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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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Towards Building an Automatic Array QC Tool from Signal Singular Values .
Abstract not provided.
Applying Geochemical Signals and Statistical Tools to Ensure CO2 Storage through Water Monitoring
2022 Carbon Management Project Review Meeting, Pittsburgh, PA, August 15-19, 2022
S&T Work in Progress Seminar: Mach-Zehnder fiber-optic modulators for high-bandwidth signal recording
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Signals of a New Gauge Boson from IceCube and Muon $g-2$
A $Z'$ boson associated with a broken $U(1)_{L_{\mu} - L_{\tau}}$ gauge symmetry offers an economical solution to the long-standing $g_\mu-2$ anomaly, confirmed and strengthened by recent measurements at Fermilab. Here, we revisit the impact of such a $Z'$ on the spectrum of high-energy astrophysical neutrinos, as measured by the IceCube experiment. This spectrum has been observed to exhibit a dip-like feature at $E_{\nu} \sim 0.2-1 \, {\rm PeV}$, which could plausibly arise from the physics of the sources themselves, but could also be the consequence of high-energy neutrinos resonantly scattering with the cosmic neutrino background, mediated by a $Z'$ with a mass on the order of $m_{Z'} \sim 10 \, {\rm MeV}$. In this study, we calculate the impact of such a $Z'$ on the high-energy neutrino spectrum for a variety of model parameters and source distributions. For couplings that can resolve the $g_{\mu}-2$ anomaly, we find that this model could self-consistently produce a spectral feature that is consistent with IceCube's measurement, in particular if the neutrinos observed by IceCube predominantly originate from high-redshift sources.
Detector Wall Research for Fast Gamma Signal Detection in Neutron-Diagnosed Subcritical Experiment Applications
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Incorporation of Market Signals for the Optimal Design and Operation of Flexible Post-Combustion Capture Systems
The presentation was delivered at the 2022 American Institute of Chemical Engineers (AIChE) annual meeting.
Detector Wall Research for Fast Gamma Signal Detection in Neutron-Diagnosed Subcritical Experiment Applications
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Sampling synchronization through GPS signals
A method uses a distributed data acquisition system with multiple, physically unconnected, data acquisition units, that can be in wireless communication with a remote host, to timestamp measurement data with sub-microsecond time base accuracy of sampling clock relative to an absolute timeframe. A current absolute time is derived from messages received from a satellite radio beacon positioning system (GPS). Measurement data is sampled by each unit at a specified sampling rate. Using hardware logic, batches of sampled data are associated with corresponding timestamps representing the absolute time at which the data was sampled. Data and timestamps may be transmitted to the host. A time offset bias is compensated by comparing timestamps against a nominal time based on start time and nominal sampling rate. The sampling clock rate may be disciplined using time pulses from the GPS receiver. An initial start of data sampling by all units can also be synchronized.
Characterization of Seismic Signals from Air Filtration Systems in a Nuclear Facility.
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Government Perspective: Signals from microbiology and network analysis of unconventional oil environments
Invited presentation to the American Society for Microbiology Microbe meeting in Houston, TX, June 15-19, 2023
Small-signal Approximations of Frequency Estimation Algorithms.
Abstract not provided.
A Method for Estimating the Amplitude and Phase of Oscillating Signals.
Abstract not provided.
Sample-to-answer point-of-care diagnostics using strand exchange signal processors.
Abstract not provided.
Decoding Auditory Tones from Brain Signals Recorded using OPM-MEG.
Abstract not provided.
Using Approximate Nearest Neighbor Methods to Rapidly Search Large Seismic Signal Archives.
Abstract not provided.
2022 ION GNSS+ Paper: Protecting the Skies: GNSS-less Aircraft Navigation with Terrestrial Cellular Signals of Opportunity.
Abstract not provided.
Identifying aquifer recharge signals using unsupervised machine learning: A case study of the Pajarito Plateau, NM
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