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At least 145 records · Page 8

Distributed Sensing Node Configuration

A vision and radar sensor integration strategy for surveillance of Advance Air Mobility Mission concept of airspace is contained in the CAD drawing in this publication developed as part of NASA's Transformational Tools and Technology project. High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. Contained herein are drawings that are available in the stp and creo file formats of the distributed sensing nodes. Additional dovetail integration is included to enable rapid changing of embedded system. A day in the life node deployment is included in the 2023_last_flight_day.mp4. Please cite this publication if you use these drawings. This sensor configuration methodology is presented in detail in the publication reference below. Chester Dolph, Thomas Lombaerts, Corey A. Ippolito, Vahram Stepanyan, Evan Kawamura, Keerthana Kannan, George Szatkowski, Todd Ferante, Christopher Morris, Federica Vitiello, Flavia Causa, Roberto Opromolla and Giancarmine Fasano. "Distributed Sensor Fusion of Ground and Air Nodes using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds," AIAA 2024-1781. AIAA SCITECH 2024 Forum. January 2024.

Chester V Dolph↗

Sensing Electrical Networks Securely & Economically (SENSE)

The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Polar cap potential distributions during periods of positive IMF B(sub y) and B(sub z)

We compare the DE-2 electric field measurements used by HEPPNER and MAYNARD (1987) to illustrate strongly distorted, BC convection patterns for interplanetary magnetic field (IMF) B(sub z) greater than 0 and large absolute value of B(sub y), with simultaneous detections of particle spectra, plasma drifts and magnetic perturbations. Measured potentials greater than 50 keV, driven by the solar wind speeds exceeding 500 km/s, are greater than published correlation analysis predictions by up to 27%. The potential distributions show only two extrema and thus support the basic conclusion that under these conditions the solar wind/IMF drives two-rather than four-cell convection patterns. However, several aspects of the distorted two-cell convection pattern must be revised. In addition to the strong east-west convection in the vicinity of the cusp, indicated by Heppner and Maynard, we also detect comparable components of sunward (equatorward) plasma flow. Combined equipotential and particle precipitation distributions indicate the presence of a lobe cell embedded within the larger, afternoon reconnection cell. Both types rotate in the same sense, with the lobe cell carrying 20-40% of the total afternoon cell potential. We detected no lobe cell within morning convection cell.

Burke, William J.↗

Fourier-based three-dimensional multistage transformer for aberration correction in multicellular specimens

High-resolution tissue imaging is often compromised by sample-induced optical aberrations that degrade resolution and contrast. Although wavefront sensor-based adaptive optics (AO) can measure these aberrations, such hardware solutions are typically complex, expensive to implement and slow when serially mapping spatially varying aberrations across large fields of view. Here we introduce AOViFT (adaptive optical vision Fourier transformer)—a machine learning-based aberration sensing framework built around a three-dimensional multistage vision transformer that operates on Fourier domain embeddings. AOViFT infers aberrations and restores diffraction-limited performance in puncta-labeled specimens with substantially reduced computational cost, training time and memory footprint compared to conventional architectures or real-space networks. We validated AOViFT on live gene-edited zebrafish embryos, demonstrating its ability to correct spatially varying aberrations using either a deformable mirror or postacquisition deconvolution. By eliminating the need for the guide star and wavefront sensing hardware and simplifying the experimental workflow, AOViFT lowers technical barriers for high-resolution volumetric microscopy across diverse biological samples.

Alshaabi, Thayer [Howard Hughes Medical Institute,↗

Machine Learning-Enabled Wearable Piezoelectric Acoustic Sensor for Real-Time Breast Abnormality Detection

In contemporary society, breast health has become a significant public health concern, particularly among women. According to statistics from the World Health Organization, both the incidence and mortality rates of breast tumors have steadily increased in recent years. Therefore, effective early-stage screening and postoperative monitoring are essential for maintaining breast health. However, conventional clinical diagnostic modalities are typically bulky, operationally complex, and unsuitable for continuous real-time monitoring, which limits their use in portable and everyday health management applications. To address these limitations, this study proposes a machine learning-integrated wearable piezoelectric sensing platform as an auxiliary tool for breast health assessment. The device consists of a PDMS matching layer embedded with flexible silver nanowires, a P(VDF-TrFE) piezoelectric layer, and a multi-channel low-noise signal acquisition circuit. It is capable of acquiring acoustic echo signals from tissue-mimicking environments and automatically evaluating signal validity using a convolutional neural network (CNN). By integrating piezoelectric sensing with deep learning-based signal analysis, the proposed system achieves a signal-to-noise ratio exceeding 70 dB and a real-time classification accuracy above 96% under controlled conditions. These results demonstrate that the platform provides a compact, portable, and intelligent approach for wearable sensing of mechanical heterogeneity and highlight its potential for future development in continuous biomedical monitoring technologies.

He, Shuaitong↗

Decentralized Observer with a Consensus Filter for Distributed Discrete-Time Linear Systems

This paper presents a decentralized observer with a consensus filter for the state observation of a discrete-time linear distributed systems. In this setup, each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors' estimates. We assume that the communication graph is connected for all times as well as the sensing graph. It is proven that the state estimates of the proposed observer asymptotically converge to the actual plant states under arbitrarily changing, but connected, communication and sensing topologies. As a byproduct of this research, we also obtained a result on the location of eigenvalues, the spectrum, of the Laplacian for a family of graphs with self-loops.

embedded consensus↗

Polarization as a Discriminator of Light-Absorbing Impurities in or Above Snow

This conceptual study presents advanced radiative transfer computations of light polarization originating from a snowpack consisting of nonspherical grains and variable content of light-absorbing impurities, either embedded in the snowpack or (with the same optical properties) lofted above it in the form of atmospheric aerosols. The results highlight the importance of considering shapes other than spherical for the snow grains, which otherwise can lead to non-negligible errors in the retrieval of snow albedo from remote sensing observations. More importantly, it is found that polarimetric measurements provide a means to partition light-absorbing impurities embedded in the snowpack from absorbing aerosols aloft, a task traditionally prohibitive for sensors capable exclusively of measurements of total reflectance. Heritage techniques to obtain snow grain size from shortwave infrared observations of total reflectance are well established, as are those that leverage polarimetric, multiangular observations across the entire optical spectrum to characterize the optical and microphysical properties of atmospheric aerosols. The polarization signatures of near-infrared (e.g., 864 nm) observations carry critical information on snow grain shape. The prospected launch of space-borne polarimeters with proven accuracy, therefore, advocates for the development of data inversion schemes, to boost the accuracy of simultaneous retrievals of atmospheric and surface parameters in the polar and snow-covered regions, critical to climate studies.

light polarization↗

Securing Solar for the Grid: Extreme Control Whitepaper

Emerging standards outlining desired behaviors for Distributed Energy Resources (DER), such as IEEE 1547-2018, define several device-level control functions to regulate DER power injections/consumptions in response to locally sensed grid conditions. The ability to adjust settings of aggregations of DER with standardized embedded control functionality constitutes a mechanism which can, potentially, create undesirable or deleterious effects on the power grid. The purpose of this white paper is to highlight unintended effects stemming from improperly tuned embedded control functions in Distributed Energy Resources (DER), which could be exploited by a malicious entity as a means to attack the power grid.

14 SOLAR ENERGY↗

Detecting rare earth elements via optically detected magnetic resonance (ODMR) and spin-relaxometry using nitrogen vacancy centers in nanodiamonds

Nanodiamonds embedded with nitrogen-vacancy (NV) centers are emerging as powerful tools in quantum sensing due to their remarkable sensitivity to local variations in electromagnetic fields, temperature, and pressure. These point defects in the diamond lattice can be probed using optically detected magnetic resonance (ODMR) and spin relaxometry techniques, allowing for the detection and characterization of magnetic nanoparticles and ions. The sensing mechanism relies on laser-induced excitation of the NV center's non-degenerate triplet ground state, which promotes electrons to an excited state. Subsequent photoluminescence (PL) emission, which is spin-state dependent, is then measured. These spin states are highly responsive to magnetic perturbations in the surrounding environment. By analyzing changes in the ODMR spectra and spin relaxation times, we can effectively monitor how magnetic species influence the NV center's spin dynamics, thus enabling sensitive and selective characterization of nanoscale magnetic materials. These techniques have been applied for the characterization of transition metals and rare earth elements which shows natural ferromagnetic properties.

magnetic nanopartgicles and ions↗

Efficient Ada multitasking on a RISC register window architecture

This work addresses the problem of reducing context switch overhead on a processor which supports a large register file - a register file much like that which is part of the Berkeley RISC processors and several other emerging architectures (which are not necessarily reduced instruction set machines in the purest sense). Such a reduction in overhead is particularly desirable in a real-time embedded application, in which task-to-task context switch overhead may result in failure to meet crucial deadlines. A storage management technique by which a context switch may be implemented as cheaply as a procedure call is presented. The essence of this technique is the avoidance of the save/restore of registers on the context switch. This is achieved through analysis of the static source text of an Ada tasking program. Information gained during that analysis directs the optimized storage management strategy for that program at run time. A formal verification of the technique in terms of an operational control model and an evaluation of the technique's performance via simulations driven by synthetic Ada program traces are presented.

Kearns, J. P.↗

Triboluminescent Fiber-Optic Sensors Measure Stresses

Triboluminescence exploited in fiber-optic sensor system for measuring changes in pressures, strains, vibrations, and acoustic emissions, in structural members. Sensors embedded in members for in situ monitoring of condition of structure. System passive in sense no source of radiation required to interrogate optical fiber. Technique has potential for wide range of applications in which detection and measurement of structural stress required.

Rogowski, Robert S.↗

Evaluation of Mechanical Modal Characteristics Using Optical Techniques

In this paper the sensitivity of embedded fiber optic sensors to changes in modal characteristics of plates is discussed. In order to determine the feasibility of embedded fiber Bragg gratings for the detection of modal shapes and modal frequencies, a comparison of holographically imaged modes and the detected dynamic strain from embedded fiber optic Bragg gratings is made. Time averaged optical holography is used for the detection of mechanical defects, or damage, in various aerospace components. The damage is detected by measuring an alteration in structural dynamics, which is visually apparent when using time-averaged holography. These shifts in the mode shapes, both in frequency of the resonance and spatial location of vibration nodes, are caused by changes in parameters that affect the structure's mechanical impedance, such as stiffness, mass and damping, resulting from cracks or holes. It is anticipated that embedded fiber optic sensor arrays may also be able to detect component damage by sensing these changes in modal characteristics. This work is designed to give an initial indication to the feasibility of damage detection through the monitoring of modal frequencies and mode shapes with fiber optic sensors.

Lekki, John↗

Optically Active Spin Defects in Few-Layer Thick Hexagonal Boron Nitride

Optically active spin defects in hexagonal boron nitride (hBN) are promising quantum systems for the design of two-dimensional quantum sensing units offering optimal proximity to the sample being probed. In this Letter, we first demonstrate that the electron spin resonance frequencies of boron vacancy centers ($V$$^{–}_{B}$) can be detected optically in the limit of few-atomic-layer thick hBN flakes despite the nanoscale proximity of the crystal surface that often leads to a degradation of the stability of solid-state spin defects. We then analyze the variations of the electronic spin properties of $V$$^{–}_{B}$ centers with the hBN thickness with a focus on (i) the zero-field splitting parameters, (ii) the optically induced spin polarization rate and (iii) the longitudinal spin relaxation time. Furthermore, this Letter provides important insights into the properties of $V$$^{–}_{B}$ centers embedded in ultrathin hBN flakes, which are valuable for future developments of foil-based quantum sensing technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Chemist’s Guide to Solid-State Qubits: Diamond Color Centers as Embedded Vacancy-Centered Molecules

Diamond point defects or color centers are at the crux of solid-state quantum technology applications, from computing to sensing. Modeling molecular qubits has advanced by leaps and bounds mainly due to the advanced quantum mechanical (QM) tools in the arsenal of quantum chemists for modeling (isolated) molecular systems, which should be easily translatable for analogous systems in the solid state. Here, we simulate a series of diamond defects: a carbon vacancy (V C ) and second row substitutions that are adjacent to a V C or D C V C , with D = B, N, and O, to evaluate their magnetic and optical properties. We applied molecular orbital principles, an embedded cluster method, and a multiconfigurational QM theory to computationally characterize the above-mentioned defects for a multitude of spin, charge, and excited states. Our computational approach delivered high-quality QM insights that compare well with experiments. Furthermore, with this framework, we confirm the spin-triplets B C V C – and O C V C 0 to be analogous to N C V C – , with calculated bright transitions that respectively correspond to UV (3.80 eV) and blue (2.65 eV) light absorption and emission lifetimes (τ) of 2.3 and 5.6 ns, which are higher in energy and more short-lived (and thus brighter) than that for N C V C – : green (2.26 eV), τ = 9.5 ns.

Martirez, John Mark P. [Princeton Plasma Physics L↗

Towards Multifunctional Characteristics of Embedded Structures With Carbon Nanotube Yarns

This paper presents recent results on research of achieving multifunctional structures utilizing Carbon Nanotube (CNT) yarns. The investigation centers on creating composite structures with CNT yarns to simultaneously achieve increases in mechanical strength and the ability to sense strain. The CNT yarns used in our experiments are of the single-ply and two-ply variety with the single-ply yarns having diameters on the order of 10-20 m. The yarns are embedded in silicon rubber and polyurethane test specimens. Mechanical tests show an increase in modulus of elasticity, with an additional weight increase of far less than one-percent. Sensing characteristics of the yarns are investigated on stainless steel test beams in an electrical bridge configuration, and are observed to have a strain sensitivity of 0.7mV/V/1000 micro-strain. Also reported are measurements of the average strain distribution along the direction of the CNT yarns on square silicon rubber membranes.

Hernandez, Corey D.↗

Embedded sensors integrated into critical components for in situ health monitoring of steam turbines

Operational flexibility is desired in today’s coal-fired power plants to balance power grids by compensating for the variable electricity supply from renewable energy sources and distributed gensets. This demanding requirement accelerates materials degradation and makes in-situ health monitoring essential. Life monitoring of components and subsystems is thus seen as essential in assessing material and mechanical behavior to estimate system reliability, move to a conditionbased maintenance strategy and determine time to failure of the units in their actual operating conditions. Vibration monitoring can be exploited for blade tip timing to measure blade vibration amplitude and tip clearance to detect any deterioration taking place in the condition of steam turbine blades. A failure of a rotating blade can lead to severe turbine damage followed by extensive repairs and loss of power production. A blade vibration monitoring system can help early detection of abnormal blade vibration behavior. In conjunction with a health monitoring system, the vibration characteristics can be analyzed to support a pro-active maintenance and inspection schedule. While the feasibility of this inspection technique has been amply demonstrated, there is a need to install induction probes to magnetize the blade for signal output. Siemens, in partnership with Raytheon Technologies Research Corporation (RTRC), proposes a holistic approach to develop embedded sensors to utilize radio frequency for not only coupling to sensors, but as the sensing modality. The goal of this project is to “embed” the novel sensing approach by using either additively manufactured or extruded waveguides on rotating blades for recording, evaluation and monitoring of blade vibrations in Low Pressure turbines, with applications extending to aero engines

01 COAL, LIGNITE, AND PEAT↗

Triboluminescent Materials for Smart Optical Damage Sensors for Space Applications

There is a need to develop a new technique of damage detection for composites, which could detect cracking or delamination from any desired location within a material structure in real time. Recently, triboluminescent materials have been proposed as smart sensors of structural damage. To sense the damage, these materials can be epoxy bonded, coated in a polymer matrix, or embedded in a composite host structure. When the damage or fracture takes place in the host structure, the resultant fracture of triboluminescent crystals creates a light emission. This will warn in real time that structural damage has occurred. The triboluminescent emission of the candidate phosphor has to be bright enough that the light reaching from the point of fracture to the detector through a fiber optic cable is detectable. There are a large number of triboluminescent materials, but few satisfy the above criterion. The authors have synthesized an organic material known as Europium tetrakis (dibenzoylmethide) triethylammonium (EuD4TEA), which is a potential candidate for application as a damage sensor and could be made into a wireless sensor with the addition of microchip, antenna, and electronics. Preliminary results on the synthesis and characterization of this material are presented.

Aggarwal, M. D.↗

Distributed Sensing of Carbon-Epoxy Composites and Filament Wound Pressure Vessels Using Fiber-Bragg Gratings

Multiple Fiber Bragg-gratings are embedded in carbon-epoxy laminates as well as in composite wound pressure vessel. Structural properties of such composites are investigated. The measurements include stress-strain relation in laminates and Poisson's ratio in several specimens with varying orientation of the optical fiber Bragg-sensor with respect to the carbon fiber in an epoxy matrix. Additionally, fiber Bragg gratings are bonded on the surface of these laminates and cylinders fabricated out of carbon-epoxy composites and multiple points are monitored and compared for strain measurements at several locations.

Grant, J.↗