TiO2-Coated Optical Fibers for Distributed pH Monitoring at High Pressures and Temperatures
SPIE Defense and Commercial Sensing, Orlando, FL, April 30-May 4, 2023
Shumski, Alexander↗
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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.
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Regulation of Renewable Energy Sources to Optimal Power Flow Solutions Using ADMM
This paper considers power distribution systems featuring renewable energy sources (RESs), and develops a distributed optimization method to steer the RES output powers to solutions of AC optimal power flow (OPF) problems. The design of the proposed method leverages suitable linear approximations of the AC-power flow equations, and is based on the Alternating Direction Method of Multipliers (ADMM). Convergence of the RES-inverter output powers to solutions of the OPF problem is established under suitable conditions on the stepsize as well as mismatches between the commanded setpoints and actual RES output powers. In a broad sense, the methods and results proposed here are also applicable to other distributed optimization problem setups with ADMM and inexact dual updates.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Overview of the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES)
Substantial uncertainties still exist in the scientific understanding of the possible interactions between urban and natural (biogenic) emissions in the production and transformation of atmospheric aerosol and the resulting impact on climate change. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Carbonaceous Aerosol and Radiative Effects Study (CARES) carried out in June 2010 in Central Valley, California, was a comprehensive effort designed to improve this understanding. The primary objective of the field study was to investigate the evolution of secondary organic and black carbon aerosols and their climate-related properties in the Sacramento urban plume as it was routinely transported into the forested Sierra Nevada foothills area. Urban aerosols and trace gases experienced significant physical and chemical transformations as they mixed with the reactive biogenic hydrocarbons emitted from the forest. Two heavily-instrumented ground sites - one within the Sacramento urban area and another about 40 km to the northeast in the foothills area - were set up to characterize the evolution of meteorological variables, trace gases, aerosol precursors, aerosol size, composition, and climate-related properties in freshly polluted and 'aged' urban air. On selected days, the DOE G-1 aircraft was deployed to make similar measurements upwind and across the evolving Sacramento plume in the morning and again in the afternoon. The NASA B-200 aircraft, carrying remote sensing instruments, was also deployed to characterize the vertical and horizontal distribution of aerosols and aerosol optical properties within and around the plume. This overview provides: a) the scientific background and motivation for the study, b) the operational and logistical information pertinent to the execution of the study, c) an overview of key observations and initial results from the aircraft and ground-based sampling platforms, and d) a roadmap of planned data analyses and focused modeling efforts that will facilitate the integration of new knowledge into improved representations of key aerosol processes in climate models.
54 ENVIRONMENTAL SCIENCES↗
Auto-adaptive Harris corner detection algorithm based on entropy-improved block processing
Extracting well distributed control points (CPs) is a very challenging task for remote sensing image registration, particularly for large high-resolution images over heterogeneous landscape. Based on image analysis such as edge detection, corner detection, and information theory, a new CP detection approach is proposed to select high- quality, evenly distributed CPs. The Entropy-Block-Based variant of the Harris Corner Detector (EBB-HCD) is achieved by dividing the image into blocks and by allocating the number of CP's based upon the entropy of each block. While the block-based strategy improves the CP balance problem, a factor calculated from entropy avoids overdetection. We conducted a comparison study utilizing the well-known Harris Corner Detector (HCD) and an implementation of the Block-Based Harris Corner Detector (BB-HCD). Experimental results indicate that using EBB-HCD to find the CPs improves the overall alignment accuracy during registration compared with HCD or BB-HCD.
Sun, Yihang↗
Behavior and mechanisms of Doppler wind lidar error in varying stability regimes
Abstract. Wind lidars are widespread and important tools in atmospheric observations. An intrinsic part of lidar measurement error is due to atmospheric variability in the remote-sensing scan volume. This study describes and quantifies the distribution of measurement error due to turbulence in varying atmospheric stability. While the lidar error model is general, we demonstrate the approach using large ensembles of virtual WindCube V2 lidar performing a profiling Doppler-beam-swinging scan in quasi-stationary large-eddy simulations (LESs) of convective and stable boundary layers. Error trends vary with the stability regime, time averaging of results, and observation height. A systematic analysis of the observation error explains dominant mechanisms and supports the findings of the empirical results. Treating the error under a random variable framework allows for informed predictions about the effect of different configurations or conditions on lidar performance. Convective conditions are most prone to large errors (up to 1.5 m s−1 in 1 Hz wind speed in strong convection), driven by the large vertical velocity variances in convective conditions and the high elevation angle of the scanning beams (62∘). Range-gate weighting induces a negative bias into the horizontal wind speeds near the surface shear layer (−0.2 m s−1 in the stable test case). Errors in the horizontal wind speed and direction computed from the wind components are sensitive to the background wind speed but have negligible dependence on the relative orientation of the instrument. Especially during low winds and in the presence of large errors in the horizontal velocity estimates, the reported wind speed is subject to a systematic positive bias (up to 0.4 m s−1 in 1 Hz measurements in strong convection). Vector time-averaged measurements can improve the behavior of the error distributions (reducing the 10 min wind speed error standard deviation to <0.3 m s−1 and the bias to <0.1 m s−1 in strong convection) with a predictable effectiveness related to the number of decorrelated samples in the time window. Hybrid schemes weighting the 10 min scalar- and vector-averaged lidar measurements are shown to be effective at reducing the wind speed biases compared to cup measurements in most of the simulated conditions, with time averages longer than 10 min recommended for best use in some unstable conditions. The approach in decomposing the error mechanisms with the help of the LES flow field could be extended to more complex measurement scenarios and scans.
17 WIND ENERGY↗
Characterizing Aerosol Distributions and Optical Properties Using the NASA Langley High Spectral Resolution Lidar
The objective of this project was to provide vertically and horizontally resolved data on aerosol optical properties to assess and ultimately improve how models represent these aerosol properties and their impacts on atmospheric radiation. The approach was to deploy the NASA Langley Airborne High Spectral Resolution Lidar (HSRL) and other synergistic remote sensors on DOE Atmospheric Science Research (ASR) sponsored airborne field campaigns and synergistic field campaigns sponsored by other agencies to remotely measure aerosol backscattering, extinction, and optical thickness profiles. Synergistic sensors included a nadir-viewing digital camera for context imagery, and, later in the project, the NASA Goddard Institute for Space Studies (GISS) Research Scanning Polarimeter (RSP). The information from the remote sensing instruments was used to map the horizontal and vertical distribution of aerosol properties and type. The retrieved lidar parameters include profiles of aerosol extinction, backscatter, depolarization, and optical depth. Products produced in subsequent analyses included aerosol mixed layer height, aerosol type, and the partition of aerosol optical depth by type. The lidar products provided vertical context for in situ and remote sensing measurements from other airborne and ground-based platforms employed in the field campaigns and was used to assess the predictions of transport models. Also, the measurements provide a data base for future evaluation of techniques to combine active (lidar) and passive (polarimeter) measurements in advanced retrieval schemes to remotely characterize aerosol microphysical properties. The project was initiated as a 3-year project starting 1 January 2005. It was later awarded continuation funding for another 3 years (i.e., through 31 December 2010) followed by a 1-year no-cost extension (through 31 December 2011). This project supported logistical and flight costs of the NASA sensors on a dedicated aircraft, the subsequent analysis and archival of the data, and the presentation of results in conferences, workshops, and publications. DOE ASR field campaigns supported under this project included: • MAX-Mex /MILAGRO (2006), • TexAQS 2006/GoMACCS (2006), • CHAPS (2007), • RACORO (2009), and • CARE/CalNex (2010). In addition, data acquired on HSRL airborne field campaigns sponsored by other agencies were used extensively to fulfill the science objectives of this project and the data acquired have been made available to other DOE ASR investigators upon request.
99 GENERAL AND MISCELLANEOUS↗
Analysis of Niobium Electropolishing Using a Generalized Distribution of Relaxation Times Method
Using electrochemical impedance spectroscopy, we have devised a method of sensing the microscopic surface conditions on the surface of niobium as it is undergoing an electrochemical polishing (EP) treatment. The method uses electrochemical impedance spectroscopy (EIS) to gather information on the surface state of the electrode without disrupting the polishing reaction. The EIS data is analyzed using a so-called distribution of relaxation times (DRT) method. Using DRT, the EIS data can be deconvolved into discrete relaxation time peaks without any a priori knowledge of the electrode dynamics. By analyzing the relaxation time peaks, we are able to distinguish two distinct modes of the EP reaction. As the polishing voltage is increased, the electrode transitions from the low voltage EP mode, characterized by a single relaxation time peaks, to the high voltage EP mode, characterized by two relaxation time peaks. We theorize that this second peak is caused by the formation of an oxide layer on the electrode. We also find that this oxide induced peak transitions from to a negative relaxation time, which is indicative of a blocking electrode process. By analyzing EPed samples, we show that samples polished in the low voltage mode have significantly higher surface roughness due to grain etching and faceting. We find that the surface roughness of the samples only improves when the oxide film peak is present and in the negative relaxation time region. This shows that EIS combined with DRT analysis can be used to predict etching on EPed Nb. This method can also be performed before or during the EP, which could allow for adjustment of polishing parameters to guarantee a smooth cavity surface finish.
43 PARTICLE ACCELERATORS↗
Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation
ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.
Glubokovskikh, Stanislav↗
Ubiquitous Low-Cost Functionalized Multi-Walled Carbon Nanotube Sensors for Distributed Methane Leak Detection
This paper presents a highly sensitive, energy efficient and low-cost distributed methane (CH 4 ) sensor system (DMSS) for continuous monitoring, detection, and localization of CH 4 leaks in natural gas infrastructure, such as transmission and distribution pipelines, wells, and production pads. The CH 4 sensing element, a key component of the DMSS, consists of a metal oxide nanocrystal (MONC) functionalized multi-walled carbon nanotube (MWCNT) mesh which, in comparison to existing literature, shows stronger relative resistance change while interacting with lower parts per million (ppm) concentration of CH 4 . A Gaussian plume triangulation algorithm has been developed for the DMSS. Given a geometric model of the surrounding environment the algorithm can precisely detect and localize a CH 4 leak as well as estimate its mass emission rate. A UV-based surface recovery technique making the sensor recover 10 times faster than the reported ones is presented for the DMSS. In conclusion, a control algorithm based on the UV-accelerated recovery is developed which facilitates faster leak detection.
47 OTHER INSTRUMENTATION↗
Change-point Detection and Image Segmentation for Time Series of Astrophysical Images
Many astrophysical phenomena are time-varying, in the sense that their intensity, energy spectrum, and/or the spatial distribution of the emission suddenly change. This paper develops a method for modeling a time series of images. Under the assumption that the arrival times of the photons follow a Poisson process, the data are binned into 4D grids of voxels (time, energy band, and x-y coordinates), and viewed as a time series of non-homogeneous Poisson images. The method assumes that at each time point, the corresponding multiband image stack is an unknown 3D piecewise constant function including Poisson noise. It also assumes that all image stacks between any two adjacent change points (in time domain) share the same unknown piecewise constant function. The proposed method is designed to estimate the number and the locations of all of the change points (in time domain), as well as all of the unknown piecewise constant functions between any pairs of the change points. The method applies the minimum description length principle to perform this task. A practical algorithm is also developed to solve the corresponding complicated optimization problem. Simulation experiments and applications to real data sets show that the proposed method enjoys very promising empirical properties. Applications to two real data sets, the XMM observation of a flaring star and an emerging solar coronal loop, illustrate the usage of the proposed method and the scientific insight gained from it.
79 ASTRONOMY AND ASTROPHYSICS↗
Technical Performance and Cost Optimization of Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) for Wide-area Surveillance and Identification of Marine Life at Marine Energy Installations
Florida Atlantic University developed an underwater optical monitoring system prototype - Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) - suitable for marine energy full project lifecycle observation (baseline, commissioning, and decommissioning), with an automated real-time classification of marine animals. With precursor 2014 DOE funding (award DE-EE0006787), a prototype UMSLI was demonstrated in a controlled laboratory environment and achieved a TRL 6. This EERE DE-EE0007828 award aimed to both increase the TRL of the UMSLI by improving the technology performance (e.g., increase distance of marine animal target detection capability, add additional species classification capabilities, improve the system performance during the day, etc.) and reduce the cost. The UMSLI presents a novel application of underwater distributed Light Detection And Ranging (LiDAR), an advanced remote sensing method that uses light in the form of laser pulses for an application, this paired with an algorithm provides 360 degrees underwater detection, imaging, and classification of marine life. This solution for underwater monitoring of biota preserves the advantages of traditional optical and acoustic solutions while overcoming many associated disadvantages for marine energy site environmental monitoring, such as difficulties in species detection and classification in low light or night and turbid environments. This new approach is a purposefully designed, reconfigurable adaptation of an existing class 3B laser technology into one UMSLI instrument that can be easily mounted on or around different classes of marine energy equipment, such as devices to capture ocean current energy or wave energy. The system uses relatively low average power, utilizes far-red (> 635nm) laser illumination to be invisible and eye-safe to marine animals, is compact, and cost-effective. The equipment is designed for long-term, maintenance-free operations (i.e., current design is targeting more than 7 days continuous operation), to inherently generate a sparse primary dataset that only includes detected anomalies, and to allow robust real-time automated animal classification and identification with a low data bandwidth requirement. The technology’s overarching goal for application, is a system that can be deployed to collect pre-installation baseline species observations at a proposed marine energy deployment site with minimal post-processing overhead. The envisioned system will also produce high-resolution imagery of marine animals through a wide range of conditions and support automated tracking and notification of the presence of managed animals within established perimeters of marine energy equipment to satisfy deployed marine energy projects’ endangered and threatened species monitoring requirements. Through the current project, we demonstrated the UMSLI prototype in an operational environment and increased the UMSLI’s Technology Readiness Level from 6 to 7. The project resulted in many novel technologies, including: 1) an eye-safe red laser based, low-cost LiDAR system that can detect targets up to 10 meters distance; 2) the GAN-based machine learning underwater LiDAR image enhancement technique (this is the first known application of GAN technique in underwater LiDAR); 3) LiDAR-based real-time automated detection capabilities; and 4) a template matching based automated classification tool. These technologies build a solid foundation for future efforts to develop an extended range electro-optical monitoring system suitable for marine energy deployments. In addition to technology development, a key lesson learned is that addressing regulatory and safety requirements must be front and center in any marine energy monitoring applications.
16 TIDAL AND WAVE POWER↗
Distributed Fiber Sensor Interrogators for Multi-Parameter Monitoring
University of Pittsburgh Infrastructure Sensing Collaboration Workshop, Pittsburgh, PA, August 25, 2022
Lalam, Nageswara↗
Template‐Directed Growth of Palladium Nanoparticles in Holey Single‐Layer Graphene for High‐Performance Room‐Temperature Hydrogen Sensing
Holey graphene (HG), formed by introducing nanoscale perforations into graphene sheets, combines the structural advantages of continuous sp 2 conjugation with the beneficial effects of high surface area and enhanced chemical reactivity associated with nanoscopic holes. Conventional HG fabrication methods often rely on harsh oxidative treatments that compromise graphene's intrinsic electronic properties by disrupting its sp 2 conjugation. A new approach is introduced to fabricate HG directly from single-layer graphene (SLG), using two-dimensional covalent organic frameworks (COFs) as a template followed by controlled oxygen plasma etching. This method preserves the integrity of the SLG's sp 2 network while producing well-defined holes with an average diameter of 2.7 nm. These hole edges act as reactive sites that facilitate the confined, autoreductive growth of palladium nanoparticles (PdNPs) without external reducing agents. The confined hole geometry prevents NP agglomeration and ensures a uniform size distribution. The resulting Pd@HG hybrid exhibits exceptional chemiresistive hydrogen sensing characteristics, including ultrahigh sensitivity, low detection limits, rapid response and recovery, and long-term stability under both dry and humid conditions. Mechanistic investigations reveal a two-step sensing process involving surface redox interactions and hydrogen absorption into the PdNP lattices. This strategy presents a scalable platform for integrating metal NPs within conductive carbon frameworks for advanced sensing applications.
chemical vapor deposition↗
Mid-Infrared Interband Cascade and Quantum Cascade Lasers for Chemical Sensing
Explore the source record for details and available documents.
36 MATERIALS SCIENCE↗
INFERRING THE ECCENTRICITY DISTRIBUTION
Standard maximum-likelihood estimators for binary-star and exoplanet eccentricities are biased high, in the sense that the estimated eccentricity tends to be larger than the true eccentricity. As with most non-trivial observables, a simple histogram of estimated eccentricities is not a good estimate of the true eccentricity distribution. Here, we develop and test a hierarchical probabilistic method for performing the relevant meta-analysis, that is, inferring the true eccentricity distribution, taking as input the likelihood functions for the individual star eccentricities, or samplings of the posterior probability distributions for the eccentricities (under a given, uninformative prior). The method is a simple implementation of a hierarchical Bayesian model; it can also be seen as a kind of heteroscedastic deconvolution. It can be applied to any quantity measured with finite precision-other orbital parameters, or indeed any astronomical measurements of any kind, including magnitudes, distances, or photometric redshifts-so long as the measurements have been communicated as a likelihood function or a posterior sampling.
79 ASTRONOMY AND ASTROPHYSICS↗
Suitability of Type-II Fiber Bragg Gratings in Silica Optical Fiber for Temperature Sensing in TREAT
Optical fibers provide a variety of options for instrumentation in reactor environments. Optical fibers can be used to measure multiple physical phenomena including, temperature, strain, pressure, and fluid level. In addition to the various sensing applications, optical fibers are immune to electromagnetic interference, have a small footprint (~100 μm), and a fast response. The Department of Energy and Idaho National Laboratory have considered optical fibers for use as in-pile instrumentation in the Transient Reactor Test Facility (TREAT). TREAT was designed to test reactor fuels under accident conditions by replicating accident conditions for a variety of reactor transients, such as those associated with a loss of coolant accident (LOCA). This work investigates silica fiber optic temperature sensors with inscribed type-II fiber Bragg gratings (FBGs) under conditions similar to those that would be experienced in a TREAT transient. Separate effects testing was used to test the sensors under high-temperature step transients and under irradiation up to a total fluence similar to that of TREAT. Specifically, this work investigates distributed temperature measurements, using the Optical Frequency Domain Reflectometry (OFDR) sensing technique, using a Luna Innovations Optical Backscatter Reflectometer (OBR) 4600, with silica optical fibers inscribed with type-II fiber Bragg gratings (FBGs). In conclusion, separate effects testing of type-II FBGs in silica optical fiber, to high temperature and to neutron fluences that are an order of magnitude larger than fluences that are anticipated for TREAT tests, demonstrate that type-II FBGs in silica optical fiber hold great promise for high-temperature reactor instrumentation in TREAT.
McCary, Kelly↗
Remote Sensing and Sea-Truth Measurements of Methane Flux to the Atmosphere (HYFLUX project)
A multi-disciplinary investigation of distribution and magnitude of methane fluxes from seafloor gas hydrate deposits in the Gulf of Mexico was conducted based on results obtained from satellite synthetic aperture radar (SAR) remote sensing and from sampling conducted during a research expedition to three sites where gas hydrate occurs (MC118, GC600, and GC185). Samples of sediments, water, and air were collected from the ship and from an ROV submersible using sediments cores, niskin bottles attached to the ROV and to a rosette, and an automated sea-air interface collector.
03 NATURAL GAS↗
Probabilistic Change Detection Framework for Analyzing Settlement Dynamics Using Very High-resolution Satellite Imagery
Global human population growth and an increasingly urbanizing world have led to rapid changes in human settlement landscapes and patterns. Timely monitoring and assessment of these changes and dissemination of accurate information is important for policy makers, city planners, and humanitarian relief workers. Satellite imagery provides useful data for the aforementioned applications, and remote sensing can be used to identify and quantify change areas. We explore a probabilistic framework to identify changes in human settlements using very high-resolution satellite imagery. As compared to predominantly pixel-based change detection systems which are highly sensitive to image registration errors, our grid (block) based approach is more robust to registration errors. The presented framework is an automated change detection system applicable to both panchromatic and multi-spectral imagery. The detection system provides comprehensible information about change areas, and minimizes the post-detection thresholding procedure often needed in traditional change detection algorithms.
99 GENERAL AND MISCELLANEOUS↗