Linear Covariance Analysis Framework for Aerospace Vehicle Trajectory Modeling and Parametric Design.
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In collaboration with researchers from Virginia Tech, Savannah River National Laboratory has continued development of a natural language processing pipeline to identify and extract events of interest from massive open data sources in the domain of worldwide state-sponsored civil nuclear energy. The foundation of the pipeline is built on compass aligned temporal word embedding models, whereby contextual shifts are automatically identified by comparing keyword embedding vectors across successive time windows. Within the approach, a contextual shift indicates the occurrence of a potential event of interest. However, in such a broad topical domain that captures events at a global scale, across various life cycle stages, and across numerous different technology types, a user that is monitoring events may have broad interests in capturing many different event types with varying degrees of signal. As such, the quantity of information that may be returned from an automated event extraction pipeline can be substantial, requiring manual effort to sift through the information to identify any relevant bits of information. Therefore, a more streamlined workflow that aids in directing a user toward specific information at different points in time is necessary. The workflow presented here has been developed with this concept in mind, built on top of the initial prototype event extraction pipeline, whereby a user can analyze temporal text-based data sources at multiple different contextual levels to isolate key points in time and key subdomains captured within a data corpus. Using multiple corpuses that consist of approximately 7 million Tweets and 7 million news articles, the team has extended compass aligned temporal word embedding models to establish an interconnected and hierarchical structure that relates known key words of interest to documents, local topics (i.e., within a time window), and global topics across the corpuses. All of this information is packaged into a visual analytics system that is linked to the information extraction pipeline and enables a user to identify contextual information that describes the evolution of a high dimensional embedding space across time to isolate changes of interest and explore associated events. This report demonstrates the use of these analytics and a means to fuse information across multiple datasets.
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The Electron Ion Collider (EIC) requires cooling of protons at the injection energy to obtain emittances needed to achieve the design luminosity. The low energy cooler (LEC) provides such a capability. The LEC is an electron cooler utilizing a non-magnetized, RF-based electron cooling. This approach to cooling was successfully used in Low Energy RHIC Electron Cooler (LEReC).
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Recording changes in beam transverse positions re-ported by Beam Position Monitors (BPMs) in response to a beam deflection by an upstream dipole corrector (orbit response) is a powerful tool for analysis of accelerator optics and assisting with machine tuning. In the Fermilab Linac, orbit responses are recorded by oscillating the currents of up to 19 correctors, providing faster, drift-resistant measurements through frequency-domain analysis. This report describes the technique, including error estimations and consistency checks and shows an example of the measurements.