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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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Radiosonde‐to‐Space (R2S) Atmospheric Specifications: Bridging Observations and Models for Infrasound Propagation
Manuscript for submission to GRL. Must also pass HQ Interagency Review before submission to journal.
Supporting data for the journal article titled "Multi-parameter constraints on empirical infrasound period–yield relations for bolides and implications for planetary defense"
This supporting dataset comprises input files, regression output files, and associated plots that document the analytical framework used in the study.
Infrasound Detection, Geolocation, and Yield Estimate of the May 2026 Blue Origin New Glenn Static-Fire Explosion
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Modeling Partial Reflection Paths for Infrasound Analysis
Numerical methods enabling simulation of scattered and partially reflected infrasonic propagation paths produced by interaction with fine-scale structure in the middle atmosphere have been implemented in the infraGA ray tracing software. This capability enables simulation of ensonification in the classical stratospheric “shadow zone” that has been observed during the Humming Roadrunner and LSECE surface explosion campaigns as well as in other data sets. In the case of LSECE, a pair of stations roughly 140 kilometers east of the source location observed arrivals with celerities (horizontal group velocities) slightly slower than observed stratospheric paths at similar azimuths. The arrivals exhibited increasing trace velocity later in the wavetrain indicating a steepening of the arrival path for longer or slower propagation paths. Simulation of partially reflected paths using the updated infraGA software methods finds good agreement between observed and predicted infrasonic ensonification at these locations within the stratospheric shadow zone. Further development of the partial reflection physics and comparison with other data sets is needed to more robustly understand how such anomalous infrasonic signals can be predicted; however, the demonstration of this capability is a promising first step in such analyses.
Synthetic Infrasound Data for Machine Learning Detectors
Synthetic data is a powerful tool to generate large amounts of training data for machine learning models. The methods outlined in this report will be used to retrain the deep learning classifier for increased accuracy. Synthetic data will be useful to address the natural class imbalance between the different categories in the original ML work. Additionally, these tools will be applied for a variety of signal analysis methods that would use signals with a known signal-to-noise ratio for validation and testing.
Leveraging infrasound for estimating the characteristics of shock waves generated by large bolides
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Multi-station infrasound detections of shock waves produced by high-altitude shallow entry angle fireballs
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Infrasound as a Method of Characterizing Atmospheric Objects
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Quantifying bolide yield through infrasound analysis: Implications for planetary defense
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Infrasound Sensor Performance at Extreme Temperatures and Low Frequencies
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Quantifying bolide energy through infrasound analysis: A case study of the 2023 Australian event
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Leveraging multi-station infrasound detections for characterization of high-altitude fireballs
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Infrasound detections of the OSIRIS-REx Sample Return Capsule re-entry
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Leveraging infrasound detected by stations of the IMS network for estimating the characteristics of shock waves generated by large bolides
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Infrasound detections of the OSIRIS-REx Sample Return Capsule re-entry
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Detection and characterization of meteor-generated shock waves using infrasound sensing
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Investigation of Early Arrival of Infrasound Signals Generated by Bolide Entries
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