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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗
NASA NTRS2014

An Intrinsic Fiber-Optic Sensor for Structure Lightning Current Measurement

An intrinsic optical-fiber sensor based on Faraday Effect is developed that is highly suitable for measuring lightning current on aircraft, towers and complex structures. Originally developed specifically for aircraft installations, it is light-weight, non-conducting, structure conforming, and is immune to electromagnetic interference, hysteresis and saturation. It can measure total current down to DC. When used on lightning towers, the sensor can help validate other sensors and lightning detection network measurements. Faraday Effect causes light polarization to rotate when the fiber is exposed to a magnetic field in the direction of light propagation. Thus, the magnetic field strength can be determined from the light polarization change. By forming closed fiber loops and applying Ampere's law, measuring the total light rotation yields the total current enclosed. A broadband, dual-detector, reflective polarimetric scheme allows measurement of both DC component and AC waveforms with a 60 dB dynamic range. Two systems were built that are similar in design but with slightly different sensitivities. The 1310nm laser system can measure 300 A - 300 kA, and has a 15m long sensing fiber. It was used in laboratory testing, including measuring current on an aluminum structure simulating an aircraft fuselage or a lightning tower. High current capabilities were demonstrated up to 200 kA at a lightning test facility. The 1550nm laser system can measure 400 A - 400 kA and has a 25m fiber length. Used in field measurements, excellent results were achieved in the summer of 2012 measuring rocket-triggered lightning at the International Center for Lightning Research and Testing (ICLRT), Camp Blanding, Florida. In both systems increased sensitivity can be achieved with multiple fiber loops. The fiber optic sensor provides many unique capabilities not currently possible with traditional sensors. It represents an important new tool for lightning current measurement where low weight, complex shapes, large structure dimension, large current, and low frequency capabilities are important considerations.

Nguyen, Truong X.↗
NASA NTRS2007

Flexible Skins Containing Integrated Sensors and Circuitry

Artificial sensor skins modeled partly in imitation of biological sensor skins are undergoing development. These sensor skins comprise flexible polymer substrates that contain and/or support dense one- and two-dimensional arrays of microscopic sensors and associated microelectronic circuits. They afford multiple tactile sensing modalities for measuring physical phenomena that can include contact forces; hardnesses, temperatures, and thermal conductivities of objects with which they are in contact; and pressures, shear stresses, and flow velocities in fluids. The sensor skins are mechanically robust, and, because of their flexibility, they can be readily attached to curved and possibly moving and flexing surfaces of robots, wind-tunnel models, and other objects that one might seek to equip for tactile sensing. Because of the diversity of actual and potential sensor-skin design criteria and designs and the complexity of the fabrication processes needed to realize the designs, it is not possible to describe the sensor-skin concept in detail within this article.

Liu, Chang↗
NASA NTRS2009

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.

May, George A.↗
NASA NTRS2011

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".

May, George A.↗
NASA NTRS2016

Flight Test 4 Preliminary Results: NASA Ames SSI

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements as well as the safety substantiation and end-to-end assessment of DAA system performance. The Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS) Project conducted flight test program, referred to as Flight Test 4, at Armstrong Flight Research Center from April -June 2016. Part of the test flights were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as JADEM (Java Architecture for DAA Extensibility and Modeling). The encounter scenarios, which involved NASA's Ikhana UAS and a manned intruder aircraft, were designed to collect data on DAA system performance in real-world conditions and uncertainties with four different surveillance sensor systems. Flight test 4 has four objectives: (1) validate DAA requirements in stressing cases that drive MOPS requirements, including: high-speed cooperative intruder, low-speed non-cooperative intruder, high vertical closure rate encounter, and Mode CS-only intruder (i.e. without ADS-B), (2) validate TCASDAA alerting and guidance interoperability concept in the presence of realistic sensor, tracking and navigational errors and in multiple-intruder encounters against both cooperative and non-cooperative intruders, (3) validate Well Clear Recovery guidance in the presence of realistic sensor, tracking and navigational errors, and (4) validate DAA alerting and guidance requirements in the presence of realistic sensor, tracking and navigational errors. The results will be presented at RTCA Special Committee 228 in support of final verification and validation of the DAA MOPS.

Detect-And-Avoid (DAA)↗
NASA NTRS2020

Overcoming Dimensionality Barriers in Satellite Data to Elucidate SPECTRAL-SPATIAL-TEMPORAL Trends in the Ocean

The weighted harmonic mean of spectral wavelengths can be used as an index of optical water types that share similar spectral signatures.This technique can be translated to relate spectral shape between sensors of varying spectral resolution.The output along a continuum of color values enables spatio-temporal analysis of subtle spectral shifts.Directional trends in absorption and backscatter data lend a hidden context to changes in water color. Conceptualization of multiple data dimensions is imperative as passive/active sensors grow increasingly sophisticated in nature.

Vandermeulen, Ryan↗
DOE OSTI2022

Super-resolution demodulation for fiber sensor arrays based on the MUSIC algorithm

This paper studies the use of MUltiple SIgnal Classification (MUSIC) as a super-resolution algorithm to improve demodulation results for intrinsic Fabry–Perot interferometer (IFPI) sensor arrays. Through distinction between noise and signal subspaces in an observation matrix, this paper shows that a 38-fold improvement in the full width at half maximum (FWHM) estimation of IFPI optical path differences (OPD) can be achieved using this algorithm. Based on this improved method, this paper demonstrates that a tunable laser with a 1.3-nm tuning range can achieve the same sensor demodulation performance as a tunable laser with a 50-nm tuning range if a conventional Fourier transform-based algorithm is used. This paper presents a new approach to analyzing optical signals produced by multiple multiplexed interferometers with similar OPDs with potential applications for both single-mode and multiple-mode devices.

Li, Yuqi (ORCID:0000000291643663)↗
DOE OSTI2020

Non-invasive (non-contact) measurements of human thermal physiology signals and thermal comfort/discomfort poses -A review

Heating, ventilation and air-conditioning (HVAC) systems have been adopted to create comfortable, healthy and safe indoor environments. In the control loop, the technical feature of the human demand-oriented supply can help operate HVAC effectively. Among many technical options, real time monitoring based on feedback signals from end users has been frequently reported as a critical technology to confirm optimizing building performance. Recent studies have incorporated human thermal physiology signals and thermal comfort/discomfort status as real-time feedback signals. A series of human subject experiments used to be conducted by primarily adopting subjective questionnaire surveys in a lab-setting study, which is limited in the application for reality. With the help of advanced technologies, physiological signals have been detected, measured and processed by using multiple technical formats, such as wearable sensors. Nevertheless, they mostly require physical contacts with the skin surface in spite of the small physical dimension and compatibility with other wearable accessories, such as goggles, and intelligent bracelets. Most recently, a low cost small infrared camera has been adopted for monitoring human facial images, which could detect the facial skin temperature and blood perfusion in a contactless way. Also, according to latest pilot studies, a conventional digital camera can generate infrared images with the help of new methods, such as the Euler video magnification technology. Human thermal comfort/discomfort poses can also be detected by video methods without contacting human bodies and be analyzed by the skeleton keypoints model. Here, new sensing technologies were summarized, their cons and pros were discussed, and extended applications for the demand-oriented ventilation were also reviewed as potential development and applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Generalist multimodal AI: A review of architectures, challenges and opportunities

Multimodal models are expected to be a critical component to future advances in artificial intelligence. Here, this field is starting to grow rapidly with a surge of new design elements motivated by the success of foundation models in natural language processing (NLP) and vision. It is widely hoped that further extending the foundation models to multiple modalities (e.g., text, image, video, sensor, time series, graph, etc.) will ultimately lead to generalist multimodal models, i.e. one model across different data modalities and tasks. However, there is little research that systematically analyzes recent multimodal models (particularly the ones that work beyond text and vision) with respect to the underling architecture proposed. Therefore, this work provides a fresh perspective on generalist multimodal models (GMMs) via a novel architecture and training configuration specific taxonomy. This includes factors such as Unifiability, Modularity, and Adaptability that are pertinent and essential to the wide adoption and application of GMMs. The review further highlights key challenges and prospects for the field and guide the researchers into the new advancements.

Artificial intelligence (AI)↗
DOE OSTI2024

LogPath: Log data based energy consumption analysis enabling electric vehicle path optimization

Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.

EV (Electric vehicles) navigation↗
DOE OSTI2024

Insights on seasonal solifluction processes in warm permafrost Arctic landscape using a dense monitoring approach across adjacent hillslopes

Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km² watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4 to 0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging -1.13°C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw–freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a Factor of Safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Wireless Sensing and Communication Capability from In-Core to a Monitoring Center

Significant cost savings can be made if electrical cables can be replaced by wireless technology in current Nuclear Power Plants (NPP) and in advance reactor designs. Wireless technology can also provide in-core opportunities by significantly reducing the number of penetrations in the pressure vessel, cost and complexity of sensor installation and by increasing the efficiency of current and advanced reactors. Unlike other deployment scenarios for an industrial environment, operators need to have centralized control over all the networks. Centralized control will reduce implementation costs, provide single point control and enable monitoring of network devices, improve security, and enhance connectivity. Micro-sensors that can simultaneously monitor temperature and pressure within a fuel rod inside nuclear reactors will enable preventative actions during abnormal operating conditions. This ability could avert accidents and enable the expedient development of accident tolerant fuels. A novel micro-sensor suite (~ mm) to simultaneously measure multiple parameters such as temperature, strain, pressure, and neutron/gamma flux inside a fuel rod is being developed for use in reactors. The necessary communication architecture is also being developed to transmit measurement signals from the core to the plant's data cloud or control room. A three three-tier strategy has been developed to support wireless transmission of in-core measurements to the control room or to a secure cloud platform for control, analytics, and decision-making purposes. 1. In-core: data signal from in-core to outside of the pressure vessel within the containment building 2. Containment building: data signal from inside to the outside of the containment building and into the balance of the plant network 3. Balance of the plant network: information transmitted to the data cloud and control room This plan presents a wireless sensing and communication system for use within a reactor core and elsewhere. The communication technology is advantageous to compensate for network equipment failures and adverse data transmission conditions. Wireless technology will significantly increase the resiliency of the plants network system. The wireless system naturally provides multiple transmission path capability and data redundancy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1965

Bio-grid system Final report

Feasibility of multiple bio-electrode arrays to sensor galvanic skin response signals during body movement

BODY MEASUREMENT /BIOL/↗
NASA NTRS1993

Spectral-Content Readout Of Birefringent Sensor

Stresses and strains measured optically at temperatures up to 2,000 degrees F. Spectrum of light processed through polarizer, sensor, analyzer, and associated optical components measured and processed to extract amount of retardation and, equivalently, stress-induced birefringence in sensor. Method offers same advantages as electrical strain sensors, including acquisition of data from multiple locations and under dynamic conditions. Additional advantage: immunity of fiber-optic transmission to interference by electromagnetic interference at radio and lower frequencies.

Redner, Alex S.↗
NASA NTRS2002

Navigation Algorithms for the SeaWiFS Mission

The navigation algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) were designed to meet the requirement of 1-pixel accuracy-a standard deviation (sigma) of 2. The objective has been to extract the best possible accuracy from the spacecraft telemetry and avoid the need for costly manual renavigation or geometric rectification. The requirement is addressed by postprocessing of both the Global Positioning System (GPS) receiver and Attitude Control System (ACS) data in the spacecraft telemetry stream. The navigation algorithms described are separated into four areas: orbit processing, attitude sensor processing, attitude determination, and final navigation processing. There has been substantial modification during the mission of the attitude determination and attitude sensor processing algorithms. For the former, the basic approach was completely changed during the first year of the mission, from a single-frame deterministic method to a Kalman smoother. This was done for several reasons: a) to improve the overall accuracy of the attitude determination, particularly near the sub-solar point; b) to reduce discontinuities; c) to support the single-ACS-string spacecraft operation that was started after the first mission year, which causes gaps in attitude sensor coverage; and d) to handle data quality problems (which became evident after launch) in the direct-broadcast data. The changes to the attitude sensor processing algorithms primarily involved the development of a model for the Earth horizon height, also needed for single-string operation; the incorporation of improved sensor calibration data; and improved data quality checking and smoothing to handle the data quality issues. The attitude sensor alignments have also been revised multiple times, generally in conjunction with the other changes. The orbit and final navigation processing algorithms have remained largely unchanged during the mission, aside from refinements to data quality checking. Although further improvements are certainly possible, future evolution of the algorithms is expected to be limited to refinements of the methods presented here, and no substantial changes are anticipated.

Hooker, Stanford B.↗
NASA NTRS2006

Two-micron Detector Development using Sb-based Material Systems

NASA Langley Research Center (LaRC), in partnership with the University of Delaware (UD), developed AlGaAsSb/InGaAsSb custom-designed phototransistors in the 0.6-2.5 micron wavelength range for applications to laser remote sensing. The phototransistor s performance greatly exceeds the previously reported results at this wavelength range in the literature. The performances of the custom-designed phototransistor, such as responsivity, detectivity, and gain, are improved significantly as compared to the previously published detectors as well as commercial detectors. Detection in the 0.6- to 2.5- micron broadband with a single phototransistor will result in reduction or elimination of heavy and complex optical components now required for multiple wavelength detection in atmospheric remote sensors resulting in smaller, lighter, simpler instruments with higher performance. This high performance broadband phototransistor will eliminate the need for high power laser for active remote sensing and also the Si (1.0- micron cutoff) and InGaAs (extended 2.3- micron cutoff) detectors. The developed broadband phototransistor will be applicable for the next generation of space-based Earth observations and other planetary instruments for active and passive remote sensing with substantial reduction in size, complexity, and weight to measure water vapor, methane, and carbon dioxide in planetary atmospheres as well as aerosol, cloud, water vapor, O2, CO, and CO2 for a broad range of applications to Earth and Space Science Missions under Science Mission Directorate (SMD) research programs.

Abedin, M. N.↗
NASA NTRS2002

Predicting System Accidents with Model Analysis During Hybrid Simulation

Standard discrete event simulation is commonly used to identify system bottlenecks and starving and blocking conditions in resources and services. The CONFIG hybrid discrete/continuous simulation tool can simulate such conditions in combination with inputs external to the simulation. This provides a means for evaluating the vulnerability to system accidents of a system's design, operating procedures, and control software. System accidents are brought about by complex unexpected interactions among multiple system failures , faulty or misleading sensor data, and inappropriate responses of human operators or software. The flows of resource and product materials play a central role in the hazardous situations that may arise in fluid transport and processing systems. We describe the capabilities of CONFIG for simulation-time linear circuit analysis of fluid flows in the context of model-based hazard analysis. We focus on how CONFIG simulates the static stresses in systems of flow. Unlike other flow-related properties, static stresses (or static potentials) cannot be represented by a set of state equations. The distribution of static stresses is dependent on the specific history of operations performed on a system. We discuss the use of this type of information in hazard analysis of system designs.

Malin, Jane T.↗