SEARCH · Search NASA
Results for “Distributed Sensing”
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.
Using Distributed Acoustic and Temperature Sensing to Characterize the Rapidly Changing Nearshore Arctic Ocean (PEMDATS)
Explore the source record for details and available documents.
Characterizing the Nearshore Arctic Seabed Using Distributed Acoustic and Temperature Sensing (DATS)
Explore the source record for details and available documents.
Monitoring Arctic Coastal Processes with Seafloor Distributed Acoustic and Temperature Sensing
Explore the source record for details and available documents.
Distributed Fiber-Optic Sensing in a High-Temperature Solid-Oxide Fuel Cell
Presented by NETL at SPIE Optics and Photonics, 08/16
System, method, and computer-accessible medium for remote sensing of the electrical distribution grid with hypertemporal imaging
An exemplary system, method, and computer-accessible medium for determining a property(ies) regarding an electrical grid(s) can be provided, which can include, for example, receiving a video(s) of the electrical grid(s), determining a flicker(s) in the electrical grid(s) based on the video(s), and determining the property(ies) based on the flicker(s). The flicker(s) can be a 120 Hertz flicker. The flicker(s) can be a flicker in a light(s) recorded in the video(s). A frequency and a phase of the flicker(s) can be determined.
Entanglement-enhanced optomechanical sensor array with application to dark matter searches
Abstract Squeezed light has long been used to enhance the precision of a single optomechanical sensor. An emerging set of proposals seeks to use arrays of optomechanical sensors to detect weak distributed forces, for applications ranging from gravity-based subterranean imaging to dark matter searches; however, a detailed investigation into the quantum-enhancement of this approach remains outstanding. Here, we propose an array of entanglement-enhanced optomechanical sensors to improve the broadband sensitivity of distributed force sensing. By coherently operating the optomechanical sensor array and distributing squeezing to entangle the optical fields, the array of sensors has a scaling advantage over independent sensors (i.e., $$\sqrt{M}\to M$$ M → M , where M is the number of sensors) due to coherence as well as joint noise suppression due to multi-partite entanglement. As an illustration, we consider entanglement-enhancement of an optomechanical accelerometer array to search for dark matter, and elucidate the challenge of realizing a quantum advantage in this context.
Two-mode squeezing over deployed fiber coexisting with conventional communications
Explore the source record for details and available documents.
Distributed Temperature Profiles of Silicon Carbide Catalyst Bed in a Microwave Reactor using Fiber-optic Sensor
Microwave heating is of great interest for reducing greenhouse gas emissions of catalytic chemical conversion processes because it can heat up the reactants rapidly and efficiently and accelerate reaction rates. In microwave-assisted catalytic thermochemical conversion processes, accurate internal temperature measurement would help facilitate effective process control. Metallic thermocouples interfere and spark in the microwave heating environment, so they are not an option. Infrared pyrometers typically provide a single temperature value by averaging over a finite surface area of the catalyst bed. In this work, we use fiber-optic sensors passing through the catalyst bed to provide more accurate temperatures along the height of the catalyst bed. The fiber optic sensors are immune to the electromagnetic microwave radiation and provide temperature profiles along their length. Here, custom fiber-optic sensors were coupled to the optical distributed temperature sensing devices to measure the temperature profiles along the height of the catalyst bed at high temperatures with ~1 mm spatial resolution. The sensing devices use optical frequency domain reflectometry (OFDR) technique for distributed temperature measurement. This work shows the temperature profiles along the height of the silicon carbide powder catalyst bed in the variable and fixed frequency microwave reactors.
Nanocrystalline ferrites Ni{sub x}Zn{sub 1-x}Fe{sub 2}O{sub 4}: Influence of cation distribution on acidic and gas sensing properties
This work is devoted to a detailed analysis of the interconnection between composition, cation distribution and acidic properties of the surface of nanocrystalline ferrites Ni{sub x}Zn{sub 1-x}Fe{sub 2}O{sub 4} obtained by aerosol pyrolysis. The detailed analysis of the Moessbauer spectra allows us to determine the distribution of cations between tetrahedral and octahedral positions in spinel structure. Depending on samples composition, the tetrahedral positions can be occupied by only Fe{sup 3+} cations (inverse spinel, x{>=}0.4) or by Fe{sup 3+} and Zn{sup 2+} cations (mixed spinel, x=0, 0.2). Increasing the nickel concentration in the ferrite leads to decrease in the number of strong acid centers on the surface. It was found that the decrease in the contribution of strong surface acid sites leads to an increase in sensory sensitivity of the ferrite towards ammonia. For ethanol detection an inverse relationship between sensor signal and surface acidity was observed. - Graphical abstract: (a) n- and p-types change in electrical resistance and (b) sensor signal of Ni{sub x}Zn{sub 1-x}Fe{sub 2}O{sub 4} towards NH{sub 3} and ethanol vapor vs. the part of strong acid sites. Highlights: > Relationship between composition, cation distribution, and acidity in nanocrystalline Ni{sub x}Zn{sub 1-x}Fe{sub 2}O{sub 4}. > Degree of inversion of spinel is determined by Moessbauer spectroscopy. > Increase of nickel content leads to decrease in the number of strong acid centers. > This results in an increase in sensory sensitivity of the ferrite towards ammonia. > Relationship between sensor signal to ethanol and surface acidity is opposite.
Remote Sensing-Based, 5-m, Vegetation Distributions, Kougarok Study Site, Seward Peninsula, Alaska, ca. 2009 - 2016
A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5~m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. This data was developed using the fusion of hyperspectral, multispectral, and terrain datasets. The current data is located in the Kougarok watershed but we plan to expand this over the Seward Peninsula. Additional metadata and vegetation maps included as two *.pdf, one *.txt, one *.nc, and three *.tif files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
Corrosion Sensors for Structural Health Monitoring of Oil and Natural Gas Infrastructure: A Review
Corrosion has been a great concern in the oil and natural gas industry costing billions of dollars annually in the U.S. The ability to monitor corrosion online before structural integrity is compromised can have a significant impact on preventing catastrophic events resulting from corrosion. This article critically reviews conventional corrosion sensors and emerging sensor technologies in terms of sensing principles, sensor designs, advantages, and limitations. Conventional corrosion sensors encompass corrosion coupons, electrical resistance probes, electrochemical sensors, ultrasonic testing sensors, magnetic flux leakage sensors, electromagnetic sensors, and in-line inspection tools. Emerging sensor technologies highlight optical fiber sensors (point, quasi-distributed, distributed) and passive wireless sensors such as passive radio-frequency identification sensors and surface acoustic wave sensors. Emerging sensors show great potential in continuous real-time in-situ monitoring of oil and natural gas infrastructure. Distributed chemical sensing is emphasized based on recent studies as a promising method to detect early corrosion onset and monitor corrosive environments for corrosion mitigation management. Additionally, challenges are discussed including durability and stability in extreme and harsh conditions such as high temperature high pressure in subsurface wellbores.
GFOC Project results: High Temperature / High Pressure, Hydrogen Tolerant Optical Fiber
Tests results are given for exposure of multimode optical fiber to high temperatures (300 deg. C) and high partial pressure (15 bar) hydrogen. These results demonstrate that fluorine down doped optical fibers are much more hydrogen tolerant than traditional germanium doped multimode optical fibers. Also demonstrated is the similar hydrogen tolerance of carbon coated and non-carbon coated fibers. Model for reversible H2 impact in fiber versus T{sup o}C and H2 pressure is given. These results have significant impact for the longevity of use for distributed temperature sensing applications in harsh environments such as geothermal wells.
Predicting distribution of malaria vector larval habitats in Ethiopia by integrating distributed hydrologic modeling with remotely sensed data
Abstract Larval source management has gained renewed interest as a malaria control strategy in Africa but the widespread and transient nature of larval breeding sites poses a challenge to its implementation. To address this problem, we propose combining an integrated high resolution (50 m) distributed hydrological model and remotely sensed data to simulate potential malaria vector aquatic habitats. The novelty of our approach lies in its consideration of irrigation practices and its ability to resolve complex ponding processes that contribute to potential larval habitats. The simulation was performed for the year of 2018 using ParFlow-Common Land Model (CLM) in a sugarcane plantation in the Oromia region, Ethiopia to examine the effects of rainfall and irrigation. The model was calibrated using field observations of larval habitats to successfully predict ponding at all surveyed locations from the validation dataset. Results show that without irrigation, at least half of the area inside the farms had a 40% probability of potential larval habitat occurrence. With irrigation, the probability increased to 56%. Irrigation dampened the seasonality of the potential larval habitats such that the peak larval habitat occurrence window during the rainy season was extended into the dry season. Furthermore, the stability of the habitats was prolonged, with a significant shift from semi-permanent to permanent habitats. Our study provides a hydrological perspective on the impact of environmental modification on malaria vector ecology, which can potentially inform malaria control strategies through better water management.
University of Illinois Campus Deep Direct-Use Feasibility Study - Subsurface Temperature Profile
High resolution fiber-optic distributed temperature sensing logs from the Illinois Basin Decatur Project (IBDP) in Decatur, IL were used to model the thermal profile in the Illinois Basin.
A multi-scale temperature-based strategy to map hydrologic exchange flows in highly dynamic systems
Mapping and quantifying hydrologic exchange flows (HEFs) is critical to environmental monitoring and remediation at contaminated sites; however, these objectives are challenging in highly dynamic systems, e.g., along dam-regulated rivers, where HEFs vary rapidly. Direct seepage measurements are labor-intensive and difficult to automate, whereas indirect (e.g., thermal) and remote sensing methods have potential to allow continuous monitoring with limited field effort. We present a preliminary assessment of a multi-scale temperature-based strategy for monitoring HEFs along the Hanford Reach of the Columbia River, in eastern WA, United States. Five thermal methods were assessed. First, a vertical temperature profile (VTP) was installed into the streambed. The VTP data were analyzed using a data assimilation algorithm designed for automated real-time estimation in dynamic systems. Second, a thermal infrared (TIR) camera was used in roving surveys to identify seeps. Third, a TIR camera was stationed at the VTP site to collect images at 1-h intervals. Together, the two TIR datasets provided a basis to assess the potential for drone-based TIR. Fourth, temperature was measured at the sediment/water interface to assess fiber-optic distributed temperature sensing. Fifth, imagery from the ECOSTRESS satellite mission was acquired to assess the potential of spaceborne thermal monitoring. Based on our preliminary assessment, VTP, TIR, and bed temperature measurements provide complementary spatial coverage, temporal sampling, and resolution; these methods have potential for long-term, automated monitoring of HEFs. The publicly available spaceborne imagery, however, proved inadequate because of insufficient spatial resolution and data gaps resulting from cloud cover and revisit frequency.
Utah FORGE: Well 58-32 Stimulation Conference Paper and Data
The U.S. Department of Energy’s (U.S. DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is a field laboratory that provides a unique opportunity to develop and test new technologies for characterizing, creating and sustaining Enhanced Geothermal Systems (EGS) in a controlled environment. In 2018, the U.S. DOE selected a site in south-central Utah for the FORGE laboratory. Numerous geoscientific studies have been conducted in the region since the 1970s in support of geothermal development at Roosevelt Hot Springs. A vertical scientific well, 58-32, was drilled and tested to a depth of 2290 m (7515 ft) GL in 2017 on the FORGE site to provide additional characterization of the reservoir rocks. The well encountered a conductive thermal regime and a bottom hole temperature of 199degC (390degF). More than 2000 natural fractures were identified, but measured permeabilities are low, less than 30 micro-darcies. Induced fractures indicate that the maximum horizontal stress trends NNE-SSW, consistent with geologic and well observations from the surrounding area. Approximately 45 m (147 ft) at the base of the well was left uncased. A maximum wellhead pressure of 27.6 MPa (4000 psig) at an injection rate of ~1431 L/min (~9 bpm) was measured during stimulation testing in September 2017. Conventional diagnostic evaluations of the data suggest that hydraulic fracturing and shearing occurred. Estimates of the stress gradient for delta_h_min range from of 16.7 to 17.6 kPa/m (0.74 to 0.78 psi/ft). A gradient of 25.6 kPa/m (1.13psi/ft) was calculated for delta_V. In 2019, the 2017 open-hole stimulation in well 58-32 was repeated with injection rates up to 2385 L/min (15 bpm). Two additional stimulations were conducted in the cased portion of the well; one to stimulate critically stressed fractures and the second to test noncritically stressed fractures. Breakdown of the zone spanning critically-stressed fractures occurred at a surface pressure of approximately 29.0 MPa (4200 psig). Although stimulation of the noncritically stressed fractures was interrupted by failure of the bridge plug beneath the perforated interval, micro-seismic data suggests stimulation of the fractures may have been initiated at a surface pressure of 45.5 MPa (6600 psig). These stimulation results support the conclusion the Mineral Mountains granitoid is an appropriate host for EGS development. Micro-seismicity was monitored during the stimulations using surface and downhole instrumentation. Five seismometers and a nodal array of 150 seismic sensors were deployed on the surface. A Distributed Acoustic Sensing (DAS) cable and a string of 12 geophones were deployed in well 78-32, drilled to a depth of 998 m (3274 ft) GL. A broadband sensor and a high-temperature geophone were deployed in well 68-32, drilled to a depth of 303 m (994 ft) GL. More than 420 micro-seismic events were detected by the geophone string. Other instruments detected fewer events.