Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distributed Sensing”

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

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

At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

A Recursive Multiscale Correlation-Averaging Algorithm for an Automated Distributed Road Condition Monitoring System

A signal processing approach is proposed to jointly filter and fuse spatially indexed measurements captured from many vehicles. It is assumed that these measurements are influenced by both sensor noise and measurement indexing uncertainties. Measurements from low-cost vehicle-mounted sensors (e.g., accelerometers and Global Positioning System (GPS) receivers) are properly combined to produce higher quality road roughness data for cost-effective road surface condition monitoring. The proposed algorithms are recursively implemented and thus require only moderate computational power and memory space. These algorithms are important for future road management systems, which will use on-road vehicles as a distributed network of sensing probes gathering spatially indexed measurements for condition monitoring, in addition to other applications, such as environmental sensing and/or traffic monitoring. Our method and the related signal processing algorithms have been successfully tested using field data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Potential of hotspot solar‐induced chlorophyll fluorescence for better tracking terrestrial photosynthesis

Abstract Remote sensing of solar‐induced fluorescence (SIF) opens a new window for quantifying a key ecological variable, the terrestrial ecosystem gross primary production (GPP), because of the revealed strong SIF–GPP correlation. However, similar to many other remotely sensed metrics, SIF observations suffer from the sun‐sensor geometry effects, which may have important impacts on the SIF–GPP relationship but remain poorly understood. Here we used remotely sensed SIF, globally distributed tower GPP data, and a mechanistic model to provide a systematic analysis. Our results reveal that leaf physiology, canopy structure, and sun‐sensor geometries all affect the SIF–GPP relationship. In particular, we found that SIF observations in the sun‐tracking hotspot direction can be a better proxy of GPP due to the similar responses of light use efficiency and SIF escaping probability in the hotspot direction to the increasing incoming solar radiation. Such conclusions are supported by a variety of modeling simulations and satellite observations over various plant function types, at different time scales and with satellite observational modes. This study demonstrates the potential and advantage of normalizing SIF observations to the hotspot direction for better global GPP estimations. This study also demonstrates the great potentials of current and future spaceborne sun‐tracking satellite missions for a significant improvement in measuring and monitoring, at a wide range of spatial and temporal scales, the changes in terrestrial ecosystem GPP in response to anticipated changes in the Earth's environmental conditions.

Hao, Dalei↗
DOE OSTI2016

VOLTTRON 2016

VOLTTRON is a flexible, reliable, and scalable platform for distributed control and sensing. VOLTTRON serves in four primary roles: •A reference platform for researchers to quickly develop control applications for transactive energy. •A reference platform with flexible data store support for energy analytics applications either in academia or in commercial enterprise. •A platform from which commercial enterprise can develop products without license issues and easily integrate into their product line. •An accelerator to drive industry adoption of transactive energy and advanced building energy analytics. Pacific Northwest National Laboratory, with funding from the U.S. Department of Energy’s Building Technologies Office, developed and maintains VOLTTRON as an open-source community project. VOLTTRON source code includes agent execution software; agents that perform critical services that enable and enhance VOLTTRON functionality; and numerous agents that utilize the platform to perform a specific function (fault detection, demand response, etc.). The platform supports energy, operational, and financial transactions between networked entities (equipment, organizations, buildings, grid, etc.) and enhance the control infrastructure of existing buildings through the use of open-source device communication, control protocols, and integrated analytics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Voltron Compatible Whole Building Root-Fault Detection and Diagnosis

Buildings consume more than 40% of primary energy in the U.S. Malfunctioning sensors, components, and control systems, as well as degrading components in Heating, Ventilating and Air-conditioning (HVAC) and lighting systems are main reasons for energy waste and unsatisfactory indoor environment. Field studies have shown that an energy saving of 5-30% of total building energy consumption and improved indoor air quality can be achieved by simply applying automated fault detection and diagnosis (AFDD), followed by corrections even if these are not done in real time. Extensive research has been made on the development of component level AFDD tools in the past two decades. However, in recent years, the development of method for a whole building level AFDD has received much attention. Here, a whole building fault refers to a fault happening in one subsystem but impact on more than one subsystems, or has a significant impact on building performances, such as building’s energy consumption. Existing component level AFDD tools could fail to detect or give false alarm for faults that trigger abnormalities in multiple subsystems. Isolating such whole building faults, which have impacts on multiple subsystems, is also challenging by simply using component based AFDD solutions. On the other hand, it might be more cost-effective for medium- or small-sized commercial buildings that have subsystems (e.g. primary cooling subsystem, air loop subsystem, heating subsystem, lighting subsystem, etc.) to install one whole building level AFDD tool, rather than many component level AFDD tools, to focus on significant faults. The focus of this project is firstly to provide training opportunities in building AFDD research area for undergraduate students and to develop a workforce pipeline in building sciences. The objective of the proposed research activities is to develop cost-effective and scalable AFDD solutions for whole building level faults. The developed AFDD solution is VOLTTRONTM compatible to further increase its plug-n-play capacity and the market penetration. VOLTTRONTM is an open-source innovative distributed control and sensing software platform developed by the Pacific Northwest National Laboratory. A VOLTTRONTM compatible AFDD tool brings the benefits such as low-cost deployment, and better building to grid integration, etc. The performance of the developed whole building AFDD tools is evaluated using data collected from a mixed-use medium-sized university campus building. Another significant goal of this project is to engage undergraduate students in research activities and expose them to building control and AFDD fields. A demonstration building – Nesbitt Hall at Drexel University is identified for this study. This demonstration building has a typical HVAC system configuration, which includes a water-cooled chiller system, three variable air volume (VAV) air handling unit (AHU) systems, and a hydronic heating system. Faults, that are expected to have a whole building level impact, are artificially implemented in this demonstration building for three different seasons. Building data have been collected in this project, which include fault free building automation system (BAS) data and BAS data that contain system behaviors caused by artificially implemented and naturally occurred faults. These collected data are used to evaluate the developed whole building AFDD tools. A data-driven method, which includes a weather and schedule-based pattern matching (WPM) method and Feature based Principal Component Analysis (FPCA) method, is developed for whole building level fault detection. Parameter sensitivity tests, including snapshot window size, data sample searching pool size, etc., are implemented to evaluate the impacts of various WPM-FPCA parameters. A data-driven and expert knowledge/rule-based method using Bayesian Network (BN) and WPM is developed for whole building level fault diagnosis. The developed WPM-BN method, which includes a two-layer BN structure model and BN parameters, are either learned from baseline data or developed from expert knowledge. The developed whole building AFDD tools are evaluated using BAS data collected from the demonstration building. Using the evaluation data set, the WPM-FPCA fault detection method is evaluated under two different Principle Component (PC) retention rates, i.e., 0.65 retention rate and 0.95 retention rate. It is observed that when using 0.65 PC retention rate, the WPM-FPCA fault detection method achieves a 79% fault detection rate (this rate reaches to 85% when including the six make-up fault test cases discussed in the next bullet), while when using 0.95 PC retention rate, the WPM-FPCA fault detection method achieves 100% fault detection rate (this rate remains to be 100% when including the six make-up fault test cases). Under both PC retention rates, the WPM-FPCA fault detection method demonstrates 0% false alarm rates. Using the evaluation data set, the developed WPM-BN fault diagnosis method has successfully diagnosed thirteen (13) faults out of the fourteen (14) fault test cases. The one mis-diagnosed case exhibits fewer fault symptoms in different subsystems, when compared with other fault test cases. Overall speaking, the developed whole building AFDD solutions demonstrate satisfactory fault detection/diagnosis accuracy with very low false alarm rate. Lastly, a survey and market study has been performed to understand the existing AFDD market, including its gaps and needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Single Photon Detection with On-Chip Number Resolving Capability

Single photon detection (SPD) plays an important role in many forefront areas of fundamental science and advanced engineering applications. In recent years, rapid developments in superconducting quantum computation, quantum key distribution, and quantum sensing call for SPD in the microwave frequency range. We have explored in this LDRD project a new approach to SPD in an effort to provide deterministic photon-number-resolving capability by using topological Josephson junction structures. In this SAND report, we will present results from our experimental studies of microwave response and theoretical simulations of microwave photon number resolving detector in topological Dirac semimetal Cd 3 As 2 . These results are promising for SPD at the microwave frequencies using topological quantum materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Using Strain in the Vadose Zone During Sinusoidal-Rate Well Tests to Characterize an Aquifer

Well tests with sinusoidal variation in pumping rate are appealing because of the ability to filter competing signals and they also can be set up with no net removal of water, which is an advantage at contaminated sites. Current methods of interpreting sinusoidal-rate well tests analyze the phase lag and amplitude of pressure signals in the aquifer. This approach is restricted by the availability of monitoring wells. An alternative approach could be to measure the stain in the vadose zone instead of pressure in the aquifer. The goal of this research is to evaluate the feasibility of using signals from in-situ sensors in the vadose zone to characterize sinusoidal-rate well tests. Well tests with a variety of periods and amplitudes were performed using a well completed in an unconfined saprolite aquifer with a water table at 9m depth at our test site near Clemson, South Carolina. Vertical strain was measured every meter between 1 to 7 m using a distributed optical fiber sensing technique called coherence length gated microwave photonics interferometry (CMPI). A novel packaging system was designed to couple the optical fiber to the saprolite. The results show that strain measured in the vadose zone during sinusoidal-rate pumping varies periodically with amplitudes from 0.1 to 3 microstrain, depending on the amplitude of the sinusoidal pumping rate. Hydraulic heads at similar radial distances were also periodic with changing amplitudes ranging up to ±0.2 meters. The strain in the vadose zone responds to pressure in the underlying aquifer—the strain is tensile when the pressure is falling, and compressive when the pressure is rising. The phase lag between the pumping rate and the strain was 3 min with a pumping period of 15 minutes, and this gives a hydraulic diffusivity of 0.06 m2/s. This is the same diffusivity obtained by analyzing a constant rate pumping test, and it is slightly larger than the diffusivity (0.044 m2/s) obtained by analyzing the phase lag of the pressure in a nearby monitoring well. Strain measurements in the vadose zone could be made with much less cost and effort than installing a deep monitoring well. These results suggest that strain measurements in the vadose zone could be used to supplement monitoring wells, thereby increasing the resolution, and reducing costs of analyzing well tests.

well test, sinusoidal, periodic pumping, strain↗
DOE OSTI2025

DTS data from SGP TBS

Distributed temperature-sensing data collected using a Silixa-XT DTS and 50/125 MM fiber. Data are calibrated using two water baths at the surface and an iMet aloft at the end of the fiber and tether. The data are then assigned an altitude for the TBS flight. Data collected prior to Febuary 11, 2020 were collected at the SGP Central Facility (CF). Data from 2/11/20 were collected with a Sensornet Oryx DTS at the E9 site, not at the CF. Data from May 2021 were collected with a Sensornet Oryx at the CF, and with a Silixa XT at the CF. Data from July 2021 were collected at the SGP CF, EF9, and EF36 with a Silixa XT. Data from October 2021 were collected at the SGP EF36 with a Silixa XT. Data from February 2022 were collected at the CF with a Silixa XT.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Transaction-Based Controls for Building-Grid Integration: VOLTTRON™

The U.S. Department of Energy’s (DOE’s) Building Technologies Office (BTO) is supporting the development of a “transactional network” concept that supports energy, operational, and financial transactions between building systems (e.g., rooftop units -- RTUs), and the electric power grid using applications, or 'agents', that reside either on the equipment, on local building controllers, or in the Cloud. The transactional network vision is delivered using a real-time, scalable reference platform called VOLTTRON that supports the needs of the changing energy system. VOLTTRON is an agent execution and an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions.

DOE↗
DOE OSTI2024

Distributed Optical Fiber Sensor Systems: Application to Natural Gas Pipeline Monitoring

Distributed fiber optic sensing is a cutting-edge technology that has found extensive applications in the monitoring of pipelines. Considering the low backscattering level of standard single-mode fiber as fiber under test, a Rayleigh enhanced optical fiber embedded within the tight-buffered cable is demonstrated in field testing. We analyzed the increased backscattering fiber cable's vibration performance to the conventional single-mode telecom fiber using a custom-built Φ-OTDR interrogator system. Thereafter, using a 4-inch steel pipeline with a flow rate of 5, 10, 15, and 20 ft/s and a fixed pressure level of 1000 psi, we field-tested the sensor system for monitoring natural gas pipeline acoustic vibrations. We also field tested Brillouin optical time domain analysis (BOTDA) system for pipeline hoop strain monitoring under various pressure conditions. The pilot-scale testing results presented in this study suggested that pipeline operators can accurately perform flow monitoring, leak detection, and pressure monitoring for pipeline integrity monitoring.

Lalam, Nageswara↗
DOE OSTI2019

Reduced Mode Sapphire Optical Fiber and Sensing System

This is the final technical report for the Virginia Tech Center for Photonics Technology (VT-CPT) research project entitled “Reduced Mode Sapphire Optical Fiber and Sensing System”. The objective of the five-year effort was to develop a low modal volume (LMV) single crystal sapphire fiber and demonstrate its advantages in current state-of-the-art sapphire-based temperature sensors and in novel distributed ultra-high temperature sensing systems. The project, sponsored by the Crosscutting Research Program, began in 2014 and had the original goal of developing the next generation of harsh environment sensing systems. After successfully completing the original scope of the award, the project was expanded and extended to allow for the development of harsh environment packaging and testing of a prototype sensor system. These novel fiber optic sensing technologies provide real-time, accurate, and reliable temperature measurements at distributed locations in existing coal-fueled electricity generating units to improve the overall performance, reliability, and flexibility of the nation’s coal-fired power plant fleet. In the final year (2018) of the project, prototype sensing systems were successfully deployed and operated in small commercial coal and natural gas fired boilers at the Virginia Tech Power Plant. The harsh environment quasi-distributed temperature sensing technology was advanced from a (Technology Readiness Level) TRL=1 to a TRL=7 by demonstrating the full validation of the sensing system prototype in a relevant industrial environment. The real-time, accurate and reliable monitoring of temperatures at distributed locations is expected to lower operating costs by allowing more accurate measurement of the harsh conditions inside a boiler system to better control its operation. The technologies developed by Virginia Tech’s Center for Photonics Technology will support the mission of the National Energy Technology Laboratory (NETL) to advance energy options to fuel our economy, strengthen our security, and improve the environment.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

FiberFlex: Real-time FPGA-based Intelligent and Distributed Fiber Sensor System for Pedestrian Recognition

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.

Distributed↗
DOE OSTI2015

Complete Fiber/Copper Cable Solution for Long-Term Temperature and Pressure Measurement in Supercritical Reservoirs and EGS Wells

High Temperature insulated wire and optical fiber cable is a key enabling technology for the Geothermal Technologies Program (GTP). Without insulated electrical wires and optical fiber, downhole temperature and pressure sensors, flow meters and gauges cannot communicate with the surface. Unfortunately, there are currently no insulated electrical wire or fiber cable constructions capable of surviving for extended periods of deployment in a geothermal well (240-325°C) or supercritical (374°C) reservoir. This has severely hindered engineered reservoir creation, management and utilization, as hot zones and cool water intrusions cannot be understood over time. The lack of a insulated electrical wire and fiber cable solution is a fundamental limitation to the viability of this energy source. The High Temperature Downhole Tools target specification is development of tools and sensors for logging and monitoring wellbore conditions at depths of up to 10,000 meters and temperatures up to 374oC. It well recognized in the industry that no current electronic or fiber cable can be successfully deployed in a well and function successfully for more a few days at temperatures over 240oC. The goal of this project was to raise this performance level significantly. Prysmian Group’s objective in this project was to develop a complete, multi-purpose cable solution for long-term deployment in geothermal wells/reservoirs that can be used with the widest variety of sensors. In particular, the overall project objective was to produce a manufacturable cable design that can perform without serious degradation: • At temperatures up to 374°C; • At pressures up to 220 bar; • In a hydrogen-rich environment; and • For the life of the well (> 5 years). This cable incorporates: • Specialty optical fibers, with specific glass chemistry and high temperature and pressure protective coatings for data communication and distributed temperature and pressure sensing, and • High-temperature insulated wire conductors Prysmian Group has developed a geothermal fiber optic cable (GFOC) solution which incorporates novel glass chemistry for optical fibers to operate at the required bandwidths in high temperature/high pressure hydrogen rich environments with fiber protection, high temperature insulated conductors and protective cladding for cable components. The cable solution has been tested in a geothermal installation for 10 months. The electrical insulation and optical fibers have been validated through laboratory testing to ensure successful operation for greater than 5 years at 300°C, with the possibility of higher temperatures depending on the particular well environment. With the 300°C optical fiber and electrical insulation developments completed and validated in laboratory tests the greatest challenge to a complete 300°C cable solution was protecting the optical fibers in the cable. Optical fibers are typically incased in a protective tube where the tube is filled with a gel. The gel serves as mechanical protection, prevent moisture ingress, and can include hydrogen scavenging materials. A suitable gel for use at 300°C could not be identified and an industrialized alternative was not fully attained. Despite the problems encountered and the lower long-term operating temperature of the cable solution, the project showed success in developing a complete cable solution for a large portion of the geothermal wells in operation today. Further work to obtain the higher long-term temperature goal of the project can be achieved based on the knowledge gained in the current project. This project is significant for many reasons including the new materials science, manufacturing technology, energy independence, and jobs created and will create.

15 GEOTHERMAL ENERGY↗
DOE OSTI2011

Evaluation of moist processes during intense precipitation in km-scale NWP models using remote sensing and in-situ data: Impact of microphysics size distribution assumptions

This study investigates the sensitivity of moist processes and surface precipitation during three extreme precipitation events over Belgium to the representation of rain, snow and hail size distributions in a bulk one-moment microphysics parameterisation scheme. Sensitivities included the use of empirically derived relations to calculate the slope parameter and diagnose the intercept parameter of the exponential snow and rain size distributions and sensitivities to the treatment of hail/graupel. A detailed evaluation of the experiments against various high temporal resolution and spatially distributed observational data was performed to understand how moist processes responded to the implemented size distribution modifications. Net vapor consumption by microphysical processes was found to be unaffected by snow or rain size distribution modifications, while it was reduced replacing formulations for hail by those typical for graupel, mainly due to intense sublimation of graupel. Cloud optical thickness was overestimated in all experiments and all cases, likely due to overestimated snow amounts. The overestimation slightly deteriorated by modifying the rain and snow size distributions due to increased snow depositional growth, while it was reduced by including graupel. The latter was mainly due to enhanced cloud water collection by graupel and reduced snow depositional growth. Radar reflectivity and cloud optical thickness could only be realistically represented by inclusion of graupel during a stratiform case, while hail was found indispensable to simulate the vertical reflectivity profile and the surface precipitation structure. Precipitation amount was not much altered by any of the modifications made and the general overestimation was only decreased slightly during a supercell convective case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

The Modular Borehole Monitoring Program. A research program to optimize well-based monitoring for geologic carbon sequestration

Understanding the impacts caused by injection of large volumes of CO 2 in the deep subsurface necessitates a comprehensive monitoring strategy. While surface-based and other remote geophysical methods can provide information on the general morphology of a CO 2 plume, verification of the geochemical conditions and validation of the remote sensing data requires measurements from boreholes that penetrate the storage formation. Unfortunately, the high cost of drilling deep wellbores and deploying instrumentation systems constrains the number of dedicated monitoring borings as well as limits the technologies that can be incorporated in a borehole completion. The objective of the Modular Borehole Monitoring (MBM) Program was to develop a robust suite of well-based tools optimized for subsurface monitoring of CO 2 that could meet the needs of a comprehensive well-based monitoring program. It should have enough flexibility to be easily reconfigured for various reservoir geometries and geologies. The MBM Program sought to provide storage operators with a turn-key fully engineered design that incorporated key technologies, function over the decades long time-span necessary for post-closure reservoir monitoring, and meet industry acceptable risk profiles for deep-well installations. While still within the conceptual design phase of the MBM program, the SECARB Anthropogenic Test in Citronelle, Alabama, USA was identified as a deployment site for our engineered monitoring systems. The initial step in designing the Citronelle MBM system was to down-select from the various monitoring tools available to include technologies that we considered essential to any program. Monitoring methods selected included U-tube geochemical sampling, discrete quartz pressure and temperature gauges, an integrated fibre-optic bundle consisting of distributed temperature and heat-pulse sensing, and a sparse string of conventional 3C-geophones. While not originally planned within the initial MBM work scope, the fibre-optic cable was able to also be used for the emergent technology of distributed acoustic sensing. The MBM monitoring string was installed in March, 2012. To date, the Citronelle MBM instruments continue to operate reliably. Results and lessons learned from the Citronelle MBM deployment are addressed along with examples of data being collected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Comparing the Cloud Vertical Structure Derived from Several Methods Based on Radiosonde Profiles and Ground-based Remote Sensing Measurements

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44-88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

atmospheric↗
DOE OSTI2017

A positive correlation between energetic electron butterfly distributions and magnetosonic waves in the radiation belt slot region

Energetic (hundreds of keV) electrons in the radiation belt slot region have been found to exhibit the butterfly pitch angle distributions. Resonant interactions with magnetosonic and whistler-mode waves are two potential mechanisms for the formation of these peculiar distributions. Here we perform a statistical study of energetic electron pitch angle distribution characteristics measured by Van Allen Probes in the slot region during a three-year period from May 2013 to May 2016. Our results show that electron butterfly distributions are closely related to magnetosonic waves rather than to whistlermode waves. Both electron butterfly distributions and magnetosonic waves occur more frequently at the geomagnetically active times than at the quiet times. In a statistical sense, more distinct butterfly distributions usually correspond to magnetosonic waves with larger amplitudes and vice versa. The averaged magnetosonic wave amplitude is less than 5 pT in the case of normal and flat-top distributions with a butterfly index BI = 1 but reaches ~ 35–95 pT in the case of distinct butterfly distributions with BI > 1:3. For magnetosonic waves with amplitudes > 50 pT, the occurrence rate of butterfly distribution is above 80%. Our study suggests that energetic electron butterfly distributions in the slot region are primarily caused by magnetosonic waves.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Radionuclide Risk Coefficient Uncertainty Distributions for Use in Performance Assessments - 19156

Traditionally, radiation dose has been used as the regulatory criterion for decision making in performance assessments (PAs), despite the concept of cancer risk arguably being a more easily understood endpoint than dose for the public, and a preferable metric for decision analysis. However, the United States Environmental Protection Agency (EPA) has developed risk parameters for use in risk assessments and PAs in the form of radionuclide-specific risk coefficients, or RCs, which are published in various Federal Guidance Reports (FGRs). RCs are employed as scalars to convert environmental radionuclide exposure (via ingestion, inhalation, and external exposure) estimates to incremental lifetime cancer risk (ILCR). ILCR is the additional cancer risk averaged over a lifetime, over-and-above all-cause cancer risk, associated with carcinogen exposure. Uncertainties associated with RCs are discussed in FGR 13 and in a joint report published by EPA and Oak Ridge National Laboratory, but statistical distributions for the RCs were not directly developed. The uncertainty assessments in the EPA/ONRL report were based on dosimetric modeling and elicitation of nine experts. From these sources, five uncertainty categories were defined based on ratios of the 5. and 95. quantiles of uncertainty. Thus, the representations of uncertainty defined by EPA/ORNL are not distributions in a traditional sense. Furthermore, the authors only addressed uncertainty in RCs for inhalation and ingestion pathways. We develop a methodology for assigning statistical distributions to EPA's published mortality RC values (i.e. to estimate the probability of dying from radiation-induced cancers) for the inhalation (slow, medium, and fast absorption types), ingestion (water, food, and soil), and external exposure pathways associated with all cancer types. We employed the same dosimetric concepts and assumptions as EPA/ORNL, including cancer risk (dose-response) distributional information from a previous expert elicitation, which was also employed by EPA/ORNL in their work. We assumed that uncertainty in RCs can be described by lognormal distributions based on the modeling conducted previously by EPA/ORNL, and that point estimates tabulated in FGR 13 represent median values of the distributions. We also extended EPA/ORNL's uncertainty ratios to statistical distributions for external exposure RCs. The results are a set of radionuclide-specific distributions that are applicable in PAs that focus on cancer mortality. These distributions are currently and will subsequently be employed in PAs at various sites, in addition to the required regulatory dose limits. Quantification of ILCRs and associated uncertainty in PAs will provide regulators and the public with additional information for good decision making. Future directions include further refinement of the distributions and development of statistical distributions for morbidity RCs, which are used to estimate the probability of developing, but not necessarily dying as a result of, radiation-induced cancer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Toward Linking Aboveground Vegetation Properties and Soil Microbial Communities Using Remote Sensing

Despite their vital role in terrestrial ecosystem function, the distributions and dynamics of soil microbial communities (SMCs) are poorly understood. Vegetation and soil properties are the primary factors that influence SMCs. This paper discusses the potential effectiveness of remote sensing science and technologies for mapping SMC biogeography by characterizing surface biophysical properties (e.g., plant traits and community composition) strongly correlated with SMCs. Using remotely sensed biophysical properties to predict SMC distributions is extremely challenging because of the intricate interactions between biotic and abiotic factors and between above- and belowground ecosystems. However, the integration of biophysical and soil remote sensing with geospatial information about the e nvironment holds great promise for mapping SMC biogeography. Additional research needs invol ve microbial taxonomic definition, soil environmental complexity, and scaling strategies. The collaborative effort of experts from diverse disciplines is essential to linking terrestrial surface biosphere observations with subsurface microbial community distributions using remote sensing.

Hamada, Yuki↗