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At least 1,225 records · Page 68

Synergistic Integration of Chemo-Resistive and SERS Sensing for Label-Free Multiplex Gas Detection

Practical sensing applications such as real-time safety alerts and clinical diagnoses require sensor devices to differentiate between various target molecules with high sensitivity and selectivity, yet conventional devices such as oxide-based chemo-resistive sensors and metal-based surface-enhanced Raman spectroscopy (SERS) sensors usually do not satisfy such requirements. In this report a label-free, chemo-resistive/SERS multimodal sensor based on a systematically assembled 3D cross-point multifunctional nanoarchitecture (3D-CMA), which has unusually strong enhancements in both “chemo-resistive” and “SERS” sensing characteristics is introduced. 3D-CMA combines several sensing mechanisms and sensing elements via 3D integration of semiconducting SnO 2 nanowire frameworks and dual-functioning Au metallic nanoparticles. It is shown that the multimodal sensor can successfully estimate mixed-gas compositions selectively and quantitatively at the sub-100 ppm level, even for mixtures of gaseous aromatic compounds (nitrobenzene and toluene) with very similar molecular structures. This is enabled by combined chemo-resistive and SERS multimodal sensing providing complementary information.

36 MATERIALS SCIENCE↗

Additively Manufactured IN718 Components with Wirelessly Powered and Interrogated Embedded Sensing

A methodology is described for embedding commercial-off-the-shelf sensors together with wireless communication and power circuit elements using direct laser metal sintered additively manufactured components. Physics based models of the additive manufacturing processes and sensor/wireless level performance models guided the design and embedment processes. A combination of cold spray deposition and laser engineered net shaping was used to fashion the transmitter/receiving elements and embed the sensors, thereby providing environmental protection and component robustness/survivability for harsh conditions. By design, this complement of analog and digital sensors were wirelessly powered and interrogated using a health and utilization monitoring system; enabling real-time, in situ prognostics and diagnostics.

embedded sensing↗

Sensor Integrated Pilot Mask for On-Board, Real-Time, Monitoring of Pilot Breathing Gas

A pilot's job is unique in the demands it places on the human body, and many conditions can seriously affect pilot performance, threatening mission completion and pilot safety. The gas in a flight mask contains key indicators of the pilot's physiological state, including oxygen inhaled and carbon dioxide exhaled, which can signal hypoxia, hyperoxia, hypocapnia, and hypercapnia. A fiber optic-based sensor system, integrated into the pilot mask, has been developed to monitor in real time, during flight, the pilot breathing gas levels. Monitoring the partial pressure of oxygen and carbon dioxide in the pilot mask supports real-time closed loop control of the on-board oxygen generation system, based on a direct reading of what the pilot is actually breathing. The pilot Mask Sensor (MASES) system incorporates luminescence sensors for pO2, pCO2, relative humidity, pressure, and temperature in a compact probe in the pilot mask; it is based on sensor technology developed for gas monitoring in space suit systems, in work supported by NASA under the Small Business Innovation Research program. Relevant requirements for the MASES system include sensor operation while wet, operation at reduced pressure, ability to withstand rapid decompression, operation in a pure oxygen atmosphere, low power consumption, a compact readout unit, and flexible miniature sensors; many of these requirements are shared with gas monitors in space suits. Data are presented from tests conducted with human subjects in an altitude chamber and in a centrifuge.

Delgado Alonso, Jesus↗

Attitude and vibration control of a large flexible space-based antenna

The problem of control systems synthesis is considered for controlling the rigid body attitude and elastic motion of a large deployable space based antenna. Two methods for control systems synthesis are considered. The first method utilizes the stability and robustness properties of the controller consisting of torque actuators and collocated attitude and rate sensors. The second method is based on the linear quadratic Gaussian (LQG) control theory. A combination of the two methods, which results in a two level hierarchical control system, is also briefly discussed. The performance of the controllers is analyzed by computing the variances of pointing errors, feed misalignment errors and surface contour errors in the presence of sensor and actuator noise.

Joshi, S. M.↗

Attitude and vibration control of a large flexible space-based antenna

Control systems synthesis is considered for controlling the rigid body attitude and elastic motion of a large deployable space-based antenna. Two methods for control systems synthesis are considered. The first method utilizes the stability and robustness properties of the controller consisting of torque actuators and collocated attitude and rate sensors. The second method is based on the linear-quadratic-Gaussian control theory. A combination of the two methods, which results in a two level hierarchical control system, is also briefly discussed. The performance of the controllers is analyzed by computing the variances of pointing errors, feed misalignment errors and surface contour errors in the presence of sensor and actuator noise.

Joshi, S. M.↗

Air Quality Forecasting at Sub-City Scale by Combining Models, Satellites, and Surface Measures

While there are a variety of sources for air quality information, no one source simultaneously allows for high accuracy, low bias, fine spatial resolution, wide spatial coverage, high temporal frequency, and the capability for near-term forecasting of air quality. Global models, like the NASA’s Goddard Earth Observing System -Composition Forecasting (GEOS-CF) model, provide global coverage and forecasting capabilities, but operate at relatively coarse spatial resolution and require ground-truthing with in-situ data. Polar-orbiting satellite data products, like those of the ESA TROPOspheric Monitoring Instrument (TROPOMI), provide higher-spatial-resolution remote sensing of atmospheric composition, but are limited by cloud cover and overpass times and report column-integrated quantities. Surface measurements, both from regulatory-grade monitors and low-cost networks, measure “nose-level” air quality, but may not represent concentration variability across large spatial domains, and (in the case of low-cost sensors) are subject to interference and biases. There exists a great potential to combine these diverse data sources together, using the strengths of some to offset the weaknesses of others to build a more comprehensive picture of air quality. This presentation will summarize results from ongoing efforts to produce such a combined forecast, with application case studies for surface-level Nitrogen Dioxide forecasting in several major US cities. Furthermore, we will examine the relative impacts and benefits of different data sources on the forecasting accuracy at different spatial and temporal scales. Finally, we will examine the potential for integrating low-cost sensors into such a system, both in terms of using these integrated air quality estimates as a baseline from which to calibrate networks of low-cost sensors in the field, and in terms of using dense networks of low-cost sensors to refine the spatial resolution of integrated air quality forecasts.

Air Quality↗

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: 1. an EOF Approach to the Spatial-Temporal Variability of Aerosol Optical Depth Using Multiple Remote Sensing Data Sets

Many remote sensing techniques and passive sensors have been developed to measure global aerosol properties. While instantaneous comparisons between pixel-level data often reveal quantitative differences, here we use Empirical Orthogonal Function (EOF) analysis, also known as Principal Component Analysis, to demonstrate that satellite-derived aerosol optical depth (AOD) data sets exhibit essentially the same spatial and temporal variability and are thus suitable for large-scale studies. Analysis results show that the first four EOF modes of AOD account for the bulk of the variance and agree well across the four data sets used in this study (i.e., Aqua MODIS, Terra MODIS, MISR, and SeaWiFS). Only SeaWiFS data over land have slightly different EOF patterns. Globally, the first two EOF modes show annual cycles and are mainly related to Sahara dust in the northern hemisphere and biomass burning in the southern hemisphere, respectively. After removing the mean seasonal cycle from the data, major aerosol sources, including biomass burning in South America and dust in West Africa, are revealed in the dominant modes due to the different interannual variability of aerosol emissions. The enhancement of biomass burning associated with El Niño over Indonesia and central South America is also captured with the EOF technique.

variability↗

Spatial Grid-Based Object Localization from A Single Passive Sensor: A Deep Learning-Integrated Approach

Ongoing efforts at NASA’s Langley Research Center have produced a single passive sensor system for detecting ground objects and pinpointing their real-world location to a desired level of precision. The Langley center serves as a test range for unmanned aerial systems (UAS) and real-time knowledge about the location of people on campus is needed to inform least-risk UAS flight operations. The proposed system provides this knowledge through a camera combined with a convolutional neural network and an algorithm that projects an imaginary grid of square cells from the ground plane onto the perspective view of the camera. The position of detected objects on the camera’s projected grid determines their location in the real-world. The imaginary grid is easily mapped to a universal coordinate system, such as longitude and latitude, to provide both relative and absolute positional information of the detected objects. This simple system is shown to be accurate and effective, with decisive advantages over alternative multi-sensor and active sensor approaches. Extensions to the system are described to allow adaptation to a variety of other use cases.

object localization↗

Measurement of free chlorine levels in water using potentiometric responses of biofilms and applications for monitoring and managing the quality of potable water

We report residual free chlorine is not monitored continuously at scale in drinking water distribution systems because existing real-time sensor technologies require frequent maintenance, cleaning, and calibration, which makes these products too costly to be used throughout a distribution system. As a result, current measurement approaches require manual sampling, which is not feasible for the consistent monitoring of free chlorine because chlorine concentrations vary significantly throughout pipeline distribution and over time and space. This research presents an alternative and cost-effective method of predicting free chlorine levels in drinking water using graphite electrodes coated with naturally grown microbial biofilms. This Microbial Potentiometric Sensor (MPS) array was installed in a Continuously Mixed Batch Reactor (CMBR), and drinking water containing variable free chlorine concentrations. The chlorine concentrations were introduced in a controlled manner, and the MPS signals were monitored over time. MPS signals were measured from the change in Open Circuit Potential (OCP) across the MPS array in real-time. An empirically derived relationship between the normalized change in OCP and free chlorine was established by fitting individual and average MPS data to a decaying exponential growth function in order to predict free chlorine levels. The results show that free chlorine can be predicted with reasonable accuracy, with model validation showing an average absolute error of ±0.09 ppm below 1.1 ppm and ±0.30 ppm between 1.1 and 2.7 ppm. However, the accuracy of predictions was reduced at higher free chlorine levels. The researchers conclude that MPS systems may benefit drinking water distribution systems by measuring free chlorine. These advantages of the MPS are especially pronounced in the developing world because this system is inexpensive and does not require routine maintenance or cleaning. The system relies on a naturally forming and regenerating biofilm and an inexpensive potentiometric meter to produce stable measurements.

54 ENVIRONMENTAL SCIENCES↗

Real-time measurements of endogenous CO production from vascular cells using an ultrasensitive laser sensor

Carbon monoxide (CO) has been implicated as a biological messenger molecule analogous to nitric oxide. A compact gas sensor based on a midinfrared laser absorption spectroscopy was developed for direct and real-time measurement of trace levels (in approximate pmol) of CO release by vascular cells. The midinfrared light is generated by difference frequency mixing of two nearinfrared lasers in a nonlinear optical crystal. A strong infrared absorption line of CO (4.61 microm) is chosen for convenient CO detection without interference from other gas species. The generation of CO from cultured vascular smooth muscle cells was detected every 20 s without any chemical modification to the CO. The sensitivity of the sensor reached 6.9 pmol CO. CO synthesis was measured from untreated control cells (0.25 nmol per 10(7) cells/h), sodium nitroprusside-treated cells (0.29 nmol per 10(7) cells/h), and hemin-treated cells (0.49 nmol per 10(7) cells/h). The sensor also detected decreases in CO production after the addition of the heme oxygenase (HO) inhibitor tin protoporphyrin-IX (from 0.49 to 0.02 nmol per 10(7) cells/h) and increases after the administration of the HO substrate hemin (from 0.27 to 0.64 nmol per 10(7) cells/h). These results demonstrate that midinfrared laser absorption spectroscopy is a useful technique for the noninvasive and real-time detection of trace levels of CO from biological tissues.

Non-NASA Center↗

Chapter 6: Wind Turbine Control Design

In this chapter, the author introduced wind turbine control, discussing sensors and actuators, operating regions, and the operational controller loops. The author then described the different levels of models needed in the controller development process, emphasizing that the models needed for control design are a simplification of the detailed models used in control simulation testing. Scripts used in conjunction with MATLAB are used to synthesize the controller, and detailed models are used for controller simulations. We described the design of the basic operational controller based on simplified models, including the generator torque controller for optimizing energy capture, and the blade pitch controller for regulating turbine speed (or power). The author described how to account for the effects of turbine nonlinearities and actuator dynamics and saturation. We then gave an overview of modern state-space control design methods, which are useful when designing a controller to meet multiple control objectives. The author also described a variety of advanced multivariable control methods. The author gave an overview of the use of advanced sensors (such as lidar sensors for upwind wind-speed measurements) and actuators (outboard blade aerodynamic devices used in 'smart' blade technology). The use of individual blade pitch, although not considered an advanced actuator, was also described. The author concluded with some special control issues for offshore floating systems.

17 WIND ENERGY↗

Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing

Wheat, being the third largest U.S. crop and the principal food grain, faces significant risks from climate extremes such as drought. This necessitates identifying and developing methods for early water-stress detection to prevent yield loss and improve water-use efficiency. This study investigates the potential of hyperspectral imaging to detect the early stages of drought stress in wheat. The goal is to utilize this technology as a tool for screening and selecting drought-tolerant wheat genotypes in breeding programs. Additionally, this research aims to systematically evaluate the effectiveness of various existing sensors and methods for detecting early stages of water stress. The experiment was conducted in a durum wheat experimental field trial in Maricopa, Arizona, in the spring of 2019 and included well-watered and water-limited treatments of a panel of 224 replicated durum wheat genotypes. Spectral indices derived from hyperspectral imagery were compared against other plant-level indicators of water stress such as Photosystem II (PSII) and relative water content (RWC) data derived from proximal sensors. Our findings showed a 12% drop in photosynthetic activity in the most affected genotypes when compared to the least affected. The Leaf Water Vegetation Index 1 (LWVI1) highlighted differences between drought-resistant and drought-susceptible genotypes. Drought-resistant genotypes retained 43.36% more water in leaves under well-watered conditions compared to water-limited conditions, while drought-susceptible genotypes retained only 15.69% more. The LWVI1 and LWVI2 indices, aligned with the RWC measurements, revealed a strong inverse correlation in the susceptible genotypes, underscoring their heightened sensitivity to water stress in earlier stages. Several genotypes previously classified based on their drought resistance showed spectral indices deviating from expectations. Results from this research can aid farmers in improving crop yields by informing early management practices. Moreover, this research offers wheat breeders insights into the selection of drought-tolerant genotypes, a requirement that is becoming increasingly important as weather patterns continue to change.

Roy, Bishal (ORCID:0000000199125505)↗

Multi-Satellite Observations of Oceanic Lightning

This paper will present several case studies of active oceanic lightning storms. Measurements by instruments on the Tropical Rainfall Measuring Mission (TRMM) and Fast On-orbit Recording of Transient Events (FORTE) platforms demonstrate that the two sets of sensors reinforce and complement one another. There is spatial and temporal coincidence between the optical data sets from Lightning Imaging Sensor (LIS) on TRMM and the photo-diode detector on FORTE. The LIS flash analysis provides a framework to interpret the stroke level data from FORTE. For these cases, the VHF receiver on FORTE is slaved to the optical system to provide stroke level radio frequency (RF) diagnostics. The occasions when TRMM and FORTE simultaneously have a lightning storm in their overlapping fields of view are extremely rare. One case study in the Gulf of Mexico is within range of land based sensor networks. These networks confirm the interpretation of satellite data and well as provide context for the storm conditions.

Boeck, W. L.↗

Multiple-amplifier sensing charged-coupled device: model and improvement of the node removal efficiency

The multiple-amplifier sensing charge-coupled device (MAS-CCD) has emerged as a promising technology for astronomical observation, quantum imaging, and low-energy particle detection due to its ability to reduce the readout time for the same readout noise level compared with its predecessor, the skipper-CCD, by reading out the same charge packet through multiple inline amplifiers. Previous works identified a new parameter in this sensor, called node removal inefficiency (NRI), related to inefficiencies in charge transfer and residual charge removal from the sense node of each amplifier after readout. These inefficiencies can lead to distortions in the measured signals similar to those produced by the charge transfer inefficiencies in standard CCDs. We introduce more details in the mathematical model of the NRI mechanism and provide techniques to quantify its magnitude from the measured data. It also proposes a new operation strategy that significantly reduces its effect with minimal alterations of the timing sequences or voltage settings for the other signals of the sensor. The proposed technique is demonstrated experimentally on a 16-amplifier MAS-CCD. At the same time, the experimental data demonstrate that this approach minimizes the NRI effect to levels comparable with other sources of distortion such as the charge transfer inefficiency in scientific devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Using In-Situ Deposition of Metallic Thin Films on Mars to Monitor Atmospheric H20

We describe the use of a novel sensor, designed to characterize the reactive nature of the Martian atmosphere, to also characterize the instantaneous abundance of atmospheric H,O. The sensor deposits, in situ, a thin silver film onto a sapphire substrate and monitors oxidation by measuring resistance of the Ag film during both deposition and subsequent oxidation [1,2]. . The evaporation source is placed in the center of a hollow, open-ended tube. On flash heating the source, evaporated metallic silver rapidly reacts with oxidizing gases in the tube, depositing on the tube walls as a resisitive Ag oxide film. Unoxidized silver deposits over the Ag oxides, once the oxidizing gases in the vicinity of the source have been consumed. Since the ends of the tube are open, atmospheric gases in the tube cause a time delay as the evaporated silver initially reacts with the available O2, and H2O; once oxidizing gases in the tube are significantly depleted, a silver film closes the chemiresistor circuit. In principle this operation mode provides a repeatable measure of the variable H2O abundance, since O2, levels are constant in the atmosphere. To explore the utility of the instrument as an H2O sensor, predict its behavior, and identify possible failure modes, we developed a numerical model of the instrument, and exercised it for Mars conditions. The model predicts the behavior of the electrical circuit, the temperature dependence of resistivity for each component, and the resultant Joule heating. The model balances Joule heating against radiation, sensible heat loss to ambient CO2, and, latent heat loss from sublimating Ag. The flux of Ag atoms from the source is tracked continuously. In the gas phase, the number density of Ag, O2, and H2O is calculated, along with their reaction rates on collision. The model suggests that Ag substantially depletes H2O only near the center of the tube. The model supports the hypothesis that the onset of high conductivity between the A u electrodes is a function of the H2O abundance in the ambient gas, but only to a limit; when H2O abundances are buffered at or above 240K (an H2O abundance that would not have occurred on Mars), metallic Ag never deposits in excess of Ago, and the circuit does not close. A significant difference in the Mars simulation is that the Ag source sublimates more quickly, primarily because of differences in sensible heat fluxes from the source. This allows subsequent heating of the W filament used to support the Ag source. Had the originally-designed experimental sequence been carried out on Mars, the filament might have melted, making subsequent investigations impossible.

Zent, A. P.↗

Sensor Co-design for $\textit{smartpixels}$

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in the first level of the trigger for a hadron collider. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p$_T$) based on the geometrical shape of the charge deposition (``cluster''). To design a viable detector for deployment at an experiment, the dependence of the NN as a function of the sensor geometry, external magnetic field, and irradiation must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. A smaller sensor pitch in the bending direction improves the p$_T$ discrimination, but a larger pitch can be partially compensated with detector depth. An external magnetic field parallel to the sensor plane induces Lorentz drift of the electron-hole pairs produced by the charged particle, broadening the cluster and improving the network performance. The absence of the external field diminishes the background rejection compared to the baseline by $\mathcal{O}$(10%). Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by $\sim$ 30 - 60%, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data.

Shekar, Danush [Illinois U., Chicago]↗

Point Sensor Networks Struggle to Detect and Quantify Short Controlled Releases at Oil and Gas Sites

This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of the mixing ratio readings at downwind sensors were greater than the site’s baseline plus two standard deviations. Four of seven total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from −100% to 24% for solution D, −100% to −43% for solution E, −25% for solution F (solution F was only at one site), and −99% to 430% for solution G, with an overall average of −29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within ±2.5 kg/h of the study team’s best estimate of site-level emissions at the time of the releases.

42 ENGINEERING↗