Search NASA⌕ Search

SEARCH · Search NASA

Results for “distributed sensor”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Enhanced Bottom Anode Monitoring in DC Electric Arc Furnaces Using Fiber-Optic Sensors

A pin style bottom anode employs conductive steel rods that serve as the pathway for the high electrical power through rammed refractory at the bottom of a DC Electric Arc Furnace (EAF). Anode wear during operation is important to monitor, as anode replacement is expensive and impacts EAF productivity. Liquid steel penetration into the un-sintered refractory layer can result from rapid electrical power ramp-up, dips in furnace temperature, or operating the anode for too long between EAF campaigns. In extreme cases, the liquid steel may penetrate the bottom of the furnace when anode wear progresses too close to the bottom shell, which is extremely dangerous and must be avoided. The current state of the art for monitoring bottom anode wear employs thermocouples imbedded in the anode pins at points in the anode. However, this approach is not sensitive enough to detect localized damage to the anode, especially when cracking occurs. Here, the present work utilizes fiber optic sensors to monitor the health of the anode, by creating a real-time spatially distributed temperature map of the anode. Unlike the traditional thermocouples, these sensors can be mounted at significantly greater depths, provide distributed temperature measurements, and can withstand temperatures of up to 900°C. Additionally, they are able to perform temperature measurements with a spatial resolution of 1.3 mm at a 5 Hz acquisition rate, providing unprecedented high-density real time monitoring of anode health and increasing the efficiency, and safety of EAF operation.

Bottom Anode↗
NASA NTRSDate not supplied

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗
NASA NTRS2025

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗
NASA NTRS1988

Fingertip-shaped optical tactile sensor for robotic applications

Progress is described regarding the development of a high-density, fiber-optic, fingertip-shaped tactile sensor specifically designed for application to dexterous robotics. The sensor operates on optical principles involving the frustration of total internal reflection at a waveguide/elastomer interface and generates a grey-scale tactile image that represents the normal forces of contact. The sensor contains 256 taxels (sensing sites) distributed in a dual-density pattern that includes a tactile fovea near the tip which measures 13 mm x 13 mm and contains 169 taxels. The details regarding the design and construction of this tactile sensor are presented, in addition to photographs of tactile imprints.

Begej, Stefan↗
NASA NTRS2002

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.

multipoint measurement sensor networks↗
NASA NTRS2007

Diurnal Lightning Distributions as Observed by the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS)

Data obtained from the OTD (April 1995 to March 2000) and LIS (December 1997 to December 2005) satellites (70 and 35 degree inclination low earth orbits, respectively) are used to statistically determine the number of flashes in the diurnal cycle both as a function of local and universal time. Also included are global flash density maps. The data is further subdivided by season, continental versus oceanic, night time versus day time, northern versus southern hemisphere, and other regions of interest such as the Brazilian rain forest and the Congo. The data includes corrections for detection efficiency and instrument view time. The data was compared with the "Carnegie Curve" and the diurnal global thunderstorm contributions from thunderday statistics fiom different continents as derived by Whipple and Scrase, 1936. Initial results indicate that the northern hemisphere fall (September to November) has a larger amplitude than the northern hemisphere spring (March to May). This may be due to the differences in the contribution of the Brazilian rain forest during these periods (the main lightning peak starts in September and ends in February with a secondary peak in April). For some areas of the world, the peak of the diurnal curve appears to be shifted to later in the evening.

Blakeslee, R. J.↗
NASA NTRS2007

Diurnal Lightning Distributions as Observed by the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS)

Data obtained from the OTD (April 1995 to March 2000) and LIS (December 1997 to December 2005) satellites (70 and 35 degree inclination low earth orbits, respectively) are used to statistically determine the number of flashes in the diurnal cycle both as a function of local and universal time. Also included are global flash density maps. The data are further subdivided by season, continental versus oceanic, night time versus day time, northern versus southern hemisphere, and other regions of interest. The data include corrections for detection efficiency and instrument view time. The data are compared with both the "Carnegie Curve" and the diurnal global thunderstorm contributions from thunderday statistics from different continents, and are found to agree closely in phase and amplitude with the global thunderday statistics. The analysis also indicates that the southern hemisphere spring (September to November) has larger amplitude than the southern hemisphere fall (March to May). This may be due to differences in the contribution from the Brazilian rain forest during these periods. In general, as highlighted by a difference analysis, more lightning is observed in local springtime than the fall for continental locations, while oceanic regions display an opposite effect. For some areas of the world, the peak of diurnal curve appears to be shifted to later in the evening.

Bailey, Jeff C.↗
NASA NTRS2007

Diurnal Lightning Distributions as Observed by the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS)

Data obtained from the Optical Transient Detector (April 1995 to March 2000) and the Lightning Imaging Sensor (December 1997 to December 2005) satellites (70 and 35 inclination low earth orbits, respectively) are used to statistically determine the number of flashes in the annual and seasonal diurnal cycle as a function of local and universal time. The data are further subdivided by season, land versus ocean, northern versus southern hemisphere, and other spatial (e.g., continents) and temporal (e.g., time of peak diurnal amplitude) categories. The data include corrections for detection efficiency and instrument view time. Continental results display strong diurnal variation, with a lightning peak in the late afternoon and a minimum in late morning. In regions of the world dominated by large mesoscale convective systems the peak in the diurnal curve shifts toward late evening or early morning hours. The maximum diurnal flash rate occurs in June-August, corresponding to the Northern Hemisphere summer, while the minimum occurs in December-February. Summer lightning dominates over winter activity and springtime lightning dominates over autumn activity at most continental locations. This latter behavior occurs especially strongly over the Amazon region in South America in September-November. Oceanic lightning activity in winter and autumn tends to exceed that in summer and spring. Global lightning is well correlated in phase but not in amplitude with the Carnegie curve. The diurnal flash rate varies about 4-35 percent about the mean, while the Carnegie curve varies around 4-15 percent.

Bailey, Jeff C.↗
NASA NTRS2011

Satellite-Derived Distributions, Inventories and Fluxes of Dissolved and Particulate Organic Matter Along the Northeastern U.S. Continental Margin

Estuaries and the coastal ocean experience a high degree of variability in the composition and concentration of particulate and dissolved organic matter (DOM) as a consequence of riverine and estuarine fluxes of terrigenous DOM, sediments, detritus and nutrients into coastal waters and associated phytoplankton blooms. Our approach integrates biogeochemical measurements, optical properties and remote sensing to examine the distributions and inventories of organic carbon in the U.S. Middle Atlantic Bight and Gulf of Maine. Algorithms developed to retrieve colored DOM (CDOM), Dissolved (DOC) and Particulate Organic Carbon (POC) from NASA's MODIS-Aqua and SeaWiFS satellite sensors are applied to quantify the distributions and inventories of DOC and POC. Horizontal fluxes of DOC and POC from the continental margin to the open ocean are estimated from SeaWiFS and MODIS-Aqua distributions of DOC and POC and horizontal divergence fluxes obtained from the Northeastern North Atlantic ROMS model. SeaWiFS and MODIS imagery reveal the importance of estuarine outflow to the export of CDOM and DOC to the coastal ocean and a net community production of DOC on the shelf.

Mannino, A.↗
DOE OSTI2025

Virtual sensing-enabled digital twin framework for real-time monitoring of nuclear systems leveraging deep neural operators

Abstract Real-time monitoring is a foundation of nuclear digital twin technology, crucial for detecting material degradation and maintaining nuclear system integrity. Traditional physical sensor systems face limitations, particularly in measuring critical parameters in hard-to-reach or harsh environments, often resulting in incomplete data coverage. Machine learning-driven virtual sensors offer a transformative solution by complementing physical sensors in monitoring critical degradation indicators. This paper introduces the use of Deep Operator Networks (DeepONet) to predict key thermal-hydraulic parameters in the hot leg of pressurized water reactor. DeepONet acts as a virtual sensor, mapping operational inputs to spatially distributed system behaviors without requiring frequent retraining. Our results show that DeepONet achieves low mean squared and Relative L2 error, making predictions 1400 times faster than traditional CFD simulations . These characteristics enable DeepONet to function as a real-time virtual sensor, synchronizing with the physical system to track degradation conditions and provide insights within the digital twin framework for nuclear systems.

Hossain, Raisa↗
NASA NTRS1994

Micro-Sensor Networks

The concept of an all-fiber, IC-based sensor network is presented. Fundamental issues including topology tradeoffs, power budget, and power distribution subsystem are analyzed. Some potential applications of such sensor networks are discussed.

networks↗
DOE OSTI2024

Minimization of Measurement Uncertainty in Optical Frequency Domain Reflectometry

Optical frequency domain reflectometry (OFDR) is a technique for interrogating optical fiber sensors to generate relative, quasi-distributed measurements. Although Optical frequency domain reflectometry (OFDR) is increasingly being adopted for aerospace, energy production, and structural monitoring applications, the quantification of uncertainty for OFDR measurements has not been developed beyond sparse empirical relationships. To address this knowledge gap, an uncertainty metric for OFDR measurements was developed. This uncertainty metric was applied to weight the edges between OFDR measurements on directed correlation graphs and analyzed to minimize the cumulative uncertainty. In conclusion, this work is the first to propose an uncertainty metric for OFDR and provides a generalized mathematical framework for optimizing OFDR hardware selection, optical fiber sensor selection, and postprocessing strategy.

42 ENGINEERING↗
NASA NTRS2002

Image Dis-Integration for Improved Plasmasphere Visualization

Traditionally, study of the plasmasphere has involved terrestrial observation of local characteristics. Global modeling of the plasmasphere in such an observation regime made use of an ensemble of (sparse) local measurements. Recently, sensors aboard the IMAGE (Imager for Magnetopause-to-Aurora Global Exploration) satellite (in particular, the EUV (Extreme Ultra Violet) Imager) have created the potential for truly global study of the plasmasphere. IMAGE was launched in spring of 2000 in an orbit with apogee altitude 7.2 R E (Earth radii) and perigee altitude 1000 km. IMAGE's EUV sensor allows an external view of the distribution of cold plasma in the plasmasphere to be acquired. EUV is designed to image light emission at 30.4 nanometers, which is the emission wavelength of the He + ion in the presence of solar radiation. He + makes up approximately 15-20% of the plasma in the plasmasphere, thus imaging of He + enables determination of plasma distribution. The EUV instrument provides a 90° by 84° field of view which is imaged as an equally spaced 150x140 pixel array on a spherical imaging surface. The EUV produces an image approximately every 10 minutes when the sensor is operating. Since EUV images contain line-of-sight integrations of plasma distributions, they do not directly express equatorial plane density (which would enable comparison of observed plasma distributions with predictions from models). Furthermore, the plasma density at any point in three-space is not known. The goal of our work was development of a technique that can enable plasma density to be determined throughout three-space. Our approach to creation of a three-space representation of the plasma distribution involves disintegrating the EUV lines of sight to form a volumetric map of plasma densities.

Timothy S. Newman↗
DOE OSTI2026

Optimizing infrasound observations for sample return capsule re-entry: Insights from OSIRIS-REx and Hayabusa2

The atmospheric entry of meteoroids presents a rare and unpredictable phenomenon, posing challenges for systematic observation and detailed characterization. Such events are nonetheless critical for advancing understanding of acoustic wave propagation, atmospheric structure, and entry dynamics. In contrast, sample return capsules (SRCs) from space missions follow well constrained re-entry trajectories, enabling planned observations of shock wave generation and propagation under controlled conditions. This study compares two SRC atmospheric entries, Hayabusa2 in 2020 and OSIRIS-REx in 2023, to assess how different infrasound array configurations influence shock wave detection and trajectory validation. Hayabusa2’s re-entry was monitored using a distributed network of 28 portable infrasound sensors across seven arrays in Woomera, Australia, permitting three-dimensional reconstruction of the trajectory and analysis of wave characteristics. For OSIRIS-REx, a compact four-sensor array deployed near Eureka Airport provided trajectory confirmation through arrival-time differences and back-azimuth estimates. Spectral and waveform analyses revealed differences in signal properties associated with variations in entry angle and velocity. The results illustrate both the strengths and the limitations of the deployed array configurations. The dense and distributed arrays during Hayabusa2’s re-entry enabled detailed trajectory reconstruction, whereas the compact array at Eureka primarily provided confirmation of signal coherence and back-azimuth consistency. These case studies highlight that even relatively small arrays, if located close to the predicted ground track, can still capture useful information on arrival direction and timing. Such insights provide practical guidance for planning future observational campaigns of SRC returns and other controlled atmospheric entries, and may also inform approaches to opportunistic observations of meteoroid events and other atmospheric acoustic phenomena.

celestial mechanics: orbit determination↗
NASA NTRS2014

High Sensitivity Stress Sensor Based on Hybrid Materials

A sensing device is used to detect the spatial distributions of stresses applied by physical contact with the surface of the sensor or induced by pressure, temperature gradients, and surface absorption. The sensor comprises a hybrid active layer that includes luminophores doped in a polymeric or organic host, altogether embedded in a matrix. Under an electrical bias, the sensor simultaneously converts stresses into electrical and optical signals. Among many applications, the device may be used for tactile sensing and biometric imaging.

Cao, Xian-An↗
NASA NTRS2015

Non-Intrusive, Distributed Gas Sensing Technology for Advanced Spacesuits

Chemical sensors for monitoring gas composition, including oxygen, humidity, carbon dioxide, and trace contaminants are needed to characterize and validate spacesuit design and operating parameters. This paper reports on the first prototypes of a non-intrusive gas sensing technology based on flexible sensitive patches positioned inside spacesuit prototypes and interrogated by optical fibers routed outside the suit, taking advantage of the transparent materials of the suit prototypes. The sensitive patches are based on luminescent materials whose emission parameters vary with the partial pressure of a specific gas. Patches sensitive to carbon dioxide, humidity, oxygen, and ammonia have been developed, and their preliminary characterization in the laboratory using Mark III-like helmet parts is described. The first prototype system consists of a four-channel fiber optic luminescent detector that can be used to monitor any of the selected target gases at four locations. To switch from one gas to another we replace the (disposable) sensor patches and adjust the system settings. Repeatability among sensitive patches and of sensor performance from location to location has been confirmed, assuring that suit engineers will have flexibility in selecting multiple sensing points, fitting the sensor elements into the spacesuit, and easily repositioning the sensor elements as desired. The evaluation of the first prototype for monitoring carbon dioxide during washout studies in a space suit prototype is presented.

Delgado, Jesus↗
NASA NTRS2015

Non-Intrusive, Distributed Gas Sensing Technology for Advanced Spacesuits

Chemical sensors for monitoring gas composition, including oxygen, humidity, carbon dioxide, and trace contaminants, are needed to characterize and validate spacesuit design and operating parameters. This paper reports on the first prototypes of a non-intrusive gas sensing technology based on flexible sensitive patches positioned inside spacesuit prototypes and interrogated via optical fibers routed outside the suit, taking advantage of the transparent materials of the suit prototypes. The sensitive patches are based on luminescent materials whose emission parameters vary with the partial pressure of a specific gas. Patches sensitive to carbon dioxide, humidity, and temperature have been developed, and their preliminary laboratory characterization in Mark III-like helmet parts is described. The first prototype system consists of a four-channel fiber optic luminescent detector that can be used to monitor any of the selected target gases at four locations. To switch from one gas to another we replace the (disposable) sensor patches and adjust the system settings. Repeatability among sensitive patches and of sensor performance from location to location has been confirmed, assuring that suit engineers will have flexibility in selecting multiple sensing points, fitting the sensor elements into the spacesuit, and easily repositioning the sensor elements as desired. The evaluation of the first prototype for monitoring carbon dioxide during washout studies in a spacesuit prototype is presented.

Delgado, Jesus↗
NASA NTRS2019

HYDRAFloods Near Real-Time Mapping of Flood Events Using Multiple Satellite Sensors

Information about inundated areas is critical for distributing aid and resources in flood emergency response operations. Conventional methods of monitoring floods, like gauge based observations and reports from local authorities, provide very detailed and accurate information about flood depth and location. However, the geographic coverage of these point-based observations is limited and delays are common. Satellite-based images can help address these challenges, providing near real-time flood extent information over large areas of coverage. The Hydrological Remote Sensing Analysis of Floods (HYDRAFloods) tool, currently being developed by SERVIR-Mekong in collaboration with the Myanmar Department of Disaster Management, is one such example. Generating flood maps, even from satellite imagery, is challenging, given the many disparate sources of information. HYDRAFloods leverages the most recently available remotely sensed data acquired by multiple satellite platforms to automate the creation of daily flood maps. Through combining multiple satellite sources, including optical, microwave, and synthetic aperture radar datasets, near real-time flood maps with reduced cloud impact and increased satellite observations can be generated for use by disaster managers.

Nauman, Claire↗