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Relative charge-transfer efficiencies of super 2 P sub 3/2 and super 2 P sub 1/2 xenon ions in Xe and in O sub 2.
Excited xenon ion charge transfer efficiencies in Xe and oxygen, discussing Xe ion formation in electron impact monitoring
Algorithm Development and Validation for Satellite-Derived Distributions of DOC and CDOM in the US Middle Atlantic Bight
In coastal ocean waters, distributions of dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) vary seasonally and interannually due to multiple source inputs and removal processes. We conducted several oceanographic cruises within the continental margin of the U.S. Middle Atlantic Bight (MAB) to collect field measurements in order to develop algorithms to retrieve CDOM and DOC from NASA's MODIS-Aqua and SeaWiFS satellite sensors. In order to develop empirical algorithms for CDOM and DOC, we correlated the CDOM absorption coefficient (a(sub cdom)) with in situ radiometry (remote sensing reflectance, Rrs, band ratios) and then correlated DOC to Rrs band ratios through the CDOM to DOC relationships. Our validation analyses demonstrate successful retrieval of DOC and CDOM from coastal ocean waters using the MODIS-Aqua and SeaWiFS satellite sensors with mean absolute percent differences from field measurements of < 9 %for DOC, 20% for a(sub cdom)(355)1,6 % for a(sub cdom)(443), and 12% for the CDOM spectral slope. To our knowledge, the algorithms presented here represent the first validated algorithms for satellite retrieval of a(sub cdom) DOC, and CDOM spectral slope in the coastal ocean. The satellite-derived DOC and a(sub cdom) products demonstrate the seasonal net ecosystem production of DOC and photooxidation of CDOM from spring to fall. With accurate satellite retrievals of CDOM and DOC, we will be able to apply satellite observations to investigate interannual and decadal-scale variability in surface CDOM and DOC within continental margins and monitor impacts of climate change and anthropogenic activities on coastal ecosystems.
The Mass Index and Total Mass of the Geminid Meteoroid Stream as Found with Radar, Optical, and Lunar Impact Data
The Geminid meteor shower was observed in 2015 using the Western Meteor Physics Group’s Canadian Meteor Orbit Radar (CMOR), Marshall Space Flight Center’s (MSFC) eight wide-field optical cameras, and MSFC’s lunar impact monitoring. These observations allowed Geminid fluxes to be calculated in three unique mass-ranges, from 1.8 (exponent -4) grams to 30 grams. From these fluxes, a mass index of 1.68 plus or minus 0.04 is found, which is in excellent agreement with past Geminid mass indices such as 1.69 found by Blaauw et al using only radar data and 1.7 found by Arlt and Rendtel using visual data. This mass index, however, is found over five orders of magnitude of mass, which allows a higher level of confidence that this mass index holds over a large portion of the stream. Mass indices are an important quantity to be accurately measured for a shower, indicating the distribution of mass in a well-studied stream in which we know the parent body (3200 Phaethon), improving forecasts of the shower activity, and allow fluxes to be scaled to high and low masses. The quantities derived here, along with a profile of the Geminid meteor shower activity in 2015 from CMOR, permit the total Geminid mass the Earth encountered in 2015 to be found, along with a minimum total mass of the Geminid meteoroid stream. Attempts have been made in the past to measure the mass of meteoroid streams using Zenithal Hourly Rate (ZHR) profiles, but here this new and improved treatment uses empirically derived fluxes and measured mass indices for the 2015 encounter with the meteoroid stream. This is to be compared with other meteoroid stream mass estimates including that of the Perseids, caused by comet Swift Tuttle.
Comprehensive Severe Weather Impact Assessment and Monitoring using Synthetic Aperture Radar and Auxiliary Data
Remote sensing datasets, particularly acquired by Synthetic Aperture Radar (SAR) sensors, have become increasingly important in severe weather disaster impact studies given their ability to observe the Earth largely irrespective of weather and sunlight conditions. The reliability of existing SAR change detection products applied on a pair of SAR images is constrained by the limitation of current methods to differentiate and classify disaster specific changes from anthropogenic surface alterations. Moreover, the inherent properties of the sensors, variations in SAR backscatter due to changes in surface conditions, and other factors exacerbate these limitations. We proposed a novel procedure expanding on earlier SAR-based change detection methods to exclude anthropogenic alterations and other sources of ambiguity that might lead to inaccurate mapping of the impacts of severe weather disasters. We applied the proposed procedure that is based on long term interferometric and amplitude-based change detection analyses of Sentinel- 1 SAR imagery to two study sites recently impacted by severe weather disasters (Flooding post severe weather events in urban centers; Hailstorm damage on crops). For the first case study, Sentinel-1 SLC scenes from two flood events in the Houston area (April 2016 flooding event and Hurricane Harvey of August-September 2017) were used to construct a flood map depicting areas repeatedly affected by the flood. Pixels with consistent coherence values in the pre-disaster coherence stack were retained for comparison with the pre- and post-disaster coherence stack and pixels with significant decline (greater than 60%) in coherence values were retained in the final flood map. The findings of the applied technique were calibrated and validated through datasets from NOAA/NWS Service storm reports, aerial imaging (NOAA and Civil Air Patrol), Federal Emergency Management Agency (FEMA) reporting, and targeted collections of NASA’s L-band UAVSAR data. Findings and products derived from the adopted methodology can be useful in disaster response and mitigation activities.
Data Mining and Machine Learning for Power System Monitoring, Understanding, and Impact Evaluation
This chapter presents results from the Big Data analysis framework to improve power system situational awareness and system reliability. For this purpose, a dataset with real-world phasor measurement unit data and historical transmission system outage data has been created and used to carry out the analysis. Several statistical analysis and machine learning methods have been developed and implemented for event and anomaly detection and modeling. Detection and analysis results for actual examples of power system events are presented. Finally, data-driven characterization and risk assessment methods for weather-related extremes in power systems are developed and demonstrated on the Bonneville Power Administration system. These applications demonstrate the capability of Machine Learning (ML) methods to monitor system abnormalities, to predict system events, and to characterize the impact of extreme events on power grid
The Utility of Infrasound in Global Monitoring of Extraterrestrial Impacts: A Case Study of the 2008 July 23 Tajikistan Bolide
Abstract Among the various observational techniques used for the detection of large bolides on a global scale is a low-frequency sound known as infrasound. Infrasound, which is also one of the four sensing modalities used by the International Monitoring System, offers continuous global monitoring and can be leveraged for planetary defense. Infrasonic records can provide an additional dimension for event characterization and a distinct perspective that might not be available through any other observational method. This paper describes the infrasonic detection and characterization of the bolide that disintegrated over Tajikistan on 2008 July 23. This event was detected by two infrasound stations at distances of 1530 and 2130 km. Propagation paths to one of the stations were not predicted by the model, despite being clearly detected. The presence of the signal is attributed to the acoustic energy being trapped in a weak but leaky stratospheric AtmoSOFAR channel. The infrasound signal analysis indicates that the shock originated at the point of the main breakup at an altitude of 35 km. The primary mode of the shock production of the signal detected at the two stations was a spherical blast resulting from the main gross fragmentation episode. The energy estimate, based on the signal period, is 0.17–0.51 kt of TNT equivalent, suggesting a mass of 6.6–23.5 tons. The corresponding object radius, assuming the chondritic origin, was 0.78–1.18 m.
Integrating System State and Application Performance Monitoring: Network Contention Impact.
Abstract not provided.
Developing a Set of Indicators to Identify, Monitor, and Track Impacts and Change in Forests of the United States
United States forestland is an important ecosystem type, land cover, land use, and economic resource that is facing several drivers of change including climatic. Because of its significance, forestland was identified through the National Climate Assessment(NCA) as a key sector and system of concern to be included in a system of climate indicators as part of a sustained assessment effort. Here, we describe 11 informative core indicators of forests and climate change impacts with metrics available or nearly available for use in the NCA efforts. The recommended indicators are based on a comprehensive conceptual model which recognizes forests as a land use, an ecosystem, and an economic sector. The indicators cover major forest attributes such as extent, structural components such as biomass, functions such as growth and productivity, and ecosystem services such as biodiversity and outdoor recreation. Interactions between humans and forests are represented through indicators focused on the wildland-urban interface, cost to mitigate wildfire risk, and energy produced from forest-based biomass. Selected indicators also include drought and disturbance from both wildfires and biotic agents. The forest indicators presented are an initial set that will need further refinement in coordination with other NCA indicator teams. Our effort ideally will initiate the collection of critical measurements and observations and lead to additional research on forest-climate indicators.
Distributed Impact Detector System (DIDS) Health Monitoring System Evaluation
Damage due to impacts from micrometeoroids and orbital debris is one of the most significant on-orbit hazards for spacecraft. Impacts to thermal protection systems must be detected and the damage evaluated to determine if repairs are needed to allow safe re-entry. To address this issue for the International Space Station Program, Langley Research Center and Johnson Space Center technologists have been working to develop and implement advanced methods for detecting impacts and resultant leaks. LaRC funded a Small Business Innovative Research contract to Invocon, Inc. to develop special wireless sensor systems that are compact, light weight, and have long battery lifetimes to enable applications to long duration space structures. These sensor systems are known as distributed impact detection systems (DIDS). In an assessment, the NASA Engineering and Safety Center procured two prototype DIDS sensor units to evaluate their capabilities in laboratory testing and field testing in an ISS Node 1 structural test article. This document contains the findings of the assessment.
Bone Remodeling Monitor
The impact of bone loss due to different mechanical loadings in microgravity is a major concern for astronauts upon reintroduction to gravitational forces in exploration missions to the Moon and Mars. it has been shown that astronauts not only lose bone at differing rates, with levels up to 2% per month, but each astronaut will respond to bone loss treatments differently. Pre- and post-flight imaging techniques and frozen urine samples for post-flight laboratory immunoassays To develop a novel, non-invasive, highly . sensitive, portable, intuitive, and low-powered device to measure bone resorption levels in 'real time' to provide rapid and Individualized feedback to maximize the efficacy of bone loss countermeasures 1. Collect urine specimen and analyze the level of bone resorption marker, DPD (deoxypridinoline) excreted. 2. Antibodies specific to DPD conjugated with nanoshells and mixed with specimen, the change in absorbance from agglutination is measured by an optical device. 3. The concentration of DPD is displayed and recorded on a PDA
Acoustic emission monitoring of low velocity impact damage in graphite/epoxy laminates during tensile loading
An acoustic emission (AE) system was set up in a linear location data acquisition mode to monitor the tensile loading of eight-ply quasi-isotropic graphite/epoxy specimens containing low velocity impact damage. The impact damage was induced using an instrumented drop weight tower. During impact, specimens were supported by either an aluminum plate or a membrane configuration. Cross-sectional examinations revealed that the aluminum plate configuration resulted in primarily matrix cracking and back surface fiber failure. The membrane support resulted in only matrix cracking and delamination damage. Penetrant enhanced radiography and immersion ultrasonics were used in order to assess the amount of impact damage in each tensile specimen. During tensile loading, AE reliably detected and located the damage sites which included fiber failure. All specimens with areas of fiber breakage ultimately failed at the impact site. AE did not reliably locate damage which consisted of only delaminations and matrix cracking. Specimens with this type of damage did not ultimately fail at the impact site. In summary, AE demonstrated the ability to increase the reliability of structural proof tests; however, the successful use of this technique requires extensive baseline testing.
Modeling of fission and activation products in molten salt reactors and their potential impact on the radionuclide monitoring stations of the International Monitoring System
Molten Salt Reactors (MSRs) are one of six Generation IV reactor designs currently under development around the world. Because of the unique operating conditions of MSRs, which include molten fuel and the continuous removal of gaseous fission products during operation, work was performed to analyze the potential impact of emissions on the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Simulations were performed to predict the production of IMS-relevant radionuclides in four MSR designs operating under two scenarios: (1) a sealed reactor with releases only during operational shutdown, and (2) continuous reprocessing or sparging of the fuel salt. From these production estimates the radioxenon and radioiodine signatures were extracted and compared to three current reactor designs (Pressurized Water Reactor (PWR), BWR, RBMK). In cases where continuous reprocessing of the fuel salt occurred, both the radioxenon and radioiodine signatures were nearly indistinguishable from a nuclear explosion. Estimates were also made of the potential emission rate of radioxenon for three reactor designs and it was found that MSRs have the potential to emit radioxenon isotopes at a rate of 10^15-8×10^16 Bq/d for 133Xe if no abatement is used. An assessment was made of activation products using a candidate fuel salt (FLiBe) mixed with corrosion products for the Thorium Molten Salt Reactor (TMSR-LF1).
Modeling of fission and activation products in molten salt reactors and their potential impact on the radionuclide monitoring stations of the International Monitoring System
Molten Salt Reactors (MSRs) are one of six Generation IV reactor designs currently under development around the world. Because of the unique operating conditions of MSRs, which include molten fuel and the continuous removal of gaseous fission products during operation, work was performed to analyze the potential impact of emissions on the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Simulations were performed to predict the production of IMS-relevant radionuclides in four MSR designs operating under two scenarios – (1) a sealed reactor with releases only during operational shutdown and (2) continuous reprocessing or sparging of the fuel salt. From these production estimates the radioxenon and radioiodine signatures were extracted and compared to three current reactor designs (PWR, BWR, RBMK). In the cases where continuous reprocessing of the fuel salt occurred both the radioxenon and radioiodine signatures are nearly indistinguishable from a nuclear explosion. Estimates were also made of the potential emission rate of radioxenon for three reactor designs and it was found that MSRs have the potential to emit radioxenon isotopes at a rate of 1015 – 8×1016 Bq/d for 133Xe if no abatement is used. An assessment was also made of activation products using a candidate fuel salt (FLiBe) mixed with corrosion products for the Thorium Molten Salt Reactor (TMSR-LF1)
Damage Detection Sensor System for Aerospace and Multiple Applications
The damage detection sensory system is an intelligent damage detection ‘skin’ that can be embedded into rigid or flexible structures, providing a lightweight capability for in-situ health monitoring for applications such as spacecraft, expandable or inflatable structures, extravehicular activities (EVA) suits, smart wearables, and other applications where diagnostic impact damage monitoring might be critical. The sensor systems can be customized for detecting location, damage size, and depth, with velocity options and can be designed for particular environments for monitoring of impact or physical damage to a structure. The operation of the sensor detection system is currently based on the use of parallel conductive traces placed on a firm or flexible surface. Several detection layers can be implemented, where alternate layers are arranged in orthogonal direction with respect to the adjacent layers allowing for location and depth calculations. Increased flexibility of the damage detection sensor system designs will also be introduced.
NRAP Recommended Practices for Containment Assurance and Leakage Risk Quantification
This report presents recommendations for quantitatively assessing and managing leakage risk and effective containment assurance at geologic carbon storage (GCS) sites, amidst uncertainty in site characteristics and performance. These recommended practices are a product of the U.S. Department of Energy’s (DOE) Office of Fossil Energy and Carbon Management’s National Risk Assessment Partnership (NRAP)—a multi-year collaborative research effort of Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, National Energy Technology Laboratory, and Pacific Northwest National Laboratory. These recommended practices are organized as a set of conceptual workflows that correspond with the stages of the GCS project lifecycle. They consider aspects of site characterization, quantification of potential leakage, assessing the spatial extent of potential environmental impacts, optimizing monitoring design for detection of potential leakage, evaluation of concordance between monitored and forecasted reservoir response, assessing conformance with expected/accepted performance, and determination of the timeline over which risk of impactful leakage can be expected to abate. These conceptual workflows are intended to aid stakeholders in making risk management decisions at GCS sites and to support development of sound, risk-based justifications for characterizing the subsurface, defining area of potential leakage impact, designing site monitoring plans, selecting leakage risk management/mitigation alternatives, and estimating site closure timelines.
Impact of the Ozone Monitoring Instrument Row Anomaly on the Long-Term Record of Aerosol Products
Since about three years after the launch the Ozone Monitoring Instrument (OMI) on the EOS-Aura satellite, the sensor's viewing capability has been affected by what is believed to be an internal obstruction that has reduced OMI's spatial coverage. It currently affects about half of the instrument's 60 viewing positions. In this work we carry out an analysis to assess the effect of the reduced spatial coverage on the monthly average values of retrieved aerosol optical depth (AOD), single scattering albedo (SSA) and the UV Aerosol Index (UVAI) using the 2005-2007 three-year period prior to the onset of the row anomaly. Regional monthly average values calculated using viewing positions 1 through 30 were compared to similarly obtained values using positions 31 through 60, with the expectation of finding close agreement between the two calculations. As expected, mean monthly values of AOD and SSA obtained with these two scattering-angle dependent subsets of OMI observations agreed over regions where carbonaceous or sulphate aerosol particles are the predominant aerosol type. However, over arid regions, where desert dust is the main aerosol type, significant differences between the two sets of calculated regional mean values of AOD were observed. As it turned out, the difference in retrieved desert dust AOD between the scattering-angle dependent observation subsets was due to the incorrect representation of desert dust scattering phase function. A sensitivity analysis using radiative transfer calculations demonstrated that the source of the observed AOD bias was the spherical shape assumption of desert dust particles. A similar analysis in terms of UVAI yielded large differences in the monthly mean values for the two sets of calculations over cloudy regions. On the contrary, in arid regions with minimum cloud presence, the resulting UVAI monthly average values for the two sets of observations were in very close agreement. The discrepancy under cloudy conditions was found to be caused by the parameterization of clouds as opaque Lambertian reflectors. When properly accounting for cloud scattering effects using Mie theory, the observed UVAI angular bias was significantly reduced. The analysis discussed here has uncovered important algorithmic deficiencies associated with the model representation of the angular dependence of scattering effects of desert dust aerosols and cloud droplets. The resulting improvements in the handling of desert dust and cloud scattering have been incorporated in an improved version of the OMAERUV algorithm.
Simulation Framework for Cosmic Ray Muon Impact on Radiation Portal Monitors
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