 to the -11th W/sq cm per sr per kayser can be achieved between 2.5 and 20 microns.

Mcguirk, M.↗
NASA NTRS1987

Large format, high resolution images sensors

The performance requirements for scientific-quality CCDs are discussed, focusing on the design of two devices, and the progress toward achieving the desired performance is discussed. These devices are intended for rear-illuminated applications and have 512 x 512 and 2048 x 2048 pixel formats. The thinned 10 to 20 micron thick Si membrane is fully supported by a unique glass ceramic substrate. Quantum efficiencies of greater than 70 percent at 700 nm and greater than 40 percent at wavelengths less than 400 nm have been measured on a test device. Dark currents as low as 6 pA/sq cm also have been measured recently.

Blouke, Morley M.↗
NASA NTRS2018

The Impact of Transition Edge Sensor Design on Achievable Performance Uniformity of Kilo-Pixel Arrays

Future astronomy missions using x-ray transition-edge sensor (TES) microcalorimeters, such as X-IFU on Athena, will require large arrays of 1000s of pixels fabricated on a single wafer. To wire out so many pixels the current array designs have pixels with different rotational orientations. Fabrication is done in multiple layers and so, dependent on method, there is potential for spatial misalignment between layers. Because of the variation of orientation of pixels, misalignment may not impact each pixel equally. This has the potential to degrade the achievable uniformity of performance across an array. How well aligned do different layers need to be? How does sensitivity to misalignment depend on choice of pixel design?

Wakeham, Nicholas↗