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DOE OSTI2017

Modeling Urban Scenarios & Experiments: Fort Indiantown Gap Data Collections Summary and Analysis

This report summarizes experimental radiation detector, contextual sensor, weather, and global positioning system (GPS) data collected to inform and validate a comprehensive, operational radiation transport modeling framework to evaluate radiation detector system and algorithm performance. This framework will be used to study the influence of systematic effects (such as geometry, background activity, background variability, environmental shielding, etc.) on detector responses and algorithm performance using synthetic time series data. This work consists of performing data collection campaigns at a canonical, controlled environment for complete radiological characterization to help construct and benchmark a high-fidelity model with quantified system geometries, detector response functions, and source terms for background and threat objects. This data also provides an archival, benchmark dataset that can be used by the radiation detection community. The data reported here spans four data collection campaigns conducted between May 2015 and September 2016.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1982

Report of subpanel on feature extraction

The state of knowledge in feature extraction for Earth resource observation systems is reviewed and research tasks are proposed. Issues in the subpixel feature estimation problem are defined as: (1) the identification of image models which adequately describe the data and the sensor it is using; (2) the construction of local feature models based on those image models; and (3) the problem of trying to understand these effects of preprocessing on the entire process. The development of ground control point (GCP) libraries for automated selection presents two concerns. One is the organization of these GCP libraries for rectification problems, i.e., the problems of automatically selecting by computer the specific GCP's for particular registration tasks. Second is the importance of integrating ground control patterns in a data base management system, allowing interface to a large number of sensor image types with an automatic selection system. The development of data validation criteria for the comparison of different extraction techniques is also discussed.

Source record↗

NASA NTRS2007

Ultra-Wideband Radar Measurements of Thickness of Snow Over Sea Ice

An accurate knowledge of snow thickness and its variability over sea ice is crucial for determining the overall polar heat and freshwater budget, which influences the global climate. Recently, algorithms have been developed to extract snow thicknesses from passive microwave satellite data. However, validation of these data over the large footprint of the passive microwave sensor has been a challenge. The only method used thus far has been with meter sticks during ship cruises. To address this problem, we developed an ultra wideband frequency-modulated continuous-wave (FM-CW) radar to measure snow thickness over sea ice. We made snow-thickness measurements over Antarctic sea ice by operating the radar from a sled during September and October, 2003. We performed radar measurements over 11 stations with varying snow thickness between 4 and 85 cm. We observed excellent agreement between radar estimates of snow thickness with physical measurements, achieving a correlation coefficient of 0.95 and a vertical resolution of about 3 cm.

Kanagaratnam, P.↗

NASA NTRS2016

A Generic Approach for Inversion of Surface Reflectance over Land: Overview, Application and Validation Using MODIS and LANDSAT8 Data

This paper presents a generic approach developed to derive surface reflectance over land from a variety of sensors. This technique builds on the extensive dataset acquired by the Terra platform by combining MODIS and MISR to derive an explicit and dynamic map of band ratio's between blue and red channels and is a refinement of the operational approach used for MODIS and LANDSAT over the past 15 years. We will present the generic approach and the application to MODIS and LANDSAT data and its validation using the AERONET data.

validation↗

NASA NTRS2018

A Generic Approach for Inversion of Surface Reflectance over Land: Overview, Application and Validation Using MODIS and LANDSAT8 Data

validation↗

NASA NTRS2007

Retrieval Lesson Learned from NAST-I Hyperspectral Data

The retrieval lesson learned is important to many current and future hyperspectral remote sensors. Validated retrieval algorithms demonstrate the advancement of hyperspectral remote sensing capabilities to be achieved with current and future satellite instruments.

Zhou, Daniel K.↗

DOE OSTI2016

Solar variability datalogger

To address the lack of knowledge of local solar variability, we have developed and deployed a low-cost solar variability datalogger (SVD). While most currently used solar irradiance sensors are expensive pyranometers with high accuracy (relevant for annual energy estimates), low-cost sensors display similar precision (relevant for solar variability) as high-cost pyranometers, even if they are not as accurate. In this work, we present evaluation of various low-cost irradiance sensor types, describe the SVD, and present validation and comparison of the SVD collected data. In conclusion, the low cost and ease of use of the SVD will enable a greater understanding of local solar variability, which will reduce developer and utility uncertainty about the impact of solar photovoltaic (PV) installations and thus will encourage greater penetrations of solar energy.

14 SOLAR ENERGY↗

NASA NTRS1976

Performance modeling of earth resources remote sensors

A technique is presented for constructing a mathematical model of an earth resources remote sensor. The technique combines established models of electronic and optical components with formulated models of scan and vibration effects, and it includes a model of the radiation effects of the earth's atmosphere. The resulting composite model is useful for predicting in-flight sensor performance, and a descriptive set of performance parameters is derived in terms of the model. A method is outlined for validating the model for each sensor of interest. The validation for one airborne infrared scanning system is accomplished in part by a satisfactory comparison of predicted response with laboratory data for that sensor.

Kidd, R. H.↗

DOE OSTI2022

Modeling Air Handling Units to Create a Diverse Fault Dataset for FDD Innovation: Lessons Learned and Recommendations

As energy management and information systems (e.g., automated fault detection and diagnostics [AFDD] tools) become more prevalent in the commercial building stock, it is important to determine the effectiveness of these technologies by benchmarking their performance. The authors have been working to develop the largest publicly available dataset of HVAC fault datasets for performance benchmarking applications, covering the most common HVAC systems and designs including chiller plants, rooftop packaged units, dual duct air handling unit and single duct air handling units. This study covers the development, modeling, and validation of a synthetic fault dataset for the air handling unit (AHU), one of the most common HVAC configurations found in the commercial building stock. Despite this being a common system, real-world time series data are scarce and usually do not span a wide range of weather conditions. Due to this limitation, two detailed AHU models, which included the single duct AHU and dual duct AHU developed in the Modelica language and HVACSIM+ were employed to carry out annual simulations of numerous common sensor faults, mechanical faults, and control sequence faults. The fault inclusive data were then validated by comparing fault effects on system performance to expected symptoms. We summarize the nature of each fault and their impacts under different weather and operation conditions. We report some lessons learnt during the efforts of validating the high volumes of the FDD data sets. Finally, we highlight considerations for FDD developers that may want to use this dataset to assess their algorithms’ performance and their improvement over time.

Casillas, Armando↗

NASA NTRS2000

Airborne Sunphotometry of African Dust and Marine Boundary Layer Aerosols in PRIDE

The Puerto Rico Dust Experiment (PRIDE) was conducted during summer 2000 to study the radiative, microphysical and transport properties of Saharan dust in the Caribbean region. During PRIDE, NASA Ames Research Center's six-channel airborne autotracking sunphotometer (AATS-6) was operated aboard a Piper Navajo airplane based at Roosevelt Roads Naval Station on the northeast coast of Puerto Rico. AATS-6 measurements were taken during 21 science flights off the coast of Puerto Rico in the western Caribbean. Data were acquired within and above the Marine Boundary Layer (MBL) and the Saharan Aerosol Layer (SAL) up to 5.5 km altitude tinder a wide range of dust loadings. Aerosol optical depth (AOD) spectra and columnar water vapor (CWV) values have been calculated from the AATS-6 measurements by using sunphotometer calibration data obtained at Mauna Loa Observatory (3A kin ASL) before (May) and after (October) PRIDE. Mid-visible AOD values measured near the surface during PRIDE ranged from 0.07 on the cleanest day to 0.55 on the most turbid day. Values measured above the MBL were as high as 0.35; values above the SAL were as low as 0.01. The fraction of total column AOD due to Saharan dust cannot be determined precisely from AATS-6 AOD data alone due to the uncertainty in the extent of vertical mixing of the dust down through the MBL. However, analyses of ground-based and airborne in-situ aerosol sampling measurements and ground-based aerosol lidar backscatter data should yield accurate characterization of the vertical mixing that will enable calculation of the Saharan dust AOD component from the sunphotometer data. Examples will be presented showing measured AATS-6 AOD spectra, calculated aerosol extinction and water vapor density vertical profiles, and aerosol size distributions retrieved by inversion of the AOD spectra. Near sea-surface AOD spectra acquired by AATS-6 during horizontal flight legs at 30 m ASL are available for validation of AOD derived from coincident satellite sensor (TOMS, MODIS, MISR) measurements. AATS-6 AOD data acquired during numerous aircraft ascents and descents through the MBL and the SAL should permit atmospheric column closure analyses with respect to aerosol optical depth, extinction, and size distribution by comparison with coincident aircraft-based in-situ particle size distribution measurements and ground-based (Cabras Island, Puerto Rico) micropulse lidar aerosol backscatter measurements. The aerosol information derived from the column closure analyses can be used subsequently to calculate radiative flux changes, which can then be compared with coincident spectral flux measurements taken from aboard the aircraft with a solar spectral flux radiometer.

Livingston, John M.↗

NASA NTRS2020

Psyche Magnetometer Engineering Model Test and Thermal Model Correlation to Validate Operational Thermal Requirement

Psyche Fluxgate Magnetometer candidate fabricated by UCLA has a critical temperature gradient requirement inside the magnetometer sensor head. Since the temperature gradient requirement is a driving factor for the magnetometer operation and science data collection at 16 Psyche, it is critical to validate and verify this requirement via modeling and test. In this work, a thermal vacuum test was completed for Psyche flight-like magnetometer engineering model. Flight-like environments were simulated for a hot operational case (after launch), a cold survival case (cruise), and two cold operational cases to characterize thermal performance of the instrument. An additional, non-flight, steady-state test case was completed to better correlate the magnetometer thermal model. During the test, sensitive Cernox temperature sensors with accuracy of ±0.1°C were used to precisely characterize the temperature gradient and correlate the model to the best accuracy. Collected test data indicated power consumption of 28% lower than predicted. The temperature gradient measured met the expected value and the requirement. Test data indicated the magnetometer also met the AFTs in relevant hot and cold environments. Test Results were used to correlate the thermal model. The correlated thermal model will be integrated to the spacecraft thermal model to predict magnetometer thermal performance while collecting science data in Psyche orbits.

Caron, Ryan↗

DOE OSTI2016

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those it is found that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely because of differences in instrumentation, calibration, and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat-dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory), and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but they poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration, or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Finally, data from models and observations should be put on the same spatial and temporal scales before comparison.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Novel Sensor for the In Situ Measurement of Uranium Fluxes

The goal of this project was to develop a sensor that incorporates the field-tested concepts of the passive flux meter to provide direct in situ measures of flux for uranium and groundwater in porous media. Measurable contaminant fluxes [J] are essentially the product of concentration [C] and groundwater flux or specific discharge [q ]. The sensor measures [J] and [q] by changes in contaminant and tracer amounts respectively on a sorbent. By using measurement rather than inference from static parameters, the sensor can directly advance conceptual and computational models for field scale simulations. The sensor was deployed in conjunction with DOE in obtaining field-scale quantification of subsurface processes affecting uranium transport (e.g., advection) and transformation (e.g., uranium attenuation) at the Rifle IFRC Site in Rifle, Colorado. Project results have expanded our current understanding of how field-scale spatial variations in fluxes of uranium, groundwater and salient electron donor/acceptors are coupled to spatial variations in measured microbial biomass/community composition, effective field-scale uranium mass balances, attenuation, and stability. The coupling between uranium, various nutrients and micro flora can be used to estimate field-scale rates of uranium attenuation and field-scale transitions in microbial communities. This research focuses on uranium (VI), but the sensor principles and design are applicable to field-scale fate and transport of other radionuclides. Laboratory studies focused on sorbent selection and calibration, along with sensor development and validation under controlled conditions. Field studies were conducted at the Rifle IFRC Site in Rifle, Colorado. These studies were closely coordinated with existing SBR (formerly ERSP) projects to complement data collection. Small field tests were conducted during the first two years that focused on evaluating field-scale deployment procedures and validating sensor performance under controlled field conditions. In the third and fourth year a suite of larger field studies were conducted. For these studies, the uranium flux sensor was used with uranium speciation measurements and molecular-biological tools to characterize microbial community and active biomass at synonymous wells distributed in a large grid. These field efforts quantified spatial changes in uranium flux and field-scale rates of uranium attenuation (ambient and stimulated), uranium stability, and quantitatively assessed how fluxes and effective reaction rates were coupled to spatial variations in microbial community and active biomass. Analyses of data from these field experiments were used to generate estimates of Monod kinetic parameters that are ‘effective’ in nature and optimal for modeling uranium fate and transport at the field-scale. This project provided the opportunity to develop the first sensor that provides direct measures of both uranium (VI) and groundwater flux. A multidisciplinary team was assembled to include two geochemists, a microbiologist, and two quantitative contaminant hydrologists. Now that the project is complete, the sensor can be deployed at DOE sites to evaluate field-scale uranium attenuation, source behavior, the efficacy of remediation, and off-site risk. Because the sensor requires no power, it can be deployed at remote sites for periods of days to months. The fundamental science derived from this project can be used to advance the development of predictive models for various transport and attenuation processes in aquifers. Proper development of these models is critical for long-term stewardship of contaminated sites in the context of predicting uranium source behavior, remediation performance, and off-site risk.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Introduction to the JPSS-2 Advanced Technology Microwave Sounder (ATMS) Government Calibration Data Book (GCDB)

The third Advanced Technology Microwave Sounder (ATMS) is an instrument onboard the Joint Polar Satellite System (JPSS), JPSS-2 (renamed NOAA-21 in orbit) mission. This report is to introduce the JPSS-2 Government Calibration Data Book (J2 GCDB) for ATMS, SN 304. This J2 GCDB document contains key information generated during the calibration testing campaign that is driving parameters for radiometric performance. This document also contains supporting data that augments the calibration results. The values in this document are utilized by ATMS’s calibration packet which is, in turn, an integral component in the interpretation of science data. The calibration data in this report was collected from tests such as shelf-level testing, antenna testing, instrument thermal vacuum (TVAC) testing; satellite TVAC testing; and JPSS-2 post-launch tests. JPSS-2 was launched on November 10, 2022. In the subsequent years, the Government will release an ATMS GCDB for each JPSS mission. We expect that all public users can download these ATMS GCDBs from the NOAA operational Integrated Calibration and Validation System (ICVS) website, see more discussions below. The goal of this GCDB is to demonstrate how to characterize ATMS measurements using JPSS-2 ATMS on-orbit operational data and to provide relevant explanations. This document serves as a primary public domain reference for calibrating operational ATMS Raw Data Records (RDR) science data, as used in the current operational Interface Data Processing Segment (IDPS) system. This same RDR science data is distributed through direct broadcast (DB) to DB users for use in their ground processing systems. This J2 GCDB provides the results of the ATMS system radiometric calibration, the antenna flat reflector emissivity [1], the antenna pattern measurements, the antenna pattern corrected brightness temperature [2], the brightness temperature of the lunar disk [3], Lunar Intrusion (LI) correction algorithm [4], receiver spectral parameters, and mechanical alignment on-orbit pointing results, and the striping effect appeared significantly in S-NPP on-orbit radiance data when the data are compared to the Radiative Transfer Model (RTM) simulation in numerical weather prediction (NWP) system [5]. It also provides the parameters required for conversion of telemetry counts to engineering units, for radiometric calibration, and for antenna beam geo-location. Moreover, it provides JPSS-2 ATMS Spectral Response Functions data, some additional information related to ATMS on-orbit performance, on-orbit lunar intrusion correction parameters and Earth contamination bias, and on how to derive ATMS RDR, antenna Temperature Data Records (TDR), and Sensor Data Records (SDR). Furthermore, an introduction of NOAA operational Integrated Calibration and Validation System (ICVS) website and services is added in this J2 GCDB. This ICVS hosts a long-term monitoring system which allows to visualization and comparison of data from JPSS missions, NOAA legacy Polar Operational Environmental Satellites (POES), and Geostationary Operational Environmental Satellites (GOES). From NOAA Comprehensive Large Array-data Stewardship System (CLASS), the public users can download all JPSS ATMS data products for all JPSS missions.

Microwave Sounder↗

NASA NTRS2011

Continued Development of Meandering Winding Magnetometer (MWM (Register Trademark)) Eddy Current Sensors for the Health Monitoring, Modeling and Damage Detection of Composite Overwrapped Pressure Vessels

Composite Overwrapped Pressure Vessels (COPVs) are used in essentially all NASA spacecraft, launch. vehicles and payloads to contain high-pressure fluids for propulsion, life support systems and science experiments. Failure of any COPV either in flight or during ground processing would result in catastrophic damage to the spacecraft or payload, and could lead to loss of life. Therefore, NASA continues to investigate new methods to non-destructively inspect (NDE) COPVs for structural anomalies and to provide a means for in-situ structural health monitoring (SHM) during operational service. Partnering with JENTEK Sensors, engineers at NASA, Kennedy Space Center have successfully conducted a proof-of-concept study to develop Meandering Winding Magnetometer (MWM) eddy current sensors designed to make direct measurements of the stresses of the internal layers of a carbon fiber composite wrapped COPV. During this study three different MWM sensors were tested at three orientations to demonstrate the ability of the technology to measure stresses at various fiber orientations and depths. These results showed good correlation with actual surface strain gage measurements. MWM-Array technology for scanning COPVs can reliably be used to image and detect mechanical damage. To validate this conclusion, several COPVs were scanned to obtain a baseline, and then each COPV was impacted at varying energy levels and then rescanned. The baseline subtracted images were used to demonstrate damage detection. These scans were performed with two different MWM-Arrays. with different geometries for near-surface and deeper penetration imaging at multiple frequencies and in multiple orientations of the linear MWM drive. This presentation will include a review of micromechanical models that relate measured sensor responses to composite material constituent properties, validated by the proof of concept study, as the basis for SHM and NDE data analysis as well as potential improvements including design changes to miniaturize and make the sensors durable in the vacuum of space

Russell, Richard↗

NASA NTRS2001

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

Ichoku, Charles↗

DOE OSTI2026

Asi Nuclear Energy Sensors Data Portal Chatbot And Data Structuring Tool

The Idaho National Laboratory (INL) is advancing the development of an AI-powered chatbot and data structuring tool specifically designed to accelerate data mining processes for sensor-related information and seamlessly integrate the results into the ASI Sensors Data Portal (https://nes.energy.gov/). By doing so, the software aims to enhance the accessibility, usability, and organization of sensor data for nuclear energy applications. The software initial phase focuses on retrieving comprehensive datasets, prioritizing the past five years of publicly available information from the Office of Scientific and Technical Information (OSTI). These datasets will be meticulously processed to ensure compatibility, employing cleaning and preprocessing steps to eliminate irrelevant, incomplete, or corrupted information, thus establishing a robust foundation for subsequent AI use. The data will serve as the backbone for training an AI model and chatbot, which will act as an interactive tool enabling users to ask complex, context-specific questions and receive accurate, validated answers derived from constrained literature. In parallel, the project incorporates a data structuring process supported by AI to organize sensor information from multiple sources into a standardized format. This structured data will include detailed sensor specifications, such as measurement range, applications, accuracy, and operating conditions, generated and documented with AI. These specifications will be systematically integrated into the sensor portal. To maintain the highest levels of accuracy and relevance, all AI-generated outputs will be reviewed and validated by subject matter experts (SMEs), with additional fields or parameters added as needed. Future stages of the project aim to expand the dataset beyond OSTI to include other sources and potentially incorporate unclassified controlled information (UCI) with restricted access protocols to address security and confidentiality requirements.

Mapes, NormanJ. [Idaho National Laboratory (INL), ↗

NASA NTRS2001

SIMBIOS Sun Photometer Program

Aerosol optical thickness (AOT) values determined from the satellite ocean color data provide useful information on the spatial and temporal distributions of aerosols and are by-products of the atmospheric corrections required to estimation of water-leaving radiances. The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project is using in situ atmospheric data, primarily from sun photometers, for several purposes including: (1) validation the SeaWiFS and other ocean color mission aerosol optical products, e.g., AOT and Angstrom exponent; (2) evaluation of the aerosol models currently used for atmospheric corrections; and (3) development of vicarious sensor calibration methodologies, especially for the near-infrared bands where in situ water-leaving radiance data in the visible from sites like the Marine Optical Buoy cannot be used. The principal source of in situ aerosol observations was the Aerosol Robotic Network (AERONET).

McClain, Charles↗