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DOE OSTI2024

Underground hydrogen storage leakage detection and characterization based on machine learning of sparse seismic data

Underground hydrogen storage (UHS) is considered as a scalable approach for massive storage and seasonal extraction of hydrogen (H 2 ). Although conventional leakage detection and characterization methods based on time-lapse seismic imaging and inversion generally apply to H 2 leakage detection problem, a high-fidelity yet cost effective geophysics approach is still missing to reliably inform leakage location and properties based on very sparse data. In response, we develop a novel supervised machine learning method to detect and characterize H 2 leakage from UHS. The input to our neural network are sparse time-lapse seismic waveforms, while the output from the neural network includes the spatial location and physical properties of a H 2 leakage. Here, we generate high-quality time-lapse waveforms using the elastic-wave equations to train the neural network. We train and validate our machine learning model and find that it attains high accuracy in using extremely sparse time-lapse seismic data to detect and characterize H 2 leakage. Our investigation is the first systematic study that focuses on applying machine learning to subsurface H 2 leakage detection and characterization and could potentially serve as a cost-effective geophysical tool for underground hydrogen leakage detection and characterization with high fidelity.

08 HYDROGEN↗

DOE OSTI2021

Aftershock Identification Using a Paired Neural Network Applied to Constructed Data

This report is intended to detail the findings of our investigation of the applicability of machine learning to the task of aftershock identification. The ability to automatically identify nuisance aftershock events to reduce analyst workload when searching for events of interest is an important step in improving nuclear monitoring capabilities and while waveform cross - correlation methods have proven successful, they have limitations (e.g., difficulties with spike artifacts, multiple aftershocks in the same window) that machine learning may be able to overcome. Here we apply a Paired Neural Network (PNN) to a dataset consisting of real, high quality signals added to real seismic noises in order to work with controlled, labeled data and establish a baseline of the PNN's capability to identify aftershocks. We compare to waveform cross - correlation and find that the PNN performs well, outperforming waveform cross - correlation when classifying similar waveform pairs, i.e., aftershocks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Mapping Glacier Basal Sliding Applying Machine Learning

During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Ka-Band GaN-on-SiC MMIC Balanced High Power Amplifier for NASA's Lunar Missions

The feasibility of Ka-band GaN-on-SiC MMIC based balanced power amplifier for science data downlinks from NASA’s lunar mission assets in space is investigated. The balanced amplifier combines the RF output power from two power amplifiers using a rectangular waveguide based 3-dB hybrid coupler. The investigation includes characterizing the balanced amplifier for the overall RF output power, Gain, power added efficiency, RMS error vector magnitude for offset-QPSK, 8PSK, 16APSK, and 32APSK waveforms, 3rd order intermodulation products, and noise figure. The balanced amplifier has high output RF power and good linearity and can support high data rate downlinks from the surface and vicinity of the Moon to Earth.

Gallium Nitride↗

NASA NTRS1989

Ice-type classifications from airborne pulse-limited radar altimeter return waveform characteristics

During mid-March 1978, the NASA C-130 aircraft was deployed to Eielson Air Force Base in Fairbanks, Alaska, to make a series of flights over ice in the Beaufort Sea. The radar altimeter data analyzed were obtained northeast of Mackenzie Bay on March 14th in the vicinity of 69.9 deg N, 134.2 deg W. The data were obtained with a 13.9 GHz radar altimeter developed under the NASA Advanced Applications Flight Experiments (AAFE) Program. This airborne radar was built as a forerunner of the Seasat radar altimeter, and utilized the same pulse compression technique. Pulse-limited radar data taken with the altimeter from 1500-m altitude over sea ice are registered to high-quality photography. The backscattered power is statistically related the surface conductivity and to the number of facets whose surface normal is directed towards the radar. The variations of the radar return waveform shape and signal level are correlated with the variation of the ice type determined from photography. The AAFE altimeter has demonstrated that the return waveform shape and signal level of an airborne pulse-limited altimeter at 13.9 GHz respond to sea ice type. The signal level responded dramatically to even a very small fracture in the ice, as long as it occurred directly at the altimeter nadir point. Shear zones and regions of significant compression ridging consistently produced low signal levels. The return waveforms frequently evidenced the characteristics of both specular and diffuse scattering, and there was an indication that the power backscattered at 3 deg off-nadir in a shear zone was actually somewhat higher than that from nadir.

Fedor, L. S.↗

DOE OSTI2026

First light from beam neutrinos on an LAPPD in ANNIE

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is both a physics experiment and a technology testbed for next-generation light-based neutrino detection. In this paper, we report the first demonstration of a fully integrated Large Area Picosecond Photodetector (LAPPD) operating in a running neutrino beam experiment. Particular focus is given to the design, commissioning, and successful deployment of the Packaged ANNIE LAPPD (PAL), a waterproof, self-triggering module incorporating fast waveform digitization and precision timing synchronized to the ANNIE detector subsystems. We identify beam-correlated LAPPD data frames consistent with charged-current neutrino interactions observed in multiple detector subsystems, establishing the first detection of neutrino-induced Cherenkov light with an LAPPD. These results validate the system-level performance of LAPPDs under realistic experimental conditions — including long-term stability, timing synchronization, and event matching with conventional PMT and muon detector systems — marking a critical step toward their deployment in future large-scale neutrino and particle detectors.

Cherenkov detectors↗

DOE OSTI2019

Search for Subsolar Mass Ultracompact Binaries in Advanced LIGO’s Second Observing Run

Here, we present a search for subsolar mass ultracompact objects in data obtained during Advanced LIGO's second observing run. In contrast to a previous search of Advanced LIGO data from the first observing run, this search includes the effects of component spin on the gravitational waveform. We identify no viable gravitational-wave candidates consistent with subsolar mass ultracompact binaries with at least one component between $0.2 M_{⊙}-1.0 M_{⊙}$. We use the null result to constrain the binary merger rate of ($0.2 M_{⊙}, 0.2 M_{⊙}$) binaries to be less than $3.7×10^{5} Gpc^{-3} yr^{-1}$ and the binary merger rate of ($1.0 M_{⊙}, 1.0 M_{⊙}$) binaries to be less than $5.2×10^{3} Gpc^{-3} yr^{-1}$. Subsolar mass ultracompact objects are not expected to form via known stellar evolution channels, though it has been suggested that primordial density fluctuations or particle dark matter with cooling mechanisms and/or nuclear interactions could form black holes with subsolar masses. Assuming a particular primordial black hole (PBH) formation model, we constrain a population of merging $0.2 M_{⊙}$ black holes to account for less than 16% of the dark matter density and a population of merging $1.0 M_{⊙}$ black holes to account for less than 2% of the dark matter density. We discuss how constraints on the merger rate and dark matter fraction may be extended to arbitrary black hole population models that predict subsolar mass binaries.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

A Weather Radar Simulator for the Evaluation of Polarimetric Phased Array Performance

A radar simulator capable of generating time series data for a polarimetric phased array weather radar has been designed and implemented. The received signals are composed from a high-resolution numerical prediction weather model. Thousands of scattering centers, each with an independent randomly generated Doppler spectrum, populate the field of view of the radar. The moments of the scattering center spectra are derived from the numerical weather model, and the scattering center positions are updated based on the three-dimensional wind field. In order to accurately emulate the effects of the system-induced cross-polar contamination, the array is modeled using a complete set of dual-polarization radiation patterns. The simulator offers reconfigurable element patterns and positions as well as access to independent time series data for each element, resulting in easy implementation of any beamforming method. It also allows for arbitrary waveform designs and is able to model the effects of quantization on waveform performance. Simultaneous, alternating, quasi-simultaneous, and pulse-to-pulse phase coded modes of polarimetric signal transmission have been implemented. This framework allows for realistic emulation of the effects of cross-polar fields on weather observations, as well as the evaluation of possible techniques for the mitigation of those effects.

phased array↗

DOE OSTI2020

ADC Nonlinearity Correction for the Majorana Demonstrator

Imperfections in analog-to-digital conversion cannot be ignored when signal digitization requirements demand both wide dynamic range and high resolution, as is the case for the MAJORANA DEMONSTRATOR 76 Ge neutrinoless double beta decay search. Enabling the experiment's high-resolution spectral analysis and efficient pulse shape discrimination required careful measurement and correction of ADC nonlinearites. Here, a simple measurement protocol was developed that did not require sophisticated equipment or lengthy data taking campaigns. A slope-dependent hysteresis was observed and characterized. A correction applied to digitized waveforms prior to signal processing reduced the differential and integral nonlinearites by an order of magnitude, eliminating these as dominant contributions to the systematic energy uncertainty at the double-beta decay Q value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2012

TALENT User's Manual

The Ground-Based Monitoring R and E Component Evaluation project performs testing on the hardware components that make up Seismic and Infrasound monitoring systems. The majority of the testing is focused on the Digital Waveform Recorder (DWR), Seismic Sensor, and Infrasound Sensor. The software tool used to capture and analyze the data collected from testing is called TALENT: Test and Analysis Evaluation Tool. This document is the manual for using TALENT. Other reports document the testing procedures that are in place (Kromer, 2007) and the algorithms employed in the test analysis (Merchant, 2011).

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Comparing the predictive capabilities of subjective crackle metrics using leave-one-out cross validation

Leave-one-out cross validation was used to show the capability to predict crackling sound quality based on the use of the standard deviation of the time-varying sharpness and the skewness of the derivative of the pressure waveform. The predictive output of this method implies that the more sophisticated fits used to describe this data were not overfit, but instead exhibited substantial predictive value.

Swift, Stephen Hales [Sandia National Laboratories↗

NASA NTRS1976

The leaking mode problem in atmospheric acoustic-gravity wave propagation

The problem of predicting the transient acoustic pressure pulse at long horizontal distances from large explosions in the atmosphere is examined. Account is taken of poles off the real axis and of branch line integrals in the general integral governing the transient waveform. Perturbation techniques are described for the computation of the imaginary ordinate of the poles and numerical studies are described for a model atmosphere terminated by a halfspace with c = 478 m/sec above 125 km. For frequencies less than 0.0125 rad/sec, the GR sub 1 mode, for example, is found to have a frequency dependent amplitude decay of the order of 0.0001 nepers/km. Examples of numerically synthesized transient waveforms are exhibited with and without the inclusion of leaking modes. The inclusion of leaking modes results in waveforms with a more marked beginning rather than a low frequency oscillating precursor of gradually increasing amplitude. Also, the revised computations indicate that waveforms invariably begin with a pressure rise, a result supported by other theoretical considerations and by experimental data.

Kinney, W. A.↗

NASA NTRS1986

A general numerical analysis program for the superconducting quasiparticle mixer

A user-oriented computer program SISCAP (SIS Computer Analysis Program) for analyzing SIS mixers is described. The program allows arbitrary impedance terminations to be specified at all LO harmonics and sideband frequencies. It is therefore able to treat a much more general class of SIS mixers than the widely used three-frequency analysis, for which the harmonics are assumed to be short-circuited. An additional program, GETCHI, provides the necessary input data to program SISCAP. The SISCAP program performs a nonlinear analysis to determine the SIS junction voltage waveform produced by the local oscillator. The quantum theory of mixing is used in its most general form, treating the large signal properties of the mixer in the time domain. A small signal linear analysis is then used to find the conversion loss and port impedances. The noise analysis includes thermal noise from the termination resistances and shot noise from the periodic LO current. Quantum noise is not considered. Many aspects of the program have been adequately verified and found accurate.

Hicks, R. G.↗

NASA NTRS1986

Interpretation of a class of in-flight lightning signatures

Data recorded on the NASA F-106B research aircraft during lightning strikes often reveals electric field waveforms which begin with a series of abrupt changes and end in an exponential variation. A possible interpretation of such events is that an ionized channel is completed to the aircraft during the time of the abrupt changes, and the charge on the aircraft dumps into this channel during the time of the exponential. An analysis of measured waveforms assuming a simple RC-circuit model has been carried out for one event, and the results include I = 1000 A, V = -650 kV, R = 1000 Ohms, and W = 100 J.

Trost, T. F.↗

NASA NTRS2004

NASA Tech Briefs, December 2004

opics include: High-Rate Digital Receiver Board; Signal Design for Improved Ranging Among Multiple Transceivers; Automated Analysis, Classification, and Display of Waveforms; Fast-Acquisition/Weak-Signal-Tracking GPS Receiver for HEO; Format for Interchange and Display of 3D Terrain Data; Program Analyzes Radar Altimeter Data; Indoor Navigation using Direction Sensor and Beacons; Software Assists in Responding to Anomalous Conditions; Software for Autonomous Spacecraft Maneuvers; WinPlot; Software for Automated Testing of Mission-Control Displays; Nanocarpets for Trapping Microscopic Particles; Precious-Metal Salt Coatings for Detecting Hydrazines; Amplifying Electrochemical Indicators; Better End-Cap Processing for Oxidation-Resistant Polyimides; Carbon-Fiber Brush Heat Exchangers; Solar-Powered Airplane with Cameras and WLAN; A Resonator for Low-Threshold Frequency Conversion; Masked Proportional Routing; Algorithm Determines Wind Speed and Direction from Venturi-Sensor Data; Feature-Identification and Data-Compression Software; Alternative Attitude Commanding and Control for Precise Spacecraft Landing; Inspecting Friction Stir Welding using Electromagnetic Probes; and Helicity in Supercritical O2/H2 and C7H16/N2 Mixing Layers.

Source record↗

NASA NTRS2019

Search for Subsolar Mass Ultracompact Binaries in Advanced LIGO’s Second Observing Run

We present a search for subsolar mass ultracompact objects in data obtained during Advanced LIGO’s second observing run. In contrast to a previous search of Advanced LIGO data from the first observing run, this search includes the effects of component spin on the gravitational waveform. We identify no viable gravitational-wave candidates consistent with subsolar mass ultracompact binaries with at least one component between 0.2 𝑀 ⊙ –1.0 𝑀 ⊙ . We use the null result to constrain the binary merger rate of (0.2 𝑀 ⊙ , 0.2 𝑀 ⊙ ) binaries to be less than 3.7×10 5 Gpc −3 yr −1 and the binary merger rate of (1.0 𝑀 ⊙ , 1.0 𝑀 ⊙ ) binaries to be less than 5.2×10 3 Gpc −3 yr −1 . Subsolar mass ultracompact objects are not expected to form via known stellar evolution channels, though it has been suggested that primordial density fluctuations or particle dark matter with cooling mechanisms and/or nuclear interactions could form black holes with subsolar masses. Assuming a particular primordial black hole (PBH) formation model, we constrain a population of merging 0.2 𝑀 ⊙ black holes to account for less than 16% of the dark matter density and a population of merging 1.0 𝑀 ⊙ black holes to account for less than 2% of the dark matter density. We discuss how constraints on the merger rate and dark matter fraction may be extended to arbitrary black hole population models that predict subsolar mass binaries.

B. P. Abbott↗

DOE OSTI2024

Testing Gravity with Realistic Gravitational Waveforms in Pulsar Timing Arrays

We consider the effects of relaxing the assumption that gravitational waves composing the stochastic gravitational wave background (SGWB) are uncorrelated between frequencies in analyses of the data from Pulsar Timing Arrays (PTAs). While individual monochromatic plane waves are often a good approximation, a background composed of astrophysical sources cannot be monochromatic since an infinite plane wave carries no signal. We consider how relaxing this assumption allows us to extract potential information about modified dispersion relations and other fundamental physics questions, as both the group and phase velocity of waves become relevant. After developing the formalism we carry out simple Gaussian wavepacket examples and then consider more realistic waveforms, such as that from binary inspirals. When the frequency evolves only slowly across the PTA temporal baseline, the monochromatic assumption at an effective mean frequency remains a good approximation and we provide scaling relations that characterize its accuracy.

Hu, Wayne↗

DOE OSTI2026

Machine learning for seismic low-frequency extrapolation

The cycle-skipping problem that plagues full waveform inversion (FWI) can be at least partially mitigated if low frequencies (which encode the kinematics of wave propagation in seismic data) are recorded. However, seismic sources and receivers are band-limited, so seismic data does not generally include signals down to 0 Hz. To improve our ability to solve the seismic inverse problem, one can synthesize this missing low-frequency (LF) content from the recorded high-frequency (HF) data using machine learning (ML) models. Deep learning models such as convolutional neural networks (CNNs) demonstrate impressive ability to perform low frequency extrapolation. However, such models require powerful hardware (GPU machines) and careful training. We assess the extrapolation capabilities of three different ML models that do not require GPU machines, namely, random forest, Gaussian process regression and gradient boosting, on both synthetic and real data. Experimental results on two synthetic data sets (generated from a low velocity lens embedded in a homogeneous medium, and the Marmousi model) demonstrate that FWI applied to the extrapolated data consistently improves inversion accuracy relative to FWI applied to the original data sets that do not contain low frequencies. Application of low-frequency extrapolation to real data from the Northwest Shelf of Australia demonstrates that tree-based ML models such as gradient boosting can outperform CNNs in terms of both accuracy and computational cost on non-GPU architectures.

58 GEOSCIENCES↗