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Title: Synthesis of Disparate Optical Imaging Data for Space Domain Awareness

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Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
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Conference: Presented at: Advanced Maui Optical and Space Surveillance Technologies Conference, Maui, HI, United States, Sep 20 - Sep 23, 2016
Country of Publication:
United States

Citation Formats

Schneider, M D, and Dawson, W A. Synthesis of Disparate Optical Imaging Data for Space Domain Awareness. United States: N. p., 2016. Web.
Schneider, M D, & Dawson, W A. Synthesis of Disparate Optical Imaging Data for Space Domain Awareness. United States.
Schneider, M D, and Dawson, W A. 2016. "Synthesis of Disparate Optical Imaging Data for Space Domain Awareness". United States. doi:.
title = {Synthesis of Disparate Optical Imaging Data for Space Domain Awareness},
author = {Schneider, M D and Dawson, W A},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 9

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  • Rapid assessment of space weather effects on satellites is a critical step in anomaly resolution and satellite threat assessment. That step, however, is often hindered by a number of factors including timely collection and delivery of space weather data and the inherent com plexity of space weather information. As part of a larger, integrated space situational awareness program, Los Alamos National Laboratory has developed prototype operational space weather tools that run in real time and present operators with customized, user-specific information. The Dynamic Radiation Environment Assimilation Model (DREAM) focuses on the penetrating radiation environment from natural or nuclear-produced radiation belts.more » The penetrating radiation environment is highly dynamic and highly orbit-dependent. Operators often must rely only on line plots of 2 MeV electron flux from the NOAA geosynchronous GOES satellites which is then assumed to be representative of the environment at the satellite of interest. DREAM uses data assimilation to produce a global, real-time, energy dependent specification. User tools are built around a distributed service oriented architecture (SOA) which will allow operators to select any satellite from the space catalog and examine the environment for that specific satellite and time of interest. Depending on the application operators may need to examine instantaneous dose rates and/or dose accumulated over various lengths of time. Further, different energy thresholds can be selected depending on the shielding on the satellite or instrument of interest. In order to rapidly assess the probability that space weather was the cause of anomalous operations, the current conditions can be compared against the historical distribution of radiation levels for that orbit. In the simplest operation a user would select a satellite and time of interest and immediately see if the environmental conditions were typical, elevated, or extreme based on how often those conditions occur in that orbit. This allows users to rapidly rule in or out environmental causes of anomalies. The same user interface can also allow users to drill down for more detailed quantitative information. DREAM can be run either from a distributed web-based user interface or as a stand-alone application for secure operations. In this paper we discuss the underlying structure of the DREAM model and demonstrate the user interface that we have developed . We also present some prototype data products and user interfaces for DREAM and discuss how space environment information can be seamlessly integrated into operational SSA systems.« less
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  • Potential CO{sub 2} reservoirs are often geologically complex and possible leakage pathways such as those created. Reservoir heterogeneity can affect injectivity, storage capacity, and trapping rate. Similarly, discontinuous caprocks and faults can create risk of CO{sub 2} leakage. The characteristics of potential CO{sub 2} reservoirs need to be well understood to increase confidence in injection project success. Reservoir site characterization will likely involve the collection and integration of multiple geological, geophysical, and geochemical data sets. We have developed a computational tool to more realistically render lithologic models using multiple geological and geophysical techniques. Importantly, the approach formally and quantitatively integratesmore » available data and provides a strict measure of probability and uncertainty in the subsurface. The method will characterize solution uncertainties whether they stem from unknown reservoir properties, measurement error, or poor sensitivity of geophysical techniques.« less
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