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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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At least 181 records · Page 10

Identification of Acoustic Wave Signatures in the Ionosphere From Conventional Surface Explosions Using MF/HF Doppler Sounding

Here, we present an experiment to detect one ton TNT-equivalent chemical explosions using pulsed Doppler radar observations of isodensity layers in the ionospheric E region during two campaigns. The first campaign, conducted on 15 October 2019, produced potential detections of all three shots. The detections closely resemble the temporal and spectral properties predicted using the InfraGA ray tracing and weakly nonlinear waveform propagation model. Here the model predicts that within 6.5–7.25 min of each shot a waveform peaking between 0.9 and 0.4 Hz will impact the ionosphere at 100 km. As the waves pass through this region, they will imprint their signal on an isodensity layer, which is detectable using a Doppler radar operating at the plasma frequency of the isodensity. Within the time windows of each of the three shots in the first campaign, we detect enhanced wave activity peaking near 0.5 Hz. These waves were imprinted on the Doppler signal probing an isodensity layer at 2.785 MHz near 100 km altitude. Despite these detections, the method appears to be unreliable as none of the six shots from the second campaign, conducted on 10 July 2020 were detected. The observations from this campaign were characterized by an increased acoustic noise environment in the microbarom band and persistent scintillation on the radar returns. These effects obscured any detectable signal from these shots and the baseline noise was well above the detection levels of the first campaign.

47 OTHER INSTRUMENTATION↗

Electrical Conductivity and Sound Velocities of Talc Under High Pressure and High Temperature Conditions and Application to the Subducting Cocos Plate

Talc is expected to be an important water carrier in Earth's upper mantle, and understanding its electrical and seismic properties under high pressure and temperature conditions is required to detect possible talc-rich regions in subduction zones imaged using geophysical observations. Here, we conducted acoustic and electrical experiments on natural talc aggregates at relevant pressure-temperature conditions. Compressional wave velocity (V p ) was measured using ultrasonic interferometry in a Paris-Edinburgh press at pressures up to 3.4 GPa and temperatures up to 873 K. Similar Vp values are obtained regardless of the initial crystallographic preferred orientation of the samples, which can be explained by talc grain reorientation during the experiment, with the (001) plane becoming perpendicular to the uniaxial compression axis. Electrical conductivity of the same starting material was determined using impedance spectroscopy in a multi-anvil press up to 6 GPa and 1263 K. Two conductivity jumps are observed, at ∼860–1025 K and ∼940–1080 K, depending on pressure, and interpreted as talc dehydroxylation and decomposition, respectively. Electrical anisotropy is observed at low temperature and decreases with increasing pressure (∼10 at 1.5 GPa and ∼2 at 3.5 GPa). Comparison of acoustic and electrical results with geophysical observations in central Mexico supports the presence of a talc-bearing layer atop the subducted Cocos plate.

Cocos plate↗

Use of vision and sound to classify feller-buncher operational state

Productivity measures in logging involve simultaneous recognition and classification of event occurrence and timing, and the volume of stems being handled. In full-tree felling systems these measurements are difficult to implement in an autonomous manner because of the unfavorable working environment and the abundance of confounding extraneous events. This paper proposed a vision method that used a lowcost camera to recognize feller-buncher operational events including tree cutting and piling. It used a fine K-nearest neighbors (fKNN) algorithm as the final classifier based on both audio and video features derived from short video segments as inputs. The classifier’s calibration accuracy exceeds 94%. The trained model was tested on videos recorded under various conditions. The overall accurate rates for short segments were greater than 89%. Comparisons were made between the human- and algorithm derived event detection rates, events’ durations, and inter-event timing using continuously recorded videos taken during feller operation. Video results between the fKNN model and manual observation were similar. Statistical comparison using the Kolmogorov–Smirnov test to evaluate measured parameters’ distributions (manual versus automated event duration and inter-event timing) did not show significant differences with the lowest P-value among all Kolmogorov–Smirnov tests equal to 0.12. Here the result indicated the feasibility and potential of using the method for the automatic time study of drive-to-tree feller bunchers.

97 MATHEMATICS AND COMPUTING↗

Sub-millisecond keyhole pore detection in laser powder bed fusion using sound and light sensors and machine learning

Laser powder bed fusion is a mainstream additive manufacturing technology widely used to manufacture complex parts in prominent sectors, including aerospace, biomedical, and automotive industries. However, during the printing process, the presence of an unstable vapor depression can lead to a type of defect called keyhole porosity, which is detrimental to the part quality. In this study, we developed an effective approach to locally detect the generation of keyhole pores during the printing process by leveraging machine learning and a suite of optical and acoustic sensors. Simultaneous synchrotron x-ray imaging allows the direct visualization of pore generation events inside the sample, offering high-fidelity ground truth. A neural network model adopting SqueezeNet architecture using single-sensor data was developed to evaluate the fidelity of each sensor for capturing keyhole pore generation events. Our comparative study shows that the near infrared images gave the highest prediction accuracy, followed by 100 kHz and 20 kHz microphones, and the photodiode sensitive to processing laser wavelength had the lowest accuracy. Using a single sensor, over 90% prediction accuracy can be achieved with a temporal resolution as short as 0.1 ms. A data fusion scheme was also developed with features extracted using SqueezeNet neural network architecture and classification using different machine learning algorithms. Our work demonstrates the correlation between the characteristic optical and acoustic emissions and the keyhole oscillation behavior, and thereby provides strong physics support for the machine learning approach.

36 MATERIALS SCIENCE↗

Diurnal Variation of the Planetary Boundary Layer Height Observed from GNSS Radio Occultation and Radiosonde Soundings over the Southern Great Plains

>The planetary boundary layer (PBL) height (PBLH) is a key physical parameter of the PBL affected by numerous physical processes within the boundary layer. Specifically, the PBLH over land exhibits large spatial and temporal variation across different geographical regions. In this study, the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation (RO) profiles and high-resolution radiosonde profiles from 2007 to 2013 were analyzed to estimate the diurnal cycle of the PBLH over the Southern Great Plains (SGP) in the United States. Large variations in PBLH derived from radiosonde temperature, moisture, and refractivity are observed on seasonal scales. COSMIC RO is capable of observing diurnal and seasonal variations in the terrestrial PBLH over the SGP region. Annual mean diurnal amplitude of approximately 250 m in the terrestrial PBLH was observed, with maxima occurring at around 1500 local solar time (LST) in both the collocated radiosondes and COSMIC RO profiles. Seasonal changes in the PBLH diurnal cycles ranging from approximately 100 to 400 m were also observed. Such PBL diurnal and seasonal changes can be further incorporated into PBL parameterizations to help improve weather and climate model prediction. Significance Statement. The atmospheric planetary boundary layer (PBL) and its height (PBLH) control many atmospheric processes that affect our everyday lives. Observations of the PBL are usually limited to radiosondes at limited time intervals. GNSS radio occultation (RO) provide high-vertical-resolution atmospheric observations that are ideal for PBL study. This study demonstrates that the GNSS RO is capable of capturing the diurnal and seasonal variations of the PBLH over the southern Great Plains (SGP) well as compared to the collocated radiosonde observations.

54 ENVIRONMENTAL SCIENCES↗

Sound speed and refractive index of amorphous CaSiO3 upon pressure cycling to 40 GPa

Abstract Brillouin spectroscopy at room temperature and pressures up to 40 GPa documents nearly identical elasticity and refractive index of amorphous CaSiO3 created by two different methods: temperature-quenching the melt at ambient pressure and pressure-amorphizing crystalline wollastonite at room temperature. We find reproducible hysteresis of 0 to 8% on pressure cycling that is small relative to the 30 to 60% changes in shear and longitudinal wave velocities over this pressure range. Together with observed changes in refractive index and previous results from Raman spectroscopy, these measurements reveal a continuous and reversible change in atomic packing induced by pressure. Unlike many other silicate glasses, amorphous CaSiO3 exhibits highly reproducible properties, behaving smoothly and reversibly under pressure cycling and possessing similar structure and elasticity regardless of synthesis paths for the starting material, which suggests that the amorphous solid may mimic the liquid over the pressure range investigated.

Geochemistry & Geophysics↗