Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sensor array”

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 307 records · Page 17

Material condition assessment with eddy current sensors

Eddy current sensors and sensor arrays are used for process quality and material condition assessment of conducting materials. In an embodiment, changes in spatially registered high resolution images taken before and after cold work processing reflect the quality of the process, such as intensity and coverage. These images also permit the suppression or removal of local outlier variations. Anisotropy in a material property, such as magnetic permeability or electrical conductivity, can be intentionally introduced and used to assess material condition resulting from an operation, such as a cold work or heat treatment. The anisotropy is determined by sensors that provide directional property measurements. The sensor directionality arises from constructs that use a linear conducting drive segment to impose the magnetic field in a test material. Maintaining the orientation of this drive segment, and associated sense elements, relative to a material edge provides enhanced sensitivity for crack detection at edges.

Goldfine, Neil J.↗

Room Temperature Carbon Nanotube Based Sensor for Carbon Monoxide Detection

Sulfonated single-walled carbon nanotubes have been used in an integrated electrode structure forthe detection of carbon monoxide. The sensor responds to 0.5 ppm of CO in air at room temperature. All eightsensors with this material in a 32-sensor array showed good repeatability and reproducibility, with response andrecovery times of about 10 s. Pristine nanotubes generally do not respond to carbon monoxide and the resultshere confirm sulfonated nanotubes to be a potential candidate for the construction of an electronic nose thatrequires at least a few materials for the selective detection of CO.

Nanomaterial functionalization↗

An Examination of Coarse Sun Sensor Contingencies in Attitude Determination and the Sun Vector Calculation

Satellite pointing is vital to the success of a mission. One element of that entails describing the position of the sun relative to the frame of the satellite. Coarse Sun Sensors (CSS) are typically used to provide the information to calculate the sun's position in Safe Modes or contingency operations. In the OCO-2 configuration there are 13 CSS total, which provide redundant 4 celestial coverage. Failures of the individual CSS elements can introduce holes in the celestial coverage resulting in potential loss of sun knowledge. These failures must be analyzed to determine if the contingency plan is sufficient to assure mission success. First the static case was looked at and determined that at a maximum, 3 CSS failures can be sustained on the body and 1 on the array without causing coverage holes. Also array sensors are more important to mission success. The Sun Vector calculation has been transcribed to MATLAB code and failure scenarios are being examined to determine the maximum error given a set of failure scenarios. This activity indicated that if there is a loss of the sun, the sun-searching algorithm could be modified to use XZ rotation as that is guaranteed to find it whereas the design using the YZ rotation misses the sun if it is at the + or - Y orientation.

celestial bodies↗

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

54 ENVIRONMENTAL SCIENCES↗

An Acoustic Quench Detection Method for CICC Conductor Operating in Gas or Liquid

Here, a method using micro-electro-mechanical system (MEMS) acoustic sensor technology to detect a quench and abnormal behavior of a superconductor is discussed. MEMS of microphone chips are installed along the coolant space of a superconducting conductor to monitor the coolant condition. By arranging the acoustic sensor array in a coolant flow channel, it is possible to quickly detect a change in the local condition of the coolant with precise spatial resolution. This method is useful for monitoring superconducting magnets and power cables, especially those made with a cable-in-conduit-conductor (CICC) configuration. The methodology described in this work will also be very useful for a high temperature superconducting (HTS) conductor, such as REBCO tape conductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Limb-atmospheric infrared spectrum observed on the satellite Ohzora

The Institute of Space and Astronautical Science (ISAS) launched the 9th scientific satellite Ohzora at 17:00 JST on February 14, 1984. This satellite bears the spectrometer, which measures the infrared spectrum of the solar radiation passing the limb atmosphere in the wavelength region of 2 to 10 m. The spectrometer is based on multichannel spectroscopy by using image sensors. Since the wavelength is scanned electronically, it can measure the spectrum unaffected by the satellite motion. A definite axis, i.e., the Z-axis of the satellite, which coincides to the optical axis of the spectrometer, is controlled to the direction of the Sun, and the finer control to introduce the solar light into the spectrometer is made with a 2-axes-controlled mirror. This solar tracking equipment is derived fast enough to measure the spectra in a moment after sunrise. The solar light introduced into the spectrometer is focused on the slits of the monochromators (f=100mm). For better altitude resolution, the horizontal slit is also used with the vertical slit, which is used for the separation of the dispersion. The dispersion light is detected with the pyroelectric array sensors. To obtain maximum dynamic range and spectral resolution, the three-stage polychromator is used.

Matsuzaki, A.↗

Robust Heat-Flux Sensors for Coal-Fired Boiler Extreme Environments

In this project, robust heat-flux measurement systems were developed. The heat-flux sensors utilize thermoelectric effects to directly transduce the heat-flux inputs to analog electrical voltage signals. They were constructed from dedicated materials that can withstand temperatures of at least 1000°C and maintain adequate performance at these conditions for prolonged periods of time. The proposed approaches took into account numerous considerations, including system cost, sensor head resilience, sensor footprint, data accuracy, response time, and maintenance requirements. Through modern thermoelectric materials design, methodical materials selection and rigorous testing in materials characterization labs and medium-scale fire research facilities, we have demonstrated functioning laboratory prototypes, upon which one could base industrial heat-flux sensing platforms capable of operating in the challenging high-temperature, corrosive environments of the boilers of coal-fired power plants. A distributed sensor array for heat-flux measurements throughout the furnace water-wall, the superheater area and the economizer coils can provide critical data for the power plant control systems to increase efficiency, improve safety and reduce down times. For example, the combined heat-flux sensor/control systems can contribute to the optimization of burner and boiler operations under flexible loads, the optimization of heat-exchange conditions and overall reduction of heat rate and emissions, the prediction of imminent overheating conditions, and the optimization of the soot-blowing protocols.

20 FOSSIL-FUELED POWER PLANTS↗

Two-Level Switches for Advanced Time-Division Multiplexing

Superconducting quantum interference device (SQUID)-based time-division multiplexing (TDM) is a mature and widely implemented technology used to read out transition-edge sensor arrays. As the number of pixels in modern arrays continues to increase, a higher multiplexing factor is required to reduce the number of wires and amplifier channels. Yet, as the multiplexing factor is increased, the number of row-select wires (used to turn on a row of TDM SQUIDs in a two-dimensional configuration) also increases, limiting the reduction in array wires. We introduce a more advanced TDM architecture that enforces multi-level switching between subgroups of pixels. We show that this technique can dramatically reduce the number of required row-select lines. We also present the design, fabrication, and testing of a TDM multiplexer incorporating a two-level switch, which implements a second switch for each group of ten TDM pixels. In this application, a multiplexing factor of 100 can be addressed using ten group-select wiring pairs and ten row-select wiring pairs. We demonstrate multiplexer functionality and present measured operating margins of this new TDM multiplexer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

MEMS Applications in Aerodynamic Measurement Technology

Microelectromechanical systems (MEMS) embodies the integration of sensors, actuators, and electronics on a single substrate using integrated circuit fabrication techniques and compatible bulk and surface micromachining processes. Silicon and its derivatives form the material base for the MEMS technology. MEMS devices, including microsensors and microactuators, are attractive because they can be made small (characteristic dimension about 100 microns), be produced in large numbers with uniform performance, include electronics for high performance and sophisticated functionality, and be inexpensive. For aerodynamic measurements, it is preferred that sensors be small so as to approximate measurement at a point, and in fact, MEMS pressure sensors, wall shear-stress sensors, heat flux sensors and micromachined hot wires are nearing application. For the envisioned application to wind tunnel models, MEMS sensors can be placed on the surface or in very shallow grooves. MEMS devices have often been fabricated on stiff, flat silicon substrates, about 0.5 mm thick, and therefore were not easily mounted on curved surfaces. However, flexible substrates are now available and heat-flux sensor arrays have been wrapped around a curved turbine blade. Electrical leads can also be built into the flexible substrate. Thus MEMS instrumented wind tunnel models do not require deep spanwise grooves for tubes and leads that compromise the strength of conventionally instrumented models. With MEMS, even the electrical leads can potentially be eliminated if telemetry of the signals to an appropriate receiver can be implemented. While semiconductor silicon is well known for its electronic properties, it is also an excellent mechanical material for MEMS applications. However, silicon electronics are limited to operations below about 200 C, and silicon's mechanical properties start to diminish above 400 C. In recent years, silicon carbide (SiC) has emerged as the leading material candidate for applications in high temperature environments and can be used for high-temperature MEMS applications. With SiC, diodes and more complex electronics have been shown to operate to about 600 C, while the mechanical properties of SiC are maintained to much higher temperatures. Even when MEMS devices show benefits in the laboratory, there are many packaging challenges for any aeronautics application. Incorporating MEMS into these applications requires new approaches to packaging that goes beyond traditional integrated circuit (IC) packaging technologies. MEMS must interact mechanically, as well as electrically with their environment, making most traditional chip packaging and mounting techniques inadequate. Wind tunnels operate over wide temperature ranges in an environment that is far from being a 'clean-room.' In flight, aircraft are exposed to natural elements (e.g. rain, sun, ice, insects and dirt) and operational interferences(e.g. cleaning and deicing fluids, and maintenance crews). In propulsion systems applications, MEMS devices will have to operate in environments containing gases with very high temperatures, abrasive particles and combustion products. Hence deployment and packaging that maintains the integrity of the MEMS system is crucial. This paper presents an overview of MEMS fabrication and materials, descriptions of available sensors with more details on those being developed in our laboratories, and a discussion of sensor deployment options for wind tunnel and flight applications.

Reshotko, E.↗

Chemiresistors for the Real‐Time Wireless Detection of Anions

Abstract Reported is an electrical transduction platform for real‐time wireless anion sensing using single‐walled carbon nanotubes (SWCNTs) noncovalently functionalized with squaramide‐based anion binding selectors. Systematically studied are anion‐binding properties and efficiency of the electrical transduction of the functionalized SWCNT composites using the squaramide‐based selectors with two similar electron‐withdrawing groups, 3,5‐bis(trifluoromethyl)benzyl ( 1 ) and 3,5‐bis(trifluoromethyl)phenyl ( 2 ), which induce hydrogen‐bonding interaction with anions and deprotonation of a squaramide N–H proton upon addition of acetate (AcO − ), respectively. Charge transduction occurs with AcO − as a result of charge transfer from the deprotonated selector 2 , whereas less sensitive transduction is observed with selector 1 via hydrogen‐bonding interaction. These results provide guidelines to efficiently transduce the chemical interaction between selectors and anions to create resistive transduction with functionalized SWCNTs. Electron‐withdrawing groups adjacent to the squaramide as well as proximate cationic pyridyl groups, enhance the anion binding affinity and also lower the selector's p K a . The chemiresistive sensor arrays are readily integrated with a wireless sensing module and demonstrated real‐time sensing of multiple anions with a smartphone readout.

Choi, Seon‐Jin↗

In situ detection and characterization of alkali-silica reaction damage in concrete using contactless ultrasonic wavefield imaging

Here we present work to characterize cracking damage in concrete caused by alkali-silica reactivity distress. We apply contactless ultrasonic scan inspection, exploiting Rayleigh wave scattering from concrete inhomogeneities. The scanning system utilizes a multi-channel MEMS sensor array to collect ultrasonic wavefield data from concrete subjected to ASR-promoting environments. The location and extent of ASR damage are established by internal expansion measurements from embedded strain gauges, scanning electron microscope images of cored samples, and expansion measurements from companion samples. A wavefield data processing method extracts oscillatory fields from the ultrasonic wavefield data to detect distinct zones of ASR damage. A damage index is proposed to further characterize the extent of ASR damage. The results confirm the feasibility and accuracy of the approach to characterize ASR damage in concrete. The fully contactless ultrasonic scanning measurement system does not require separate material samples and enables in situ characterization of ASR damage within concrete structures.

36 MATERIALS SCIENCE↗

A simple, validated approach for design of two-dimensional periodic particle patterns via acoustophoresis

Two-dimensional patterning of microparticles enables a wide range of functional materials, including patterned energy storage electrodes, flexible electronics, and sensor arrays. Particle patterning via acoustics offers an attractive path to generate a wide variety of 2D periodic patterns that introduce tailorable hierarchical porosity, useful for controlling surface area, transport distances, and other properties. This method is most effective with micron scale particles and patterns of tens to hundreds of microns. To enable systematic exploration of the broad design space for such patterns, this work develops a model of 2D and 3D assembly of particles at high loadings and validates the obtained patterns against both experiments and more computationally intensive modeling techniques. Using this simple model, connections are mapped between input parameters (like actuation conditions, particle volume fraction, material properties) and output geometrical features (like void size and shape, pattern connectivity, and surface area) so that they can be tailored to given applications. The utility of this simple model is illustrated by predicting and then experimentally demonstrating new hierarchical patterns resulting from multiple waves of different frequencies interacting. These multiscale patterns offer the potential to lift the limits on surface area, diffusion distances, and other features.

42 ENGINEERING↗

Hyporheic Zone Microbiome Assembly Is Linked to Dynamic Water Mixing Patterns in Snowmelt-Dominated Headwater Catchments

We report that terrestrial and aquatic elemental cycles are tightly linked in upland fluvial networks. Biotic and abiotic mineral weathering, microbially mediated degradation of organic matter, and anthropogenic influences all result in the movement of solutes (e.g., carbon, metals, and nutrients) through these catchments, with implications for downstream water quality. Within the river channel, the region of hyporheic mixing represents a hot spot of microbial activity, exerting significant control over solute cycling. To investigate how snowmelt-driven seasonal changes in river discharge affect microbial community assembly and carbon biogeochemistry, depth-resolved pore water samples were recovered from multiple locations around a representative meander on the East River near Crested Butte, CO, USA. Vertical temperature sensor arrays were also installed in the streambed to enable seepage flux estimates. Snowmelt-driven high river discharge led to an expanding zone of vertical hyporheic mixing and introduced dissolved oxygen into the streambed that stimulated aerobic microbial respiration. These physicochemical processes contributed to microbial communities undergoing homogenizing selection, in contrast to other ecosystems where lower permeability may limit the extent of mixing. Conversely, lower river discharge conditions led to a greater influence of upwelling groundwater within the streambed and a decrease in microbial respiration rates. Finally, associated with these processes, microbial communities throughout the streambed exhibited increasing dissimilarity between each other, suggesting that the earlier onset of snowmelt and longer periods of base flow may lead to changes in the composition (and associated function) of streambed microbiomes, with consequent implications for the processing and export of solutes from upland catchments.

58 GEOSCIENCES↗

Active‐Source Seismic Imaging of Fault Re‐Activation and Leakage: An Injection Experiment at the Mt Terri Rock Laboratory, Switzerland

Abstract We conducted a time‐lapse seismic experiment utilizing automated active seismic source and sensor arrays to monitor a reactivated fault within the Opalinus clay formation at the Mont Terri Rock Laboratory (Switzerland), an analog caprock for geologic carbon storage. A series of six brine injections were conducted into the so‐called Main Fault to reactivate it. Seismic instrumentation in five monitoring boreholes on either side of the fault was used to continuously probe changes in P‐wave travel‐times associated with fault displacement and leakage. We performed time‐lapse travel‐time tomography on five hundred sequential data sets; this revealed a zone of decreased P‐wave velocity, up to 16 m/s, during each injection cycle, followed by a velocity increase during shut‐in. These results demonstrate varying elastic property perturbations, both spatially and temporally, along the fault plane during reactivation. We then interpreted these velocity changes in terms of fault dilation induced by pressurized fluids along the fault.

58 GEOSCIENCES↗

High-throughput terahertz imaging: progress and challenges

Abstract Many exciting terahertz imaging applications, such as non-destructive evaluation, biomedical diagnosis, and security screening, have been historically limited in practical usage due to the raster-scanning requirement of imaging systems, which impose very low imaging speeds. However, recent advancements in terahertz imaging systems have greatly increased the imaging throughput and brought the promising potential of terahertz radiation from research laboratories closer to real-world applications. Here, we review the development of terahertz imaging technologies from both hardware and computational imaging perspectives. We introduce and compare different types of hardware enabling frequency-domain and time-domain imaging using various thermal, photon, and field image sensor arrays. We discuss how different imaging hardware and computational imaging algorithms provide opportunities for capturing time-of-flight, spectroscopic, phase, and intensity image data at high throughputs. Furthermore, the new prospects and challenges for the development of future high-throughput terahertz imaging systems are briefly introduced.

36 MATERIALS SCIENCE↗

Optical and x-ray characterization of the Daedalus ultrafast x-ray imager

The Daedalus ultrafast x-ray imager is the latest generation in Sandia’s hybrid CMOS detector family. With three frames along an identical line of sight, 1 ns minimum integration time, a higher full well than Icarus, and added features, Daedalus brings exciting new capabilities to diagnostic applications in inertial confinement fusion and high energy density science. In this work, we present measurements of time response, dynamic range, spatial uniformity, pixel cross-talk, and absolute x-ray sensitivity using pulsed optical and x-ray sources. Here, we report a measured 1.5 Me — full well, pixel sensitivity at 9.58 × 10 —7 V/e — , and an estimate of spatial uniformity at ~5% across the sensor array.

47 OTHER INSTRUMENTATION↗

Extracting the electronic structure of light elements in bulk materials through a Compton scattering method in the readily accessible hard x-ray regime

Here, our Compton profile measurements of Ti and TiH 2 using readily available hard X-ray radiation at 27.5 keV, detected by both a Hitachi Vortex silicon-drift detector and a high-resolution superconducting transition-edge sensor array, are found to be in excellent accord with state-of-the-art density functional theory based calculations. The spherically averaged difference between the Compton profiles of TiH 2 and Ti is well described by an inverted parabola, supporting an itinerant behavior of the electron gas screening the protons in the Ti matrix. Our experimental approach, validated by two different detectors, extends the applicability of Compton scattering technique to the readily accessible hard x-ray regime (below 30 keV). Our study suggests possibilities for experiments at low-flux bending magnet synchrotron beamlines and paves the way for the development of tabletop Compton experiments with x-ray tubes.

36 MATERIALS SCIENCE↗

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗