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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.

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Orbit response measurements with oscillating trajectories

Optical properties of components in a linac can be reconstructed from analysis of the orbit response matrix, composed from responses of BPMs to changes in currents of dipole correctors. An efficient way to record such response, discussed in this note, is to excite the corrector current with a sine wave and record its Fourier component of the BPM spectrum. Because of a narrow band of the excitation signal, response to multiple correctors can be recorded at the same time without significantly affecting the signal-to-noise ratio. For that, the correctors are oscillated at different frequencies, and the corresponding BPM Fourier components are recorded. In an ion (non-relativistic) linac, similar measurements can be performed for the longitudinal plane as well. Examples of measurements at the PIP2IT test linac are shown.

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Radial-offset Optics in EIC Hadron Lattices: Trajectory Lengthening

This Tech. Note describes a method for a radial orbit offset in the arcs of the EIC hadron lattices, based on the perturbation dB/B of the magnetic field of the arc main bend magnets. This can be done independently for each arc (allowing multiple rigidities) and requires the use of pairs of orbit correctors at the extremities of the arc to ensure that the radially shifted orbit is on the zero-orbit (i.e. with the horizontal coordinates x = 0, p x = 0) at the exit and entry point of the respectively upstream and downstream interaction region (IR). The goal is to produce appropriate orbit lengthening as required for time of flight adjustments between the electron and hadron beams as part of EIC operations. An ad hoc parameter is introduced: a “geometric compaction factor” α B = (dC/C)/(dB/B), to quantify the orbit lengthening, or equivalently the radial orbit shift dR = R · α B · dB/B, from bending perturbation. Detailed numerical results are produced and discussed.

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Understanding Event Trajectories Across Massive Temporal Datasets with Word Embeddings and Visualization

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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Modeling alignment of electron trajectory in cooling section of EIC Low Energy Cooler

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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