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Equalization of Intensity-Modulated Fiber-Optic Voltage Sensors for Power Distribution Systems
We test fiber-optic voltage sensors based on optical reflection from a piezoelectric transducer. Our specific devices possess a 2 kHz fundamental resonance, and we verify a readily usable frequency band from approximately 10 Hz to 3 kHz, with a dynamic range of 60 dB for a detection system integrating over this entire band. Additionally, we demonstrate a digital signal processing approach to equalize the measured frequency response, enabling accurate retrieval of short-pulse inputs. These results suggest the value and applicability of intensity-modulated fiber-optic voltage sensors for measuring both steady-state waveforms and broadband transients which, coupled with the straightforward and compact design of the sensors, should make them effective tools in electric grid monitoring.
MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques
This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.
First Soft X-ray Quantum Efficiency Measurements on Microwave Annealed Thin-Entrance Window Sensors
Free electron lasers, such as SLAC’s LCLS-II, will provide unique scientific imaging opportunities. In order to fully utilize these facilities, we need to develop detectors with shallow entrance windows that will enable detection of soft x-rays from 250eV-1.5KeV. In addition, there are other light sources such as the FERMI, EuXFEL, and FLASH XFELs, as well as numerous synchrotrons such as the ALS, where soft x-ray science would benefit from detectors with higher quantum efficiency in the 20 eV to 1.5KeV range.A new microwave annealing technology provides an efficient way to achieve shallow entrance windows in fully depleted high-resistivity silicon sensors. Previously, SRP and SIMS measurements were used to characterize the shallow dopant profile, and sensors with the new entrance window process were deployed successfully to measure an Fe-55 x-ray spectrum. For the first time, we present quantum efficiency measurement for soft x-rays. Furthermore, the resulting estimate of the entrance window is 20nm for an arsenic implanted entrance window and 55nm for a boron implanted entrance window.
Robust Group Subspace Recovery: A New Approach for Multi-Modality Data Fusion
Robust Subspace Recovery (RoSuRe) algorithm was recently introduced as a principled and numerically efficient algorithm that unfolds underlying Unions of Subspaces (UoS) structure, present in the data. The union of Subspaces (UoS) is capable of identifying more complex trends in data sets than simple linear models. In this work, we build on and extend RoSuRe to prospect the structure of different data modalities individually. We propose a novel multi-modal data fusion approach based on group sparsity which we refer to as Robust Group Subspace Recovery (RoGSuRe). Relying on a bi-sparsity pursuit paradigm and non-smooth optimization techniques, the introduced framework learns a new joint representation of the time series from different data modalities, respecting an underlying UoS model. We subsequently integrate the obtained structures to form a unified subspace structure. The proposed approach exploits the structural dependencies between the different modalities data to cluster the associated target objects. The resulting fusion of the unlabeled sensors’ data from experiments on audio and magnetic data has shown that our method is competitive with other state of the art subspace clustering methods. The resulting UoS structure is employed to classify newly observed data points, highlighting the abstraction capacity of the proposed method.
Behavior of the Fused Quartz Suspended Core Acoustic Waveguide Sensor in Gamma Radiation
Previously, a fused-quartz acoustic waveguide named the suspended core waveguide with tight-field confinement in a small diameter was developed and its sensing potential in harsh environment was demonstrated with the fabricated periodic acoustic fiber Bragg grating. In this paper, the acoustic sensor was exposed to around 70 Gy/h gamma radiation at room temperature for 3550 h at Oak Ridge National Laboratory. For comparisons, a thermocouple and two optical fiber Bragg gratings were tested under the same conditions. The central frequency reading of the acoustic sensor was found to encounter a relatively fast decrease of 0.5 kHz in the first 800 hours. The reading then became stable, centering at 478.5 kHz with a fluctuation of ±0.2 kHz, and responded to small environmental temperature variations less than 1.2 °C. The major effect to the fluctuation was concluded to be radiation-induced material compaction and expansion. For optical fiber Bragg gratings, the same one-directional fast change of readings in the first 500 hours were observed as well. Although the optical gratings were able to track temperature changes, they also showed continuous drifts. The survivability and consistency of the acoustic sensor under long-term gamma radiation could lead to new sensing methods in nuclear applications.
Multipoint sensing by intelligent collectives
Many remote sensing applications require that multiple sensors collect data simultaneously at spatially distributed locations and their information combined in order to characterize the phenomena of interest. Several basic classes of such multipoint measurement systems may be identified. For each, centralized methods exist for combining the raw data from the various sensors. However, recent advancements have given rise to small, integrated nodes comprised of one or more miniaturized sensors, processor, wireless communications capability and power supplies. Collections of these may be deployed and self-organized into intelligent sensor networks capable of performing cooperative signal processing locally, thereby providing substantial benefits.
1987 Annual Conference on Nuclear and Space Radiation Effects, Snowmass Village, CO, July 28-31, 1987, Proceedings
Various papers on nuclear and space radiation effects are presented. The general topics addressed include: basic mechanisms of radiation effects, single-event phenomena, temperature and field effects, modeling and characterization of radiation effects, IC radiation effects and hardening, and EMP/SGEMP/IEMP phenomena. Also considered are: dosimetry/energy-dependent effects, sensors in and for radiation environments, spacecraft charging and space radiation effects, radiation effects and devices, radiation effects on isolation technologies, and hardness assurance and testing techniques.
Multiphysics Modeling Framework for Soft PVC Gel Sensors with Experimental Comparisons
Polyvinyl chloride (PVC) gels have recently been found to exhibit mechanoelectrical transduction or sensing capabilities under compressive loading applications. This phenomenon is not wholly understood but has been characterized as an adsorption-like phenomena under varying amounts and types of plasticizers. A different polymer lattice structure has also been tested, thermoplastic polyurethane, which showed similar sensing characteristics. This study examines mechanical and electrical properties of these gel sensors and proposes a mathematical framework of the underlying mechanisms of mechanoelectrical transduction. COMSOL Multiphysics is used to show solid mechanics characteristics, electrostatic properties, and transport of interstitial plasticizer under compressive loading applications. The solid mechanics takes a continuum mechanics approach and includes a highly compressive Storakers material model for compressive loading applications. The electrostatics and transport properties include charge conservation and a Langmuir adsorption migration model with variable diffusion properties based on plasticizer properties. Results show both plasticizer concentration gradient as well as expected voltage response under varying amounts and types of plasticizers. Experimental work is also completed to show agreeance with the modeling results.
A flexible test facility for liquid xenon detector development
As liquid xenon time projection chambers scale to ever-larger sizes, so too do the engineering challenges they pose. Here, we describe a large, flexible, multipurpose test facility capable of supporting the development of a number of key aspects of liquid xenon detector systems. Example applications of this facility include characterization of large-area light and charge sensor arrays, tests of xenon purification techniques and materials compatibility, and investigations into high-voltage phenomena. This facility uses an automated and remotely monitored cryo-cooling system based on immersion of the test chamber in a liquid bath rather than conductive coupling, leading to advantages in temperature and pressure stability, as well as increasing required response times in the case of cooling-power loss. Design advantages, operational procedures, and performance of the facility are described, as well as five examples of liquid xenon test chambers that use the facility.
Laboratory investigation of hydraulic fracturing in granitic rocks using active and passive seismic monitoring
SUMMARY Knowledge of the fracturing processes can be important for the optimization of pressurized fluid injection operations in the deep underground rock mass. Active and passive seismic monitoring techniques have been used in the field for tracking or mapping the propagating hydraulic fracture. Although both these monitoring techniques provide valuable information about the generated fracture network, it is difficult for either technique to comprehensibly identify the different processes associated with hydraulic fracturing. The combined active and passive monitoring has the potential for better characterization of the complex hydraulic fracturing phenomena. In this study, laboratory hydraulic fracturing experiments with combined active and passive seismic monitoring were conducted on true triaxially loaded Barre granite cubes with different fluid injection rates. The seismic inelastic fracturing was detected by 16 passive acoustic emission sensors, where 3678 and 2370 seismic source events were detected for the high and low injection rate experiments, respectively. For active monitoring, strong variations in the attributes of signals were observed which were transmitted through four source–receiver pairs, placed both perpendicular and parallel to the generated hydraulic fracture. Positive velocity changes were observed for active sensor pairs with ray paths passing through the generated hydraulic fracture indicating fluid permeation, whereas isolated dry deformation was characterized by a slight but permanent velocity decrease. Compared to velocity, the energy of the active signals was 1–2 orders of magnitude more sensitive to different hydraulic fracturing processes. However, the sensitivity and signatures of the active signal attributes were found to be dependent on the frequency range and direction of ray path with respect to the location of the generated fracture network. Using the coupled evaluation of the active and passive signals we were able to systematically identify various hydraulic fracturing processes including: (1) aseismic deformation, (2) fracture initiation and fluid permeation, (3) pressure build-up, (4) fracture propagation and (5) pressure release and leak-off. The results of this study showed that combining the respective advantages of active and passive seismic techniques and using both of them to monitor the failure processes can facilitate a more comprehensive understanding and better control of the hydraulic stimulations in subsurface operations.
Climate Informatics
The impacts of present and potential future climate change will be one of the most important scientific and societal challenges in the 21st century. Given observed changes in temperature, sea ice, and sea level, improving our understanding of the climate system is an international priority. This system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. But with an ever-growing supply of climate data from satellites and environmental sensors, the magnitude of data and climate model output is beginning to overwhelm the relatively simple tools currently used to analyze them. A computational approach will therefore be indispensable for these analysis challenges. This chapter introduces the fledgling research discipline climate informatics: collaborations between climate scientists and machine learning researchers in order to bridge this gap between data and understanding. We hope that the study of climate informatics will accelerate discovery in answering pressing questions in climate science.
Characterization of Intrinsic Fiber Optic Temperature Sensors by In-core and Furnace Testing
Increased research and development in nuclear technology has raised the demand for novel sensors and instrumentation to meet data objectives, and survive in different conditions and environments, beyond conventional light water reactor (LWR) environments. Expediting the deployment of advanced nuclear technologies by developing, demonstrating, and qualifying advanced reactor fuel forms necessitates a deeper understanding of how irradiation affects fuels and materials' performance. To achieve a more comprehensive understanding of fuels and materials performance, researchers require more specialized experiments and measurements. The demand for innovative sensors to support nuclear fuel development arises from the complexity of materials' behavior under irradiation and the challenges of deploying instrumentation in Material Test Reactors (MTRs) for irradiation tests. Additionally, measurements of material properties require integrated measurement systems to characterize thermal properties, mechanical properties, chemistry, and microstructure [1]. Among the potential measurement techniques, optical fiber-based sensors have been identified as potential sensors to measure different physical phenomena such as temperature, strain, pressure, and fluid level. Optical fiber sensors have the capability to provide multi-sensing and multiplexing instrumentation, allowing the measurement of different physical parameters within a single sensor configuration, and transmitting data collected at multiple locations through a single fiber. They offer immunity to electromagnetic interference, electrical passivity, compatibility with various sensing methodologies, and cost-effectiveness. Beyond their widespread use in telecommunications, silica fiber-based instruments are utilized in industrial applications, even at temperatures reaching 300?400°C, such as distributed temperature sensing in oil and gas recovery. The Department of Energy (DOE) is interested in using fiber optics to support fuel cycle development [2]. Fiber optics are an excellent candidate for harsh environment sensing, including sensing at very high temperatures (1900oC for sapphire optical fibers). Distributed fiber optic sensing has been deployed in other harsh environments like coal gasification plants [3]. Distributed strain sensing, which operates similarly to distributed temperature sensing, has been deployed to monitor underground mines and fibers have been imbedded in soil to monitor sink-hole development [4][5]. The application of fiber optic sensors to advanced reactor development is a promising area of research.
Advanced Manufactured Strain Sensors for Extreme Environments
Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties). To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.
Advanced Manufactured Strain Sensors for Extreme Environments
Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties).To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.
Clustering Acoustic Background Noise in the Stratosphere Using Machine Learning
Infrasound, characterized by low-frequency sound inaudible to humans (<20 Hz), emanates from natural and anthropogenic sources. Its efficacy for monitoring phenomena necessitates robust sensing networks. Traditional ground-based infrasound sensors have limitations due to atmospheric dynamics and noise interference. Balloon-bore sensors have emerged as an alternative, offering reduced noise and improved capabilities. This study bridges clustering algorithms with balloon borne infrasound data, a domain yet to be explored. Employing K-Means, DBSCAN, and GMM algorithms on normalized and reshaped data and only normalized data from a New Zealand-based NASA balloon flight, insights into background noise at stratospheric altitudes were revealed. Despite challenges arising from distinguishing signals amid unique background noise, this research provides vital reference material for noise analysis and calibration. Beyond infrasound event capture, the dataset enriches comprehension of background noise characteristics in the southern hemisphere.
Optical Electronic Bragg Reflection Sensor System with Hydrodynamic Flow Applications
This project, as described in the following report, involved design and fabrication of fiber optic sensors for the detection and measurement of dynamic fluid density variations. These devices are created using UV (ultraviolet) ablation and generally modified transverse holographic fiber grating techniques. The resulting phase gratings created on or immediately underneath the flat portion of D-shaped optical waveguides are characterized as evanescent field sensing devices. The primary applications include the sensor portion of a real-time localized or distributed measurement system for hydrodynamic flow, fluid density measurements, and phase change phenomena. Several design modifications were implemented in an attempt to accomplish the tasks specified in our original proposal. In addition, we have established key collaborative relationships with numerous people and institutions.
Atmospheric Science Experiment for Mars: ATMIS for the Netlander 2005 Mission
ATMIS (Atmospheric and Meteorological Instrumentation System) is a versatile suite of atmospheric instrumentation to be accommodated onboard the Netlander Mission slated for launch in 2005. Four Netlanders are planned to form a geophysical measurement network on the surface of Mars. The atmospheric sciences are among the scientific disciplines benefiting most of the network concept. The goal of the ATMIS instrument is to provide new data on the atmospheric vertical structure, regional and global circulation phenomena, the Martian Planetary Boundary Layer (PBL) and atmosphere-surface interactions, dust storm triggering mechanisms, as well as the climatological cycles of H2O, dust and CO2. To reach the goal of characterization of a number of phenomena exhibiting both spatial and temporal variations, simultaneous observations of multiple variables at spatially displaced sites Deforming a network D are required. The in situ observations made by the ATMIS sensors will be supported by extensive modeling efforts. Additional information is contained in the original extended abstract.