Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Sensor Validation”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Aircraft active and passive microwave validation of sea ice concentration from the Defense Meteorological Satellite Program special sensor microwave imager

Results are presented of a series of coordinate special sensor microwave imager (SSM/I) underflights that were carried out during March 1988 with NASA and Navy aircraft over portions of the Bering, Beaufort, and Chukchi seas. NASA DC-8 AMMR data from Bering Sea ice edge crossings were used to verify that the ice edge location, defined as the position of the initial ice bands encountered by the aircraft, corresponds to an SSM/I ice concentration of 15 percent. Direct comparison of SSM/I and aircraft ice concentrations for regions having at least 80 percent aircraft coverage reveals that the SSM/I total ice concentration is lower on average by 2.4 +/-2.4 percent. For multiyear ice, NASA and Navy flights across the Beaufort and Chukchi seas show that the SSM/I algorithm correctly maps the large-scale distribution of multiyear ice: the zone of first-year ice off the Alaskan coast, the large areas of mixed first-year and multiyear ice, and the region of predominantly multiyear ice north of the Canadian archipelago.

Cavalieri, D. J.↗
NASA NTRS2003

Assessment, Validation, and Refinement of the Atmospheric Correction Algorithm for the Ocean Color Sensors

The primary focus of this proposed research is for the atmospheric correction algorithm evaluation and development and satellite sensor calibration and characterization. It is well known that the atmospheric correction, which removes more than 90% of sensor-measured signals contributed from atmosphere in the visible, is the key procedure in the ocean color remote sensing (Gordon and Wang, 1994). The accuracy and effectiveness of the atmospheric correction directly affect the remotely retrieved ocean bio-optical products. On the other hand, for ocean color remote sensing, in order to obtain the required accuracy in the derived water-leaving signals from satellite measurements, an on-orbit vicarious calibration of the whole system, i.e., sensor and algorithms, is necessary. In addition, it is important to address issues of (i) cross-calibration of two or more sensors and (ii) in-orbit vicarious calibration of the sensor-atmosphere system. The goal of these researches is to develop methods for meaningful comparison and possible merging of data products from multiple ocean color missions. In the past year, much efforts have been on (a) understanding and correcting the artifacts appeared in the SeaWiFS-derived ocean and atmospheric produces; (b) developing an efficient method in generating the SeaWiFS aerosol lookup tables, (c) evaluating the effects of calibration error in the near-infrared (NIR) band to the atmospheric correction of the ocean color remote sensors, (d) comparing the aerosol correction algorithm using the singlescattering epsilon (the current SeaWiFS algorithm) vs. the multiple-scattering epsilon method, and (e) continuing on activities for the International Ocean-Color Coordinating Group (IOCCG) atmospheric correction working group. In this report, I will briefly present and discuss these and some other research activities.

Wang, Menghua↗
DOE OSTI2021

Adapting Secure MultiParty Computation to Support Machine Learning in Radio Frequency Sensor Networks

In this project we developed and validated algorithms for privacy-preserving linear regression using a new variant of Secure Multiparty Computation (MPC) we call "Hybrid MPC" (hMPC). Our variant is intended to support low-power, unreliable networks of sensors with low-communication, fault-tolerant algorithms. In hMPC we do not share training data, even via secret sharing. Thus, agents are responsible for protecting their own local data. Only the machine learning (ML) model is protected with information-theoretic security guarantees against honest-but-curious agents. There are three primary advantages to this approach: (1) after setup, hMPC supports a communication-efficient matrix multiplication primitive, (2) organizations prevented by policy or technology from sharing any of their data can participate as agents in hMPC, and (3) large numbers of low-power agents can participate in hMPC. We have also created an open-source software library named "Cicada" to support hMPC applications with fault-tolerance. The fault-tolerance is important in our applications because the agents are vulnerable to failure or capture. We have demonstrated this capability at Sandia's Autonomy New Mexico laboratory through a simple machine-learning exercise with Raspberry Pi devices capturing and classifying images while flying on four drones.

42 ENGINEERING↗
DOE OSTI2016

Robust Ceramic Coaxial Cable Down-Hole Sensors for Long-Term In Situ Monitoring of Geologic CO 2 Injection and Storage

Energy generation by use of fossil fuels produces large volumes of CO 2 and other greenhouse gases, whose accumulation in the atmosphere is widely seen as undesirable. CO 2 Capture followed by sequestration has been identified as the solution. Subsurface geologic formations offer a potential location for long-term storage of CO 2 because of their requisite size. Unfortunately, the inaccessibility and complexity of the subsurface, the wide range of scales of variability, and the coupled nonlinear processes, impose tremendous challenges to determine the transport and predict the fate of the stored CO 2 . Among the various monitoring approaches, in situ down-hole monitoring of the various state parameters provides critical and direct data points that can be used to validate the models, optimize the injection, detect leakage and track the CO 2 plume. However, down-hole sensors that can withstand the harsh conditions and operate over decades of the project lifecycle remain unavailable. Given that the widespread of carbon capture and storage will be the necessity and reality in the future, fundamental and applied research is required to address the significant challenges and technological gaps in lack of long-term reliable down-hole sensors This project focused on the development and demonstration of a novel, low-cost, distributed, robust ceramic coaxial cable sensor platform for in situ down-hole monitoring of geologic CO 2 injection and storage with high spatial and temporal resolutions. The coaxial cable Fabry-Perot interferometer (CCFPI) has been studied as a general sensor platform for in situ, long-term, measurement of temperature, pressure and strain, which are critical to CO 2 injection and storage. A novel signal processing scheme has been developed and demonstrated for dense multiplexing of the sensors for low-cost distributed sensing with high spatial resolution. The developed temperature, pressure and strain sensors have been extensively tested under laboratory conditions that are similar to the downhole CO 2 storage environment, showing excellent capability for in situ monitoring the various parameters that are important to model, optimize the injection, detect leakage and track the CO 2 plume. In addition, the interactions between the sensor datum and the geological models have been investigated in details for the purposes of model validation, guiding sensor installation/placement, enhancement of model prediction capability and optimization of the injection processes. This project has resulted in the successful development of new ceramic coaxial cable based sensor systems that can monitor directly the changes in pressure, temperature, and strain caused by increased reservoir pressure and reduced reservoir temperature due to the supercritical CO 2 injection. Integrated with geological models, the sensors and measurement data can improve the possibility to identify plume movement and leakage in the cap rock and wells with higher precision and more accuracy. The low cost, ease of deployment, small size and dense multiplexing features of the new sensing technology will allow a large number of sensors to be deployed to address the objective to demonstrate that 99% of the CO 2 remains in the injection zone.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1997

Wake Vortex Radar System Development: Overview

The objectives of the work are to: (1) Investigate microwave and millimeter wave sensors to locate, track, quantify, and observe the wake vortex hazard; (2) Develop and evaluate system concepts and designs using sensor system models and employing a theoretical reflectivity model for the wake vortex; (3) Test the validity of the theoretical model; (4) Acquire sensor systems and conduct field testing to evaluate; and to (5) Refine a system for field testing as a wake vortex sensor.

Neece, Robert T.↗
DOE OSTI2018

Modulating the Electronic Properties and Magnetism of Bilayer Phosphorene with Small Gas Molecules Adsorbing

First-principles calculations based on the density functional theory have been performed to investigate the physisorption of small gas molecules, including CO, H{sub 2}, H{sub 2}O, NH{sub 3}, NO, NO{sub 2}, and O{sub 2}, on the surface of bilayer phosphorene. The calculated results show that (1) CO, NH{sub 3}, NO, and O{sub 2} molecules act as charge donors, whereas H{sub 2}O, H{sub 2}, and NO{sub 2} molecules serve as charge acceptors. (2) The interaction between O{sub 2} molecule and bilayer phosphorene is strongest among all the researched gas molecules.(3) The physisorption of gas molecules on bilayer phosphorene produces prominent charge transfer, which not only makes phosphorene a promising candidate as a gas sensor, but also provides a valid approach to changing the polarity of phosphorene. (4) The band structure of phosphorene is also modulated by decorating with gas molecules, the NO, O{sub 2}, and NO{sub 2} adsorbed bilayer phosphorene system exhibits magnetism, and NO (O{sub 2})-adsorbed phosphorene is a typical n(p)-type semiconductor. (5) In addition, the band gap of CO/H{sub 2}O adsorbed bilayer phosphorene decreases by exerting increasing external electric fields, which suggests that applying an external electric field would be an effective way to tune the electronic properties of phosphorene and broaden the way to the application of phosphorene in nanoelectronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) southern great plains (SGP) site at Oklahoma, USA has become a reference research site for meteorological studies. Due to an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, SGP instrumentations, the site and some site-specific atmospheric conditions which potentially effect wind turbines within the region. As the atmospheric boundary layer is bounded and influenced by the surface, observations of surface radiation components and heat fluxes are crucial in understanding land-atmosphere interactions. The entrainment of air, updrafts, downdrafts and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both surface in-situ and remote sensing observations at SGP provide an overall climatology and their interactions from surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at SGP central facility were analyzed. All the measurements were generally within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in-situ and remote sensing instrumentation used in the report; provides mathematical equations to analyze fluxes, turbulence and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site specific atmospheric conditions, such as nocturnal low-level jets. Diurnal, seasonal and yearly variations of surface, sub-surface and boundary layer quantities, such as wind speed, direction, temperature, atmospheric stability, soil temperature, and various atmospheric fluxes at SGP showed distinct trends useful for focused modeling studies. The applicability of surface similarity theory on ARM SGP data is also evaluated, which showed northerly flows are aligned with MO theory estimates compared to southerly flows. Boundary layer winds and direction profiles for several years from a Doppler lidar shows a consistent presence of a nocturnal low-level jet and predominant southerly wind directions through the boundary layer at SGP. The inter-annual variability at SGP is low (<3.5%), with a mean annual wind speed of approximately 7 m s -1 at 100 m above ground level. Boundary layer turbulence and moisture transport from Doppler and Raman lidars are evaluated, which provides evidence of increased water vapor mass flux into the great plains during nocturnal low-level jets. The moisture flux from nocturnal low-level jets is observed to be maximum during summer periods. A novel machine learning algorithm is implemented to accurately estimate the planetary boundary layer height, providing further insights into growth and destruction of the convective boundary layer height during various seasons and land-atmosphere conditions. The high frequency of low-level clouds during winter, spring and fall seasons is validated using the multi-sensor array and satellite estimates of cloud top height. Satellite vegetative fraction data provides insight into seasonal surface roughness and vegetation variability around SGP site.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Estimating groundwater use and demand in arid Kenya through assimilation of satellite data and in-situ sensors with machine learning toward drought early action

Groundwater is an important source of water for people, livestock, and agriculture during drought in the Horn of Africa. In this work, areas of high groundwater use and demand in drought-prone Kenya were identified and forecasted prior to the dry season. Estimates of groundwater use were extended from a sentinel network of 69 in-situ sensored mechanical boreholes to the region with satellite data and a machine learning model. The sensors contributed 756 site-month observations from June 2017 to September 2021 for model building and validation at a density of approximately one sensor per 3700 sq.km. An ensemble of 19 parameterized algorithms was informed by features including satellite-derived precipitation, surface water availability, vegetation indices, hydrologic land surface modeling, and site characteristics to dichotomize high groundwater pump utilization. Three operational definitions of high demand on groundwater infrastructure were considered: 1) mechanical runtime of pumps greater than a quarter of a day (6+ hr) and daily per capita volume extractions indicative of 2) domestic water needs (35+ L), and 3) intermediate needs including livestock (75+ L). Gridded interpolation of localized groundwater use and demand was provided from 2017 to 2020 and forecasted for the 2021 dry season, June–September 2021. Cross-validated skill for contemporary estimates of daily pump runtime and daily volume extraction to meet domestic and intermediate water needs was 68%, 69%, and 75%, respectively. Forecasts were externally validated with an accuracy of at least 56%, 70%, or 72% for each groundwater use definition. The groundwater maps are accessible to stakeholders including the Kenya National Drought Management Authority (NDMA) and the Famine Early Warning Systems Network (FEWS NET). These maps represent the first operational spatially-explicit sub-seasonal to seasonal (S2S) estimates of groundwater use and demand in the literature. Knowledge of historical and forecasted groundwater use is anticipated to improve decision-making and resource allocation for a range of early warning early action applications.

Katie Fankhauser↗
DOE OSTI2024

NREL Hydrogen Sensor Testing Laboratory

Relevance: Detection is recognized as a critical element for hydrogen facility safety design and supports risk mitigation. Detection methodologies will support validation of H2 behavior research. Hydrogen point sensors play a critical role for safety and process monitoring, but other methodologies can be developed. Approach: NREL Sensor Laboratory tests and verifies sensor performance for manufacturers, developers, end-users, regulatory agencies and SDOs/CDOs NREL deployment activity supports regulatory requirement verification, hydrogen behavior models, and method development for use by stakeholders. Accomplishments and Progress: NREL's R&D accomplishments have supported developers, industry, and SDOs by providing sensor performance and deployment expertise not otherwise available. Development of alternative detection strategies for hydrogen applications have been initiated. HyWAM and advanced detection methodologies deployments at H2@Scale Facilities are being implemented. Collaborations: Collaboration with government laboratories, universities, private organizations and regulatory agencies has leveraged the NREL Sensor Laboratory's success in advancing hydrogen safety sensors and process control. Proposed Future Work: NREL will support hydrogen deployment by the proper implementation of hydrogen sensors and advanced detection strategies. NREL will continue to support science-based codes and standards. This effort will be guided by the needs of the hydrogen community.

codes and standards↗
NASA NTRS2020

How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies

Geophysical data sets derived from satellite sensors, ground/airborne instrumentation, and computational models are often compared against each other. A common example is the validation of satellite aerosol optical depth (AOD) retrievals against measurements from Aerosol Robotic Network (AERONET) Sun photometers. Spatiotemporal mismatch between data set sampling means that uncaptured variation in the underlying geophysical field introduces apparent disagreement into such comparisons, known as representation or collocation matchup uncertainty. This study uses variogram analysis of AERONET data to estimate temporal mismatch uncertainties and decorrelation time scales for the global AERONET record. As well as total AOD, the fine‐ and coarse‐mode AODs, Ångström Exponent (AE), and fine‐mode fraction (FMF) of AOD are analyzed. Globally, a time difference of 30 min typically induces from 0.011–0.035 variation in AOD. For total, fine, and coarse AODs the typical time to decorrelation is around 2–10 days. For AE and FMF it is 3–33 days; that is, aerosol systems often persist significantly longer than individual events in them. Biomass burning regions tend to show the largest and fastest subdaily AOD variability and also longest times to decorrelation. Some sites show significant season‐to‐season variations in behavior. These results can be used to inform site‐specific time collocation thresholds for aerosol validation analyses and account for temporal variation when estimating data set uncertainty. They also have implications for comparisons between different satellite products or models, data aggregation, and time series analyses. Results are provided on a site‐by‐site basis to facilitate use by other researchers.

satellite↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, validation of AD models through real-world sensor data is important for their application in nuclear facilities. In this paper, we propose an Autoencoder (AE)— a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD) — as another AD scheme for identifying irregularities within the same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We also validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

MARVEL Instrumentation, Control, and Software Considerations

This paper details the various I&C considerations and design decisions made throughout the MARVEL (Micro-reactor Applications Research Validation and Evaluation) project, including sensor and actuator selection, safety-related functionality, digital control hardware and software, and testing methodologies. Key challenges such as managing radiation, temperature, and space constraints are discussed, along with the trade-offs between using standard equipment and custom solutions. The successful integration of off-the-shelf components, the emphasis on minimizing safety-related instrumentation, and the lessons learned from prototyping and testing are highlighted. The authors aim to provide insights that can benefit future micro-reactor designs and emphasize the importance of real-world testing in advancing reactor technology.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2018

Quantifying Soiling Loss Directly From PV Yield

Soiling of photovoltaic (PV) panels is typically quantified through the use of specialized sensors. Here, we describe and validate a method for estimating soiling loss experienced by PV systems directly from system yield without the need for precipitation data. The method, termed the stochastic rate and recovery (SRR) method, automatically detects soiling intervals in a dataset, then stochastically generates a sample of possible soiling profiles based on the observed characteristics of each interval. In this paper, we describe the method, validate it against soiling station measurements, and compare it with other PV-yield-based soiling estimation methods. The broader application of the SRR method will enable the fleet scale assessment of soiling loss to facilitate mitigation planning and risk assessment.

14 SOLAR ENERGY↗
DOE OSTI2022

Advanced Collision Detection and Site Monitoring for Avian and Bat Species for Offshore Wind Energy (Final Technical Report)

This final technical report summarizes the outcomes from a project that aimed to design, build, and test a persistent and autonomous monitoring system for avian and bat collisions with offshore wind turbines blades and structures. The system comprises four primary sensor modules: 1) on-blade sensor modules for collision detection and dual-vision image capture on each blade with both visible light and near-infrared imagers; 2) additional on-blade collision sensors mounted further from the root; 3) a nacelle-mounted unit including a 360º camera and ultrasonic microphone array; and, 4) an on-blade, high-performance infrared camera module. Primary targeted outcomes were high sensitivity for the detection of blade strikes from bats and small birds, and automatically captured visual confirmation of the striking object; these features are critical for monitoring offshore wind turbine installations, where ground-based methods are not viable. In addition, local recording will provide a long-term sensor recording database. Following laboratory validation, field testing was conducted on an operational wind turbine in collaboration with the National Wind Technology Center at the NREL Flatirons campus over two planned field tests.

17 WIND ENERGY↗
NASA NTRS1990

Factors affecting the perception of transparent motion

It is possible to create a perception of transparency by combining patterns having different motions. Two particular combination rules, have specific interpretations in terms of physical phenomena: additive (specular reflection) and multiplicative (shadow illumination). Arbitrary combination rules applied to random patterns generate percepts in which the motions of the two patterns are visible, but have super-imposed noise. It is also possible to combine the patterns (using an exclusive-OR rule) so that only noise is visible. Within a one-dimensional family of combination rules which include addition and multiplication, there is a range where smooth motions are seen with no superimposed noise; this range is centered about the additive combination. This result suggests that the motion system deals with a linear representation of luminance, and is consistent with the analysis of motion by linear sensors. This research gives tentative validation the use in beam splitters (which combine images additively) in the construction of heads-up aviation displays. Further work is needed to determine if the superiority of additive combination generalizes to the case of full-color imagery (there are results in the literature suggesting that subtractive color mixture yields the best legibility of overlapping alphanumerics).

Mulligan, Jeffrey B.↗
NASA NTRS1990

Active structural control design and experiment for the Mini-Mast

Control system design and closed-loop test results for the Mini-Mast truss structure located at the NASA Langley Research Center are presented. The simplicity and effectiveness of a classical control approach to the active structural control design are demonstrated by ground experiments. The concepts of robust nonminimum phase compensation and periodic disturbance rejection are also experimentally validated. The practicality of a sensor output decoupling approach is demonstrated for the inherent, multivariable control problem of the Mini-Mast.

Wie, Bong↗
NASA NTRS1991

Moderate Resolution Imaging Spectrometer (MODIS) design evolution and associated development and verification of data product efforts

The Moderate Resolution Imaging Spectrometer (MODIS) is a key observing facility to be flown on the Earth Observing System (EOS). The facility is composed of two instruments called MODIS-N (nadir) and MODIS-T (tilt). The MODIS-N is being built under contract to NASA by the Santa Barbara Research Center. The MODIS-T is being fabricated by the Engineering Directorate at the Goddard Space Flight Center. The MODIS Science Team has defined nearly 40 biogeophysical data products for studies of the ocean and land surface and properties of the atmosphere including clouds that can be expected to be produced from the MODIS instruments shortly after the launch of EOS. The ocean, land, atmosphere, and calibration groups of the MODIS Science Team are now proceeding to plan and implement the operations and facilities involving the analysis of data from existing spaceborne, airborne, and in-situ sensors required to develop and validate the algorithms that will produce the geophysical data products. These algorithm development and validation efforts will be accomplished wherever possible within the context of existing or planned national and international experiments or programs such as those in the World Climate Research Program.

Salomonson, Vincent V.↗
NASA NTRS1992

NASA wind shear flight test in situ results

The main objectives in developing the NASA in situ windshear detection algorithm were to provide a measurement standard for validation of forward-look sensors under development, and to demonstrate the algorithm's ability to operate with a suitably low nuisance alert rate. It was necessary to know exactly how the algorithm was implemented and what parameters and filtering were used, in order to be able to fully test its effectiveness and correlate in situ results with forward-look sensor data.

Oseguera, Rosa M.↗